Maintaining an adequate micronutrient status can be achieved by following a complete, diverse diet. Yet, food trends in Western countries show suboptimal consumption of healthy nutrients. In this study we explored the prevalence of vitamin and mineral imbalances in a general population cohort of Dutch adults, and evaluated the effect of a digital lifestyle program on the nutritional status and nutrition health behaviors of these individuals. A micronutrient panel was measured in 348 participants, alongside a dietary assessment. One-hundred users subsequently underwent a remeasurement. We identified at least one nutritional imbalance in 301 individuals (86.5%). 80% improved and normalized B6, 67% improved folate, 70% improved B12, and 86% improved vitamin D. Iron abnormalities were corrected in 75% of participants. In conclusion, this study found micronutrient deficiencies of easily obtainable vitamins through diet or supplementation such as B vitamins and vitamin D were more prevalent than expected in a Dutch population. This can partly be explained by an insufficient consumption of food groups rich in B vita-mins. Our preliminary results in those remeasured after a digitally-enabled lifestyle intervention show these imbalances can be corrected with adequate behavioral support in a “food as medicine” approach complemented with supplementation where needed.

Worldwide, it is estimated that at least 1 in 4 adults suffers from hypertension, and this number is expected to increase as populations grow and age. Blood pressure (BP) possesses substantial heritability, but is also heavily modulated by lifestyle factors. As such, digital, lifestyle-based in-terventions are a promising alternative to standard care for hypertension prevention and man-agement. In this study we assessed the prevalence of elevated and high BP in a Dutch general pop-ulation cohort undergoing a health screening, and observed the effects of a subsequent self-initiated, digitally-enabled lifestyle program on BP regulation. Baseline data were available for 348 participants, of which 56 had partaken in a BP-focused lifestyle program and got re-measured 10 months after the intervention. Participants with elevated SBP and DBP at baseline showed a mean decrease of 7.2 mmHg and 5.4 mmHg, respectively. Additionally, 70% and 72.5% of participants showed an improvement in systolic and diastolic BP at remeasurement. These improvements in BP are superior to those seen in other recent studies. The long-term sustainability and the efficacy of this and similar digital lifestyle interventions will need to be estab-lished in additional, larger studies.

Mitochondria are dynamic organelles ubiquitously present in nucleated eukaryotic cells, subserving multiple metabolic functions, including cellular ATP generation by oxidative phosphorylation (OXPHOS). The OXPHOS machinery comprises five transmembrane respiratory chain enzyme complexes (RC). Defective OXPHOS gives rise to mitochondrial diseases (mtD). The incredible phenotypic and genetic diversity of mtD can be attributed at least in part to the RC dual genetic control (nuclear DNA [nDNA] and mitochondrial DNA [mtDNA]) and the complex interaction between the two genomes. Despite the increasing use of next-generation-sequencing (NGS) and various -omics platforms in unraveling novel mtD genes and pathomechanisms, current clinical practice for investigating mtD essentially involves a multipronged approach including clinical assessment, metabolic screening, imaging, pathological, biochemical and functional testing to guide molecular genetic analysis. This review addresses the broad muscle pathology landscape including genotype-phenotype correlations in adult and paediatric mtD, the role of immunodiagnostics in understanding some of the pathomechanisms underpinning the canonical features of mtD, and recent diagnostic advances in the field.

The development of the Internet of Things (IoT) has triggered a virtual wave of interconnection and intercommunication among an enormous number of universal things. This has caused an exceptional surge of colossal heterogeneous information, known as an information explosion. Until now, cloud computing has filled in as a proficient method to process and store these data. Still, it came to light that by utilizing just cloud computing, pesky issues like, the expanding requests of actual-time or speed-sensitive applications and the restrictions on system transfer speed could not be solved. Consequently, another computing platform, called fog computing has been advanced as a supplement to the cloud arrangement. Fog computing spreads the cloud administrations and services to the edge of the system, and brings processing, communications and reserving and storage capacity closer to edge gadgets and end-clients and, in the process, aims at enhancing versatility, low latency, transfer speed and safety and protection. This paper takes an extensive and wide-ranging view of fog computing, covering several aspects. At the outset is outlined the many-layered structural design of fog computing and its attributes. After that, chief advances like communication and inter-exchange, computing, reserving and storage, asset administration, naming, safety and safeguarding of privacy are delineated while showing how this backup and facilitate the installations and various applications. Then, numerous applications like augmented reality (AR), healthcare, gaming and brain-machine interface, vehicular computing, smart scenarios etc. are highlighted to explain the fog computing application milieu. Following that, it is shown that how, despite fog computing being a features-rich platform, it is dogged by its susceptibility to several security, privacy and safety concerns, which stem from the nature of its widely distributed and open architecture. Finally, some suggestions are advanced to address some of the safety challenges discussed so as to propel the further growth of fog computing.

Mobile Cloud Computing(MCC) is a recent technology used by various users worldwide. In 2015, more than 240 million users used mobile cloud computing which gives a profit of $5.2 billion to service providers. MCC is a combination of Mobile computing and cloud computing. By the combination of these two, it gives various challenges like network access, elasticity, management, availability, security, privacy, etc. Here security issues are considered because both the security issues of mobile computing and cloud computing are considered as important like data security, virtualization security, partitioning security, Mobile cloud application security, Mobile device security. This paper gives a detailed study of security issues in mobile cloud computing and its prevention measures.

This paper focuses on the crucial role that remote sensing plays in divining land features. Data that is collected distantly provides information in spectral, spatial, temporal and radiometric domains, with each domain having the specific resolution to information collected. Diverse sectors such as hydrology, geology, agriculture, land cover mapping, forestry, urban development and planning, oceanography and others are known to use and rely on information that is gathered remotely from different sensors. In the present study, IRS LISS IV Multi-spectral data is used for land cover mapping. It is known, however, that the task of classifying high-resolution imagery of land cover through manual digitizing consumes time and is way too costly. Therefore, this paper proposes accomplishing classifications by way of enforcing algorithms in computers. These classifications fall in three classes: supervised, unsupervised, and object-based classification. In the case of supervised classification, two approaches are relied upon for land cover classification of high-resolution LISS-IV multispectral image. These approaches are Maximum Likelihood and Support Vector Machine (SVM). Finally, the paper proposes a step-by-step procedure for optical image classification methodology. This paper concludes that in optical data classification, SVM classification gives a better result than the ML classification technique.

Extracellular vesicles (EVs) have been identified as novel mediators of intercellular communication. They work via delivering the sequestered cargo to cells in close vicinity as well as distant sites in the body, regulating pathophysiological processes. Cell death and inflammation are biologically crucial processes in both normal physiology and pathology. These processes are indistinguishably linked with their effectors modulating the other process. For instance, during an unresolvable infection, the upregulation of specific immune mediators leads to inflammation causing cell death and tissue damage. EVs have gained considerable interest as mediators of both cell death and inflammation during conditions such as sepsis. This review summarizes the types of extracellular vesicles known to date and their roles in mediating immune responses leading to cell death and inflammation with specific focus on sepsis and lung inflammation.

The emergence of Internet of Things (IoT) devices is revolutionizing healthcare. This dynamic healthcare environment relies on Internet of Healthcare Things (IoHT) and Internet of Medical Things (IoMT) technologies. Economic, social, and technological opportunities from the IoHT are transforming healthcare systems. This article covers the history, present condition, and future prospects of IoHT, as well as its topologies, platforms, services, applications, market trends, and solution types. It examines security issues, requirements, and a threat taxonomy, studying smart healthcare privacy and security. It explores future research and the challenges IoHT-based solutions face. International health rules and regulations based on the IoT and their social and economic effects on long-term development are also examined. Integrating IoMT into healthcare infrastructures enhances scalability, efficiency, reliability, and accuracy. Through communication networks and data-processing algorithms, IoMT creates smart hardware and software platforms that enhance decision-making. IoMT devices' low resources raise privacy and security concerns. Security and privacy issues are organised by healthcare IoMT adoption in this study. We give an extensive attack taxonomy against the IoMT infrastructure, encompassing devices, security mechanisms, and their pros and cons. Furthermore, it describes the privacy and security requirements for any unique security solutions against IoMT's multiple attack vectors. This article explains the complicated difficulties, security concerns, and future research pathways needed to safeguard and ensure the long-term expansion of these game-changing technologies in the healthcare ecosystem.

The term Concept has been a prominent part of investigations in psychology and neurobiology where, mostly, it is mathematically or theoretically represented. The Concepts are also studied computationally through their symbolic, distributed and hybrid representations. The majority of these approaches focused on addressing concrete concepts notion, but the view of the abstract concept is rarely explored. Moreover, most computational approaches have a predefined structure or configurations. The proposed method, Regulated Activation Network (RAN), has an evolving topology and learns representations of Abstract Concepts by exploiting the geometrical view of Concepts, without supervision. In the article, the IRIS data was used to demonstrate: the RAN's modeling; flexibility in concept identifier choice; and deep hierarchy generation. Data from IoT's Human Activity Recognition problem is used to show automatic identification of alike classes as abstract concepts. The evaluation of RAN with 8 UCI benchmarks and the comparisons with 5 Machine Learning models establishes the RANs credibility as a classifier. The classification operation also proved the RAN's hypothesis of abstract concept representation. The experiments demonstrate the RANs ability to simulate psychological processes (like concept creation and learning) and carry out effective classification irrespective of training data size.

RaTG13 (a bat derived SARS-like CoV) is the closest relative sequence of SARS-CoV-2 reported till date. The sample from which RaTG13 was sequenced was a bat fecal swab collected in 2013 from Tongguan, Mojiang, Yunnan province, China. The Illumina based sequence of RaTG13, MN996532.1, was deposited on 27^th Jan 2020 and the raw data (Illumina), https://www.ncbi.nlm.nih.gov/sra/SRX7724752[accn]. There are discrepancies in dates about when the metagenome sequencing of RaTG13 sample was done (2018 or 2020), both stated by the same corresponding author. Comparison of the RNA Seq data of RaTG13 fecal swab to the corresponding data from the bat fecal swabs deposited by the same working group using the same methods indicated that the RaTG13 raw data seemed to be different in various aspects. The fecal swab sample showed abnormally less read of bacterial reads in the swab was exceptionally low, i.e. 0.7%, compared to the 20-90% abundance in other fecal swabs from bats processed by similar methods. Also, another raw data in the form of amplicon sequences was deposited in May 2020; however, the dates mentioned on the files of the sequenced amplicons were older (2017, 2018). The genome assembly of RaTG13 could not be done de-novo and the average coverage of the genome ~8%. Also, literature indicates that RaTG13 RBD cannot bind to Rhinolophus ACE-2 receptors. Collectively, the anomalies in the raw data of RaTG13 and other issues pose an important question about the overall authenticity of the RaTG13 genome sequence.

High-flow Nasal Cannula (HFNC) oxygen therapy is gaining traction globally as a treatment for respiratory failure. There are several physiological benefits and there may be a growing patient preference for HFNC. In this narrative review, we aim to outline the basic mechanisms of HFNC, who can use it and review the literature regarding its utility both in the critical care setting, as well as in the home setting for chronic hypercapnic respiratory failure with an emphasis on Chronic Obstructive Pulmonary Disease (COPD). The role of non-pharmacological interventions like non-invasive ventilation (NIV) and HFNC in the prevention of hospital readmissions following acute exacerbations of COPD (AECOPD) is an area of increasing importance because randomised controlled trials and systematic reviews have found measures like nurse-led predischarge bundles to be clinically ineffective and to have a high cost per quality adjusted life year. This review therefore considers the evidence of NIV vs HFNC in the context of AECOPD and the application of HFNC at home in the prevention of AECOPD. We also look at applications of HFNC in specific settings, such as in the peri-operative period, emergency department, acute (mainly Critical Care) setting including in immunocompromised patients and palliative care.

Since the origin of COVID-19, everyone is getting accustomed to the new rules and regulations, travel restrictions and new lifestyle. Constant changes in the government advisories and the COVID-19 guidelines poses a real challenge for children to adapt to causing stress, anxiety and other mental health issues. Therefore, it is imperative to raise awareness about the challenges that Indian children are dealing with to help them better cope with this stressful and frantic time. The focus of this review is on various child-related problems that the Indian government is trying to tackle such as stress, depression, malnutrition, school closures, digital divide, child labor, child trafficking in context of mental health issues caused by them during COVID-19. Highlights:The reader will come to appreciate that: Digital-divide caused by shifting offline learning to online mode. Strategies implemented by Indian government to combat malnutrition Effect of COVID-19 lockdown on children suffering from mental disorders Child labor and trafficking and the strategies that aim to decrease child labor during the pandemic Educating the children appropriately regarding COVID protocols

The wind flow patterns and pressure distribution around a plus-shaped building are significantly influenced by the dimensions of its re-entrant corners and the overall building height. The present study aims to find the wind effects and study of the pressure distribution with different flow patterns. Plan area of the building is around 300 square meter while the height of the building is 50 meters by keeping the equal length of the re-entrant corners. The research is performed using ANSYS CFX academic version and the results are depicted in various forms such as pressure coefficient (Cpe), stream lines in both vertical as well as in specific surface and pressure contours. The analysis is carried out by varying the wind incident angles, from 0° to 90° at the interval of 15°. The building dimension are scale down to perform the test on length scale of 1:100. Since the considered building model exhibits symmetry along both the axes, present study mostly emphasis on examining re-entrant corners located in the building. This method yields valuable information about how air circulates and how pressure is distributed across a broad spectrum of wind angles. This study provides valuable insights into flow circulation and pressure distribution for a wide range of wind angles.

Building situated in the flow path of wind is subjected to differential velocity and pressure distribution around the building envelope. Wind effects are influenced and vary for each individual shape of the tall building. Tall building structures are considered as cantilever structures with fixed ends at the ground. Wind exponential velocity acting along the height of the building makes velocity and pressure distribution more complex as the height of the building structure increases. This study discussed the effect of wind on an irregular cross-section shape. The study was conducted numerically with a building model placed in a virtual wind tunnel using the ANSYS (CFX) software tool. Wind effects are investigated on building model situated in a terrain category - II defined in IS: 875 (Part 3): 2015 wind scale model of 1:100 and turbulence intensity is 5 % and power law index α is considered as 0.143. Validation and verification of the study were made by comparing pressure coefficients on faces of a rectangular model of similar floor area and height as taken for a C-plan diamond-shaped model under similar boundary conditions, wind environment, and solver setting of numerical setup. The values of surface pressures generated on the recessed faces of the model and wind flow patterns within the recessed cavity were studied at wind incident angles 0°, 300, 60°, 1050, 1350 & 1800. The critical suction on all the recessed faces was observed to be at a 105° angle of wind attack.

Although Support Vector Machines (SVM) are widely used for classifying human motion patterns, their application in the automatic recognition of dynamic and static activities of daily life in the healthy older adults is limited. Using a body mounted wireless inertial measurement unit (IMU), this paper explores the use of SVM approach for classifying dynamic (walking) and static (sitting, standing and lying) activities of the older adults. Specifically, data formatting and feature extraction methods associated with IMU signals are discussed. To evaluate the performance of the SVM algorithm, the effects of two parameters involved in SVM algorithm—the soft margin constant C and the kernel function parameter $\mathsf{\gamma }$—are investigated. The changes associated with adding white-noise and pink-noise on these two parameters along with adding different sources of movement variations (i.e., localized muscle fatigue and mixed activities) are further discussed. The results indicate that the SVM algorithm is capable of keeping high overall accuracy by adjusting the two parameters for dynamic as well as static activities, and may be applied as a tool for automatically identifying dynamic and static activities of daily life in the older adults.

Transplanted rice cultivation has caused groundwater depletion in several regions globally. Direct-seeded rice under aerobic conditions is a water-saving alternative. However, under aerobic conditions, iron in the soil is oxidized from ferrous to ferric, which is not easily available for rice, resulting in iron deficiency induced chlorosis (IDIC) causing significant reduction in yield. Cultivated rice genotypes have limited variations for IDIC tolerance, while wild Oryza germplasm could be a potential source for IDIC tolerance. In this study, 313 Oryza accessions were evaluated for IDIC tolerance at the tillering stage under aerobic conditions and twenty IDIC tolerant lines were identified. The twenty lines showed no signs of chlorosis and had high levels of iron content and SPAD values, while eight cultivated controls exhibited varying degrees of chlorosis symptoms and low levels of SPAD and iron content. To confirm their tolerance, the selected lines were evaluated again in a subsequent year, and they showed comparable levels of tolerance indicating these lines were efficient in iron uptake and utilization resulted maintained high chlorophyll and leaf area index. These accessions may be useful for developing IDIC-tolerant cultivars for aerobic rice cultivation and future study of molecular basis of IDIC tolerance.

The technique of obtaining information or data about any feature or object from afar, called in technical parlance as remote sensing, has proven extremely useful in diverse fields. In the ecological sphere, especially, remote sensing has enabled collection of data or information about large swaths of areas or landscapes. Even then, in remote sensing the task of identifying and monitoring of different water reservoirs has proved a tough one. This is mainly because getting correct appraisals about the spread and boundaries of the area under study and the contours of any water surfaces lodged therein becomes a factor of utmost importance. Identification of water reservoirs is rendered even tougher because of presence of cloud in satellite images, which becomes the largest source of error in identification of water surfaces. To overcome this glitch, the method of the shape matching approach for analysis of cloudy images in reference to cloud-free images of water surfaces with the help of vector data processing, is recommended. It includes the database of water bodies in vector format, which is a complex polygon structure. This analysis highlights three steps: First, the creation of vector database for the analysis; second, simplification of multi-scale vector polygon features; and third, the matching of reference and target water bodies database within defined distance tolerance. This feature matching approach provides matching of one to many and many to many features. It also gives the corrected images that are free of clouds.

Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two’s limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

Public Transport has been seen since ages as the most environmentally sustainable mode of transport. The users of public transport are diverse and have different socio-economic character. Hence the public transport which is not only supposed to be environmentally sustainable but also envisaged to ensure equity amongst various stakeholders of society like the females, elderly and other vulnerable groups through its service. Gender in binary terms of being differentiated based on men and women is a social construct. Public transport systems in developing countries like India witness socio-cultural factors that shape the experience of women in public spaces by social norms extant in society. Along with this, gender-based issues related to public transport are social and behavioural shortcomings as a consequence of a lack of gender sensitivity. On similar lines, elderly have a negative experience involving safety threats, physical and psychological discomfort while accessing public transport systems. The literature published regarding such issues on the gender and elderly question in public transport systems have been studied and has been brought forth under a stand- alone narrative literature review. A literature review is a prerequisite to conducting either stand-alone reviews or as a preliminary study to be supported with quantitative or qualitative analysis. Here, a stand-alone literature review concerning issues in the public transport system in India has been performed. A narrative type of review is conducted to provide an overview of pre- existing published literature. Narrative overviews are useful educational articles as they help present a broad perspective on a topic and often define the development of a problem and/or ways to manage it. The semi-systematic or narrative-review approach is designed for topics that have been theorized differently and studied within diverse disciplines making it unfavourable to study under a full systematic-review process which majorly caters to reviewing quantitative researches. As narrative-styled literature reviews prefer a semi- systematic data collection method, utmost care has been taken to include perspectives from diverse disciplines. The scope of this review is restricted to summarizing the Indian policies, schemes of public transport in light of socio-equity consideration while narrowing the inherent discrepancies within the socio-cultural ethos of the Indian society which influences socio-equity consideration in public spaces in general and the modes of public transport in particular. Research articles from electronic databases were selected based on relevance to understand the issues this viewpoint, their essential findings and possible recommendations are formulated to provide a comprehensive summary of previous researches.

