Children from rural areas face numerous possibilities for neurodevelopmental conditions that may compromise their well-being and optimal development. Neuropsychology and electroencephalography (EEG) have shown strong agreement in detecting correlations between these two variables and suggest an association with specific environmental and social risk factors. The present meta-analysis aims to integrate the qualitative and quantitative EEG findings, their relationship with cognitive impairment in children living in vulnerable or rural environments, and the main risk factors influencing EEG abnormalities. The method for this purpose was based on a systematic string-based review from Ebscohost and Web of Science, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Qualitative and quantitative analyses were conducted from the outcomes that complied with the selected criteria. A total of 92 records were identified; however, only 20 were eligible, considering 11 for qualitative and 9 for quantitative analysis. The findings highlight a significant amount of literature on EEG and its relation with cognitive impairment from studies in children with epilepsy and malnutrition. In general, there is evidence about the advantages of implementing EEG diagnosis and research techniques in children living under risk conditions. Further research is needed to better describe and integrate the state of the art regarding EEG features extraction.

The current classification of acute myeloid leukemia (AML) relies largely on genomic alterations. AML with mutated Nucleophosmin1 (NPM1-mut) is the largest of the genetically defined groups, involving about 30% of adult AMLs and is currently recognized as a distinct entity in the actual AML classifications. NPM1-mut AML usually occurs in de novo AML and is associated predominantly with a normal karyotype and relatively favorable prognosis. However, NPM1-mut AMLs are genetically, transcriptionally, and phenotypically heterogeneous. Furthermore, NPM1-mut is a clinically heterogenous group. Recent studies have in part clarified the consistent heterogeneities of these AMLs and have strongly supported the need for an additional stratification aiming to improve the therapeutic response of the different subgroups of NPM1-mut AML patients.

Caffeine is a naturally occurring alkaloid found in various plants. It acts as a stimulant, antioxidant, anti-inflammatory and even an aid in pain management, and is found in several over-the-counter medications. This naturally derived bioactive compound is the best-known ingredient in coffee and other beverages, such as tea, soft drinks, and energy drinks, and is the most widely consumed substance worldwide. Therefore, it is extremely important to research the effects of this substance on the human body. With this in mind, caffeine and its derivatives have been extensively studied to evaluate its ability to prevent diseases and exert anti-aging and neuroprotective effects. This review is intended to provide an overview of the effects of caffeine on cancer, cardiovascular, immunological, inflammatory, and neurological diseases, among others. The heavily researched area of caffeine in sports will also be discussed. Finally, recent advances in the development of novel formulations, in the form of dietary supplements of caffeine and nanocarriers, to enhance the bioavailability of caffeine and its beneficial effects will be discussed. On the other hand, caffeine may contribute to elevated blood pressure, anemia, and migraine.

Shrimps are under the influence of several environmental factors such as fluctuation of physical and chemical parameters of the water affected by variations in rainfall, temperature, salinity, and pH. These factors have also been identified as risk factors for shrimp disease outbreaks. Despite the high levels of production, shrimp producers suffered significant economic losses in years, mainly due to the presence of diseases that now plague the industry. In particular, viral diseases have had and will continue to have profound impact on industry growth. In response to stress such environmental or pathophysiological, cells are able to up regulating selectively the expression of a protein group known as Heat Shock Proteins (HSPs). In a recent search at the literature we observed a close relation between HSP70 with apoptotic proteins and others stress proteins such HSP60 and HSP90. Moreover, the response of shrimp to viral stress was examined, some of which are correlated to the reactions of HSP70. Thus, the aim of this review is to describe the current knowledge on the status of stress responses in shrimps, particularly HSP70 responses, triggered by viruses.

The main objective of this work is to study the effects of carbon nanotubes (CNT) on the strength and electrical properties of cement mortar. Molecular dynamic simulations (MDS) were carried out for the mechanical and electrical properties of the cementitious composite and the associated mechanisms. To model the atomic structure of the Calcium-Silicate-Hydrates (C-S-H) gel, tobermorite 11Å was chosen. Single-walled carbon nanotubes (SWCNTs) embedded in tobermorite structure were tested numerically. In particular, the effect of the concentration of CNT in cement paste was studied. An innovative experiment of electrical characterization of a cementitious composite of carbon nanotubes has been developed.

The connexin gene family is the most prevalent gene that contributes to hearing loss. Connexins 26 and 30, encoded by GJB2 and GJB6 respectively, are the most abundant expressed connexins in the inner ear. Connexin 43 which is encoded by GJA1 appears to be widely expressed in various organs, including the heart, skin, brain, and inner ear. The mutations that arise in GJB2, GJB6 and GJA1 can all result in comprehensive or non-comprehensive genetic deafness in newborns. As it is predicted that connexins include at least 20 isoforms in humans, the biosynthesis, structural composition, and degradation of connexins must be precisely regulated so that the gap junctions can operate properly. Certain mutations result in connexins possessing a faulty subcellular localization, failing to transport to the cell membrane and preventing gap junction formation, ultimately leading to connexin dysfunction and hearing loss. In this review, we provide a discussion of the transport models for connexin 43, connexins 30 and 26, mutations affecting trafficking pathways of connexin 26, the existing controversies in trafficking pathways of connexins, and the molecules involved in connexin trafficking and their functions. This review can contribute to a new way of understanding the etiological principles of connexin mutations and finding therapeutic strategies for hereditary deafness.

Objective: To carry out a bibliometric analysis study of systematic reviews and meta-analyses in dentistry, divided into different thematic areas. Material and method: A search was conducted in the Science Citation Index-Expanded on the core collection of Web of Science, they were selected from the area of Dentistry and Oral Surgery and Medicine categories, the data was downloaded on April 20, 2022 and The 100 most cited articles from each of the thematic areas were selected. Results: An increase in this type of articles was observed in the last decade in the areas of pediatric and medical dentistry and oral pathology. The thematic area that received the most citations was periodontics. The two authors with the most citations are Zwahlen, Marcel and Pjetursson, Bjarni Eluar. The countries that receive the most citations are European, along with the USA and China. The topics that are most published in this type of article deal with Cancer with 50 publications, caries treatment with 25 and fluoridation with 1. The entities that finance this type of articles the most are private companies (26.76%). Conclusions: Together with an exponential increase in the number of publications in dentistry, there has been an increase in the number of publications in systematic reviews. The areas publishing the most articles and having the most citations are Periodontics and Implantology, despite the fact that the most studied topic is cancer.

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry and science related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, rational design of combination therapies and the global response to the Covid19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human focused, systems-based approach to drug discovery and research.

The purpose of this project was to demonstrate the potential of converting an existing internal combustion engine for hydrogen operation at relatively low cost and to optimize the combustion process for ultra-low NOx emissions. The conversion has been carried out on a 450cc naturally aspirated single cylinder engine. The first baseline measurements and setup have shown lower NOx emissions than the baseline gasoline engine (without catalytic converter) for similar power output and engine efficiency. Further optimization of the combustion process allowed to achieve Euro VI and (latest European Commission proposal) Euro VII heavy-duty NOx limits without exhaust gas aftertreatment system (EATS) in steady state conditions. The concept is very promising and the knowledge gained should allow for further optimization to achieve near zero NOx emissions at high engine efficiency and power output with supercharging. It should also allow an efficient conversion of other engine types for different applications. In particular, a project with the aim to convert a heavy duty 6 cylinder engine intended for public transport buses has started. It follows a feasibility study which has shown the competitiveness of the hydrogen engine for this application.

In this study, the Bohler K 190 steel was used. The steel was manufactured by the powder metallurgy (PM) process. The boronizing process was carried out in the range of 1173 to 1323 K, for 1-10 h. The samples were boronized in solid medium, called the Durborid powder mixture. For the microstructural observations, the scanning electron microscopy was utilized for determining the morphology of interfaces and measuring the layers’ thicknesses. The phase composition of boride layers was also determined with X-ray diffraction analysis. To investigate the redistribution of chemical elements redistribution during the boronizing process, the EDS mapping and EDS point analysis were used. The boride layers were constituted by FeB and Fe2B phases except for 1173 K for 1 h. The values of Vickers microhardness of Fe2B, FeB and transition zone were estimated. Finally, to assess the boron activation energies in FeB and Fe2B, the so-called integral method was applied and the results in terms of activation energies were confronted with the literature data.

The Societal Patterns Evolution Model (SPEM) (Gakh, 2023a) has been developed to apply to socio-technical systems. It contains patterns representing stages of societal development. Mapping of these patterns to the development of Information and Communication Technologies (ICTs) and Information Systems was presented at FedCSIS 2022 conference (Gakh, 2022c). This paper discusses the application of SPEM to model the development of three pillars of sustainability: economic, social, and environmental (Purvis, et al., 2019; United Nations, 2023).

Begomovirus infection in plant causes a great economic loss in many countries every year. Increasing rate of the infectivity of this single stranded DNA virus forces to study of its transmission in detail for the necessary researches regarding the control of this disease. This pathogenic virus is whitefly vector borne and transferred from one plant to another plant during the suckling of phloem sap by that vector. Viral transmissibility through this insect vector may depend on the genetic variations within the cryptic species groups. Two distinct categories of begomoviruses viz., bipartite and monopartite types consist of different genome organization. Virion particles modify the intracellular environment of the host according to their need of replication and survival. Viral replication takes place through RCR as well as RDR methods. Interplay among host, vector and pathogen is crucial for the establishment of infection. Several endosymbiotic organisms living within the insect vector also have vital role here. Being infected with this virus, host plant responds with defensive activities like TGS, PTGS, autophagy, hormonal regulation, metabolic alteration etc. However, virus also counteracts those through the manipulation of several pathways of cellular events. It is necessary to study in different directions and utilize advanced molecular biological techniques to develop begomovirus resistance within plants.

This paper applies a new artificial intelligence architecture, the Temporal Fusion Transformer (TFT), for the joint GDP forecasting of 25 OECD countries at different time horizons. This new attention-based architecture offers significant advantages over other deep learning methods. First, results are interpretable since the impact of each explanatory variable on each forecast can be calculated. Second, it allows to visualize persistent temporal patterns and to identify significant events and different regimes. Third, it provides quantile regressions and permits to train the model on multiple time series from different distributions. Results suggest that TFTs outperform regression models, especially in periods of turbulence such as the COVID-19 shock. Interesting economic interpretations are obtained depending on whether the country is domestic demand-led or export-led growth. In essence, TFT is revealed as a new tool that artificial intelligence provides to economists and policy makers, with enormous prospects for the future.

Abstract. Can we nowadays keep a qualitative difference between the primitive and advanced Theory-of-Mind? The old criteria have become blurry. In addition, it is clear that in ‘apes’ lifestyle’ it is not necessary to use the communicative-cognitive basic abilities which became indispensable in ‘the new lifestyle’. Thus, it is usual to conclude that apes would have to some degree such abilities. However, this article tries to reformulate and defend that qualitative difference. Thus, after underlining the contrast between two kinds of mental states (‘contents’ and ‘expectations’), I apply it to the detection of foreign mental states as well. Then, three points are proposed: First, ‘vicarious expectations’ sustain the primitive ToM; second, a subject can have no expectation of inner states which are intrinsically impossible for him; third, the state of interacting with ourselves as with a different person –e.g., the thinking what others think of us– cannot be a vicarious expectation of ours, but it requires the estimation of foreign contents. From this hypothesis, I deduce that vicarious expectations are unable to sustain self-conscious emotions or the really effective reception of pointing gestures. These abilities could appear only when ‘the estimation of foreign contents’ –i.e., the origin of the advanced ToM– arose.

This paper mainly used database technology, machine learning, thermodynamic calculation, experimental verification, etc., on integrated computational materials engineering. The interaction between different alloying elements and the strengthening effect of precipitated phases are investigated mainly for martensitic ageing steels. Modelling and parameter optimization were performed by machine learning, and the highest prediction accuracy was 98.58%. Investigated the influence of composition fluctuation on performance and correlation tests to analyze the influence of elements from multiple perspectives. Furthermore, screen out the three-component composition process parameters with composition and performance with high contrast. Thermodynamic calculations studied the effect of alloying element content on the nano-precipitation phase, Laves phase, and austenite in the material. The heat treatment process parameters of the new steel grade were also developed based on the phase diagram. A new type of martensitic ageing steel was prepared by selected vacuum arc melting. The sample with the highest overall mechanical properties had a yield strength of 1887 MPa, a tensile strength of 1907 MPa, and a hardness of 58 HRC. The sample with the highest plasticity had an elongation of 7.8%. The machine learning process for the accelerated design of new ultra-high tensile steels was found to be generalizable and reliable.

The Internet of Vehicles (IoV) is an emerging field that has attracted significant attention due to its potential to transform transportation and mobility. IoV enables the development of new services and applications that can improve transportation systems' efficiency, safety, and sustainability. However, ensuring secure and trustworthy communication among the different components of an IoV system is a critical challenge that needs to be addressed. This paper proposes a blockchain-enabled communication framework for secure and trustworthy IoV applications. The proposed framework leverages the security and decentralization features of blockchain technology to provide secure communication channels for different components of the IoV system, including vehicles, infrastructure, and service providers. The proposed framework provides an identity management system to authenticate and authorize users and devices, thereby preventing unauthorized access and data breaches. To evaluate the effectiveness of the proposed framework, we conducted experiments using a real-world IoV scenario, and the results demonstrate that the proposed framework can provide secure and trustworthy communication for IoV applications. The proposed blockchain-enabled communication framework offers a promising approach to address the security and trust challenges in IoV communication systems.

This study seeks to interrogate the degree to which lecturers and students of higher institutions in Nigeria perceive the role of lecturers doubling as parents under the term lecturenting, i.e., a coinage used to refer to a person who performs the dual roles of lecturing and parenting students of higher institutions. The study is based on Professor Obiora Ike’s ideology of communication of values, normally applicable to traditionally homes only. The research used a quantitative survey of 266 undergraduates and 109 lecturers, totaling 375 respondents from two purposively selected higher institutions in Nigeria, namely: Edo state University Uzairue and Federal Polytechnic Auchi, both in Etsako West Local Government Area of Edo state, Nigeria. A questionnaire with a set of nine semi-structured questions was used to obtain data from the students during the school semesters between July 15 and August 31, 2022. The study was based on the value theory. Findings indicate that lecturers frequently engage in lecturenting which helped improve the academic performance of students but shows that students do not want lecturenting on their behavioral change. The study concludes that the more lecturers engage in Lecturenting, the more positive impact it will have on their students. It is recommended that lecturers should engage in the practice of lecturenting as it helps to improve student academic performance and that students should perceive lecturenting as positive as well as be favorably disposed to it and approach their lecturers for counselling frequently.

Burkina Faso is a sub-Saharan African country with a high poverty rate that has quadruplicated its population in the last half fifty years, that is, from 4.5 to 18 million inhabitants. Such demographic changes together with an intense migration process from rural areas to large cities, among other issues, are contributing to a rapid process of socio-cultural transformation. In this context, changes in both traditional and contemporary housing are analyzed and a complete ther-mo-hygrometric evaluation is carried out by processing significant data from on-site measure-ments to shed new light on the response of the said dwellings to the environmental and local cultural values. Results show that the introduction of land ownership linked to climate change and the increasing scarcity of natural resources are forcing native ethnic groups to modify their traditional ways of life, threatening their subsistence. Consequently, we can prove that the new building typologies are not in the least suitable for the climatic conditions nor the rich cultural heritage of Burkina Faso. This fact, negatively affects the possibility of revitalizing vernacular and environmentally-oriented solutions for the contemporary world and the necessary advance to-wards a more sustainable architecture.

Polylactic acid (PLA) was modified with three types of MVOs, which are the epoxidized soybean oil (ESBO), maleinized sunflower oil (MSO) and maleinized olive oil (MOO), at different weight fractions. A co-rotating twin screw extruder was used to produce composite materials by melt mixing process. The effect of MVOs content, from 2.5% to 10%, on the morphology, mechanical properties, density and water absorption were investigated in detail. Addition of ESBO and maleinized vegetable oils leads to a slight decrease in density of PLA from 1.252 to 1.231 g/cm3. As the concentration of MVO in PLA increases, the amount of water absorption also increased and the highest water absorption value was observed in P10MSO. In general, the elastic modulus (EM) was slightly changed by the addition of MVO to PLA, while the tensile strength (TS) decreased. Due to the plasticizing effect of MVOs, an increase in the Izod impact strength was obtained.

When discussing the gauge symmetries of any theory, the Henneaux-Teitelboim transformations are often underappreciated or even completely ignored, due to their on-shell triviality. Nevertheless, these gauge transformations play an important role in understanding the structure of the full gauge symmetry group of any theory, especially regarding the subgroup of diffeomorphisms. We give a review of the Henneaux-Teitelboim transformations and the resulting gauge group in the general case, and then discuss its role in the applications to the class of topological theories called nBF models, relevant for the constructions of higher gauge theories and quantum gravity.

Peyronie's disease (PD) is a benign condition caused by plaque formation on the tunica albuginea of the penis. It is associated with penile pain, curvature, and shortening, and contributes to erectile dysfunction, which worsens patient quality of life. In recent years, understanding of the detailed mechanisms and risk factors involved in development of PD has been increasing. In this review, the pathological mechanisms and several closely related signaling pathways, including TGF-β, WNT/β-catenin, Hedgehog, YAP/TAZ, MAPK, ROCK, and PI3K/AKT, are described. Findings regarding cross-talk among these pathways are then discussed to elucidate the complicated cascade behind tunica albuginea fibrosis. Finally, various risk factors including genetic involved in the development of PD are presented and their association with the disease summarized. The purpose of this review is to provide better understanding regarding involvement of risk factors in the molecular mechanisms associated with PD pathogenesis, as well as provide insight into disease prevention and novel therapeutic interventions.

In the last two decades, the continuous ever growing demand for energy has determined a significant development in the production of photovoltaic (PV) modules. Anyway, a critical and very important issue in the module design process is the adoption of suitable encapsulant materials and technologies for cell embedding. Therefore, adopted encapsulants have a significant impact on modules efficiency, stability and reliability, and to ensure the unchanged performance of PV modules in time, the encapsulant materials must be selected properly. The selection of encapsulant materials must maintain a good balance between the encapsulant performance in time and costs, related to materials production and technologies for cells embedding. However, the encapsulants must ensure excellent isolation of active photovoltaic elements by the environment, preserving accurately the PV cells against humidity, oxygen and accidental causes that may compromise the PV modules function. This review provides an overview of different encapsulant materials, their main advantages and disadvantages in adoption for PV production, and also in relation to used encapsulant technologies for cell embedding, additives and the interaction of these materials with other PV components.

Using flexible AC transmission system (FACTS) devices in power systems while adhering to some equality and inequality constraints, researchers around the world sought to address this issue with the objectives of improving the voltage profile, reducing power losses in transmission lines, and increasing system reliability and safety. The recent development of FACTS controllers opens up new perspectives for safer and more efficient operation of electrical power networks by continuous and rapid action on power systems parameters, such as phase angle shifting, voltage injection and line impedance compensation. Thus, an improvement on voltage profile and enhancement of power transfer capability can be obtained. It is for that, the idea behind the FACTS concept is to enable the transmission system to be an active element in increasing the flexibility of power transfer requirements and in securing stability of integrated power system. It may also be effective in transient stability improvement, power oscillations damping and balancing power flow in parallel lines. The primary issue that has significantly piqued the interest of a number of researchers working in this field is the FACTS optimization problem, which involves determining the optimal type, location, and size of FACTS devices in electrical power systems. For solving this mixed integer, nonlinear and non-convex optimization problem, this paper provides an in-depth and comprehensive review of the various optimization techniques covered in published works in the field. In this review, a classification of optimization techniques in five main groups that are widely used, such as classical optimization techniques or conventional optimization approaches, Meta heuristic methods, analytic methods or sensitive index methods and mixed or hybrid methods, is summarized. In addition, a performance descriptions and comparison of these different optimization techniques are discussed in this study. Finally, some advice is offered for future research in this field.

The Atlantic Goliath Grouper Epinephelus itajara (Lichtenstein, 1822) is thought to occur on both sides of the Atlantic, from the Carolinas (USA) to Brazil in the western Atlantic, and from North Senegal to North Angola off West Africa in the eastern Atlantic. While there are fairly good data on their distribution in the western Atlantic, genetic verification of species status, confirmed occurrences, population status, fishing reports, and trade data are almost non-existent off West Africa. Part of the problem is that tropical West African countries lack a network of marine reserves that might protect this species. Add to this destruction of mangrove forests and other coastal habitats on which the species depends when in the post-larval and juvenile stages coupled heavy pollution and intense overfishing and it becomes clear that their survival is deeply threatened. The focus of this paper is to describe all of the known historical data and examine all current data to better evaluate their present status.

The rapid development of LiDAR technology has promoted great changes in forest resource surveys. The airborne LiDAR point cloud can provide precise tree height and detailed vertical structure of the tree stands. Coordinating some representative ground sample plots, LiDAR can be used to estimate key forest resource indicators such as forest stock volume, diameter at breast height, and forest biomass at a large scale. By establishing relationship models between the forest parameters of sample plots and the calculated parameters of LiDAR, these developments may eventually expand the models to large-scale forest resource surveys of entire areas. In this study, eight sample plots in northeast China are used to verify and update the information using point cloud obtained by the LiDAR scanner riegl-vq-1560i. Firstly, the tree crowns are segmented using the profile-rotating algorithm, and dominant trees height are used to check and rectify the tree locations. Secondly, considering the correlation between forestry parameters and tree species, we establish models to distinguish between species using geometric characteristics of tree crowns. Thirdly, when the tree species is known, parameters such as height, crown width, diameter at breast height, biomass and stock volume can be extracted from trees. The prediction models of forestry parameters can also be verified, which can be extended to accurate large-scale forestry surveys based on LiDAR data. Finally, experiment results demonstrate that the F-score of the eight plots in the tree segmentation exceed 0.95, the accuracy of tree species correction exceeds 90%, and the R2 of tree height, east-west canopy width, north-south canopy width, diameter at breast height, above-ground biomass and stock volume are 0.893, 0.757, 0.694, 0.840, 0.896 and 0.891, respectively. The above results indicate that the LiDAR-based estimation of forestry parameters is practical and that these forestry parameter prediction models can be widely applied in forest resource monitoring.

Based on the marine natural products piperafizine B, X334 and our previously reported compound 4m, fourteen novel 3,6-diunsaturated 2,5-diketopiperazine (2,5-DPK) derivatives (1-2, 4-6, 8-16), together with two known ones (3 and 7), were designed and synthesized as anticancer agents against cell lines A549 and Hela. The MTT assay results showed that the derivatives 6, 8-12 and 15 had moderate to good anticancer capacities with the IC50 values ranging from 0.7 to 8.9 μM. Among them, compound 11 with naphthalen-1-ylmethylene and 2-methoxybenzylidene functions at the 3- and 6-positions of 2,5-DPK ring, respectively, displayed good inhibitory activities to both cancer cells A549 (IC50 = 1.2 μM) and Hela (IC50 = 0.7 μM). It could also induce apoptosis and obviously block the cell cycle progression at G2/M phase in both cells at 1.0 μM. The electron withdrawing functions might not be favorable for the derivatives with high anticancer activities. Additionally, compared to piperafizine B and X334, these semi-N-alkylated derivatives have high liposolubilities (> 1.0 mg•mL-1). Compound 11 can be further developed aiming to the discovery of novel anticancer candidate.

Seafood products are the main dietary source of n-3 polyunsaturated fatty acids (n-3 PUFA), which are essential for human health. However, due to the widespread use of processed fish products, the presence of these n-3 PUFAs may be subject to changes related to different processing methods. The aim of this study was to determine the fatty acid composition, with a focus on n-3 polyunsaturated fatty acids (n-3 PUFAs), in different processed fish and shellfish food of EU and non-EU origin purchased in supermarkets and ethnic food shops in Messina (Italy), using gas chromatography with flame-ionization detector (GC-FID). From the fatty acid profile, the atherogenic index (AI), thrombogenicity index (TI) and flesh-lipid quality index (FLQ) were determined: 0.13-1.04 (AI), 0.31-9.84 (TI) and 0.41-29.90 (FLQ). The percentages of saturated (SFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids had the following ranges: 13.55-50.48%, 18.91-65.58%, 13.84-52.73%, respectively. All samples showed a good presence of PUFAs and, in particular, eicosapentaenoic (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3) were the main n-3 polyunsaturated fatty acids (n-3 PUFA).

A planar microwave sensor devoted to the detection of humidity in underwear and clothes in general is proposed. The ultimate goal of the sensor is to detect the presence of liquids in fabrics, of interest to aid patients that suffer from certain pathologies, such as hyperhidrosis and enuresis. The main target in the design of the sensor, considering the envisaged application, is simplicity. Thus, the sensor operates at a single frequency, and the working principle is the variation in the mag-nitude of the transmission coefficient of a matched line loaded with an open-ended quar-ter-wavelength sensing stub resonator. The stub, which must be in contact with the so-called fabric under test (FUT), generates a notch in the transmission coefficient with a resonance frequency that depends on the humidity level of the fabric. By designing the stub with a moderately high quality factor, the variation in the resonance frequency causes a significant change in the magnitude level at the operating frequency, the resonance frequency when the sensing stub is loaded with the dry fabric, and the presence of liquid can be detected by means of an amplitude detector. A prototype device is proposed and experimentally validated.

Neutrophils are the most abundant immune cells and make up about 70% of white blood cells in human blood and play a critical role as the first line of defense in the innate immune response. They also help regulate the inflammatory environment to promote tissue repair. However, in cancer, neutrophils can be manipulated by tumors to either promote or hinder tumor growth depending on the cytokine pool. Studies have shown that tumor-bearing mice have increased levels of neutrophils in peripheral circulation, and that neutrophil-derived exosomes can deliver various cargos, including lncRNA and miRNA, which contribute to tumor growth and degradation of extracellular matrix. Exosomes derived from immune cells generally possess anti-tumor activities and induce tumor-cell apoptosis by delivering cytotoxic proteins, ROS generation, H2O2 or activation of Fas-mediated apoptosis in target cells. Engineered exosome-like nanovesicles have been developed to deliver chemotherapeutic drugs precisely to tumor cells. However, tumor-derived exosomes can aggravate cancer-associated thrombosis through the formation of neutrophil extracellular traps. Despite the advancements in neutrophil-related research, a detailed understanding of tumor-neutrophil crosstalk is still lacking and remains a major barrier in developing neutrophil-based or targeted therapy. This review will focus on the communication pathways between tumors and neutrophils, and the role of neutrophil-derived exosomes (NDEs) in tumor growth. Additionally, potential strategies to manipulate NDEs for therapeutic purposes will be discussed.

To study the feasibility and effect of compounding lignin and its derivatives to improve expansive soil, the physical properties, mechanical properties, and microstructure of the improved soil mixed with calcium lignosulfonate alone, calcium lignosulfonate and lignin fibers were investigated through indoor experiments and electron microscope scanning. Select samples with better performance for water stability tests, and discuss the improvement mechanism of expansive soil by combining macroscopic mechanical changes with microstructural characteristics. The research results show that the addition of calcium lignosulfonate can reduce the water content of the soil and enhance its strength of the soil. The overall performance is the best when the calcium lignosulfonate content is 3%. 3% calcium lignosulfonate compounded with 1.5% lignin fiber has the best all-around performance; the composite improved soil has a better pore-filling effect, the whole is more compact, and the connection between particles significantly enhances the strength, which greatly inhibits the development of cracks good water stability. Lignin and its derivatives compound improved expansive soil have better effect than traditional improvement methods, and have no pollution to the environment, which can provide a particular reference for engineering practice

To study the feasibility and effect of compounding lignin and its derivatives to improve expansive soil, the physical properties, mechanical properties, and microstructure of the improved soil mixed with calcium lignosulfonate alone, calcium lignosulfonate and lignin fibers were investigated through indoor experiments and electron microscope scanning. Select samples with better performance for water stability tests, and discuss the improvement mechanism of expansive soil by combining macroscopic mechanical changes with microstructural characteristics. The research results show that the addition of calcium lignosulfonate can reduce the water content of the soil and enhance its strength of the soil. The overall performance is the best when the calcium lignosulfonate content is 3%. 3% calcium lignosulfonate compounded with 1.5% lignin fiber has the best all-around performance; the composite improved soil has a better pore-filling effect, the whole is more compact, and the connection between particles significantly enhances the strength, which greatly inhibits the development of cracks good water stability. Lignin and its derivatives compound improved expansive soil have better effect than traditional improvement methods, and have no pollution to the environment, which can provide a particular reference for engineering practice.

The Anthropocene epoch marks a critical phase in the history of humanity, where anthropogenic activities have significantly impacted our planet. Along the unpreceedendent ecological crises, the Anthropocene worldview has raised existential questions with a cultural and ethical discourse that recognises intrinsic value and calls for more responsible sustainable living. To address these challenges collectively, a broader perspective is required, guided by a unified sense of purpose towards personal and planetary health. In this context, the role of religious leaders in shaping the social and environmental worldviews of their followers cannot be underestimated. Religious teachings provide a moral framework for promoting climate action, global ethics, indigenous people, peace, and justice, and many other aspects of planetary health. By assessing the global ecological crises through the lens of Islam; Religion of Nature, or Din al-Fitra, and its environmental teachings across all realms, we can gain insights into humanity’s connection to the fabric of creation and its interaction with this world. These value-leden principles are integrated with accountability; thus, the role of Muslim religious leaders considering the planetary-scale threats warrant further elucidation; recognizing that many other faiths and faith leaders can similarly contribute together for common good.

Porous structured metallic implants are preferable as bone graft substitutes due to their faster tissue integration mediated by bone in-growth and vascularization. The porous scaffolds/ implants should also mimic the graded structure of natural bone to ensure a match of mechanical properties. This article presents a method to design graded porous structured acetabular implant and identifies the suitable parameters for manufacturing the model through additive manufacturing. The design method is based on slice-wise modification to ensure continuity of gradation. Modification of the slices was achieved through the binary image processing route. A geodesic dome type design was adopted for developing the acetabular cup model from the graded porous structure. The model had a solid shell with the target porosity and pore size gradually changing from 65% and 950 µm, respectively, in the inner side to 75% and 650 µm, respectively, towards the periphery. The required dimensions of the unit structures, and the combinations of pore structure and strut diameter to obtain the target porosity and pore size were determined analytically. Suitable process parameters were identified to manufacture the model by Direct Metal Laser Sintering (DMLS) using Ti6Al4V powder after carrying out a detailed experimental study to minimize the variation of surface roughness and warping over different build angles of the strut structures. A dual contour scanning was implemented to simplify the scan strategy. The minimum diameter of struts that could be manufactured using the selected scanning strategy and scanning parameters was found to be 375 µm. Finally, the model was built and from the micro-CT data, the porosities and pore sizes were found to be closely conforming to the designed values. The stiffness of the structures, as found from compression testing, was also found to be well matching with that of human trabecular bone. Further, the structure exhibited compliant bending-dominated behavior under compressive loading.

The inappropriate use of pesticides in the world and particularly in Africa, explains their presence in various environmental compartments. This presence in the environment has harmful consequences on living beings, especially humans. This review, based on scientific publications, aims to analyze the problem of pesticides in Africa. From a corpus of 81 articles published in Africa on this topic between 1996 and 2019, we have outlined the issues relating to phytosanitary practices, environmental pollution, food contamination, intoxication of farmers and consumers, qualitative and quantitative analysis methods used, as well as the regulations on the subject and their application in Africa. Based on an analysis of the factors that are at the root of the problems of environmental pollution, contamination and health that they cause in Africa, possible solutions were proposed to produce healthy products and preserve our common environmental heritage.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA approved AI applications for breast imaging, but adoption and utilization are widely variable and overall low. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer and many of the most exciting research and available AI applications focus on cancer detection for mammography. There are however multiple additional potential applications for AI in breast imaging including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Advanced Nano structural hard coatings are thin materials films that range in thickness from a few nanometers to a few micrometers and are applied to different surfaces to increase their hardness and wear resistance. Physical vapor deposition (PVD) or chemical vapor deposition (CVD) methods are frequently used to deposit these coatings. These coating’s distinctive characteristics result from their microstructure, which is made up of material columns or grains with a diameter of only a few nanometers. Increased hardness, higher wear resistance, and improved tribological properties result from these short dimensions. In applications with significant wear and/or high contact pressures, such as cutting tools, bearings, and engine parts, the usage of sophisticated Nano structural hard coatings is crucial. Advanced Nano structural hard coatings include, 1. Amorphous carbon coatings with high hardness, low friction, and exceptional wear resistance are known as diamond-like carbon (DLC) coatings. DLC coatings are frequently used in a variety of industries, including the automotive, aerospace, and biomedical ones. 2. Coatings made of titanium nitride (TiN): These metallic coatings have high hardness and wear resistance. Cutting tool, machining, and aerospace industries frequently use TiN coatings. 3. Chromium nitride (CrN) coatings: These coatings have great corrosion resistance, good wear resistance, and high hardness. Cutting tools, gears, and bearings are just a few of the objects that use CrN coatings. 4. Tungsten carbide (WC) coatings: These coatings, which have a high degree of hardness and wear resistance, are frequently employed in cutting tools and other applications that require wear resistance. Advanced Nano structural hard coatings provide many advantages over conventional coatings, including better hardness, increased wear resistance, and improved tribological qualities. The automotive, aerospace, and biomedical industries are just a few that could use these coatings. In this paper the author will explain about the design synthesis and applications of advanced Nano structural hard coating in aerospace and automotive applications.

The makeup of human microbiota has been linked to a number of autoimmune disorders. Recent developments in whole metagenome sequencing and 16S rRNA sequencing technology have considerably aided research into the microbiome and its relationship to disease. Due to the inherent high dimensionality and complexity of data generated by high-throughput platforms, conventional bioinformatics techniques could only provide an inadequate explanation for the most relevant changes and seldom provide correct predictions. Machine learning, on the other hand, is a subset of artificial intelligence applications that enable the untangling of high-dimensional systems and intricate knots in correlation by learning complex patterns and improving automatically from training data without being explicitly programmed. Machine learning is increasingly being utilized to research the influence of microbes on the onset of illness and other clinical features since computer power has increased dramatically in the last few decades. In this review paper, we focused on emerging methodological approaches of supervised machine learning algorithms for identification of autoimmune disorders utilizing metagenomics data, as well as the potential benefits and limitations of machine learning models in clinical applications.

The main goal of this article is the characterization of Herz-type Besov-Morrey spaces K˙p,qαN˙μ,rs and Triebel-Lizorkin-Morrey spaces K˙p,qαE˙μ,rs via ball means of differences, atomic, molecular and wavelet decompositions. There are provided necessary facts for implying these results, which can help to explore such spaces on different domains in further researches. Proposed spaces allow to extend the class of studying functions, containing Leray projection, heat semi-group and other operators, which can be helpful in exploring weak, strong and mild solutions of nonlinear partial differential equations.

The composite post insulator composed of a large diameter mandrel and flange pressed by one-time integral pultrusion has high strength and good toughness, widely used in the existing flexible converter valve. For constructing the finite element model of the crimped post insulator, most of the flange surface and the mandrel surface are directly connected, making the simulation model's stiffness deviate from the actual model and the model distortion. Based on this, this study proposes a new finite element simplified model of crimped composite post insulator based on Multi-Point Constraints (MPC), which accurately simulates the crimping area of man-drel and flange in engineering practice. It verifies the model's reliability through static tests and characteristic vibration tests. The results show that the difference between the finite element simulation and test results is within 5 %. The finite element modeling method based on MPC local constraints is very reliable in applying crimped composite post insulators. Based on the proposed model, the influence of flange height and thickness on the mechanical properties of composite post-insulators is further explored. The results show that the influence of flange height on mechanical properties can be ignored when the height of the insulator stiff-ener ( non-press common area ) is constant. Within the allowable thickness range of the flange crimping process, the increase in flange thickness will significantly reduce the maximum bend-ing stress of the insulator and increase its safety margin. It provides a good design idea for the design of crimping composite insulators.

Cytokines and chemokines (chemotactic cytokines) are soluble extracellular proteins that bind to specific receptors and play an integral role in the cell-to-cell signaling network, in addition can promote the homing of cancer cells into different organs. We investigated the potential relationship between human hepatic sinusoidal endothelial cells (HHSECs) and several melanoma cell lines for the expression of chemokine and cytokine ligand and receptor expression during invasion of melanoma cells. In order to define the invasion related gene expression differences, we selected invasive and non-invasive subpopulations of cells after co-culturing with HHSECs. In addition, we determined protein expression of the endothelial cells before and after co-culturing with melanoma cell lines originated from primary tumors. Cell lines with increased invasive capacity after culturing with conditioned medium showed a set of receptor genes (CXCR1, IL1RL1, IL1RN, IL3RA, IL8RA, IL11RA, IL15RA, IL17RC, and IL17RD) with significantly different expression. It is very important note, that the IL11RA gene expression level was also significantly increased in primary melanoma tissues with liver metastasis as well. Proteome arrays revealed 15 differentially expressed proteins (including CD31, VCAM-1, ANGPT2, CXCL8, and CCL20) in the hepatic endothelial cells after co-cultured with melanoma cells. Our findings clearly indicate the interaction between liver endothelial- and melanoma cells. Based on our data, we assume that overexpression of the IL11RA gene might has key role in the formation of organ specific metastasis to the liver by primary melanoma cells.

In recent years, the discharge of various emerging pollutants, chemicals and dyes in water and wastewater has represented one of the prominent human problems. Since water pollution is directly related to human health, highly resistant and emerging compounds in aquatic environments will pose many potential risks to the health of all living. Therefore, water pollution is a very acute problem that has constantly increased in recent years with the expansion of various industries. Consequently, choosing efficient and innovative wastewater treatment methods to remove contaminants is crucial. Among advanced oxidation processes, electrochemical oxidation (EO) is the most common and effective method for removing persistent pollutants from municipal and industrial wastewater. However, there are still many gaps despite the great progress in using EO to treat real wastewater. This is due to the lack of comprehensive information on the operating parameters which affect the process and its operating costs. In this paper, among various scientific articles, the impact of operational parameters on the EO performances, a comparison between different electrochemical reactor configurations, and a report on general mechanisms of electrochemical oxidation of organic pollutants have been reported. Moreover, an evaluation of cost analysis and energy consumption requirements have also been discussed. Finally, the combination process between EO and another important advanced oxidation technology, PEC, called photoelectrocatalysis (PEC), has shortly been discussed and reviewed. This article showed that there is a direct relationship between important operating parameters with the amount of costs and the final removal efficiency of emerging pollutants. Optimal operating conditions can be achieved by paying special attention to reactor design, which can lead to higher efficiency and more efficient treatment. The rapid development of EO for removing emerging pollutants from impacted water and its combination with other green methods can result in more efficient approaches to face the pressing water pollution challenge.

Crop genetic diversity is most for the long-term sustainable production system. The breeding and production strategies of developing and growing uniform and homogenous varieties have created many different problems. Such populations are static and very sensitive to unpredictable stresses. In Nepal, more than 80% of seed system is informal s which has contributed greatly to creating and maintaining genetic diversity within the field particularly contributing to landrace diversity. This paper aims to assess and present the approaches and advantages of increased crop genetic diversity in the fields. The paper is developed based on experiences of implementing on-farm conservation activities carried out in Nepal since last two decades. Some of the evidences have been derived from on-going evolutionary plant breeding project being implemented in Nepal. The information is supplemented with field assessment, focus group discussion, and literature review. The major approaches to increase crop genetic diversity are evolutionary plant breeding, cultivar mixture, landrace enhancement, informal seed system, bulk method, diversifying the sources, participatory plant breeding, open pollination, etc. EPB and cultivar mixture are very simple and effective approaches to increase crop genetic diversity at field level. The involvement of farmers in these approaches helps to accelerate the population improvement particularly for landraces. The major advantages of increased crop genetic diversity are: seed maintenance by farmers themselves, minimal risk of crop failure, resilience to unpredictable stresses, increased amount of diversified nutrition, production increment each year, ease to produce organically, etc. However, there are some issues and problems associated with mixtures and diverse varieties, for example, not being able to harvest by machine, mature at a different date, difficulty in maintaining seeds and registration, etc. Crop genetic diversity should be considered for a climate-resilient and self-dependent production system. The higher the genetic diversity in farming land, the more chance of getting the multiple benefits in the agriculture system (Vernooy 2022).

It was recently shown that urban networks might exhibit two different critical points, one for the percolation of congested links through the network, and another one for the flow of vehicles through the network. It was observed that the percolation critical point happens after the flow critical point, where network throughput is maximized. This result is important because if a causal relationship exists between these two processes, it can be leveraged for improving control methods to avoid network collapse. This paper presents the results of numerical experiments to understand the possible causal relationship between the percolation and flow processes by focusing on the relative timing between the two critical points. The goal is to understand the impacts of important factors such as: (i) urban network type: long- and short-block networks, (ii) signal timing control type: fixed, random, responsive, and (iii) route choice: turning proportions at intersections. We find that the threshold density $k^*_c$ to determine if a link is congested has the main impact on the timing of the percolation transition, where lower values trigger earlier transitions. This implies that $k^*_c$ can be set such that the percolation transition happens before the flow critical point, opening the door for improved congestion management strategies. If $k^*_c$ is set to the average network critical density, maximum network throughput happen simultaneously with the percolation transition. Surprisingly, it appears that these results, and more generally, the relationship between the percolation and flow processes is independent of (i) and (ii) above.

Sunn pest is one of the most crucial noxious species in agriculture. As the sunn pest penetrates and makes damage to the grains, they can no longer be utilized to make bakery goods like bread, pasta, and other baked foods since they become unusable. Therefore, analysis and detection of damaged wheat grains are necessary for production to continue. We recommend that the dataset could be used for analysis and segmentation of the wheat grains, detection of the sunn pest damage condition, and classification of the 6 species of which the dataset consists. As mentioned, in our dataset, there are 6 different species of wheat, including Bezostaja, Müfitbey, Nacibey, Sönmez-2001, Tosunbey, and Ekiz, which are the species that were made in Türkiye. Our dataset differs from the others due to its various species and the condition, whether it is healthy or sunn pest damaged or broken wheat grain, and because the dataset is a multiclass one, it can be used for the classification of the varieties. On the other hand, when the sunn pest damage condition is taken into account, the dataset is suitable for the detection of the sunn pest damage. In addition to that, the dataset includes grains that touch each other which makes it more applicable to problems that arise in real-life. The dataset consists of 83 sunn pest damaged and 87 healthy wheat images. In addition, there are 170 images that contain 3565 wheat grains. As can be observed, the dataset contains a variety of wheat species with sunn pest affected which displays that the promised dataset is suitable for numerous machine learning problems such as classification, segmentation, and detection.

Due to the content of biologically active substances, sea buckthorn (Hippophae rhamnoides L.) is of growing interest to scientists, the food industry, pharmaceuticals, cosmetology and consumers. The aim of this study is to investigate the correlation between the chemical composition (Carotenoid content (CC), Ascorbic acid content (AAC), Total dry matters (TDM), Titratable acidity (TA), pH, Organic acids (OA)) and the Antibacterial effect (AA) (Diameter of the inhibition zone in mm of Bacillus pumilus) of four species of sea buckthorn (Clara, Dora, Cora, Mara), cultivated in the Republic of Moldova. The sea buckthorn species tested was found to have a different Carotenoid content (1.79±0.43 … 48.92±0.61 mg/100g), Ascorbic acid content (74.36±0.60 … 373.38±2.29 mg/100g), Organic acids (malic acid 5.8±0.02 ... 13.4±0.01 mg/100g, citric acid 0.08±0.00 ... 0.32±0.01 mg/100g, succinic acid 0.03±0.00 ... 1.1±0.00 mg/100g), Total dry matters (16.71±0.05 … 24.54±0.09 %), Total acidity (2.15±0.05 ... 8.76±0.00 %), and pH value (2.73±0.02 ... 3.00±0.07). The microbial activity of sea buckthorn, evaluated by the diameter of the inhibition zone, constituted for Bacillus pumilus (3.70…15.91mm/g-1 for whole sea buckthorn fruits and respectively 13.33…26.67 mm/g-1 for sea buckthorn puree).

Background and aim: Human Papillomavirus (HPV) is sexually transmitted, one of the three most common sexually transmitted infections (STIs) in both males and females, and the most common viral STI. A crucial public health strategy to protect people against HPV is through vaccination, which has shown its effectiveness in preventing HPV related diseases. Presently three types of vaccines are available (bivalent, quadrivalent, and nonavalent) and they all target at least the two most oncogenic virus genotypes (HPV 16, 18). In the past few years, the need to implement vaccination programmes that include all genders has been discussed in order to achieve herd immunity against HPV. To date, only a few countries have included young males in their vaccination programmes, so we aim through this review to provide an overview of the epidemiology of HPV and prevention strategies to prevent it, reporting the latest findings from the scientific literature.

Vehicle safety promises to be one of the Advanced Driver Assistance System (ADAS) biggest benefits. Higher levels of automation remove the human driver from the chain of events that can lead to a crash. Sensors play an influential role in vehicle driving as well as in ADAS by helping the driver to watch the vehicle’s surroundings for safe driving. Thus, the driving load is drastically reduced from steering as well as accelerating and braking for long-term driving. The baseline for the development of future intelligent vehicles relies even more on the fusion of data from surrounding sensors such as Camera, Lidar and Radar. These sensors not only need to perceive in clear weather but also need to detect accurately adverse weather and illumination conditions. Otherwise, a small error could have an incalculable impact on ADAS. As most of the current study is based on indoor or static testing. In order to solve this problem, this paper designs a series of dynamic test cases with the help of outdoor rain and intelligent lightning simulation facilities to make the sensor application scenarios more realistic. As a result, the effect of rainfall and illumination on sensor perception performance is investigated. As speculated, the performance of all automotive sensors is degraded by adverse environmental factors, but their behaviour is not identical. Future work on sensor model development and sensor information fusion should therefore take this into account.

Phytoplasma diseases pose a substantial threat to diverse crops of agricultural importance. Management measures are usually implemented only after the disease has already occurred. Early detection of such phytopathogens, prior to disease outbreak, has rarely been attempted but would be highly beneficial for phytosanitary risk assessment, disease prevention and mitigation. In this study we present the implementation of a recently proposed proactive disease management protocol (DAMA: Document, Assess, Monitor, Act) for a group of vector-borne phytopathogens. We used insect samples collected during a recent biomonitoring program in southern Germany to screen for the presence of phytoplasmas. Insects were collected with Malaise traps in different agricultural settings. DNA was extracted from these mass trap samples and subjected to PCR-based phytoplasma detection and COI sequence metabarcoding. In about 1% of the analyzed samples, phytoplasma DNA was detected. Phytoplasma group identification was performed by 16S rRNA gene sequence analysis and the detected phytoplasmas could be assigned to the 16SrI subgroups B and L. Insect species in the sample were identified by DNA metabarcoding. By using established databases, checklists, and archives, we documented historical associations and records of phytoplasmas and its hosts in the study region. For the assessment in the DAMA protocol, phylogenetic triage was performed in order to determine the risk for tri-trophic interactions (plant-insect-phytoplasma) and associated disease outbreaks in the study region. A phylogenetic heat map constitutes the basis for risk assessment and was used here to identify a minimum number of seven leafhopper species suggested to be monitored by stakeholders in this region. A proactive stance in monitoring changing patterns of association between hosts and pathogens can be a cornerstone in capabilities to prevent future phytoplasma disease outbreaks. To our knowledge, this is the first time that the DAMA protocol has been applied in the field of phytopathology and vector-borne plant diseases.

Multimodal user interfaces hold the promise to enable natural and intuitive means of human-machine interaction. But is the effort of using many sensors rewarded by the users - or is a single modality sufficient? For an industrial use case of a weld seam inspection workstation we study three independent interfaces (augmented spatial button interaction on (1) a workpiece or (2) a worktable and through (3) speech commands) and their combination (4). While users preferred the interaction on the augmented worktable when comparing single modalities, they used all three in multimodal user interface. From the isolated test of an input modality it is not possible to infer its use in a complex system. Therefore, the effort implementing and using multiple input modalities is reasonable.

Staphylococcus aureus (S. aureus), particularly Methicillin-resistant S. aureus (MRSA), is a life-threatening pathogen that causes a variety of infections in hospital and community settings. It poses a significant risk and challenge for global health that hinders our ability to control and treat bacterial infections. Recently, the emergence and spread of variant strains of bacteria, misuse of the limited available options of effective antibiotics, spread of fake drugs, and climate change that increased the contact between humans and animals’ populations carrying different bacterial has significantly increased the incidence of Multi-Drug Resistance strains (MDR). This in turn, has created a severe problem in the infection control treatment of S. aureus infected patients. Treatment options for MRSA infection are increasingly limited and complicated. Unfortunately, different strains of MRSA are showing tolerance and resistance toward vancomycin, which is the standard of care for complicated MRSA. Therefore, it is crucial now to invest developing new effective anti-biotics and synergies, develop and implement national action plans for the management of an-tibiotic resistance, as well as improving our understanding of the antimicrobial resistance mechanisms. Here, in this review we explain the main mechanisms of antibiotic resistance in MRSA and describes different approaches to manipulate it in MRSA, providing a basis for de-signing effective drugs, and shedding some light on the evolution of S. aureus.

In order to properly cover different scenarios, radiation patterns of antennas should be accordingly adjusted before fabrication. However, most antennas are unable to provide both broadside beam and designable conical beam which are usually-used radiation patterns for radio coverage. In this paper, a planar Circular Polarized (CP) annular Leaky-Wave Antenna (LWA) with conical beam is proposed, which is realized on annular Substrate-Integrated Waveguide (SIW). Broadside beam or conical beam could be easily obtained by fabricating the LWA with modified structural parameters. The central operating band is 5.8 GHz. The LWA allows only the -1th spatial harmonic to radiate, while the fundamental wave and other spatial harmonics are suppressed in slow wave mode. In order to validate the design effectiveness, two examples for broadside beam and conical beam radiation are fabricated and measured. The measurement results show good agreement with the simulation results. The proposed LWA presents a promising radiation performance and is a good candidate for wireless communication applications.

