An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm

Data stored on physical storage devices and transmitted over communication channels often have a lot of redundant information, which can be reduced through compression techniques to conserve space and reduce the time it takes to transmit the data. The need for adequate security measures, such as secret key control in specific techniques, raises concerns about data exposure to potential attacks. Encryption plays a vital role in safeguarding information and maintaining its confidentiality by utilizing a secret key to make the data unreadable and unalterable. The focus of this paper is to tackle the challenge of simultaneously compressing and encrypting data without affecting the efficacy of either process. The authors propose an efficient and secure compression method incorporating a secret key to accomplish this goal. Encoding input data involves scrambling it with a generated key and then transforming it through the Burrows-Wheeler Transform (BWT). Subsequently, the output from the BWT is compressed through both Move-To-Front Transform and Run-Length Encoding. This method blends the cryptographic principles of confusion and diffusion into the compression process, enhancing its performance. The proposed technique is geared towards providing robust encryption and sufficient compression. Experimentation results show that it outperforms other techniques in terms of compression ratio. A security analysis of the technique has determined that it is susceptible to the secret key and plaintext, as measured by the unicity distance. Additionally, the results of the proposed technique showed a significant improvement with a compression ratio close to 90% after passing all the test text files.

Development of sequence-characterized amplified region (SCAR) markers for accurate and differential identification of multienzyme-producing and non-enzymatic Aspergillus strains of industrial importance

Aspergillus strains are known to produce multiple enzymes of industrial importance. To screen Aspergillus isolates and select a strain with the ability to produce multiple enzymes and discriminate it from non-enzymatic strains, a rapid and accurate approach is required. With this background, a DNA fingerprinting-based study was conducted to develop a simple but accurate molecular detection method with the potential to discriminate multienzyme-producing Aspergillus strains from non-enzymatic strains, irrespective of species. To achieve this, Enterobacterial Repetitive Intergenic Consensus (ERIC) PCR was employed to derive group-specific Sequence Characterized Amplified Region (SCAR) markers (i.e., markers corresponding to PCR amplicons of known DNA sequence). To this end, both group-specific (multienzyme-producing and non-enzymatic Aspergillus group) SCAR markers were sought by comparing the ERIC fingerprint profiles and used to develop primers for use in specific and differential identification of multienzyme-producing Aspergillus isolates. As an outcome, the two SCAR-PCR formats were developed. One format is for specific identification of multienzyme-producing Aspergillus strains (SCAR-PCR1), and the other for identifying non-enzymatic Aspergillus strains (SCAR-PCR2). Both SCAR-PCRs were able to discriminate between these two contrasting groups. These formats are simple but accurate and rapid compared to the time-consuming and laborious conventional methods. Therefore, they could be efficient as an alternative strategy for the high-throughput screening of industrially important Aspergillus strains.

A decision model for ranking Asian Higher Education Institutes using an NLP-based text analysis approach

Identification of the best institute for higher education has become one of the most challenging issues in the present education system. It has become more complicated as more institutes exist with extraordinary infrastructural facilities. Therefore a decision model is required to identify the best institute for higher education based on multiple criteria. This paper proposes a Natural Language Processing (NLP) based decision model for the identification of the best higher education institute using MCDM methods. The existing decision models for the selection of the best higher education institutions consider a limited number of criteria for decision making. In this proposed model, 17 criteria and 15 institute datasets have been identified for the development of the decision model through extensive research and experts opinion. The NLP-based text analysis approach is applied to extract the relevant information and convert it to a suitable format. As the relative importance of the criteria plays a crucial role in decision making, CRITIC and Rank centroid methods are applied for the calculation of relative weights of criteria. TOPSIS method is used to generate the ranking grades of alternatives for each criterion. An objective function is defined to calculate the evaluation scores and select the best institute for higher education. It has been observed that the ranks obtained from the developed model match pretty well with the ranks obtained from other MCDM methods and the experts.

Antifungal potential of Azotobacter species and its metabolites against Fusarium verticillioides and biodegradation of fumonisin

AIMS

In the study, seven Plant Growth Promoting Rhizobacteria (PGPR) Azotobacter species were screened against three strains of Fusarium verticillioides to test its antifungal activity. Azotobacter strains were tested for the degradation of fumonisin produced by F. verticillioides. Secondary metabolites were isolated and characterized from the Azotobacter strains for the first time.

