Evaluation of perceptual interactions between key aldehydes in Kung Pao Chicken

Aldehydes are the strongest and most abundant aromatic compounds in Kung Pao Chicken. However, the perceptual interactions between these aldehydes are not fully understood. Therefore, the flavor contribution of nine key aldehydes was estimated by determining thresholds. Except for benzaldehyde, the thresholds of all aldehydes measured in tasteless chicken matrices (TM) were significantly larger than their comparable values in water. Based on these results, the perceptual interactions of nine aldehydes were evaluated using S-curves and σ-τ plots. The interactions indicated that 31 of their 36 binary mixtures exhibited additive effects, three had masking effects, while two had synergistic effects. Recombination experiments showed that the addition of aldehydes lowered the odor threshold of aldehyde reconstitution (AR), thereby enhancing the aroma intensity of AR. These findings contribute to a better understanding of Kung Pao Chicken's aroma and can be used to improve its aroma quality.

An integrated DEMATEL and system dynamic model for project cost prediction

Actual cost fluctuations in construction projects are common in the construction industry, including the Kingdom of Saudi Arabia (KSA). This study's objective is to establish a simulation forecasting model for Saudi projects' cost changes that will be used to anticipate the actual cost spent at the project's end. It also indicates if there are cost overruns or savings by considering ten identified cost-risk impact factors. The study involves a systematic, integrated approach to developing system dynamics (SD) to reflect the ten cost overrun impact factors (COICs) in the KSA construction industry. Thus, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique aids in evolving a Causal Loop Diagram (CLD) in the SD modeling stages. After performing the consistency and extreme tests, the model is verified by being applied in two case studies (an academic building and an infrastructure project) in Riyadh City, KSA. The main findings reveal that the model provided cost savings for the first and second case studies of 4.8% and 3.76%, respectively. Different experts have evaluated the developed dynamic system. According to the experts who support the developed model, the model is applicable if the contractor has a reasonable profit margin. In contrast, opponents' experts noted that the system still generates a profit margin despite change orders and project delays. The main conclusion that the experts recognize is that the approach successfully considered the relationships between the influencing factors. The findings can be utilized to create an integrated conceptual framework for construction management, which could result in a rapid and profitable project launch.

Investigation of Lactone Chiral Enantiomers and Their Contribution to the Aroma of Longjing Tea by Odor Activity Value and S-Curve

Odor activity value (OAV) and S-curve were used to study the content, proportion, and contribution of lactone chiral enantiomers in Longjing tea. A total of 10 enantiomers were identified in this study, among which (S)-(-)-δ-decalactone (45.4-84.4 μg/L), (S)-(-)-γ-decalactone (31.5-109 μg/L), (S)-(-)-γ-nonanolactone (23.4-72.8 μg/L), and (S)-(-)-γ-undecalactone (21.1-56.2 μg/L) presented the highest concentrations. Furthermore, (R)-(+)-γ-nonanolactone (OAV: 2-7), (S)-(-)-γ-nonanolactone (OAV: 1-5), (S)-(-)-δ-decalactone (OAV: 2-4), (R)-(+)-δ-decalactone (OAV: 1-3), and (R)-(+)-γ-undecalactone (OAV: 1-5) were determined as enantiomeric compounds that play an important role in the perceived aroma of Longjing tea. Compared with the aromatic reconstitution (AR), the threshold increased to different degrees after adding γ-nonanolactone, γ-decalactone, δ-decalactone, γ-undecalactone, and their chiral enantiomers. This finding indicated that these compounds exert significant effects on the overall aroma of the AR. The contribution of racemates and chiral enantiomers to the AR threshold and aroma is completely different. In view of the difference between racemic and enantiomers' aroma characteristics in Longjing tea, the analysis and identification of chiral enantiomers are necessary to enrich and improve the accurate analysis of the flavor profile of Longjing tea.