Background. To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle, and to compare the acquisition time associated with these two methods. Methods. Foot volume was measured in 29 healthy volunteers (58 feet, 24 female/5 male) by a 3D scanner (UPOD-S 3D Laser Full-Foot Scanner ®) and by water-displacement volumetry. Measurements were performed on both feet, up to a height of 10 cm above the ground. The acquisition time for each method was evaluated. Kolmogorov-Smirnov test, Lin's Concordance Correlation Coefficient, and a Student’s t-test were performed. Results: Mean foot volume was 869.7+/-165.1cm3 (3D scanner) versus 867.9+/-155.4cm3 (water-displacement volumetry) (p <10-5). Concordance of measurements was 0.93, indicative of a high correlation between the two techniques. Volumes were 47.8 cm3 lower when using the 3D scanner versus water volumetry. After statistically correcting this underestimation, the concordance was improved (0.98, residual bias = -0.03 +/- 35.1 cm3). Mean examination time was 4.2 +/-1.7 min (3D optical scanner) versus 11.1 +/-2.9 min (water volumeter) (p<10-4). Conclusion: Ankle/foot volumetric measurements performed using this portable 3D scanner are reliable and fast, and can be used in clinical practice and research.

Regional heterogeneity of microglia was first described a century ago by Pio del Rio Hortega. Currently, new hints on microglia heterogeneity across central nervous system (CNS) regions are still being unraveled by high-throughput techniques. It remains unclear whether these spatial specificities translate into different microglial behaviors in vitro. We cultured microglia isolated from the cortex and spinal cord and analyzed the effect of the CNS spatial source on in vitro behavior by applying the same experimental protocol and culture conditions. We analyzed microglial cell numbers, function, and morphology and found a distinctive in vitro phenotype. We found that microglia were present in higher numbers in spinal cord-derived glial cultures, presenting different expression of inflammatory genes and a lower phagocytosis rate under basal conditions or after activation with LPS and IFN-. Morphologically, cortical microglial cells are more complex and present longer ramifications, which were also observed in vivo in CX3CR1+/GFP transgenic reporter mice. Collectively, our data demonstrated that microglial behavior in vitro is defined according to specific spatial characteristics acquired in the tissue. Thus, our study highlights the importance of microglia as a source of CNS for in vitro studies.

Corneal opacity is a leading cause of vision impairment and suffering worldwide. Transplantation can effectively restore vision and reduce chronic discomfort. However, there is a considerable shortage of viable corneal graft tissues. Tissue engineering may address this issue by advancing xeno- keratoplasty as a viable alternative to conventional keratoplasty. In particular, livestock decellularization strategies offer the potential to generate bioartificial ocular prosthetics in sufficient supply to match existing and projected needs. To this end, we have examined the best practices and characterizations that have supported the current state-of-the-art driving preclinical and clinical applications. Identifying the challenges that delimit activities to supplement the donor corneal pool derived from acellular scaffolds allowed us to hypothesize a model for keratoprosthesis applications derived from livestock combining 3D printing and decellularization.

Geological structures such as joints and faults in rock mass have significant influence on open pit mining. Hence, it is critical to develop a understanding of dynamic joint behaviour under blasting loading. This in turn can provide both theoretical and practical guidance to improve blasting rock fragmentation and associated bucket excavating efficiency. In this paper, delayed blasting on the highwall bench at Baiyunebo open-pit mine was used as an example, a nonlinear joint blasting model was also constructed. By simplifying the blasting wave propagation velocity, the P-wave normal incidence to the joint was obtained. The peak vibration velocity was 0.33m/s at 3.0s. The S-wave reflected by the joint interface was first reflected backward and then forward, which the peak vibration velocity was 0.027 m/s. By combining the relevant stress and displacement theories of type I and II cracks, the equipotential diagrams of the stress and displacement field with the vibration velocity of the particle were obtained. σx was positive in the direction of 0~330° and subjected to tensile stress, whereas σy was positive in the direction of 0~180° and under tensile stress. The longitudinal σy along joint was low in compressive stress distribution area and did not affect surrounding rock at the time. The stress concentration appeared in the lower right corner. Based on the continuous behavior of stress wave in joints, the asymmetry and continuous changes reflected in the whole process could not be analysed by the contour diagram. Hence, ANSYS used to analyse distribution of the stress field. The intensity of the shock wave after detonation was greater than that of the rock strength. Subsequently, the sub-layer shock wave supplemented the shock wave energy that was not enough to break the rock and induced further cracking. This was able to be visualized by the degree of color change post-processing. It was concluded that with the attenuation of the detonation wave energy, the stress exhibited a decreasing trend in this process. According to distribution of the peak effective stress, it was found that the peak value first increased to 10-12 MPa and then showed a downward trend. Overall, the results were validated against the finite element simulation and mathematical analysis.

While modeling data in reality, uncertainties in both data (aleatoric) and model (epistemic) are not necessarily Gaussian. The uncertainties could appear with multimodality or any other particular forms which need to be captured. Gaussian mixture models (GMMs) are powerful tools that allow us to capture those features from a unknown density with a peculiar shape. Inspired by Fourier expansion, we propose a GMM model structure to decompose arbitrary unknown densities and prove the property of convergence. A simple learning method is introduced to learn GMMs through sampled datasets. We applied GMMs as well as our learning method to two classic neural network applications. The first one is learning encoder output of autoencoder as GMMs for handwritten digits images generation. The another one is learning gram matrices as GMMs for style-transfer algorithm. Comparing with the classic Expectation maximization (EM) algorithm, our method does not involve complex formulations and is capable of achieving applicable accuracy.

Experimental systems to simulate future elevated CO2 conditions in the field often have large, rapid fluctuations in CO2. To examine possible impacts of such fluctuations on photosynthesis, intact leaves of field grown plants of five species were exposed to two-minute cycles of CO2 between 400 and 800 mol mol-1 lasting a total of 10 minutes, with photosynthesis, stomatal conductance and PSII fluorescence measured at the end of each half-cycle, and also 10 minutes after the end of the cycling. Prior to the cyclic CO2 treatments, steady-state responses of leaf gas exchange and fluorescence to CO2 were determined. In four of the five species, in which stomatal conductance decreased with increasing CO2, the cyclic CO2 treatments reduced stomatal conductance. In those species, both photosynthesis and the photochemical efficiency of PSII were reduced at limiting internal CO2 levels, but not at saturating CO2. In the fifth species, there was no change in stomatal conductance with CO2, and no change in either photosynthesis or PSII efficiency at any CO2 level with CO2 cycling. It is concluded that in many, but not all, species fluctuations in CO2 may reduce photosynthesis at low CO2 partly by decreasing the photochemical efficiency of photosystem II, as well as by decreasing stomatal conductance.

Background. The main impetus behind the worldwide Covid-19 vaccination campaign in 2021 was to reduce the mortality attributed to SARS-CoV-2 infection in the preceding year. Nevertheless, rigorous analyses of the mortality benefits conferred by this massive vaccination effort have been lacking. Methods Statistics offers us an essential methodological approach for measuring the impacts of Covid-19 vaccination on public health. The mathematical relation between vaccinated-alive groups can be repeated between vaccinated-dead groups with relatively high statistical reliability because of the large population numbers involved. This method also confers greater statistical usefulness because it eliminates the Simpson effect. Results Calculations were performed for each of the following five(5) four-week intervals: weeks 35-38 (2021), weeks 39-42 (2021), weeks 43-46 (2021), weeks 47-50 (2021), and weeks 50(2021)-1(2022). The results obtained confirm that the mortality of the vaccinated coronavirus-infected groups was 14.5% higher on average than the mortality of non-vaccinated coronavirus-infected groups. Conclusions Vaccinated infected groups appear to have higher average mortality than their non-vaccinated infected counterparts. The findings suggest the legitimacy of extending the statistics between vaccinated living and vaccinated dead individuals for different age groups. Calculating the impact of Covid-19 vaccination on the mortality rate is a necessary step towards satisfying the first principle of medicine: “Primum non nocere”, “Do no harm”.

This work investigates how to balance the electricity supply and demand in a carbon-neutral northern Europe. Applying a cost-minimizing electricity system model including options to invest in eleven different flexibility measures, cost-efficient combinations of strategies to manage varia-tions are identified. The results of the model are post-processed using a novel method to map the net load before and after flexibility measures are applied to reveal the contribution of each flexi-bility measure. The net load is mapped in the space spanned by the amplitude, duration, and number of occur-rences. The mapping shows that, depending on cost structure, flexibility measures contribute to reduce the net load in three different ways; 1) by reducing variations of long duration but low amplitude, 2) by reducing variations of high amplitude but short duration and low occurrence or 3) by reducing variations of high amplitude, short duration and high occurrence. It is found that cost-efficient variation management is achieved by combining wind and solar power and by combining strategies (1-3) to manage variations. The cost-efficient combination of strategies de-pends on electricity system context where electricity trade, flexible hydrogen and heat production (1) manage the majority of variations in regions with good conditions for wind power while sta-tionary batteries (3) are the main contributors in regions with good conditions for solar power.

Intracortical microelectrodes that can be implanted have the ability to capture fast-changing neuron action potentials in the living brain. Despite this potential, many obstacles must still be overcome for reliable, long-term, high-quality recordings and accurate analysis of brain activity. These challenges include improving recording quality, enhancing recording stability, increasing recording capacity, and adding multi-functional features. One potential approach to enhance implantable microelectrodes involves the advancement of materials, refinement of implantation methodologies, and augmentation of the number of sites for recording. However, these challenges are still being actively researched, and advancements in microelectrode technology are underway. The difficulties with implantable microelectrodes are evaluated, and solutions are presented from different perspectives. The latest advancements in microelectrode technology are reviewed and condensed, and future possibilities are explored.

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

The development of antimicrobial resistance to conventional antibiotics is a major global health challenge. Infections caused by multidrug-resistant gram-negative bacteria have been named one of the most urgent global health threats. Considerable efforts are devoted to developing new antibiotic drugs and investigating the mechanism of antibiotic resistance. Recently, Anti-Microbial Peptides (AMPs) have emerged as a new platform for the target and design of novel drug resistant anti-microbial agents promising a new therapeutic strategy. AMPs are rapid, potent, possess an unusually broad spectrum of activity, and have shown efficacy as topical agents. Unlike traditional therapeutics that interfere with essential bacterial enzymes, AMPs interact with microbial membranes through electrostatic interactions and physically damage cell integrity. However, naturally occurring AMPs have limited selectivity and modest efficacy. Therefore, recent efforts have focused on the development of synthetic AMP analogs as suitable drug targets. This work explores the development of novel antimicrobial agents which mimic the structure of graft-copolymers and mirror the mode of action of an AMP. Chitosan-graft-polypeptide side chains are synthesized by the ring-opening polymerization of N-carboxyanhydrides of L-lysine and L-leucine initiated from the functional groups of chitosan. The derivatives with random- and block-copolymer side chains are explored as drug targets. These graft copolymer systems exhibit activity against clinically significant pathogens and disrupt biofilm formation. This work highlights the potential of chitosan-graft-polypeptide structures in biomedical applications.

Cream cheese presents a favorable environment for the growth of pathogenic and spoilage microorganisms. The antimicrobial and antioxidant effects of plant extracts are well known, but their use is limited because they affect the physicochemical and sensory characteristics of products. Encapsulation presents an option to limit or prevent these changes. The paper presents the composition of individual polyphenols (HPLC–DAD-ESI-MS) from basil extracts (BE) with significant antioxidant activity (644.75±21.37 mM Trolox/g DW) and inhibitory effect against strains of Staphylococcus aureus, Geobacillus stearothermophilus, Bacillus cereus, Candida albicans, Enterococcus faecalis, Escherichia coli, and Salmonella Abony. The basil extract was encapsulated in sodium alginate (Alg) using the drop technique. The encapsulation efficiency of microencapsulated basil extract (MBE) was 78.59±0.01%. SEM and FTIR analyzes demonstrated the existence of weak physical interactions between the components. In the optimal concentration range of 0.6-0.9% MBE determined the inhibition of the post-fermentation process and the improvement of the degree of water retention. This led to the improvement of the textural parameters of the cream cheese, contributing to the extension of the shelf life of the product by 7 days. The influence of storage period and MBE concentration on texture parameters, pH and sensory analysis (overall acceptability) were evaluated by mutual information analysis.

