The transportation sector stands out as California's primary contributor to greenhouse gas emissions, necessitating urgent action from government agencies to promote the adoption of low-carbon transportation (LCT) within the heavy-duty vehicles (HDV) and off-road equipment (ORE) sectors. This study conducts content analysis to delve into the impact of behavioral factors, specifically awareness and impression, on LCT adoption within these sectors. The analysis results are honed using a generative artificial intelligence (AI) tool. Positive associations emerge between the potential for LCT adoption and awareness, as well as factors linked to LCT (government incentives, environmental considerations). Notably, the study reveals that financial barriers and incentives hold greater significance for small-fleet organizations compared to their large-fleet counterparts. These findings offer actionable insights for government agencies to formulate targeted strategies, including mandates and incentives, tailored to the unique needs of organizations within the HDV and ORE sectors.

Spike (S) protein of Coronaviruses help in receptor attachment and virus entry into the host cells. While S protein is required for virus entry, it is also important as an immunogen as it is the most accessible part of the virus architecture. S protein form knob like structures (viral spikes) protruding outwards in the form of homotrimers containing an S1 and S2 as monomers. Mutations in structural proteins of virus play crucial role in determining virulence and also in many instances influencing emergence of antibody escape variants and cellular tropism. In this paper we have performed in depth analyses of spike protein sequences from various parts of the world and tried to correlate the data with possible functional relevance of such mutations.

Introduction: Due to COVID-19 pandemic, performance of many program has been declined and Tuberculosis (TB) program is not an exception. TB case detection and notification has been recognized as one of worst hit area. The objective of this study was to explore the TB notification status of India during this pandemic and explore options to mitigate the issue. Methods: A secondary data analysis was performed on open source TB notification database of India. Relevant literature review was done to find out remedies based on the different initiative taken by different states of India. Results: In 2020, total TB notification decreased in all the states in comparison to 2019. The percentage of loss in the country was 34%. Private TB notification also decreased in 2020 in all the states except in Jharkhand. The percentage of loss in private TB notification in the country was 35%. Notification started declining in the month of February 2020 and it was lowest in the month of April-2020. The trend of notification began to improve since May 2020 when the States started taking innovative initiatives like Integrated TB Covid Case Search. Conclusion: Due to the ongoing COVID-19 pandemic the notifications of TB cases declined noticeably which has a serious implication in terms of silent spread within household and community. But the picture can be improved with integrated approach for TB-COVID case finding and management.

Rapidly rotating neutron stars with very strong surface magnetic fields are observed to emit pulsed emission in the whole range of electromagnetic spectrum from radio to high energy gamma-rays. These so called pulsars are known for their exceptional rotational stability. The radio emission from pulsars is generally believed to be powered by the rotational energy of neutron stars. More than 3000 pulsars have been currently known from radio observations, however, it is observed that a large population of pulsars is also bright in optical, X-rays and gamma-rays. The Fermi-LAT observations in the energy range above 100 MeV have discovered about 300 pulsars. However, origin of high energy non-thermal radiation from pulsars is not completely understood and remains an active area of research. In this contribution, we report a summary of observational features of the gamma-ray pulsars and perform pulsar population study to predict their detectability for the MACE gamma-ray telescope, which has just started its regular science operation at Hanle in India.

Electric vehicles (EVs) play a significant role in reducing carbon emissions. In the US, EVs are mostly owned by multi-vehicle households, and their usage is primarily studied in the context of vehicle miles traveled. This study takes a unique approach by analyzing EV usage through the lens of vehicle choice (between EVs and internal combustion engine vehicles) within multi-vehicle households. A two-step machine-learning framework (clustering and decision trees) is proposed. The framework determines the preferred trip category for EV use and captures the effects of household attributes, driver attributes, built-environment factors, and gas prices on EV use in multi-vehicle households. Results indicate that discretionary trips (accumulated local effect = 0.037) are mostly preferred for EV use. EV preference is more pronounced among households with fewer workers (<2) and lower income levels. These findings are valuable for policymakers and auto manufacturers in targeting specific market segments and promoting EV adoption.

PDEF is expressed in luminal epithelial cells of the prostate gland and associates with luminal phenotype. Hippo pathway regulates cell growth/proliferation, cellular homeostasis, and organ development by modulating phosphorylation of its downstream effectors. In previous studies, we observed decreased levels of PDEF during prostate cancer progression. In the present studies, we evaluated the effects of PDEF on total and phospho (Ser-127)YAP1 protein(a downstream effector of the Hippo pathway) levels in PC3 cells, a line of castrate resistant prostate cancer. We observed that the expression of PDEF in PC3 cells resulted in increased increased phospho(Ser127) -YAP1 protein levels. Our immunofluorescence analysis for YAP1 revealed an increased cytoplasmic/nuclear ratio of YAP1 in PDEF-PC3 cells as compared to VC-PC3 cells, suggesting PDEF may play a critical role in modulating YAP1 phosphorylation, and by extension in the regulation of the Hippo pathway. We also observed a decrease in YAP1 protein levels in prostate cancer tissues as compared to normal prostate tissues. Our analysis of multiple publicly available clinical cohorts revealed a gradual decrease in YAP1 mRNA expression during prostate cancer progression and metastasis. This decrease was similar to the decrease in PDEF levels which we reported earlier. In addition we observed further decreased in PDEF and YAP1 expression in Neuro-Endocrine Prostate Cancer (NEPC), and a direct correlation between PDEF and YAP1 expression. To the best of our knowledge, these results provide the first demonstration of modulation of YAP1 by PDEF in any system and suggest a cross-talk between PDEF and the Hippo pathway.

Objective: In India, yearly, estimated one million TB cases are missing from notification, mostly from private sector. The large number of patients in private sector has raised concerns for suboptimal quality of care. This study was conducted to find out the treatment adherence status among the private TB patients and factors associated with poor adherence.Data Source: Secondary project data, obtained through adherence monitoring house visit by NGO workers. Data collected by reviewing different records available with the patients & data was entered into the CommCare HQ, an open-source mobile platform designed for data collection.Methods: Descriptive observational study.Results: Default rate among private patients was 5%. Commonest reasons stated for being a defaulter were ‘Medicine is not good’ (30%), ‘Travel’ (28.6%), ‘Cost of treatment’ (21.8%) and ‘Side effects’ (11.6%). Despite best of efforts only 36.9% defaulter could be retrieved. Higher default rate was associated with 15-59 years age, males, earning member of the family, addiction, DR-TB, continuation phase of treatment, previous history of TB, presence of symptoms and inability to walk.Conclusion: Privately treated TB patients are vulnerable to non-adherence. Once defaulted, it is difficult to retrieve them. Economically productive age group is at higher risk of being defaulter. Strict adherence monitoring for private TB patients and extensive advocacy communication & social mobilization program in the community, workplaces and institutions is a need of hour.

In this article, we analyse the computer aid screening method of COVID19 using Xray and CT scan images. The main objective is to set an analytical closure about the computer aid screening of COVID19 among the X-ray image and CT scan image. The computer aid screening method includes deep feature extraction, transfer learning and traditional machine learning image classification approach. The deep feature extraction and transfer learning method considered 13 pre-trained CNN model. The machine learning approach includes three sets of features and three classifiers. The pre-trained CNN models are alexnet, googlenet, vgg16, vgg19, densenet201, resnet18, resnet50, resnet101, inceptionv3, inceptionresnetv2, xception, mobilenetv2 and shufflenet. The features and classifiers in machine learning approaches are GLCM, LBP, HOG and KNN, SVM, Naive bay’s respectively. In addition, we also analyse the different paradigms of classifiers. In total, the comparative analysis is carried out in 65 classification models, i.e. 13 in deep feature extraction, 13 in transfer learning and 39 in machine learning approaches. Finally, all the classification models perform better in X-ray image set compare to CT scan image set.

The rapid growth of the global population is causing a significant increase in waste production, leading to serious environmental and public health challenges. To address these issues, waste management systems are incorporating advanced technologies. Machine learning and computer vision are used to predict waste patterns, optimize collection schedules, and improve sorting accuracy. Deep learning automates the sorting process, provides predictive analytics, and enhances recycling rates. Robotics, combined with AI and computer vision, improves sorting efficiency, while the Internet of Things (IoT) monitors waste levels and optimizes collection routes. Despite these benefits, challenges such as data scarcity, high computational demands, and the need for substantial infrastructure investments must be addressed. This research explores the integration of advanced technologies into waste management and evaluates their effectiveness using waste datasets. It highlights the potential to tackle environmental challenges and lay the groundwork for more intelligent waste management solutions.

Till date there are three full length COVID 19 virus genome sequences available from India. The earlier two were reported from Kerala, Southern India and the more recent one has been reported from Gujarat, western part of India. In this paper we report two novel mutations in the Spike protein sequence of Gujarat’s isolate. These mutations are based on comparison with the original Wuhan sequence. The two mutations have been found to be located just upstream and downstream of the receptor binding domain (RBD). Out of these two one has also been found to affect the secondary structure of the S1 domain. Since both of these mutations lie near the receptor binding domain, they might influence the spike receptor interactions by changing the conformation of the spike protein S1 domain. These mutations are uniquely placed and might be important in the context of vaccine engineering and therapeutic interventions.

The attempt of this study made us to Study the Competency Mapping (CM) in Software Companies”. CM is a process of categorizing the gap of a person or an employee’s performance routine or professional related skills to fill the gaps through effective programs. (1) Background: Integrating competencies such as “Developing people through Empowering and Training Programs, Providing Feedback, and Rewards, Recognizing the Employee for their work, Effective Communication, Aligning right values ensuring standards, etc. to evaluate and improve the performance an employee to get desired results; (2) Methods: This study involved 100 software employees (n = 100) to state that the competencies that are mapped have a significant impact on performance.. Chi- square and one – way ANOVA tests we used to identify the relationship between two variables; (3) Results: Goal oriented people can adopt the changes and work in any kind of circumstance for better outcomes; (4) Conclusions: competencies that are mapped have a significant impact on performance. And the person who is goal oriented will try to achieve his/her goals in any type of circumstances.