A bibliometric analysis of research progress in sulfate-rich wastewater pollution control technology

Sustainable industrial development requires research on pollution control in industrial wastewater, particularly sulfate-rich wastewater, which poses a threat to the environment. This article differs from the previous sulfate wastewater treatment process and equipment review. Based on the quantitative analysis, this paper has determined some characteristics of the related literature on the pollution control technology of high-concentration sulfate wastewater to help researchers establish future research directions. From 1991-2020, the WoS database published 9473 articles related to high-concentration sulfate wastewater treatment technology. We used bibliometric analysis combined with social network analysis and s-curve technical analysis in this research. The United States was the first to start this type of research, Australia has insightful and instructive research articles in this area, and China is the most active in international cooperation. The keywords that appear most frequently in the dataset are degradation, adsorption, oxidation, reduction, and recovery. By S-curve fitting, it is known that biological treatment methods are closer to the maturity stage than physical and chemical treatment methods.

Association Between Serum Calcium and the Prevalence of Hypertension Among US Adults

Background: Hypertension is a significant risk factor of cardiovascular diseases, posing a serious threat to global health. Calcium plays an important role in regulating body homeostasis. The association of calcium with hypertension remains uncertain in the general population.

Methods and Results: Cross-sectional data from the 2007–2018 National Health and Nutrition Examination Survey (NHANES) were analyzed. Adjusted multivariable logistic regression analysis and restricted cubic spline were used to investigate the association of serum calcium with the prevalence of hypertension. A total of 26,778 participants were included. The increase in calcium levels showed a positive association with the prevalence of hypertension in all three models with ORs of 1.347 (1.249–1.454), 1.522 (1.401–1.654), and 1.438 (1.306–1.583). The further subgroup analysis demonstrated a robust trend across all categories by sex, age, race, BMI, and eGFR. The restricted cubic spline plot exhibited an S-curve relationship between calcium and hypertension.

Conclusion: Our cross-sectional study demonstrated a positive association between higher serum calcium level and the prevalence of hypertension. Our findings highlighted serum calcium level in hypertensive patients.

Bibliometric analysis of phosphogypsum research from 1990 to 2020 based on literatures and patents

The demand together with the urgency of phosphogypsum (PG) treatment will pose significant challenges for many countries. This research aims to explore the research progress of PG, including basic status, cooperation situation, research fields, and development trends, based on the Web of Science database through bibliometric analysis of publications (articles and patents) from 1990 to 2020. The results show that academic research on PG originated early, but the number of patents grew quickly. China is a global leader in terms of the number of publications and plays a significant role in international cooperation. The knowledge of PG has remained concentrated in the fields of natural radioactivity, cement paste backfilling, soil, crystal morphology, and synthetic gas. However, academic hotspots focus on the microstructure of chemical processes and various environmental impacts; patents and hot technologies are based on the production of refractory materials, ceramics, surface materials, cement mortar, and composite materials. The academic frontiers of PG will be centered on exploiting the methods of recovering rare earth elements from PG, the conditions of ion solidification/stabilization in PG, the impact of reaction conditions on product quality, and the reaction mechanism at the micro-level. The frontiers of patents need to focus on the improvement of manufacturing equipment, new wall materials, and chemically modified polymer materials. Envisaging the number of articles and patents to be published in the future, architectural research has a large room for improvement. This paper conducts an in-depth analysis of PG and provides information on the technological development prospects and opportunities, which is helpful for researchers engaged in PG management.