METHODS AND RESULTS

Potential seven Azotobacter species antifungal activity was tested following the dual culture assay against three starins of Fusarium verticillioides namely FVM-42, FVM-86, MTCC156 estimating the substantial zone of inhibition. Azotobacter species AZT-31 and AZT-50 strains significantly inhibited the growth of F. verticillioides recording drastic growth enhancement of maize under in-vitro conditions by calculating the infection incidence, vigour index and germination percentage. As confirmation, dereplication studies were conducted for the reconfirmation of Azotobacter strains by isolating from rhizoplane. Azotobacter strains played a key role in degradation of fumonisin produced by F. verticillioides reporting 98% degradation at 2hr of incubation with the pathogen. Furthermore, in the study first time we have tried to isolate and characterize the secondary metabolites from the Azotobacter strains exhibiting six compounds from the species AZT-31 (2) and AZT-50 (4). Preliminary in-vitro experiments were carriedout using the compounds extracted to check the reduction of infection incidence (90%) and increase in germination percentage upto 50 to 70% when compared to test pathogen.

CONCLUSION

Azotobacter strains referred as PGPR on influencing the growth of plant by producing certain substances that acts as stimulators on inhibiting the growth of pathogen.

SIGNIFICANCE AND IMPACT OF THE STUDY

Future perspective would be the production of active combination of carboxamide compound and Azotobacter species for preventively controlling the phytopathogenic fungi of plants and crops and also towards the treatment of seeds.

Exploring biotechnological and functional characteristics of probiotic yeasts: A review

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In this review, the probiotic attributes of yeasts other than Saccharomyces boulardii and the various applications of probiotic yeast in biotechnology have been explored.

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This review comprises of the probiotic attributes, antagonistic activity against pathogens, plant growth promoting attributes, industrial application and their biotherapeutic potentials.

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Advanced and additional studies on non-Saccharomyces yeasts are necessary prior to administer these yeasts as potential probiotics for health and wellbeing.

Probiotics are vital and beneficial organisms which offers the health benefits to the host organisms. The fungal probiotic field is one of the developing fields nowadays. Yeast has an enormous and diverse group of microorganisms that is attracting and expanding the attention from researchers and industries. Saccharomyces boulardii, the only patented strain belonging to yeast genera for the human use, has been broadly evaluated for its probiotic effect. Yeasts belonging to the genera Debaryomyces, Pichia, Yarrowia, Meyerozyma, Kluyveromyces etc.., have attained more interest because of their beneficial and probable probiotic features. These yeast probiotics produce VOCs (Volatile organic compounds), mycocins and antimicrobials which shows the antagonistic effect against pathogenic fungi and bacteria. Additionally, those yeasts have been recorded as good plant growth promoting microorganisms. Yeast has an important role in environmental applications such as bioremediation and removal of metals like chromium, mercury, lead etc., from waste water. Probiotic yeasts with their promising antimicrobial, antioxidant, anticancer properties, cholesterol assimilation and immunomodulatory effects can also be utilized as biotherapeutics. In this review article we have made an attempt to address important yeast probiotic attributes.

Detecting COVID-19-Related Fake News Using Feature Extraction

Since its emergence in December 2019, there have been numerous posts and news regarding the COVID-19 pandemic in social media, traditional print, and electronic media. These sources have information from both trusted and non-trusted medical sources. Furthermore, the news from these media are spread rapidly. Spreading a piece of deceptive information may lead to anxiety, unwanted exposure to medical remedies, tricks for digital marketing, and may lead to deadly factors. Therefore, a model for detecting fake news from the news pool is essential. In this work, the dataset which is a fusion of news related to COVID-19 that has been sourced from data from several social media and news sources is used for classification. In the first step, preprocessing is performed on the dataset to remove unwanted text, then tokenization is carried out to extract the tokens from the raw text data collected from various sources. Later, feature selection is performed to avoid the computational overhead incurred in processing all the features in the dataset. The linguistic and sentiment features are extracted for further processing. Finally, several state-of-the-art machine learning algorithms are trained to classify the COVID-19-related dataset. These algorithms are then evaluated using various metrics. The results show that the random forest classifier outperforms the other classifiers with an accuracy of 88.50%.