This research paper examines a cosmological model in flat space-time via $f(R,G)$ gravity where $R$ and $G$ are respectively the Ricci scalar and Gauss-Bonnet invariant. Our model assumes that $f(R,G)$ is an exponential function of $G$ combined with a linear combination of $R$. We scrutinize the observational limitations under a power law cosmology that relies on two parameters - $H_0$, the Hubble constant, and $q$, the deceleration parameter, utilizing the 57-point $H(z)$ data, 8-point BAO data, 1048-point Pantheon data, joint data of $H(z)$ + Pantheon, and joint data of $H(z)$ + BAO + Pantheon. The outcomes for $H_0$ and $q$ are realistic within observational ranges. We have also addressed Energy Conditions, $Om(z)$ analysis and cosmographical parameters like Jerk, Lerk and Snap. Our estimate of $H_0$ is remarkably consistent with various recent Planck Collaboration studies that utilize the $\Lambda$CDM model. According to our study, the power law cosmology within the context of $f(R,G)$ gravity provides the most comprehensive explanation for the important aspects of cosmic evolution.

Computer vision methods have shown to be effective in classifying garbage into recycling categories for waste processing, existing methods are costly, imprecise, and unclear. To tackle this issue, we introduce MWaste, a mobile application that uses computer vision and deep learning techniques to classify waste materials as trash, plastic, paper, metal, glass or cardboard. Its effectiveness was tested on various neural network architectures and real world images, achieving an average precision of 92% on the test set. This app can help combat climate change by enabling efficient waste processing and reducing the generation of greenhouse gases caused by incorrect waste disposal.

Background: Aging is commonly accepted as a time period of declining heath. Aims: This review aimed to examine the research base concerning the use of term ‘successful aging’, a process and outcome deemed desirable, but challenging to attain. A second was to provide related information to demonstrate how health professionals as well as individuals can aim for a ‘successful aging’ process and outcome, despite the presence of disabling osteoarthritis. Methods: Information specifically focusing on ‘successful aging’ and the concept of improving opportunities for advancing ‘successful aging’ despite osteoarthritis was sought. Results: Among the many articles on ‘successful aging’, several authors highlight the need to include, a broader array of older adults into the conceptual framework. Moreover, conditions such as osteoarthritis should not necessarily preclude the individual from attaining a personally valued successful aging outcome. Conclusion: Pursuing more inclusive research and research designs, and not neglecting to include people with chronic osteoarthritis can potentially heighten the life quality of all aging individuals, while reducing pain and depression, among other adverse aging and disability correlates among those with osteoarthritis

Biofortification refers to the increase in the amount of essential vitamins or provitamins or minerals in crops to improve the nutritional status of the people, which is largely intended to alleviate the problem of micronutrient malnutrition. I argue that biofortification may not be an effective weapon to fight against the hidden hunger since it demonstrates limited capacity on nutritional enhancement and can negatively impact the socio-economic fabric of the society in many different ways. Finally, I suggest a couple of alternatives that might meet the challenge more efficiently than biofortified crops.

X-ray Fluorescence Computed Tomography (XFCT) is an emerging non-invasive imaging technique providing molecular-level data, gaining attention for high-resolution imaging. However, increased sensitivity with benchtop X-ray sources raises radiation exposure. Artificial Intelligence (AI), particularly deep learning (DL), has revolutionized medical imaging by delivering high-quality images in the presence of noise. In XFCT, traditional methods rely on complex algorithms for noise reduction, but AI holds promise in addressing high-dose concerns. We present an optimized SCUNet model for noise reduction in low-concentration XRF images. Compared to higher-dose images, our method’s effectiveness is evaluated. While various denoising techniques exist for X-ray and CT, few address to XFCT. The DL model is trained and assessed using the augmented data, focusing on background noise reduction. Image quality is measured using PSNR and SSIM, comparing outcomes with 100% X-ray dose images. Results show the proposed algorithm achieves high-quality images from low-dose and low-contrast agents, with a maximum PSNR of 39.05 and SSIM of 0.86. The model outperforms BM3D, NLM, DnCNN, and SCUNet in both visual inspection and quantitative analysis, particularly in high-noise scenarios. This indicates the potential of AI, specifically the SCUNet model, in significantly improving XFCT imaging by mitigating the trade-off between sensitivity and radiation exposure.

The Internet of Things (IoT) is a promising technology for sensing and monitoring the environment to reduce disaster impact. Energy is one of the major concerns for IoT devices, as sensors used in IoT devices are battery-operated. Thus, it is important to reduce energy consumption, especially during data transmission in disaster-adverse situations. Clustering-based communication helps reduce a node’s energy decay during data transmission and enhances the network’s lifetime. Many hybrid combination algorithms are proposed for clustering and the routing protocol to improve the network lifetime in disaster scenarios. However, the performance of these protocols is widely varied based on the underlying network configuration and the optimisation parameters considered. In this research, we have used the clustering parameters that are most relevant to disaster scenarios, such as the node’s residual energy, distance to sink, and network coverage. Then, we proposed a bio-inspired hybrid (BAO-PSO) algorithm where the Butterfly Optimisation Algorithm (BOA) is used for clustering and Particle Swarm Optimisation (PSO) is used for the routing protocol. The performance of the proposed algorithm is compared with the benchmark protocols LEACH, DEEC, PSO, PSO-GA, and PSO-HAS. Residual energy, network throughput, and network lifetime are considered performance matrices. The simulation result showed that the proposed algorithm increases network lifetime by 10%-20% by comparison with the benchmark algorithm.

The atomic nucleus contains protons and neutrons surrounded by a structured electron cloud. Some combinations of protons and neutrons induce the nucleus to behave like a microscopic magnet, possessing a unique magnitude and orientation known as the nuclear magnetic moment (µ). When the numbers of protons and neutrons are both even then µ=0, but otherwise each nu-clide’s nuclear magnetic moment is unique. A second unique nuclear physical property relates to the nucleon binding energy (BE), which can be thought of as the energy between protons and neu-trons bound within the nucleus. The sequence of stable nuclides increases one nucleon at a time through 36Ar. The binding energy associated with the addition of each successive nucleon (∆BE) through this progression is unique. The hypothesis here is that the unique non-zero magnetic mo-ment and ∆ binding energy of each nuclide derive from its respective microscopic nuclear struc-ture, analogous to the way that the atomic physical properties of an element ultimately derive from its unique electron orbital structure. By extension, the identification of nuclear periodic pat-terns might eventually inform a theory of nuclear structure. The light, stable nuclides through 36Ar were arranged in ascending order according to atomic mass, and their nuclear magnetic mo-ments and binding energies were evaluated for periodic patterns. Fixed-period lengths from 4 through 18 nuclides per period were considered. These fixed periods, each of equal length, were stacked one upon the other and analyzed for vertical trends. The best evidence of periodicity in both µ and ∆BE converges precisely at the fixed 12-nuclide period. Implications for nuclear structure are discussed.

Identifying productive, profitable and less risky cropping systems is important for sustaining farm-based livelihoods in the context of climatic uncertainties and market volatility in many developing nations. Reductionist field crop research identifies the best-bet solutions based on treatment replicates at a single point in time, which may not account for price instability under climatic uncertainties and volatile markets. Keeping this in mind, we estimated productivity, profitability and weather-related risk from eleven different rice-based cropping systems (eight existing and three potential systems) in the coastal region of West Bengal, India. Information on the crop management practices, yield and prices of the component crops of these eleven cropping systems, under ’best,’ ’normal’ and ‘worst’ situations (scenario), were collected through a ques-tionnaire survey on50 farms of Gosaba Block, West Bengal, India. Irrespective of the scenarios, the rice-lathyrus systems, followed by rice-onion and rice-lentil systems recorded the lowest rice-equivalent yields and system yields. However, the highest rice-equivalent yields and system yields were recorded for rice-chilli systems, followed by rice-tomato and rice-potato-green gram systems. Per hectare total paid-out cost (TPC) of rice-tomato systems was higher, followed by rice-chilli, rice-potato-green gram and rice-potato systems. However, irrespective of seasonal conditions (best, normal and worst), rice-chilli systems gave a higher net return followed by rice-tomato and rice-potato-green gram systems. The rice-fallow system recorded the lowest value for both parameters. Under the worst seasonal conditions, the rice-onion system gave a negative net return. Under all the scenarios, the highest B:C ratio was observed for rice-chilli, rice-tomato, rice-potato-green gram and rice-potato systems. The cumulative probability distribution of the rice-tomato system showed first-degree stochastic dominance over other systems and the rice-chilli system showed second-degree stochastic dominance over the rest of the systems. Only the rice-onion system had a small chance (< 1%) of a negative net return, while the rest of the cropping systems were highly likely to get a positive net return. Taking productivity, economics, and risk assessment of different rice-based systems into account, rice-vegetable systems, especially rice-tomato and rice-chilli among the existing systems and rice-potato-green gram system among the potential systems, can be recommended for sustainable intensification in these coastal saline tracts of the region. We also discuss additional socio-economic factors explored by in-depth in-terviews with the farmers, which might influence the adoption and upscaling of these cropping systems in the region.

Heterocycles are unique precursors for the synthesis of various pharmaceuticals and agrochemicals particularly those possessing N- or O- moieties. The development of methods to prepare heterocycles is of great importance in synthesis of organic compounds, especially the heterocycles which can be found in natural products. The synthesis of nitrogen and oxygen containing heterocycles viz. coumarins, dihydropyrimidinones, imidazoles, isoxazoles and benzimidazoles represented an attractive and demanding work for chemists as these nucleus has found extensive applications in several fields such as material science, analytical chemistry and most importantly in medicinal chemistry. Organic synthesis has been attracted towards the development of new environmental friendly procedures to achieve the goals of green chemistry. The fundamental aspects of green chemistry are use of biocatalysts and environmental benign solvents under mild conditions. The present review article summarized the green synthetic methods and biological activities of nitrogen and oxygen containing heterocycles.

This interdisciplinary work communicates identification and quantification of elements responsible for the bioactive potency of leaves from pointed gourd, trichosanthes dioica,using laser induced breakdown spectroscopy (LIBS). Calibration-free LIBS determines the presence of various trace and major elements, their concentrations, and ratios in which they are present in the leaves. The presence of specific elemental ratios of magnesium/sodium and magnesium/potassium could be promising for managing diabetes mellitus. Variable doses of 500, 750, 1000, and 1250 mg per kg body weight of aqueous extract from trichosanthes dioica leaves are administered. A dose of 1000 mg per kg body weight is found to be the most effective. Based on encouraging results, the extract could be harvested to serve as anti-diabetic medication for diabetes and associated symptoms.