A comprehensive review on green buildings research: bibliometric analysis during 1998-2018

Buildings account for nearly 2/5ths of global energy expenditure. Due to this figure, the 90s witnessed the rise of green buildings (GBs) that were designed with the purpose of lowering the demand for energy, water, and materials resources while enhancing environmental protection efforts and human well-being over time. This paper examines recent studies and technologies related to the design, construction, and overall operation of GBs and determines potential future research directions in this area of study. This global review of green building development in the last two decades is conducted through bibliometric analysis on the Web of Science, via the Science Citation Index and Social Sciences Citation Index databases. Publication performance, countries' characteristics, and identification of key areas of green building development and popular technologies were conducted via social network analysis, big data method, and S-curve predictions. A total of 5246 articles were evaluated on the basis of subject categories, journals' performance, general publication outputs, and other publication characteristics. Further analysis was made on dominant issues through keyword co-occurrence, green building technologies by patent analysis, and S-curve predictions. The USA, China, and the UK are ranked the top three countries where the majority of publications come from. Australia and China had the closest relationship in the global network cooperation. Global trends of the top 5 countries showed different country characteristics. China had a steady and consistent growth in green building publications each year. The total publications on different cities had a high correlation with cities' GDP by Baidu Search Index. Also, barriers and contradictions such as cost, occupant comfort, and energy consumption were discussed in developed and developing countries. Green buildings, sustainability, and energy efficiency were the top three hotspots identified through the whole research period by the cluster analysis. Additionally, green building energy technologies, including building structures, materials, and energy systems, were the most prevalent technologies of interest determined by the Derwent Innovations Index prediction analysis. This review reveals hotspots and emerging trends in green building research and development and suggests routes for future research. Bibliometric analysis, combined with other useful tools, can quantitatively measure research activities from the past and present, thus bridging the historical gap and predicting the future of green building development.

A bibliometric analysis of industrial wastewater treatments from 1998 to 2019

For the foreseeable future, industrial water demand will grow much faster than agriculture. The demand together with the urgency of wastewater treatment, will pose big challenges for most developing countries. We applied the bibliometric analysis combined with social network analysis and S-curve technique to quantitatively analyze 9413 publications related to industrial wastewater treatment in the Scientific Citation Index (SCI) and Social Sciences Citation Index (SSCI) databases from 1998 to 2019. The results showed that: (1) Publications on industrial wastewater treatment have increased from 120 in 1998 to 895 in 2019 with a steady annual increment rate, and researchers have focused more on the application and optimization of existing technologies. (2) China had the highest number of publications (n = 1651, 19.66% of global output) and was a core country in the international cooperation network, whereas the United States and European countries produced higher quality papers. (3) By analyzing the co-occurrence and clusters of keywords and comparing three wastewater treatment categories (physical, chemical, biological), adsorption (n = 1277), oxidation (n = 1085) and activated sludge process (n = 1288) were the top three techniques. Researchers have shifted their focus to treatment technologies for specific wastewater type, such as textile wastewater, pulp and paper wastewater, and pharmaceutical wastewater. The S-curve from articles indicates that physical and chemical treatment technologies are attached with great potential in the near future, especially adsorption and advanced oxidation, while the biological treatment technologies are approaching to the saturation stage. Different pattern is observed for the S-curve derived from patents, which stressed the limited achievement until now and further exploration in the field application for the three treatment categories. Our analysis provides information of technology development landscape and future opportunities, which is useful for decision makers and researchers who are interested in this area.

Data-Driven Regularization Parameter Selection in Dynamic MRI

In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where reconstructions yield expected sparsity levels in the regularization domains. The expected sparsity levels are obtained from the measurement data for temporal regularization and from a reference image for spatial regularization. Two formulations are proposed. Simultaneous search for a parameter pair yielding expected sparsity in both domains (S-surface), and a sequential parameter selection using the S-curve method (Sequential S-curve). The approaches are evaluated using simulated and experimental DCE-MRI. In the simulated test case, both methods produce a parameter pair and reconstruction that is close to the root mean square error (RMSE) optimal pair and reconstruction. In the experimental test case, the methods produce almost equal parameter selection, and the reconstructions are of high perceived quality. Both methods lead to a highly feasible selection of the regularization parameters in both test cases while the sequential method is computationally more efficient.