Dietary components are important for the structural and functional development of the brain. Among these, docosahexaenoic acid,22:6n-3 (DHA) is critically required for the structure and development of the growing fetal brain in utero. DHA is the major n-3 long-chain fatty acid in brain gray matter representing about 15% of all fatty acids in the human frontal cortex. DHA affects neurogenesis, neurotransmitter, synaptic plasticity & transmission, and signal transduction in the brain. Studies in animals and humans show that adequate levels of DHA in neural membranes are important for cortical astrocyte maturation and vascular coupling, and helps cortical glucose uptake and metabolism. In addition, specific metabolites of DHA are bioactive molecules that protect tissues from oxidative injury and stress in the brain. A low DHA level in the brain results in behavior changes and is associated with learning problems and memory deficits. In humans, the third trimester-placental supply of maternal DHA to the growing fetus is critically important as the growing brain obligatory requires DHA during this window period. Besides, DHA is also involved in the early placentation process, essential for placental development. This underscores the critical importance of maternal DHA intake for the structural and functional development of the brain. This review describes DHA's multiple roles during gestation, lactation, and the consequences of its lower intake during pregnancy and postnatally on the children's brain development and function.

Genomic analysis indicates that SARS-CoV-2 is most related to RaTG13, a beta corona virus derived from bats by 96% ¹. At present, RaTG13 is only available on the public database in the form of a genome sequence. The genome of RaTG13 (MN996532.1) was sequenced from the RNA of a bat faecal swab collected in 2013 from Yunnan, China, however the exact location is not mentioned. Since RaTG13 is one of the main supports for SARS-CoV-2 to have a natural origin, it is of utmost importance to understand the sample location. RNA dependent RNA polymerase (RdRp) sequence of RaTG13 shows that it is 100% similar to that of bat corona virus BtCoV/4991 and 98.7-98.9% similar to SARS-CoV-2 RdRp ². BtCoV/4991 was described to be a SARS-like (SL-) corona virus from bat faeces sampled in an abandoned mine from Mojiang ². Both the publications ^1,2 are authored by Dr. Zheng-li Shi (Z-L Shi), who is described as the bat woman of China ³. However, BtCoV/4991 has not been mentioned by Zhou et al 2020 ¹ where novel corona virus was first described. Based on the RdRp sequence similarities, similarities in sample collection dates, sample locations, and the fact that RaTG13 is mentioned synonymous to BtCoV/4991 on the Chinese bat database, it is predicted that RaTG13 and BtCoV/4991 originate from the same sample. The sample, bat faecal swab was collected in 2013 from an abandoned mineshaft in Mojiang by Dr. Shi and her work group. In 2012, in a Mojiang mineshaft, six mine workers suffered from atypical pneumonia and three of them died. These workers were engaged in the work of clearing debris from a mineshaft which had a lot of bats and bat faeces ^3,4. A detailed health investigation indicated that the miners suffered from atypical pneumonia mostly of the viral origin ⁴. Therefore, in the light of the present Covid-19 caused by SARS-CoV-2, the fact that its phylogenetic neighbour RaTG13 originated from bat faeces collected from a mineshaft, which was also the origin of pneumonia-like disease in miners in 2012, should be noted.

This study investigates the complex role of financial risks in the context of public–private partnerships (PPPs) in India and their relationship to the amount and extent of investments made by private partners (s). We hypothesize that subsidies, bid criteria, and risk have a positive relationship with investments made by private partners. A project’s leverage moderates these relationships. Regression was used to analyze the hypotheses using SPSS 24 and PROCESS Macro. Data from the World Bank were collected from 2009 to 2019 for the study variables. Interestingly, our research finds support for these relationships that may seem contrary to some commonly-held notions of risk relationships, such as – the government using ‘viability gap’ funding to attract private investment and ‘leverage’ does not moderate the relationship between risk assumed and private investment. This study is among the first to recognize and elaborate on financial risk relationships, specifically in the context of Indian PPPs. These findings are significant for both private and public participants in terms of financial considerations in PPP projects, especially in emerging markets.

Evidence is emerging on the role of maternal diet, gut microbiota, and other lifestyle factors in establishing lifelong health and disease, which are determined by trans-generationally inherited epigenetic modifications. Understanding epigenetic mechanisms may help identify novel biomarkers for pregnancy-related exposure, burden, or disease risk. Such biomarkers are essential for developing tools for the early detection of risk factors and exposure levels. It is necessary to establish the exposure threshold to the fetus due to nutrient deficiencies or other environmental factors that can lead to clinically relevant epigenetic changes that modulate disease risks. This narrative review summarizes the latest updates on the roles of maternal nutrients (n-3 fatty acids, polyphenols, vitamins) and gut microbiota on the placental epigenome and its impacts on fetal brain development.

Background: Producing, distributing or discussing child sexual abuse materials (CSAM) is often committed through the dark web in order to remain hidden from search engines and regular users. Additionally, on the dark web, the CSAM creators employ various techniques to avoid detection and conceal their activities. The large volume of CSAM on the dark web presents a global social problem and poses a significant challenge for helplines, hotlines and law enforcement agencies. Objective: Identifying CSAM discussions on the dark web and uncovering associated metadata insights into characteristics, behaviours and motivation of CSAM creators. Participants and Setting: We have conducted an analysis of more than 353,000 posts generated by 35,400 distinct users and written in 118 different languages across eight dark web forums in 2022. Out of these, approximately 221,000 posts were written in English and contributed by around 29,500 unique users. Method: We propose a CSAM detection intelligence system. The system uses a manually labelled dataset to train, evaluate and select an efficient CSAM classification model. Once we identify CSAM creators and victims through CSAM posts on the dark web, we proceed to analyze, visualize and uncover information concerning the behaviors of CSAM creators and victims. Result: The CSAM classifier, based on Support Vector Machine model, exhibited good performance, achieving the highest precision of 92.3\%, accuracy of 87.6\% and recall of 84.2\%. Its prediction time is fast, taking only 0.3 milliseconds to process a single post on our laptop. While, the Naive Bayes combination is the best in term of recall, achieving 89\%, and its prediction time is just 0.1 microseconds per post. Across the eight forums in 2022, our Support Vector Machine model detected around 63,000 English CSAM posts and identified near 10,500 English CSAM creators. The analysis of metadata of CSAM posts revealed meaningful information about CSAM creators and their victims, such as: (1) the ages and nationalities of the victims typically mentioned by CSAM creators, (2) forum topics where the CSAM creators assign their posts, and (3) online platforms preferred by CSAM creators for sharing or uploading CSAM. Conclusion: Our CSAM detection system exhibits high performance in precision, recall, and accuracy in real-time when classifying CSAM and non-CSAM posts. Additionally, it can extract and visualize valuable and unique insights about CSAM creators and victims by employing advanced statistical methods. These insights prove beneficial to our partners, i.e. national hotlines and child agencies.

As digital communication becomes increasingly integral to personal and corporate activities, phishing attacks have emerged as a prevalent threat, ingeniously mimicking legitimate sources to illicitly acquire sensitive information. This research paper details the development of a sophisticated phishing detection application utilizing the DistilBERT-based model, finetuned on a diverse array of email datasets. The application significantly enhances the precision of phishing detection mechanisms, adeptly reducing the incidence of successful phishing attacks. Initial tests have demonstrated a precision rate of over 95% in detecting phishing emails, outperforming traditional rule-based filters substantially. The application exhibits robust defences against zero-day phishing attacks through its advanced machine learning framework, which dynamically adapts to emerging phishing strategies. This paper explores the methodology of developing the DistilBERT model, evaluates its efficacy against existing solutions, and discusses its implications for future cybersecurity practices. The study’s findings underscore the potential of AI-driven tools in transforming cybersecurity measures, offering a proactive approach to thwarting phishing attempts and safeguarding sensitive data.

Sustainability transition theories analyse a systematic shift towards sustainability at micro (niche), meso (regime) and macro (landscape) level. The assessment of technological systems and structures at the firm level in sustainability transition literature is scant. The present study, taking the technological assessment perspective at the firm level, finds answers to questions like (a) how do established corporations move towards sustainable practices? (b) what role does technological innovation play in the firm’s transition towards sustainability? (c) what technological modes are adopted for sustainability transition? We find answers to these questions through an in-depth case analysis of two multi-national companies in the consumer goods industry. Internally developed and externally acquired technologies by firms in the last 15 years are plotted using qualitative and quantitative indicators on pre-designed templates. Technologies for all three sustainability dimensions, namely, environmental, social and economic, are mapped and the impact assessed. The analysis finds a sustainability transition landscape that shows the use of protected (patents, trademarks, designs) and unprotected technologies (open innovation) to generate impacts like production efficiency, consumption reduction, emission reduction, reduce-recycle-reuse among others. Companies implementing sustainable technologies do observe positive impacts. Implementation of reduce-reuse-recycle (3R)-based technologies enhance the achievement of sustainable development targets. Furthermore, the use of trademarks seems common in differentiating their technologies and identities. These and other results are detailed and used to comment on the role of managing intellectual property and harnessing the effect of technological innovations in sustainability transition.

The disaster response operational strategies requires tool that a may provide time bound clear picture of potential spots. Natural disaster sometimes comes slowly like increment of water level resulting flood or early warning of tsunami whereas in manmade disasters like 1CBRNE attack or chemical accident or industrial structure collapse or leakage through a pipeline of some toxic hazardous gas requires very accurate and quick response strategies. 2Unmanned Aerial System is commercially used tools present in the market and also used by military organization for various operations throughout the world. The accuracy and time bound pictorial representation of the spots by these tow tools makes them very useful for providing clear picture of potential disaster sites and enabling decision makers to take decision on these representation. Apart of these the potential to deliver important material faster than any other mode also makes these equipment and technology a very important asset for making disaster risk reduction strategies. This paper elaborates the efficacy and utility of Unmanned Aerial System or Drones in developing robust and time bound strategies for disaster risk reduction. This paper also evaluates some experiences and describes some initiatives using Unmanned Aerial System to support disaster risk reduction strategies and post disaster decision making efforts.

One of the most basic pieces of information gained from dynamic electromyography is accurately defining muscle action and phase timing within the gait cycle. The human gait relies on selective timing and the intensity of appropriate muscle activations for stability, loading, and progression over the supporting foot during stance, and further to advance the limb in the swing phase. A common clinical practice is utilizing a low-pass filter to denoise integrated electromyogram (EMG) signals and to determine onset and cessation events using a predefined threshold. However, the accuracy of the defining period of significant muscle activations via EMG varies with the temporal shift involved in filtering the signals; thus, the low-pass filtering method with a fixed order and cut-off frequency will introduce a time delay depending on the frequency of the signal. In order to precisely identify muscle activation and to determine the onset and cessation times of the muscles, we have explored here onset and cessation epochs with denoised EMG signals using different filter banks: the wavelet method, empirical mode decomposition (EMD) method, and ensemble empirical mode decomposition (EEMD) method. In this study, gastrocnemius muscle onset and cessation were determined in sixteen participants within two different age groups and under two different walking conditions. Low-pass filtering of integrated EMG (iEMG) signals resulted in premature onset (28% stance duration) in younger and delayed onset (38% stance duration) in older participants, showing the time-delay problem involved in this filtering method. Comparatively, the wavelet denoising approach detected onset for normal walking events most precisely, whereas the EEMD method showed the smallest onset deviation. In addition, EEMD denoised signals could further detect pre-activation onsets during a fast walking condition. A comprehensive comparison is discussed on denoising EMG signals using EMD, EEMD, and wavelet denoising in order to accurately define an onset of muscle under different walking conditions.

Leakages in the water distribution networks (WDNs) are real problems for utilities and other governmental agencies. Timely leak detection and location identification has been a challenge. In this paper, an integrated approach to geospatial and infrared image processing method was used for robust leak detection. The method combines drops in flow, pressure, and chlorine residuals to determine potential water leakage locations in the WDN using Geographic Information System (GIS) techniques. GIS layers were created from the hourly values of these three parameters for the city of Sharjah provided by Sharjah Electricity, Water and Gas Authority (SEWA). These layers are then analyzed for locations with dropped values of each of the parameters and are overlaid with each other. In the case where there were no overlaying locations between flow and pressure, further water quality analysis was avoided, assuming no potential leak. In the case where there are locations with drops in flow and pressure layers, these overlaying locations are then examined for drops in chlorine values. If overlaying locations are found, then these regions are considered potential leak locations. Once potential leak locations are identified, a specialized remote sensing technique can be used for precise leak location. This study also demonstrated the suitability of using an infrared camera for leak detection in a laboratory-based setup. This paper concludes that the following methodology can help water utility companies in the timely detection of leaks, saving money, time, and effort.

Myocardial deformation imaging (strain imaging) is a technique to directly quantify the extent of myocardial contractility and overcomes several of the limitations of ejection fraction. The application of the most commonly used strain imaging method; speckle-tracking echocardiography to patients with sepsis cardiomyopathy heralds an exciting development to the field. However; the body of evidence and knowledge on the utility, feasibility and prognostic value of left ventricular global longitudinal strain in sepsis cardiomyopathy is still evolving. We conducted a review of literature on utility of left ventricular global longitudinal strain in sepsis cardiomyopathy. We discuss the role of left ventricular global longitudinal strain in mortality prediction, utility and limitations of the technique in the context of sepsis cardiomyopathy.

Background: Although, negative repercussions of inadequate health service use on the health outcomes has been presumably exacerbated by COVID-19, the impact of the pandemic measures has been not evaluated properly yet. Objective: Our study aimed to quantify the COVID-19 pandemic measures’ effect on the general practitioner (GP) visit, specialist care, hospitalization and cost-related prescription nonredemption (CRPNR) among adults in Hungary, and to identify the social strata susceptible to the pandemic effect. Methods: This community-based cross-sectional study based on nationally representative data of 6,611 (Nprepandemic=5,603 and Npandemic=1,008) subjects aged 18 years and above. Data were obtained from the European Health Interview Survey 2019 (EHIS) and International Social Survey Program 2021 (ISSP) for prepandemic and pandemic, respectively. Multivariable logistic regression models were applied to determine the sociodemographic and clinical factors influencing the health care use by odds ratios (OR) along with the corresponding 95% confidence intervals (CI). To identify the social strata susceptible to pandemic effect, the interaction of the time of data collection with level of education, marital status, and ethnicity, was also tested. Results: While, the CRPNR did not changed, the frequency of GP visit, specialist care and hospitalization rate were remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic in Hungary. Roma proved to be not specifically affected by the pandemic in any studied respect. The pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (ORhigh-school vs primary-education =0.434; 95% CI 0.243-0.776, ORhigh-school vs primary-education =0.598; 95% CI 0.364-0.985), and among widows (ORwidowed vs married =2.284; 95% CI 1.043-4.998, ORwidowed vs married=1.915; 95% CI 1.157-3.168) on the frequency of GP visit and specialist visit; and the prepandemic CRPNR inequality by level of education was increased (ORhigh-school vs primary-education =0.236; 95% CI 0.075-0.743). Conclusion: Primary educated and widowed did not follow the general trend, and their prepandemic limited health care use was not reduced further during pandemic, resulting in an inequality reduction. The vulnerability of primary educated to CRPNR was the only gap widened in the pandemic period. This shows that although the management of pandemic health care use restrictions was implemented by increasing the social inequality in Hungary, the prevention of inequity in drug availability for primary educated individuals could require more support.

Objectives: As institutions modified medical practices to mitigate the spread of the SARS-CoV-2 virus, providers were forced to modify care through the implementation of telemedicine. The objective of this article is to review the current practices of otolaryngology during the COVID-19 pandemic and the limitations of telemedicine in current practice. Methods: A thorough review of the PubMed and MEDLINE databases was performed for publications between 2020 and 2021. Studies discussing telemedicine in otolaryngology during COVID-19 pandemic were selected. Results: As worldwide cases of COVID-19 continue to oscillate, we must continue to be vigilant in our clinical practice, implementing safe techniques to mitigate the spread of the SARS-CoV-2 virus through the continual use of telemedicine in all specialties of otolaryngology. Trends of increased patient acceptance of the use of telemedicine have been seen across subspecialities, including otolaryngology. Conclusion: Currently there are challenges associated with the implementation of telemedicine in the field of otolaryngology that rely heavily on adjunct physical examination, imaging studies, and specialty procedures. However, telemedicine has tremendous potential and can be adapted to include in the otolaryngologist’s toolbelt during public health emergencies such as the COVID-19 pandemic.

During the last trimester of gestation and for the first 18 months after birth, both docosahexaenoic acid,22:6n-3 (DHA) and arachidonic acid,20:4n-6 (ARA) are preferentially deposited within the cerebral cortex at a rapid rate. Although, the structural and functional roles of DHA in brain development are well investigated, similar roles of ARA are not well documented. The mode of action of these two fatty acids and their derivatives at different structural-functional roles and their levels in the gene expression and signaling pathways of the brain have been continuously emanating. In addition to DHA, importance of ARA has been much discussed in recent years for fetal and postnatal brain development and the maternal supply of ARA and DHA. These fatty acids are also involved in various brain developmental processes; however, their mechanistic cross talks are not clearly known yet. This review describes the importance of ARA, in addition to DHA to support the optimal brain development and growth and functional roles in the brain.

We enriched and isolated a novel gammproteobacterial methanotroph; strain FWC3, from tropical freshwater wetland, near Nagaon beach, Alibag, India. FWC3 is a coccoid, flesh pink/peach pigmented, non-motile methanotroph and the cells are present in pairs and as tetracocci. The culture can grow on methane (20%) as well as on a wide range of methanol from concentrations (0.02%-5%). Based on the comparison of genome data, FAME analysis, morphological characters and biochemical characters, FWC3 belongs to the tentatively and newly but not validly described genus ‘Methylotetracoccus’ of which only a single species strain was described, Methylotetracoccus oryzae C50C1. The ANI index between FWC3 and C50C1 strains is 94%, and the DDH value is 55.7%, less than the cut-off values 96% and 70%, respectively. The genome size of FWC3 is smaller (3.4 Mbp) compared to that of C50C1 (4.8 Mbp). Additionally, the FAME profile of FWC3 shows differences in cell wall fatty acid profiles compared to Methylotetracoccus oryzae C50C1. Also, there are other differences on the morphological, physiological and genomic levels. We propose FWC3 to be a member of a novel species of the genus Methylotetracoccus, for which the name Methylotetracoccus aquaticus is proposed. Also, an amended description of the genus Methylotetracoccus gen. nov. is given here. FWC3 is available in two international culture collections with the accession numbers: MCC 4198 (Microbial Culture collection, India) and JCM 33786 (Japan Collection of Microorganisms, Japan).

The necessity for effective intrusion detection systems (IDS) in big data environments has grown critical due to the rising prevalence of big data systems and the rising amount of security threats. Applying conventional intrusion detection methods to the enormous and intricate data produced by big data ecosystems presents difficulties. Deep learning, has proven to be exceptionally adept at deciphering complex, large-scale data. This study proposes a Deep Learning-based Intrusion Detection System (IDS) created specifically for the Big Data environment. Traditional intrusion detection systems struggle to efficiently identify and prevent cyber threats due to the ever-increasing volume and complexity of data in current networks. We suggest an IDS that makes use of Deep Learning (CNN, LSTM, GAN, etc.), to address this problem. These cutting-edge neural network topologies give the system the ability to process and analyze massive amounts of data for precise intrusion detection. Data collection, data preprocessing, feature engineering, DL model training, intrusion detection, warning generation, and reaction are some of the crucial parts of the suggested IDS. The data collection module mines the Big Data environment for network traffic, system logs, and security event information. To make sure the data is suitable for analysis, it is preprocessed. To improve the detection abilities of the DL models, important features are extracted from the data using feature engineering approaches.

The rapid urbanization growth of Dubai has resulted in connectivity issues, considered tre-mendous development pressure. That leads the local authorities to set a vision for Dubai as a 15-20 minute city by 2040. The 15-minute city, where all services can be reached with minimum travel time using sustainable mobility means (walking, cycling, or electric bik-ing). This paper aims to assess the current walkability situation within 15 minutes in the most significant parts of Dubai. This study considered 13 communities; Bur-Dubai and Business Bay were selected to represent the ungated communities, and eleven major gated communities were considered to indicate the gated ones. Those neighborhoods are selected based on the developments' socio-economic status and population density. The assessment considered 14 essential services, categorized into five categories: educational, health, social, entertainment, and religious. The research methodology conducted desktop research, site visits, interviewing random residents to collect data, and then using ArcGIS to assess walk-ability. The results show (64.5%) of the ungated neighborhoods population which access essential services within 15 minutes, while most of the gated communities residents must use cars to access many services. Furthermore, services distribution patterns and walkability infrastructures outside these developments should be developed to obtain higher walkability indicators.

As the most commonly used hydrogel material in contact lenses, the amount of water in a lens affects its optical properties and comfort for the wearer. Therefore, an important challenge is to determine the safety and efficacy of contact lenses by accurately and non-destructively measuring the water content in real time. In this study, we demonstrate the accurate detection of water content in hydrogel contact lenses using a high-precision ATR format in a portable terahertz time-domain spectroscopy system. The technique can resolve small variations in the dielectric constant in solution, which is difficult to achieve with traditional transmission and reflection measurement modes. Information is obtained from the interaction between the sample and the swift waves propagating along the prism surface. The swift waves can excite longitudinal modes that are not directly accessible by conventional techniques. It is worth noting that the reference wave can be measured by removing the sample without disturbing the optical path. We also enhance the plasma effect at the interface with the hydrogel by using PVDF dielectric films of different polarities. We observed that the water content and refractive index changes in the ATR mode show different response patterns for nonpoled PVDF and poled PVDF membranes. This suggests that reflection and relative phase can be accurately evaluated in the THz-ATR technique, resulting in an accurate method for determining complex dielectric constants in the reflection geometry. This will allow accurate measurement of both surface and in vivo water content in hydrogels in the future and is a potential technical route for application in bioaqueous tissue measurements.

An emissions baseline for a city is the foundation to building an informed clean air action plan. This includes an understanding of the sources and their intensities to device cost-effective measures with the least health impacts. In an urban environment, emissions from road transport is one of the major contributors to the air pollution problem, and accounting for this sector requires a detailed profile of in-use vehicles, covering their age-mix, usage, and fuel economy. In this paper, we present a simplified framework to survey at select fuel stations to establish the necessary inputs and use them to build a localized vehicle emissions inventory. The methodology is illustrated with an application in the city of Patna, India. Here, the FuSS was employed to profile the in-use passenger vehicle characteristics by 19 trained students, over nine days and at ten fuel stations, to collect 9,775 survey points. The methodology outlined in this paper, along with the tools and training framework, is also replicable in settings other than the fuel stations.

Germplasm is a valuable natural resource in plant diversity that is crucial for its potential use. It provides knowledge about a species genetic composition. Germplasm protection strategies are not just planting hope threatened with extinction, they preserve medicinal and other essential plants on which survival rests. The successful use of genetic plant resources necessitates diligent collection, storage, analysis, documentation, and germplasm exchange. Slow growth cultures, cryopreservation, pollen and DNA banks, botanic gardens, genetic reserves and farmer’s fields are few conservation techniques. However, usage of an in vitro procedure with any chance of genetic instability leads to the destruction of the entire substance. Improved understanding of basic regeneration biology would, in turn, undoubtedly increase the capacity to regenerate plants from in vitro harvested explants, thus expanding selection possibilities. Germplasm conservation seeks to conserve endangered and vulnerable plant species worldwide for future proliferation and development; it is also the bedrock of agricultural production.

The HER2 overexpression occurs in 10–20% of breast cancer patients. HER2+ tumors are characterized by increase in Ki67, early relapse and increased metastasis. There is little known about factors influencing early stages of HER2- tumorigenesis and diagnostic markers. Previously, it was shown that deletion of NEDD9 in mouse models of HER2 cancer interferes with tumor growth, but the role of NEDD9 upregulation is currently unexplored. We report that NEDD9 is overexpressed in a significant subset of HER2+ breast cancers and correlates with limited response to anti-HER2 therapy. To investigate the mechanisms through which NEDD9 influences HER2-dependent tumorigenesis, we generated MMTV-Cre-NEDD9 transgenic mice. The analysis of mammary glands shows extensive ductal epithelium hyperplasia, increased branching, and terminal end bud expansion. The addition of oncogene Erbb2 (neu) leads to development of early hyperplastic benign lesions earlier (~16 weeks) with a significantly shorter latency than the control mice. Similarly, NEDD9 upregulation in MCF10A-derived acini leads to hyperplasia like DCIS. This phenotype is associated with activation of ERK1/2 and AURKA kinases leading to an increased proliferation of luminal cells. These findings indicate that NEDD9 is setting permissive conditions for HER2-induced tumorigenesis, thus identifying this protein as a potential diagnostic marker for early detection.

Self-compacting concrete is essential for vertical structures due to high reinforcement and usage of pumps for transporting the concrete at the working site. SCC is mainly influenced by self-curing for arid areas. To explore the SCC (Self-Compacting Concrete) mixture and condition influencing the self-curing condition were determined using the experimental procedure. Determination of various parameters was done using T50 slump flow, V-funnel, L-box-box, J ring test, compressive strength, splitting tensile strength, and flexural strength test. After the experimental investigation, it shows that if the dose if the dosage of superplasticizer (SNF%) increases, it will improve the concrete mixture's different properties, such as flowability and ability to pass. Higher water-to-cement ratios (w/c) generally result in enhanced flowability and stability. Mixture 9 (SNF 0.35, w/c 0.5) demonstrates favourable results across all parameters, indicating excellent flowability and stability. Mixture 9 (SNF 0.35, w/c 0.5) also shows favourable flowability and stability characteristics. Lower concentrations, such as 0.5%, may have a positive effect up to a certain point but might not provide sustained improvement over the curing period. On the other hand, concentrations of 1% and 2% demonstrated consistent and significant enhancement in strength throughout the 28 days. It is found that the higher concentrations of PEG 4000 may be more effective in improving the material strength.

Climate change has had a significant impact on many ecosystems worldwide, prompting native population species to adapt to the current weather patterns eventually. Pre-existing genetic variation in populations explains part of this adaptation. Still, recent studies have shown that new stable phenotypes can be generated through epigenetic modifications in just a few generations, thereby contributing to the stability and survival of plants in their natural habitat as they eventually adjust to the surrounding impacts. The state of chromatin inside plant cells varies, allowing cells to fine-tune their transcriptional profiles to better adapt to stimuli from the external environment. Within a cell, chromatin state changes such as post-transcriptional histone modifications and variations, DNA methylation, and non-coding RNA activity are all examples of chromatin state alterations that may epigenetically dictate certain transcriptional outputs. Recent advances in the field of ‘Omics’ in major crops has made it easier to identify epigenetic changes and their impact on plant responses to environmental stresses. These epigenetic mechanisms thus play an important role in improving crop adaptation and resilience to changing environments. This variation that has emerged can thus be exploited in crop breeding, ultimately leading to the generation of stable climate-resilient genotypes.

Artificial membrane systems can serve as models to investigate molecular mechanisms of different cellular processes, including transport, pore formation, and viral fusion. However, the current simulacrums such as SUVs, GUVs, and the supported lipid bilayers suffer from issues, namely high curvature, heterogeneity, and surface artefacts, respectively. Freestanding membranes provide a facile solution to these issues, but current systems developed by various groups use silicon or aluminium oxide wafers for fabrication that involves access to a dedicated nanolithography facility and high cost while conferring poor membrane stability. Here, we report the development, characterization and applications of an easy-to-fabricate suspended lipid bilayer (SULB) membrane platform leveraging commercial track-etched porous filters (PCTE) with defined microwell size. Our SULB system offers a platform to study the lipid composition-dependent structural and functional properties of membranes with exceptional stability in a high throughput fashion. With dye entrapped in PCTE microwells by SULB, we show that sphingomyelin significantly augments the activity of pore-forming toxin, Cytolysin A (ClyA) and the pore formation induces lipid exchange between the bilayer leaflets. Further, we demonstrate high efficiency and rapid kinetics of membrane fusion by dengue virus in our SULB platform. Our suspended bilayer membrane mimetic offers a novel platform to investigate a large class of biomembrane interactions and processes.

For a significant period, conventional breeding and genetic modification were the key techniques that were effective in managing biotic and abiotic stresses in crops and adding desirable traits. However, the recent appearance of novel diseases and unexpected climatic changes that have substantial implications for agriculture worldwide have urged scientists to look for alternative methods to quickly manage seasonal crises. The primary emphasis of this chapter is on the obstacles and diverse biotechnological methods employed to enhance crop resilience against a range of biotic and abiotic stressors in plants. Furthermore, we consider gene transformation, omics techniques, genome editing, and other sophisticated biotechnological tools that utilize transcriptomic, proteomic, metabolomic, phenomics, RNA interference, and epigenome modifications for enhancing plant resilience. Lastly, we examine the potential of merging these eco-friendly and innovative methods with conventional breeding to promote modern agriculture and aid in enhancing tolerance to different biotic, abiotic stresses and growth promotion.

The use of credit cards and online banking is expanding exponentially. As more individuals use debit cards, credit cards, and internet banking, the likelihood of falling victim to various forms of fraud also rises. Due to ignorance, credit card company customers have provided their card details, personal information, and one-time password to an unknown bogus caller on several occasions in the recent past. One of the biggest issues facing financial institutions and customers alike is credit card theft. It may result in large financial losses and harm to the financial institution's image. While there are several ways to identify credit card fraud, one of the best is machine learning.By using past data, machine learning algorithms may be trained to recognize trends and abnormalities that point to fraud. The state-of-the-art in machine learning for credit card fraud detection is reviewed in this study. Numerous research on the same subject have been conducted in the past with a variety of well-known machine-learning techniques. However, with a grasp of the notion of hybrid machine learning, we will now examine how well hybrid machine learning performs on the same problem statement.