Abstract: The recently described perivascular unit (PVU) resides immediately adjacent to the true capillary neurovascular unit (NVU) in the postcapillary venule and contains the normal-benign perivascular spaces (PVS) and pathological enlarged perivascular spaces (EPVS). The PVS are important, in that, they also have recently been identified to be the construct and the conduit responsible for the delivery of metabolic waste from the interstitial fluid to the ventricular cerebrospinal fluid for disposal into the systemic circulation and has been termed the glymphatic system. Importantly, the outermost boundary of the PVS is lined by protoplasmic perivascular astrocyte endfeet (pvACef) that communicate with regional neurons. As compared to the well-recognized and described neurovascular unit (NVU) and NVU coupling, the PVU is less well understood and remains an emerging concept. The primary focus of this narrative review is to compare the similarities and differences between these two units and discuss each of their structural and functional relationships and how they relate not only to brain homeostasis but also how they may relate to the development of multiple clinical neurological disease states and specifically how they may relate to obesity, metabolic syndrome, and type 2 diabetes mellitus. Additionally, the concept and importance of a perisynaptic astrocyte coupling to the neuronal synapses with pre- and postsynaptic neurons will also be considered as a perisynaptic unit to provide for the creation of the information transfer in the brain via synaptic transmission and brain homeostasis. Multiple electron microscopic images and illustrations will be utilized in order to help explain these complex units.

This hypothesis demonstrates that the efficiency of Loop-Mediated Isothermal Amplification (LAMP) for nucleic acid detection can be positively influenced by preconcentration of microbial cells onto hydrophobic paper surfaces. The mechanism of this model is based on the high attraction of microbes towards hydrophobic surfaces. Extensive studies have demonstrated that hydrophobic surfaces exhibit enhanced bacterial and fungal adhesion. The preconcentration approach by exploiting this inherent affinity of hydrophobic paper substrates enables the adherence of a greater number of target cells, resulting in a higher concentration of target templates for amplification directly from urine samples. In contrast to conventional methods, which often involve complex procedures, this approach offers a simpler, cost-effective, and user-friendly alternative. Moreover, the integration of cell adhesion, LAMP amplification, and signal readout within paper origami-based devices can provide a portable, robust, and highly efficient platform for rapid nucleic acid detection. This innovative hypothesis holds significant potential for point-of-care (POC) diagnostics and field surveillance applications. Further research and development in this field will advance the implementation of this technology, contributing to improved healthcare systems and public health outcomes.

Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In Wireless Body Area Network (WBAN), for example, the patients’ health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity rendering the data transmission slower. Cognitive Radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors rendering the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.

G-quadruplex, a unique secondary structure in nucleic acids found throughout human genome elicited widespread interest in the field of therapeutic research. Being present in key regulatory regions of oncogenes, G-quadruplex structure regulates transcription, translation, splicing, telomere stability etc. Changes in its structure and stability lead to differential expression of oncogenes causing cancer. Thus, targeting G-Quadruplex structures with small molecules/ other biologics has shown elevated research interest. Covering previous reports, in this review we try to enlighten the facts on the structural diversity in G-quadruplex ligands aiming to provide newer insights to design first-in-class drugs for the next generation cancer treatment.

RNA sequencing (RNA-Seq) is a complicated protocol, both in the laboratory in generation of data and at the computer in analysis of results. Several decisions during RNA-Seq library construction have important implications for analysis, most notably strandedness during complementary DNA (cDNA) library construction. Here we clarify bioinformatic decisions related to strandedness in both alignment of DNA sequencing reads to reference genomes and subsequent determination of transcript abundance.

A model for parasitic motility has been proposed in which parasite filamentous actin (F-actin) is attached to surface adhesins by a large component of the glideosome, known as the glideosome-associated connector protein (GAC). This large 286 kDa protein interacts at the cytoplasmic face of the plasma membrane with the phosphatidic acid-enriched inner leaflet and cytosolic tails of surface adhesins to connect them to the parasite actomyosin system. GAC is observed initially to the conoid at the apical pole and re-localised with the glideosome to the basal pole in gliding parasite. GAC presumably functions in force transmission to surface adhesins in the plasma membrane and not in force generation. Proper connection between F-actin and the adhesins is as important for motility and invasion as motor operation itself. This notion highlights the need for new structural information on GAC interactions, which has eluded the field since its discovery. We have obtained crystals that diffracted to 2.6-2.9 Å for full-length GAC from Toxoplasma gondii in native and selenomethionine-labelled forms. These crystals belong to space group P212121, cell dimensions are roughly a=119 Å, b=123Å, c=221Å, α=90, β=90, γ=90 with 1 molecule per asymmetric unit, suggesting a more compact conformation than previously proposed.

In this study, we explored the performance of the cumulus convection parameterization schemes of Regional Climate Modeling System (RegCM) towards the Indian summer monsoon (ISM) of a catastrophic year through various numerical experiments conducted with different convection schemes (Kuo, Grell amd MIT) in RegCM. The model is integrated at 60KM horizontal resolution over Indian region and forced with NCEP/NCAR reanalysis. The simulated temperature at 2m and the wind at 10m are validated against the forced data and the total precipitation is compared with the Global Precipitation Climatology Centre (GPCC) observations. We find that the simulation with MIT convection scheme is close to the GPCC data and NCEP/NCAR reanalysis. Our results with three convection schemes suggest that the RegCM with MIT convection scheme successfully simulated some characteristics of ISM of a catastrophic year and may be further examined with more number of convection schemes to customize which convection scheme is much better.

Mitochondria are classically termed as powerhouse of a mammalian cell. Most of the cellular chemical energy in the form of adenosine tri phosphate (ATP) is generated by mitochondria and dysregulation of mitochondrial functions thus can be potentially fatal of cellular homeostasis and health. Acute respiratory distress has been earlier linked to mitochondrial dysfunction. SARS-CoV-2 infection severity leads to acute respiratory distress syndrome (ARDS) and can be fatal. We tried to investigate possible connection between SARS-CoV-2, ARDS and mitochondria. Here, we report identification of SARS-CoV-2 non-structural proteins (particularly Nsp12 and 13) that have recognition sequence with respect to mitochondrial entry. We also report that these proteins can potentially shuttle between cytoplasm and mitochondria based on the localization signals and help in downstream maintenance of the virus. Their properties to use ATP for enzymatic activities may cause ATP scavenging allowing viral RNA functions in lieu of host cell health.

Air pollution is a serious global issue, responsible for approximately one in every nine deaths each year, ranking it among the greatest environmental hazards to human health. It is of particular concern in urban areas, where elevated pollutant concentrations and potential sufferers converge. Over one half of the world’s population presently lives in urban areas, and the urban population ratio is expected to reach 68% by 2050. Common air pollutants include particulate matter (PM), sulphur dioxide (SO2), ground-level ozone (O3), nitrogen oxide (NOx) and carbon monoxide (CO). While elevated rates of air pollution pose serious health risks for humans, outdoor plants can help reduce the harmful effects of air pollution by filtering and purifying the air around us.In this project Common Ivy, Aster and Miniature Andromeda plants were evaluated for air pollutant mitigation. In this study we developed a vegetation barrier model with the plant located in the middle of the greenhouse box, and air pollutant was sprayed on one side of the plant. Dispersion patterns of sprayed pollutants were tested with and without vegetation barrier. Measurements of carbon dioxide (CO2), Formaldehyde (HCHO), Total Volatile Organic Compounds (TVOC), and Particulate Matter (PM2.5/PM10) were taken before spraying, then at 0 and 30 minutes after spraying, using both monitors.The results show mitigation rates (in 177 ft3 of air after 30 min): for TVOC the minimum reduction is 5 mg/m3; for HCHO, 1 mg/m3; for CO2, 2000 ppm; for PM2.5, 2000 ug/m3; and for PM10 it was 1000 ug/m3.

Using desi-cow waste products like Jeevamrit, natural farming is widespread among farmers for improving soil biology and productivity. Jeevamrit enhances soil chemical and microbiological properties without needing large quantities of farmyard manure (FYM), as a sustainable farming practice with a reduced carbon footprint. Despite its traditional use, Jeevamrit faces criticism due to a lack of scientific evidence. This study investigated the comparative effect of Jeevamrit and chemical fertilizers on the growth and yield of marigold cv. Siracole. In this study mother block of marigold was raised for both summer and winter seasons. The cuttings were harvested from the mother block and then kept for rooting. The rooted cuttings were planted at monthly intervals and evaluated for flowering parameters and compared to those treated with RDF (30:20:20 N, P, and K g/m2). Soil supplied with Jeevamrit enhanced bacteria (26.33%), fungi (18.92%), and actinomycetes (31.21%) populations compared over the recommended dose of fertilizers (RDF) (i.e. N:P: K @ 30:20:20 g m-2). Jeevamrit-treated plants have marketable flower yield per square meter (3.98 %) and shelf life (9.93 %) compared to RDF. The study concludes that Jeevamrit @ 2 liter m-2 is a sustainable and effective alternative to traditional fertilizers for enhancing marigold production in the mid-hills of the Himalayan region, where natural farming is already accepted.

Abstract Cerebral microbleed(s) (CMBs) are increasingly being viewed not only as a marker for cerebral small vessel disease (SVD) but also as having an increased risk for the development of stroke (hemorrhagic/ischemic) and aging-related dementia. Recently, brain endothelial cell activation and dysfunction and blood-brain barrier dysfunction and/or disruption have been shown to be associated with SVD, enlarged perivascular spaces, and the development and evolution of CMBs. CMBs are a known disorder of cerebral microvessels that are visualized as 3-5mm, smooth, round or oval, and hypointense (black) lesions seen only on T2*-weighted gradient recall echo or susceptibility-weighted sequences on MRI images. CMBs (a global problem) are known to occur with high prevalence in community-dwelling older individuals. Since our current global population is the oldest recorded in history and only expected to continue to grow, we can only expect the health care burdens associated with CMBs to also grow. CMBs should raise a red flag regarding the increased risk of large symptomatic neurologic intracerebral hemorrhages. Importantly, CMBs are also currently regarded as markers of diffuse vascular and neurodegenerative brain damage. Thus, it is essential that we try to learn as much as we can about their development, evolution, and their relation to impaired cognition, dementia, and neurodegeneration.