Poorly known aspects of flattening the curve of COVID-19

A negative correlation between the final ceiling of the logistic curve and its slope, established long time ago via a simulation study, motivated this closer look at flattening the curve of COVID-19. The diffusion of the virus is analyzed with S-shaped logistic-curve fits on the 25 countries most affected in which the curve was more than 95% completed at the time of the writing (mid-May 2020.) A negative correlation observed between the final number of infections and the slope of the logistic curve corroborates the result obtained long time ago via an extensive simulation study. There is both theoretical arguments and experimental evidence for the existence of such correlations. The flattening of the curve results in a retardation of the curve's midpoint, which entails an increase in the final number of infections. It is possible that more lives are lost at the end by this process. Our analysis also permits evaluation of the various governments' interventions in terms of rapidity of response, efficiency of the actions taken (the amount of flattening achieved), and the number of days by which the curve was delayed. Not surprisingly, early decisive response-such as countrywide lockdown-proves to be the optimum strategy among the countries studied.

Characterization of the key aroma compounds in Laoshan green teas by application of odour activity value (OAV), gas chromatography-mass spectrometry-olfactometry (GC-MS-O) and comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-qMS)

To investigate the key aroma compounds in Laoshan green teas (Huangshan (S1), Changling (S2), and Fangling (S3)), gas chromatography-mass spectrometry-olfactometry (GC-MS-O), a flame photometric detector (FPD), odor activity value (OAV), and comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-qMS) were employed. A total of 50 aroma compounds were perceived and 24 compounds were identified as important compounds related to OAV, such as dimethyl sulfide (OAV: 126-146), skatole (OAV: 27-50), furaneol (OAV: 8-27), (Z)-jasmone (OAV: 16-23), 2-methylbutanal (OAV: 15-22), and 3-methylbutanal (OAV: 68-87). Furthermore, the S-curve method was used to research the effect of aroma compounds on the threshold of aroma recombination (AR). The AR thresholds decreased from 3.8 mL to 0.45, 0.66, 0.93, 0.95, 0.75, 1.09, 3.01, and 2.57 mL after addition of eight compounds (skatole, furaneol, (Z)-jasmone, α-damascenone, sclareololide, dihydroactinidiolide, vanillin, and δ-valerolactone), indicating that those compounds (OAV >1) were contributors to the overall aroma of Laoshan teas.

Systematic Review and Study of S Curves for Biomass Quantification in Solid-state Fermentation (SSF) and Digital Image Processing (DIP) Applied to Biomass Measurement in Food Processes

BACKGROUND

There are several methods for the quantification of biomass in SSF, such as glucosamine measurement, ergosterol content, protein concentration, change in dry weight or evolution of CO2 production. However, all have drawbacks when obtaining accurate data on the progress of the SSF due to the dispersion in cell growth on the solid substrate, and the difficulty encountered in separating the biomass. Studying the disadvantages associated with the process of biomass quantification in SSF, the monitoring of the growth of biomass by a technique known as digital image processing (DIP), consists of obtaining information on the production of different compounds during fermentation, using colorimetric methods based on the pixels that are obtained from photographs.

OBJECTIVE

The purpose of this study was to know about the state of the technology and the advantages of DIP.

METHODS

The methodology employed four phases; the first describes the search equations for the SSF and the DIP. A search for patents related to SSF and DIP carried out in the Free Patents Online and Patent inspiration databases. Then there is the selection of the most relevant articles in each of the technologies. As a third step, modifications for obtaining the best adjustments were also carried out. Finally, the analysis of the results was done and the inflection years were determined by means of six mathematical models widely studied.

RESULTS

For these models, the inflection years were 2018 and 2019 for both the SSF and the DIP. Additionally, the main methods for the measurement of biomass in SSF were found, and are also indicated in the review, as DIP measurement processes have already been carried out using the same technology.

CONCLUSION

In addition, the DIP has shown satisfactory results and could be an interesting alternative for biomass measurement in SSF, due to its ease and versatility.

