An empirical analysis of land property lawsuits and rainfalls

Recent Advancement of the Current Aspects of g-C3 N4 for its Photocatalytic Applications in Sustainable Energy System

Being one of the foremost enticing and intriguing innovations, heterogeneous photocatalysis has also been used to effectively gather, transform, and conserve sustainable sun's radiation for the production of efficient and clean fossil energy as well as a wide range of ecological implications. The generation of solar fuel-based water splitting and CO₂ photoreduction is excellent for generating alternative resources and reducing global warming. Developing an inexpensive photocatalyst can effectively split water into hydrogen (H₂ ), oxygen (O₂ ) sources, and carbon dioxide (CO₂ ) into fuel sources, which is a crucial problem in photocatalysis. The metal-free g-C₃ N₄ photocatalyst has a high solar fuel generation potential. This review covers the most recent advancements in g-C₃ N₄ preparation, including innovative design concepts and new synthesis methods, and novel ideas for expanding the light absorption of pure g-C₃ N₄ for photocatalytic application. Similarly, the main issue concerning research and prospects in photocatalysts based g-C₃ N₄ was also discussed. The current dissertation provides an overview of comprehensive understanding of the exploitation of the extraordinary systemic and characteristics, as well as the fabrication processes and uses of g-C₃ N₄ .

Comparative metabolomic analysis reveals shared and unique chemical interactions in sponge holobionts

BACKGROUND

Sponges are ancient sessile metazoans, which form with their associated microbial symbionts a complex functional unit called a holobiont. Sponges are a rich source of chemical diversity; however, there is limited knowledge of which holobiont members produce certain metabolites and how they may contribute to chemical interactions. To address this issue, we applied non-targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) and gas chromatography mass spectrometry (GC-MS) to either whole sponge tissue or fractionated microbial cells from six different, co-occurring sponge species.

RESULTS

Several metabolites were commonly found or enriched in whole sponge tissue, supporting the notion that sponge cells produce them. These include 2-methylbutyryl-carnitine, hexanoyl-carnitine and various carbohydrates, which may be potential food sources for microorganisms, as well as the antagonistic compounds hymenialdisine and eicosatrienoic acid methyl ester. Metabolites that were mostly observed or enriched in microbial cells include the antioxidant didodecyl 3,3'-thiodipropionate, the antagonistic compounds docosatetraenoic acid, and immune-suppressor phenylethylamide. This suggests that these compounds are mainly produced by the microbial members in the sponge holobiont, and are potentially either involved in inter-microbial competitions or in defenses against intruding organisms.

CONCLUSIONS

This study shows how different chemical functionality is compartmentalized between sponge hosts and their microbial symbionts and provides new insights into how chemical interactions underpin the function of sponge holobionts. Video abstract.

Controlling pore-scale processes to tame subsurface biomineralization

Microorganisms capable of biomineralization can catalyze mineral precipitation by modifying local physical and chemical conditions. In porous media, such as soil and rock, these microorganisms live and function in highly heterogeneous physical, chemical and ecological microenvironments, with strong local gradients created by both microbial activity and the pore-scale structure of the subsurface. Here, we focus on extracellular bacterial biomineralization, which is sensitive to external heterogeneity, and review the pore-scale processes controlling microbial biomineralization in natural and engineered porous media. We discuss how individual physical, chemical and ecological factors integrate to affect the spatial and temporal control of biomineralization, and how each of these factors contributes to a quantitative understanding of biomineralization in porous media. We find that an improved understanding of microbial behavior in heterogeneous microenvironments would promote understanding of natural systems and output in diverse technological applications, including improved representation and control of fluid mixing from pore to field scales. We suggest a range of directions by which future work can build from existing tools to advance each of these areas to improve understanding and predictability of biomineralization science and technology.

Signal processing techniques applied to impedance cardiography ICG signals - a review

Over the last decade, Computer-Aided Diagnosis (CAD) systems have been provided significant research focus by researchers. CAD systems have been developed in order to minimise visual errors, to compensate manual interpretation, and to help medical staff to take decisions swiftly. These systems have been considered as powerful tools for a reliable, automatic, and low-cost monitoring and diagnosis. CAD systems are based on analysis and classification of several physiological signals for detecting and assessing different diseases related to the corresponding organ. The implementation of these systems requires the application of several advanced signal processing techniques. Specifically, in cardiology, CAD systems have achieved promising results in providing an accurate and rapid detection of cardiovascular diseases (CVDs). Particularly, the number of works on signal processing field for impedance cardiography (ICG) signals starts to grow slowly in recent years. This paper presents a review study of signal processing techniques applied to the ICG signal for the denoising, the analysis, the classification and the characterisation purposes. This review is intended to provide researchers with a broad overview of the currently used signal processing techniques for ICG signal analysis, as well as to improve future research by applying other recent advanced methods.

Additional effect of azithromycin over β-lactam alone for severe community-acquired pneumonia-associated acute respiratory distress syndrome: a retrospective cohort study

Background

Community-acquired pneumonia (CAP) is the most common cause of acute respiratory distress syndrome (ARDS). Although previous studies have suggested that macrolide therapy is beneficial for ARDS, its benefit for severe CAP-associated ARDS remains uncertain. Previous studies were limited in that they had a small sample size and included patients with non-pulmonary ARDS and those with pulmonary ARDS. This study aimed to investigate the additional effect of azithromycin when used with β-lactam compared with the effect of β-lactam alone in mechanically ventilated patients with CAP-associated ARDS.

Methods

We identified mechanically ventilated patients with CAP-associated ARDS between July 2010 and March 2015 using data in the Diagnosis Procedure Combination database, a Japanese nationwide inpatient database. We performed propensity score matching analysis to assess 28-day mortality and in-hospital mortality in mechanically ventilated patients with CAP-associated ARDS who received β-lactam with and without azithromycin within hospital 2 days after admission. The inverse probability of treatment weighting analysis was also conducted.

Results

Eligible patients (n = 1257) were divided into the azithromycin group (n = 226) and the control group (n = 1031). The one-to-four propensity score matching analysis included 139 azithromycin users and 556 non-users. No significant difference was observed between the groups with respect to 28-day mortality (34.5% vs. 37.6%, p = 0.556) or in-hospital mortality (46.0% vs. 49.1%, p = 0.569). The inverse probability of treatment weighting analysis showed similar results.

Conclusions

Compared with treatment with β-lactam alone, treatment with azithromycin plus β-lactam had no significant additional effect on 28-day mortality or in-hospital mortality in mechanically ventilated patients with CAP-associated ARDS. To the best of our knowledge, this study is the first to determine the effect of azithromycin in mechanically ventilated patients with CAP-associated ARDS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41479-021-00093-8.

Evaluation of Human Wharton's Jelly-Derived Mesenchymal Stem Cells Conditioning Medium (hWJ-MSCs-CM) or Scorpion Venom Breast Cancer Cell Line In Vitro

PURPOSE

The present study aimed to evaluate the anticancer potential of Egyptian scorpion Leiurus quinquestriatus venom (ScV) or human Wharton's jelly-derived mesenchymal stem cells conditioning medium (hWJ-MSCs-CM)/CM against breast cancer (MCF-7) cell line as an alternative effective cancer biotherapy.

METHODS

Venom (ScV) toxicity was performed recording concentration-dependent viability % and ScV IC₅₀ value was in the order of 100 μg/ml. MCF-7 were treated with hWJ-MSCs-CM used as (25%, 50%, and 75% ml) or the IC₅₀ of ScV. Apoptotic activity was traced via evaluation the apoptotic (Bax, Casp-3, and Casp-9) and anti-apoptotic genes (Bcl2, ALDOA, and PKM2) profile.

RESULTS

Both Bax and Casp-3 showed a significant upregulation while anti-apoptotic genes were significantly downregulated. In the meantime, Casp-3 and Casp-9 protein were monitored using ELISA, and their level was less than in control. Additionally, MCF-7 apoptosis was monitored using flow cytometry recording a significant DNA accumulation in the G0-G1 and S phases in case of cell treatment with ScV or CM75% ml and 50% ml. Also, there was a significant total necrotic cells % compared with control cells, and total apoptosis under the effect of ScV or CM75% ml was significantly elevated than rest of treatment.

CONCLUSION

Apoptosis induction was both dose- and time-dependent for hWJ-MSCs-CM and ScV. According to the present study and other studies, there is an ample evidence that hWJ-MSCs-CM and the venom IC₅₀ abolish tumor growth.

Heavy metals contamination and associated health risks in food webs-a review focuses on food safety and environmental sustainability in Bangladesh

Heavy metals occur naturally in very small amounts in living organisms, but exposure to their higher concentrations is hazardous. Heavy metals at hazardous levels are commonly found in foodstuffs of Bangladesh, mainly due to the lack of safety guidelines and poor management of industrial effluents. Several lines of evidence suggest that the level of heavy metals in foodstuffs of Bangladesh is higher than the acceptable limits set by World Health Organization/Food and Agriculture Organization. Literature survey revealed that the sources and transport pathways of heavy metals in the ecosystem and the abundance of heavy metals in the food products of Bangladesh are potential threats to food safety. However, an extensive assessment of the toxicity of heavy metals in food webs is lacking. Although widespread heavy metal contamination in various foodstuffs and environmental matrices have been summarized in some reports, a critical evaluation regarding multi-trophic transfer and the health risk of heavy metal exposure through food chain toxicity in Bangladesh has not been performed. This systematic review critically discussed heavy metal contamination, exposure toxicity, research gaps, existing legislation, and sustainable remediation strategies to enhance Bangladesh's food safety. In particular, this study for the first time explored the potential multi-trophic transfer of heavy metals via food webs in Bangladesh. Furthermore, we recommended a conceptual policy framework to combat heavy metal contaminations in Bangladesh.

Approach to multi-attribute decision-making problems based on neutrality aggregation operators of T-spherical fuzzy information

In the process of decision-making, uncertain information is always challenging to deal with. T-spherical fuzzy set (TSFS) operates vagueness of data by analysing three independent functions, namely membership, non-membership, and abstinence function. The TSFS provides us robust scheme with parameter \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$q\ge 1$$\end{document} q ≥ 1 to handle the countless opportunities. Hence, this set proves its superiority over the existing picture fuzzy set (PFS) and spherical fuzzy set (SFS). Now a day, decision-makers usually assign impartial values throughout the assessment. This manuscript demonstrates some new operational laws by fusing the neutral characteristics of the degrees of membership and using the probability sum (PS) function. Meanwhile, we determine several aggregation operators (AOs) including weighted averaging neutral, ordered weighed neutral, and hybrid averaging neutral AOs to aggregate the data under T-spherical fuzzy (TSF) environment. As it came to the notice that weighted neutral averaging aggregation operators of the Pythagorean fuzzy set (PyFS), single-valued neutrosophic fuzzy set (SVNFS), and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$q$$\end{document} q -rung orthopair fuzzy set (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$q$$\end{document} q -ROFS) have some restrictions during the decision-making problems. So, to overcome this, we introduce a new multi-attribute group decision-making method (MAGDM) based on proposed AOs. Lastly, we provide various numerical instances to explain the method and exhibit its supremacy. Furthermore, a comparative analysis is conducted to compare the potential of proposed AOs with some other existing methods.

The impacts of performance-based assessment on reading comprehension achievement, academic motivation, foreign language anxiety, and students’ self-efficacy

The types of assessment tasks affect the learners’ psychological well-being and the process of learning. For years, educationalists were in search of finding and implementing accurate and convenient approaches to assess learners efficiently. Despite the significant role of performance-based assessment (PBA) in affecting second/foreign language (L2) learning processes, few empirical studies have tried to explore how PBA affects reading comprehension achievement (RCA), academic motivation (AM), foreign language anxiety (FLA), and students’ self-efficacy (SS-E). To fill this lacuna of research, the current study intended to gauge the impact of PBA on the improvement of RCA, AM, FLA, and SS-E in English as a foreign language (EFL) context. In so doing, a sample of 88 intermediate EFL learners were randomly divided into experimental group (EG) and CG (control group). During this research (16 sessions), the learners in the CG (N = 43) received the tradition assessment. In contrast, the learners in the EG (N = 45) were exposed to some modification based on the underpinning theories of PBA. Data inspection applying the one-way multivariate analysis of variance (i.e., the one-way MANOVA) indicated that the learners in the EG outperformed their counterparts in the CG. The results highlighted the significant contributions of PBA in fostering RCA, AM, FLA, and S-E beliefs. The implications of this study may redound to the benefits of language learners, teachers, curriculum designers, and policy makers in providing opportunities for further practice of PBA.

A modular microfluidic platform for serial enrichment and harvest of pure extracellular vesicles

A modular microfluidic platform is developed to enrich EVs on micron-sized carrier beads immobilized with EV-specific antibodies, based on affinity capture, and elute pure EVs from the carrier beads in a high throughput.

Niclosamide for Covid-19: bridging the gap

AIM/PURPOSE

Niclosamide (NCL) is an anthelminthic drug, which is widely used to treat various diseases due to its pleiotropic anti-inflammatory and antiviral activities. NCL modulates of uncoupling oxidative phosphorylation and different signaling pathways in human biological processes. The wide-spectrum antiviral effect of NCL makes it a possible candidate for recent pandemic SARS-CoV-2 infection and may reduce Covid-19 severity. Therefore, the aim of the present study was to review and clarify the potential role of NCL in Covid-19.

METHODS

This study reviewed and highlighted the protective role of NCL therapy in Covid-19. A related literature search in PubMed, Scopus, Web of Science, Google Scholar, and Science Direct was done.

RESULTS

NCL has noteworthy anti-inflammatory and antiviral effects. The primary antiviral mechanism of NCL is through neutralization of endosomal PH and inhibition of viral protein maturation. NCL acts as a proton carrier, inhibits homeostasis of endosomal PH, which limiting of viral proliferation and release. The anti-inflammatory effects of NCL are mediated by suppression of inflammatory signaling pathways and release of pro-inflammatory cytokines. However, the major limitation in using NCL is low aqueous solubility, which reduces oral bioavailability and therapeutic serum concentration that reducing the in vivo effect of NCL against SARS-CoV-2.

CONCLUSIONS

NCL has anti-inflammatory and immune regulatory effects by modulating the release of pro-inflammatory cytokines, inhibition of NF-κB /NLRP3 inflammasome and mTOR signaling pathway. NCL has an anti-SARS-CoV-2 effect via interruption of viral life-cycle and/or induction of cytopathic effect. Prospective clinical studies and clinical trials are mandatory to confirm the potential role of NCL in patients with Covid-19 concerning the severity and clinical outcomes.

Gesture Classification of Surface Electromyography Signals Using Machine Learning Algorithms for Hand Prosthetics

The actions of humans executed by their hands play a remarkable part in controlling and handling variety of objects in their daily life activities. The effect of losing or degradation in the functioning of one hand has a greater influence in bringing down the regular activity. Hence the design of prosthetic hands which assists the individuals to enhance their regular activity seems a better remedy in this new era. This paper puts forward a classification framework using machine learning algorithms for classifying hand gesture signals. The surface electromyography (sEMG) dataset acquired for 9 wrist movements of publicly available database are utilized to identify the potential biomarkers for classification and in evaluating the efficacy of the proposed algorithm. The statistical and time domain features of the sEMG signals from 27 intact subjects and 11 trans-radial amputated subjects are extracted and the optimal features are determined implementing the feature selection approach based on correlation factor. The classifiers performance of machine learning algorithms namely support vector machine (SVM), Naïve bayes (NB) and Ensemble classifier are evaluated. The experimental results highlight that the SVM classifier can yield the maximum accuracy movement classification of 99.6% for intact and 97.56% for trans-amputee subjects. The proposed approach offers better accuracy and sensitivity compared to other approaches that have used the sEMG dataset for movement classification.

Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak

This study aims to conduct text mining of affective valence of the sentiments generated on social media during the COVID-19 and measure their association with different outcomes of the disease. 50,000 tweets per day over 23 days during the pandemic were extracted using the VADER sentiment analysis tool. Overall, tweets could effectively be classified in terms of polarity, i.e., “positive,” “negative” and “neutral” sentiments. Furthermore, on a day-to-day basis, the study identified a positive and significant relationship between COVID-19-related (a) global infections and negative tweets, (b) global deaths and negative tweets, (c) recoveries and negative tweets, and (d) recoveries and positive tweets. No significant association could be found between (e) infections and positive tweets and (f) deaths and positive tweets. Furthermore, the statistical analysis also indicated that the daily distribution of tweets based on polarity generates three distinct and significantly different numbers of tweets per category, i.e., positive, negative and neutral. As per the results generated through sentiment analysis of tweets in this study, the emergence of “positive” tweets in such a gloomy pandemic scenario shows the inherent resilience of humans. The significant association between news of COVID-19 recoveries and positive tweets seems to hint at a more optimistic scenario whenever the pandemic finally comes to an end or is controlled. Such public reactions—for good—have the potential to go viral and influence several others, especially those who are classified as “neutral” or fence-sitters.

The structure of the cereal leaf beetle (Oulema melanopus) microbiome depends on the insect's developmental stage, host plant, and origin

Cereal leaf beetle (CLB, Oulema melanopus, Coleoptera, Chrysomelidae) is a serious agricultural pest that causes considerable damages to agricultural production. The aim of this study was to characterize the bacterial communities associated with larvae and imagoes of CLB collected from various cereal host species and locations. The bacterial profile was characterized by 16S rRNA gene sequencing at the V3-V4 hypervariable region. Using taxonomy-based analysis, the bacterial community of CLB containing 16 phyla, 26 classes, 49 orders, 78 families, 94 genera, and 63 species of bacteria was identified. The abundance of Wolbachia, Rickettsia, and Lactococcus genus was significantly higher in CLB imagoes than in larvae. Statistical analysis confirmed that the bacterial community of the larvae is more diverse in comparison to imagoes and that insects collected from spring barley and wheat are characterized by a much higher biodiversity level of bacterial genera and species than insects collected from other cereals. Obtained results indicated that the developmental stage, the host plant, and the insect's sampling location affected the CLB's microbiome. Additionally, the CLB core microbiome was determined. It consists of 2 genera (Wolbachia and Rickettsia) shared by at least 90% tested CLB insects, regardless of the variables analysed.

Cryotherapy and compression in sports injury management: a scoping review

Background/Aims

For the management of sports injury, cryotherapy is commonly applied, yet modalities differ extensively in application including levels of compression. The aim of this study was to provide a comprehensive review of the current position in the literature on contemporary cryo-compression applications for musculoskeletal sports injury management.

Methods

A total of eight databases were searched: Sport Discus, Science Direct, CINHAL, Scopus, PubMed, Cochrane, ProQuest and MEDLINE. Publications were restricted to 30 years and had to be in the English language. Medical subject headings, free-text words, and limiting descriptors for concepts related to cryotherapy and compression for sports injury were applied. Inclusion criteria determined at least one modality of cryotherapy treatment applied simultaneous to compression or as a comparison, relevant to sports injury management. Modalities included cryo-compressive devices and gel/ice packs, in association with concomitant compression. Male, female, healthy and injured participants were included. Two reviewers independently selected eligible articles, resulting in 22 studies meeting the inclusion criteria following full-text appraisal.

Results

Inconsistent methodologies, low sample sizes and variability in outcome measures provided uncertainty over optimum protocols. A lack of previous understanding in the protocols in the available literature for isolated cryotherapy/compression applications prevents understanding of the therapeutic benefits of combined cryo-compression. No definitive agreement behind optimal cryo-compression applications were identified collectively from studies other than the consensus that compression aids the magnitude of cooling.

Conclusions

Although compression appears a useful adjunct to cooling modalities for the management of sports injury, no definitive agreement on optimum compression concurrent with cooling protocols were drawn from the studies. This was because of several methodological gaps in reporting throughout studies, highlighting a lack of studies that represent applications of compression and cryotherapy within a sporting context or applied nature within the available research.

Masked face recognition with convolutional neural networks and local binary patterns

Face recognition is one of the most common biometric authentication methods as its feasibility while convenient use. Recently, the COVID-19 pandemic is dramatically spreading throughout the world, which seriously leads to negative impacts on people’s health and economy. Wearing masks in public settings is an effective way to prevent viruses from spreading. However, masked face recognition is a highly challenging task due to the lack of facial feature information. In this paper, we propose a method that takes advantage of the combination of deep learning and Local Binary Pattern (LBP) features to recognize the masked face by utilizing RetinaFace, a joint extra-supervised and self-supervised multi-task learning face detector that can deal with various scales of faces, as a fast yet effective encoder. In addition, we extract local binary pattern features from masked face’s eye, forehead and eyebow areas and combine them with features learnt from RetinaFace into a unified framework for recognizing masked faces. In addition, we collected a dataset named COMASK20 from 300 subjects at our institution. In the experiment, we compared our proposed system with several state of the art face recognition methods on the published Essex dataset and our self-collected dataset COMASK20. With the recognition results of 87% f1-score on the COMASK20 dataset and 98% f1-score on the Essex dataset, these demonstrated that our proposed system outperforms Dlib and InsightFace, which has shown the effectiveness and suitability of the proposed method. The COMASK20 dataset is available on https://github.com/tuminguyen/COMASK20 for research purposes.

Galerkin finite element analysis of magneto two-phase nanofluid flowing in double wavy enclosure comprehending an adiabatic rotating cylinder

In this work, the finite element method is employed to simulate heat transfer and irreversibilities in a mixed convection two-phase flow through a wavy enclosure filled with water-alumina nanoliquid and contains a rotating solid cylinder in the presence of a uniform magnetic field. Impact of the variations of undulations number (0 ≤ N ≤ 5), Ra (103 ≤ Ra ≤ 106), Ha (0 ≤ Ha ≤ 100), and angular rotational velocity (- 500 ≤ Ω ≤ 500) were presented. Isotherms distribution, streamlines and isentropic lines are displayed. The governing equations are verified by using the Galerkin Finite Element Method (GFEM). The Nusselt numbers are calculated and displayed graphically for several parametric studies. The computational calculations were carried out using Buongiorno's non-homogeneous model. To illustrate the studied problem, a thorough discussion of the findings was conducted. The results show the enhacement of the maximum value of the flow function and the heat transfer process by increasing the value of Rayleigh number. Furthermore the irreversibility is primarily governed by the heat transfer component and the increment of the waviness of the active surfaces or the cylinder rotational velocity or hartmann number will suppress the fluid motion and hinders the heat transfer process.

Multi-GPU approach to global induction of classification trees for large-scale data mining

This paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers. It searches for the tree structure and tests simultaneously and thus gives improvements in the prediction and size of resulting classifiers in many situations. However, it is the population-based and iterative approach that can be too computationally demanding to apply for big data mining directly. The paper demonstrates that this barrier can be overcome by smart distributed/parallel processing. Moreover, we ask the question whether the global approach can truly compete with the greedy systems for large-scale data. For this purpose, we propose a novel multi-GPU approach. It incorporates the knowledge of global DT induction and evolutionary algorithm parallelization together with efficient utilization of memory and computing GPU’s resources. The searches for the tree structure and tests are performed simultaneously on a CPU, while the fitness calculations are delegated to GPUs. Data-parallel decomposition strategy and CUDA framework are applied. Experimental validation is performed on both artificial and real-life datasets. In both cases, the obtained acceleration is very satisfactory. The solution is able to process even billions of instances in a few hours on a single workstation equipped with 4 GPUs. The impact of data characteristics (size and dimension) on convergence and speedup of the evolutionary search is also shown. When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.

On periodic solutions of a discrete Nicholson's dual system with density-dependent mortality and harvesting terms

In this study, we discuss the existence of positive periodic solutions of a class of discrete density-dependent mortal Nicholson's dual system with harvesting terms. By means of the continuation coincidence degree theorem, a set of sufficient conditions, which ensure that there exists at least one positive periodic solution, are established. A numerical example with graphical simulation of the model is provided to examine the validity of the main results.

Metabolic landscapes in sarcomas

Metabolic rewiring offers novel therapeutic opportunities in cancer. Until recently, there was scant information regarding soft tissue sarcomas, due to their heterogeneous tissue origin, histological definition and underlying genetic history. Novel large-scale genomic and metabolomics approaches are now helping stratify their physiopathology. In this review, we show how various genetic alterations skew activation pathways and orient metabolic rewiring in sarcomas. We provide an update on the contribution of newly described mechanisms of metabolic regulation. We underscore mechanisms that are relevant to sarcomagenesis or shared with other cancers. We then discuss how diverse metabolic landscapes condition the tumor microenvironment, anti-sarcoma immune responses and prognosis. Finally, we review current attempts to control sarcoma growth using metabolite-targeting drugs.

Effects of antiepileptic drugs on ovaries of female Wistar rats

Valproate (VPA) induced changes in ovarian morphology are observed in humans with epilepsy and in non-epileptic animals. The effects of lamotrigine (LTG) on female reproduction is not well known. We investigated whether LTG might be a safer drug for use with patients of reproductive age. Forty Wistar albino female rats were divided into five groups. The control group was injected with saline-vehicle solution. The low dose (LD)-VPA group was injected with 100 mg/kg VPA. The high dose (HD)-VPA group was injected with 500 mg/kg VPA. The LD-LTG group was injected with 10 mg/kg LTG. The HD-LTG group was injected with 50 mg/kg LTG. We evaluated histological and biochemical changes in the ovaries. The number of atretic and cystic follicles was increased in the HD-VPA and HD-LTG groups compared to the control group. A significant increase in malondialdehyde level was found in the VPA groups compared to the control and LTG groups. No significant differences in total glutathione levels or superoxide dismutase activity were found among study groups. Catalase activity was significantly higher in HD-VPA and HD-LTG groups compared to the control, LD-VPA and LD-LTG groups. Prevalence and intensity of caspase-3 immunoreactivity in the luteal cells were significantly greater in the HD-LTG group compared to the control group. VPA administration caused polycystic ovarian syndrome-like changes in the ovary. We found that LD-LTG, which reflects the dose for humans, might be a safer option for use during the reproductive age.