Immune-mediated bowel diseases (IMBD), including Ulcerative colitis and Crohn's disease, represent a significant global health burden with their complex etiology and increasing prevalence. The connection between intestinal parasites and the gut microbiome in immune-mediated bowel disease is a complex and evolving field of research. Several studies have demonstrated that intestinal parasites can modulate the composition and function of the gut microbiome. Parasitic infections can result in alterations in the gut microbial community, including changes in microbial diversity, abundance, and metabolic activity. These changes can influence the immune response and contribute to the development of IMBDs. In contrast, the gut microbiome serves a pivotal function in maintaining intestinal homeostasis and immune regulation. Dysbiosis, characterized by changes in the gut microbial composition, has been associated with the pathogenesis of IMBDs. Imbalances in the gut microbiota can result in increased gut permeability, chronic inflammation, and aberrant immune responses, all of which are hallmarks of IMBDs. The bidirectional interaction between intestinal parasites and the gut microbiome further complicates the understanding of immune-mediated bowel diseases. Certain parasites, such as hookworms and Necator americanus, have been found to downregulate immune responses and may have therapeutic potential in treating celiac disease. On the other hand, infections with parasites like Strongyloides stercoralis and Blastocystis have been shown to mimic the symptoms of IBD, highlighting the intricate relationship between parasites and the pathogenesis of these diseases. Additional investigation is required to comprehensively elucidate the mechanisms that underlie the association between intestinal parasites and the gut microbiome in immune-mediated bowel disease. This knowledge could potentially lead to the development of targeted therapeutic strategies that aim to restore gut microbiota homeostasis and alleviate the symptoms of these debilitating conditions. By understanding and harnessing the complex interplay between parasites, the gut microbiome, and the host immune system, researchers may uncover novel approaches for the management and treatment of immune-mediated bowel diseases.

Introduction: Subtalar Arthroereisis (STA) is a surgical intervention for pediatric flexible flatfoot (PFF), primarily targeting hindfoot alignment by limiting excessive subtalar eversion. However, its effects on forefoot parameters remain underexplored. This study aims to investigate radiological changes following STA in pediatric patients. Materials and Methods: A retrospective analysis was conducted on consecutive patients treated with STA for PFF. First ray-related angles, including Hallux Valgus Angle (HVA) and Inter-Metatarsal Angle (IMA), alongside hindfoot radiological parameters such as Meary, Calcaneal Pitch, and Costa Bartani angles, were assessed. Subgroup analysis by gender was performed, and correlations between demographic and pre-operative radiological parameters were examined. Results: Forty-one patients (81 feet) with a mean age of 11.6 years were included, with a mean follow-up duration of 6.4 months. No significant differences were observed in first ray-related an-gles pre- and post-operatively, with mean IMA changing from 7.97° to 7.18° and mean HV angles from 9.51° to 8.66°. Noteworthy improvements were seen in flat foot angles, including Meary, Calcaneal Pitch, and Costa Bartani angles, postoperatively. Age subgroup analysis revealed similar trends in IMA and HVA changes between Group A (operated before peak growth) and Group B (operated later). Higher preoperative angles tended to improve, while lower preoperative IMA and HVA tended to worsen postoperatively, all remaining within normal ranges. Conclusion: STA showed positive radiological outcomes for PFF treatment, while negligible changes in first ray-related angles were observed. Age subgroup analysis indicated similar trends regardless of operation timing. Higher preoperative angles tended to improve, while lower preoperative angles tended to worsen postoperatively, despite all falling within non-pathological ranges. Further re-search is warranted to confirm this correlation.

For applications in sensing and cavity-based quantum computing and metrology, open-access Fabry-Perot cavities – with an air or vacuum gap between a pair of high reflectance mirrors – offer important advantages compared to other types of microcavities. For example, they are inherently tunable using MEMS-based actuation strategies, and they enable atomic emitters or target analytes to be located at high field regions of the optical mode. Integration of curved-mirror Fabry-Perot cavities on chips containing electronic, optoelectronic, and optomechanical elements is a topic of emerging importance. Micro-fabrication techniques can be used to create mirrors with small radius-of-curvature, which is a prerequisite for cavities to support stable, small-volume modes. We review recent progress towards chip-based implementation of such cavities, and highlight their potential to address applications in sensing and cavity quantum electrodynamics.

The atomic structures of Zn and Na borophosphate glasses were studied by X-ray and neutron diffraction. Peaks assigned to the B−O, P−O, and O−O distances confirm that only BO4 units co-exist with the PO4 tetrahedra. The Zn−O and Na−O coordination numbers are found to be a little larger than four. The narrowest peaks of the Zn−O first-neighbor distances exist for the glasses along a line connecting the Zn(PO3)2 and BPO4 compositions (50 mol% P2O5) which is explained by networks of ZnO4, BO4, and PO4 tetrahedra with twofold coordinated oxygens. Calculated amounts of the available oxygen support this interpretation. Broadened peaks occur for glasses with lower P2O5 contents, consistent with the presence of threefold coordinated oxygens. The two distinct P−O peak components of the Zn and Na borophosphate glasses differ in their relative abundances which is interpreted by Na+ cations that coordinate oxygens in some P−O−B bridges, something not seen for the Zn2+ ions.

The novel coronavirus has affected the mental state of the general public, more so among healthcare workers. During the pandemic when the infectivity had become intense, dental professionals were at stake as their work demanded more proximity with oral and nasal secretions. Many dentists had to close their clinics for fear of infection. This had a significant impact on their financial, social and emotional wellbeing. Stress is what arises when something we care about is at stake. Dentistry which is already a stressful discipline, the pandemic has multiplied the already existing pressures of isolation, the focus on perfectionism, compromise on treatment, and time pressures. Our study has attempted to assess the perceived stress among dentists and the various correlates impacting the same. Resilience is the capacity to bounce back productively during stressful situations. Resilience acts like a buffer to wither stress. Resilience is neither permanent nor global. In our study, we have attempted to assess resilience among dentists using a standard validated scale and various sociodemographic factors impacting resilience. Further, we have tried to assess the correlation between stress and resilience. We found that senior dentists with more years of experience had more resilience and their perceived stress was less. Though we found increased perceived stress among women dentists, resilience did not have any gender difference. It is essential to be pandemic prepared with the implementation of resilience-building strategies at various levels.

Low-energy cosmic rays (LECRs) play a crucial role in the formation of planetary systems, and detecting and reconstructing the properties of early LECRs is essential for understanding the mechanisms of planetary system formation. Given that LECRs interact with the surrounding medium to produce nuclear de-excitation line emissions with energy mainly within 0.1–10 MeV, which are unaffected by stellar wind modulation, these gamma-ray emissions can accurately reflect the properties of LECRs. This study introduces an innovative method for using gamma-ray emissions to infer LECR properties. We employed the Parker transport equation to simulate the propagation and spectral evolution of LECRs in a protoplanetary disk and calculated the characteristic gamma-ray emissions resulting from interactions between LECRs and disk material. These gamma-ray emissions encapsulate the spectral information of LECRs, providing a powerful tool to reconstruct the cosmic ray environment at that time. This method, supported by further theoretical developments and observations, will fundamentally enhance our understanding of the impact of CRs on the origin and evolution of planetary systems and address significant scientific questions regarding the cosmic ray environment at the origin of life.

We used an ultrasensitive, broadband optomechanical ultrasound sensor to study the acoustic signals produced by pressurized nitrogen escaping from a variety of small syringes. Harmonically related jet tones extending into the MHz region were observed for a certain range of flow (i.e., Reynolds number), in qualitative agreement with historical studies on gas jets emitted from pipes/orifices of much larger dimensions. For higher turbulent flow rates, we observed broadband ultrasonic emission in the ~ 0 – 5 MHz range, likely limited on the upper end by attenuation in air. These observations are made possible by the broadband, ultrasensitive response (for air-coupled ultrasound) of our optomechanical devices. Aside from their theoretical interest, our results could have practical implications for the non-contact monitoring and detection of early-stage leaks in pressured fluid systems.

Households and businesses are generating unprecedented levels of electrical and electronic wastes (e-waste), fueled by modernisation and rapid obsolescence. While the challenges imposed by e-waste are similar everywhere in the world, disparities in progress to deal with it exists; with developing nations such as South Africa lagging. The increase in e-waste generation increases the need to formulate strategies to manage it. This paper presents an overview of e-waste management on a global and South African scenarios with a specific case for Cathode Ray Tube (CRT) waste management practices in South Africa. CRTs present the biggest problem for recyclers and policy makers because they contain hazardous elements such as lead and antimony. Common disposal practices have been either landfilling or incineration. The research into the South African practices with regards to CRT waste management showed that there is still more to be done to effectively manage this waste stream. This is despite clear waste regulatory frameworks in the country. However, recent developments have placed e-waste as a priority waste stream, which should lead to intensified efforts in dealing with it. Overall, these efforts should aim to maximise diversion from landfilling and to create value-addition opportunities, leading to social and environmental benefits.

Abstract: Objective: To assess both individual and interactive effects of prenatal medical conditions depression and Diabetes, and health behaviors including smoking during pregnancy on infant birth defects. Methods: The data for this research study were collected by the Pregnancy Risk Assessment Monitoring System (PRAMS) in 2018. Birth certificate records were used in each participating jurisdiction to select a sample representative of all women who delivered a live-born infant. Complex sampling weights were used to analyze the data with a weighted sample size of 4,536,867. Descriptive statistics were performed to explore frequencies of the independent and dependent variables. Bivariate and multivariable analyses were conducted to examine associations among the independent and dependent variables. Results: The results indicate and significant interaction between the variables smoking and Depression and Depression and Diabetes (OR= 3.17; p-value <0.001 and OR= 3.13; p-value <0.001 respectively). Depression during pregnancy was found to be strongly associated with delivering an infant with a birth defect (OR= 1.31, P-value < 0.001). Conclusion: Depression during pregnancy and its interaction with smoking and Diabetes are vital in determining birth defects in infants. The results indicate that birth defects in the United States can be lowering Depression in pregnant women.

While the two primary risk factors for head and neck squamous cell carcinoma (HNSCC) are alcohol and tobacco, viruses account for an important and significant upward trend in HNSCC incidence. Human papillomavirus (HPV) is the causative agent for a subset of oropharyngeal squamous cell carcinoma (OPSCC)—a cancer that is impacting a rapidly growing group of typically middle-aged non-smoking white males. While HPV is a ubiquitously present virus (with about 7% of the population having oral HPV infection at any one time), only 1% of those infected develop OPSCC— suggesting that additional cofactors or coinfections may be required. Epstein-Barr virus (EBV) is a similarly ubiquitous virus that is strongly linked to nasopharyngeal carcinoma (NPC). Both of these viruses cause cellular transformation and chronic inflammation. While dysbiosis of the human microbiome has been associated with similar chronic inflammation and the pathogenesis of mucosal diseases (including OPSCC and NPC), a significant knowledge gap remains in understanding the role of bacterial-viral interactions in the initiation, development, and progression of head and neck cancers. In this review, we utilize the known associations of HPV with OPSCC and EBV with NPC to investigate these interactions. We thoroughly review the literature and highlight how perturbations of the pharyngeal microbiome may impact host-microbiome-tumor-viral interactions—leading to tumor growth.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

This short communication makes use of the principle of singular perturbation to approximate the ordinary differential equation (ODE) of prompt neutron (in the point kinetics model) as an algebraic equation. This approximation is shown to yield a large gain in computational efficiency without compromising any significant accuracy in the numerical simulation of primary coolant system dynamics in a PWR nuclear power plant. The approximate (i.e., singularly perturbed) model has been validated with a numerical solution of the original set of neutron point-kinetic and thermal–hydraulic equations. Both models use variable-step Runge–Kutta numerical integration.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

To achieve higher crop yields and maintain environmental conservation, it becomes imperative to adopt novel agricultural methods that improve both the quantity and quality of produce. The above study focused on investigating the effectiveness of integrated use of biogas slurry (BS) and inorganic nutrigation on spinach growth and nutrient uptake through drip irrigation. Under field conditions and using a split plot design, spinach was cultivated with seven different treatments: biogas slurry nutrigation (BSN) (T1), integrated inorganic + organic nutrigation: 40% Recommended dose of fertilizer (RDF) +BSN (T2), 60% RDF +BSN (T3), 80% RDF +BSN(T4), 100% RDF(T5), slurry broadcasting (SB) (T6), and control(T7). The results showed that spinach grown with T4 80% RDF +BSN exhibited optimum plant height and leaf count compared to spinach under other treatments and was at par with T5 100% RDF for crop parameters. T5 treated plants demonstrated the longest roots, followed by T4 treated plants. The biomass produced by T4 was at par with T5 in the first (T4= 4.60 tonha-1, T5 =4.67 tonha-1) and second harvesting(T4= 6.69 tonha-1, T5 =6.89 tonha-1).In terms of macronutrient content in spinach leaves, significant differences were found only for nitrogen (N),potassium (K), while the phosphorus contents were not significantly influenced. Incorporating biogas slurry into the soil modifies microbial enzyme activities, specifically dehydrogenase and phosphatase. Normally, alkaline phosphatase shows greater activity than acidic phosphatase, but the addition of biogas slurry equalized the enzymatic activity of both, establishing a harmonized enzymatic profile. Fertilizing spinach with integrated Biogas slurry nutrigation + inorganic nutrigation not only improves growth and development to a similar extent as inorganic fertilizer but also enhances the nutrient content of the spinach, contributes to environmental preservation, and reduces production costs.

In this article, we introduce the concept of soft intervals, soft ordering and sequences of soft real numbers, and some of their structural properties are studied. The notion of soft Lebesgue measure on the soft real numbers has been introduced. Also, a correspondence relationship has been established between the soft Lebesgue measure and the classical Lebesgue measure. Furthermore, we have studied some exciting results and relations between the soft Lebesgue measure and the Lebesgue measure of soft real sets.

Building a widely distributed hotspot network is a very tedious task due to its complexity. Providing security, fully distributed network services, and cost-conscious impact are the major challenges behind this goal. To overcome these issues, we have presented a novel distributed hotspot network architecture with five layers that can provide large-scale hotspot coverage as an assimilated result. Our contributions to this new architecture highlight important aspects. First, scalability can be increased by including many Internet-of-Things (IoT) devices with sensors and Wi-Fi and/or LoraWAN connectivity modules. Second, hotspot owners can rent out their hotspots to create a distributed hotspot network in which the hotspots can act as an ordinary data gateway, a full-fledged hotspot miner, and a lightweight hotspot miner to earn crypto tokens as rewards for certain activities. Third, the advantages of Wi-Fi and LoraWAN can be seamlessly leveraged to achieve optimal coverage, higher network security, and suitable data transmission rate for transferring sensor data from IoT devices to remote application servers and users. Fourth, blockchain is used to enhance the decentralized behavior of the architecture presented here by providing immutability and independence from a centralized regulator and making the network architecture more reliable and transparent. The main feature of our paper is the use of the tau-computing paradigm along with hotspots to improve availability, Internet backhaul-agnostic network coverage, and synchronous update capability, and tau-aware leasing to strengthen and improve coverage. We also discuss the key challenges and future roadmap that require further investment and deployment.

Hydraulic conductivity is the key and one of the most uncertain parameters in groundwater modeling. The grid based numerical simulation require spatial distribution of sampled hydraulic conductivity at un-sampled locations in the study area. This spatial interpolation has been routinely performed using variogram based models (two-point geostatistics methods). These traditional techniques fail to capture the complex geological structures, provides smoothing effects and ignore the higher order moments of subsurface heterogeneities. In this work, a multiple-point geostatistics (MPS) method is applied to interpolate hydraulic conductivity data which will be further used in WASH123D numerical groundwater simulation model for regional smart groundwater management. To do this, MPS need ‘training images (TIs) as a key input. TI is a conceptual model of subsurface geological heterogeneity which was developed by using concept of ages, topographic slope as an index criteria and knowledge of geologist. After considerations of full physics of study area, an example shows the advantages of using multiple-point geostatistics compared with the traditional two-point geostatistics methods (such as Kriging) for the interpolation of hydraulic conductivity data in a complex geological formation.

The concept of smart morphing blades, which can control themselves to reduce or eliminate the need for active control systems, is a highly attractive solution in blade technology. In this paper an innovative passive control system based on Shape Memory Alloys (SMAs) is proposed. On the basis of previous thermal and shape characterization of a single morphing blade for a heavy-duty automotive cooling axial fan, this study deals with the numerical analysis of the aerodynamic loads acting on the fan. By coupling CFD and FEM approaches it is possible to analyze the actual blade shape resulting from both the aerodynamic and centrifugal loads. The numerical results indicate that the polymeric blade structure ensures proper resistance and enables shape variation due to the action of the SMA strips.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

Samarinda City is one of the most attractive cities in Borneo Island (Indonesia) and also as a capital city of EastBorneo Province. The expansion of urban areas becomes essential due to rapid population and housing demand. Base on the statistical report, the annual population growth rate is 0.018% from the year 2016-2017 with a total population of 843446 inhabitants. Many natural disasters occur in some areas in this city, especially flooding. This natural disaster occurs almost every year, many people suffered and forced to evacuate. In 2018 there is 3 flood event with 28311 people was suffered and evacuated, and 5170 houses were flooded [1]. During the flood event, it was very possible to gain damages to their property and make traffic stuck. One common way to reducing the damages is using Early Warning Systems (EWS). Early warning is a major element for disaster risk reduction, including damages. To prevent and mitigate the impact of a disaster, many countries had taken action to build various methods of a public warning system. An effective early warning system focused on people-centered and comprises the following element, such as risk knowledge, technical monitoring and service, communication and dissemination of warnings, and community response capability [2]. Related to the existing condition which Samarinda is a Muslim-dominated city and obviously has a lot of a number of mosques. This is a good potency to develop an early warning system because every mosque has a loudspeaker for echoing Adzan (Muslim prayer-calling). With this existing condition, the loudspeaker can be utilized as a flood outdoor-voice warning announcer. The aim of this study is to briefly introduce the strategy of dissemination early warning by utilizing mosques. The hope of early warning dissemination is giving enough time to the people to evacuate their property to reduce damages and possibly to giving information to avoiding traffic stuck (in a certain location)due to flooding. The results of this study can be used as input for decision-makers to develop effective flood management strategies and policies, especially in the case of an early warning system where not well-developed in Samarinda.

The main objective of this study is to find out the influence of cooperation and intra-specific competition in escaping predation through refuge of the prey population and the effect of the two intra-specific interactions on the dynamics of prey-predator systems. For this purposes, two mathematical models with Holling type-II functional response function have been proposed and analyzed. The first model includes cooperation among prey populations whereas the second one incorporates intra-specific competition. Existence conditions and stability of different equilibrium points of both models have been carried out for the qualitative behaviour of the systems. Refuge through intra-specific competition has a stabilizing role, whereas cooperation has a destabilizing role on the system dynamics. Periodic oscillations are observed in both the systems through Hopf bifurcation. From the analytical and numerical findings, we conclude that intra-specific competition affects the prey population and continuously checks the refuge class under a critical value, and thus it never becomes too large to cause predator extinction due to food scarcity. Conversely, cooperation leads maximum individuals to escape predation through the refuge so that predators will suffer from low predation success.

High-quality and large-size single crystals of lead-free Na0.5Bi0.5TiO3 were grown using the Czo-chralski technique. The crystals had pure perovskite structure with rhombohedral symmetry and were translucent in the visible and near infrared spectral ranges recorded in the interval 350-1050 nm. The energy gaps determined from the X-ray photoelectron spectroscopy (XPS) and optical measurements were approximately 2.92 eV. The current-voltage characteristics, depolarization current, dc (σdc) and ac (σac) electrical conductivity, and Seebeck coefficient of the crystals were investigated. The frequency/temperature-dependent electrical properties were also measured and analyzed through complex impedance spectroscopy. An overlapping reversible insulator-metal transition (resistive switching) on nanoscales, caused by the electric field, was detected. This was the first time that most of these investigations were performed for this material. The following conductivity mechanisms of NBT single crystals were identified: (i) quasi-free electron and hole conduction and hopping-charges mechanism at low temperatures, (ii) small polaron conductivity in the middle temperature range, and (iii) a significant contribution of the oxygen vacancies to conductivity in the high temperature range. The activation energy values determined from the conductivity data, the imaginary part of the electric impedance and the modulus indicate that the relaxation process in the high-temperature range is attributable to both single and double ionized oxygen vacancies, in combination with the hopping of electrons between Ti4+ and Ti3+. P-type electrical conductivity was also found. These discoveries create new possibilities of reducing the electrical conductivity of NBT and improving the process of effectively poling this material. The density of the electronic states was investigated using an ab initio method. The energy gap cal-culated for NBT (R3c) was 2.8 eV, and is well comparable to those determined from XPS and optical measurements. Our results indicate the possibility of tuning material properties by inten-tionally creating non-stoichiometry/structural defects (oxygen vacancies, cation excess and cation deficiency).

The present study aimed to undertake a detailed investigation of pathological epidemiology and molecular confirmation of Ehrlichia canis among pet dogs in smart city Bhubaneswar, Odisha, a state in eastern India. A total of 178 dogs were screened for Ehrlichiosis on the basis of history, clinical signs, blood, and buffy coat smear examination, resulting in only 56 dogs (31.46%) screening positive. The epidemiological study recorded an increase in incidences among dogs less than one year of age (41%), males (68%), German Shepherds (25%), dogs more than 20 kg body weight (75%), summer months (55%) and dogs housed on pukka houses with exposure to the outside (59%). The majority of the infected dogs had a history of tick infestation (79%) at some point in their life. Clinical signs showed non-typical manifestations like fever, lethargy, diarrhoea, epistaxis, hind limb edema, and corneal opacity. Haematological studies revealed anaemia and thrombocytopenia along with neutrophilia with relative lymphopenia and monocytosis. A decreasing trend was observed in the levels of total protein and albumin with an increase in the levels of globulin, AST, ALT, BUN, and creatinine. The ultrasonography studies revealed hepatosplenomegaly along with hyper-echogenicity in various organs. Pro-teinuria and haematuria were consistent, along with the presence of bile salts in the urine of affected dogs. Molecular confirmation from n-type PCR data using Ehrlichia-specific primers targeting p28 gene (843 bp) was done, and the identified gene sequences submitted to NCBI databases have accession numbers OQ383671-OQ383674 and OP886674-OP886677. Ticks collected from dogs were identified morphologically through microscopy and scanning electron microscopy as Rhipicephalus sanguineus.

Observations of the X-ray binary system Her X-1 by the AstroSat Soft X-ray Telescope 1 (SXT) were carried out in 2020 through 2023 with the goals of measuring X-ray spectrum changes with the 35-day disk rotation phase and measuring eclipses at different 35-day phases. The four multi-day long observations were scheduled during: turn-on to Main High (MH) and MH rise; MH state; Short High (SH) state; and Low State (LS). 35-day phase was determined using monitoring observations with the Swift Burst Alert Telescope (BAT). Nine eclipses were observed at a range of 35-day phases, with at least one eclipse during each observation. Data with dips were separated from data without dips. The variation of X-ray spectral parameters vs. 35-day phase shows the following: eclipse parameters are nearly constant, showing that the scattering corona does not change with 35-day phase; dips show an increase in covering fraction but not column density compared to non-dip data; the 1 keV line normalization indicates an origin in a small region near the continuum emission region, likely the magnetospheric accretion flow from the inner disk onto the neutron star; and the change in blackbody normalization (area) shows that the emission region is much larger than the 1 keV emission region, and consistent with the inner edge of the accretion disk.

This paper presents an on-device semi-supervised human activity detection system that can learn and predict human activity patterns in real time. The proposed semi-supervised learning (SSL) framework uses sparsely labelled user activity events acquired from Inertial Measurement Unit (IMU) sensors installed as wearable device. The objective is to learn classification of multiple classes of human activities in real-time. The proposed cluster-based learning model in this approach is trained with data from the same target user, thus preserving data privacy while providing personalized activity detection services. Two different cluster labelling strategies, namely, population-based, and distance-based, are employed to achieve the desired classification performance. A comparative study of these strategies has been presented in terms of classifiability and classification accuracies. The proposed system is shown to be computationally efficient, which is relevant in the context of limited computing resources on typical wearable devices. The trade-off between classification accuracy and computation complexity is analyzed for different algorithmic hyper-parameters and other system parameters. Extensive experimentation and simulation study have been conducted on a multi-user human activity data from the public do-main in order to validate the proposed learning paradigm.

Adolescence is a critical developmental period associated with an increase in stress, the appearance of anxiety and depressive symptoms, and changes in sleep patterns. Even though the disruption of sleep patterns in stress and anxiety and depressive disorders is well known, the independent effects of childhood trauma and stressful life events on sleep patterns are less understood. We tested the independent effects of stress (childhood trauma and stressful life events) while controlling for anxiety and depression on adolescent sleep patterns. Seven hundred fifty-two adolescents completed self-report questionnaires about childhood trauma, stressful life events, anxiety, and depression. Four sleep factors identifying movement during sleep, sleep regularity, sleep disturbances and sleep pressure were extracted in the principal component analysis of sleep questions. Both childhood trauma and recent stressful life events were significantly associated with sleep disturbances before and after controlling for anxiety and depression.

Abstract: Background: To determine the impact of a patient's ethnicity on the seeking preventive dental services at the Community Health Centers (CHCs) in South-Central Texas. Methods: Pri-mary electronic health records (HER) data were collected regarding each patient's medical and dental history, and comprehensive treatment planning. The researchers retrieved EHR from Jan-uary 2016 to 2022. Bivariate analysis was completed to test outcome with predicator and covariates using appropriate statistical tests. A multiple linear regression model was used to understand the association between the predictor and outcome variable while controlling for confounders. Results: The study findings revealed significantly higher dental visits (2.26 ± 2.88) for Hispanic patients. The results from the multiple regression model indicated that non-Hispanic patients had a 8% fewer chance of visiting the CHCs for preventive dental services compared to the Hispanic population (p-value<0.001) when all other variables are held constant. However, the study results were not significant as the effect size was small to conclude the effect of ethnicity on the patients visiting the dental clinic at the CHCs for preventive services. Conclusion: The study concluded that there is no difference in the preventive dental services completed by Hispanics and Non-Hispanics when all other variables are controlled.

Dengue virus (DENV), being one of the lethal pathogens in the hot climatic regions of the world, have been extensively studied to decipher its mechanism of pathogenesis and missing links of its life cycle. With respect to the entry of DENV, multiple receptors have been recognised in different cells of the human body. However, scientists still argue whether these identified receptors are the exclusive entry mediators for the virus. Adding to the complexity, DENV has been reported to be infecting multiple organ types in its human host. Also, more than one receptor in a particular cell has been discerned to take part in mediating the ingress of DENV. In this review, we aim to discuss about the different cells of the human immune system that support DENV infection and their corresponding receptors that DENV deploy to gain access to the cells.

Lactoperoxidase (LP), which is a high-value minor whey protein, has recently drawn extensive attention from research scientists and industry due to its multi-function and potential therapeutic applications. In this study, the separation and optimization of two similar-sized proteins, LP and lactoferrin (LF) were investigated using strong cation exchange column chromatography. Optimization was started with central composite design based experiments to characterize the importance of different decision variables. The three variables used in the optimization were flow rate, length of gradient and final salt concentration in the linear elution gradient step. The obtained empiric functional model represented the effect of the significant factors on the yield as the objective function. Afterwards, the calibrated mechanistic model was employed to predict accurate optimal set of variables. The optimal operating points were found and the results were compared with validation experiments. Predictions respecting yield confirmed a very good agreement with experimental results while keeping purity, a product quality characteristic, equal or above to a predefined value.

This study assesses the pursued impacts of Tulsi value chain development intervention on the livelihoods of rural poor in Uttarakhand state of India. Tulsi as an alternative livelihood, particularly for the rural poor, is less explored. With increased crop depredation of major cereal crops grown in the district by wild animals and pests, and decreasing availability of water agriculture, attempts were made to improve earnings from Tulsi as an alternative livelihood. Findings suggest that the average households’ gross profit from Tulsi farming increases by more than double within a span of two years. Total crop income of beneficiary farmers’ increases by 0.8 percent for every 1 percent increase in Tulsi income. Intervention helped enhance productivity of Tulsi, thereby enhancing earnings from Tulsi farming. Most importantly, intervention has shown a tremendous adoption rate. Towards the end of the intervention, the value chain work was out-scaled to another 19 villages in Chamoli district, thereby reaching out to more than 400 households.

MicroRNA (miRNA) is small non-coding RNAs that play vital roles in post-transcriptional gene regulation by inhibiting mRNA translation or promoting mRNA degradation. Dysregulation of miRNA has been implicated in numerous human diseases, including cancers. The family members of miR-34 (miR-34s), composed of miR-34a, miR-34b, and miR-34c, have emerged as the most extensively studied tumor-suppressive miRNAs. In this comprehensive review, we aim to provide an overview of the major signaling pathways and gene networks regulated by the miR-34s in various cancers and highlight the critical tumor suppressor role of miR-34s. Furthermore, we will discuss the potential of using miR-34 mimics as a novel therapeutic approach against cancer, while also addressing the challenges associated with their development and delivery. It is anticipated that gaining a deeper understanding of the functions and mechanisms of miR-34s in cancer will greatly contribute to the development of effective miR-34-based cancer therapeutics.

One of the solutions of the Einstein equations, called McVittie solution, signifying a black hole embedded by the dynamic spacetime is studied. In the stationary spacetime the Mcvittie metric becomes the Schwarzschild-de Sitter metric (SdS). The geodesic of a freely falling test particle towards the black hole is examined in the SdS spacetime. It is found that unlike Schwarzschild case the potential of such particle becomes maximum at a point where it eventually stops to follow an unstable circular motion and then resumes its motion towards black hole center. It is shown that an observer or system of particles is spaghettified near the black hole singularity in the SdS spacetime. The dynamic of the universe in the framework of McVittie metric, being a generalized time dependent SdS solution, is represented in terms of that point, called stationary or turning point. The motion of the stationary point is studied in various regimes of the expanding universe and the possible outcomes are discussed in brief.

Women of color (WoC) in the health professions encounter challenges in advancement to higher positions, disparities in wages, discrimination, lack of expectation to achieve leadership positions, and absence of extensive support networks. Articles in the literature have addressed race and/or gender in the context of professional development. However, applying an intersectionality lens or framework to better understand the contextual issues of professional development for WoC remains to be addressed. Thus, this scoping review aimed to (i) identify health professions literature that addresses disparities affecting WoC, and (ii) describe strategies and approaches to support WoC in the health professions. Methods: Literature searches were conducted in multiple databases. Three independent reviewers reviewed and screened articles for inclusion. Results: 31 articles were included - medicine(17), nursing(1), pharmacy(7), other(4), and multiple health professions(2). Key findings included underrepresentation of women and minority groups, inequities in professional advancement and leadership positions for WoC, and greater dissatisfaction and attrition among minority and women professionals. Conclusion: WoC face unique and distinct challenges and barriers in their professional careers resulting from the intersectionality of not only race and gender, but also lived experiences and opportunities. Strategies to improve diversity and representation should include an intersectionality framework or lens and be critically evaluated.