Exploring and quantifying the impact of climate change on surface water temperature of a high mountain lake in Central Europe

Lake surface water temperature (LSWT) is a key indicator which drives ecosystem structure and function. Quantifying the impact of climate change on LSWT variations is thus of great significance. In this study, observed data of LSWT during the period 1969-2018 in a high mountain lake (Morskie Oko Lake, Central Europe) were analyzed. The results showed that the prominent warming of the LSWT and air temperature began around 1997. A logistic non-linear S-curve function was used to model monthly average LSWT. The non-linear model performed well to capture monthly average LSWT and air temperature relationships (Nash-Sutcliffe efficiency coefficient 0.86 and the root mean squared error 1.63 °C). Using the 2009-2018 period as base scenario, a sensitivity analysis was conducted. The results showed that the annual mean LSWT will likely increase about + 1.29 °C and + 2.64 °C with air temperature increases of + 2 °C and + 4 °C respectively at the end of the twenty-first century. If realized, such a scenario will cause serious consequences on lake ecosystem.

The S-curve discontinuity theory predicts the path towards a "well" society and increased longevity

The logistic function or logistic growth curve is an "S" shape (sigmoid curve) that has been applied to numerous fields, including geology, physics, biology, mathematics, chemistry, economics, sociology, oncology, and statistics. The S-curve initiates with exponential growth, followed by slowing of growth as saturation occurs, and completion of growth at maturity. The S-curve follows the law of natural growth with a limiting factor, whether it be a competition for resources, investigation and demand for new products, or an economic bubble. The concept of the S-curve has been utilized in medicine to describe the advancements in the 20th century based on the diagnosis and treatment of disease (the "illness" curve [first S-curve]) and predict the future focused on disease prevention and health promotion (the "wellness" curve [second S-curve]). Herein, we propose a third S-curve that we are labeling the "longevity" curve.

Frequency patterns of semantic change: corpus-based evidence of a near-critical dynamics in language change

It is generally believed that when a linguistic item acquires a new meaning, its overall frequency of use rises with time with an S-shaped growth curve. Yet, this claim has only been supported by a limited number of case studies. In this paper, we provide the first corpus-based large-scale confirmation of the S-curve in language change. Moreover, we uncover another generic pattern, a latency phase preceding the S-growth, during which the frequency remains close to constant. We propose a usage-based model which predicts both phases, the latency and the S-growth. The driving mechanism is a random walk in the space of frequency of use. The underlying deterministic dynamics highlights the role of a control parameter which tunes the system at the vicinity of a saddle-node bifurcation. In the neighbourhood of the critical point, the latency phase corresponds to the diffusion time over the critical region, and the S-growth to the fast convergence that follows. The durations of the two phases are computed as specific first-passage times, leading to distributions that fit well the ones extracted from our dataset. We argue that our results are not specific to the studied corpus, but apply to semantic change in general.

The S-curve for forecasting waste generation in construction projects

Forecasting construction waste generation is the yardstick of any effort by policy-makers, researchers, practitioners and the like to manage construction and demolition (C&D) waste. This paper develops and tests an S-curve model to indicate accumulative waste generation as a project progresses. Using 37,148 disposal records generated from 138 building projects in Hong Kong in four consecutive years from January 2011 to June 2015, a wide range of potential S-curve models are examined, and as a result, the formula that best fits the historical data set is found. The S-curve model is then further linked to project characteristics using artificial neural networks (ANNs) so that it can be used to forecast waste generation in future construction projects. It was found that, among the S-curve models, cumulative logistic distribution is the best formula to fit the historical data. Meanwhile, contract sum, location, public-private nature, and duration can be used to forecast construction waste generation. The study provides contractors with not only an S-curve model to forecast overall waste generation before a project commences, but also with a detailed baseline to benchmark and manage waste during the course of construction. The major contribution of this paper is to the body of knowledge in the field of construction waste generation forecasting. By examining it with an S-curve model, the study elevates construction waste management to a level equivalent to project cost management where the model has already been readily accepted as a standard tool.

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving.