Around the world, there is no population clear from urinary tract infection (UTI), particularly among women. UTI is considered the most predominant bacterial infection. This study aimed to detect the incidence of the most common major uropathogens in patients severe from urinary tract infection with antibiotic sensitivity tests that assist urologist doctors for appropriate antimicrobial empirical therapy.Methods: This study was carried in a private laboratory in Babil city, Iraq from May 2019 to May 2020. Totally 70 individuals suffering from clear symptoms of UTI, as well as, 20 healthy persons participated in this study as a control group. Then, the standard microbiological methods carried out to isolate and identify bacterial species. Antimicrobial susceptibility tests were performed using different antimicrobial discs by applying the Kirby–Bauer disc diffusion method.Results: Totally, 90 specimens were obtained from them 20 control group, 19 with no growth, and 51 patients with bacterial growth distributed as 43 (83%) females and 8 (17%) males. E. coli were the most common predominant organisms. All isolates were showed a high rate of resistance to evaluated cephalosporins 100% and 82% to cefotaxime and ceftriaxone respectively, while very low resistance recorded in Aminoglycosides 20% and 13% to Gentamicin and amikacin respectively. Most age group infected with UTI was 21-40 years old.Conclusion: The current study showed an increasing burden of urinary tract infection caused by various bacteria implicated in UTI that causes changeable sensitivity to various antimicrobial agents. Therefore, in clinical use appropriate medications should be selected based on the data obtained from antimicrobial susceptibility tests.

This work investigated the effects of manufacturing variations including coil resistance, initial pod mass, and e-liquid color on coil lifetime and aerosol generation of Vuse ALTO pods. Random samples of pods were used until failure (where e-liquid was consumed, and coil resistance increased to high value indicating a coil break). Initial coil resistance, initial pod mass, and e-liquid net mass ranged between 0.89 to 1.14 [], 6.48 to 6.61 [g], and 1.88 to 2.00 [g] respectively. Coil lifetime with light color e-liquid was (mean) = 149, (standard deviation) = 10.7 puffs while pods with dark color e-liquid was = 185, = 22.7 puffs with a difference of ~36 puffs (p <0.001). Total mass of e-liquid consumed until coil failure was = 1.93, = 0.035 [g]. TPM yield per puff of all test pods for the first session (brand new pods) was = 0.0123, = 0.0003 [g]. During usage, TPM yield per puff of pods with light color e-liquid was relatively steady while it was continuously decreasing for pods with dark e-liquid. Coil lifetime and TPM yield per puff were not correlated with either variation in initial coil resistance or variation in initial pod mass. The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. There is a potential correlation of e-liquid color with both coil lifetime and TPM yield per puff. Change of e-liquid color might have been a result of oxidation which changed some nicotine into nicotyrine.

A E. Crassipes is considered a problem in different aquatic ecosystems, due to its abundance could become a solution to design and build economic and efficient treatment plants, and especially for the production of biofuels such as bioethanol. The objective of this research is to design and implement a sustainable development process between phytoremediation and bioethanol production with E. crassipes, evaluating the incidence of chromium adhered to the biomass of this plant in the production of bioethanol. Materials and methods: A system was installed to evaluate the phytoremediation with E crassipes with water loaded with chromium, determining the effectiveness of this plant to remove this heavy metal even if it is alive in a body of water. After this process, we proceeded to bring the biomass loaded with chromium to bioreactors to evaluate the production of bioethanol, assessing three types of biomass, one without chromium adhered and the other two with chromium adhered to its plant structure. There was an impact of the ethanol production of the E crassipes due to the presence of chromium, but this production can be taken into account for the assembly of an integral system of phytoremediation and bioethanol production, making the most of this biomass.

Clinical training in medical schools in Spain is performed by rotations in university hospitals. During these internships, students are expected to acquire and master basic procedural skills. However, the assessment tools available rarely check whether these skills are completely acquired by the students. We have used an e-portfolio to determine the optimal number of times the students need to repeat a procedure to be able to perform it independently. The results were compared with the actual performance during the internships. An e-portfolio collected qualitative information about the internships. Quantitative information was also requested about the number of times each clinical skill was performed. Later, a survey asked these students and their teachers the optimal number of times each skill should be repeated before it could be considered fully acquired. The questionnaire was answered by 98.6% of the students and 70.3% of their teachers. Out of the 21 clinical skills and procedures selected, both students and their tutors agreed in a similar optimal value in 16 of them; only in five of them, teachers thought that students needed a greater number of times than that selected by the students. When these optimal values were compared with the actual values recorded in the portfolio during the internships, it was found that about half of the clinical skills were carried out less frequently than expected, thus providing an important feedback about the internships. Quantitative information collected in portfolios reveals a moderate mismatch between students and tutors perceptions of their training needs.

DDX3 is an ATP-dependent RNA helicase involved in multiple cellular activities, including RNA metabolism and innate immunity. DDX3 is known to assist the replication of some viruses while restricting some others through direct interaction with the viral proteins. However, the role of DDX3 in the replication of the hepatitis E virus (HEV) is unknown. In this study, DDX3 is shown to interact with the HEV capsid protein and provide an indispensable role in HEV replication. The DDX3 C-terminal domain was demonstrated to interact with the capsid protein, which was previously demonstrated to inhibit the production of type I interferons. Knockdown of DDX3 compromised the capsid protein-mediated blockage of interferon induction. Notably, DDX3 silencing led to a significant reduction in HEV replication. Also, the ATPase activity of DDX3 is required for the HEV replication as an ATPase-null mutant DDX3 failed to rescue the viral replication in the DDX3-silenced cells. These results demonstrate a pro-viral role of DDX3 in HEV replication, providing further insights into the virus-cell interactions.

Immunosensors have been widely developed to use antibodies to detect a pathogen of interest; it is interesting to look at the effect of nonspecific antibody binding to E. coli using electrochemical methods. IgG antibody not specific to E. coli O157:H7 was crosslinked onto a screen-printed carbon electrode. The presence of E. coli at 4, 4 × 10², 4 × 10⁵, and 4 × 10⁸ CFU/mL on the electrode surface was detected via linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). Current transfer at both electrodes was reduced as the concentration of bacteria increased; however, the calibration of number of cells to decreased current was nonlinear for IgG-modified electrodes. The nonlinearity is confirmed by EIS measurements which showed highest impedance at 4 CFU/mL E. coli when impedance should be the lowest. FESEM images showed higher binding of cells when IgG is present compared to electrodes with reduced graphene oxide (rGO) alone. Electrodes with rGO alone show less attachment of E. coli, with EIS showing a linear calibration profile, while LSV shows not much difference in current values for all concentrations aside from the highest concentration. These results suggest that nonspecific binding can provide false signals in electrochemical measurements, and it is crucial to provide proper controls.

Specific nutrients including n-3 long chain polyunsaturated fatty acids (LCPUFAs), flavonoids, vitamin A, D and E are considered to possess protective properties on human health by impacting on immunological reactions. An ‘inflammation-suppressive’ effect appears to be the common denominator of the beneficial effects of most of these dietary components which may protect against the development of chronic immune disorders such as allergy. However, the majority of these promising data are from preclinical studies such as animal disease models, as the majority of clinical studies only indicate associations. PUFAs, especially n-3 LCPUFAs, have been shown to interact with both the sensitization as well as the effector phase in food allergy. However, it should be noted and realised that PUFAs are highly susceptible to lipid oxidation. Flavonoids and fat-soluble vitamins both contain anti-inflammatory properties and are able to act as anti-oxidants as well. Here, we explore the anti-allergic properties of PUFAs, flavonoids and fat-soluble vitamins in order to create an overview and, more importantly, suggest a strategy to target food allergies using these components and combinations thereof. Dietary n-3 LCPUFAs and the above mentioned micronutrients are promising anti‐allergy agents capable of influencing the allergic immune response through multiple and different biological pathways.

In this project, we use a statistical multiple regression to study the impact of eight various predictors (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area distribution) to estimate the cooling load energy efficiency of residential buildings. We try to analyze and visualize the effect of each predictor with each of the response variable using different classical statistical analysis tools used in describing linear models, in such a way so that we can find out the most strongly related predictor variables. Before starting all of this, we use the idea of model selection by stepwise regression technique and compare the AIC of these models and identified a better model between all of them. Then, we compare a classical linear regression approach by simulations on 768 diverse residential buildings show that we can predict CL with low mean absolute error. By using ANOVA we determine variation in the different residuals. Also, we use non constant variance test to verify it. Furthermore, we check leverage and influence points as well as outliers as well as determined cook distance for influential points. By taking box cox transformation and weights, we also introduce WLS technique to fit the model for better results and did all type of important analysis to understand the energy efficiency. Finally, we show 5-fold cross validation to verify our model.

Increased nutrient withdrawal by rapidly expanding intensive cropping systems, in combination with imbalanced fertilization, is leading to potassium (K) depletion from agricultural soils in Asia. There is an urgent need to better understand the soil K-supplying capacity and K-use efficiency of crops to address this issue. Maize is increasingly being grown in rice-based systems in South Asia, particularly in Bangladesh and North East India. The high nutrient extraction, especially K, however, causes concerns for the sustainability of maize production systems in the region. The present study was designed to estimate, through a plant-based method, the magnitude, and variation in K-supplying capacity of a range of soils from the maize-growing areas and the K-use efficiency of maize in Bangladesh. Eighteen diverse soils were collected from several upazillas (or sub-districts) under 11 agro-ecological zones to examine their K-supplying capacity from the soil reserves and from K fertilization (@ 100 mg K kg-1 soil) for successive seven maize crops grown up to V10-V12 in pots inside a net house. A validation field experiment was conducted with five levels of K (0, 40, 80, 120 and 160 kg ha-1) and two fertilizer recommendations based on “Nutrient Expert for Maize-NEM” and “Maize Crop Manager-MCM” decision support tools (DSSs) in 12 farmers’ fields in Rangpur, Rajshahi and Comilla districts in Bangladesh. Grain yield and yield attributes of maize responded significantly (P < 0.001) to K fertilizer, with grain yield increase from 18 to 79% over control in all locations. Total K uptake by plants not receiving K fertilizer, considered as potential K-supplying capacity of the soil in the pot experiment, followed the order: Modhukhali >Mithapukur >Rangpur Sadar >Dinajpur Sadar >Jhinaidah Sadar >Gangachara >Binerpota >Tarash >Gopalpur >Daudkandi >Paba >Modhupur >Nawabganj Sadar >Shibganj >Birganj >Godagari >Barura >Durgapur. Likewise in the validation field experiment, the K-supplying capacity of soils was 83.5, 60.5 and 57.2 kg ha-1 in Rangpur, Rajshahi, and Comilla, respectively. Further, the order of K-supplying capacity for three sites was similar to the results from pot study confirming the applicability of results to other soils and maize-growing areas in Bangladesh and similar soils and areas across South Asia. Based on the results from pot and field experiments, we conclude that the site-specific K management using the fertilizer DSSs can be the better and more efficient K management strategy for maize.

Electric moped scooter sharing services have recently experienced strong growth rates, particularly in Europe. Due to their compactness, environmental-friendliness and convenience, shared e-mopeds are suitable modes of transport in urban mobility to help reduce the environmental impact. However, its traffic-related, economic and environmental effects are merely represented in academic research. We used passenger car traffic data in Berlin generated by the multi-agent transport simulation framework MATSim to develop a python-based simulation, resembling an e-moped sharing system. Based on the results, a total cost of ownership and a life cycle assessment for fleet sizes of 2,500, 10,000 and 50,000 vehicles were conducted. The results indicate that a substantial part of all passenger car trips in Berlin can be substituted. The larger the fleet, the more and longer trips are replaced. Simultaneously, the efficiency in terms of fleet utilization decreases. The scenario with 10,000 e-mopeds offers the lowest total distance-based costs for sharing operators, whereas a fleet consisting of 2,500 vehicles exhibits the lowest environmental emissions per kilometer driven over the expected lifespan of a shared e-moped. Based on the renewable energy potential for 2050 forecasted by the German Federal Environment Agency, a significant overall decline in environmental impacts can be achieved.

Background and Objectives: The site types of Eucalyptus urophylla × Eucalyptus grandis clonal plantations in southern Yunnan were compared, aiming to provide basis for site selection and scientific plantations management. Materials and Methods: In this study, 80 standard plots were set up in the 6−9-year-old Eucalypts plantations in Pu'er City and Lincang City. Furthermore, the quantitative theory I model and canonical correlation analysis were used to analyze the relationship between dominant tree growth traits and site factors, and evaluate the growth potential of E. urophylla × E. grandis plantation. Results: The multiple correlation coefficient between 8 site factors (altitude, slope, slope level, soil thickness, slope direction, texture, soil bulk density, and litter thickness) and the quantitative growth of the dominant wood was 0.825 (P < 0.05). According to the correlation coefficient of the quantitative regression model, slope, altitude, and soil thickness were the main factors for the classification of E. urophylla × E. grandis plantations in southern Yunnan. In addition, E. urophylla × E. grandis plantations grew best downhill and mid uphill at relatively low altitude, where the soil layer was thick and composed of weathered red soil. Contrastingly, E. urophylla × E. grandis plantation growth was extremely poor in uphill sites at higher altitude, where the soil layer was thin and composed of semi-weathered purple soil. Furthermore, total N, and available B, Cu, and Zn content, as well as soil organic matter content in the soil had a great influence on the growth of E. urophylla × E. grandis. Conclusions: Nitrogen and phosphate fertilizer as well as trace elements such as B, Zn, and Cu can be properly applied in middle- and low-yield forests to promote the growth and development of E. urophylla × E. grandis plantations.

Data mining plays a critical role in the sustainable decision making. The k-prototypes algorithm is one of the best-known algorithm for clustering both numeric and categorical data. Despite this, however, clustering a large number of spatial object with mixed numeric and categorical attributes is still inefficient due to its high time complexity. In this paper, we propose an efficient grid-based k-prototypes algorithms, GK-prototypes, which achieves high performance for clustering spatial objects. The first proposed algorithm utilizes both maximum and minimum distance between cluster centers and a cell, which can remove unnecessary distance calculation. The second proposed algorithm as extensions of the first proposed algorithm utilizes spatial dependence that spatial data tend to be more similar as objects are closer. Each cell has a bitmap index which stores categorical values of all objects in the same cell for each attribute. This bitmap index can improve the performance in case that a categorical data is skewed. Our evaluation experiments showed that proposed algorithms can achieve better performance than the existing pruning technique in the k-prototypes algorithm.

The emergence of acute, severe non hepA–E hepatitis of unknown etiology (ASHUE) has attracted global concern owing to the very young age of the patients and its unknown etiology. Although this condition has been linked to several possible causes, including viral infection, drugs, and/or toxin exposure, the exact cause remains unknown; this makes treatment recommendations very difficult. In this review, we summarize recent updates on the clinical manifestations, complemented with laboratory results, case numbers with the global distribution and other epidemiological characteristics, and the possible etiologies. We also provide the proposed actions that could be undertaken to control and prevent further spread of this hepatitis. Since many etiological and pathological aspects of the acute non hepA–E hepatitis remain unclear, further research is needed to minimize the severe impact of this disease.

: E-commerce sales surge represents a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by COVID19 pandemic) and delivering in few predefined places might help coping with missed deliveries substantially. Furthermore, this option enables consolidated shipping and reducing delivery trip costs. This paper analyses and compares consumers’ preferences for alternative collection strategies. It investigates home delivery vs parcel locker use and forecasts their future market shares. This is performed based on both customers’ socio-economic variables and attributes characterising these alternative logistic fulfilment strategies. The case study considered rests upon a stated preference survey deployed in the city of Rome. The investigation specifically targets young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

The experience gained over the last hundred years clearly indicates that two groups of viruses represent the main risk for the development of highly transmissible epidemics and pandemics in the human species: influenza viruses and coronaviruses (CoV). Although the search for viruses with pandemic potential in the environment may have an important predictive and monitoring role, it is still based on empirical methodologies, mostly translated from the clinic and not fully validated for environmental matrices.As far as the SARS-CoV-2 pandemic, currently underway, is concerned, environmental monitoring activities aiming at checking the presence of SARS-CoV-2 in wastewater can be extremely useful to predict and control the diffusion of the disease. For this reason, the present study aims to evaluate the SARS-CoV-2 diffusion by means of a wastewater-based environmental monitoring developed in Piedmont, N-W Italy, during the pandemic second and third waves. Sampling strategies, sampling points, sample pre-treatments and analytical methods have been developed and validated to give representative and reliable results. The outcomes highlighted by the present paper demonstrate a strong correlation between SARS-CoV-2 concentration in untreated wastewater and epidemic evolution in the considered areas as well as a predictive potential that could provide decision-makers with indications for establishing effective policies to mitigate the effects of the ongoing pandemic and to prepare response plans for future pandemics that could certainly arise in the decades to come.Moreover, the study highlights the potential of wastewater treatment plants to degrade the genetic material referable to SARS-CoV-2 as well.In conclusion, the preliminary data reported in the present paper, although they need to be complemented by further studies considering other geographical regions as well, are very promising.

With the diversified development of media forms, livestreaming e-commerce has become a new sales model. Unlike the traditional sales model, this paper constructs a three-party game model composed of manufacturers, social media influencers and consumers based on the livestreaming model. It explores the equilibrium strategy selections of each participant in the supply chain system. In analyzing the evolutionary game stability of each participant, this paper obtains the equilibrium strategy and stability factors by analysis of the income and expenditure matrix. It uses the simulation model to analyze reasons for strategy selections of different game participants in the livestreaming e-commerce model. The results show that the strategies of manufacturers, social media influencers and consumers' selections have different impacts on their decision-making mechanism, and man-ufacturers are more sensitive to consumers' active participation in livestreaming e-commerce.

Animal behavior analysis is a crucial tasks for the industrial farming. In an indoor farm setting, extracting Key joints of animal is essential for tracking the animal for longer period of time. In this paper, we proposed a deep network that exploit transfer learning to trained the network for the pig skeleton extraction in an end to end fashion. The backbone of the architecture is based on hourglass stacked dense-net. In order to train the network, key frames are selected from the test data using K-mean sampler. In total, 9 Keypoints are annotated that gives a brief detailed behavior analysis in the farm setting. Extensive experiments are conducted and the quantitative results show that the network has the potential of increasing the tracking performance by a substantial margin.

Several studies have quantified the responses of Eucalyptus globulus plantations to weed control on its early development (2-3 years after establishment). However, long-term results of competing vegetation effects have been rarely incorporated into growth and yield models that forecast the long-term effects of reducing the intensity of competing vegetation control and its interaction with site resource availability on stem volume production close to rotation age. We compared several models predicting stand stem volume yield of Eucalyptus globulus plantations established across a water and fertility gradient growing under different intensity levels of free area of competing vegetation maintained during the first 3 years of stand development. Four sites were selected encompassing a gradient in rainfall and amount of competing vegetation. Treatments were applied at stand establishment and were monitored periodically until age 9 years. Competing vegetation control intensity levels considered 0, 5, 20, 44 and 100% weed-free cover around individual E. globulus seedlings. Maximum competing vegetation biomass production during the first growing season were 2.9, 6.5, 2.2 and 12.9 Mg ha^-1, for sites ranging from low to high annual rainfall. As expected, reductions in volume yield at age 9 years were observed as competing vegetation control intensity decreased during the first growing season. A strong relationship was established between stem volume yield loss and the intensity of competing vegetation control, the amount of competing vegetation biomass produced during the first growing season and mean annual rainfall. The slope of the relationship was different among sites and was related mainly to water and light limitations. Our results, suggest that the biomass of competing vegetation (intensity of competition) affecting site resource availability, contribute to observed long-term effects on E. globulus plantations productivity. The site with the lowest mean annual rainfall showed the highest volume yield loss at age 9 years. Sites with highest rainfall showed contrasting results related to the amount of competing vegetation biomass.

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

Background: Electronic cigarette (e-cigarette) use among youth in Poland has become very popular. The aim of this study was to identify potential points of access to these products among students aged 16-17 before implementation of sales restrictions to minors in Poland in November 2016. Methods: A school-based, cross-sectional survey was administered in 2015-2016 in 21 secondary/technical schools across two regions of Poland. Analyses focused on 341 students aged 16-17 who reported past 30-day use of e-cigarettes. Pearson chi-square analyses were utilized to examine associations between access-related items, e-cigarette use, and demographics. Results: Among youth e-cigarette users, the most common access to their first e-cigarette was from a friend (38%), followed by purchasing from vape shops (26%). Similar patterns emerged when students were asked about the access to their currently used e-cigarette. Most youth reported no difficulty purchasing cartridges/e-liquid containing nicotine (90%); the majority of users (52%) reported buying such products in vape shops. Conclusions: Prior to implementing age-related sales restrictions, youth access to e-cigarettes and paraphernalia did not pose any significant barriers. Poland’s introduction of a new age limit on e-cigarette sales may help limit the number of youth who purchase e-cigarettes from vape shops.

In this paper we introduce the New/Generalized two parameter Gamma function and Pochhammer symbol. We named them, as Generalized p - k Gamma Function and Generalized p - k Pochhammer symbol and denoted as $ _{p}^{a}\Gamma_{k}(x) $ and $ _{p}^{a}(x)_{n,k} $ respectively. We prove the several identities for $ _{p}^{a}\Gamma_{k}(x) $ and $ _{p}^{a}(x)_{n,k} $ those satisfied by the classical Gamma function. Also we provide the integral representation for the $ _{p}^{a}\Gamma_{k}(x) $

The majority of E-commerce transactions reveal private information such as customers' identities, order contents, and payment information during the transaction. Other personal information such as health conditions, religion, and even ethnicity may be also deduced. Even when deploying electronic cryptocurrencies such as Bitcoin, anonymity cannot be fully guaranteed. Also, many anonymous payment schemes suffer from possible double spending circumstances. E-commerce privacy is basically a difficult problem as it involves parties with concurring interests. Three major e-commerce requirements are highly difficult to resolve: anonymous purchase, anonymous delivery, and anonymous payment. This work presents a possible e-commerce system addressing all three anonymity requirements for electronic-items business on open networks. The system offers anonymous entities authentication mechanisms up to completing a fair anonymous e-commerce transaction. The system is based on deploying a physically clone-resistant hardware token for each relevant involved party. The tokens are made clone-resistant by accommodating a Secret Unknown Cipher (SUC) in each hardware-token as a digital PUF-like identity. A set of novel generic system-setups for units, protocols and e-commerce schemes is introduced. The proposed anonymization is basically attained by virtually-replacing relevant e-commerce entities by low-cost, unique and clone-resistant tokens/units using SUCs. The units act as trustable anonymous, authenticated and non-replaceable entities monitored by their acting users.

RAD51 is a recombinase that plays a pivotal role in homologous recombination. Although the role of RAD51 in homologous recombination has been extensively studied, it is unclear whether RAD51 can be involved in gene regulation as a co-factor. In this study, we found in silico evidence that RAD51 may contribute to the regulation of genes involved in the autophagy pathway through interaction with E-box proteins such as USF1, USF2, and/or MITF in GM12878, HepG2, K562, and MCF-7 cell lines. The canonical USF binding motif (CACGTG) was significantly identified at RAD51 binding sites in all four cell lines. In addition, genome-wide USF1, USF2, and/or MITF-binding regions significantly coincided with the RAD51-binding sites in the same cell line. Interestingly, the promoters of genes associated with the autophagy pathway were significantly occupied by RAD51 in all four cell lines. Taken together, these results predicted a novel role of RAD51 that had not been addressed previously, and provided evidence that RAD51 could possibly be involved in regulating genes associated with the autophagy pathway, through interaction with E-box binding proteins.

The epithelial-mesenchymal (E/M) hybrid state has emerged as an important mediator of elements of cancer progression, facilitated by epithelial mesenchymal plasticity (EMP). We review here evidence for the presence, prognostic significance, and therapeutic potential of the E/M hybrid state in carcinoma. We further assess modelling predictions and validation studies to demonstrate stabilised E/M hybrid states along the spectrum of EMP, as well as computational approaches for characterising and quantifying EMP phenotypes, with particular attention to the emerging realm of single-cell approaches through RNA sequencing and protein-based techniques.

Although the complexity of physically based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e. HBV. This has been rarely done for conceptual models as satellite data are often used in spatial calibration of the distributed models. Three different soil moisture products from ESA CCI SM v04.4, AMSR-E and SMAP, and total water storage anomalies from GRACE are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture are used to analyse the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis and then, these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal substantial contribution of remote sensing products to the lumped model calibration even if their spatially distributed information is lost during the spatial aggregation. Inclusion of new observations such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model’s physical behaviour while it keeps a reasonable water balance that is the key objective of every hydrologic model.

Increased proliferation of IT services in all sectors has reinforced the adoption and diffusion across all levels of education and training institutions. However, lack of awareness of and knowledge about the key challenges and opportunities of elearning, seem to allude policymakers, resulting in low adoption or increased failure rate of many e-learning projects. Our study tries to address this problem through a review of relevant literature in e-learning. Our goal was to draw from the existing literature, insights into the opportunities and challenges of e-learning diffusion, and the current state-of-research in the field. To do this, we employed a systematic review of literature on some of the salient opportunities and challenges of e-learning innovation for educational institutions. These results aimed to inform policymakers and suggest some interesting issues to advance the research and adoption and diffusion of e-learning. Moreover, the bibliometric analysis shows that the field is experiencing high research attraction among scholars. However, several research areas in the field witnessed relatively low research paucity. Based on these findings, we discussed topics for possible future research.

The arrival of new developments in the field of power electronics circuit’s applications in power systems builds new control strategy to improve voltage quality for power grid by overcome interruptions. Wind energy resources are unconventional resources and get advanced problems to power grid when it is connected. Uncertainty of load sharing, peak energy management, climatic conditions, wind velocity and wind energy injected into power grid leads many of power quality problems on power grid based on the existing guidelines specified in IEC-61400 standard. This system plans efficient operation of DFIG to eliminate the voltage collapse and mismatch frequency to power grid. The DFIG connected diode rectifier and rotor side converter wind generator works as an Efficient Static Synchronous Compensator (E-SATCOM) for supplying the demand of reactive power for power grid to mitigate PQ problems. The benefit of using a combined controller was verified by simulink/Matlab and its simulated results used Doubly Fed Induction Generator (DFIG), wind Turbine. This simulation results gives good quality transient and stable state response to manage and support reactive power for both symmetrical and unsymmetrical faults in connection of grid codes to provide continuous quality of power supply, multiple wind generators are required for 140 bus power grid.

General characteristics of K changes together with their fine structure associated with ground flashes in Sri Lanka in the tropics are presented. It is found that on average there are about 2 K changes associated with each return stroke. Analysis of the fine structure of the K changes shows that the K change is a chaotic pulse burst. Some of these chaotic pulse bursts start and the others end as a regular pulse bursts. Sometimes the chaotic part occurs in between two regular pulse bursts. This is in agreement with the recent published results that claim that chaotic pulse bursts are a random superposition of regular pulse bursts. The results show that the small step fields identified in the literature as K changes are the static fields associated with these pulse bursts.

Accurate estimates of daily rainfall are essential for understanding and modeling the physical processes involved in the interaction between the land surface and the atmosphere. In this study, daily satellite soil moisture observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) generated by implementing the standard NASA- algorithm are employed for estimating rainfall, firstly, through the use of recently developed approach, SM2RAIN (Brocca et al., 2013) and, secondly, the nonlinear autoregressive network with exogenous inputs (NARX) neural modelling at five climate stations in the Karkheh river basin (KRB), located in southwest Iran. In the SM2RAIN method, the period 1 January 2003 to 31 December 2005 is used for the calibration of algorithm and the remaining 9 months from 1 January 2006 to 30 September 2006 is used for the validation of the rainfall estimates. In the NARX model, the full study period is split into a training (1 January 2003 to 31 September 2005) and a testing (1 September 2005 to 30 September 2006) stage. For the prediction of the rainfall as the desired target (output), relative soil moisture changes from AMSR-E and measured air temperature time series are chosen as exogenous (external) inputs in NARX. The quality of the estimated rainfall data is evaluated by comparing it with observed rainfall data at the five rain gauges in terms of the correlation coefficient R, the RMSE and the statistical bias. For the SM2RAIN method, R ranges between 0.44 and 0.9 for all stations, whereas for the NARX- model the values are generally slightly lower. Moreover, the values of the bias for each station indicate that although SM2RAIN is likely to underestimate large rainfall intensities, due to the known effect of soil moisture saturation, its biases are somewhat lower than those of NARX. In conclusion, the results of the present study show that with the use of AMSR-E soil moisture products in the physically based SM2RAIN- algorithm as well as in the NARX neural network, rainfall for poorly gauged regions can be fairly predicted.

Different forces play a key-role in the stability of food colloid dispersions. Focus is here on those controlling attraction and/or repulsion, which concur to stabilization, phase separation, coagulation, and are quite evident in water-based systems. Combination of attractive and repulsive forces favors, or hinders, the association of colloid entities; such processes are often met in food technology. The above processes depend on the forces at work, and on colloid concentration in the medium (i.e. on inter-particle distance). Worked examples deals with milk manipulation procedures, ending in cheese formation. The whole milk-working sequence is controlled by the combination of forces leading to aggregation and phase separation of casein and other milk components. Thereafter, one gets either fresh, for prompt consumption, or aged cheeses. The combination of attractive (van der Waals, vdW, and depletion) with repulsive (double layer, DL, but also with steric) forces results in the dominance of aggregation versus dispersion modes in all steps of milk transformation, which depend on the distance among colloid particles, on the amplitude of the mentioned forces, and on their decay length. The combined role of double layer and van der Waals (vdW) forces is at the basis of the DLVO theory on colloid stability, which is properly modified when these forces overlap with steric stabilization and, eventually, with depletion. Steric effects are dispersive, depletion ones favor colloid nucleation in a single phase. The milk manipulation chain is a worked example of the intriguing association features controlled by the mentioned forces (and of ancillary ones, as well), and indicates which forces favor the formation of products such as Parmesan or Mozzarella cheese, but are not alien to the preparation of many other dairy products.

Although the signaling function of Na/K ATPase is been studied for decades, the chasm between the pumping function and the signaling function of Na/K – ATPase is still an open issue. This article explores the relationship between ion pumping and signaling with attention to the amplification of oxidants through this signaling function. Starting with some experimental observations published by our laboratories and others, we develop some predictions regarding cellular oxidant stress.

Given the rise in the number of cases and their recurrences, Urinary Tract Infections (UTI) are one of the major burdens on public healthcare worldwide. Rapid, inexpensive and selective detection of Uropathogenic E. coli (UPEC), a major contributor to UTIs, is the need of the hour for effective treatment, given the rise of antibiotic-resistant bacteria due to improper diagnosis. Here we present a rapid, real-time, selective and label-free detection of UPEC using an integrated sensing platform based on Crossed Surface Relief Gratings (CSRGs) as nanoplasmonic sensors. Detection is achieved due to the unique Surface Plasmon Resonance (SPR)-based light energy exchange attributed to the CSRGs, allowing real-time sensing in a very narrow bandwidth of the incident light to pass where the SPR energy conversion occurs. The sensing ability of the platform is experimentally demonstrated by the detection of bulk Refractive Index (RI) changes, with a bulk sensitivity of 382.2 nm/RIU and a resolution in the order of 10-6 RIU. We demonstrate selective capture and detection of clinical concentration of UPEC, as opposed to other gram-negative bacteria, in real-time, a first for CSRGs. This work is particularly important for effective treatment of UTIs, allowing point-of-care diagnosis for economically disadvantaged regions around the world.

Currently, with the rapid growth of the population, the demand for metals has increased, especially for the manufacture of electronic devices such as cell phones, computer equipment, among others. Once these devices stop working, most are sent to landfills, which represents a danger since these wastes contain metals and other materials that must be properly managed to prevent them from having a negative effect on the environment and the human being. On the other hand, e-waste contains valuable metals such as copper, gold, and silver, the concentration of which in these materials makes it cost-effective to recover. This paper presents a review of the extraction and recovery of valuable metals from electronic waste by hydrometallurgical methods, as well as patents and industrial processes related to the management and treatment of this waste.

Mints emit diverse scents that exert specific biological functions and are relevance for applications. The current work strives to develop electronic noses that can electronically discriminate the scents emitted by different species of Mint as alternative to conventional profiling by gas chromatography. Here, 12 different sensing materials including 4 different metal oxide nanoparticle dispersions (AZO, ZnO, SnO2, ITO), one Metal-Organic Frame as Cu(BPDC), and 7 different polymer films including PVA, PEDOT: PSS, PFO, SB, SW, SG, PB were used for functionalizing of QCM sensors. The purpose was to discriminate six economically relevant Mint species (Mentha x piperita, Mentha spicata, Mentha spicata ssp. crispa, Mentha longifolia, Agastache rugosa, and Nepeta cataria). The adsorption and desorption datasets obtained from each modified QCM sensor were processed by three different classification models including Principal Component Analy-sis (PCA), Linear Discriminant Analysis (LDA), and k-Nearest Neighbor Analysis (k-NN). This allowed discriminating the different Mints with classification accuracies of 97.2% (PCA), 100% (LDA), and 99.9% (k-NN), respectively. Prediction accuracies with a repeating test measurement reached up to 90.6% for LDA, and 85.6% for k-NN. These data demonstrate that this electronic nose can discriminate different Mint scents in a reliable and efficient manner.

Hyperspectral imaging provides vital information about the objects and elements present inside the image. That’s why they are very useful in satellite imagery as well as image forensics. Hyperspectral document analysis (HSDI) can be used for document authentication using ink analysis which can provide sufficient information about the composition and type of ink. In this project, we have implemented HSDI based ink classification technique using Principle Component Analysis for dimensionality reduction and K-means clustering for ink classification. This is unsupervised learning approach and it is very simple and efficient in order to classify limited number of bands. We have used this technique to classify 33 different bands of ink.

The importance of measuring sustainability in tourism has been significantly advancing in recent years, following the need to manage the impact of tourism on territories and hosting communities. It was further boosted by the pandemic, where sustainability has been defined as one of the central elements to restart global tourism. The ETIS model, developed by the European Commission, is a point of reference based on self-assessment, data collection and analysis by the destinations themselves. The application of ETIS toolkit has faced many challenges, especially at sub-national level, mostly related to the lack of available and updated data to feed the model. The hypothesis explored by the authors is to solve the implementation issues, developing an indicator based on the use of the Sentiment Analysis to frame e-reputation and tourism satisfaction, and further combining it with other open data sources. The Tourism Sustainability Index (TSI) can provide a scalable and geo-referenced evaluation of tourism sustainability, measuring the four pillars and sub-components referenced to ETIS criteria, applicable to any tourism destination. Results show that the TSI can be seen as a consistent and valid tool for destinations to analyze sustainability, monitor its evolution through time periods and sub-areas, and compare it to other benchmark or competitive areas.

Candida albicans as an opportunistic pathogen exploits the host immune system and causes a variety of life-threatening infections. The polymorphic nature of this fungus gives it tremendous advantage to breach mucosal barriers and cause a variety of oral and disseminated infections. Enterococcus faecalis, another opportunistic pathogen co-exists with C. albicans in several niches in the human body, including the oral cavity and gastrointestinal tract. However, interactions between E. faecalis and C. albicans on oral mucosal surfaces remain unknown. Here, for the first time, we comprehensively characterized the interactive profiles between laboratory and clinical isolates of C. albicans (SC5314 and BF1) and E. faecalis (OG1RF and 846) on an organotypic oral mucosal model. Our results demonstrated that the two species formed robust biofilms on the mucosal tissue surface with profound surface erosion and fungal invasion. Specifically, this effect was more pronounced in the laboratory isolates than in the clinical isolates. Notably, several genes of C. albicans involved in tissue adhesion, hyphal formation, fungal invasion, and biofilm formation were significantly upregulated in the presence of E. faecalis. This study highlights the strain-dependent cross-kingdom interactions between E. faecalis and C. albicans on oral mucosa, demonstrating the requisite to study more substrate-dependent polymicrobial interactions.

Hyper spectral imaging (HSI) is a technique that is used to obtain the spectrum for each pixel in the image. It helps in finding objects and identifying materials etc. Such an identification is very difficult using other imaging techniques. It allows the researchers to investigate the documents without any physical contact. Nowadays detection of unequal Ink mismatch based on HSI has shown vast improvement in distinguishing the inks. Detection of unequal Ink mismatch is an unbalanced clustering problem. This paper used K-means Clustering for ink mismatch detection. K-means Clustering find same subgroups in the data based on Euclidean distance. This paper demonstrates performance in unequal Ink mismatch based on HSI.

Public participation is significant for the success of any urban planning project. However, most members of the general public are not planning professionals and may not understand the technical details of a 2D paper-based plan, which might hamper their participation. One way to expand the participation of citizens is to present plans in well-designed, user-friendly and interactive platforms that allow participation regardless of the technical skills of the participants. This paper investigates the impacts of the combined use of 3D visualization and E-participation on public participation in Kisumu, Kenya. A 3D City model, created with CityEngine2016, was exported into a web-based geo-portal and used as a Planning Support System in two stakeholder workshops in order to evaluate its usability. For e-participation, 300 questionnaires given out to planning practitioners. Five indicators were developed for evaluating the usability of the 3D model while the usability of e-participation was evaluated using communication, collaboration and learning as indicators. Results showed that effectiveness and efficiency varies within different professional groups while the questionnaires showed strong preference for e-participation methods, especially SMSs/USSDs and emails. The study concludes that the use of 3D visualization and E-participation has the potential for improving the quality and quantity of public participation and recommends further research on the subject.

In the present work we study the properties of geodesic sub-$ (\alpha,b,s) $-preinvex functions on Hadamard manifolds and establish some basic properties in both general and differential cases. Further, we study sufficient conditions of optimality and proved some new inequalities under geodesic sub-($ \alpha,b,s $)-preinvexity.

In today's world it is very much important to maintain the security of information and its risks. The biometric-based techniques are very much useful in these problems. Among the several kinds of biometric-based technique, face detection is much complex and much more important. Due to the age and several other problems, a human face structure changes over time, again a human has lots of expressions. Sometimes due to the lighting condition or the variation of the angle of an input device, the pattern of a human face structure also changed. As a result, the face cannot be detected properly. In this paper, a method is proposed that can detect the human faces both automatically and manually very efficiently. In manual mode, a user can select the input faces referred by the system according to their choice. In automated mode, the system detected all possible face areas using the Kohonen Self-Organizing Feature Map technique. This method reduced the complex color image into a vector quantized image with desired colors. Then a color segmentation technique is used to detect the possible face skin areas from the vector quantized image. Then the Histogram Oriented Gradient technique used to detect the feature from the faces and K-Nearest Neighbour Classifier is used to compare both face images detected by the two modes. The automated method prosed better accuracy than the manual method.

Classical k-ratio models, e.g. ZAF and phi(rho z), used in electron probe microanalysis (EPMA) assume a homogeneous or multi-layered material structure, which essentially limits the spatial resolution of EPMA to the size of the interaction volume where characteristic x-rays are produced. We present a new model for characteristic x-ray emission that avoids assumptions on the material structure to not restrict the resolution of EPMA a-priori. Our model bases on the spherical harmonic (PN) approximation of the Boltzmann equation for electron transport in continuous slowing down approximation. PN models have a simple structure, are hierarchical in accuracy and well-suited for efficient adjoint-based gradient computation, which makes our model a promising alternative to classical models in terms of improving the resolution of EPMA in the future. We present results of various test cases including a comparison of the PN model to a minimum entropy moment model as well as Monte-Carlo (MC) trajectory sampling, a comparison of PN-based k-ratios to k-ratios obtained with MC, a comparison with experimental data of electron backscattering yields as well as a comparison of PN and Monte-Carlo based on characteristic X-ray generation in a three-dimensional material probe with fine structures.

In the current natural environment, due to the complexity of the background and the high similarity of the color between immature green tomato and plant, the occlusion of the key organs (flower and fruit) by the leaves and stems will lead to low recognition rate and poor generalization of the detection model. Therefore, an improved tomato organ detection method based on convolutional neural network has been proposed in this paper. Based on the original Faster R-CNN algorithm, Resnet-50 with residual blocks was used to replace the traditional vgg16 feature extraction network, and K-means clustering method was used to adjust more appropriate anchor size than manual setting to improve detection accuracy. A variety of data augmentation techniques were used to train the network. The test results showed that compared with the traditional Faster R-CNN model, the mean average precision (mAP) of the optimal model was improved from 85.2% to 90.7%, the memory requirement decreased from 546.9MB to 115.9 MB, and the average detection time was shortened to 0.073S/sheet. As the performance greatly improved, the training model can be transplanted to the embedded system, which lays a theoretical foundation for the development of precise targeting pesticide application system and automatic picking device.

The violation of privacy, others people or personal, is a very current problem, which concerns not only on the web but also in private life. In the years 1990 it was expected that nowadays, that any routine operation was carried out "manually", and it would be performed through mobile phones or personal computers. The problem pertains the distribution network that allows to share and bring together information and as result the network becomes unsafe, if subjected to attacks. Nowaday we put personal information on web because otherwise we are seen as “weak”. This work aims to measure and analyze how much information are shared by users of a pre-established social network and it is carried out through a set of algorithms techniques of machine learning.

Biofilms enable the persistence of pathogens in food processing environments. In order to inactivate these microorganisms, sanitizing agents are needed that are effective against pathogens entrapped in biofilms which are more difficult to inactivate than planktonic cells that are displaced and found on equipment surfaces. We examined conditions to develop, analyze, and enumerate robust biofilms of 3 different foodborne pathogens assisted by fluorescence adherence assay and enzymatic detachment. We compared 3 different isomeric forms of fluorescent substrates that are readily taken up by bacterial cells based on carboxy-fluorescein diacetate (5-CFDA, 5,6-CFDA, 5,6-CFDA,SE). Biofilm-forming strains of L. monocytogenes, E.coli O157:H7, and Salmonella serovars were detected using the chosen substrate in a microplate fluorescence assay define previously for use with Listeria. Adherence levels were determined by differences in relative fluorescence units (RFU). Multiple hydrolytic enzymes were examined for each representative pathogen for the most suitable enzyme for detachment and enumeration to confirm data obtained by fluorescence assay. Cultures were grown overnight in microplates, incubated, washed and replenished with fresh sterile growth medium; this cycle was repeated 7 times before used as ‘biofilms’. All treatments were performed in triplicate and compared by one-way analysis of variance (ANOVA) to determine significant differences (p < 0.05). Analysis of 7-day biofilms by SEM indicated possible extracellular polysaccharide involvement with Salmonella and E. coli.

We report on the successful preparation of wet dressings hydrogels based on Chitosan-Poly(N-Vinyl-Pyrrolidone)-Poly(ethylene glycol)-Poly(acrylic acid) and Poly(ethylene oxide) by e-beam cross-linking in weakly acidic media, to be used for rapid healing and pain release of infected skin wounds. The structure and compositions of hydrogels investigated according to sol-gel and swelling studies, network parameters, as well as FTIR and XPS analyses showed the efficient interaction of the hydrogel components upon irradiation, maintaining the bonding environment while the cross-linking degree increasing with the irradiation dose and the formation of a structure with the mesh size in the range 11-67 nm. Hydrogels with gel fraction above 85% and the best-swelling properties in different pH solutions were obtained for hydrogels produced with 15 kGy. The hydrogels are stable in the simulated physiological condition of an infected wound and show appropriate moisture retention capability and the water vapor transmission rate up to 272.67 g m-2 day-1, to ensure fast healing. The hydrogels proved to have a significant loading capacity of ibuprofen (IBU), being able to incorporate a therapeutic dose for the treatment of severe pains. Simultaneously, IBU was released up to 25% in the first 2h, having a release maximum after 8h.

The effect of proteolytic enzymes including Cathepsin K, a cysteine cathepsin, in onset and progression of cancers in human has been research intensive. Cathepsin K involves in many aspects and stages of cancers including apoptosis, cell proliferation, cancer immunology, inflammatory cell recruitment to tumors and aiding in the process of mobilization of normal healthy cells from their tissue compartments assisting in metastasis and angiogenesis. The objective of this review is to collect together and summarize and analyze the biochemical and physiological pathways of how cathepsin K is involved in onset and progression of cancers with more emphasis on breast and prostate cancers and cathepsin K regulated mechanisms underlying metastasis of such cancers to bones. Information for the review was gathered through published literature from global databases such as Google Scholar, PUBMED and NCBI on different studies on physiological interactions between enzymatic activity of cathepsin K with cancers and metastasis to bones. Analysis of published studies reveal that immunohistochemical studies of breast cancer cells indicate that they overexpress cathepsin K resulting in induction of aberrant mechanisms of cell signaling in breast cancers, creating a higher tendency for their metastasis to bones. Immunohistochemical, immunoprecipitation and fluorgenic assays of several studies done on the association of the same enzymatic activity on prostate cancers shows elevated levels of cathepsin K. Lesions derived from prostate cancer cell masses were observed to undergo increased bone formation and resorption levels. Such resorption levels cause secretion of biological factors promoting tumor expansion. In addition, studies indicate that Cathepsin K was observed to be a key component promoting higher bone resorption levels in patients suffering from cancer. Authors suggest that, to completely understand the association of cathepsin K on cancerous cells and their mechanism in metastasis, distributary patterns of cathepsin K in healthy human tissues needs to be extensively studied initially. It is also suggested that metastasis of breast and prostate cancers to bone could be terminated and overcome by successful production of efficient and precise inhibitory therapeutics targeting the enzymatic activity of Cathepsin K with minimum unintended adverse health effects.

Exploring the dynamic behavior of cellular metabolism requires a standard laboratory method that guarantees rapid sampling and extraction of the cellular content. We propose a versatile sampling technique applicable to cells with different cell wall and cell membrane properties. The technique is based on irreversible electroporation with simultaneous quenching and extraction by using a microfluidic device. By application of electric pulses in the millisecond range, permanent lethal pores are formed in the cell membrane of Escherichia coli and Saccharomyces cerevisiae, facilitating the release of the cellular contents; here demonstrated by the measurement of glucose-6-phosphate and the activity of the enzyme glucose-6-phosphate dehydrogenase. The successful application of this device was demonstrated by pulsed electric field treatment in a flow-through configuration of the microfluidic chip in combination with sampling, inactivation, and extraction of the intracellular content in a few seconds. Minimum electric field strengths of 10 kV/cm for E. coli and 7.5 kV/cm for yeast S. cerevisiae were required for successful cell lysis. The results are discussed in the context of applications in industrial biotechnology, where metabolomics analyses are important.

E-commerce businesses employ recommender models to assist in identifying a personalized set of products for each visitor. To accurately assess the recommendations’ influence on customer clicks and buys, three target areas—customer behavior, data collection, user-interface —will be explored for possible sources of erroneous data. Varied customer behavior misrepresents the recommendations’ true influence on a customer due to the presence of B2B interactions and outlier customers. Non-parametric statistical procedures for outlier removal are delineated and other strategies are investigated to account for the effect of a large percentage of new customers or high bounce rates. Subsequently, in data collection we identify probable misleading interactions in the raw data, propose a robust method of tracking unique visitors, and accurately attributing the buy influence for combo products. Lastly, user-interface issues discuss the possible problems caused due to the recommendation widget’s positioning on the e-commerce website and the stringent conditions that should be imposed when utilizing data from the product listing page. This collective methodology results in an exact and valid estimation of the customer’s interactions influenced by the recommendation model in the context of standard industry metrics such as Click-through rates, Buy-through rates, and Conversion revenue.

At present more than 9 million people die of cancer every year. Simple and broad-spectrum drugs are still an urgent need for cancer patients. Recently, we proposed a new hypothesis that intracellular osmotic pressure (IOP) is the driving force of cell division, and abnormal tumor proliferation is the result of uncontrolled IOP in cells. On the one hand, aneuploidy and abnormal function of Na⁺/K⁺ pump lead to a faster rise of IOP in tumor cell than normal cells, on the other hand, abnormality of cytoskeleton assembly leads to the decrease of tolerance limit of cell membrane (TLCM) of tumor cells for resisting IOP. This hypothesis predicts: 1)Tumor cells were more intolerant to hypotonic stress than normal cells. 2) Maligancies may be sellectively killed by a suddenn increase of IOP and combined with decrease of the TLCM of tumors. Na⁺/K⁺ pump inhibitors can promotely increase the IOP of tumor cells and cytoskeleton inhibitors can dramatically lower the TLCM of tumor cells. Therefore, Na⁺/K⁺ pump and cytoskeleton inhibitors may have a synergetic effect to kill tumor cells. 3) Molecules regulating cell osmolality may be new targets for cancer treatment.

For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer details are influential while considering possibilities of taking term deposit subscription. An automated system is provided in this paper that approaches towards prediction of term deposit investment possibilities in advance. Neural network(NN) along with stratified 10-fold cross-validation methodology is proposed as predictive model which is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concluded that proposed model provides significant prediction results over other baseline models with an accuracy of 88.32% and Mean Squared Error (MSE) of 0.1168.

This study was undertaken to derive and analyze the Advanced Microwave Scanning Radiometer - EOS (AMSR-E) sea surface temperature (SST) footprint associated with the Remote Sensing Systems (RSS) Level-2 (L2) product. The footprint, in this case, is characterized by the weight attributed to each 4  4 km square contributing to the SST value of a given AMSR-E pixel. High-resolution L2 SST fields obtained from the MODerate-resolution Imaging Spectroradiometer (MODIS), carried on the same spacecraft as AMSR-E, are used as the sub-resolution “ground truth“ from which the AMSR-E footprint is determined. Mathematically, the approach is equivalent to a linear inversion problem, and its solution is pursued by means of a constrained least square approximation based on the bootstrap sampling procedure. The method yielded an elliptic-like Gaussian kernel with an aspect ratio  1.58, very close to the AMSR-E 6.93GHz channel aspect ratio,  1.7. (The 6.93GHz channel is the primary spectral frequency used to determine SST.) The semi-major axis of the estimated footprint is found to be alignedwith the instantaneous field-of-view of the sensor as expected fromthe geometric characteristics of AMSR-E. Footprintswere also analyzed year-by-year and as a function of latitude and found to be stable – no dependence on latitude or on time. Precise knowledge of the footprint is central for any satellite-derived product characterization and, in particular, for efforts to deconvolve the heavily oversampled AMSR-E SST fields and for studies devoted to product validation and comparison. A preliminarly analysis suggests that use of the derived footprint will reduce the variance between AMSR-E and MODIS fields compared to the results obtained.

Pediculus humanus capitis, the head louse, is an obligate blood-sucking ectoparasite that occurs in six divergent mitochondrial haplogroups (A, D, B, F, C and E), each exhibiting a particular geographic distribution. A few years ago, several studies reported the presence of different pathogenic agents in head lice specimens from different clades collected worldwide. These findings suggest that head louse could be a vector for dangerous diseases and therefore a serious public health problem. Herein, we aimed to study the mitochondrial genetic diversity, the PHUM540560 gene polymorphisms profile of head lice collected in Guinea, as well as to screen for the pathogens present in these lice. In 2018, a total of 155 head lice were collected from 49 individuals at the Medicals Centers of rural (Maférinyah village) and urban (Kindia city) areas, in Guinea. All head lice were subjected to genetic analysis and screened for the presence of several pathogens using molecular tools. The results showed that all head lice belonged to the haplogroups C/E using the duplex qPCR which detects both clades. Standard PCR and sequencing revealed that all specimens belonged to the haplogroup E, including 8 haplotypes, whither 6 new identified for the first time in this study. The study of the PHUM540560 gene polymorphisms in our Guinean head lice revealed that 7/40 (17.5%) of our tested samples exhibit three different polymorphism profiles compared to the clade A-head lice PHUM540560 gene profile, while the remaining specimens 33/40 (82,5%) showed the same PHUM540560 gene polymorphism profile as the previously reported clade A-body lice. Molecular investigations of the targeted pathogens revealed only the presence of Acinetobacter species in 9% of our samples using real time PCR. Sequencing results identified highlighted the presence of several Acinetobacter species, including Acinetobacter baumannii (14.3%), Acinetobacter nosocomialis (14.3%), Acinetobacter variabilis (14.3%), Acinetobacter haemolyticus (7.2%), Acinetobacter towneri (7.2%). Furthermore, a candidate new species of Acinetobacter sp. (7.2%) was detected. Positive specimens were collected from 24,5% individuals in Maférinyah. We also investigated in our study the carbapenem’s-resistant profile of A. baumannii, none of our specimens were positive for the following resistance genes blaOXA-21, blaOXA-24 and blaOXA-58. To the best of our knowledge, our study is the first to report the existence of the Guinean haplogroup E, the PHUM540560 gene polymorphism profile as well as the presence of Acinetobacter species in head lice collected from Guinea.

Whistler mode waves play a major role in regulating the lifetime of trapped electrons in the Earth's radiation belts. Specifically, whistler mode hiss waves are one of the mechanisms that maintains the slot region between the inner and outer radiation belts. The generation mechanism of hiss is a topic still under debate with at least three prominent theories present in the literature. Lightning generated whistlers in their ducted or non-ducted modes, are considered to be one of the possible sources of hiss. We present a study of new observations from the Radio Receiver Instrument (RRI) on the Enhanced Polar Outflow Probe (ePOP: currently known as SWARM-E). RRI consists of two orthogonal dipole antennas, which enables polarization measurements, when the satellite boresight is parallel to the geomagnetic field. Here we present 75 passes of ePOP - RRI from 2014 - 2018, in which lightning whistlers and hiss waves were observed. In more than 50% of those passes hiss is found to co-exist with the lightning whistlers. Moreover, the whistler observations are correlated with observations of wave power at the lower-hybrid resonance. The observations and a whistler mode ray-tracing study suggest that multiple-hop lightning induced whistlers can be a source of hiss and plasma instabilities in the magnetosphere.

The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

This study focuses on a new class of functions called sub-b-s-preinvex, that is a generalization of sub-b-s-convex and preinvex functions, and discusses some of their properties. A new sub-b-s-preinvex programming is introduced and the sufficient conditions of optimality under this type of function is established.

For a positive integer k, a radio k-coloring of a simple connected graph G = (V (G), E(G)) is a mapping | f(u) - f(v)| ≥ k +1-d (u , v ) such that f :V (G)→{0,1, 2,...} for each pair of distinct vertices u and v of G, where d(u, v) is the distance between u and v in G. The span of a radio k-coloring f, rck(f), is the maximum integer it assigns to some vertex of G. The radio k-chromatic number, rck(G) of G is min{rck(f)}, where the minimum is taken over all radio k-colorings f of G. If k is the diameter of G, then rck(G) is known as the radio number of G. In this work, we propose four algorithms (two serial algorithms and their parallel versions) which related to the radio k-coloring problem. One of them is an approximate algorithm that determines an upper bound of the radio number of a given graph. The other is an exact algorithm which finds the radio number of a graph G. The approximate algorithm is a polynomial time algorithm while the exact algorithm is an exponential time algorithm. The parallel algorithms are parallelized using the Message Passing Interface (MPI) standard. The experimental results prove the ability of the proposed algorithms to achieve a speedup 7 for 8 processors.

The adverse relationship between viral hepatitis and pregnancy in developing countries was seen as a reflection of retrospective biased hospital-based data collection by the West. However, the discovery of HEV from an epidemic of non-A, non-B hepatitis in Kashmir and documenting increased incidence and severity of hepatitis E in pregnancy from a house-to-house survey unmasked the unholy alliance. Among the family of HEV’s, genotype (gt)-1, with a unique ORF4-encoded protein enhancing viral polymerase activity and viral replication, is the sole HEV that shows this adverse relationship. The epidemics caused by HEV-gt1 and not by HEV-gt2 show adverse relationship with pregnancy. The pathogenesis of the unholy alliance is complex and at present not well understood. Possibly multiple factors play a role in causing severe liver disease in the mother including: infection, replication and damage to the maternal-foetal interface by HEV-gt1; vertical transmission of HEV to foetus causing severe foetal/neonatal hepatitis; and combined viral and hormone related immune dysfunction of diverse nature in the mother promoting viral replication. Management is multidisciplinary and needs a close watch for the development and management of ALF. Preliminary data suggest beneficial maternal outcomes by early termination of pregnancy in patients with lower grades of encephalopathy.

Studies have shown that aerosols generated from flavored e-cigarettes contain Reactive Oxygen Species (ROS), promoting oxidative stress-induced damage within pulmonary cells. Our lab investigated the ROS content of e-cigarette vapor generated from disposable vape bars, a product exempt from the Federal Drug Enforcement Agency’s (FDA) 2020 flavor ban. Specifically, we analyzed vape bars belonging to multiple flavor categories (Tobacco, Minty Fruit, Fruity, Minty/Menthol, Desserts, and Drinks), manufactured by various vendors and of various nicotine concentrations (0-6.8%). Aerosols from these flavored vape bars were generated by a single puff aerosol generator and individually bubbled through a fluorogenic solution to detect and semi-quantify ROS in H2O2 equivalents generated by the vape bars. We compared and contrasted the ROS levels generated by each flavor as an indirect determinant of oxidative stress potential by these disposable vape bars. Our results showed that ROS concentration (μM) of aerosols produced from the vape bars varied significantly between different flavors and a function of nicotine concentration. Likewise, our results suggest that flavoring chemicals and nicotine concentration play a role in alerting ROS production in e-cigarette aerosols. Our study provides insight into the differential health effects of flavored disposable vape bars and the need for their regulation.

In this work, two embroidered textile moisture sensors are characterized with three different conductive yarns. The sensors are based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidered conductor yarn. The performance comparison of 3 different type of conductive yarns has been addressed. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 30% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity and the used conductor yarns. This dependence points out the optimum conductive yarn to be used to develop wearable applications for moisture measurement.

Historically, macrophages have been long implicated in the control of the severity of infectious diseases. This has been based on the observations of a higher risk of severe disease and death upon rechallenge with viral variants due to antibody dependent enhance-ment (ADE) of infection into macrophages. The question remains as to what can account for this potent heterologous protection in macrophages? Here it is argued that the elusive defense mechanism of M1-like pro-inflammatory macrophages may pertain to a novel virus anti-virus response. This system initiates with high replication of human endogenous retrovirus K102 (HERV-K102), a non-pathogenic, protector foamy retrovirus of humans which generates M1-like pro-inflammatory foamy macrophages, glycolysis, and epigenetic changes, all characteristic of trained immunity. This virus-anti-virus system kills virally infected cells by several mechanisms, amplifies the innate interferon response via ‘viral mimicry’, has many unique components that interfere with exoge-nous virus replication, and may be especially adept at neutralizing enveloped exogenous pandemic viruses, such as SARS-CoV-2 and HIV-1. The goal of this treatise is to introduce the multifaceted HERV-K102 protector system, to illustrate how SARS-CoV-2 may target the HERV-K102 protector system by ADE, and to explore how this innate defense system may be exploited for pandemic preparedness.

Geomagnetic induced current (GIC) is a ground end manifestation associated with the space weather perturbations that should be greatly taken into account by the society. Although the GICs implication to the power system is not regular, it can cause large scale of system failure. In equatorial, the power system is considered safe since the most intense of geomagnetic storm happened in high latitude. However, the internal damage due to GICs which finally led to the South African power system failure has totally changed the normal perception. Therefore, a preliminary investigation on the GICs activity in equatorial region is performed to understand the space weather impact to the power system. Time derivative of the horizontal magnetic field component (dB/dt) is done to indicate the GICs activity value based on Faraday’s law. All the reported power failures are compiled to produce the threshold value of dB/dt, which possibly cause the harmful effect to the system. Then, dB/dt analysis is extended to show the pattern of GICs activity in function of magnetic latitude and local time. The results reveal that power network in equatorial region has possibly suffered by GIC. Plus, high number of intense GIC activity in this region occurred during dayside.