Current generation witnesses a huge interest in optical waveguide due to their salient feature such as low cost, immune to electromagnetic interference, easy to multiplex, compact size, etc. These features of the optical fibers makes it an useful tool for various sensing applications including medicine, automotive, biotechnology, food quality control, aerospace, physical and chemical monitoring etc. Among all the reported application, the device has been widely exploited to measure the physical and chemical variation in surrounding environment. Optical fiber based temperature sensor plays a crucial role in this decade to detect high fever and tackle COVID like pandemic. Recognizing the major developments in the field of the optical fibers, this article aims to provide recent progress in temperature sensor utilizing several sensing configuration including standard fiber, photonic crystal fiber, and Bragg grating fibers. Additionally, the article also highlights the advantages, limitations, and future possibilities in this area.

The healing of osteochondral defects (OCD) resulting from injury, osteochondritis, or osteoarthritis in middle- and old-age individuals, bearing lesions in the cartilage and bone, pain, and loss of joint function, presents challenges to the clinical practitioners because of non-regenerative cartilage and the limitations of current therapies. Bioactive peptide-based osteochondral (OC) tissue regeneration is becoming more popular because it does not have the immunogenicity, misfolding, or denaturation problems associated with original proteins. Periodically, reviews are published on the regeneration of bone and cartilage; however, none of them address the simultaneous healing of these tissues in the complicated heterogeneous environment of the OC interface. As regulators of cell adhesion, proliferation, differentiation, angiogenesis, immunomodulation, and antibacterial activity, potential therapeutic strategies for OC defects utilizing bone and cartilage-specific peptides should be examined and investigated. Therefore, the main goal of this review is to study how they contribute to the healing of OC defects, either alone or in conjunction with other peptides and biomaterials.

As the worldwide demand for meat per person is continuously increasing, there is a corresponding rise in the number of livestock animals, leading to an increase in livestock manure. Selecting appropriate treatment technologies for livestock manures is still a complex task and considerable debates over this issue persist. To develop a more comprehensive understanding of the manure treatment framework, this review was undertaken to assess the most utilized manure management technologies and underscore their respective challenges. Anaerobic digestion has become a commercial reality for treating livestock manures. However, the mono-digestion of single substrates comes with certain drawbacks associated with manure characteristics. Anaerobic co-digestion, involving the utilization of multiple feedstocks, holds the potential to overcome these limitations. Extensive research and development have underscored numerous intrinsic benefits co-digestion. These include improved digestibility resulting from synergistic effects of co-substrates and enhanced process stability. This review underscores the limitations associated with the mono-digestion of livestock manures and critically evaluates the advantages of their co-digestion with carbon-rich substrates. Additionally, this review delves into key livestock manure management practices globally, emphasizing the significance of co-digesting livestock manures while addressing the progress and challenges in this field.

Background: Green synthesis of silver (Ag) nanoparticle was performed with the fruit extract of Scindapsus officinalis and test against HepG-2, MCF-7 cancer cell lines. These biosynthesized metal nanoparticles have a potential of therapeutic use as an alternative medicine for the treatment of hepatic & breast cancer cases. Results : AgNPs were identified by change of color & their absobtion at 340 nm measured by UV-visible spectroscopy, FTIR spectral analysis confirmed phenolic compounds presence, morphology & size visualized in SEM, TEM used for determination of size, shape & light scattering analysis. Synthesized silver nanoparticles were spherical in shape and size less than 50 nm. XRD analysis was affirmed the crystalline nature of metal particles. In-vitro cytotoxic result showed an excellent IC50 value of 155.81μg/ml and 114.74 μg/ml against HepG-2 & MCF-7 cell lines. Conclusion: The current study reveals green synthesized AgNPs possess high cytotoxic action against HepG-2 & MCF-7 cell lines which suggested the use of silver nanoparticles as a medicine to treat hepatic & breast cancer.

The ongoing evolution of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has resulted in the recent emergence of a highly divergent variant of concern (VOC) defined as Omicron or B.1.1.529. This VOC is of particular concern because it has the potential to evade most therapeutic antibodies and has undergone a sustained genetic evolution, resulting in the emergence of five distinct sub-lineages. However, the evolutionary dynamics of initially identified Omicron BA.1 and BA.2 sub-lineages remain poorly understood. Herein, we combined Bayesian phylogenetic analysis, mutational profiling, and selection pressure analysis to track virus genetic changes that drive the early evolutionary dynamics of the Omicron. Based on the Omicron dataset chosen for the improved temporal signals and sampled globally between November 2021 and January 2022, most recent common ancestor (tMRCA) and substitution rates for BA.1 were estimated to be 18 September 2021 (95% highest posterior density (HPD) 04 August – 22 October 2021) and 1.435×10-3 (95% HPD = 1.021×10-3 – 1.869×10-3) substitution/site/year, respectively, whereas 03 November 2021 (95% highest posterior density (HPD) 26 September – 28 November 2021) and 1.074×10-3 (95% HPD = 6.444×10-4 – 1.586×10-3) substitution/site/year for BA.2 sub-lineage. The findings of this study suggest that the Omicron BA.1 and BA.2 sub-lineages originated independently and evolved over time. Furthermore, we identified multiple sites in spike protein undergoing continued diversifying selection that may alter the neutralization profile of BA.1. This study shed light on the ongoing global genomic surveillance and Bayesian molecular dating analyses to better understand the evolutionary dynamics the virus and, as a result, mitigate the impact of emerging variants on public health.

Understanding microbial composition in upper respiratory infections (URIs) is critical for effective diagnosis and treatment. Precision Metagenomic next-generation sequencing p(mNGS) can provide a comprehensive yet clinically relevant profile of respiratory infection. The hybridization capture-based targeted sequencing generated a precision metagenomics profile of 29 patients with acute URIs. Nasopharyngeal samples were collected from the subjects suspected of respiratory infection, and p(mNGS) was performed using the Illumina®/IDbyDNA Respiratory Pathogen ID/AMR Panel (RPIP). The dataset obtained from the mNGS analysis contains a wealth of information on the composition of acute URI microbiota, including the relative abundance of known pathogens and potential clinical implications. The dataset represents a valuable resource for future research endeavors in respiratory medicine, infectious disease epidemiology, and therapeutic interventions. In addition, the dataset offers significant potential for reuse and integration with other omics datasets. The comprehensive nature of the mNGS data allows the exploration of associations between the respiratory microbiota and host factors such as clinical outcomes, immune responses, or genetic predisposition. Combining this dataset with other relevant datasets, such as transcriptomics or metabolomics, could provide a deeper understanding of the complex interactions between the microbiota and the host in acute URIs.

The COVID-19 pandemic caused by SARS-CoV-2 has been showing a speedy growth in the number of infected patients with a remarkable mortality rate, thus it has become a worldwide public health concern. From March 8, 2020, the disease was confirmed to start spreading in Bangladesh. Since then, people got infected so exponentially that the country positions at the list of top infected countries in the world. Therefore, the objective of this comprehensive review was representing overall scenario of COVID-19 in different sectors of Bangladesh, particularly prioritizing the health sector. Up to 14 September 2020, 339,332 confirmed cases and 4,759 deaths were reported. An alarming fact is that while the global mutation rate of coronavirus is 7.23 % in average, the rate is 12.6 % in Bangladesh. Although the government ruled preventive strategies such as nationwide lockdown, social distancing, contact monitoring, quarantine and isolation, it was difficult to implement those due to lack of public awareness, inappropriate attitudes and so on. Moreover, the overburdened healthcare system had a weak response at initial stage because of insufficient healthcare facilities. Consequently, this pandemic affected severely almost all the important sectors of the country, specifically the economy, agriculture and health sectors. Hence, focusing on healthcare system as well as maintaining social distance and other essential precautions can limit the spread of infection and help to alleviate the severity of the pandemic.

Introduction: Governance, the least studied health system component, comprises a system of rules and processes, and is a key determinant for effective decision making for health care planning. This study aims to identify institutional, legal and policy factors which are either barriers or facilitators for the implementation of integrated mental health in primary care in the India. Methods: Semi-structured interviews were conducted with 33 key informants at the district and national levels with policy makers, state level health care planners and district planners and managers in India. The data were analysed using thematic analysis using the qualitative software NViVO 10. Findings: Participants stated that a conducive environment for mental health service delivery is necessary at the legislative, policy and planning levels, to facilitate integration of mental health into primary care. Amongst other factors, the need for active involvement of civil society and service user organisations, strengthening mental health information systems, and building the non-technical skills of the mental health workforce, were identified as particularly necessary to deliver adequate mental health services.Conclusion: Amidst the favourable policy context supporting collaborative and integrated care in India, this study identified low resourcing, weak collaborations and inadequate information to be crucial for integrated mental health in India at present.

Alzheimer’s disease (AD) is a significant health concern worldwide with enormous social and economic impact globally. The gradual deterioration of cognitive functions and irreversible neuronal losses are primary features of the disease. Even after decades of research, most therapeutic options are merely symptomatic, and drugs in clinical practice present numerous side effects. Lack of effective diagnostic techniques prevents the early prognosis of disease, resulting in a gradual deterioration in the quality of life. Furthermore, the mechanism of cognitive impairment and AD pathophysiology is poorly understood. Microfluidics exploits different microscale properties of fluids to mimic environments on microfluidic chip-like devices. These miniature multichambered devices can be used to grow cells and 3D tissues in vitro, analyze cell-to-cell communication, decipher the roles of neural cells like microglia, and gain insights into AD pathophysiology. This review focuses on the applications and impact of microfluidics on AD research. We discuss the technical challenges and possible solutions provided by this new cutting-edge technique to understand disease-associated pathways and mechanisms.

Using the above results from RMS analysis the optimum values were predicted for the independent significant variables (Figure 3) the optimized levels of these variables in combination with other media variables the maximum production was predicted to be 199.90 U/mL. The predicted data were validated through confirmatory experiments performed in triplicates. A 1.29-fold increase in amylase activity against un-optimized (OVAT) medium was achieved in the present study authenticating the efficacy of RSM in process optimization (Figure 4). 2.6 Model validation and scale-up at laboratory scale (5L) bioreactor Once the parameters were standardized in the shake-flasks culture, the experiment was scaled-up to a laboratory-scale bioreactor (5 L). The yield of amylase increased by 1.01 fold (205.69 U/mL), it could be possible because the enzyme production in a bioreactor is higher than in shake-flasks culture as the various critical variable factors such as the dissolved oxygen (DO) and the pH can be optimally controlled at the desired levels [22].

