New class of triazinoindole bearing thiosemicarbazide (1-25) was synthesized and evaluated for α-glucosidase inhibitory potential. All synthesized analogues exhibited excellent inhibitory potential having IC50 values ranging from 1.30 ± 0.01 to 35.80 ± 0.80 µM when compared with the standard acarbose having IC50 value 38.60 ± 0.20 µM. Among series the analogues 1 and 23 was found the most potent having IC50 values 1.30 ± 0.05 and 1.30 ± 0.01 µM respectively. Structure activity relationship (SAR) was mainly based upon by bring about difference of substituents on phenyl rings. To confirm the binding interactions, molecular docking study was performed. Synthesized analogues were characterized through HREI-MS, 1H and 13C-NMR analysis.

This study critically analyses the realities and experiences of gender-based harassment in cyberspace, and aims to unveil the shadows that shroud this phenomenon. It discloses the online spaces that disseminate detrimental attitudes towards women, despite their physical absence. Cyber violence has become a global issue and it causes significant economic and societal consequences. Recognizing and dealing with the adverse effects caused by demeaning cyber gender harassment is essential. The study raises questions to explore the kind of cyberbullying offences that are brought on by misogynistic inclinations in online environments and the experiences of the women who have gone through cyberbullying. This study uses semi-structured interviews and the IPA technique of the analysis of data to thoroughly examine the unique experiences of cyber harassment victims by applying a qualitative research approach. The study looks into various misogynistic cyber harassment offences and analyses women's accounts. Due to obstacles to justice, cyber violence and harassment replicate physical problems like spousal abuse and sexual harassment. A constant assault of intimidation and harassment results from the traditionally male-dominated character of cyberspace, which affects women's social, economic, and psychological well-being. Participants related horrifying tales of families' indifference and law enforcement officials' trivialization. Mental health problems increase isolation and prevent involvement in academic and professional activities. Women's well-being is exacerbated by societal blaming and secondary victimization. This brief analysis clarifies the intricacies of gender-based harassment in cyberspace and emphasizes the urgent need for efficient solutions to address this widespread issue.

Phosphorus (P) is an important element in a complete and balanced fertility program that can improve crop P use efficiency and ultimately productivity and profitability. Phosphatic fertilizers use without organic fertilizers leads to gradual decline in soil organic matter, native nutrient status and ultimately reduction in agricultural productivity and economic growth. The objectives of this was to evaluate P efficiencies with incorporation of peach sources, beneficial microbes and P application. From sustainability points of view, alternative use of different sources and forms of organic sources alone or in combination with inorganic P and beneficial microbes possess potential for improving productive capacity of the soil. Separate field experiments (one each on maize and soybean as a test crop) were conducted at Agriculture Research Institute Mingora Swat (ARI) for two consecutive years in summer season of 2016 (year one) and 2017 (year two). For the first time such a study were conducted to utilize peach leftovers and biomass (leaves, twigs, fruits, stones and barks partially decomposed, its compost and biochar) along with three phosphorus (P) levels (50, 75, 100 kg P ha-1) and two beneficial microbes (PSB and Trichoderma) on such a way to enhance soil sustainability and P use efficiency of soybean and maize. The results revealed that organic sources had significant effect on soybean and maize P use efficiency (PUE), P agronomic efficiency (PAE), partial factor productivity (PFPp) and soil P concentration. In experiment 1 among the organic sources, peach residues increased soil P (12.0 mg kg-1) as compared to peach compost and biochar (8.6 & 11.7 mg kg-1). Soil P concentration was maximum (12.1 mg kg-1) with PSB than Trichoderma (9.5 mg kg-1). Application of P at 100 kg ha-1increased soil P contents (16.9 mg kg-1) as compared to 50 and 75 kg P ha 1 (5.9 & 9.6 mg kg-1) respectively. P concentration was increased drastically in year 2 (12.4 mg kg-1) than year one (9.1 mg kg-1). PUE in both crops (soybean and maize) was maximum (25.6 & 28.4%) with peach biochar than compost and residues along with Trichoderma (21.7 & 27.8%). Highest PUE in soybean was recorded with 75 kg P ha-1(22.2%) however in maize maximum PUE was noted with 50 kg P ha-1(33.5%). PAE and PFPp in both crops was maximum with biochar and soil application of Trichoderma than other organic sources and PSB. Among the P levels highest PAE in soybean and maize was recorded with 75 kg ha-1whereas PFPp in soybean was maximum with 75 kg P ha-1 and interestingly in maize it was noted with 50 kg ha-1. Conclusively soybean and maize PAE, PFPp and PUE was higher with biochar, soil incorporation of Trichoderma and P at the rate of 75 kg ha-1 and can improve soybean and maize yield and soil productivity on sustainable basis.

Endopolygalacturonase (EndoPGase) is one of the crucial pectinases belonging to the class of carbohydrase. The catalytic action of EndoPGase captivate the attention for production of this extremely valuable catalyst of industrial sector. The main focus was to ascertain a potential bacterial candidate for endoPGase production. The isolated bacterial strain was further identified by 16S rDNA gene sequencing. A genomic library was constructed by using Lambda ZAP II vector system to investigate the pectinolytic potential of the expressed genes. The parameters for enzyme biosynthesis were optimized by single as well as multiple factor approach at a time. The results of our investigation led to the identification of a potent strain of Bacillus subtilis NR2. The strain was found active for pectic enzyme activity under shaking- flask fermentation at pH 5.0 and 50 °C temperature of incubation. Among all monomeric and polymeric substrates, citrus pectin followed by wheat bran was considered the best enzyme inducers at 1 % concentration. Moreover, an increasing trend in enzyme activity was observed with the increasing inducer concentration. The combined effect of three variables (pH, substrates, and substrate concentration) was explored by response surface methodology involving Box Benken Design (BBD). The study concluded that the soil isolated B. subtilis can be utilized for commercial scale pectinase enzyme production.

Nutrients management is a mainspring in agricultural systems for sustained productivity, economy sustainability and environmental quality. Excessive and lesser nutrient application caused environmental pollution and reduced production, respectively impacting socio-economics of the entire ecosystems. Sustainable agricultural production thus demands supplementation of nutrients either through natural processes, application of animal by-products, and mineral fertilizers to crop fields. Technology application for treating useless agricultural wastes into useful source is a management strategy that prevents environment pollution. Crude animal manures triggered soil degradation, attenuation air and water quality, and resulted in higher concentrations of heavy metals. Primary nutrients, i.e., nitrogen, phosphorus and potassium are used globally and are non-renewable. Augmented upsurge in prices of inorganic fertilizers and required discharge restrictions on nutrient has stimulated the technological developments including biochar, composting, vermicomposting, composting with biochar, pyrolysis, forward osmosis, and electro-dialysis to recover nutrients. Therefore, outlining the research gaps considering the present and imminent potential of these technologies for adaptation of nutrient recycling is of great importance. Thus, it’s need of an hour to fix our environment and for that scientists are trying to introduce and renovate the technologies which have immense potential to mitigate the negative effects of technology adversities on our environment.

The brick manufacturing sector in Bangladesh is experiencing rapid growth, leading to notable environmental and health concerns. The primary objective of this research is to examine the Savar Upazila, a region of significant economic significance owing to its favorable brick manufacturing conditions and proximity to Dhaka city. Brick kilns, among other sources, constitute significant contributors to air pollution. The study utilized primary and secondary data to examine brick kiln emissions' effects on the surrounding area's environment and public health. The collection of primary data was conducted in multiple zones within Savar Upazila, which is home to a significant number of brick kilns. The utilization of secondary data provided valuable insights regarding the toxic pollutants discharged by these kilns and the corresponding health risks they pose. The participants provided accounts of various health ailments, such as dermatological conditions, optical difficulty, and respiratory complications, further aggravated by brick kilns' incidents. The prevalence of crop losses, soil degradation, and reduced agricultural yields was confirmed by 74% of the respondents. The trees and crops in the surrounding area experienced adverse effects due to the deposition of dust particles. During periods of inactivity, the concentrations of sulfur oxide (SOx) were between 6 and 9 times lower compared to periods of operation. Similarly, nitrogen oxide (NOx) levels were observed to be 4 to 6 times lower during non-operational phases. The degradation of water quality in adjacent bodies has been attributed to the deposition of dust and ash originating from brickfields, resulting in substantial repercussions on aquaculture. A significant proportion of participants indicated experiencing diverse health issues, notwithstanding the employment prospects generated by brick kilns, thereby underscoring the adverse consequences on both the environment and the local economy.

Multi-walled carbon nanotubes (MWCNTs) and graphene oxide (GO) reinforced carbon foam (CF) composite were prepared by direct pyrolysis of MWCNTs, GO and mesophase coal tar pitch. The effect of additive amount of the mixture of MWCNTs and GO on the microstruture and properties of carbon foam was analzyed by transmission electron miscroscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), Four-probe resistance meter, universal testing machine, and laser thermal conductivity tester respectively. The result shows that MWCNTs and GO had significant impact on the microstructure of carbon foam. Futhermore, the electrical, mechanical and thermal properties of carbon foam composites were significantly enhanced by increasing the additive amount. Maximum compressive strenght of 19.2 MPa and Young’s modulus of 56.8 MPa of CF composite were observed. Similarly, Highest thermal conductivity of 30.91 W/m.K and electrical conductivity of 27.2 ×103 S/m were observed at 2 wt. % of MWCNTs-GO additive loading.

Wind energy is one of the most attractive renewable energy sources because of its low operating, maintenance, and production costs as well as its low environmental impact. The goal of this study is to discover the best locations in Bangladesh where wind farms can be built and operated efficiently. This study applied the GIS and AHP methodologies to examine the eight important parameters upon which the suitability of locations is highly dependent. This analysis finds that Bangladesh has large regions appropriate for wind farm installation, with 3718.76 km² and 16631.14 km² classified as "very high" and "high" suitability, respectively. It was also observed that wind speed, land slope, and elevation each had a height-weighted criterion of 32 %, 27 %, and 12 %, respectively, when picking suitable locations. However, the viability of this study in identifying suitable sites has been evaluated based on ROC and AUC techniques and found satisfactory as per AUC value. The knowledge gained from this study will help the sustainable and renewable energy development authority (SREDA), Bangladesh to expedite the renewable energy investment process and will ensure the great certainty. The findings of this research can be considered as baseline information in the wind energy sector.

Bacterial infections are world-wide problem and resistant bacteria is increasing globally that lead to treatments failure. Thus, it is important to find new techniques that are effective for the treatment antibiotic-resistant microorganisms. Green medicine used for the medication of different bacterial infection. Therefore , the study aimed to evaluate the immunomodulatory activity of essential fatty acid semi carbazide (EFASC) compounds extracted from flaxseed to eradicate resistance pathogens . Crud extracts of Linum usitatissimum was extracted by hexane for extraction of EFASC. The results of LD₅₀ appear that a live suspension of E.coli was 0.49×10⁷ ,while HK E.coli was 10⁸ , 125 mg /ml were the optimum dose in stimulate immune response of EFASC which gave maximum dose of total WBC , Neutrophil and Monocyte count. The immunomodulatory activity appear that E.coli + EFASC released moderate levels of IL-4 . HK E.coli release higher IL-4 lead to increase the hypersensitivity and hyper responses of immune system. HK + EFASC immunogen revealed moderate increased in IL-12 mean level 0.99 pg /ml, HK bacteria recorded 1.49 pg/ml, while the mean of EFASC revealed no significant different compare with control. An effective protection was observed in immunized groups with HK E.coli and EFASC challenged with 100 of LD50 of a live E.coli.

The Coronavirus disease due to SARS-CoV-2 emerged in Wuhan city, China in December 2019 and rapidly spread more than 200 countries as a global health pandemic. There are more 3 million confirmed cases and around 207,000 fatalities. The primary manifestation is respiratory and cardiac but neurological manifestations are being reported in the literature as case reports and case series. The most common reported symptoms to include headache and dizziness followed by encephalopathy and delirium. Among the complications noted are Cerebrovascular accident, Guillian barre syndrome, acute transverse myelitis, and acute encephalitis. The most common peripheral manifestation was hyposmia. It is further noted that sometimes the neurological manifestations can precede the typical features like fever and cough and later on typical manifestations develop in these patients. Hence a high index of suspicion is required for timely diagnosis and isolation of cases to prevent the spread in neurology wards. We present a narrative review of the neurological manifestations and complications of COVID-19. Our aim is to update the neurologists and physicians working with suspected cases of COVID-19 about the possible neurological presentations and the probable neurological complications resulting from this novel virus infection.

More than fifty million people over the age of fifty have osteoporosis issues due to low bone mass, disease contribution, and not exercising continuously. Certain most important risk factors and causes of osteoporosis contain age, gender, hormones, visits to inexperienced doctors, and certain medical conditions. In this manuscript, we diagnosed certain frank operational laws under the availability of complex intuitionistic fuzzy (CIF) information. Furthermore, using the evaluated operational laws, we pioneered the theory of CIF frank weighted averaging (CIFFWA), CIF frank ordered weighted averaging (CIFFOWA), CIF frank hybrid averaging (CIFFHA), CIF frank weighted geometric (CIFFWG), CIF frank ordered weighted geometric (CIFFOWG), CIF frank hybrid geometric (CIFFHG) operators, and described their beneficial and valuable results with certain useful properties. Moreover, we aim to evaluate the most dangerous type of osteoporosis based on their symptoms, causes, and risk factors using diagnosed approaches. Finally, to enhance the worth of the evaluated operators, we compare the diagnosed result with certain prevailing results and illustrated their geometrical representation with the help of MATLAB.