A new label-free molecular probe for luminescent nucleotide detection in neutral aqueous solution is presented. Phosphate-containing molecules such as nucleotides possess vital role in cell metabolism, energy economy, and signaling. Thus the monitoring of nucleotide concentration and nucleotide related enzymatic reactions is of high importance. Two component lanthanide complex formed from Tb(III) ion carrier and light harvesting antenna, readily distinguishes nucleotides containing different number of phosphates and enable direct detection of enzymatic reactions converting nucleotide triphosphate (NTP) to nucleotide di/monophosphate or the opposite. Developed sensor enables the detection of enzymatic activity with a low nanomolar sensitivity, as highlighted with K-Ras and apyrase enzymes in there hydrolysis assays performed in high throughput screening compatible 384-well plate format.

In document forensic, Ink mismatch relays very important information about forgeries in this way we can find out the authenticity of documents. Finding out and distinguishing these unique inks from the multispectral document is very challenging task. In this paper we proposed the method to identify the inks using clustering. We used K-Mean clustering instead of widely known Fuzzy C-Means Clustering (FCM) and successfully identity the number of inks. For the purpose of optimizing and improving our results we used two optimization techniques such as Elbow and silhouette optimization techniques.

Pancreatic cancer is a fatal disease with mortality rate of 5% and a with a limited survival rate of 5 years. Despite of the extensive efforts that has been made to cure the disease it still has been considered as ‘undruggable’. It is characterized by epithelial to dense stromal tumor formation however due to lack of diagnosis options and treatment test available to detect the disease to the point at which resection of the tumor is possible, it makes it the fourth leading cause of cancer related death. The unavailable information regarding the early detection of biological markers along with the increased invasive tumor, the inherit chemoresistance against medication radiation and chemotherapy stubbornly fail the therapeutic options available. These associated problems made the scientists to reevaluate the approaches that are currently in practice and take a step back to fully understand the basic biological pathways that are involved in the pancreatic cancer, the heterogeneity of the tumor itself along with expression and a number of mutations that are observed at different locations. Clinical trial along with new approaches are nowadays focus of research to treat this tumor. The review paper describes the basic cellular pathways involved in pancreatic cancer, the gene mutations and their expression having effect on the pathology of the diseases along with treatment options that are available to treat the tumor. These efforts will help with the expansion of our knowledge to undergo the clinical trial and the synthesis of novel medicines for the prognosis of the disease.

BackgroundIt is unclear what underpins the large global variations in the prevalence of fluoroquinolone resistance in gram-negative bacteria. We tested the hypothesis that different intensities in the use of quinolones for food-animals plays a role. MethodsWe used Spearman’s correlation to assess if the country-level prevalence of fluoroquinolone resistance in human infections with Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa was correlated with the use of quinolones for food producing animals. Linear regression was used to assess the relative contributions of country-level quinolone consumption for food-animals and humans on fluoroquinolone resistance in these 4 species. ResultsThe prevalence of fluoroquinolone resistance in each species was positively associated with quinolone use for food-producing animals (E. coli [ρ=0.55; P<0.001], K. pneumoniae [ρ=0.58; P<0.001]; A. baumanii [ρ=0.54; P=0.004]; P. aeruginosa [ρ=0.48; P=0.008]). Linear regression revealed that both quinolone consumption in humans and food animals were independently associated with fluoroquinolone resistance in E. coli and A. baumanii. ConclusionsReducing quinolone use in food-producing animals may help retard the spread of fluoroquinolone resistance in various gram negative bacterial species.

This study describes the development of an image-based insect trap diverging from the plug-in camera insect trap paradigm. In short, a) it does not require manual annotation of images to learn how to count targeted pests and, b) it self-disposes the captured insects, and therefore is suitable for long-term deployment. The device consists of an imaging sensor integrated with Raspberry Pi microcontroller units with embedded deep learning algorithms that count agricultural pests inside a pheromone-based funnel trap. The device also receives commands from the server which configures its operation while an embedded servomotor can automatically rotate the detached bottom of the bucket to dispose of hydrated insects as they begin to pile up. Therefore, it completely overcomes a major limitation of camera-based insect traps: the inevitable overlap and occlusion caused by the decay and layering of insects during long-term operation, thus extending the autonomous operational capability. We study cases that are underrepresented in literature such as counting in situations of congestion and significant debris using crowd counting algorithms encountered in human surveillance. Finally, we perform comparative analysis of the results from different deep-learning approaches (YOLO7/8, crowd counting, deep learning regression) and we open-source the code and a large database of Lepidopteran plant pests.

The e-commerce platform in the digital economy era has evolved into a data platform ecosystem built around data resources and data mining technology systems. The most typical applications of big data are also concentrated in the field of e-commerce. E-commerce companies should first grasp the interactive relationship among the three major factors of data, technology and innovation, e-commerce platform operation is a multidisciplinary research field. It is not easy for researchers to obtain a panoramic view of the knowledge structure in this field. Knowledge graph is a kind of graph that shows the development process and structure relationship of knowledge with the field of knowledge as the object. It is not only a visual knowledge mapping, but also a serialized knowledge pedigree, which provides researchers with a quantitative research method for the development trend of statistics and academic status. The purpose of this research is to help researchers understand the key knowledge, evolutionary trends and research frontiers of current research. This study uses Citespace bibliometric analysis to analyze the data of the Science Net database and finds that: 1) The development of the research field has gone through three stages, and some representative key scholars and key documents have been recognized; 2) the common knowledge mapping of literature The co-occurrence of citations and keywords shows research hotspots; 3) The results of burst detection and central node analysis reveal research frontiers and development trends. Today, the visualization of big data brings different challenges. The abstraction between the world and today's data visualization occurs when the data is captured. Every user sees his own visualization data generated by standardized calculations. At the same time, there are still many controversies in the theoretical model, structure and structural dimensions. This is the direction that future researchers need to further study.

The progressive impairment analysis in gait from neurological diseases patients such as Hereditary Ataxias (HA) has been carried out using gait data collected with movement sensors. This research is focused on finding the minimum amount required of gait features to recognize efficiently and less intrusive way, HA patients based on data collected with iPhone movement sensors placed on the ankles from 14 HA patients and 14 healthy people. A twofold proposal is made , first a local minimum prominent peak criterion to find out the starting point of each stride, to get 10-stride window about which 56 spatial-temporal features are derived; second a search strategy based on Hill Climbing algorithm to reduce the number of gait features and sensors. The main results were the findings that with two gait patterns a 96% of classification accuracy was achieved by using K-Nearest Neighbors (KNN) and Multi-Layer Perceptron (MLP) algorithms, but in addition, MLP only right ankle sensor patterns were required which also allows to reduce the intrusion.

Through the half-unit circle area computation using the integration of the corresponding curve power series representation, we deduce a slow converging positive infinite series to $\pi$. However, by studying the remainder of that series we establish sufficiently close inequalities with equivalent lower and upper bound terms allowing us to estimate, more precisely, how the series approaches $\pi$. We use the obtained inequalities to compute up to four-digit denominator, what are in this sense, the best rational numbers that can replace $\pi$. It turns out that the well-known convergents of the continued fraction of $\pi$, $22/7$ and $355/113$ called, respectively, Yuel\"{u} and Mil\"{u} in China are the only ones found. Thus we apply a similar process to find rational estimations to $\pi+e$ where $e$ is taken as the power series of the exponential function evaluated at $1$. For rational numbers with denominators less than $2000$, the convergent $920/157$ of the continued fraction of $\pi+e$ turns out to be the only rational number of this type.

Human endogenous retroviruses (HERVs) are ancient retroviral DNA sequences established into germline. They contain regulatory elements and encoded proteins few of which may provide benefits to hosts when co-opted as cellular genes. Their tight regulation is mainly achieved by epigenetic mechanisms which can be altered by environmental factors, e.g. viral infections, leading to HERV activation. Aberrant expression of HERVs associates with neurological disease, such as multiple sclerosis (MS) or amyotrophic lateral sclerosis (ALS), inflammatory processes and neurodegeneration. This review summarizes recent advances on the epigenetic mechanisms controlling HERV expression and the pathogenic effects triggered by HERV derepression. The article ends describing new promising therapies targeting HERV elements, one of which, temelimab, has completed phase II trials with encouraging results in treating MS. The information gathered here may turn helpful in the design of new strategies to unveil epigenetic failures behind HERV-triggered disease, opening new possibilities for druggable targets and/or for extending the use of temelimab to treat other associated diseases.

(1) Background: Spain launched an official campaign, #EsteVirusLoParamosUnidos, to try and unite the efforts of the entire country through citizen cooperation to combat coronavirus. The research goal is to analyze the Twitter campaign’s repercussion on general citizen feeling. (2) Methods: The research is based on a composite design that triangulates from a theoretical model, a quantitative analysis and a qualitative analysis. (3) Results: Of the 7357 tweets in the sample, 72.32% were found to be retweets. Four content families were extracted: politics, education, messages to society and defense of occupational groups. The feelings expressed ranged along a continuum, from unity, admiration and support at one end to discontent and criticism regarding the health situation at the other. (4) Conclusions: The development of networked sociopolitical and technical measures that enable citizen participation facilitates the development of new patterns of interaction between governments and digital citizens, increasing citizens’ possibilities of influencing the public agenda and therefore strengthening citizen engagement vis-à-vis such situations.

Background: Biomarkers are essential for identification of individuals at high risk of mild cognitive impairment (MCI) for potential prevention of dementia. We investigated DNA methylation in the ApoE gene and plasmatic apolipoprotein E (ApoE) levels as MCI biomarkers in Colombian subjects with MCI and controls. Methods: 100 participants were included (71% women, average age, 70 yrs., range 43-91). MCI was diagnosed by neuropsychological testing, medical and social history, activities of daily living, cognitive symptoms and neuroimaging. Multivariate logistic regression models adjusted by age and gender were performed to examine the risk association of MCI with plasma ApoE and APOE methylation Results: MCI was diagnosed in 41 subjects (average age, 66.5±9.6 yrs.) and compared with 59 controls. Elevated plasma ApoE and APOE methylation of CpGs 165, 190, and 198 were risk factors for MCI (P<0.05). Higher CpG-227 methylation correlated with lower risk for MCI (P=0.002). Only CpG-227 was significantly correlated with plasmatic ApoE levels (correlation coefficient=-0.665; P=0.008). Conclusion: Differential APOE methylation and increased plasma ApoE levels were correlated with MCI. These epigenetic patterns can be used as potential biomarkers to identify early stages of MCI.

From professors overwhelmed by anxiety-driven e-mails from students, through faculty and administrative staff wasting valued time on e-mail minutia, misuse of electronic mail in the academy has become ubiquitous. After a brief overview of the unique features of e-mail communication, this study provides insight and guidelines to plan new educational activities on healthy and productive utilization of e-mail in the academy of the digital era. The overall aim is to prioritize scholarly deep work by focusing on teaching and research work, freeing working time wasted on unproductive use of e-mail.

This review paper delves into using micro-credentials in higher education ecosystems as a digital enablers. Micro-credentials, which are digital credentials that attest to a learner’s mastery of a specific skill or knowledge area, are becoming more popular in higher education. The paper examines the successful implementation of micro-credential frameworks in higher education, using case studies to demonstrate the advantages of micro-credentials. The review emphasizes the agility and flexibility of microcredentials, which enable learners to acquire new skills quickly and respond to changes in the job market. In addition, the paper discusses the digital nature of micro-credentials and how they allow institutionsto provide targeted, skills-based training that isrelevant to employers. It also explores how micro-credentials are delivered through online platforms, making them convenient and easily accessible for learners. The review underscores the significance of digital infrastructure, connectivity, and public utility for promoting micro-credentials. The paper argues that micro-credentials function as a digital enabler for higher edu- cation ecosystems, allowing learners to acquire targeted training and enabling institutions to expand their offerings and reach more students. The paper concludes by highlighting the potential for micro-credentials to help bridge the skills gap and equip learners with the skills necessary to succeed in today’s digital economy.