New normal baseline data during nationwide lock down due to Covid 19 pandemic in the world's largest ship recycling yard at Alang, India

A detailed study to generate the new normal baseline data has been carried out during nationwide lockdown (May 12 to May 16, 2020) covering sampling for ambient air, coastal water, coastal sediments, fish and bioaccumulation of heavy metals, in an around Alang, the world's biggest ship recycling yard. The lockdown data were compared with 2018 and 2019 observed data. PM10 values during lockdown were reduced by 3.75 to 4.5 times as compared with previous 2 years. Similarly, four-fold reduction of PM2.5 and SPM values was observed during lockdown. The gaseous pollutants like NO2 and O3 are within safe limit. Overall air quality index (AQI) improved significantly during lockdown. Similarly, there was drastic reduction in the majority of the nutrient parameters in the coastal water. Different heavy metal concentration in the coastal sediments samples also showed strong reduction during lockdown sampling in comparison with other two sampling. This proves that the coastal environment has its efficient self-cleaning potentials if there is considerable reduction in the anthropogenic as well as industrial activities. Diversity of phytoplankton and zooplankton also increased. The results were validated using statistical techniques like analysis of variance and least significance difference (LSD).

The Association of Morning Surge and Night-Time Dipping Blood Pressure with Significant and Complex Coronary Artery Lesions

INTRODUCTION

Hypertension responsible for more than 10 million deaths annually worldwide and abnormal diurnal blood pressure (BP) variation is associated with cardiovascular events.

AIM

This study aimed to investigate the association between the 24-h ambulatory night BP dipping and morning BP surge (MS) with characteristic of coronary artery lesions that may contribute cardiovascular events and mortality burden.

METHODS

A cross sectional study over 1-year, collected 263 cases of hypertensive (80%) and non-hypertensive patients, aged 61 ± 10 years, who undergoing invasive coronary angiography (CAG) and 24-h ambulatory BP monitoring admitted to cardiology department complain of chest pain. The night-time/day-time dip and sleep-trough MS were calculated. Non-dipper status was considered when night-time/day-time dip < 10%, and significant coronary lesion (SCL) when ≥ 50 % stenosis in 1.5 mm vessels. The SYNTAX (Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery) score was used to quantify the complexity of SCL.

RESULT

The mean morning systolic BP (SBP) surge was higher in the high SYNTAX Score subgroup than low and intermediate subgroups (25 ± 11 vs 17 ± 13 and 10 ± 10 mmHg, p < 0.010). Non-dipper SBP status was more frequently in patients with SCL than non-SCL (p < 0.019). In ordinal regression, hypertension was independent predictor of SCL (odd ratio: 0.40, p < 0.003), the night-time/day-time BP dip was independent predictor of being in a higher SYNTAX score subgroup (systolic odd ratio: 0.88, diastolic odd ratio: 1.14 p < 0.05).

CONCLUSION

Hypertension is associated with SCL and the night-time/day-time BP dip as a continuous variable is associated with complex coronary lesion. Non-dipping as categorical variable and morning BP surge were not independent predictors of significant or complex coronary lesions.

The Odd Weibull Inverse Topp-Leone Distribution with Applications to COVID-19 Data

This paper aims at defining an optimal statistical model for the COVID-19 distribution in the United Kingdom, and Canada. A combining the inverted Topp-Leone distribution and the odd Weibull family introduces a new lifetime distribution with a three-parameter to formulate the odd Weibull inverted Topp-Leone (OWITL) distribution. As a simple linear representation, hazard rate function, and moment function, this new distribution has several nice properties. To estimate the unknown parameters of OWITL distribution, maximum likelihood, least-square, weighted least-squares, maximum product spacing, Cramér-von Mises estimators, and Anderson-Darling estimation methods are used. To evaluate the use of estimation techniques, a numerical outcome of the Monte Carlo simulation is obtained.

Affinity of Mycobacterium tuberculosis strains for M059K microglial cells after migration through A549 alveolar epithelium

Tuberculosis (TB) remains a major threat worldwide while central nervous system TB (CNS-TB) is one of the most severe forms of extrapulmonary TB. CNS-TB develops as a secondary infection during the hematogenous spread of Mycobacterium tuberculosis (M. tuberculosis) from the lungs to the CNS. Factors influencing the dissemination of the bacilli to the CNS have not been studied extensively. This study evaluated the transmigration ability through the alveolar epithelium and adhesion and invasion capacity of glial cells of M. tuberculosis strains of varying drug susceptibility and genotype profiles using an in vitro co-culture model. A549 alveolar epithelial cells and M059K glial cells were co-cultured in a Transwell plate with A549 cells cultured in the upper chamber and M059K glial cells in the lower chamber. A549 epithelial cells were infected with F15/LAM4/KZN (susceptible, MDR, XDR), Beijing (susceptible, XDR), F11 (susceptible), F28 (MDR), and H37Rv strains of M. tuberculosis. The transmigration of an A549 monolayer and subsequent adhesion and invasion rates of M059K cells were established. The susceptible and XDR variants of the F15/LAM4/KZN strain transmigrate the alveolar epithelial cell monolayer more efficiently than the MDR variant. The Beijing-XDR variant showed a high transmigration rate, while the susceptible variant showed no transmigration ability. Similar to the MDR F15/LAM4/KZN, the F28 and F11 strains showed a low dissemination ability. The bacteria were still capable to adhere to M059K glial cells after passage through the A549 cells. We conclude that M. tuberculosis isolates that passed through a monolayer of A549 alveolar epithelium by transcellular migration can still adhere to M059K glial cells. There is no genetic link between resistance and transmigration.