Plant growth promoting rhizobacteria (PGPR) are capable to reduce the use of chemical fertilizers input cost of farmer. Keeping in view the study was designed to investigate and evaluate inoculation effect of indigenous rhizospheric bacteria on growth and yield of wheat (Triticum aestivum L.) under in vitro and in vivo conditions using different treatments. Ten potential strains were selected on the basis of their ACC deaminase activity, siderophore production, P-solubilization and production of indole acetic acid (IAA). Further these strains were tested in three different experiments (growth chamber, pot and field). We found significant increase in crop growth response to the inoculants in comparison with un-inoculated control. In pot and field trial we tested PGPR with recommended dose of inorganic fertilizers. The results of present study revealed that inoculation of bacterial strains with wheat seeds significantly increased plant growth and improved crop yield. Results of present study reveal that these strains could be employed in different combinations and can get higher yield in case of half recommended doses of inorganic fertilizers along with consortium of strains in comparison with sole application of recommended dose of fertilizer and with consortium of strains. These strains were further identified by 16Sr RNA gene sequencing, fatty acid profile and biolog. It can be concluded that inoculated bacteria have more potential and contributes in good crop quality, increased yield when they are applied in combination, thus have potential to minimize use of chemical fertilizers.

Academic failure, low attendance, financial difficulties, and mental illness are some of the major reasons most students drop out of high schools. We investigated how high school dropout risk is affected by socioeconomic, demographic, and institutional characteristics. Therefore, research design is composed of a literature review, Questionnaire surveys by interviewing each student. Besides, the analysis and statistical modelling, the Logistic Regression method was used. The results show that academic performance, job, lack of interest and low learning ability were the significant individual characteristics that affect the high school dropout. Moreover, parental characteristics, including financial condition, lack of awareness, and education, are significant factors associated with high school dropout rates. Some other related factors, such as adaptability and influence of the peer groups, abandoning school by siblings, and extra responsibility at home and a joint family system, are also some notable factors that significantly affect the dropout rate in schools Malakand District of KP province. This research study delivered the results that contribute to the literature in education to identify different factors like student's own, parental, institutional, and household characteristics, which affect a student being a dropout from high school in Malakand district Pakistan.

This paper aims to investigate carbon monoxide (CO) concentrations on roadways of Karachi, potential blood levels carboxy-hemoglobin (COHb) in Karachi. Geographical information system (GIS) was used for spatial analysis of diseases potentiality while an interpolation technique has been applied for surface generation with town boundaries and later evaluates risk areas.The higher concentration of carbon monoxide in the ambient is mainly due to automobile emissions. The City center and CBD areas are more perilous.

Poa crymophila is a perennial, cold-tolerant, native grass species, widely distributed to the Qing-hai-Tibet Plateau. However, the molecular mechanism behind the cold stress tolerance and role of key regulatory genes and pathways of P. crymophila are poorly understood yet. Therefore, the present study investigated the physiological and transcriptome responses of P. crymophila’s roots, stems, and leaves under cold stress to explore the molecular mechanism of cold tolerance. Results of the present study suggested that cold stress significantly changed the physiologic characteristics of roots, stems, and leaves of P. crymophila. In addition, the transcriptome results showed that 4434, 8793, and 14942 differentially expressed genes (DEGs) were identified in roots, stems, and leaves, respectively; however, 464 DEGs were commonly identified in these three tissues. The Gene On-tology (GO) results showed that a large numbers of DEGs were significantly enriched in the pho-tosynthetic related categories in leaves. In addition, the “response to stimulus” category was sig-nificantly enriched in roots and stems. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that DEGs involved in “phenylpropanoid biosynthesis” were significantly enriched in roots, “photosynthesis” and “circadian rhythm-plant” pathways significantly enriched in stems and leaves, starch and sucrose metabolism, and galactose metabolism were pathways significantly enriched in three tissues. Weighted gene coexpression network analysis (WGCNA) identified Hub genes involved in P. crymophila cold response. This study provides new insights into the molecular mechanisms underlying the cold tolerance of P. crymophila belowground and aboveground tissues. In addition, specific genes involved in Ca2+ signaling, ROS scavenging system, hormones, circadian clock, photosynthesis, and transcription factors (TFs) were identified in P. crymophila. The identi-fication of key genes may provide valuable resources for further functional genomic and breeding studies.

Optimizing the nitrogen (N) timings and rate can improve nutrient uptake, and nutrient-efficiencies, especially of N in wheat under the changing climate scenario. Climatic stress in the form of high temperature and drought resulted in the decreased crop physiology and, ultimately, grain yield. Taking the example of rainfed wheat, we quantified the impact of N application rates as full and split-dose at three variable sites of rainfed Pothwar, Pakistan by conducting field experiments for two years (2013-14 and 201-15). Treatments include, T₁ = Control (No fertilizer applied), full dose of N applied at the time of crop sowing, i.e. T₂ = 50 kg N ha^-1, T₃ = 100 kg N ha^-1 and T₄ = 150 kg N ha^-1 and split application of N at different timings during different stages of the crop called as split application of N, i.e. T₅: Application of 50 kg N ha^-1 (15 kg N ha^-1 (Sowing) : 20 kg N ha^-1 (Tillering) :15 kg N ha^-1 (Anthesis), T₆: Application of 100 kg N ha^-1 (30 kg N ha^-1 (Sowing): 40 kg N ha^-1 (Tillering) : 30 kg N ha^-1 (Anthesis) and T₇: Application of 150 kg N ha^-1(45 kg N ha^-1 (Sowing) : 60 kg N ha^-1 (Tillering) : 45 kg N ha^-1 (Anthesis). Three study sites include viz. Islamabad (High rainfall with optimum temperature), University Research Farm (URF)-Koont (Medium rainfall with moderate temperature), and Talagang (low rainfall with high temperature). Results showed that the highest stomatal conductance (0.80 mole m^-2 sec^-1), net photosynthetic rate (20.07 μmole m^-2s^-1), transpiration rate (9.58 mmole m^-2s^-1), intercellular CO₂ concentration (329.25 μmole CO₂ mol^-1 air), SPAD values (58.86 %) and proline contents (35.42 μg g^-1) were obtained for split application of N (T₆ = Split N₁₀₀) compared to control and full dose of N treatments. Among sites, these physiological traits remained highest at Islamabad and lowest at Talagang, while among years, maximum values of the measured parameters were obtained in 2013-14. A similar trend was observed for crop total N, N efficiencies, and agronomic traits of the crop. Our results suggest that optimum N application rate and its suitable timings can help to harvest real benefits of N as in our findings, split dose resulted in the maximum performance of the crop from physiological parameters to the agronomic traits of the rainfed wheat crop.

Single cell proteins are the dead dried cells of microorganisms or purified protein isolated from microorganism’s cell culture, used as a food supplement to humans’ food and animals feed. World suffer from malnutrition particularly developing countries, due to rapid increase in population, increased the demand for protein and nutrients requirement. Bacteria is potential microorganism for SCP production due to high protein content, fast generation time, bio-active secondary metabolites production and can grow on various substrates. Actinobacteria species and strain have capability to produce biological active compounds, produced about two-thirds of antibiotics available in the market, actively used as antibiotics, antiprotozoal, antifungal, antiviral, anticancer, anticholesterol, antihelminth and immunosuppressant. Actinomycetes can be used as probiotic as well as single cell protein that will deal with antibiotic as well as protein source.

The paper is devoted to the investigation of regional observability with constraints on the state of semilinear parabolic systems. The purpose is to reconstruct the initial state between two prescribed functions only on an internal subregion $\omega$ of the system evolution domain $\Omega$. The proofs use two approaches, the subdifferential and HUM approach. Finally, a numerical example is provided to verify the effectiveness of our theory results.

For over two years, the global COVID-19 pandemic has persisted, and its continuation is anticipated. The emergence and rapid spread of numerous new virus variations across continents have been observed. These variants, differing from previously known strains, manifest a spectrum of behaviors and clinical presentations, ranging from asymptomatic cases to severe illnesses and fatalities. Despite substantial research efforts in recent years, significant uncertainties persist in understanding the disease, encompassing variations in clinical outcomes, comorbidities, and challenges faced by individuals infected with COVID-19. Beyond the acute phase of infection, the prevalence of post-COVID-19 symptoms, often denoted as "long COVID," is notable, particularly in individuals recovering from the disease. Nevertheless, a research gap persists concerning the pathophysiological mechanisms underlying newly emerging viral variant infections, post-COVID-19 conditions, and the corresponding therapeutic strategies. This review is presented to analyze recent advancements in comprehending the pathophysiology and therapy of COVID-19.

Asthma causes chronic coughing, wheezing, dyspnea, and chest pressure. This study assessed asthmatic patients' knowledge, attitudes and awareness of bronchial asthma and proper education on its meaning, risk factors, symptoms, diagnosis, management, and prevention practice. We performed a cross-sectional interventional asthma KAP survey in Erbil, Iraq. We adapted a validated study questionnaire from KAP studies in other nations to the Erbil situation and culture. In Erbil, Kurdistan, Iraq, two major hospitals' asthma clinics were studied. We chose 250 asthmatic ICU patients from October 2018 to July 2019. Health education was comprehensive. The health education program used a Kurdish PowerPoint with a printout. 25 groups got two-weeks of one-hour health education pre-intervention. Each group was questioned before, 2 and 12 weeks after health education. All data were analyzed by SPSS v26. The mean age of the respondent was 37.52±15.16 with 48.7 % respondent having a positive family history of asthma. After 2weeks of health education intervention, respondent have a higher knowledge score, positive attitudes compared to pre-education and after 12 weeks of education with a significant difference (P < 0.001) with improvised prevention practice. Health education programs led to considerable improvements in asthmatic patients' knowledge, attitudes, and practices regarding their condition. After receiving health education for a period of two weeks, the majority of the participants answered correctly regarding asthma, its causes, and the elements that trigger asthma attacks.

Medical implants made of biodegradable materials could be of advantage for temporary applications such mechanical support during bone-healing or as vascular stents to keep blood vessels open. After completion of the healing process the implant would disappear, avoiding long-term side effects or the need for surgical removal. Various corrodible metal alloys based on magnesium, iron or zinc have been proposed as sturdier and potentially less inflammatory alternative to degradable organic polymers, in particular for load-bearing applications. Despite the recent introduction of magnesium-based screws the remaining hurdles to routine clinical applications are still challenging, such as limiting mechanical material characteristics or unsuitable corrosion characteristics. Here, salient features and clinical prospects of currently investigated biodegradable implant materials are summarized with a main focus on magnesium alloys. A mechanism of action for the stimulation of bone growth due to the exertion of mechanical force by magnesium corrosion products is discussed. To explain divergent in vitro and in vivo effects of magnesium a novel model for bacterial biofilm infections is proposed which predicts crucial consequences antibacterial implant strategies.

It is a theoretical exportation for mass transpiration and thermal transpiration of Casson nanofluid over an extending cylindrical surface. The Stagnation point flow through porous matrix is influenced by magnetic field of form strength. Appropriate similarity functions are availed to yield the transmuted system of leading differential equations. Existence for the solution of momentum equation is proved for various values of Casson parameter β, magnetic parameter M, porosity parameter Kp and Raynolds number Re in two situations of mass transpiration (suction/injuction). Moreover, uniqueness results are discussed and for skin friction factor are established to attain accuracy for large injection values. Thermal and concentration profiles are delineated numerically by applying Runge-Kutta method and shooting technique.

COVID-19 has created anxiety not only in individuals but also in health organizations, and countries worldwide. Not a single industry is left un-influenced and loss is being estimated in billions of dollars. The widespread of this pandemic disease has challenged researchers all over the world. Some of the researchers are working to invent its cure while, others are applying computing technologies to stop its spread, by analyzing and identifying patterns for prediction and forecasting. This is by no doubt the hottest area of research for the last 100 years. This survey has targeted the research published in computing sub-domains to combat the pandemic. The survey has clustered the scientific efforts into logical groups: surveillance, metrological effects, social media analytics, image processing and business and economy, analysis and modeling. It will serve as a leading source for the followings: researchers who want to identify what has been achieved in different computing sub-domains, those who need fresh authenticated datasets openly accessible for different research contexts and what are future directions in this area of research. The findings of analysis and modeling can be also useful for government agencies who want to set priorities and formulate policies.