Ubiquitous computing comprises scenarios where networks, devices within the network, and software components change frequently. Market demand and cost-effectiveness are forcing device manufacturers to introduce new-age devices. Also, the Internet of Things (IoT) is transitioning rapidly from the IoT to the Internet of Everything (IoE). Due to this enormous scale, effective management of these devices becomes vital to support trustworthy and high-quality applications. One of the key challenges of IoT device management is automatic device classification with the logically semantic type and using that as a parameter for device context management. This would enable smart security solutions. In this paper, a device classification approach is proposed for the context management of ubiquitous devices based on unsupervised machine learning. To classify unknown devices and to label them logically, a proactive device classification model is framed using a k-Means clustering algorithm. To group devices, it uses the information of network parameters such as Received Signal Strength Indicator (rssi), packet_size, number_of_nodes in the network, throughput, etc. Experimental analysis suggests that the well-formedness of clusters can be used to derive cluster labels as a logically semantic device type which would be a context for resource management and authorization of resources. This paper fulfills an identified need of proactive device classification for device management.

Traditionally understood in reference to distance education, cognitive presence may be defined as "the extent to which the participants in any particular configuration of a community of inquiry can construct meaning through sustained communication. The purpose of this paper was to create a blueprint for the reflective ePortfolio as the capstone project for my graduate degree. The blueprint was accomplished by adapting for use cognitive presence as a tool for both analysis and framing, which has never been done to the best of my knowledge. I considered myself to be a participant in a “community of inquiry” model and substituted the result of my interaction with each of the required instructor-course content pairings I took to serve as fellow participants in this community model. The result of my participation was understood to be the knowledge and experience that I have gained, which was reflected in eight of my academic research papers. These selected papers were the artifacts around which my ePortfolio was ultimately developed and demonstrated my participation as an active member in this community of inquiry constructing meaning through sustained communication.

Hepatitis E virus (HEV) is responsible for large waterborne epidemics of hepatitis in endemic countries and is an emerging zoonotic pathogen worldwide. In endemic regions, HEV-1 or HEV-2 genotypes are frequently associated with fulminant hepatitis in pregnant women, while with zoonotic HEV (HEV-3 and HEV-4), chronic cases of hepatitis and severe neurological disorders are reported. Hence, it is important to characterize the interactions between HEV and its host. Here, we investigated the ability of the non-structural polyprotein encoded by the first open reading frame (ORF1) of HEV to modulate the host early antiviral response and in particular the type I interferon (IFN-I) system. We found that the amino-terminal region of HEV-3 ORF1 (MetPCP), containing a putative methyltransferase (Met) and a papain-like cysteine protease (PCP) functional domain, inhibited IFN-stimulated response element (ISRE) promoter activation and the expression of several IFN-stimulated genes (ISGs) in response to IFN-I. We showed that the MetPCP domain interfered with the Janus kinase (JAK)/signal transducer and activator of transcription protein (STAT) signalling pathway by inhibiting STAT1 nuclear translocation and phosphorylation after IFN-I treatment. By contrast, MetPCP had no effect on STAT2 phosphorylation and a limited impact on the activation of the JAK/STAT pathway after IFN-II stimulation. This inhibitory function seemed to be genotype-dependent as MetPCP from HEV-1 had no significant effect on the JAK/STAT pathway. Overall, this study provides evidence that the predicted MetPCP domain of HEV ORF1 antagonises STAT1 activation to modulate the IFN response.

Trichomes are a common morphological defense against pests, in particular, type IV glandular trichomes have been associated with resistance against different invertebrates. Cultivated tomatoes usually lack or have a very low density of type IV trichomes. Thus, specific breeding programs to incorporate these natural defences, that are common within the Solanum genus, might improve a more sustainable management. We have identified a S. pimpinellifolium accession with very high density of this type of trichomes. Two F2 mapping populations using two different parents have been developed, characterized and genotyped using a new genotype methodology, K-seq. We have been able to build an ultra-dense genetic map with 147,326 markers with an average distance between markers of 0.2 cM that has allowed us to perform a detailed mapping. We have used two different families and two different approaches, QTL mapping and QTL-seq, to identify several QTLs implicated in the control of trichome type IV developed in this accession on the chromosomes 5, 6, 9 and 11. The QTL located on chromosome 9 is a major QTL that has not been previously reported in S. pimpinellifolium that increases by a factor of 9 the density of trichomes.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

The COVID-19 outbreaks have caused universities all across the globe to close their campuses and forced them to initiate online teaching. This article reviews the pedagogical foundations for developing effective distance education practices, starting from the assumption that promoting autonomous thinking is an essential element to guarantee full citizenship in a democracy and for moral decision making in situations of rapid change, which has become a pressing need in the context of a pandemic. In addition, the main obstacles related to this new context are identified, and solutions are proposed according to the existing bibliography in learning sciences.

Quadruplex-interactive small molecules have a wide potential application, not only as drugs but also as sensors of quadruplexes structures. The purpose of this work is the synthesis of analogues of the bis-methylquinolinium-pyridine-2,6-dicarboxamide G4 ligand 360A, to identify relevant structure-activity relationships to apply to the design of other G4-interactive small molecules bearing bis-quinoline or bis-isoquinoline moieties. Thermal denaturation experiments revealed that non-methylated derivatives with a relative 1,4 position between the amide linker and the nitrogen of the quinoline ring are moderate G4 stabilizers, with a preference for the hybrid h-Telo G4. Insertion of a positive charge upon methylation of quinoline/isoquinoline nitrogen increases compounds capacity to selectively stabilize G4s compared to duplex DNA, with a preference for parallel structures. Among these, compounds having a relative 1,3-position between the charged methylquinolinium/isoquinolinium nitrogen and the amide linker are the best G4 stabilizers. More interestingly, these ligands showed different capacities to selectively block DNA polymer-ization in a PCR-stop assay and to induce G4 conformation switches of hybrid h-Telo G4. Mo-lecular dynamic simulations with the parallel k-RAS G4 structure showed that the relative spatial orientation of the two methylated quinoline/isoquinoline rings determines the ligands mode and strength of binding to G4s.

The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported an extremely high number of positive cases and deaths, while some reported too few COVID-19 related cases and mortality. In this paper, the factors that could affect the transmission of COVID-19 and its risk level in different counties have been determined and analyzed. Using Pearson Correlation, K-means clustering, and several classification models, the most critical ones were determined. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, percentage of rural areas, and percent of uninsured people in each county were the most significant and effective attributes.

Hyper-spectral images contain a wide range of bands or wavelength due to which they are rich in information. These images are taken by specialized sensors and then investigated through various supervised or unsupervised learning algorithms. Data that is acquired by hyperspectral image contain plenty of information hence it can be used in applications where materials can be analyzed keenly, even the smallest difference can be detected on the basis of spectral signature i.e. remote sensing applications. In order to retrieve information about the concerned area, the image has to be grouped in different segments and can be analyzed conveniently. In this way, only concerned portions of the image can be studied that have relevant information and the rest that do not have any information can be discarded. Image segmentation can be done to assort all pixels in groups. Many methods can be used for this purpose but in this paper, we discussed k means clustering to assort data in AVIRIS cuprite, AVIRIS Muffet and Rosis Pavia in order to calculate the number of regions in each image and retrieved information of 1st, 10th and100th band. Clustering has been done easily and efficiently as k means algorithm is the easiest approach to retrieve information.

Abstract: Escherichia coli are remarkably versatile microorganisms and important members of the normal intestinal microbiota of humans and animals. This harmless commensal organism can acquire a mixture of comprehensive mobile genetic elements that contain genes encoding viru-lence factors, becoming an emerging human pathogen capable of causing a broad spectrum of intestinal and extraintestinal diseases. Nine definite enteric E. coli pathotypes have been well characterized, causing diseases ranging from various gastrointestinal disorders to urinary tract infections. These pathotypes employ many virulence factors and effectors subverting the func-tions of host cells to mediate its virulence and pathogenesis. This review summarizes new de-velopments in our understanding of diverse virulence factors associated encoding genes used by different pathotypes of enteric pathogenic E. coli to cause intestinal and extraintestinal diseases in humans.

This paper presents an alternative process to fabricate flexible bandpass filters by using embroidered yarn conductor on electronic-textile. The novelty of the proposed miniaturized filter is its complete integration on the outfit, with benefits in terms of compressibility, stretch ability and high geometrical accuracy, opening the way to develop textile filters in sport and medicine wearable applications. The proposed design consists of a fully embroidered microstrip topology with a length equal to quarter wavelength (λ/4) to develop a bandpass filter frequency response. A drastic reduction in size of the filter was achieved by taking advantage of a simplified architecture based on meandered-line stepped impedance resonator. The e-textile microstrip filter has been designed, simulated, fabricated and measured, with experimental validation at a 7.58 GHz frequency. The insertion loss obtained by simulation of the filter is substantially small. The return loss is greater than 20 dB for bands. To explore the relations between physical parameters and filter performance characteristics, theoretical equivalent circuit model of the filter constituent components were studied. The effect of bending of the e-textile filter is also studied. The results show that by changing the radius of bending up to 40 mm, the resonance frequency is shifted up 4.25 MHz/mm.

Abstract: Commercialization of extra virgin olive oil (EVOO) requires a best before date recom-mended at up to 24 months after bottling, stored under specific conditions. Thus, it is expected that the product retains its chemical properties and preserves its ‘extra virgin’ category. However, in-adequate storage conditions could alter the properties of EVOO. In this study, Arbequina EVOO was exposed to five storage conditions for up to one year to study the effects on the quality of the oil and the compounds responsible for flavor. Every 15 or 30 days, samples from each storage condition were analyzed determining physicochemical parameters, the profiles of phenols, volatile compounds, α-tocopherol and antioxidant capacity. Principal component analysis was utilized to better elucidate the relationships between composition of EVOOs and the storage conditions. EVOOs stored at -23 and 23 °C in darkness and 23 °C with light, differed from the oils stored at 30 and 40 °C in darkness. The former were associated with higher quantity of non-oxidized phenolic compounds and the latter with higher elenolic acid, oxidized oleuropein and ligstroside derivatives, which also increased with storage time. E-2-Nonenal (detected at trace levels in fresh oil) was selected as a marker of the degradation of Arbequina EVOO quality over time, with significant linear regressions identified for the storage conditions at 30 and 40 °C. Therefore, early oxidation in EVOO could be monitored by measuring E2-Nonenal levels.

E-learning with many outstanding advantages in training has drastically changed the self-study process due to the ability to personalize and effectively meet the learning activities of learners. E-learning and building an e-learning environment are currently paying attention and being deployed in many universities in Vietnam with different scope and levels. Especially in the current period, when science and technology are developing, many applications of technology and technology products have been applied in the field of education, changing the way of teaching and learning activities, the practice of both lecturers and students. Big Data and Artificial Intelligence (AI) technologies have replaced people not only for manual labor but also for intellectual labor, including the teaching of teachers. Many software applications have been used to replace people in the transmission of knowledge, testing, and evaluation of training quality, especially E-learning online training programs. However, in Vietnam today, the output quality of these online training programs has not been highly appreciated compared to similar programs in the world. The cause of this situation is that the training, teaching, and learning are not effective. Therefore, in this article, I will give some analysis, evaluate the current teaching and learning methods and propose solutions to enhance the interaction and initiative in the teaching and learning process of lecturers and students to improve the quality of online training in the future.

In this paper, we consider the relation of more than four harmonic points in a line. For this purpose, starting from the dependence of the harmonic points, Desargues’ theorems, and perspectivity, we note that it is necessary to conduct a generalization of the Desargues’ theorems for projective complete n-points, which are used to implement the definition of the generalization of harmonic points. We present new findings regarding the uniquely determined and constructed sets of H-points and their structure. The well-known fourth harmonic points represent the special case (n=4) of the sets of H-points of rank 2, which is indicated by P42.