Effective household and individual disaster preparedness can minimize physical harm and property damage during catastrophic events. To assess the risk and vulnerability of affected areas, it is crucial for relief agencies to understand the level of public preparedness. Traditionally, government agencies have employed nationwide random telephone surveys to gauge the public’s attitudes and actions towards disaster preparedness. However, these surveys may lack generalizability in certain affected locations due to low response rates or areas not covered by the survey. To address this issue and enhance the comprehensiveness of disaster preparedness assessments, we develop a framework that seamlessly integrates machine learning and simulation. Our approach leverages machine learning algorithms to establish relationships between public attitudes towards disaster preparedness and demographic characteristics. Using Monte Carlo simulation, we generate datasets that incorporate demographic information of the affected location based on government-provided demographic distribution data. The generated dataset is then input into the machine learning model to predict the disaster preparedness attitudes of the affected population. We demonstrate the effectiveness of our framework by applying it to Miami-Dade County, where it accurately predicts the level of disaster preparedness. With this innovative approach, relief agencies can have a clearer and more comprehensive understanding of public disaster preparedness.

The aim of Predictive Maintenance, within the field of Prognostics and Health Management (PHM), is to identify and anticipate potential issues in the equipment before these become critical. The main challenge to be addressed is to assess the amount of time a piece of equipment will function effectively before it fails, which is known as Remaining Useful Life (RUL). Deep Learning (DL) models, such as Deep Convolutional Neural Networks (DCNN) and Long Short-Term Memory (LSTM) networks, have been widely adopted to address the task, with great success. However, it is well known that this kind of black box models are opaque decision systems, and it may be hard to explain its outputs to stakeholders (experts in the industrial equipment). Due to the large number of parameters that determine the behavior of these complex models, understanding the reasoning behind the predictions is challenging. This work presents a critical and comparative revision on a number of XAI methods applied on time series regression model for PM. The aim is to explore XAI methods within time series regression, which have been less studied than those for time series classification. The model used during the experimentation is a DCNN trained to predict the RUL of an aircraft engine. The methods are reviewed and compared using a set of metrics that quantifies a number of desirable properties that any XAI method should fulfill. The results show that GRAD-CAM is the most robust method, and that the best layer is not the bottom one, as is commonly seen within the context of Image Processing.

The emergence of various electronic devices and equipment such as electric vehicles and drones requires higher energy density energy storage devices. Lithium-sulfur batteries (LSBs) are considered as the most promising new generation energy storage system owing to high theoretical specific capacity and energy density. However, the severe shuttle behaviors of soluble lithium polysulfides (LiPSs) and the slow redox kinetics lead to low sulfur utilization and poor cycling stability, which seriously hinder the commercial application of LSBs. Therefore, various catalytic materials have been employed to solve these troublesome problems. High entropy materials (HEMs), as advanced materials, can provide unique surface and electronic structures that expose plentiful catalytic active sites, which opens new ideas for the regulation of LiPSs redox kinetics. Notwithstanding many instructive reviews in the land of LSBs, while this review aims to offer a complete and shrewd summary of the current progresses in HEMs-based LSBs, including in-depth interpretation of design principles and mechanistic electrocatalysis functions as well as pragmatic perspectives.

Introduction: Parents’ behavior and practices affect many aspects of family life, including health, and many studies have proven that children's bad habits are associated with parents’ behavior and practices. Objectives: This study aimed to identify parents’ negative behaviors that might affect their families’ health and social development. Methodology: A descriptive cross-sectional study was conducted to examine the influence of parents’ behavior and practices on their family health, in which 192 respondents participated. Results: The results clarified the influence of parents on family health in several aspects. On the behavioral side, approximately 90% of the participants agreed that the behavior of parents may affect the behavior of their families, and the social and educational side results clarified the relationship between parents' illiteracy and support for the cognitive and social health of the family. Discussion: This study clarified that there is a significant relationship between illiterate parents and their ability to support their families, illustrating that the majority of participants thought that the development of the cognitive and social health of families depends on the presence of supportive parents, which has many implications for family social and psychological health. Conclusion: Parental behaviors and practices have a strong effect on their family’s health, which affects the development of the families’ cognitive and social health. Recommendation: The study recommends the need for supportive, friendly hospitals for family social health and the provision of specialized programs that support the family’s social and psychological health.

Malaria is a critical fevered illness caused by Plasmodium parasites transmitted among people through the bites of infected female Anopheles mosquitoes. Public awareness about the disease is important for the control of disease. This article proposes a mathematical model to study the dynamics of malaria disease transmission with the influence of awareness-based control interventions. We found two equilibria of the model, namely the disease-free and endemic equilibrium. Disease-free equilibrium is stable globally if basic reproduction number (R0) is less than unity (R0&lt;1). Some basic mathematical properties of the proposed model, such as nonnegativity and boundedness of solutions, the feasibility of the equilibrium points and their stability properties, have been studied. Finally, we adopted optimal control to minimize the cost of disease control and solve the problem by formulating Hamiltonian functional. The optimal use of insecticides for controlling the mosquito population is determined. Numerical simulations have been provided for the confirmation of the analytical results. We conclude that media awareness with optimal control approach is best for cost-effective malaria disease management.

Self-employed individuals comprise around 15% of Canada’s workforce. For those with cancer, frequent functional loss and diminished work ability due to side effects of the disease and its treatment significantly impact their well-being and business vitality. Compared to salaried can-cer survivors, the self-employed experience greater reductions in work hours and up to 48% greater income loss, yet most research addresses the former population. To describe self-employed Canadian cancer survivors’ experiences continuing and returning to work, our quali-tative study examines their strategic efforts to continue working throughout the disease trajecto-ry or return to work post-recovery. Employing an interpretive description approach and an in-terview guide based on a vocational rehabilitation model for cancer survivors, we analyze data from 23 participants—both French- and English-speaking—from six Canadian provinces, with eight different job types and nine different cancer diagnoses. Our constant comparative analysis of the transcribed interviews reveals four major themes and twelve sub-themes: Impact of can-cer on the self-employed function (physical, cognitive, and psychological), on their ability to maintain their business, and financial well-being, and facilitating factors for working with can-cer. Cancer disclosure and non-disclosure were both deemed viable strategies, but ceasing work was not. We thus recommend professional support for self-employed cancer survivors in plan-ning any necessary business modifications to accommodate their condition and cancer treatment to lessen the negative impact of cancer on self and on their business well-being.

Nanostructured dipeptide self-assemblies exhibiting quantum confinement are of great interest due to their potential applications in the field of materials science as optoelectronic materials for energy harvesting devices. Among those, aromatic cyclo-dipeptides containing the amino acid tryptophan are wide-band gap semiconductors displaying high mechanical rigidity, photoluminescence and piezoelectric properties to be used in power generation. In this work, we report the fabrication of hybrid systems based on chiral cyclo-dipeptide L-Tryptophan- L-Tryptophan incorporated into biopolymer electrospun fibers. The micro/nanofibers contain self-assembled nanospheres embedded into the polymer matrix are wide-band gap semiconductors (gap energy 3.8 eV), display blue photoluminescence and relevant piezoelectric and pyroelectric properties with coefficients as high as 57 pCN-1 and 35×10-6 Cm-2k-1, respectively. They are therefore promise systems for thermal sensing and energy harvesting applications.

Acanthopanax senticosus(rupr. rt. Maxim.; AS) is a medicinal plant used in the clinical treatment of cerebrovascular diseases and central nervous system disorders, significantly improving blood lipid levels and endothelial cell function in patients with acute cerebral infarction. Isofraxidin, one of the active ingredients of AS, is the core of the medical effects, and its extraction and purification depend on organic solvents. Deep eutectic solvents (DESs) is a new green solvent, synthesized by intermolecular hydrogen bonding between hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA), which has non-toxic, high separation and purification efficiency, and environmentally friendly compared with traditional organic solvents. In this paper, DES was used for the extraction of isofraxidin from AS. The primary findings demonstrate that the DESs had a viscosity higher than that of ethanol, and even adding a tiny amount of water (about 10%) would trigger solvent redistribution, leading to a considerable reduction in solvent viscosity. In comparison to ethanol, the extraction rate of isofraxidin by DESs was 2-3 times higher. Thus, this work developed a new technique for using green extraction of isofraxidin that has some practical implications.

Isometric exercises for physiotherapeutic rehabilitation are often prescribed, with little quantification of the load being prescribed. This article aimed to provide a framework and practical examples of how the physiotherapist may take a more quantitative evidence-based approach to isometric assessment, monitoring, and exercise prescription of knee osteoarthritis, by integrating a strain gauge into their practice. Strength measures to monitor were discussed. A series of fourteen studies were reviewed, with the intent of identifying isometric exercises that had been utilized in the rehabilitation of knee osteoarthritis. Of the fourteen studies, the three most identified isometric exercises were seated knee extension, knee flexion, and the supine straight leg raise. The integration of strain gauge technology with these exercises provided the focus of the remainder of the article.

United Nations Framework Convention on Climate Change (UNFCCC) has recently established the Reducing Emissions from Deforestation and forest Degradation (REDD+) program that requires countries to report their carbon emissions and sink estimates through national greenhouse gas inventories (NGHGI). Thus, developing automatic systems capable of estimating the carbon absorbed by forests without in-situ observation becomes essential. To support this important need, in this work we introduce ReUse, a simple but effective deep-learning approach to estimate the carbon absorbed by forest areas based on remote sensing. The novelty of the proposed method is in the use of the public above-ground biomass (AGB) data from the European Space Agency's Climate Change Initiative Biomass project as ground truth to estimate the carbon sequestration capacity of any portion of land on Earth using Sentinel-2 images and a pixel-wise Regressive UNet. The approach has been compared to two literature proposals, using a private dataset and human-engineered features. The results show a greater generalization ability of the proposed approach, with a decrease in Mean Absolute Error and Root Mean Squared Error, respectively, of 16.9 and 14.3 in the area of Vietnam and 4.7 and 5.1 in the area of Myanmar over the runner-up. Finally, as a case study, we reported an analysis made for the Astroni area, a nature reserve located near the metropolitan area of Naples in southern Italy, struck by a large fire, producing predictions consistent with values found by experts in the field. These results further support the use of such an approach for the early detection of AGB variations, both in urban and rural areas.

Sometimes when diabetic retinopathy (DR) is found and treated quickly, vision loss can indeed be spared. This study deploys a deep learning (DL) model that can discover all 5 stages of DR more accurately than other methods. The proposed methodology shows two cases scenarios: case 1 with image enhancement using CLAHE and ESRGAN, and case 2 without image enhancement. Augmentation techniques are then employed to produce a balanced dataset with the identical criteria for both scenarios. The generated model using DenseNet-121 on the APTOS dataset outperformed other approaches for locating the 5 stages of DR, with an accuracy of 98.7 percent for case 1 and 81.2 percent for case 2. Using CLAHE and ESRGAN was shown to improve a model's performance and ability to learn.

Coastal marine ecosystems worldwide, like Florida Bay, are increasingly affected by tide alteration and anthropogenic disturbances which affect water quality imbalance leading to algal blooms. Increased bloom persistence is a serious threat due to the long-lasting impact on processes like carbon cycle and services like species presence. However, exploring eco-environmental feedback patterns of algal blooms remains challenging and poorly investigated, also due to the paucity of data. Florida Bay, taken as an epitome, has long experienced algal blooms in its central and western regions, and in 2006 an unprecedented bloom occurred in the eastern habitats. We analyzed the occurrence of blooms from three perspectives: (1) the spatial spreading networks of chlorophyll-a (CHLa) that pinpoints source and unbalanced habitats; (2) the fluctuations of water quality factors pre- and post-bloom outbreaks to in assess environmental impacts of ecological dysbiosis and target prevention and control of algal of blooms; and (3) the biogeochemical-spreading network topological co-evolution to quantify ecosystemic stability and ecological shift likelihood in long-term. Here, we propose Transfer Entropy (TE) to quantify dynamical interactions between spatial areas and biogeochemical factors (ecosystem connectome) underpinning bloom emergence and spreading, as well as environmental effects; the Pareto principle is defined for identifying the salient eco-environmental interactions of CHLa. We quantified the spatial dynamics of algal blooms, and thus obtained areas in need for ecological monitoring and potential bloom control. Results show that algal blooms are increasingly persistent over space with long-term negative effects on water quality factor. A dichotomy is reported between spatial ecological corridors of spreading and biogeochemical networks as well as divergence from the optimal eco-organization: randomization of the former due to nutrients' overload and temperature increase leads to scale-free CHLa spreading and extreme outbreaks a posteriori. Subsequently this increases bloom persistence, turbidity and salinity with potentially strong ecological effects on highly biodiverse and vulnerable areas such as tidal flats and marshes. Algal blooms are important ecosystem regulators of nutrient cycles; however, beyond limit chlorophyll-a outbreaks cause aquatic species mortality due to their effect on water turbidity, nutrient balance (nitrogen and phosphorus in particular), salinity and temperature. Beyond compromising local environmental quality, socio-ecological services are also compromised at large scales, yet ecological assessment models like the one presented are in need of application in subtropical and tropical bays worldwide.