Automated medical diagnosis is one of the important machine learning applications in the domain of healthcare. In this regard, most of the approaches primarily focus on optimizing the accuracy of classification models. In this research, we argue that unlike general-purpose classification problems, medical applications, such as chronic kidney disease (CKD) diagnosis, require special treatment. In the case of CKD, apart from model performance, other factors such as the cost of data acquisition may also be taken into account to enhance the applicability of the automated diagnosis system. In this research, we have proposed two techniques for cost-sensitive feature ranking. An ensemble of decision tree models is employed in both the techniques for computing the worth of a feature in the CKD dataset. An automatic threshold selection heuristic is also introduced which is based on the intersection of features’ worth and their accumulated cost. A set of experiments are conducted to evaluate the efficacy of the proposed techniques on both tree-based and non-tree based classification models. The proposed approaches are also evaluated against several comparative techniques. Furthermore, it is demonstrated that the proposed techniques select around 1/4^th of the original CKD features while reducing the cost by a factor of 7.42 of the original feature set. Based on the extensive experimentation it is concluded that the proposed techniques employing feature-cost interaction heuristic tend to select feature subsets that are both useful and cost-effective.

In this work, Further properties of bornological groups are studied to find the sufficient conditions to introduce a bornology on a group. In particular, we show that every left (right) translations in bornological groups are isomorphisms and therefore the bornological group's structures are homogeneous, and this property from the bornological group is not shared with bornological semigroups. Further, the boundedness of a bornological group can be deduced from its boundedness at the identity.

The aim of this articles is to investigate the entropy optimization in unsteady MHD flow Darcy-Forchheimer nanofluids towards a stretchable sheet. The surface we tend to think about is porous and stretchy under acceleration. Flow occurs due to the stretching of the surface. Four distinct types of aqueous nanostructures are taken in this examination where copper oxide ( ), copper ( ), titanium dioxide ( ) and aluminum oxide ( ) are the nanoparticles. Irreversibility analysis are discussed through second law of thermodynamics. The expression of energy is mathematically designed and discussed according to heat generation / absorption, dissipation, thermal radiation, and joule heating. The nonlinear PDE (partial differential conditions) is first changed to ODE (normal differential conditions) through appropriate similarity variables. Here we used the numerically embedded solution technique to develop a numerical result for the obtained nonlinear flow expression. Influence of various flow parameter velocity temperature distribution and entropy generation are discussed. Reduction occurs in velocity profile for larger porosity and magnetic parameters. An enhancement in entropy generation and temperature distribution is seen for Brinkman number. An opposite effect is noticed in velocity and temperature through solid volume friction.

Sugarcane is an important industrial crop of semitropical and tropical areas. Due to the importance of this crop it is cultivated on nearly 20 million hectares by more than 90 countries. This crop belongs to family Poaceae, a grass family which is economically vital tracheophyte family that has properties much like that of wheat, maize, rice and sorghum. The Poaceae family is globally vital for providing dietary macromolecules, carbohydrates, and different nutrients. The most important item of sugarcane for the consumption is sucrose that gets accumulated in the stalk internodes. Sucrose is taken out and refined by different mills which is used as a sweetener in human food industries and in the fermentation industry. Large production of alcohol is attained by Brazilian sugarcane industries.

COVID-19 emerged in Wuhan and is later declared as a pandemic by World Health Organization. Different-aged people have varying gender-wise immunity control properties that necessitates understanding COVID-19 impact on age and gender which does not exist, currently. In this paper, COVID-19 surveillance variables are extensively studied along with hospitalization, tests-performed, and recovery data. Dataset is curated from three sources; however, age and gender data belong to Belgium, particularly. Visualizations, frequencies, Pearson’s and polyserial correlation, student’s t-test, and Cramer’s V are used for enhanced analysis. Results show higher mortality rate in males and need of more ventilators to combat severe symptoms.

Abstract Background COVID-19 vaccination program among Adults in India is one of the highly successful vaccination drives globally. Indian children aged 15–18 years old became eligible for COVID-19 vaccination on 3rd January, 2022 followed by 12-14 years old children on 16th March, 2022. As parents are primary decision-makers for their children, we aimed to assess parents' perceptions and intentions regarding COVID-19 vaccination for children in India. Aim To assess parental perceptions and intention to get COVID-19 vaccination for their children (aged<18 years), Materials and Methods A cross-sectional anonymous web-based survey was designed. Healthcare workers of a tertiary care institute in Eastern U.P. having any children aged <18 years were the study population. They were recruited through snowball sampling and were sent the study questionnaire in Google form through email and WhatsApp. Cross-tabulation was performed by parents' intention to vaccinate their children against COVID-19 virus with socio-demographic characteristics and their risk perception toward COVID-19, trust in the healthcare system, and their history of vaccine hesitancy behavior routine childhood immunization. Bi-variate analysis was performed to find out the predictors of child vaccination intention among the parents. Results A total of 388 healthcare workers parents (HCWPs) having A child < 18 years of age completed the survey. Mean age of the parents were 40.28 ±11.34 years with majority(97.0%) completing recommended 2 doses of COVIID-19 vaccine. Around 91% of the parents agreed that COVID-19 vaccines are important for child’s health whereas about 89% agreed to the statement that COVID-19 vaccines are effective. A total 356 (91.7%) participants were willing to vaccinate their child against COVID-19, 91.3% of them liked to do so as soon as possible. The factors significantly associated with the stated likelihood of child vaccination among the participants were younger age, female gender, urban residence, absence of any chronic illness, lower monthly income, history of COVID-19 in child and the child/children completed with routine childhood vaccines. Parental concerns mainly centered around vaccine need, safety and side effects. Conclusion The healthcare worker parents(HCWPs) have good knowledge and positive attitude towards COVID-19 vaccination for children. Around 92% of them were willing to vaccinate their children with COVID vaccine currently, which implies very low vaccine hesitancy among the HCWPs . Further longitudinal studies are required to be conducted to assess the trend of parental acceptance of COVID vaccine.

Over the past few decades, aircraft Ground Handling Operations (GHO) have been investigated by numerous researchers. Some aspects of GHO have been more focused on than others due to their importance in the GH processes. For instance, GHO performance has been tackled from different perspectives while workers and vehicles allocation suffer from the lack of research in the area. This paper is a literary review of the research that has been conducted in different areas of GHO. It sheds light on GHO performance, resource allocation and scheduling, operations scheduling, vehicle routing, and workers and vehicles allocation.

Spectrometers have a wide range of applications ranging from optical to non-optical spectroscopy. The need for compact, portable, and user-friendly spectrometers has been the pivot of attention from small laboratories to the industrial scale. Here, the Czerny Turner configuration-based optical spectrometer simulation design is carried out using ZEMAX OpticStudio. A compact and low-cost optical spectrometer in the visible range has been developed by using diffraction grating as a dispersive element and USB-type WebCAM CCD (Charge-coupled device) as a detector instead of an expensive commercial diffraction grating and detector. Using National Instruments LabVIEW, data acquisition, processing, and displaying techniques are made possible. We have employed different virtual images in LabVIEW programs to collect the pixel-to-pixel information and wavelength-intensity information from the image captured using the WebCAM CCD. Finally, we have shown that the OpticStudio-based spectrometer and experimental measurements of the developed spectrometer are in good agreement.

Post-harvest handling and ripening techniques have an impact on peach quality and shelf life, which has a big impact on consumer satisfaction and market competitiveness. This review paper examines recent advancements in ripening techniques and post-harvest technologies with the goal of improving peach fruit quality and sustainability. The factors impacting fruit quality after harvest and the physiological changes that occur throughout peach ripening are fully explained. For maintaining peach freshness and reducing losses, novel handling methods like modified atmosphere packaging (MAP) and controlled atmosphere storage (CAS) have been investigated. The study explores the possibilities of nanotechnology applications and low-temperature storage for prolonging shelf life while maintaining texture, flavor, and aroma. Examining the effectiveness and waste reduction potential of automation and mechanization in post-harvest activities. The paper also discusses ethylene-based and non-ethylene-based ripening agents, as well as innovative techniques including gene editing and RNAi technology for controlled and delayed ripening. Analyses are done on how these technologies affect the sensory qualities and nutrient profiles of peaches. The study emphasizes the significance of sustainable practices in the peach industry by focusing on waste reduction, resource efficiency, and circular economy integration. Post-harvest technologies' potential environmental consequences have been taken into consideration and the paper encourages more study and cooperation to increase sustainability.

A low-cost medium power carbon dioxide (CO₂) laser system is designed, constructed, and characterized to produce coherent, monochromatic laser radiation in the Infrared region. The laser cavity is simulated and designed by using ZEMAX optic studio. A switch-mode high tension pump source is designed and constructed using a flyback transformer and simulated using NI Multisim to study the voltage behavior at different node points. A prototype cooling system/chiller is designed and built using the Thermo-Electric Coolers (TEC) to remove the excess heat produced during laser action. Various parameters, like pumping mechanism, chiller stability, efficiency, output power, and current at different applied voltages, are studied. The chiller efficiency at different output powers of the laser is analyzed, which clearly shows that the chiller's cooling rate is good enough to compensate for the heat generated by the laser system. The center wavelength of the carbon dioxide laser is 10.6μm with FWHM of 1.2nm simulated in the ZEMAX optic studio. The output beam penetration through salt rock (NaCl), wood, and acrylic sheet at various output powers is analyzed to measure the penetration depth rate of the CO₂ laser.

We investigate the exact travelling wave solutions of the Tzitzéica-Dodd–Bullough–Mikhailov (TDBM) and Tzitzéica-type (TT) equations, appear in nonlinear optics, using simple ansatz approach. We use the Painlevé and traveling wave transformations to convert the mentioned nonlinear equations into nonlinear ordinary differential equations. Then, the simple ansatz approach has been employed to procure wave solutions, in terms of bright, singular soliton and trigonometric functions, for the Tzitzéica-Dodd–Bullough–Mikhailov (TDBM) and Tzitzéica-type (TT) equations. The study shows that the simple ansatz approach is straightforward and easy to implement for solving nonlinear problems.

As the time passes the modification in technology world lead to the evaluation in mobile application as well. With evaluation in mobile industry it is an open challenge for software quality researcher that how to enhance software quality to meet the needs of changes? Quality assurance play a key role in differentiating good application from bed application. With the continuous evaluation of mobile application developing process should be quick and efficient to comply with user requirements and satisfaction. While the listed requirement leads to bad design choices known as antipatterns, which in turn affect the reliability of the code. A tool based method PAPRIKA is used in the proposed re-search to identify and monitor these antipatterns together with a two-step assessment model for software quality assurance and object oriented software quality matrix.

Social media has become part and parcel of the world of today. These days, it’s still the most talked about thing. It cannot be overlooked because it plays a key role in our business functions such as marketing and advertising. Social Media is all about collaboration on files, ideas and projects that help users and stakeholders to successfully complete the project. It influences how people communicate, develop relationship, build trust, increase transparency and provide cultural context. The fundamental aim of this research is to investigate the capacity for project management in social media. This paper explains how social media is used for project management knowledge areas and process groups. Also this research aims to identify SM tools that can be suitable for project management processes. Two studies Delphi Study of three rounds and structured case study interview are used to investigate the impact on the performance of the project team and process robustness. These studies support social media use by accessing the contribution to relationship building, trusts, coordination and cohesion.

Bacillus Calmette-Guérin (BCG) vaccine is the only licensed vaccine against tuberculosis (TB) in humans and animals. It is most commonly administered parenterally but oral delivery is highly advantageous for immunisation of cattle and wildlife hosts of TB in particular. Since BCG is susceptible to inactivation in the gut, vaccine formulations were prepared from suspensions of Eudragit L100 copolymer powder and BCG in PBS, containing Tween 80, with and without the addition of mannitol or trehalose. Samples were frozen at -20oC, freeze-dried and the lyophilised powders were compressed to produce BCG-Eudragit matrices. Production of the dried powders resulted in a reduction in BCG viability. Substantial losses in viability occurred at the initial formulation stage and at the stage of powder compaction. Data indicated that the Eudragit matrix protected BCG against simulated gastric fluid (SGF). The matrices remained intact in SGF and dissolved completely in SIF within three hours. The inclusion of mannitol or trehalose in the matrix provided additional protection to BCG during freeze-drying. Control needs to be exercised over BCG aggregation, freeze-drying and powder compaction conditions to minimise physical damage of the bacterial cell wall and maximise the viability of oral BCG vaccines prepared by dry powder compaction.

The extended finite element method (XFEM) is now widely used in crack simulations and the direction of propagation of the XFEM crack in SS-304 has been quite interesting. This paper discusses the direction,θ(+ve in anti-clockwise direction), of the XFEM crack (under mode-I) propagation based on the von Mises stress-field around the crack-tip for static loading under the light water reactors (LWRs) conditions. The Mises core region from the crack-tip is chosen for β=〖90〗^o, the angle between the load and the initial crack. Experimental data for LWRs’environment is obtained and the simulations have been carried out applying three different static loads and results for the direction of the crack are calculated by measuring the stress-field around the crack-tip. It has been found that the direction of the XFEM varies inversely as the stress-field around the crack tip is increased. The computational results have been compared with the numerical results based on the minimum strain energy density criterion[S-criterion].

Symptoms attributed to the gastrointestinal manifestations of multi-system disorders play an important role in the long-term management of these conditions. Gastrointestinal complications of a variety of connective tissue disorders have been studied and there is an increased interest in the incidence and prevalence of these symptoms. Descriptions of the occurrence of gastrointestinal complications in Marfan syndrome have appeared infrequently in the medical literature. In this review article we focus on both structural and functional gastrointestinal pathology that may occur in patients with Marfan syndrome.

N-Acyl-homoserine lactones, the Quorum sensing signaling molecules predominantly found in gram-negative bacteria, which regulate several bacterial genes including virulence and antibiotic resistant genes. The study was aimed to identify and characterize QS and QQ bacteria from different samples. 5 samples with different ecological background were collected from soil and 10 samples from hospital setup. 31 different bacteria were isolated with either QS or QQ activities all together. CV026 and A136 biosensor strains were used for the detection of QS and QQ positive strains. QS activity was observed by cross streaking test of bacteria against CV026, it was affirmed that 13 isolates from the soil and 5 from hospital equipment’s showed positive QS activity. QQ activity of each isolate was tested by well diffusion assay, C6-HSL and C12-HSL were our candidate AHL molecules. The AHL molecule degradation was detected in 4 isolates of soil and none from the samples obtained from hospital setup. The total of 6 strongly positive QS and QQ isolates were identified and selected for 16S rRNA gene sequencing. The phylogenetic analysis revealed that these isolates were closely related to Pseudomonas, Bacillus and Exiguobacterium genera. In contrast, 1 Gram positive bacterial isolate was also purified with QS potential.

A nuclear reactor leak is undesirable and unpredictable occurrence in the plant of nuclear energy generation. For this reason, an accurate equipment is needed to inspect and supervise reactors. There are two kind of reactors for research and industry reactors, both of them are needed to inspect. Concern to inspection, regularly check is needed to ensure reactor conditions are always safe to operate. For that reason, an application of advanced technology for detecting leaks is priority. In this research, we are using underwater robot to be implemented. Using the robot is able to detect periodically, continuously with accurate reports to the operator or reactor supervisor. Furthermore, Underwater Robot namely Robaru, with 4 propellers equipped at the robot, Robaru can move on 3 axes x, y and z and rotate. The use of cameras, as well as temperature measurements to obtain data when conducting inspections of the reactor. The survey method used is direct observation to detect leaks. The robot is at a certain distance by following a predetermined connection or path. The robot has successfully performed a good check with an accurate level of positioning accuracy.

It is important to add second- or third-phase materials to improve the physical, mechanical, and biodegradable properties of polypropylene (PP) nanocomposites. A unique hybrid bio-nanocomposite was fabricated using microparticle cellulose powder from wastepaper with a polypropylene (PP) polymeric matrix using a low-shear chaotic mixing method. A small amount (2-5%) of layered micro clay was also added to investigate the hybrid effect of nanocomposite fabrication on the mechanical properties. A low-shear chaotic melt mixing method induces the formation of nano cellulose structures and layered clay nanoparticles by via exfoliation. The nanoparticles were characterized using Fourier transform infrared (FTIR) spectroscopy. Mechanical properties such as the flexural strength (FS) and tensile strength (TS) were investigated using an Izod impact tester (IZ), and a dynamic mechanical testing analyzer (DMTA). Further, scanning electron microscopy (SEM) was used to observe the microstructure of the nanocomposite. In addition, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were conducted to investigate the crystallinity and degradation of the samples, respectively. The addition of wastepaper cellulose powder below 2.5 wt. % did not improve the mechanical properties, however, improvements were observed when more than 5wt.% wastepaper cellulose powder was added. With the addition of a small amount of nano-clay, the mechanical properties were significantly improved, and a synergistic effect could be noticed. The observed results were then compared with PP-clay nanocomposites used in automotive industries to replace cellulose nanocomposites. The application areas can also cover lead production in paper cups and vacuum foaming.

Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. This study investigated the molecular evaluation of a new mango cultivar ‘Azeem Chaunsa’ using a set of the most effective 50 hyper-variable polymorphic SSR markers. Highly specific DNA fingerprints were identified in the genome of this mango cultivar, ‘Azeem Chaunsa’ compared with three standard cultivars such as Sindhri, Samar Bahisht (S.B) Chaunsa and Sufaid Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. An agglomerative hierarchical clustering method was used to construct dendrogram based on the ‘Unweighted Pair- Group Method with Arithmetic Mean’ (UPGMA). The genetic similarity coefficients were recorded between the mangos cultivars ranged from 0.49 to 0.67. Cultivar identification (CID) evaluates association among standard cultivars and Azeem Chaunsa and further concludes significant variations. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future mango breeding programmes in the context of climate change.

The literature study delves into novel therapeutic strategies in transplantation medicine, highlighting unique approaches that could revolutionize current practices. It emphasizes novel patterns that have the potential to transform the current landscape. Commencing with a thorough examination of the historical environment, it traces crucial advances and changes in transplantation. The focus is on traditional techniques, emphasizing their limitations and challenges. An extensive examination of contemporary transplantation therapies offers valuable insights into the most recent progress in organ, cellular, and tissue transplantation. This analysis examines the immunological obstacles and outlines the current advancements and constraints. The exploration further navigates into novel models and concepts such as immunomodulation, developments in organ preservation techniques, gene editing, biomaterials, scaffold-based solutions, and the integration of precision medicine, artificial intelligence, and machine learning applications. Each section analyzes the potential for change and current progress in various areas, backed by relevant scientific sources up to 2023. The subsequent sections delve into innovative cellular therapies, biotechnological progress, current clinical trials, and case studies demonstrating effective applications. This examination delves into the ethical and regulatory considerations of innovative therapeutic procedures, emphasizing ethical implications, regulatory frameworks, and the importance of balancing innovation with patient welfare. The literature review concludes by offering a forward-looking perspective, emphasizing potential progress, anticipated challenges, and advocating for collaboration and interdisciplinary approaches to overcome limitations in the field of transplantation medicine.

In this paper, a voice coil motor (VCM) actuated fast tool servo (FTS) system is developed for diamond turning. To guide motions of the VCM actuator, a crossed double parallelogram flexure mechanism is selected featuring totally symmetric structure with high lateral stiffness. To facilitate the determination of the multi-physical parameters, analytical models of both electromagnetic and mechanical systems are developed. The designed FTS with balanced stroke and natural frequency is then verified through the finite element analysis. Finally, the prototype of the VCM actuated FTS is fabricated and experimentally demonstrated to have a stroke of ±59.02 μm and a first natural frequency of 253 Hz. By constructing a closed-loop control using PID controller with the internal-model based resonant controller, the error for tracking a harmonic trajectory with ±10 μm amplitude and 120 Hz frequency is obtained to be ±0.2 μm, demonstrating the capability of the FTS for high accuracy trajectory tracking.

With the every passing day, the demand for data traffic is increasing and this demand forces the research community not only to look for alternating spectrum for communication but also urges the radio frequency planners to use the existing spectrum smartly. Cell size is shrinking with the every upcoming communication generation which makes the base station placement planning complex and cumbersome. In order to make the next-generation cost-effective, it is important to design the network in such a way which utilizes minimum number of base stations while ensure coverage and quality of service. This paper aims at develop a new approach using hybrid metaheuristic and metamodel applied in multi-transmitter placement planning (MTPP) problem. We apply radial basis function (RBF) metamodel to assist particle swarm optimizer (PSO) in a constrained simulation-optimization (SO) of MTPP to mitigate the associated computational burden of optimization procedure. We evaluate the effectiveness and applicability of proposed algorithm in a case study by simulating MTPP model with two, three, four and five transmitters.

In the search of potent α-amylase inhibitors, we have synthesized seventeen derivatives of 2-mercaptobenzimidazole bearing sulfonamide (1-17) and evaluated for their α-amylase inhibitory potential. All compounds display a variable degree of α-amylase activity having IC50 values ranging between 0.90 ± 0.05 to 11.20 ± 0.30 µM when compared with the standard drug acarbose having IC50 value 1.70 ± 0.10 µM. Compound 1, 2, 11, 12 and 14 having IC50 values 1.40 ± 0.10, 1.30 ± 0.05, 0.90 ± 0.05, 1.60 ± 0.05 and 1.60 ± 0.10 µM respectively were found many folds better than the standard drug acarbose. The remaining analogs showed good inhibitory potentials. All the synthesized compounds were characterized by HREI-MS, 1H and 13C-NMR. Structure activity relationship (SAR) has been recognized for all newly synthesized analogs. Through molecular docking study, binding mode of active analogs with α-amylase enzyme was confirmed.

The present study investigates the decision-making process of investors on the Pakistan Stock Exchange with regard to portfolio construction, explicitly focusing on the incorporation of ESG concerns. The present study employed SmartPLS and structural equation modeling (SEM) to quantitatively assess data received from a sample of 393 out of 400 respondents. Based on the available data, investors participating in the Pakistan Stock Exchange are notably impacted by ESG aspects. The findings of this study hold significance for emerging economy firms, regulators, and investors, both in terms of theoretical and practical ramifications. The study's findings demonstrate a clear indication of investors' significant emphasis on ESG matters. Furthermore, it provides valuable insights for stakeholders who are involved in the ever-evolving realm of sustainable finance within developing countries

Heavy metals have adverse effects on microalgae growth and metabolism. Photosynthesis and lipid profile are quite sensitive to heavy metal toxicity. The impact of chromium (Cr) on growth and photosynthetic activity of Dictyosphaerium pulchellum and Micractinium pusillum exposed to different concentrations (0 – 500 μg L-1) was investigated for 11 days. The influence of Cr on cell density and cell number followed similar trends, indicating a possible correlation among these growth responses. A significant (p &lt; 0.05) increase in lipid content was observed with the increasing concentration of Cr however, growth was suppressed at higher concentrations exceeding 100 μg L-1. Addition of Cr in the cell culture medium showed a negative effect on quantum yield (Fv/Fm) and a photosynthetic inhibition of &gt; 65% was noted in both species at 500 μg L-1. However, the lipid gravimetric analysis presented inner cell lipid content up to 36% and 30% of dry weight biomass for D. pulchellum and M. pusillum, respectively. The effects of chromium on growth and lipid accumulation in both microalgae species was concentration and exposure time dependent. This shows that an appropriate concentration of chromium in culture medium could be beneficial for higher lipid accumulation in freshwater eukaryotic microalgae species.

Microgrids are becoming popular nowadays because they provide clean, efficient, and low-cost energy. To use the stored energy in times of emergency or peak loads, microgrids require bulk storage capacity. Since microgrids are the future of renewable energy, the energy storage technology employed should be optimized to generate electricity. Batteries play a variety of essential roles in daily life and are used at peak hours and during a time of emergency. There are different types of batteries i.e., lion batteries, lead-acid batteries, etc. Optimal battery sizing of microgrids is a challenging problem, that limits modern technologies such as electric vehicles, etc. It is important to know different battery features such as battery life, battery throughput, and battery autonomy to get optimal battery sizing for microgrids. Mixed-integer linear programming (MILP) is an established technique for the integration and optimization of different energy sources and parameters for optimal battery sizing. A new MILP based dataset is introduced in this work. Support vector machine (SVM) is the machine learning application used to estimate the optimum battery size. The impact of feature selection algorithms on the proposed machine learning-based model is evaluated. The performance of the six best-performing feature selection algorithms is analyzed. The experimental results show that the feature selection algorithms improve the performance of the proposed methodology. Ranker search shows the best performance with a Spearman’s rank-ordered correlation constant of 0.9756, linear correlation constant of 0.9452, Kendall correlation constant of 0.8488 and root mean squared error of 0.0525.

Compressive residual stresses in thin films can inhibit crack propagation under normal or sliding contact loading, with associated enhancement of the coating apparent toughness, load bearing capacity and wear resistance. This study investigates the influence of residual stress distributions on the thin film/substrate adhesion using a nanoindenter coupled with scanning electron microscope (SEM) investigations of indentation induced failure modes. Reactive and un-reactive magnetron sputtering with ion plating was used to coat a (100) silicon substrate with aluminum nitride (AlN) with and without an aluminum (Al) adhesion layer. The presence of an Al bond layer gives additional interfacial tensile stress because of the difference in thermal expansion coefficient. Additionally, a different magnitude of residual stresses in the AlN coating was achieved by changing the applied bias voltage onto the substrate. Wafer curvature method and incremental focused ion beam (FIB) milling, combined with high-resolution in situ scanning electron microscopy (SEM) imaging and full field strain analysis by digital image correlation (DIC), were used to measure the average and in-depth stress residual stress distribution in the produced coatings. The adhesion energy was then quantified by using a nanoindentation based model. Results demonstrate that the additional tensile residual stress in the aluminum adhesion layer decrease significantly the coating adhesion, even in presence of a higher compressive stress state in the AlN top-layer. Therefore, the coatings without Al-layer showed better adhesion because of a more homogeneous compressive residual stress in comparison with the coating having Al layer, even though both groups of coatings are produced under same bias voltage. Results are discussed, and some general suggestions are made on the correlation between coating/substrate property combination and the adhesion energy of multilayer stacks. The results suggested that Al bond-layer and inhomogeneous residual stresses affected the adhesion of AlN negatively to a substrate like silicon.

Human activity recognition (HAR) using wearable sensors is gaining popularity in the healthcare domain, enabling continuous monitoring and timely interventions. The conventional HAR systems are centralised and need data sharing with a server for processing and model training. However, this data sharing leads to various challenges, such as privacy concerns, increased communication and storage costs, inefficient computational algorithms, data scarcity due to unwillingness to share, and difficulty achieving high accuracy and personalised models simultaneously. To overcome these challenges, this paper introduces a privacy and energy-aware federated learning (FL) framework for model training without data sharing. The proposed scheme incorporates spiking neural networks (SNNs), which are particularly suited for resource-constrained devices due to their event-driven information processing. The key idea is to synergise the strengths of SNNs and long short-term memory (LSTM) to create a hybrid model for robust HAR. The proposed hybrid spiking LSTM (S-LSTM) model uses the LSTM as an input layer to capture temporal dependencies efficiently, followed by spiking layers that replace the typical activation using leaky integrate-and-fire neurons. We employ the combination of surrogate gradient learning and backpropagation through time (BPTT) to update the weights of SNN layers in a supervised manner. The performance of the proposed model is evaluated using two publicly available datasets for both indoor and outdoor scenarios. The results show that the proposed S-LSTM performs much better than spike convolutional neural networks (S-CNN) and simple CNN, achieving the accuracy of 97% and 87% for indoor and outdoor datasets, respectively. Personalisation, also known as fine-tuning the global model using local data, is crucial in HAR. It allows the model to adapt to individual behaviour and preferences, making predictions more accurate. The results also show that personalisation improves the performance of participants up to 9% on average. Additionally, analysis with 50% random client participation reduces communication costs by 50% with minimal impact on accuracy.

The research community has shown significant interest in the aqueous synthesis of nanomaterials due to its ability to eliminate the need for complex organic solvents. This synthesis approach aligns with the principles of green chemistry, attracting considerable attention. Aqueous solution technology in fabricating nanostructures has gained recognition for its potential to create ultrasensitive, low-energy, and ultrafast optoelectronic devices. This report focuses on synthesizing lead iodide (PbI2) nanoplates using a water-based solution technique and fabricating a planar photodetector. The photodetectors with a planar type of device structure (ITO/PbI2 NPs/Au) demonstrated a remarkable photosensitivity of 3.9×103 and a photoresponsivity of 0.51 mA/W at a wavelength of 405 nm. Notably, the asymmetrical output properties of ITO/PbI2 NPs/Au detector deliver additional evidence of the effective creation of a Schottky contact. Thus, the photodetector exhibited a photoresponse even at 0 V bias, leading to the realization of self-powered photodetectors. Additionally, the device exhibited a rapid photoresponse of 0.21/0.38 s (−5 V) in the visible range. This study has expanded the horizons for the aqueous-phase synthesis of nanoplate nanostructures, enabling the large-area fabrication of high-performance photodetectors.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged &gt;19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and &gt;12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

To mitigate the spread of the COVID-19 coronavirus, some countries have enforced more stringent non-pharmaceutical interventions in contrast to those widely adopted (for e.g. the state of Kuwait). In addition to standard practices such as enforcing curfews, social distancing, and closure of non-essential service industries, other non-conventional policies such as the total confinement of highly populated areas has also been implemented. In this paper, we model the movement of a host population using a mechanistic approach based on random walks, which are either diffusive or super-diffusive. Infections are realised through a contact process, whereby a susceptible host may be infected if in close spatial proximity of the infectious host. Our focus is only on the short-time scale prior to the infectious period, so that no further transmission is assumed. We find that the level of infection depends heavily on the population dynamics, and increases in the case of slow population diffusion, but remains stable for a high or super-diffusive population. Also, we find that the confinement of homogeneous or overcrowded sub-populations has minimal impact in the short term. Finally, we discuss the possible implications of our findings for total confinement in the context of the current situation in Kuwait.

It is important to add second- or third-phase materials to improve the physical, mechanical, and biodegradable properties of polypropylene (PP) nanocomposites. A unique hybrid bio-nanocomposite was fabricated using microparticle cellulose powder from wastepaper with a polypropylene (PP) polymeric matrix using a low-shear chaotic mixing method. A small amount (2-5%) of layered micro clay was also added to investigate the hybrid effect of nanocomposite fabrication on the mechanical properties. A low-shear chaotic melt mixing method induces the formation of nano cellulose structures and layered clay nanoparticles by via exfoliation. The nanoparticles were characterized using Fourier transform infrared (FTIR) spectroscopy. Mechanical properties such as the flexural strength (FS) and tensile strength (TS) were investigated using an Izod impact tester (IZ), and a dynamic mechanical testing analyzer (DMTA). Further, scanning electron microscopy (SEM) was used to observe the microstructure of the nanocomposite. In addition, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were conducted to investigate the crystallinity and degradation of the samples, respectively. The addition of wastepaper cellulose powder below 2.5 wt. % did not improve the mechanical properties, however, improvements were observed when more than 5wt.% wastepaper cellulose powder was added. With the addition of a small amount of nano-clay, the mechanical properties were significantly improved, and a synergistic effect could be noticed. The observed results were then compared with PP-clay nanocomposites used in automotive industries to replace cellulose nanocomposites. The application areas can also cover lead production in paper cups and vacuum foaming.

This paper is concerned with bump-less transfer of parametrized disturbance observer based controller (DOBC) with Individual Pitch Control (IPC) strategy for full load operation of wind turbine. Aerodynamic cyclic loads are reduced by tuning multivariable DOBC with the objective to reduce output power fluctuation, tower oscillation and drive-train torsion. Furthermore tower shadow and wind shear effect are also mitigated using parametrized controller. A scheduling mechanism between two DOBC is developed and tested on Fatigue, Aerodynamics, Structures, and Turbulence ( FAST) code model of National Renewable Energy Laboratory (NREL)’s 5 MW wind turbine. The closed-loop system performance is assessed by comparing the simulation results of proposed controller with a fixed gain and Linear Parameter Varying (LPV) DOBC with Collective Pitch Control (CPC) for full load operation. It is tested with step changing wind to see the behavior of the system under step change with wind shear and tower shadow (cyclic load) effects. Also turbulent wind is applied to see the smooth transition of the controllers. It can be concluded from the results that the proposed parametrized control DOBC with IPC shows smooth transition from one controller to another by interpolation. Moreover fatigue of the gear and tower due to wind shear and tower shadow effects are reduced considerably by the proposed controller as compared to collective pitch control.

Punica granatum (PG) or Pomegranate is a bush, having many trunks and often get taller 1.8 to 4.7m long and their leaves are shiny and fleshy, approximately 7 to 8cm in length. Traditionally, it is used in diarrhea and dysentery due to its strong constricting property. Punica Granatum covering used in dysentery, diarrhea, piles, bronchitis. It is also used to minimize the risk of heart disease. The peel extract of Punica Granatum contain methanol and their dried peels has antidiarrheal venture, also help in wound healing activity. Peels of the pomegranate also holds around 60% of the fruit and they contain different types of ingredients including ellagitannins and proanthocyanidin compounds and minerals such as calcium, phosphorus, magnesium, potassium, flavonoids and sodium. Some animals were found in different local areas with both acute and chronic diarrhea. The condition of these animals were quite miserable because of dehydration and loss of electrolytes in the body cells of the animals. They were unable to move due to seriousness of the disease. 8 grams of PG Peel Powder mixed with 1 liter of water, 2 g of PG Peel Powder mixed with 250 ml water and 8 g of PG Peel Powder mixed with 1 liter of water were administrated orally by using sterilized bottles to the selected three cases. 3 days after the administration of different doses, all cases of diarrheal animals show a significant recovery. The condition of the animals seem to be healthier. Before administration of the pomegranate peel powder extract, all three cases had weak body structure due to diarrhea. Watery stool that may be yellow in color and mucus was also evident in the stool, due to this reason the patient calf was weak and depressed. In sometimes they also show unconsciousness and blood glucose levels seem to be reduced from the normal level.

The metabolic syndrome, first introduced by Hermann Haller in 1975, was sometimes also known as insulin resistance syndrome, syndrome X, and plurimetabolic syndrome. In 1989 it was rechristened by Kaplan as "Deadly Quartet" based on a consolidation of central obesity, impaired glucose tolerance, dyslipidemia, and systemic hypertension. Metabolic syndrome is positively associated with a pro-inflammatory and pro-thrombotic state, attributed to increased pro-thrombotic and inflammatory markers activity. Moreover, Metabolic syndrome is frequently associated with increased atherosclerotic cardiovascular disease, impaired glucose tolerance, hyperuricemia, obstructive sleep apnea, and chronic kidney disease. Despite concerted endeavors worldwide, the complexity of the pathophysiology of metabolic syndrome is still not clearly understood. Currently, therapeutic possibilities are confined to individual therapy of hyperglycemia, hypertension, hypertriglyceridemia, hyperuricemia, regular physical exercise, and a restricted diet.

Different materials prepared by appropriate synthesis methods and applying different post syn-thesis processes could be used as hole transport layer in perovskite solar cells. In the present work annealing was employed to enhance physical properties of copper oxide (CuO) thin films fabricated via spin coating technique and the effects of annealing on their optical, morphological, electrical and structural properties were investigated. The XRD findings revealed the polycrystalline structure with large crystallite size. Optical spectra showed larger transmission beyond the visible region, reduced absorption, and a decrease in bandgap energy from 1.93 eV to 1.81 eV. The Ag phonon modes at 299.22 and 304 cm-1 shown by the Raman shift confirmed the development of the CuO pure phase. FTIR spectra showed the Cu-O stretching band at 759, 764 and 446 cm−1. SEM revealed the agglomeration of nano crystallites with large grains on the surface. The carrier type conductivity of annealed CuO thin films was determined via two-point hot probe technique. Low resistivity values were determined via four-point probe method. These findings indicate that CuO thin films may be successfully used as a companion with an n-type layer in p-n junction solar cells, and a hole transport layer in perovskite solar cells.

We examine the profitability of the momentum and contrarian strategies in three South Asian markets i.e. Bangladesh, India and Pakistan. We also analyze, whether credit risk influences momentum and contrarian return for these markets from 2008 to 2014. We use Distance-to-default (DD) of Kealhofer, McQuown and Vasicek (KMV) model as a measure of credit risk. We calculate the credit risk and form the momentum and contrarian strategies of the firms on the basis of high, medium and low risk. We find that in all three markets, the momentum and contrarian returns are significant for medium and high credit risk portfolios and no momentum and contrarian returns for low credit risk portfolios.

Composting is one of the most economical and environmentally safe methods of recycling organic waste. Soil microorganisms play a significant role in decomposition and the availability of plant nutrients. This study was designed to prepare a suitable microbial inoculum and its evaluation on composting heap to decrease the time of waste degradation. The bacteria were isolated and molecular characterized from the soil near composting area by using 16S ribotyping technique. The identified strains of bacillus cereus used as an inoculum gives better results to expedite the degradation of organic waste. The prepared bacterial inoculum with molasses was also compared with commercial inoculum by optimizing physical and chemical parameters (temperature, oxygen, C: N, pH, and moisture content) of composting heap. Monthly reading of these parameters was taken from experimental and control treatments. The highest decomposition rate of organic waste was recorded in treatment A (experimental heap) where molasses and bacterial inoculum were added and less decomposition was observed in treatment D (experimental heap) where no inoculum and molasses were added. It was concluded from the studies that the prepared bacterial inoculum with two strains of Bacillus was effective and prepared mature compost in 2.5 months by increasing decomposition efficiency of organic waste. Furthermore, the prepared compost was also sustainable in its physical and chemical characteristic.

Unmanned Aerial Vehicles (UAV) are increasingly being used in a variety of domains and precision agriculture is no exception. Precision agriculture is the future of agriculture and will play a key role in long-term sustainability of agricultural practices. This paper presents a survey of how image data collected using UAVs has been used in conjunction with ma-chine learning techniques to support precision agriculture. Numerous agricultural applications including classification of crop types and trees, crops detection, weed detection, cropland cover, and segmentation of farming fields are discussed. A variety of supervised, semi-supervised and unsupervised machine learning techniques for image-based preci-sion agriculture are compared. The survey showed that for traditional machine learning approaches, Random Forests performed better than Support Vector Machines (SVM) and K-Nearest Neighbor Algorithm (KNN) for crop/weed classification. And, while Convolutional Neural Networks (CNN) have been used extensively, the U-Net-based models out-performed conventional CNN models for classification and segmentation tasks. Among the Single Stage Detectors (SSD), YOLO series performed relatively well. Two-Stage Detectors like R-CNN, FPN, and Mask R-CNN generally tended to outperform SSDs. Vision Trans-formers (ViT) showed promising results amongst transformer-based models which did not generally perform better than CNNs. Finally, Generative Adversarial Networks (GANs) have been used to address the problem of smaller datasets and unbalanced data

Antibiotic resistance (ABR) is an emerging global threat to public health. Substantial evidence has indicated that community pharmacists (CPs) can play a critical role in managing the ever-increasing threat of antibiotic resistance. The study aimed to determine the knowledge, attitude, and practices of CPs (n=180) towards antibiotics and antibiotic resistance as well as to improve the rational use of antibiotics. Two phases of mixed methods (quantitative and qualitative) online study were conducted in Pakistan from August 2019 to March 2020 by using validated questionnaires and semi-structured interview data. Different statistical methods were used to tabulate the quantitative data whereas inductive thematic analysis was conducted to categorize themes from the qualitative data and draw conclusions. Approximately 64.4% were male (mean: 29-33 years old). Overall, CPs had good knowledge of and were familiar with superbugs and their roles in ABR (65.6%, Median=1, IQR=1) although they were poor in differentiating some antibiotic groups with their respective ABR patterns (31.1%, Median=1, IQR=1). Most CPs have a positive attitude towards antibiotics with most (90.0%) having identified ABR as a critical issue in public health (Median=1, IQR=0). Overall, CPs' practices towards antibiotics were reasonable where they tend to educate patients about the rational use of antibiotics (52.8%, Median=1, IQR=1). Two main themes (antibiotics and counseling of patients) were related to self-medication with while educational interventions are the sub-theme. ABR is multifactorial where the subthemes related to budget, time constraints incompetent staff, the absence of CPs, the lack of training, enforcement of laws and regulations are the need of the hour in Pakistan. Effective antibiotic stewardship programs, patient education, and awareness campaigns about antibiotics and ABR along with training of the CPs are important factors that have to be addressed in a timely manner.

Leukemia represents as one of the most common primary malignancies of the hematologic system in both children’s and adults and remains a largely incurable or relapse disease. The elucidation of disease subtypes based on mutational profiling, has not improved clinical outcomes. IDH1/2 are key enzymes of TCA cycle that produces α-ketoglutarate (αKG), however their mutated version, are well reported in various cancer types including leukemia, produces D-2 hydroxyglutarate (D-2HG), an oncometabolite. Recently, some studies have shown that wild type IDH1 is highly expressed in non-small cell lung carcinoma (NSCLC), primary glioblastomas (GBM) and several hematological malignancies and corelates with disease progression. In this work, we have showed treatment of wild type IDH1 leukemia cells with specific IDH1 inhibitor switched leukemic cells towards gly-colysis from oxidative phosphorylation (OXPHOS) phenotype. We also noticed reduction in αKG in treated cells possible suggesting inhibition of IDH1 enzymatic activity. Further, we found that IDH1 inhibition reduces the metabolites related to one carbon metabolism, essential to maintain global methylation in leukemic cells. Finally, we observed that metabolic alteration in IDH1 inhibitor treated leukemic cells promotes reactive oxygen species (ROS) formation along with loss of mito-chondrial membrane potential, leading towards apoptosis in leukemic cells. Overall, we showed that wild type IDH1 targeting in leukemic cells promote metabolic alterations that can be exploited for combination therapies for better outcome.

The Armillaria genus represents one of the most common causes of chronic root rot disease in woody plants. The disease damage prompt assessment is crucial for pest management. However, the disease detection current methods are limited at the field scale. Therefore, an alternative approach that can enhance or supplement traditional techniques is needed. In this study, we investigated the potential of hyperspectral methods to identify the changes between fungi-infected and uninfected plants of Vitis vinifera in early detecting the Armillaria disease. The hyperspectral imaging sensor Specim-IQ was used to acquire images of leaves of the Teroldego Rotaliano grapevine cultivar. We analysed three groups of plants: healthy, asymptomatic, and diseased. Highly significant differences were found in the Near infrared (NIR) spectral region with a decreasing pattern from healthy to diseased plants attributable to internal leaf structure changes. Asymptomatic plants emerged from the other groups due to a smaller reflectance in the red-edge spectrum (around 705nm). Hypothetically associated with the presence of secondary metabolites involved in plant defence strategy. Furthermore, significant differences were observed in the wavelengths close to 550 nm in diseased plants versus asymptomatic. We used linear discriminant analysis from a machine learning context to classify the leaves based on the most significant variables (vegetation indices and single bands), with resulting overall accuracies of 85% and 84% respectively in healthy vs. diseased and healthy vs. asymptomatic. To our knowledge, this study represents the first report on the possibility of using hyperspectral data for root rot disease diagnosis on woody plants. Although further validation studies are required, it appears that the spectral reflectance technique, possibly implemented on unmanned aerial vehicles (UAV), could be a promising tool for a cost-effective, non-destructive method of Armillaria disease early diagnosis and mapping in the field, contributing to a significant step forward in precision viticulture.

Sugarcane mosaic virus (SCMV) is a deleterious pathogen which causes widespread Sugarcane mosaic disease (SCMD) and is classified in the genus Potyvirus (Potyviridae), disseminated by the aphid vector. RNA interference (RNAi)-mediated antiviral innate immunity is a key biological process and antiviral defence system to interfere with viral genomes for controlling plant pathogens. The current study aims to analyze sugarcane (Saccharum officinarum L. and Saccharum spp.) locus-derived microRNAs (sof-miRNAs/ssp-miRNAs) with predicted potential for targeting the SCMV +ssRNA-encoded mRNAs, using ‘five algorithms’ approach. The ultimate goal in this research is to mobilize the in silico endogenous predicted sof-miRNAs/ssp-miRNAs to trigger RNAi catalytic pathway experimentally and generate sugarcane cultivars for evaluating potential antiviral resistance monitoring capability and capacity for SCMV. Experimentally validated mature sugarcane (S. officinarum, 2n = 8X = 80) and (S. spp., 2n = 100-120) sof-miRNAs/ssp-miRNAs (n = 28) were acquired for alignment with the SCMV genome. Of the 28 targeting mature locus-derived sof-miRNAs/ssp-miRNAs investigated, one sugarcane miRNA homolog, sof-miR159c, was concluded to localize potential binding site at genomic nucleotide site 3847 targeting CI ORF of SCMV. In order to validate target prediction accuracy, whether the sugarcane sof-miRNA/ssp-miRNA might bind predicted SCMV mRNA target(s), we created an integrated Circos plot. Genome-wide in-silico-predicted miRNA-mediated target gene regulatory network validated interactions that warrant in vivo analysis. The current work provides valuable evidence and biological material for generating SCMV-resistant sugarcane varieties.

Cesium lead iodide (CsPbI3) perovskite nanocrystals (NCs) are a promising material for red light-emitting diodes (LEDs) due to their excellent color-purity and high luminous efficiency. However, small-sized CsPbI3 colloidal NCs, such as nanocubes, used in LEDs suffer from confinement effects, negatively impacting their photoluminescence quantum yield (PLQY) and overall efficiency. Here, we introduced YCl3 into the CsPbI3 perovskite, which formed anisotropic, one-dimensional (1D) nanorods. This was achieved by taking advantage of the difference in bond energies between Cl− and I− ions, which caused YCl3 to promote the anisotropic growth of CsPbI3 NCs. The YCl3-based nanorods improved the PLQY and storage stability by passivating the defects reducing the nonradiative recombination rates. When the YCl3-substituted CsPbI3 nanorods are applied to the emissive layer in LEDs, we achieve an external quantum efficiency of ~3.16% which is 1.86-fold higher than the pristine CsPbI3 NCs (1.69%) based LED. Notably, the ratio of horizontal transition dipole moments (TDMs) in the anisotropic YCl3:CsPbI3 nanorods was determined to be 75%, which is higher than the isotropically oriented TDMs in CsPbI3 nanocrystals (67%). This increased TDM ratio led to higher light outcoupling efficiency in nanorods-based LEDs. Overall, the results suggest that YCl3-substituted CsPbI3 nanorods could be promising for achieving high-performance perovskite LEDs.

This article presents a dataset of tweets in the Urdu language. There are 1,140,824 tweets in the dataset, collected from Twitter for September and October 2020. This large-scale corpus of tweets is generated by performing pre-processing which includes removing columns containing user information, retweet’s count, followers information, duplicate tweets, removing unnecessary punctuation, links, symbols, and spaces, and finally extracting emojis if present in the tweet text. In the final dataset each tweet record contains columns for tweet id, text, and emoji extracted from the text with a sentiment score. Emojis are extracted to validate Machine Learning models used for the multilingual sentiment and behavior analysis. These are extracted using a Python script that searches for an emoji from the list of 751 most frequently used emojis. If an emoji is present in the text, a column with the emoji description and sentiment score is added.

Many applications in agriculture as well as other related fields including natural resources, environment, health, and sustainability, depend on recent and reliable cropland maps. Cropland extent and intensity plays a critical input variable for the study of crop production and food security around the world. However, generating such variables manually is difficult, expensive, and time consuming. In this work, we discuss a cost effective, fast, and simple machine learning based approach to provide reliable cropland mapping model using satellite imagery. The study includes four test regions namely; Iran, Mozambique, Sri-Lanka, and Sudan where Sentinel-2 satellite imagery were obtained with assigned NDVI scores. The solution presented in this paper discusses a complete pipeline including data collection, time series reconstruction , and cropland extent and crop intensity mapping using machine learning models. The approach proposed managed to achieve high accuracy results ranging between 0.92 to 0.98 across the four test regions at hand.

Rare ginsenoside compound K (CK), is an intestinal microbial metabolite with a low natural abundance that is primarily produced by physicochemical processing, side chain modification, or metabolic transformation in the gut. Moreover, CK exhibits potent biological activity compared to primary ginsenosides, which has raised concerns in the field of ginseng research and development as well as ginsenosides-related dietary supplements and natural products. Ginsenosides Rb1, Rb2, and Rc are generally used as a substrate to generate CK via several bio-conversion processes. Current research shows that CK has a wide range of pharmacological actions including boosting osteogenesis, lipid and glucose metabolism, lipid oxidation, insulin resistance, anti-inflammatory, and anti-apoptosis properties. Further research on the bioavailability and toxicology of CK can advance its medicinal application. The purpose of this review is to lay the groundwork for future clinical studies and the development of CK as a therapy for metabolic disorders. Furthermore, the toxicology and pharmacology of CK are investigated as well in this review. The findings indicate that CK primarily modulates signal-ing pathways associated with AMPK, SIRT1, PPARs, WNTs, and NF-kB. It also demonstrates a positive therapeutic effect of CK on nonalcoholic fatty liver disease, obesity, hyperlipidemia, diabetes, and its complications, as well as osteoporosis. Additionally, the analogues of CK showed more bioavailability, less toxicity, and more efficacy against disease states. Enhancing bioavailability and regulating hazardous variables are crucial for its use in clinical trials.

An increasing global aridification due to climate change has made the health monitoring of vegetation indispensable to maintaining the food supply chain. Cost-effective and smart irrigation systems are required not only to ensure the efficient distribution of water, but also to track the moisture of plant leaves, which is an important marker of the overall health of the plant. This paper presents a novel electromagnetic method to monitor the water content (WC) and characterization in plant leaves utilizing the absorption spectra of water molecules in the terahertz (THz) frequency for four consecutive days. We extracted the material properties of leaves of eight types of pot herbs from the scattering parameters, measured using a material characterization kit in the frequency range of 0.75 to 1.1 THz. From the computed permittivity, it is deduced that the leaf specimens increasingly become transparent to the THz waves as they dry out with the passage of days. Moreover, the loss in weight and thickness of leaves were observed due to the natural evaporation of leaf moisture cells and change occurred in the morphology of fresh and water-stressed leaves. It is also illustrated that loss observed in WC on day 1 was in the range of 5\% to 22\%, and increased from 83.12\% to 99.33\% on day 4. Furthermore, we observed an exponential decaying trend in the peaks of the real part of the permittivity from day 1 to 4, which was reminiscent of the trend observed in the weight of all leaves. Thus, results in paper demonstrated that timely detection of water stress in leaves can help to take proactive action in relation to plants health monitoring, and for precision agriculture applications, which is of high importance to improve the overall productivity.

Herein, we have fabricated graphitic carbon nitride (g-C3N4) nanosheets with embedded ZnCdS nanoparticles to form a type II heterojunction using a facile synthesis approach and used for photocatalytic H2 production. The morphologies, chemical structure and optical properties of the obtained g-C3N4‒ZnCdS samples were characterized by a battery of techniques such as, TEM, XRD, XPS and UV-Vis DRS. The as-synthesized g-C3N4‒ZnCdS, photocatalyst exhibits the highest hydrogen production rate of 108.9 μmol·g-1·h-1 compared to individual components (g-C3N4: 13.5 μmol·g-1·h-1, ZnCdS: 45.3 μmol·g-1·h-1). The improvement of its photocatalytic activity is mainly attributed to the heterojunction formation and resulting synergistic effect, which provide more channels for charge carrier migration and reduce the recombination of photogenerated electrons and holes. Meanwhile, the g-C3N4‒ZnCdS heterojunction catalyst also showed higher stability over a number of repeated cycles. Our work sheds insight of using g-C3N4 and metal sulfide combination to develop low-cost, efficient, visible-light active hydrogen production photocatalysts.

Gambogic acid, a common traditional Chinese medicine and widely distributed throughout South China, Vietnam, Cambodia, and Thailand. It is prenylated xanthone which is the significant bioactive compound of gamboge. Gambogic acid is known as a strong apoptotic inducer in cancer cells. It has been found as strong anticancer agent against various types of cancer cells lines such as breast cancer, pancreatic, and cervical cancer. It induces apoptosis, down regulates the anti-apoptotic proteins (survivin and BCL2,) and down regulates the activities of P-glycoprotein in drug sensitive human breast MCF-7 and drug-resistant MCF-7/ADR cells. Similarly, it also exerts alteration in P13K, AKT, p21, MMP-2 &-9, and phosphorylated-AKT expressions. The current review highlights the anticancer and chemo-preventive perspectives of gambogic acid and its mechanistic role against human and animal cancers.