The Lamiaceae belong to the species-richest families of flowering plants and harbor many species used as herbs or for medicinal applications, such as Basils or Mints. Evolution of this group has been driven by chemical speciation, mainly of Volatile Organic Compounds (VOCs). The commercial use of these plants is characterized by a large extent of adulteration and surrogation. To authenticate and discern the species, is, thus, relevant for consumer safety, but usually requires cumbersome analytics, such as Gas Chromatography, often to be coupled with Mass Spectroscopy. We demon-strate here that quartz-crystal microbalance (QCM)-based electronic noses provide a very cost-efficient alternative, allowing for a fast, automated discrimination of scents emitted from leaves of different plants. To explore the range of this strategy, we used leaf material from four genera of Lamiaceae along with Lemongrass as similarly scented, but non-related outgroup. In order to unambiguously differentiate the scents from the different plants, the output of the 6 different SURMOF/QCM sensors was analyzed using machine learning (ML) methods, together with a thorough statistical analysis. The exposure and purging datasets (4 cycles) obtained from a QCM-based, low-cost homemade portable e-Nose were analyzed with Linear Discriminant Analysis (LDA) classification model. Prediction accuracies with repeating test measurements reached values of up to 90%. We show that it is not only possible to discern and identify plants on the genus level, but even to discriminate closely related sister clades within a genus (Basil), demonstrating that e-Noses are a powerful technology to safeguard consumer safety against the challenges of globalized trade.

Escherichia coli is the main pathogen responsible for extraintestinal infections. A total of 196 clinical E. coli consecutively isolated during 2016 in Spain (100 from Lucus Augusti hospital in Lugo) and France (96 from Beaujon hospital in Clichy) were characterized. Phylogroups, clonotypes, sequence types (STs), O:H serotypes, virulence factor (VF)-encoding genes and antibiotic resistance were determined. Approximately 10% of the infections were caused by ST131 isolates in both hospitals and approximately 60% of these infections were caused by isolates belonging to only 10 STs (ST10, ST12, ST58, ST69, ST73, ST88, ST95, ST127, ST131, ST141). ST88 isolates were frequent especially in Spain while ST141 isolates significantly predominated in France. The 23 ST131 isolates displayed four clonotypes: CH40-30, CH40-41, CH40-22 and CH40-298. Only 13 (6.6%) isolates were carriers of ESBL enzymes. However, 37.2% of the isolates were multidrug-resistant (MDR). Approximately 40% of the MDR isolates belonged to only four of the dominant clones (B2-CH40-30-ST131, B2-CH40-41-ST131, C-CH4-39-ST88 and D-CH35-27-ST69). Among the remaining MDR isolates two isolates belonged to B2-CH14-64-ST1193 i.e the new global emergent MDR clone. To our knowledge, it is the first identification of this emergent clone in Spain. Moreover, a hybrid ExPEC/enteroaggregative isolate belonging to A-CH11-54-ST10 clone was identified.

Mast cells are long-lived, granular, myeloid-derived leukocytes that have significant protective and repair functions in tissues. Mast cells sense disruptions in the local microenvironment and are first responders to physical, chemical and biological insults. When activated, mast cells release growth factors, proteases, chemotactic proteins and cytokines thereby mobilizing and amplifying the innate and adaptive immune system. Mast cells are therefore significant regulators of homeostatic functions and may be essential in microenvironmental changes during pathogen invasion and disease. During infection by helminths, bacteria and viruses, mast cells release antimicrobial factors to facilitate pathogen expulsion and eradication. Mast cell-derived proteases and growth factors protect tissues from insect/snake bites and exposure to ultraviolet radiation. Finally, mast cells release mediators that promote wound healing in the inflammatory, proliferative and remodeling stages. Since mast cells have such a powerful repertoire of functions, targeting mast cells may be an effective new strategy for immunotherapy of disease and design of novel vaccine adjuvants. In this review, we will examine how certain strategies that specifically target and activate mast cells can be used to treat and resolve infections, augment vaccines and heal wounds. Although these strategies may be protective in certain circumstances, mast cells activation may be deleterious if not carefully controlled and any therapeutic strategy using mast cell activators must be carefully explored.

Toxins present in cigarette and e-cigarette smoke constitute a significant cause of illnesses and are known to have fatal health impacts. Specific mechanisms by which toxins present in smoke impair cell repair are still being researched and are of prime interest for developing more effective treatments. Current literature suggests toxins present in cigarette smoke and aerosolized e-vapor trigger abnormal intercellular responses, damage mitochondrial function, and consequently disrupt the homeostasis of the organelle’s biochemical processes by increasing reactive oxidative species. Increased oxidative stress sets off a cascade of molecular events, disrupting optimal mitochondrial morphology and homeostasis. Furthermore, smoking-induced oxidative stress may also amalgamate with other health factors to contribute to various pathophysiological processes. An increasing number of studies show that toxins may affect mitochondria even though exposure to secondhand or thirdhand smoke. This review assesses the impact of toxins present in tobacco smoke and e-vapor on mitochondrial health, networking, and critical structural processes including mitochondria fission, fusion, hyperfusion, fragmentation, and mitophagy. The efforts are focused on discussing current evidence linking toxins present in first, second, and thirdhand smoke to mitochondrial dysfunction

Abstract Introduction: Antimicrobial resistance (AMR) is a recognised public health threat today globally. Though many active and passive stewardship strategies are employed to counter AMR clinically, educating school going children on AMR could be a futuristic cost-effective measure to minimize AMR development. We hypothesised NICE’s e-bug module to class VII school students on AMR determinants. Methodology: A prospective non-randomized intervention study on 327 students belonging to 9 schools of class VII around Manipal town, Udupi district, Karnataka state, India were included for the study. 10 questions on AMR determinants extracted from NICE’s e-bug program were quizzed in written as pre-test followed by an education intervention on the same questions followed by a post-test to end the session. Descriptive statistics to estimate epidemiological characteristics, Wilcoxon Signed Ranks and Kruskal-Wallis tests were applied to analyse statistical significance of pre/post-test performance scores for the 10 questions and between schools respectively Results: Students had inadequate knowledge on 7 AMR determinants (antimicrobial indication, its course, hand hygiene, fermentation, spread of infection, microbial multiplication and characteristics of microbe) when analysed for post-test performance (p<0.05). Comparison of post-test performance of 9 participating schools revealed statistical significance (p<0.05) for 3 questions (definition on antimicrobial, cover while cough/sneezing and microbial characteristics) Conclusion: Although students exhibited sub-optimal knowledge on few AMR determinants, they showed keenness to learn exhibited by their performance. Our findings and previous similar studies from Europe are suggestive of early pedagogic interventions on AMR through inclusion of such education modules in the curriculum could be potential tool for AMR prevention for future generations.

This article aims to investigate gaps in the law and policies on e-waste management in communi-ties of Thailand and suggests a guideline for improving, developing, and designing legal measures and state policies for more effective enforcement of the law on e-waste management in communities. The findings reveal that the currently applicable law of Thailand lacks effective approaches and rules for e-waste management. Also, there is not any implementation of key envi-ronmental principles for e-waste management in communities, such as the Polluter Pays Principle (PPP) that requires manufacturing companies to take part in being responsible for disposal ex-penses or the Public Participation principle that requires users, manufacturers, distributors, and government agencies to take parts in disposing e-waste. As a result, problems of e-waste in com-munities of Thailand have been continuously increasing. According to such problems, the authors suggest that legal measures on e-waste management in communities should be specifically de-signed by implementing key environmental principles as a basis in determining formats and guidelines of e-waste management, especially participation of all sectors that can help in solving and reducing e-waste in communities that is harmful to health, sanitation, and environment.

Air passenger traffic prediction is crucial for the effective operation of civil aviation airports. Despite some progress in this field, the prediction accuracy and methods need further improvement. This paper proposes an integrated approach to the prediction of air passenger index as follows. Firstly, the air passenger index is defined and classified by the K-means clustering method. Based on the mutual information (MI) principle, the information entropy is used to analyze and select the key influencing factors of air passenger travel. By incorporating the MI principle into the support vector regression (SVR) framework, this paper presents an innovative MI-SVR machine learning model used to predict the air passenger index. Finally, the proposed model is validated by passenger throughput data of the Shanghai Pudong International Airport, China. The experimental results prove the model feasibility and effectiveness by comparing them with conventional methods, such as ARIMA, LSTM, and other machine learning models, outperformed by the MI-SVR model. Besides, it is shown that the prediction effect of each model could be improved by introducing influencing factors based on mutual information. The main findings are considered instrumental to the airport operation and air traffic optimization.

Specifically this work is based on the concept of ‘dark energy’ as a phenomenal effect of expansion through which a theoretical value of Hubble’s constant has been introduced. It is a constant that is based on a postulate that the square root of ratio of the Siva’s constant ‘K’ and Hubble’s constant ‘H’ is exactly equal to the diameter of the neutral hydrogen atom. That is the, exact theoretical value of Hubble’s constant. This is always constant .However, space-time conversions and the changes in the velocity of light will affect the distance and velocity in Hubble’s equation. Deviation factors in velocity, distance and the Hubble’s constant have been calculated separately which are affected by change of velocity of light with expansion of space time. The observations are related to red shift. So the change factor in terms of Hubble’s constant has been calculated with respect to red shift. Thus a factor which affects the theoretical Hubble’s constant has been calculated to find the exact value of Hubble’s constant that satisfies the experimental results. The present theoretical value of Hubble’s constant has been calculated. The experimental results by plank, ACT (Atacama Cosmology Telescope), WMAP (Wilkinson Microwave Anisotropy Probe) etc. experiments are at par with the theoretical result. Thus the ontology of space time introduced in this theoretical work supposed to be correct and leads to a new theory of origin of universe for which a brief description has been provided.

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using as input medical reference texts and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false and match), can have customizable length and difficulty and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.

The growth of the fаshion industry in Bаndung, which is increаsing every yeаr, if it is not bаlаnced with the аpplicаtion of digitаlizаtion аnd the use of the lаtest technology, it would be very unfortunаte. Аpаrt from the increаse in the number of internet users, the online shopping style by the community is аlso one of the driving forces for the growth of e-commerce, especiаlly in the midst of the current Covid pаndemic situаtion. This study will exаmine the аdoption of e-commerce technology to sell online in the midst of the Covid pаndemic to fаshion industry plаyers in Bаndung using these vаriаbles: effort expectаncy, performаnce expectаncy, fаcilitаting conditions, sociаl influence, existing hаbits, hedonic motivаtion, and also the price vаlue in the UTАUT2 model. So thаt it cаn show how the contribution of the аdoption of e-commerce technology to the behаviourаl intention аnd use behaviour of the fаshion industry consumers in Bаndung. Our research use quаntitаtive approach, cаusаl research/study with Structurаl Equаtion Modeling (SEM) аnаlysis technique using the SMАRTPLS 3.2.9 softwаre. Reseаrchers chose the аccidentаl sаmpling with а totаl of 400 respondents. Аll exogenous vаriаbles аffect behаviourаl intention by 80.9% аnd 54.9% on use behаviour.

The USDA-FSIS considers mechanically-tenderized beef as ‘non-intact’ and a food safety concern because of the potential for translocation of surface E. coli O157:H7 into the interior of the meat that may be cooked ‘rare or medium-rare’ and consumed. We evaluated 14 potential spray interventions on E. coli O157:H7-inoculated lean beef wafers (~10⁶ CFU/cm² , n=80) passing through a spray system (18 sec dwell time, ~40 PSI) integrated into the front end of a Ross TC-700MC tenderizer. Inoculated and processed beef wafers were stomached with D/E neutralizing broth and plated immediately, or were held in refrigerated storage for 1-, 7-, or 14 days prior to microbial plating. Seven antimicrobials that showed better performance in preliminary screening on beef wafers were selected for further testing on beef subprimals in conjunction with blade tenderization. Boneless top sirloin beef subprimals were inoculated at ~2 x 10⁴ CFU/cm² with a four-strain cocktail of Escherichia coli O157:H7 and passed once, lean side up, through an integrated spray system and blade tenderizer. Core samples obtained from each subprimal were examined for the presence/absence of E. coli O157:H7. Absence of E coli O157:H7 translocated into core samples correlated with the ability of the antimicrobials to reduce bacterial levels on the surface of beef prior to blade tenderization.