The Interdisciplinary Canadian Collaborative ME Research Network (ICanCME), established in 2019, aims to foster research in Canada and contribute to finding the causes and possible treatments for myalgic encephalomyelitis /chronic fatigue syndrome (ME/CFS), thereby reducing the impact of ME/CFS on the health of Canadians. The main objectives of this paper are to suggest standards for ME/CFS research for the collection of data from participants (Recommended Data Elements) and to consider other factors, such as design, language, cultural issues, equity, and diversity. Consensus of the relevant contents of this research guideline was reached during the ICanCME working group meetings and were based on existing guidelines. Members of the working group contributed to guideline development based on their respective expertise. The proposed research guidelines could improve research quality and advance knowledge in the field of ME/CFS, and ultimately benefit ME/CFS patients.

Komagataeibacter spp. have been used for the bioconversion of industrial wastes and lignocellulosic hydrolysates to bacterial cellulose (BC). Recently studies have demonstrated the capacity of Komagataeibacter spp. in the biotransformation of inhibitors found in lignocellulosic hydrolysates, aromatic lignin-derived monomers (LDMs) and acetate. In general, detoxification and BC synthesis from lignocellulosic inhibitors requires a carbon flow from acetyl-coA towards tricarboxylic acid and gluconeogenesis, respectively. However, the related molecular aspects have not yet been identified in Komagataeibacter spp. In this study, we isolated a cellulose producing bacteria capable of synthesizing BC in a minimal medium containing crude glycerol, a by-product from biodiesel production process. The isolate, affiliated to Komagataeibacter genus, synthesized cellulose in minimal medium containing glucose (3.3±0.3 g/L), pure glycerol (2.2±0.1 g/L) and crude glycerol (2.1±0.1 g/L). Genome assembly and annotation identified four copies of bacterial cellulose synthase operon and genes for redirecting the carbon from central metabolic pathway to gluconeogenesis. According to the genome annotations, a BC production route from acetyl-CoA, a central metabolic intermediate, was hypothesized and was validated using acetate. We identified that when K. rhaeticus ENS9b was grown in minimal medium supplemented with acetate, BC production was not observed. However, in presence of readily utilizable substrate, such as spent yeast hydrolysate, acetate supplementation improved BC synthesis.

Hydrogenated water has emerged as a novel approach in the field of health and wellness. It is be-lieved to have potent antioxidant properties that can neutralize harmful free radicals in the hu-man body. It has also been shown to be beneficial in mitigating oxidative stress-induced damage through its anti-inflammatory and anti-apoptotic pathways. We aim to conduct a systematic re-view to evaluate the potential benefits of hydrogenated water. The review protocol was uploaded on PROSPERO. After the initial search criteria, the articles were reviewed by two blinded inves-tigators, and a total of 25 articles were included in the systematic review. The potential benefits of hydrogenated water on various aspects of health, including exercise capacity, physical endurance, liver function, cardiovascular disease, mental health, COVID-19, oxidative stress, and anti-aging research, are a subject of growing interest and ongoing research. Although preliminary results in clinical trials and studies are encouraging, further research with larger sample sizes and rigor-ous methodologies is needed to substantiate these findings. Current research needs to fully ex-plain the mechanisms behind the potential benefits of hydrogenated water. Continued scientific exploration will provide valuable insights into the potential of hydrogenated water as an adjunc-tive therapeutic approach in the future.

This research paper investigates ultra-wideband (UWB) localization systems by focusing on the use of average filter (AVG), Kalman filter (KF), and extended Kalman filter (EKF) algorithms, as well as a novel integrated filtering method that incorporates low-pass filter (LPF) into AVG, KF, and EKF. The study aims to improve localization loss in indoor environments using a TurtleBot robot equipped with a camera to observe ground truth positions. To evaluate the effectiveness of the proposed algorithms, a comprehensive comparison of the raw and filtered data with the camera-based ground truth observations is performed. Quantitative analyses of the results, including max, min, max-min, and mean error, are performed to evaluate the localization performance of the algorithms and the integrated filtering method. The results reveal that the integrated filtering method has performed better accuracy in comparison with existing methods.

Genome-wide sequencing data play an important role in evaluating the genomic level differences between superior and poor-quality crop plants and improving our understanding of molecular association with desired traits. We analyzed the obtained 92,921,066 raw reads from genome-wide resequencing of Cucumis sativus var. hardwickii through in-silico approaches and mapped to the reference genome of Cucumis sativus to identify the genome-wide single nucleotide polymorphisms (SNPs) and Single nucleotide variations (SNV). Here, we report 19, 74,213 candidate SNPs including 1,33,468 insertions and 1,43,237 deletions and 75 Indels genome-wide. A total of 2228224 identified variants were classified into four classes including 0.01% sequence alteration, 5.94% insertion, 6.37% deletion and 87.66% SNV respectively. These variations can be a major source of phenotypic diversity and sequence variation within the species. During the present study these variants were also utilized to resolve orthologous relationships among the genomes of C. melo and C. sativus var. hardwickii. Overall, the discovery of SNPs and genomic variants may help predict the plant response to certain environmental factors and can be utilized to improve crop plants' economically important traits.

Image classification in Remote Sensing and Geographic Information Systems (GIS) containing various land-cover classes is essential for efficient and sustainable land-use estimation, and other tasks like object detection, localization and segmentation. Deep Learning (DL) techniques have shown a tremendous potential in the GIS domain. While Convolutional Neural Networks (CNN) have dominated most of the image analysis domain, a new architecture called transformers have proved to be a unifying solution for several AI-based processing pipelines. Vision Transformers (ViT), a variant of transformers can have comparable and in some cases better accuracy than a CNN. However, they suffer from a significant drawback associated with an excessive use of training parameters. In this research we explore several modifications in the vision transformer architectures, especially MobileViT that can be optimized while boosting accuracy. To verify our proposed approach these new architectures are trained on four land-cover datasets AID, EuroSAT, UC-Merced, and WHU-RS19. Experiments reveal that combination of lightweight convolutional layers including ShuffleNet along with depthwise separable convolutions and average pooling can reduce the trainable parameters by 17.85% and yet achieve higher accuracy than the base MobileViT. It is also observed that utilizing a combination of convolution layers along with multi-headed self attention layers in MobileViT variants provide better performance in capturing local and global features unlike the standalone ViT architecture that utilizes almost 95% more parameters than the proposed MobileViT variant.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

This chapter explores the pivotal role of maize (Zea mays L.) in global nutrition, emphasizing its status as a staple food worldwide. It discusses maize's complex nutritional profile, including macronutrients, micronutrients, and dietary fiber. The chapter also covers biofortification efforts to enhance maize with essential nutrients, addresses nutritional concerns related to maize-centric diets, and explores genetic modification and agronomic strategies to boost nutrient-rich maize yields. Additionally, it delves into maize processing traditions, nutrient retention techniques, and the importance of promoting nutrient-rich maize varieties. The chapter outlines post-harvest strategies to combat nutrient loss and prevent contamination while emphasizing the significance of consumer education and diverse diets. Case studies illustrate the impact of improved maize nutrition and provide replicable strategies. The chapter concludes by considering emerging research and technology, identifying challenges, and proposing solutions to enhance maize's nutritional value in the future.

Japanese Encephalitis (JE) is a disease caused by the Japanese Encephalitis Virus (JEV). JEV is an arbovirus that spreads primarily through the bite of a female Culex spp. mosquito. JE shows predominance over the Asia-pacific region and has the potential to spread globally with a higher rate of morbidity and mortality. JE, a neuro-invasive disease, initiates with mild fever which may lead to encephalitis with severe neurological sequelae in some cases. Efforts have been made to identify and select various target molecules essential in JEV progression, but until now, no licensed anti-JE drugs have been available. From a prophylactic point of view, a few licensed JE vaccines are available but various factors viz. high cost and different side effects imposed by them has narrowed their global use. With an average occurrence of >67,000 cases of JE annually, there is an urgent need to find a suitable antiviral drug to treat patients at the acute phase, as only supportive care is available to mitigate infection. This systematic review highlights the current status of efforts put in to develop antivirals against JE and the available vaccines along with their effectiveness. It also summarizes epidemiology, structure, pathogenesis, and potential drug targets that can be explored to develop a new range of anti-JEV drugs to combat JEV infection globally.

The greatest pandemic of the century, COVID-19, is an ongoing global public health problem. With a clinically approved treatment available only for those who are acutely ill and are hospitalized, the control of this disease in the general population is still largely dependent on the preventive measures issued by the World Health Organization. Among the general control measures other than immunization with the COVID-19 vaccines, handwashing with soap and water has been emphasized the most because it is cost-effective and easily accessible to the general public. Studies have reported that soaps offer unique chemical properties that can completely destroy enveloped viruses. However, the general public seems to be still uncertain about whether soaps can shield us from a highly contagious disease such as COVID-19. In an attempt to help eliminate the uncertainty, we analyzed the mechanisms underlying the efficacy of soap and its prospect for preventing the spread of COVID-19. In this paper, we provide an overview of the history and characteristics of the SARS-CoV-2 virus, the current global COVID-19 situation, the possible mechanisms of the deactivation of viruses by soaps, and the potential effectiveness of soap in eliminating coronaviruses including SARS-CoV-2.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p < 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Early discharge after childbirth has led to a rise in neonatal readmission, becoming a major concern in recent decades. Our research aimed to identify the risk factors and incidence of neonatal readmission, as well as explore preventive measures. Our study at the Clinical Hospital of Pediatrics in Ploiești, Romania included 108 neonates admitted during the neonatal period. This accounted for 2.06% of all admissions (5226). The most prevalent cases were malnutrition (25%), fever (20.3%) and bronchiolitis (17.5%). Diarrhea and infectious gastroenteritis were also observed (14.8%), along with acute rhinoconjunctivitis (9.2%) and late onset sepsis (3.7%). No deaths were recorded. The most significant characteristics identified were number of children (p<0.001) and age at maternity discharge (p<0.001). By following the prevention rules, malnutrition, feeding errors, and infections can be avoided. This includes practicing proper hand hygiene for both mothers and medical staff, as well as educating and demonstrating to mothers the benefits of breastfeeding. In addition, all newborns discharged from the maternity ward should benefit from follow-up at 7-10 days of life. Our results confirm the effectiveness of a multidisciplinary team and endorse promoting breastfeeding. Implementing quality control measures and regularly evaluating the surveillance program will help improve its effectiveness.

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

Two interesting compounds such as quaternary ammonium lignin(QAL) and 2-ethylhexyl phosphoric acid mono-2-ethylhexyl ester (P507) were synthesized as ionic liquids(QP-ILs) for the extraction of metal ions. The extraction behavior of Co(II) and Ni(II) from chloride solution was compared between QP-ILs and P507. The results showed that the extraction rates of Co(II) and Ni(II) in the two solutions varied with the extraction conditions, but QP-ILs has stronger extractability for cobalt than P507, while Ni is on the contrary. Under the same conditions, the Co/Ni separation performance(βCo/Ni) in QP-ILs is superior to that in p507. At pH4.0, 55℃, concentration of 20%, extraction time of 10 minutes, the βCo/Ni of QP-ILs reached to 2703, while that of P507 was only 164. In conclusion, QP-ILs was more efficient than P507 for separating Co from mixed solutions.

Brain aging causes a wide variety of changes at molecular and cellular levels, leading to the decline of cognitive functions and increased vulnerability to neurodegenerative disorders. The research aimed at understanding the aging of the brain has made much progress in recent decades. Technological innovations such as single-cell RNA-sequencing (scRNA-seq), proteomic analyses, and spatial transcriptomic analyses have facilitated the research on the dynamic changes occurring within neurons, glia, and other cells along with their impacts on intercellular communication during aging. In this review, we introduce recent trends of how neurons and glia change during aging and discuss the impact of the brain microenvironment such as the blood-brain barrier (BBB).

In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

With the increasing concern of environment, the energy-efficiency scheduling of manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time can affect the final energy consumption and thus the spindle speed and scheduling scheme need to be optimized simultaneously. Since the turning workshop can be regarded as the flexible flow shop, this paper formulates a mixed integer linear programming model for energy-efficient scheduling of flexible flow shop. Accordingly, a new decoding method is developed by considering of the optimization of spindle speed and scheduling scheme simultaneously, and an estimation of distribution algorithm adopting the new decoding method is proposed to solve large-size problems. The parameters of this algorithm are determined by statistical technique with a simplified practical case. In order to validate the proposed method, a case from practical factories is studied, in which the makespan can be shortened by 25.22%, and the consumed energy can be saved by 5.48%. These results demonstrate the effectiveness of the proposed mathematical model and algorithm.

Climate change has resulted in increased incidences of abiotic stresses, such as heat, drought, salinity, and waterlogging. These stressors have a negative impact on the cotton (Gossypium hirsutum L.) crop and cause significant yield losses. Each stressor induces specific physiological and metabolic alterations interconnected with the complex changes at molecular levels. Understanding the molecular pathways that govern the cotton plant's stress responses is crucial to develop stress-tolerant cotton cultivars that can withstand different stresses. Molecular investigations have mapped the changes in the expression of stress-responsive genes, encompassing heat shock proteins and ion transporters, which play a vital role in facilitating adaptive responses. These approaches have been shown to help identify dynamic gene expression patterns and elucidate intricate regulatory networks using advanced metagenomics and multi-omics techniques. By leveraging genetic diversity and utilizing advanced molecular methods, it would be possible to develop stress-resilient cotton varieties to ensure sustainable cotton production in the face of abiotic stresses. This review provides an overview of the effects of various abiotic stressors on cotton plants, including drought, salt, heat, and waterlogged soil. We also explore the extensive network of stress-responsive genes, proteins, and signaling pathways in cotton by summarizing the studies on gene expression regulation, proteins involved in stress response, and biochemical characteristics.

Lignocellulosic biomass, an abundant and renewable resource, serves as a crucial raw material for the production of biofuels, biochemicals, and various value-added products. This paper aims to develop and optimize a mild alkaline treatment of sawdust assisted by ultrasound, along with enzymatic hydrolysis of the pretreated material. The sonochemical pretreatment with alkali emerged as the optimal approach to enhance the susceptibility of cellulose to subsequent enzymatic hydrolysis, thereby increasing the yield of reducing sugars. A comparative study was performed using various ultrasonic applicators (horn and bath) and conventional assisted alkaline pretreatment. The ultrasonic assisted pretreatment revealed a higher delignification as 68% (horn) and 57% (bath) comparing with conventional pretreatment. Processes were optimized using a statistical analysis based on a 23 factorial design. The ratio between sawdust and alkanine solution (RSL = 0.5–1.5 g/100 mL), US amplitude (A = 20–60%), and working temperature (t = 30–50 °C) were selected as process factors. The optimal operating conditions to maximize the reducing sugar yield (138.15 mg GE /gsubstrate) were found as following: solid/liquid ratio RSL,opt = 1.25 g/100 mL, US amplitude Aopt = 60%, and and pretreatment temperature topt = 50 °C. The overall outcomes clearly confirmed the intensification of delignification by ultrasound assisted alkaline pretreatment

At 12:28 UTC (8:28 PM, local time) on 15 January 2023, a shallow, moderate earthquake with a magnitude (Mw) of 4.7 and a depth of one (1) kilometer shook the northern part of Leyte Island in the central part of the Philippines. The ground shaking was felt at PHIVOLCS Earthquake Intensity Scale (PEIS) VI, (very strong) equivalent to Modified Mercalli Intensity (MMI) VI in areas along the strike of the Leyte segment of the Philippine Fault. Even though this earthquake is classified as moderate in size, significant geologic, structural, and socio-economic impacts were documented. Most of the earthquake impacts that include surface rupture, liquefaction, and mass movements are limited near the epicentral area. The earthquake produced an 8-km-long surface rupture, the first documented rupture generated by a magnitude &lt;6 along the Philippine Fault, and is unusual in other surface rupturing earthquakes worldwide. It injured 18 persons and damaged 434 residential buildings and 26 public infrastructures which amounts to about 500 thousand US dollars. Structural damages were caused by surface rupture and/or poor engineering construction practices. Analysis of the seismic waveform and recorded peak ground acceleration (PGA) suggests that the subsurface geology influenced the ground motion amplification in an area near the epicenter. Based on the hypocenter, focal mechanism solution, aftershock distribution, and actual field observation, the causative fault for this event is the northern end of the Philippine Fault – Leyte segment. Moderate in size, this earthquake emphasizes the need and importance of documenting moderate-sized earthquakes as a tool and guide for medium and long-term earthquake risk assessment and resiliency.

Background: The bacterium Capnocytophaga spp. is a part of the oral microbiome of dogs, which has zoonotic potential. This study aimed to assess factors that influence the prevalence of Capnocytophaga cynodegmi and Capnocytophaga canimorsus in Wrocaw’s dog population. Methods: Molecular detection (PCR) involved 105 swabs, examining parameters such as oral cavity condition, underlying health issues, recent antibiotics, age, medications, material collection, and dog chews. Results: The study highlighted significant associations between the presence of Capnocytophaga cynodegmi and oral cavity condition, material collection method, and use of dog’s chews. Conclusions: Correlations obtained in this study between the oral health of Wroclaw's dog population and the presence of Capnocytophaga cynodegmi suggest its significance in the oral microbiome of dogs. Limitations, including the small sample size, highlight the need for more research to comprehensively understand additional factors that affect the prevalence of Capnocytophaga spp. in dogs

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

The assortment of low-cost 3D printers for “in-practice” use, e.g., for clear aligner therapies, is ever increasing. To address concerns about the accuracy of orthodontic models produced on such printers when cost efficient modes of 3D printing are employed, this study examined the effect of print model body type and print angulation on accuracy. Six printing-configuration groups were included: 2 model types (solid or hollow shell) combined with 3 print angles (0°, 70°, or 90°) with 10 models/group; all models were printed with 100-µm layer thickness using a digital light processing-based 3-dimensional printer. Eleven selected structures and distances were measured on the printed models with a digital microscope and compared to the same measures on a digitized master model. The clinically-acceptability range was set at ±0.25 mm difference from the master model for single tooth measurements (intra-tooth) and ±0.5 mm for cross-arch measurements (inter-tooth). For individual measurements across all models, 98% fell within clinical acceptability. For mean measurements within each model group, only canine height for the shell-0° model had a mean difference (0.26 mm ± 0.03) outside the clinically acceptable range for intra-tooth measurements. Standard deviations for all intra-tooth measurements were within 0.07 mm. While none of the mean inter-tooth measurements exceeded the acceptability range, the standard deviations were larger (0.04 to 0.30 mm). Accuracy of orthodontic models for clear aligner therapies was not impacted beyond the clinically acceptable range when altering model body type and print angulation to improve efficiency of 3D printing. These findings suggest greater flexibility of the practitioner to alter print settings to address time and cost efficiency in various clinical scenarios and still maintain clinically acceptable model accuracy.

Background: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and large extent of non-additive genetic variance associated with its autotetraploid genome. Methods: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as autotetraploid and diploid dosage, plus allele ratios) and SNP marker subsetting (all available SNPs; only genic regions; only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used Genotyping by Sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and onset of flowering, assessed on 143 genotyped plants from a genetically-broad European reference population and their phenotyped half-sib progenies. Results: On average, allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), SNP subsetting offered an advantage compared with any tested subsettings (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting reached better performances. We also released Legpipe2, a SNP calling pipeline tailored for reduced representation (GBS, RAD) medium-sized genotyping experiments.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x104 – 2x107 CFU per ml and has a sensitivity of S = 1.655x105 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10-9 grams (g) which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).