MICP as a potential sustainable technique to treat or entrap contaminants in the natural environment: A review

In the last two decades, developments in the area of biomineralization has yielded promising results making it a potentially environmentally friendly technique for a wide range of applications in engineering and wastewater/heavy metal remediation. Microbially Induced Carbonate Precipitation (MICP) has led to numerous patented applications ranging from novel strains and nutrient sources for the precipitation of biominerals. Studies are being constantly published to optimize the process to become a promising, cost effective, ecofriendly approach when compared with the existing traditional remediation technologies which are implemented to solve multiple contamination/pollution issues. Heavy metal pollution still poses a major threat towards compromising the ecosystem. The removal of heavy metals is of high importance due to their recalcitrance and persistence in the environment. In that perspective, this paper reviews the current and most significant discoveries and applications of MICP towards the conversion of heavy metals into heavy metal carbonates and removal of calcium from contaminated media such as polluted water. It is evident from the literature survey that although heavy metal carbonate research is very effective in removal, is still in its early stages but could serve as a solution if the microorganisms are stimulated directly in the heavy metal environment.

In situ phytoremediation of heavy metal-contaminated soil and groundwater: a green inventive approach

The heavy metal contamination of soil and groundwater is a serious threat to environment worldwide. The survival of human being primarily relies upon soil and groundwater sources. Therefore, the remediation of heavy metal-contaminated soil and groundwater is a matter of utmost concern. Heavy metals are non-degradable and persist in the environment and subsequently contaminate the food chain. Heavy metal pollution puts a serious impact on human health and it adversely affects our physical body. Although, numerous in situ conventional technologies have been utilized for the treatment purpose, but most of the techniques have some limitations such as high cost, deterioration of soil properties, disturbances to soil native flora and fauna and intensive labour. Despite that, in situ phytoremediation is a cost-effective, eco-friendly, solar-driven and novel approach with significant public acceptance. The past research reflects rare discussion addressing both (heavy metal in situ phytoremediation of soil and groundwater) in one platform. The present review article covers both the concepts of in situ phytoremediation of soil and groundwater with major emphasis on health risks of heavy metals, enhanced integrated approaches of in situ phytoremediation, mechanisms of in situ phytoremediation along with effective hyperaccumulator plants for heavy metals remediation, challenges and future prospects.

Breeding potential of lablab [Lablab purpureus (L.) Sweet]: a review on characterization and bruchid studies towards improved production and utilization in Africa

Lablab (Lablab purpureus) [Lablab purpureus (L.) Sweet] is termed a lost, underutilized and neglected crop in Africa. Despite the multipurpose use, production, consumption and research are still limited. Wide genetic diversity of lablab germplasm exists in Africa. Diversity studies provide significant information for subsequent research programs and improvement. The advent of genotyping and sequencing technologies has enabled the identification of unique and agronomically important traits. Application of next-generation sequencing on lablab as a pioneer orphan crop is currently underway. This has enabled description of the whole genome, generation of reference genome and resequencing that provide information on variation within the entire genome. Information from these technological advances helps in identifying potential traits for biotic and abiotic stress for further breeding programs. Storage pests specifically bruchids (Callosobruchus spp.), are considered a major obstacle in lablab production. Screening of available genotypes for bruchid resistance and studies on the physical and biochemical factors that confer resistance in lablab is required. Applying advanced technologies provides precise and reliable identification of the novel markers responsible for bruchid resistance allowing for introgression of important genes to breeding programs. This review provides a detailed analysis on the characterization of lablab and the information on bruchid resistance vital for breeding farmer-preferred varieties that possess agronomically beneficial traits. Concerted efforts and research on this neglected crop will enhance its production, utilization and consumption.

Evolutionary Computation with User’s Preference for Solving Fuzzy Fitness Forecasting Problems

Interactive Evolutionary Computation (IEC) is a kind of human–machine interaction calculation method derived from evolutionary computation. The main problem of interactive evolutionary computation is that fitness noise can make evolution direction to deviate from user’s preferences because user’s evaluation has cognitive fluctuations and fatigue. To improve these deficiencies, this paper recommends a fuzzy fitness prediction method based on fuzzy gray model FGM (1,1) with a precise number fitness. First of all, the relationship between fitness noise intensity and the fitness function is proposed. Then, it suggests a linear programming of fuzzy fitness set width under the restriction of minimum noise intensity, which can calculate the fuzzy fitness prediction parameters. Finally, the fuzzy gray model forecasts the fuzzy fitness. The proposed method uses new computation of individual’s dominance relation and crowding distance to realize NSGA–II. The experimental results verify that this method has advantages in improving optimization quality, alleviating user’s fatigue and improving efficiency in exploration.

Mining urban sustainable performance: Spatio-temporal emission potential changes of urban transit buses in post-COVID-19 future

Emission benefits of transit buses depend on ridership. Declines in ridership caused by COVID-19 leads uncertainty about the emission reduction capacity of buses. This paper provides a method framework for analyzing spatio-temporal emission patterns of buses in combination with real-time ridership and potential emission changes in the post-COVID-19 future. Based on GPS trajectory and Smart Card data of 2056 buses from 278 routes covering 1.5 million ridership in Qingdao, China, spatio-temporal emissions characteristics of buses are studied. 7589 taxis with 0.2 million passengers' trips are used for acquiring private cars' emissions to evaluate the emissions difference between buses and cars. Empirical results show that the average difference between buses and cars with 2 persons can reach up to 117 g/km-person during 7:00-8:59 and 115 g/km-person during 17:00-18:59. However, buses have various emission benefits around the city at different periods. A double increase in emissions during non-rush hours can be observed compared with rush hours. 224 online survey data are used to study the potential ridership reduction trend in post-COVID-19. Results show that 56.3% of respondents would decrease the usage of buses in the post-COVID-19 future. Based on this figure, our analysis shows that per kilometer-person emissions of buses are higher than cars during non-rush hours, however, still lower than cars during rush hours. We conclude that when ridership reduces by more than 40%, buses cannot be "greener" travel modal than cars as before. Finally, several feasible policies are suggested for this potential challenge. Our study provides convincing evidence for understanding the emission patterns of buses, to support better buses investment decisions and promotion on eco-friendly public transport service in the post-COVID-19 future.