Towards applying internet of things and machine learning for the risk prediction of COVID-19 in pandemic situation using Naive Bayes classifier for improving accuracy

Infections such as COVID-19 are affecting the entire world and measures such as social distancing can be done so that the contact among people is reduced. IoT devices usage keeps on increasing every day thereby connecting the environments physically. Among the current technologies, machine learning can be employed along with IoT devices. Predicting the risk related with COVID-19, a novel method employing machine learning is proposed. Random forest and Naive Bayes classifier are used for the prediction from the data collected with the help of sensors. Groups of people are recognized and the disease impact can be reduced for the particular group with more population. The accuracy of RF is 97% and for NB it is 99%.

Exit-Site Infection: A Comparison of Classification Systems

In general, in peritoneal dialysis (PD) practice in hospitals, Twardowski and Prowant's exit-site classification system is used, while the International Society for Peritoneal Dialysis (ISPD) exit-site scoring system is practical to use in community visits with less experienced healthcare personnel. Nevertheless, when exit-site scoring is 3 points under the ISPD exit-site score system and it falls in the category of equivocal under the Twardowski and Prowant's exit-site classification, the physician should be vigilant about the possibility of developing peritonitis, and hence, patients need to be kept under periodic monitoring.

Morphological, pathological and mycotoxicological variations among Fusarium verticillioides isolated from cereals

Among the 194 Fusarium verticillioides isolates screened from 127 cereal samples, 176 were fumonisin producers and others were non-producers. Representative nine Fusarium verticillioides strains along with one reference standard strain MTCC156 were selected to study their morphological, pathological and mycotoxicological variations by conventional and molecular approaches. Fusarium verticillioides strains FVM86, FVM146, FV200 and FVS3 showed significant pathogenicity and also in pigmentation production but varied in fumonisin production. Fusarium verticillioides strain FVP19 recorded variations in all the assays. Fusarium verticillioides strain FVM42 showed drastic phenotypic variation and it also produced fumonisin. Genetic variation among the strains was independent of geographic area of origin but depended on their ability to produce fumonisin. The strains were independent in their cultural characteristics, pigmentation production, pathogenicity assays, fumonisin production and in their genetic variability without having any correlation.

Lactobacillus plantarum MYS6 Ameliorates Fumonisin B1-Induced Hepatorenal Damage in Broilers

Fumonisin B1 (FB1), a mycotoxin produced by Fusarium species is a predominant Group 2B carcinogen occurring in maize and maize-based poultry feeds. It is shown to be nephrotoxic, hepatotoxic, neurotoxic, and immunosuppressing in animals. In this study, we report the ameliorating effects of a probiotic strain, Lactobacillus plantarum MYS6 on FB1-induced toxicity and oxidative damage in broilers. A 6-week dietary experiment consisting of 48 broilers was performed in six treatment groups. Probiotic treatment (10⁹ cells/mL) involved pre-colonization of broilers with L. plantarum MYS6 while co-administration treatment involved supplementation of probiotic and FB1-contaminated diet (200 mg/Kg feed) simultaneously. At the end of the treatment period, growth performance, hematology, serum biochemistry, and markers of oxidative stress in serum and tissue homogenates were evaluated in all the broilers. The histopathological changes in hepatic and renal tissues were further studied. The results demonstrated that administration of L. plantarum MYS6 efficiently improved the feed intake, body weight and feed conversion ratio in broilers. It mitigated the altered levels of hematological indices such as complete blood count, hemoglobin, and hematocrit. Serum parameters such as serum glutamic oxaloacetic transaminase, serum glutamic pyruvic transaminase, creatinine, cholesterol, triglycerides, and albumin were significantly restored after administering the probiotic in FB1-intoxicated broilers. Additionally, L. plantarum MYS6 alleviated the levels of oxidative stress markers in serum and tissue homogenate of liver. The histopathological data of liver and kidney further substantiated the overall protection offered by L. plantarum MYS6 against FB1-induced cellular toxicity and organ damage in broilers. Our results indicated that co-administration of probiotic along with the toxin had better effect in detoxification compared to its pre-colonization in broilers. Collectively, our study signifies the protective role of L. plantarum MYS6 in ameliorating the FB1-induced toxicity in the vital organs and subsequent oxidative stress in broilers. The probiotic L. plantarum MYS6 can further be formulated into a functional feed owing to its anti-fumonisin attributes and role in mitigating FB1-induced hepatorenal damage.