The Bacillus Calmette-Guerin vaccine (BCG vaccine) designed to prevent tuberculosis in children has been shown to induce a trained immune response in the body to fight against bacteria as well as other parasites and viruses. This knowledge has been reciprocated to generate the idea that this vaccine can also offer protection against severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). Some recent pre-print articles have highlighted that countries with mass BCG immunizations seems to have a lower incidence of coronavirus disease 2019 (COVID-19) compared to those without BCG immunization. There are yet no experimental proof of any such association and the world health organisation (WHO) is currently testing the theory with clinical trials on selected cohorts. Epidemiologists and other scientific experts has expressed both their hope and concern simultaneously regarding the success theory of BCG vaccination to prevent COVID-19. Though its still not verified in any way whether the BCG vaccination can actually prevent COVID-19 or not but we believe a thorough analytical research in this regard is indeed worth a shot.

Monsoon winds drive upwelling along the eastern coast of India during the south-west (SW) monsoons. These winds also provide alongshore windstress (AWS) resulting in positive cross-shore Ekman transport (ET) from late May to the end of September. While instances of high ET and sea surface temperature (SST) based upwelling index (UI_SST) were observed along different parts of the coast, UI_SST was weaker in the northern section in the earlier part of monsoon. This was even in the presence of maximum AWS and ET during the 10 years analysis period spanning January-2009 to December-2018. Additionally, negative sea surface height anomalies (SSHAs), typically associated with coastal upwelling, were observed only along the southern-most coast. An empirical orthogonal function (EOF) analysis revealed two coherent modes of SSHA variation. The first principal component (PC) showed a SSHA signature coincident spatio-temporally with the first downwelling Kelvin wave, closely associated with the equatorial zonal winds that drive coastal Kelvin waves. The third PC with a coastal SSHA pattern similar to the second upwelling Kelvin wave was associated with offshore ET along the northern part of the Indian east coast. Time series of the two PCs exhibited suppression of coastal upwelling by downwelling Kelvin waves during May-July along the northeastern coast of India. Local AWS driven ET was the primary driver of coastal upwelling with the weakening of the remotely forced Kelvin waves in August. A coherent mode consisting of negative coastal SSHA signature was excited in response to local AWS driven ET during the upwelling period. This study examined the spatio-temporal variability of SW monsoon coastal upwelling along the east coast of India and illustrated the role of equatorial windstress forced first downwelling Kelvin wave in suppressing upwelling in the northern part of the coast during early SW monsoon season.

A Cu₂ZnSnS₄ (CZTS) film with a thickness of approximately 1.5 μm was fabricated on a Mo-coated glass substrate by annealing a CZTS precursor fabricated from nanoparticle ink. The chemical states of the elements in the CZTS thin film in the depth direction were studied to identify the presence of secondary phases, which are detrimental to the performance of solar cells containing CZTS. X-ray diffraction was unable to detect any secondary phases in CZTS because of their small relative amount. Instead, X-ray photoelectron spectroscopy (XPS), which is highly sensitive to chemical state, was conducted at different depths in the CZTS film to further check the presence of secondary phases. XPS analysis revealed peaks shift consistent with the presence of secondary phases. For the CZTS film annealed in a S atmosphere at 575 °C for 3 h, the film surface consisted of a secondary-phase layer composed of CuS, ZnS, and SnSx (x=1 or 2) originating from the decomposition of CZTS. At depths below 80 nm, the film was pure CZTS. Formation of MoS2 at the CZTS–Mo interface was confirmed by XPS analysis of Mo and S.

Integrated crop-livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no-tillage (NT) with ryegrass as cover crop (C) and silage (S) were investigated. The soil micromorphological properties of the soil were analyzed using X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8×103), volume (c. 26%), and number of pores (c. 32%) in a rod-like shape. On the other hand, the MT(S), NT(C), and NT(S) systems showed higher tortuosities (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivities (c. 8.3×103, c. 6.9×103, and c. 6.2×103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.

A commercially reared domesticated turkey (Meleagris gallopavo) was purchased from a local market and sections of tissue representing leg, thigh, and breast were harvested and processed for analysis of the lipids and proteins present. Leg and thigh tissue was enriched in mitochondrial proteins whereas the breast tissue was enriched in glycolytic enzymes as well as the cytosolic and mitochondrial forms of glycerol-3-phosphate dehydrogenase. A potential marker for breast tissue muscle formation and/or function was also identified. The tissues could clearly be separated based upon their lipid profiles with little differences in cardiolipin levels suggesting that mitochondrial surface areas may be similar across the tissues. The most significant differences in the lipids were found to be higher levels of oxidized lipids in thigh meat. This work provides the first untargeted proteome and lipidome datasets for the domesticated turkey. The proteome dataset is accessible from ProteomeXchange Consortium via the PRIDE partner repository with the identifier PXD008207.

Monsoon winds drive upwelling along the eastern coast of India during the south-west (SW) monsoons. These winds also provide alongshore windstress (AWS) resulting in positive cross-shore Ekman transport (ET) from March to the end of September. While instances of high ET and sea surface temperature based upwelling index (UI_SST) were observed along two parts of the coast: between Kashinagara and Kakinada in the north, and between Kavali and Point Calimere in the south. The UI_SST illustrated a much poorer agreement with local ET in the northern section, where the onset of UI_SST preceded the rise of ET and the subsidence of UI_SST signals occurred during a period of rising ET. Additionally, negative sea surface height anomalies (SSHAs), typically associated with coastal upwelling, were also missing through most of the upwelling period. A complex empirical orthogonal function (CEOF) analysis revealed two coherent modes of SSHA variation. The first mode showed a SSHA signature spatio-temporally coincident with the first upwelling and downwelling Kelvin waves closely associated with the equatorial zonal winds that drive them. The second CEOF mode, with a coastal SSHA pattern similar to the SSHA signatures of coastal upwelling, was associated with local offshore ET along the Indian east coast. The CEOF analysis exhibited the triggering of coastal upwelling in April and its suppression from June by coastally trapped Kelvin waves along the northeastern coast of India, while local AWS driven ET was the primary driver of coastal upwelling along the southeastern coast. The second CEOF mode also exhibited a coherent negative coastal SSHA signature excited by local AWS driven ET during the upwelling period. This study examined the spatio-temporal variability of premonsoon and SW monsoon coastal upwelling along the western Bay of Bengal and its relation to remotely forced coastal Kelvin waves.

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

A lack of data reproducibility (“reproducibility crisis”) is debated across many scientific and medical disciplines. A systematic analysis of the available evidence on the reliability of scientific data revealed that, although the existence of a reproducibility crisis is widely perceived, conclusive data on the scale of the problem are lacking. Most importantly we found that, although the debate is largely focused on methodological issues, researcher conduct defines research standards and in turn data reliability. The availability of reliable methods itself does not guarantee good practice. Moreover, research is typically characterised by a lack of established methods due to its immanent novelty. Despite the crucial importance of researcher conduct, research and conclusive data on the determinants of researcher behaviour are missing. In conclusion, meta-research is urgently needed that establishes an understanding of the factors that determine researcher behaviour. This knowledge can then be used to implement and iteratively improve measures, which incentivise researchers to apply the highest standards resulting in high quality data.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

We obtain exact solutions to the field equations for 5 dimensional LRS Bianchi type-I spacetime in $f(R,T)$ theory of gravity where specifically the following three cases are considered: (i) $f(R,T)=\mu(R+T)$, (ii) $f(R,T)=R \mu + R T \mu^2$ and (iii) $f(R,T)=R+\mu R^2+\mu T$ where $R$ and $T$ respectively the Ricci scalar and trace of the energy-momentum tensor. It is found that the equation of state (EOS) parameter $w$ is governed by the parameter $\mu$ involved in the $f(R,T)$ expressions. We fine-tune the parameter $\mu$ to obtain effect of phantom energy in the model, however we also restrict this parameter to obtain a stable model of the universe. It is noted that the model isotropizes at finite cosmic time.

Samarinda’s flooding issue is threatening future city development. As the most populated city in Kalimantan, Samarinda (the municipality of East Borneo) plays a role-model in disaster management for a neighboring city. This paper introduces current flood disaster handling in this city. History of disaster management in Indonesia is started from the earlier of Indonesian independence. Year 2008, after hit by severe Tsunami in Aceh and its surrounding, Government of Republic of Indonesia form special agency to manage disaster specifically, namely National Board for Disaster Management (in Bahasa called: Badan Penanggulangan Bencana Nasional [BNPB]) and follows by the regional and local government to form similar agency in provincial and local scale (including Samarinda), called Regional Board for Disaster Management (in Bahasa: Badan Penanggulangan Bencana Daerah[BPBD]) which is formed in 2009 and 2011, respectively. The aim of this paper is to explain flood management in Samarinda where is flood hazard increase gradually and need to be a priority. Descriptive analysis is used in this study including secondary data and interviewed stakeholders. Finally, the finding of study obtains found five constraints related to Samarinda’s flood management including administrative and policy, social, economic, environment and technical and knowledge constraint. This study also promotes several schemes of non-structural approach to enlarge alternative perspective in flood management.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project dedicated to global studies of extremely extended cosmic-ray phenomena, the cosmic-ray ensembles (CRE), beyond the capabilities of existing detectors and observatories. Up to date cosmic-ray research has been focused on detecting single air showers, while the search for ensembles of cosmic-rays, which may overspread a significant fraction of the Earth, is a scientific terra incognita. Instead of developing and commissioning a completely new global detector infrastructure, CREDO proposes approaching the global cosmic-ray analysis objectives with all types of available detectors, from professional to pocket size, merged into a worldwide network. With such a network it is possible to search for evidences of correlated cosmic-ray ensembles. One of the observables that can be investigated in CREDO is a number of spatially isolated events collected in a small time window which could shed light on fundamental physics issues. The CREDO mission and strategy requires active engagement of a large number of participants, also non-experts, who will contribute to the project by using common electronic devices (e.g. smartphones). In this note the status and perspectives of the project is presented.