In tracking-by-detection paradigm for multi-target tracking, target association is modeled as an optimization problem that is usually solved through network flow formulation. In this paper, we proposed combinatorial optimization formulation and used a bipartite graph matching for associating the targets in the consecutive frames. Usually, the target of interest is represented in a bounding box and track the whole box as a single entity. However, in the case of humans, the body goes through complex articulation and occlusion that severely deteriorate the tracking performance. To partially tackle the problem of occlusion, we argue that tracking the rigid body organ could lead to better tracking performance compared to the whole body tracking. Based on this assumption, we generated the target hypothesis of only the spatial locations of person’s heads in every frame. After the localization of head location, a constant velocity motion model is used for the temporal evolution of the targets in the visual scene. Qualitative results are evaluated on four challenging video surveillance dataset and promising results has been achieved.

Various methods of polymer surface tailoring have been studied to control the changes in wetting behavior. Polymers having precisely controlled wetting behavior in a specific environment are blessed with a wealth of opportunities and potential applications exploitable in biomaterial engineering. The controlled wetting behavior can be obtained by combining surface chemistry and morphology. Plasma assisted polymer surface modification technique have played a significant part to control surface chemistry and morphology. This review focuses on plasma polymerization and investigations regarding surface chemistry, surface wettability, coating kinetics, as well as coating stability. We begin with brief overview of plasma polymerization; these include growth mechanisms of plasma polymerization and influence of plasma parameters. Next, surface wettability and theoretical background structures and chemistry of superhydrophobic and superhydrophilic surfaces. In this review, overview of recent work on tunable wettability by tailoring surface chemistry and physical appearance (i.e. substrate texture) is also described. The formation of smart polymer coatings, which adjust their surface wettability by according to outside environment, including, pH, light, electric field and temperature. Finally, the applications of tunable wettability and pH responsiveness of polymer coatings in real life are addressed. This review should be of interest to plasma surface science communality specifically focused controlled wettability of smart polymer surfaces.

Laminitis is considered as an important underlying cause of lameness diseases, yet its specific pathogenesis remains unclear. Autophagy is an intracellular degradation mechanism that controls recycling of membrane-associated integrin and may aid in the progression of metabolic diseases. But the significance of autophagy for initiation and development of laminitis is unknown. The present study aimed to explore autophagy activity in the laminar tissue of dairy cows with oligofructose-induced laminitis. Twelve healthy non-pregnant Holstein cows were randomly divided to 2 groups of 6 cows each, entitled the control group and the oligofructose overload group (OF group), respectively. At 0 h, cows in OF group were gavaged with oligofructose (17 g/kg BW) dissolved in warm deionized water (20 mL/kg BW) through oral rumen tube, and dairy cows in control group were gavaged with the same volume of deionized water by the same method. At -72 h before perfusion as well as 0 h, 6 h, 12 h, 18 h, 24 h, 36 h, 48 h, 60 h, and 72 h after perfusion, clinical evaluations in both groups were monitored. After 72 h, laminar tissues of dairy cows in both groups were collected to examine genes and proteins. We found the significantly higher (P<0.05) levels of mRNA ATG5, ATG12, and Becilin1, but P62 and mTOR were extensively lower (P<0.01) in the laminar tissue of the OF group than the control group. Protein expression level of Becilin-1 was higher significantly (P<0.05), and the protein expression level of LC3II was lower significantly (P<0.05) in OF group than control group. However, the expression of P62 reduced (P>0.05) non-significantly in OF group than control group. The distribution of Beclin1 protein in laminar tissue increased (P<0.01) significantly, and distribution of P62 protein decreased (P<0.05) significantly in OF group than control group. In conclusion, laminar tissue damage occurred during the onset of laminitis, which promoted the occurrence of autophagy, and confirmed that autophagy was involved in the regulation and pathogenesis of laminitis in dairy cows.

Many assumptions exist about online learning and its impact on college students. Hitherto, the views of those meant to be the beneficiaries of this technology have been given little consideration despite the fact that students use cyberspace for academic work and beyond. This qualitative case-study report is based on research conducted by college students at a private university in the Eastern Province of Saudi Arabia. The aim was to examine the online learning experiences of their peers during the first wave of the coronavirus global pandemic, with a view to understand how prepared their university is for an academic genre located in cyberspace. The findings are based on the perspectives of 2,298 college students responding to a survey administered to the entire student population comprising around 9,000 individuals. They suggest that increasing opportunities for cyberlearning could have positive effects on students. Also provided is cautionary advice about the need to improve teaching pedagogies and combat academic dishonesty.

Modern organic synthesis is majorly focused on developing environmentally benign synthetic protocols by employing green chemistry principles. Accordingly, in our recent research work, we herein report the use of modified supramolecular host cyclodextrin as an effective solid based green catalyst for accessing structurally diverse and medicinally relevant pyrimidone architectures. The catalyst and the synthesized compounds 4 (a-r) were characterized using FT-IR, NMR and GC-Mass spectroscopy. Major highlights of the reported work include: atom economical process, extremely milder reaction conditions, operational simplicity, high isolated yields, and excellent catalyst turnover number. The molecular docking studies suggest that the compound 4n has the hydrogen bonding, hydrophobic and π-pair interactions with the active site of active sites of CXT M 15 receptor.

Diabetes is one of the fatal diseases that play a vital role in the growth of other diseases in the human body. Controlling and curing diabetes in its early stages is the most significant technique to avoid its effects of diabetes. However, lack of awareness and expensive clinical tests are the primary reasons to skip clinical diagnosis and take preventive methods in lower-income countries like Bangladesh, Pakistan, and India. From this perspective, the study aims to build an automated machine learning (ML) model, which will predict diabetes at an early stage using socio-demographic characteristics rather than clinical attributes. Because clinical features are not always known to all people from lower-income countries. To find the best fit supervised ML classifier of the model, we applied six classification algorithms and found that RF outperformed with an accuracy of 99.36%. In addition, the most significant risk factors were found based on the SHAP value by all the applied classifiers. The study reveals that polyuria, polydipsia, and delayed healing are the most significant risk factors for growing diabetes. The findings indicate that the proposed model is highly capable of predicting diabetes in the early stages.

The recent advancements in the field of communication have led data sharing to become an integral part of today's smart cities with the evolution of concepts such as the internet of vehicles (IoV) paradigm. As a part of IoV, Electric Vehicles (EVs) have recently gained momentum as authorities have started expanding their Low Emission Zones (LEZ) in an effort to build green cities with low carbon footprints. Energy is one of the key requirements of EVs not only to support the smooth and sustainable operation of EV itself but to also ensure connectivity between the vehicles and infrastructure with controlling devices like sensors and actuators installed within an EV. In this context, renewable energy sources (such as wind energy) dramatically play their parts in the automobile sector towards designing the energy harvesting electric vehicles (EH-EV) to pare the energy reliance on the national grid. In this article, a novel approach is presented to achieve electric generation due to vehicle mobility to support the communication primitives in electric vehicles which enables plenty of IoV use cases in the presence of surplus energy at hand. A small-scale wind turbine is designed to harness wind power for converting it into mechanical power. This power is then fed to the onboard DC generator to produce electrical energy. Furthermore, the acquired power is processed through a regulation circuitry to consequently achieve the desired power supply for the end load, i.e. the batteries installed. The suitable orientation for efficient power generation is proposed on ANSYS-based aerodynamics analysis. The voltages induced by DC generator at No-Load condition are 35V while at Full-Load 25V are generated at rated current of 6.9A, along with the generation of power at around 100W (at constant voltage) at the rated speed of 90 mph for nominal battery charging. Moreover, the acquired data can be monitored via an android application interface by using a Bluetooth module.

Potentilla nepalensis belongs to the Rosaceae family, and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in our earlier studies. However, the PCs affecting human genes and their roles in the body are not disclosed till now. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDS), and MMGBSA methodologies. SMILES format of PCs from the PubChem used as input to DIGEP-Pred, 764 identified as the inducing genes. Their enrichment studies have shown inducing genes gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analysing parameters done in Cytoscape v3.10 revealed three biomarkers, TP53 from MS, NR, and NS induced genes; HSPCB and Nf-kB1 from MR induced genes. From 40 PCs, two PCs 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6, and -8.0; three PCs 3a, (NR) 4a and 4c (NS) with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Biomarkers identified in this study, have a prominent role in numerous cancers. Thus, further investigations such as in-vivo and in-vitro should be done to find the molecular functions and interlaying mechanism of the identified biomarkers on numerous cancer cell lines in considering the PCs of P.nepalensis.

Delivering nucleic acid therapeutics across cell membranes is a significant challenge. Cell-penetrating peptides (CPPs) containing arginine (R), tryptophan (W), and histidine (H) show promise for siRNA delivery. To improve siRNA delivery and silencing a model STAT3 gene, we hypothesized that oleyl acylation to CPPs, specifically (WRH)n, would enhance STAT3 silencing efficiency in breast and ovarian cancer cells. Using Fmoc/tBu solid-phase peptide chemistry, we synthesized, purified, and characterized the oleyl-conjugated (WRH)n (n = 1-4) peptides. The peptide:siRNA complexes were non-cytotoxic at N/P 40 (~20 μM) against MDA-MB-231, MCF-7, SK-OV-3, and HEK-293 cells after 72 h incubation. All peptide:siRNA complexes showed serum stability at N/P ≥40. The synthesized conjugates, with a diameter of &lt;100 nm, formed nano complexes with siRNA and exhibited stable range of zeta potential values (13-18 mV at N/P 40). Confocal microscopy and flow cytometry analysis provided qualitative and quantitative evidence of successful cellular internalization of siRNA. Peptides oleyl-(WRH)3 and oleyl-(WRH)4 showed ~60% and ~75% cellular uptake of siRNA, respectively, in both MDA-MB-231 and SK-OV-3 cells. Western blot analysis of oleyl-(WRH)4 demonstrated effective silencing of the STAT-3 gene, with ~75% silencing in MDA-MB-231 cells and ~45% in SK-OV-3 cells.

Human displacement is on the rise globally, and the increase in the burden of tuberculosis (TB) is also attributed to migrations worldwide. A significant number of such displacement occur in regions with considerably higher areas of TB burden. Displacements may delay in TB diagnosis and treatment, which possibly will lead to TB transmission among healthy individuals. In this study, we assessed the association of existing determinants after a protracted internal displacement of people with the delay in TB diagnosis and treatment outcomes. A cross-sectional study was conducted on internally displaced TB patients registered at selected health facilities in three urban districts of Pakistan from March 2019 to February 2020. The univariate and multivariate logistic regression model was used to assess the delay in diagnosis and treatment outcomes. IDPs with delay in initiation of treatment beyond 30 days were at high possibility of unsuccessful TB treatment outcomes (adjusted odds ratio AOR,2.60; 95% CI 1.06-6.40). Analysis of factors that affect health seeker behavior and timely treatment showed a significant association (p<0.05) in-between age group 55-65 years (AOR, 2.66; 95% CI 1.00-7.07), female patients (AOR, 2.42; 95% CI 1.21-4.81), visited non-formal health provider (AOR, 8.81; 95% CI 3.99-19.46), self-medication (AOR, 2.72; 95 % CI 1.37-5.37), poor knowledge of TB (AOR, 11.39; 95% CI 3.31-39.1), and perceived stigma (AOR, 8.81; 95% CI 3.99-19.4). Prolong delay in treatment was associated with unfavorable treatment outcomes among IDPs, more specifically. As migrants and IDPs are more likely to experience an interruption in care due to overall exclusion from social and health care services. Therefore, it is imperative to understand the barriers in providing public health care services, particularly in preventing and treating TB.

In mice, mutations or targeted disruptions of the core circadian gene Bmal1 have been implicated in early onset of ocular pathologies, including premature/congenital cataract development. The aim of the present study was to analyze probands of consanguineous Pakistani cataract families to identify the novel pathogenic variants in the BMAL1 gene. We have studied 21 congenital cataract families. Ophthalmic examination was performed for the probands and available family members. Genomic DNA was isolated from peripheral blood. PCR and Sanger sequencing was performed for the entire coding region of the BMAL1 gene. Targeted Sanger sequencing of BMAL1 revealed a heterozygous variant c.41A>T; p.(Asp14Val) in one proband, but it did not co-segregate with the disease phenotype in the family. In addition, a nonsynonymous variant (rs2290037) was identified in five probands. Our study is the first one to analyze the role of BMAL1 gene mutations in humans for their association with congenital cataract. Although we were unable to find the variants associated with congenital cataract families from Pakistan, more studies from other populations will be informative to further prove the role of BMAL1 with the disease.