With the advent of Neural Machine Translation, the more the achievement of human-machine parity is claimed at WMT, the more we come to ask ourselves if their evaluation environment can be trusted. In this paper, we argue that the low quality of the source test set of the news track at WMT may lead to an overrated human parity claim. First of all, we report nine types of so-called technical contaminants in the data set, originated from an absence of meticulous inspection after web-crawling. Our empirical findings show that when they are corrected, about 5% of the segments that have previously achieved a human parity claim turn out to be statistically invalid. Such a tendency gets evident when the contaminated sentences are solely concerned. To the best of our knowledge, it is the first attempt to question the “source” side of the test set as a potential cause of the overclaim of human parity. We cast evidence for such phenomenon that according to sentence-level TER scores, those trivial errors change a good part of system translations. We conclude that to overlook it would be a mistake, especially when it comes to an NMT evaluation.

High-level performance in mountain sports would be unlikely unless different emotional factors are taken into account through the analysis of psychological characteristics such as mood, resilience or motivation, among many others. In this study, 788 people with a sports degree from the Spanish Federation of Mountain Sports and Climbing (FEDME) participated, 75.3% are men and 24.5% are women. The mean age of the participants was 49.8 years (±12.8), ranging from 18 to 76 years. The Wong Law Emotional Intelligence Scale (WLEIS-S), the RS-14 Resilience Scale and the Satisfaction with Life Scale (SWLS) instrument were used. The aim of this research was to determine the relationship between the dimensions of emotional intelligence, resilience and life satisfaction. The results showed a relationship between several of the dimensions from the instruments used (p<.01). In terms of gender, higher scores were found for women than for men. The regression model shows that both the dimensions of emotional intelligence [Appraisal of own emotions (β=.104; p<.001); Use of emotions (β=.30; p&lt;.001); Emotional Regulation (β=.103; p<.001)] and resilience [Personal competence (β=.402; p<.001)], are predictors of greater life satisfaction, with 44.1% positively explained by the regression model. Further proposals should extend the results obtained with the analysis of more sports modalities and provide evidence that would complement those extracted in this research.

The extracellular matrix (ECM) is a ubiquitous member of the body and is key to the maintenance of tissues and organs integrity. Initially thought to be a by-stander in many cellular processes, the extracellular matrix has been shown to have diverse components that regulate and activate many cellular processes and ultimately influence cell phenotype. Importantly, the ECM composition, architecture, and stiffness/elasticity influence cellular phenotypes. Under normal conditions and during development, the synthesized ECM is constantly undergoing degradation and remodeling processes via the action of matrix proteases that maintain tissue homeostasis. In many pathological conditions including fibrosis and cancer, the ECM synthesis, remodeling, and degradation is dysregulated causing its integrity to be altered. Both physical and chemical cues from the ECM are sensed via receptors including integrins and play key roles in driving cellular proliferation and differentiation and in various disease progression such as cancers. Advances in ‘omics’ technologies have seen an increase in studies focussing on bi-directional cell-matrix interactions and here we highlight emerging knowledge on the role played by the ECM during normal development and in pathological conditions. This review summarizes current ECM-targeted-therapies that can modify tumor ECM to overcome drug resistance and better cancer treatment.

Currently, there is increasing industrial demand for rare earth elements (REE) as these elements are now integral to the manufacture of many carbon-neutral technologies. The depleting REE ores and increasing mining costs are prompting to look for alternative sources for these valuable metals, particularly from waste streams. Although REE concentrations in most of the alternate resources are lower than current REE ores, some sources such as marine sediments, coal ash, and industrial wastes like red mud are looking promising with significant concentrations of REE in them. This review focuses on the alternative resources for REE such as ocean bottom sediments, continental shelf sediments, river sediments, stream sediments, lake sediments, phosphorites deposits, industrial waste products like red mud, and phosphogypsum, coal, coal fly ash, and related materials, waste rock sources from old and closed mines, acid mine drainage, and recycling of e-waste. Possible future Moon exploration and mining for REE and other valuable minerals are also discussed. It is evident that REE extractions from both primary and secondary ores alone are not adequate to meet the current demand, and sustainable REE recovery from the alternative resources described here is also necessary to meet the growing REE demand. An attempt is made to identify the potential of these alternative resources and sustainability challenges, benefits, and possible environmental hazards to meet the growing challenges in meeting the future REE requirements.

The development of autonomous vehicles is becoming increasingly popular and gathering real world data is considered a valuable task. Many datasets have been published recently in the autonomous vehicle sector, with synthetic datasets gaining particular interest due to availability and cost. For a real implementation and correct evaluation of vehicles at higher levels of autonomy it is also necessary to consider human interaction, which is precisely something that lacks in existing datasets. In this article the UPCT dataset is presented, a public dataset containing high quality, multimodal data obtained using state of the art sensors and equipment installed onboard the UPCT’s CICar autonomous vehicle. The dataset includes data from a variety of perception sensors including 3D LiDAR, cameras, IMU, GPS, encoders, as well as driver biometric data and driver behaviour questionnaires. In addition to the dataset, the software developed for data synchronisation and processing has been made available. The quality of the dataset was validated using an end-to-end neural network model with multiple inputs to obtain speed and steering wheel angle and obtained very promising results.

In its 8th Malaysia Plan (MP*), the Malaysian government has given nanotechnology development a high priority and has been made a Strategic Research (SR) programme. Consequently, an exhaustive and long-term approach is essential. Additionally, specific laws are required to provide an optimal health and safety environment for workers. Consequently, the current study intends to assist Malaysian policymakers in promoting improved safety, risk assessment, and management for nanotechnology workplaces, as well as drafting a comprehensive policy for the recently released DOSH guideline in 2018. Utilizing a unique methodology, this study evaluated the assessment and management of nanotechnology health and safety risks in Malaysia using the international risk governance council (IRGC) framework. In addition to document analysis, n = 20 semi-structured interviews were conducted with representatives of several nanotechnology platforms to collect data that was then analyzed thematically. The research evaluated current workplace safety regulations and laws. Consequently, we propose a future dynamic strategy for Malaysian nanotechnology with more favourable upgrades supported by increased concentrations in the following areas: I policy creation, ii) comprehensive management system, iii) knowledge transfer, and iv) infrastructure management. In addition, the findings highlight the need of cross-sectional communication in bridging existing gaps. This study laid the groundwork for a more systematic and comprehensive health and safety strategy.

This paper examines the potential of Artificial Intelligence (AI) to address societal megatrends, with a specific focus on OpenAI’s Generative Pre-Trained Transformer 3 (GPT-3). To do this, we con-ducted an analysis using GPT-3 in order to explore the benefits of AI for digitalization, urbanization, globalization, climate change, automation and mobility, global health issues and aging population. We also looked at emerging markets as well as sustainability in this study. Interaction with GPT-3 was done solely through prompt questions and generated responses were analyzed. Our results indicate that AI can significantly improve our understanding of these trends by providing insights into how they develop over time and what solutions could be implemented. Further research is needed to determine how effective AI will be in addressing them successfully but initial findings are encouraging. Our discussion focuses on the implications of our findings for society going forward and suggests that further investigation should be done into how best to utilize new technologies like GPT-3 when tackling these challenges. Lastly, we conclude that while there is still much work left to do before any tangible effects can be seen from utilizing AI tools such as GPT-3 on societal mega-trends; early indications suggest it may have a positive impact if used correctly.

November 15th, 2022 was selected as the day where the human population reached the 8 billion mark [1]. This new reality will force the governments around the world to find ways to sustainably produce and secure food, water, and energy for their countries [2-4]. In terms of water, its quality and availability has been a matter of great concern in recent decades [5], especially with the emergence of new organic and inorganic pollutants [6]. Among organic contaminants, the detection of trace amounts of fluoroquinolone antibiotics, such as ciprofloxacin (CFX) and levofloxacin (LFX), in natural water bodies, has been of great concern in the scientific community [7,8]. Some of the side effects of the consumption of these antibiotics are nausea, diarrhea, abdominal pain, rash, low sugar levels, and antibiotic resistance to bacterial infections, among others [9,10]. It was estimated that in 2019 more than 1.27 million people died due to antibiotic-resistant bacterial infections [11], and this number is expected to rise to 10 million by 2050, if the trend continues [12]. Because of this, new ways to degrade antibiotics from water have been developed over the years. A method that has been implemented for some time is the use of photocatalysts for the degradation of these compounds in water [13]. Semiconductors such as titanium oxide (TiO2), zinc oxide (ZnO), zinc sulfide (ZnS), cadmium sulfide (CdS), strontium peroxide (SnO2), or tungsten trioxide (WO3), among others, are commonly used in photocatalytic processes [14-16]. Zinc oxide has been widely used due to its low cost and stability in aqueous solution, easy production, and because it is an environmentally friendly material [17,18]. It has been identified that some of the disadvantages of ZnO as photocatalyst are photocorrosion, recombination of electron-hole pairs, fast backward reactions, and inability to use visible light [18]. Multiple approaches have been implemented over the years to reduce these limitations. One of them is the use of noble metals such as platinum (Pt), gold (Au), or even silver (Ag) as cocatalysts [15-17,19]. These metals can increase the photocatalytic activity by reducing the recombination of electron-hole pairs, as well allowing the use of visible light [20]. For example, Quin and coworkers [21] prepared a bio-inspired hierarchical assembly of carbonized spinach leaves@Au/ZnO for the degradation of CFX under visible light. The results showed a degradation of 61% of the antibiotic in a period of 180 minutes. Chankhanittha et al. [22] developed different Ag@ZnO composites for the complete degradation of red dye and ofloxacin antibiotic in 25 and 80 minutes, respectively. The researchers attributed the improved photoactivity to the high electron-hole separation efficiency at the photocatalyst interface, as well as the creation of the Schottky barrier at the silver-zinc oxide interface.

This paper is introducing KABADA (Knowledge Alliance of Business Idea Assessment: Digital Approach) unique tool, together with opinions of young people about entrepreneurship, their skills and experience with this tool. The focus is on non-business students who study natural sciences, engineering and other areas at the Faculty of Forestry and Wood Technology at Mendel University in Brno, Czech Republic. KABADA tool has been developed and tested by a team of international experts. It can be used to improve forester management. This structured, Web-based, platform which is based on theoretical research, relevant statistics, and artificial intelligence insights, guides entrepreneurs through every step of the way including what challenges and opportunities lie ahead. The research included survey answers from 60 university students before and after using KABADA tool. The results show that students are interested in entrepreneurship but do not have the knowledge, experience and support from curriculum. Majority of students had no or very low experience with entrepreneurship nor any entrepreneurship training or study course before. After using the tool, students declared to have higher knowledge of entrepreneurship and the number of students who intended to become an entrepreneur increased. The tool is available on-line, free of charge.

Following the central dogma of molecular biology, gene expression variability can aid in predicting and explaining the wide variety of protein products, functions, and, ultimately, variability in phenotypes. There is currently overlapping terminology used to describe the types of variability in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptional diversity as quantifying transcriptional changes as a measure of the variability in 1) the total expression of all genes or a gene across samples (transcriptome diversity) or 2) the isoform-specific expression of a given gene (isoform diversity). We first overview modulators and quantification of gene expression variability. Then, we discuss the role alternative splicing plays in driving transcript isoform expression variability and how isoform diversity can be quantified. Additionally, we overview computational resources for calculating transcriptome and isoform diversity for short- and long-read sequencing data. Finally, we discuss future applications of transcriptional diversity. This review provides a comprehensive overview of how gene expression variability arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms, and species

A progressive and chronic neurological condition called MSA (Multiple System Atrophy) is characterized clinically by varying degrees of dysautonomia, cerebellar ataxia, and parkinsonism. The concept of mitochondrial dysregulation in MSA is one perspective in handling this neurodegenerative disease. Damage to functional mitochondria is driven by the presence of ɑ-Synuclein-induced mitochondrial localization. The goal of MSA treatment up until now has been to reduce symptoms. One of the innovations in the treatment of MSA could be the novel idea based on mitochondrial reprogramming pathways. Mitochondrial reprogramming can be done in various ways in which the use of hydrogen, magnesium and low-dose hydrogen peroxide.

Pharmacovigilance databases are showing evidence of injury in the context of the COVID-19 modified mRNA shots. According to recent publications, adverse event reports linked to the mRNA COVID-19 products largely point to the spike protein as an aetiological agent of adverse events, but we propose that the platform itself may be culpable. To assess the safety of current and future mRNA vaccines, further analysis on the risks due to the platform itself, and not specifically the expressed antigen. If harm can be exclusively and conclusively attributed to the spike protein, then it is possible that future mRNA vaccines expressing other antigens will be safe. If harms are attributable to the platform itself, then regardless of the toxicity, or lack thereof, of the chosen payload therein, the platform may be inherently unsafe, pending modification. In this work, we examine previous studies of RNA-based delivery by a lipid nanoparticle and break down the possible etiological elements of harm.