A multi-fault diagnosis method of gear-box running on edge equipment

Edge computing equipment is a new tool that has been widely used to monitor the operation state of industrial equipment and to diagnose and analyze faults. Therefore, the fault diagnosis algorithm used in the edge computing device plays an especially significant role in fault diagnosis. The application of deep learning method in mechanical fault diagnosis has been gradually popularized, because it has many advantages, such as strong classification ability and accurate feature extraction ability. However, many of the completed papers and models are based on single label system and are used to diagnose single target fault. The validation set is not rigorous enough, and it is difficult to accurately simulate the faults that may occur in the actual production process. Nowadays, in the era of big data, the single label system ignores the joint relationship of different fault types, and it is difficult to make a correct judgment for the location, type and degree of mechanical failure. Hence, in the process of experiment, we used the bearing data of Case Western Reserve University(CWRU) to ensure the wide range and large quantity of data sets. A fault diagnosis method of gear and bearing in the gear-box based on multi-task deep learning model is put forward. In this method, gear and bearing faults can be diagnosed simultaneously. Through a separate task layer, this method can adaptively extract the characteristics of distinct targets from the same signal, and add a Batch Normalization layer(BN) to accelerate the convergence speed of the network. Through experiments, we conclude that it is an effective method which can judge the fault situation of gear and bearing accurately in a variety of working conditions.

A survey of chronic pain in China

There is an extensive body of research about chronic pain and treatment in developed countries. In contrast there is a lack of research on this topic in developing countries including China. This study was aimed to estimate the prevalence of chronic pain in different regions of China. Data on pain and its treatment were collected from 9357 participants using questionnaires and telephone-based interviews, from 31 regions of China. Gathered data were then coded into electronic data acquisition system and descriptive and inferential statistical analysis was performed. Out of 9298 participants, the ratio of chronic pain was 31.54% with the proportion of male having chronic pain (33.86%) was higher than that of female (29.53%). The average age of participants with pain (45.02 ± 15.07 years) was higher than free-pain participants (36.19 ± 11.12 years). There were also significant differences between groups in occupation, education levels, and illness history. Proportion of patients with pain duration of 1 year was 12.104%, between 1 and 5 years was 60%, and over 10 years was 10.74%. There were 63.9% of patients with moderate pain and 36.1% with severe pain. About 43.042% of patients thought that pain resulted in sleep disorder, 38.99% thought that it causes anxiety, and about 33% thought depression and irritable bowel was the result of their pain. For the chronic pain, more than half of patients used naprapathy, cupping, and other physical therapies. Up to 2016, the ratio of pain incidence was over 30% in China. The location of pain was focused on back and upper limb. There has been a lack of proper treatment. Patients with pain had obvious economic burden, and their quality of life and psychology were significantly affected.

Dopant site in indium-doped SrTiO3 photocatalysts

Strontium titanate, SrTiO3, with the perovskite ABO3 structure is known as one of the most efficient photocatalyst materials for the overall water splitting reaction. Doping with appropriate metal cations at the A site or at the B site substantially increases the quantum yield to split water into H2 and O2. The site occupied by the guest dopant in the SrTiO3 host thus plays a key role in dictating the water splitting activity. However, little is known about the detailed structure of the dopant site in the host lattice. In this study, the local structure of In3+ cations, which were shown to improve the water splitting activity of SrTiO3, is investigated with X-ray absorption fine structure spectroscopy and density functional theory (DFT) calculations. The In3+ cations exclusively substitute for Ti4+ cations at the B site to form InO6 octahedra. Further optical experiments using UV-Vis diffuse reflectance spectroscopy and DFT calculations of the density of states indicate that the substitution of In3+ for Ti4+ does not alter the band structure and bandgap energy (remaining at 3.2 eV). The mechanism underlying the increased water splitting activity is discussed in relation to occupation of the B site by In3+ cations.

Viscous Dissipation and Joule Heating Effects on MHD Bioconvection Flow of a Nanofluid Containing Gyrotactic Microorganisms Over a Vertical Isothermal Cone

The main objective of the present study is to explore the flow of a nanofluid containing gyrotactic microorganisms over a vertical isothermal cone surface in the presence of viscous dissipation and Joule heating. The combined effects of a transverse magnetic field and Navier slip in the flow are considered. Using appropriate transforms the set of partial differential equations governing the flow are converted to a set of ordinary differential equations. Influence of the parameters governing the flow is shown for velocity, temperature, concentration and motilemicroorganisms as well as local skin Friction coefficient, local Nusselt number, local Sherwood number and local density of the motile microorganisms number. An increasing in the value of Eckert number rises the velocity of the fluid and reduce the temperature, concentration and density of motile microorganisms profiles, while buoyancy ratio Nr and magnetic field parameters increase local skin friction coefficient, local Nusselt number, local Sherwood number and local density of the motile microorganisms number decrease as a result of the presence of Lorentz force which resist the motion of the flow. On the other hand, the motile microorganisms boundary layer thickness decreases with an increasing on the bioconvection Lewis number.