Administration of crude polysaccharides extract from natural product is a promising gut microbiota-targeted approach to preventing obesity and associated metabolic disorders. Dietary restrictions can change the type and number of gut bacteria, which is an important factor in delaying the onset and burden of diseases. This study aimed to investigate the effects of high-yield crude polysaccharides from Cordyceps militaris (CMP) on high-fat diet (HFD) mice model and the gut microbiota community assembly, and to identify whether selenium (Se) addition would improve CMP action mode during cultivation. We found that the CMP treatment ameliorated adipose and liver pathologic morphology and fat accumulation in obese mice, while, SeCMP intervention was not superior than CMP in body mass gain, but notably decreasing serum triglyceride level increased by HFD. The upregulated expression of gene Cyp7a1 in liver and protein UCP1 in brown adipose tissue (BAT) preliminary indicated that the effect might relate to bile acids (BAs) metabolism pathway and thermogenesis. In addition, CMP showed a drastic decrease in the gut microbes which positively correlated with dyslipidemia parameters. Our result reveals the potential of CMP to be used as functional food in the prevention of diet-induced adipose and liver steatosis, so does SeCMP has outstanding capacity of improving dyslipidemia.

The rise in precocious puberty cases can be attributed to a combination of genetic and environmental factors. Genetic factors play a significant role, with studies identifying genetic abnormalities in genes such as KISS1, KISS1R, MKRN3, DLK1, GABRA1, LIN28B, NPYR, TAC3, and TACR3, which are associated with central precocious puberty (CPP). Epigenetic factors like DNA methylation and histone modifications may mediate the relationship between genetic and environmental influences on CPP development. Environmental factors such as exposure to secondhand smoke, cesarean section, and BMI have also been linked to precocious puberty, particularly in girls, highlighting the multifactorial nature of this phenomenon. Understanding the interplay between these genetic and environmental factors is crucial in addressing the increasing prevalence of precocious puberty in children. The published literature in the past five years was systematically reviewed and summarized highlighting the interplay of genetic and environmental factors for the rise in the precocious puberty.

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.

Delineating chilling and forcing periods is one of the challenging topics in understanding how temperatures drive the timing of budburst and bloom in fruit tree species. Here, we investigated this question on olive trees, using flowering data collected over six years on 331 cultivars in the worldwide collection of Marrakech, Morocco. Using a Partial Least Squares approach on a long-term phenology (29 years) of ‘Picholine Marocaine’ cultivar, we showed that the relevance of delineating the chilling and forcing periods depends more on the variability of inter-annual temperatures than on the long-term datasets. In fact, chilling and forcing periods are similar between those delineated by using datasets of 29 years and those of only 6 years (2014–2019). We demonstrated that the variability of inter-annual temperatures is the main factor explaining this pattern. We then used the datasets of six years to assess the chill and heat requirements of 285 cultivars. We classified Mediterranean olive cultivars into four groups according to their chill requirements. Our results, using the Kriging interpolation method, indicated that flowering dates of most of these cultivars (92%) were governed by both chilling and forcing temperatures. Our investigations provided first insights to select adapted cultivars to global warming.

Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Total genomic DNA (gDNA) was generated using CTAB method from each cultivar. The most effective 50 hyper-variable SSR markers were selected. Highly specific DNA fingerprints were identified in the candidate line ‘Azeem Chaunsa’ compared with three standard cultivars using SSR-PCR. An agglomerative hierarchical clustering method was used to construct dendrogram based on the UPGMA clustering method. Cultivar identification diagram (CID) was constructed to evaluate association among standard cultivars and Azeem Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. The genetic similarity coefficients were recorded between the cultivars of mango ranged from 0.49 to 0.67. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future.

Abstract: The study aimed to investigate the antitumor efficacy of anti-LMP1 antibodies in EBV-positive nasopharyngeal and stomach cell lines and xenograft models. The study also exam-ined the NF-κB expression and cell cycle activation of NPC serum exosome-associated LMP1. An-ti-LMP1 antibody treatment before or during cell implantation prevented tumor growth in nude mice. A small dose of antibodies resulted in complete tumor regression for at least three months af-ter the tumors had grown in size. The consumption of antigen-antibody complexes by tumor cells limited tumor growth. In vitro experiments showed that anti-LMP1 antibodies killed EBV-positive NPC- or GC-derived epithelial cell lines and EBV-positive human B cell lines but not EBV-negative cell lines. Treatment with anti-LMP1 reduced NF-κB expression in cells. The animal model experi-ments showed anti-LMP1 inhibited and prevented NPC- or GC-derived tumor growth. The results suggest that LMP1 antibody immunotherapy could cure nasopharyngeal cancer, EBV-positive gastric carcinoma, and EBV-associated lymphomas. However, further validation of these findings is required through human clinical trials.

The build-up of greenhouse gases (GHGs) is causing warmness in the Earth’s atmosphere, resulting in climate change. The transport sector is one of the active members of GHG emissions and it is imperative to use sustainable transport sources to control climate change. The measure aims to encourage citizens to stop using their private vehicles as their choice of transport and instead opt for joint sustainable mobility during traveling. In this study, a quantitative research method was used and data were collected from a sample of 410 respondents through questionnaire. On the other hand, study also took a simulation-based (N=10000) sample size of private vehicle data. The data were analyzed using structural equation modelling. The results revealed that sustainable transportation, climate change technologies and electric rail vehicles reduce climate change in the ecoregions of China. We conclude that sustainable transportation policies could be formulated and implemented to reduce climate change. In response to the research results, it is recommended that, since climate change is a multi-level governance issue and the outdated pyramidal transport industry models must be shifted to a sustainable transportation system model.

We report photon-phonon atomic coherence (cascade- and nested-dressing) interaction from various phase transitions of Eu3+: BiPO4 crystal. Such atomic coherence spectral interaction evolves from out of phase fluorescence to in-phase spontaneous four-wave mixing (SFWM) by changing the time gate. The dressing dip switch and three dressing dips of SFWM result from strong photon-phonon destructive cross- and self-interaction for hexagonal phase, respectively. The more phonon dressing result in destructive interaction, while less phonon dressing result in constructive interaction of atomic coherences. The experimental measurements of photon-phonon interaction agree with theoretical simulations. Based on our results, we proposed a model for an optical transistor (as an amplifier and switch).

pH is considered one of the paramount factors in bodily functions, because most of the cellular tasks exclusively rely on precise pH values. The regulation of pH is a necessary feature of the intracellular atmosphere and can be established as a strong indicator to judge a physiological abnormality in most of the cases. In this context, the current techniques for pH sensing provide us with the futuristic insight to further design therapeutic and diagnostic tools. Thus, pH-sensing (electrochemically and optically) is rapidly evolving toward exciting new applications and expanding researchers’ interests in many chemical contexts, especially in biomedical applications. The adaptation of cutting-edge technology is subsequently producing the modest form of these biosensors as wearable devices, which are providing us the opportunity to target the real-time collection of vital parameters, including pH for improved healthcare systems. The motif of this review is to provide an insight of trending tech-based systems employed in real time or in-vivo pH responsive monitoring. Herein, we briefly go through the pH regulation in the human body to help the beginners and scientific community with quick background knowledge, recent advances in the field, and pH detection in cancerous environments. In the end, we summarize our review by providing an outlook; challenges that need to be addressed and prospective integration of various pH in vivo platforms with modern electronics that can open new avenues of cutting-edge techniques for disease diagnostics and prevention.

This study utilised an ensemble of pre-trained networks and digital mammograms to develop a supplementary diagnostic tool for radiologists. Digital mammograms and their associated information were collected from the department of radiology and pathology, Hospital Universiti Sains Malaysia. Thirteen pre-trained networks were selected and explored in this study. ResNet101V2 and ResNet152 had the highest mean PR-AUC, MobileNetV3Small and ResNet152 had the highest mean precision, ResNet101 had the highest mean F1 score, and ResNet152 and ResNet152V2 had the highest mean Youden J index. Subsequently, three ensemble models were developed using the top three pre-trained networks based on PR-AUC, precision, and F1 score. The final ensemble model had a mean precision, F1 score, and Youden J index of 0.82, 0.68, and 0.12, respectively. Additionally, the final model demonstrated a balanced performance across mammographic density. In conclusion, this study exhibited the good performance of the ensemble transfer learning on digital mammograms for the purpose of breast cancer risk estimation. This model can be utilised as a supplementary diagnostic tool for radiologists, thus, reducing their workloads.

Probiotics are namely yeast and bacteria which are regarded as dietary supplements and food. Many probiotics are being commonly used now, the most frequently used, lactic acid bacteria are called Lactobacillus and Bifidobacterium. Many of the diseases associated with GIT are related to microbiota found in GIT, an imbalance of which causes gastrointestinal diseases. Probiotics, in light of scientific literature, are thought to play an important role in relieving symptoms of many diseases associated with GIT, i.e. beneficially regulating the microbiota composition. In the present review, we aimed to highlight the main considerations for main probiotic formulations to date. This study reviews the role of different probiotic formulations introduced so far in treating GI diseases in cohort ageing ≤18 years. We searched PubMed and Clinicaltrials.gov without any restrictions. This study comprises the descriptive and comparative analysis between Single-organism and Composite probiotics. These GI diseases include NEC, FAP, AGE, Acute Diarrhea, Ulcerative Colitis and etc. The results have been categorized according to title and outcomes. The positive outcomes emphasize the drug’s effectiveness in improving health and the negative outcome elaborates on the adverse effects the drug may have shown. Conclusively, discussed practices will assist in reducing GI disorders and strengthening the gut. Further insight into the various gut microbes and microbiomes with specific demographic is recommended.

This study aimed to determine the feasibility of the development of an over-the-counter (OTC) screening model using machine learning for breast cancer screening in the Asian women population. Data were retrospectively collected from women who came to the Hospital Universiti Sains Malaysia, Malaysia. Five screening models were developed based on machine learning methods; random forest, artificial neural network (ANN), support vector machine (SVM), elastic-net logistic regression and extreme gradient boosting (XGBoost). Features used for the development of the screening models were limited to information from the patients’ registration form. The model performance was assessed across the dense and non-dense groups. SVM had the best sensitivity while elastic-net logistic regression had the best specificity. In terms of precision, both random forest elastic-net logistic regression had the best performance, while, in terms of PR-AUC, XGBoost had the best performance. Additionally, SVM had a more balanced performance in terms of sensitivity and specificity across the mammographic density groups. The three most important features were age at examination, weight and number of children. In conclusion, OTC models developed from machine learning methods can improve the prognostic process of breast cancer in Asian women.

Emotion detection from the text is an important and challenging problem in text analytics. The opinion-mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions. However, most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets, resulting in performance degradation. To overcome this issue, this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset. The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision, recall ad f-measure. Finally, a classifier with the best performance is recommended for the emotion classification.

Cultivated adlay or Job’s tear (Coix lacryma-jobi L.) is an important food crop having numerous therapeutic and nutraceutical health benefits. Our study aimed to determine nutrients, minerals, fatty acid composition, and functional groups of seven wild Adlay accessions (brown, black, yellow, grey, green, off-white, and purple) to find out their scope as cereal crops using simple, rapid, and modern analytical techniques. Results revealed variations among bulk densities, specific densities, percent empty spaces, and corresponding grain counts per 10g of sample are valuable characteristics in distinguishing the accessions. Contents of fat, protein, ash, and fibre were found to be comparable to cultivated Adlay. Brown adlay was measured with the highest protein, fat, and fibre contents, 15.82%, 4.76% and 2.37%, respectively. Phosphorus, potassium, calcium, and sodium ranged 0.3% - 2.2%, whereas boron, iron, copper, zinc, and manganese were in the range 1.6mg/kg - 20.8mg/kg. Wild adlay triglyceride composition constituted of polyunsaturated fatty acids as primary fraction followed by olein and palmitic acid as prominent fatty acids. Distinguishing functional groups expressed infra-red frequencies in narrow bands and fingerprint region of proteins associated with out-of-plane region evident structural differences among adlay accessions. Frequency of functional groups in seven accessions indicated black genotype promising for varietal development.

Qatar experienced five SARS-CoV-2 waves dominated sequentially by the original virus, Alpha, Beta, Omicron BA.1 and BA.2, and Omicron BA.4 and BA.5, in addition to a prolonged low-incidence phase dominated by the Delta variant. The two-dose primary series of BNT162b2 (Pfizer-BioNTech) COVID-19 vaccine against SARS-CoV-2 infection has been approved for use in 10µg formulations among children and adolescents aged 12-17 years as of May 16, 2021. This study aimed at estimating the effectiveness of the 30µg BNT162b2 Pfizer-BioNTech mRNA COVID-19 vaccine against the pre-Omicron variants of SARS-CoV-2 infection in children and adolescents aged 12-17 years residing in Qatar. A test-negative matched case-control study was conducted where any child or adolescent aged 12-17 years who had been tested for SARS-CoV-2, RT-PCR tests performed on nasopharyngeal or oropharyngeal swabs, as part of contact tracing, between June and November 2021 and eligible to receive the BNT162b2 vaccine as per the national guidelines. Data regarding 14,161 children/adolescents meeting inclusion-exclusion criteria were retrieved from the national Surveillance and Vaccine Electronic System (SAVES). Of the total, 3.1% (444) were positive for SARSCoV-2. More than half (55.96%) were vaccinated with two doses of Pfizer-BioNTech-mRNA COVID-19 vaccine. Amongst those immunized with two doses, 1.2% tested positive for SARS CoV2, while 5.6% amongst the unvaccinated tested positive. The vaccine effectiveness was calculated to be 79%. Pfizer-BioNTech mRNA COVID-19 vaccine provides protection from COVID-19 infection for children/adolescents, hence it is crucial to ensure they receive the recommended vaccines.