This paper studies pandemic viruses that spread during the period (1759–2020) according to solar activity cycles. Our findings and results include the following: (1) The severity of a pandemic correlates negatively with the strength of solar activity; (2) Pandemic viruses are classified into three types based on their compatibility with solar activity associations. Most of them spread through the quiet Sun, where viruses survive better in cold and rainy weather, and in stable geomagnetic fields without strong disturbances; (3) The emergence of new strains of influenza viruses was manifested in two ways. First, the annual epidemics due to antigenic drift. Second, pandemics recur every 1–12 solar cycles (about 11–120 years) due to viral reassortment of new subtypes, which results in antigenic shifts; (4) Pandemic viruses have two groups according to their recurring period: first, recurring in nine solar cycles; second, recurring in twelve solar cycles. Furthermore, we reassort pandemic viruses from their previous spread in the same periodic classification. Moreover, we derive a periodicity formula for each subtype of the pandemic virus as a spread date.

Objectives: One of the home-made herbal remedy being traditionally used against gout is evaluated to identify any new and characteristic marker compound which may be used as characteristic analytical marker to standardize this polyherbal remedy. Materials and method: A distinct and remarkable peak in the HPLC chromatogram of remedy was identified which was further isolated by fraction collector. This fraction was then evaporated and characterized for structure elucidation using set of various techniques such as RP-HPLC,UV, FTIR, TLC, EIMS and NMR. Results: The compound characterized was non polar compound, ester of betulin and palmitoleic acid. Although the remedy has been standardized using set of four markers as discussed in literature but this newly developed marker compound can be used to further standardize this remedy and other herbal preparations comprising of this marker compound.Conclusion: Hence the isolated compound can be used as novel analytical marker in the standardization of this herbal remedy and the other herbal preparations containing such marker compound

Microbial immune escape represents the primary cause of induced pathogenesis in humans, and it represents a pivotal method used by viral agents to increase their load and suppress key mechanisms of the innate and adaptive immune system. This phenomenon represents the primary factor that led to the onset of the 1918-1920 A(H1N1) Influenza and 2020-2022 COVID-19 pandemics, and it possibly played a major role in the onset of the AIDS pandemic as well. Moreover, repeated incidents of immune evasion could be associated with higher rates of cellular aging (Jackson et al., 2017), most likely due to the consequent increased demands of energy consumption. Highly developed viral immune evasion ultimately indicates the high inner intelligence of human immunity due to reflective and imitative characteristics of reactions that are produced against initial actions. Ribonucleic acid-based viral genomes contain open reading frames, which consist of genes producing sixteen non-structural proteins. Such proteins play a considerable role in desensitizing first-line immunity during cellular infection, and non-structural proteins 1, 10 and 16 have the strongest effects against a healthy expression rate of Type I and Type III Interferon-encoding genes. Type I Interferons consist of IFN-alpha, -beta, -delta, -epsilon, -omega, -tau and -zeta, whilst Type III Interferons consist of IFN-lambda1, -lambda2 and -lambda3, and they act as stimulators of intracellular signalling cascades that in turn lead to the activation and expression of interferon-stimulated genes (Brown et al., 2022). The earlier the interferon-stimulated genes are activated, the lower the extent of pro-inflammatory mediation and overall, the more effective the antiviral immune response will be, given the exponential nature of the viral load increase. Non-structural protein 16 methylates the 5’ cap of the virus, making the pathogen-associated molecular patterns less recognisable by pattern-recognition receptors, and it requires activation by bonding with non-structural protein 10. It is preserved in the S-Adenosyl-L-Methionine pocket of the SARS-CoV-2 genome. Non-structural protein 1 (NS1) directly cleaves the host cell mRNA producing Type I and possibly Type III Interferons, thereby preventing a translation process of the immune proteins. NS1 has recently been found to often be packaged into exosomes once secreted by the viral genome in the cytosol, meaning that exocytosis and paracrine signalling to neighbouring cells before their actual infection is possible. As a result, NS1 is highly capable of silencing the first-line immune responses of uninfected neighbouring cells as well, thereby highlighting the need to adjust the focus of therapeutics and vaccinology toward first-line immunity and further indicating its foundational importance in the support for the development of precise and balanced defenses against microbial agents of concern (EL SAFADI et al., 2022).

Advances in nanomedicine bring the attention of researchers to the molecular targets which can play a major role in the development of novel therapeutic and diagnostic modalities for cancer management. The choice of a proper molecular target can decide on the efficacy of the treatment and endorse the personalized medicine approach. Gastrin-releasing peptide receptor (GRPR) is a G-protein-coupled membrane receptor, well known to be overexpressed in numerous malignancies including pancreatic, prostate, breast, lung, colon, cervical and gastrointestinal cancers. Therefore, many research groups express a deep interest in targeting GRPR with their nanoformulations. A broad spectrum of the GRPR ligands has been described in the literature, which allows tuning of the properties of the final formulation, particularly in the field of the ligand affinity to the receptor and internalization possibilities. Hereby the recent advances in the field of applications of various nanoplatforms which are able to reach the GRPR expressing cells are reviewed.

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

A Traumatic brain injury (TBI) is among the main causes of sudden death after head trauma. These injuries can result in severe degeneration and neuronal cell death in the CNS, including the retina which is a crucial part of the brain responsible for perceiving and transmitting visual information. The long-term effects of mild-repetitive TBI (rmTBI) are far less studied thus far, even though damages induced by repetitive injuries occurring in the brain are more common, especially amongst athletes. rmTBI can also have a detrimental effect on the retina and the pathophysiology of these injuries are likely to differ from the severe TBI (sTBI) retinal injury.Here we showed how rmTBI and sTBI can dissimilarly affect the retina. Our results indicate an increase in the number of activated microglial cells and Caspase3-positive cells in the retina in both traumatic models, suggesting a rise in the level of inflammation and cell death after TBI. The pattern of microglial activation appears evenly distributed and widespread but differs amongst the various retinal layers. sTBI induced microgial activation in both the superficial and deep retinal layers. In contrast to sTBI, no significant change occurred following the repetitive mild injury in the superficial layer, only the deep layer (spanning from the inner nuclear layer to the outer plexiform layer) shows microglial activation. This difference suggests that alternate response mechanisms play a role in the case of the different TBI incidents. The Caspase3 activation pattern showed a uniform increase in both the superficial and deep layers of the retina. This suggests a different action in the course of the disease in sTBI and rmTBI models and points to the need for new diagnostic procedures.Our present results suggest that the retina might serve as such a model of head injuries since the retinal tissue reacts to both forms of TBI and is the most accessible part of the human brain.

Postpartum depression (PPD) can predispose to physical and mental health problems in women. However, PPD is associated with health and perceived social support but their causal relationship is unclear. Therefore, this study intended to evaluate the association of PPD with insomnia, mental health, and physical health. Convenience sampling technique was used to collect data from 320 (52.8 %) young and middle aged postpartum women, in the outpatient departments of obstetrics and gynecology in Government Maula Bakhsh Hospital, District Head Quarter in Sargodha, Pakistan. The Edinburgh Postnatal depression scale, Pittsburg sleep quality index, Warwick-Edinburgh mental wellbeing scale, Patient health questionnaire, and Multidimensional scale of perceived social support were used to measure study variables. Results revealed a significant positive relationship of PPD with physical health (r= .45, p=.001), while a negative relationship with insomnia (r= -.24, p<.001), and perceived social support (r= -.38, p=.001). Results further confirmed that perceived social support played a moderating role (β = .97, p=.01) in the relationship between PPD and mental health among females. This study concluded that perceived social support has an important role in PPD and women’s health. The study also concluded that poor health is a risk indicator for identifying aid in the early stages of postpartum among women.

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

The research is on the SuperHyperGirth and the neutrosophic SuperHyperGirth. A SuperHyperGraph has SuperHyperGirth where it’s the longest SuperHyperCycle. To get structural examples and instances, I’m going to introduce the next SuperHyperClass of SuperHyperGraph based on SuperHyperGirth. It’s the main. It’ll be disciplinary to have the foundation of previous definition in the kind of SuperHyperClass. This SuperHyperClass is officially called “SuperHyperFlower”. If there’s a need to have all SuperHyperCycles until the SuperHyperGirth, then it’s officially called “SuperHyperOrder” but otherwise, it isn’t SuperHyperOrder. There are two instances about the clarifications for the main definition titled “SuperHyperGirth”. These two examples get more scrutiny and discernment since there are characterized in the disciplinary ways of the SuperHyperClass based on SuperHyperGirth and they’re called “SuperHyperFlower.” A SuperHyperGraph has “neutrosophic SuperHyperGirth” where it’s the strongest [the maximum value from all SuperHyperCycles amid the minimum value amid all SuperHyperEdges from a SuperHyperCycle.] SuperHyperCycle. In “Cancer’s Recognitions”, the aim is to find either the longest SuperHyperCycle or the strongest SuperHyperCycle in those neutrosophic SuperHyperModels. For the longest SuperHyperCycle, called SuperHyperGirth, and the strongest SuperHyperCycle, called neutrosophic SuperHyperGirth, some general results are introduced. Beyond that in SuperHyperStar, all possible SuperHyperPaths have only two SuperHyperEdges but it’s not enough since it’s essential to have at least three SuperHyperEdges to form any style of a SuperHyperCycle. There isn’t any formation of any SuperHyperCycle but literarily, it’s the deformation of any SuperHyperCycle. It, literarily, deforms and it doesn’t form. A basic familiarity with SuperHyperGraph theory and neutrosophic SuperHyperGraph theory are proposed.

Terminalia arjuna possesses significant cardio protective, antidiabetic and antioxidant properties as these properties are described in Ayurveda. In the present study, three flavonoids were isolated through the separation and chromatographic purification of the whole plant material of T. arjuna. Spectroscopic characterization identified one of them as a new flavonoid “Terminalone A (1)” and two known flavonoids i.e. 6-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4H-chromen-4-one (2) and 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one (3). The bioactivity studies showed considerable antibacterial and antioxidant (DPPH was used as a scavenger) potential for all the three compounds 1-3 where the compound 1 showed strong antibacterial and antioxidant activity.

A novel scheme that can simultaneously measure the Doppler frequency shift (DFS) and angle of arrival (AOA) of microwave signals is proposed. At the signal receiving unit (SRU), two echo signals and the reference signal are modulated by a Sagnac loop structure and sent to the central station (CS) for processing. At the CS, two low-frequency electrical signals are generated after polarization control and photoelectric conversion. The DFS without direction ambiguity and wide AOA measurement can be real-time acquired by monitoring the frequency and power of the two low-frequency electrical signals. In the simulation, an unambiguous DFS measurement with errors of ±3×10-3 Hz and a -90° to 90° AOA measurement range with errors of less than ±0.5° are realized. The safety and robustness of the system to environmental disturbance are improved, and it is more suitable for the modern electronic warfare system.

This exploratory study examined the impacts of COVID-19 and emerging challenges and opportunities from aviation recovery. Using archival and secondary data analysis, the study found that there are several challenges to aviation recovery chief among them are labour challenges and extreme weather events, which have been responsible for traffic disruptions in major aviation markets such as Europe and the USA. Other emerging challenges include high debt, inflation, interest rates, fuel, cost of labour, and general operational costs. The study recommends several interventions to address the sector’s challenges, including adopting risk disaster preparedness and management to foster sustainability.

High-grade gliomas are the most common and aggressive adult primary brain tumors with a median survival of only 12-15 months. Current standard therapy consists of maximal safe surgical resection followed by DNA-damaging agents, such as irradiation and chemotherapy that can delay but not prevent inevitable recurrence. Some have interpreted glioma recurrence as evidence of glioma stem cells which persist in a relatively quiescent state after irradiation and chemotherapy, before the ultimate cell cycle re-entry and glioma recurrence. Conversely, latent cancer cells with a therapy-induced senescent phenotype have been shown to escape senescence, giving rise to more aggressive stem-like tumor cells than those present in the original tumor. Therefore, approaches are needed to either eliminate or keep these glioma-initiating cells in a senescent state for a longer time to prolong survival. In our current study, we demonstrate that the radiation-induced cell cycle inhibitor P21 can provide a powerful route to induce cell death in short-term explants of PDXs derived from three molecularly diverse human gliomas. Additionally, cells not killed by P21 overexpression were maintained in a stable senescent state for longer than control cells. Collectively, these data suggest that P21 activation may provide an attractive therapeutic target to improve therapeutic outcomes.