News Information Services at the Energy and Resources Institute: A Case Study

Describes significant developments in the news information services at The Energy Resources Institute (TERI), in New Delhi, India. News information service is one of the most demand driven services in today’s information market. Every organization needs current information, which can be provided by news information services. The news information service at TERI is based on the institute’s mandate, which is focused on energy, environment, and sustainable development. It serves external and internal researchers, consultants and other users. The service was initially print-based, providing conventional press clippings, but with the emergence of new technologies it evolved into daily and weekly electronic services and now also offers web-based services. The information services have been tailored to meet the demands of the user community.

Curcumin-loaded N,O-carboxymethyl chitosan nanoparticles for cancer drug delivery

Chitosan (CS) and its carboxymethyl derivatives are smart biopolymers that are non-toxic, biocompatible and biodegradable, and, hence, suitable for various biomedical applications, such as drug delivery, gene therapy and tissue engineering. Curcumin is a major chemotherapeutic agent with antioxidant, anti-inflammatory, anti-proliferative, anticancer and antimicrobial effects. However, the potential of curcumin as a chemotherapeutic agent is limited by its hydrophobicity and poor bioavailability. In this work, we developed a nanoformulation of curcumin in a carboxymethyl chitosan (CMC) derivative, N,O-carboxymethyl chitosan (N,O-CMC). The curcumin-loaded N,O-CMC (curcumin-N,O-CMC) nanoparticles were characterized using DLS, AFM, SEM, FT-IR and XRD. DLS studies revealed nanoparticles with a mean diameter of 150 ± 30 nm. AFM and SEM confirmed that the particles have a spherical morphology within the size range of 150 ± 30 nm. Curcumin was entrapped with in N,O-CMC nanopartcles with an efficiency of 80%. The in vitro drug-release profile was studied at different pH (7.4 and 4.5) at 37°C for different incubation periods with and without lysozyme. Cytotoxicity studies using MTT assay indicated that curcumin-N,O-CMC nanoparticles showed specific toxicity towards cancer cells and non-toxicity to normal cells. Cellular uptake of curcumin-N,O-CMC nanoparticles was analyzed by fluorescence microscopy and was reconfirmed by flow cytometry. Overall, these results indicate that like previously reported curcumin loaded O-CMC nanoparticles, N,O-CMC will also be an efficient nanocarrier for delivering curcumin to cancer cells.

Influence of heavy metals on methane oxidation in tropical rice soils

In a laboratory incubation study, the effect of select heavy metals on methane (CH4) oxidation in two rice soils was investigated under two moisture regimes. Heavy metals differed in their effect on CH4 oxidation in both soils under the two water regimes. Cr significantly inhibited CH4 oxidation in the alluvial soil at 60% moisture holding capacity, while Cu stimulated the process. On the contrary, Zn inhibited CH4 oxidation in both alluvial and laterite soils only under flooded conditions. Application of rice straw alleviated the inhibitory effect of heavy metals on CH4 oxidation and CO2 production. Inhibition of CH4 oxidation in the alluvial soil was related to the methanotrophic bacterial population in Cr- and Zn-amended alluvial soil.

Salubrious effect of vitamin C and vitamin E on tamoxifen-treated women in breast cancer with reference to plasma lipid and lipoprotein levels

Tamoxifen, a non-steroidal antiestrogen, has been used in the hormonal treatment for breast cancer. The hepatic estrogenic effect of tamoxifen causes severe triglyceridemia. The combined effect of tamoxifen, vitamin C and vitamin E on plasma lipid and lipoprotein is important, since, vitamin C and vitamin E encumbered the lipid abnormalities instigated by tamoxifen. Therefore supplementation of vitamin C (Celin 500 mg) and vitamin E (Evion 400 mg) for 90 days along with tamoxifen (10 mg twice a day) to postmenopausal breast cancer patients was ventured. In tamoxifen-treated patients, total cholesterol (TC), free cholesterol (FC), phospholipids (PL), free fatty acids (FFA), low density lipoprotein cholesterol (LDL) levels were decreased and the triglycerides (TG), ester cholesterol (EC), high density lipoprotein cholesterol (HDL) and very low density lipoprotein cholesterol (VLDL) levels were increased. Combination therapy reduce all the cholesterol level and VLDL, LDL. TG levels were significantly decreased and HDL, EC levels were significantly increased. These results suggested that tamoxifen treatment is the most effective during co-administration of vitamin C and vitamin E in that they reduce the tamoxifen-induced hypertriglyceridemia.