Since the first reported case of COVID-19 in December 2019, several SARS-CoV-2 variants has evolved and some of them have shown higher transmissibility becoming the prevalent strains. Genomic epidemiological investigations into strains from different time points including the early stages of the pandemic are very crucial for understanding the evolution and transmission patterns. Using whole genome sequences, our study describes the early landscape of SARS-CoV-2 variants in central India retrospectively (including the first known occurrence of SARS-CoV-2 in Madhya Pradesh). We performed amplicon based whole genome sequencing of randomly selected SARS-CoV-2 isolates (n=38) collected between 2020-2022 at state level VRDL, ICMR-NIRTH, Jabalpur from 11899 RT-qPCR positive samples. We observed the presence of five lineages namely B.1, B.1.1, B.1.36.8, B.1.195 and B.6 in 19 genomes from the first wave cases and variants of concern (VOC) lineages i.e. B.1.617.2 (Delta), and BA.2.10 (Omicron) in the second wave cases. There was a shift in mutational pattern of SRAS-CoV-2 strains from the second wave in contrast to the first wave. We have identified five immune escape variants in the S gene: P681R, P681H, L452R, Q57H, and N501Y in the isolates collected during the second wave. Furthermore, these genomes were compared with 2160 complete genome sequences reported from central India that encompass 109 different SARS-CoV-2 lineages. Among them, VOC lineages Delta (28.93%), and Omicron (56.11%) were circulating predominantly in this region. This study provides useful insights into the genetic diversity of SARS-CoV-2 strains over the initial course of the COVID-19 pandemic in central India.

Several studies have shown that changes in incoming solar radiation and variations of the diffuse fraction can significantly modify the vegetation carbon uptake. Hence, monitoring the incoming solar radiation at large scale and with high temporal frequency is crucial for this reason along with many others. The EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA SAF) operationally disseminates in near real time estimates of the downwelling shortwave radiation at the surface since 2005. This product is derived from observations provided by the SEVIRI instrument onboard the Meteosat Second Generation series of geostationary satellites, which covers Europe, Africa, the Middle East, and part of South America. However, near real time generation of the diffuse fraction at the surface level has only recently been initiated. The main difficulty towards achieving this goal was the general lack of accurate information on the aerosol particles in the atmosphere. This limitation is nowadays less important thanks to the improvements in atmospheric numerical models. This study presents an upgrade of the LSA-SAF operational retrieval method, which provides the simultaneous estimation of the incoming solar radiation and its diffuse fraction from satellite every 15 minutes. The upgrade includes a comprehensive representation of the influence of aerosols based on physical approximations of the radiative transfer within an atmosphere-surface associated medium. This article explains the retrieval method, discusses its limitations and differences with the previous method, and details the characteristics of the output products. A companion article will focus on the evaluation of the products against independent measurements of solar radiation. Finally, the access to the source code is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable.

In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of oper-ating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which, then, emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only rec-ords the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innova-tion lies in the combination of electron beam projection, CMOS imager scintillation-based de-tection and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device's utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe's per-formance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.

We investigate the behavior of the solutions of the ray equation in isotropic media. We discuss local and global transversals and wavefronts and give examples of rays without wavefronts.

The Cosmic Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic ray ensembles (CRE): groups of a minimum of two CR with a common primary interaction vertex or the same parent particle. The CREDO program embraces testing known CR and CRE scenarios, and preparing to observe unexpected physics, it is also suitable for multi-messenger and multi-mission applications. Perfectly matched to CREDO capabilities, CRE could be formed both within classical models (e.g. as products of photon-photon interactions), and exotic scenarios (e.g. as results of decay of Super Heavy Dark Matter particles), their fronts might be significantly extended in space and time, and they might include cosmic rays of energies spanning the whole cosmic ray energy spectrum. CRE are expected to be partially observable on Earth even if the initiating interaction or process occurs as far as ~1 Gpc away. They would have a footprint composed of at least two extensive air showers with correlated arrival directions and arrival times. Since CRE are mostly expected to be spread over large areas and, because of the expected wide energy range of the contributing particles, CRE detection might only be feasible when using available cosmic ray infrastructure collectively, i.e. as a globally extended network of detectors. Thus, with this review article, the CREDO Collaboration invites the astroparticle physics community to actively join or to contribute to the research dedicated to CRE, and in particular to share any cosmic ray data useful for the specific CRE detection strategies.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

Pancreatic cancer (PC) is one of the most lethal forms of cancers with 5-year mean survival rate of less than 10%. Most of the PC associated deaths are due to metastasis to secondary sites. Calcium (Ca²⁺) signaling plays a critical role in regulating hallmarks of cancer progression including cell proliferation, migration and apoptotic resistance. Store operated Ca²⁺ entry (SOCE) mediated by Orai1/2/3 channels is a highly regulated and ubiquitous pathway responsible for Ca²⁺ influx into non-excitable cells. In this study, we performed extensive bioinformatic analysis of publicly available datasets and observed that Orai3 expression is inversely associated with the mean survival time of PC patients. Orai3 expression analysis in a battery of PC cell lines corroborated its differential expression profile. We then carried out thorough Ca²⁺ imaging experiments in 6 PC cell lines and found that Orai3 forms a functional SOCE in PC cells. Our in vitro functional assays show that Orai3 regulates PC cell cycle progression, apoptosis and migration. Most importantly, our in vivo xenograft studies demonstrate a critical role of Orai3 in PC tumor growth and secondary metastasis. Mechanistically, Orai3 controls G₁ phase progression, matrix metalloproteinase expression and epithelial-mesenchymal transition in PC cells. Taken together, this study for the first time reports that Orai3 drives aggressive phenotypes of PC cells i.e. migration in vitro and metastasis in vivo. Considering that Orai3 expression is inversely associated with the PC patients survival time, it appears to be a highly attractive therapeutic target.

Long COVID, also referred to as post-COVID-19 condition, describes the lingering after-effects of COVID-19 infection. This complex syndrome encompasses a range of symptoms affecting physical well-being, cognitive function, and mental health. The widespread impact of long COVID extends beyond individual sufferers, placing significant strain on healthcare systems and causing far-reaching socioeconomic consequences. The scale of this multifaceted health crisis is unparalleled in recent history, affecting millions globally and challenging our understanding of post-viral conditions. This study aimed to explore the possibility of targeting G protein-coupled receptors (GPCRs) signaling pathway-related genes as therapeutics for long COVID using computational analysis. Targeting GPCRs and their signaling pathways holds significant promise for long COVID therapeutics, as these receptors are involved in crucial physiological processes including immune regulation, inflammation control, and neurotransmission. All of these are implicated in the diverse and persistent symptoms of long COVID, potentially offering a versatile approach to addressing multiple aspects of the condition simultaneously. This study identified 21 genes associated with GPCRs for further exploration as potential targets. Notably, GPCR genes such as HRAS, KRAS, GNAQ, and GNA11 were determined to be possible therapeutic targets for the pathophysiological mechanisms of long COVID. FDA-approved drugs targeting these genes were identified, including Binimetinib, Cabozantinib, Selumetinib, Panitumumab, Cetuximab, Adagrasib, Tipifarnib, and Sotorasib. Additionally, Naltrexone and Tipifarnib have emerged as potential new treatment options for long COVID. SARS-CoV-2 may hijack GPCR signaling pathways to dysregulate lung ion and fluid transport, contributing to the pathophysiology of pulmonary edema in patients with COVID-19. Further research is required to translate the findings into the development of therapeutics and to investigate the relationship between viral infection and GPCR signalling.

High frequency knowledge of the spatio-temporal distribution of the Downwelling Surface Shortwave Flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface-atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The EUMETSAT Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (Downwelling Surface Short-wave radiation Fluxes – Total and Diffuse fraction) product with an operational status since the year 2019. The method for the retrieval was presented in the companion paper [40]. The part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents the comparison of the corresponding outputs, i.e. total DSSF and diffuse fraction (fd) components, against in-situ measurements acquired at four BSRN stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20Wm^-2 for DSSF<200Wm^-2, and 10% for DSSF>=200Wm^-2. The MBE and rMBE compared to the ground measurements are 3.618Wm^-2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd<0.5, and 20% for fd>=0.5. The MBE and rMBE compared to the ground measurements are -0.044 and -17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud-aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the Aerosol Optical Depth (AOD) forecasts currently available is enough accurate to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.

With the development of sensor and communication technologies, Internet of Things (IoT) subsystem is gradually becoming a crucial part in vehicles. It can effectively enhance functionalities of vehicles. However, new attack types are also emerged. For example, a driver with the smart key in the pocket can push the start button to start a car when. At the same time, security issues in the push-to-start scenario are alerted, such as smart key forgery. In this paper, we propose a vehicle Passive Entry Passive Start (PEPS) system that uses deep learning algorithms to recognize the driver by the Electrocardiogram (ECG) signals measured by his or her smart watch. ECG signals are used for verification. Smart watches, as a new smart key of PEPS system, can replace traditional smart keys to improve security. Experiment results show that Long Short-Term Memory (LSTM) models have achieved the best accuracy score for identity recognition (91%) when single ECG cycle is used. However, it takes at least 30 minutes for training. The training time of Auto Encoder successfully reduces to 5 minutes. When 15 continuous ECG cycles are used, it can achieve 100% identity accuracy.

The present article describes the synthesis of an isonicotinate-derived meso-arylporphyrin, that has been fully characterized by spectroscopic methods (including fluorescence spectroscopy), as well as by elemental analysis and by HR-MS. The structure of a n-hexane monosolvate has been determined by single crystal X-ray diffraction analysis. The radical scavenging activity of this new porphyrin against the 2,2-diphenyl-1-picrylhydrazyl (DDPH) radical has been measured. Its antifungal activity against three yeast strains (C. albicans ATCC 90028, C. glabrata ATCC 64677 and C. tropicalis ATCC 64677) has been tested, using the disk diffusion and the microdilution methods. Whereas the measured antioxidant activity was low, the porphyrin showed moderate but encouraging antifungal activity. Finally, a study of its effect on the germination of lentil seeds revealed interesting allelopathic properties.

Traditional photodynamic therapy (PDT) is often limited in its efficacy by insufficient light penetration, inefficient photosensitizer energy transfer, and inadequate target tissue oxygenation. X-ray activated PDT (XPDT), using nanoparticle (NPs) photosensitizers comprised of europium-doped yttrium oxide cores encased within silica shells (Y₂O₃:Eu@SiO₂), offers the potential of overcoming most of these limitations. Aimed at maximizing the generation of reactive oxygen species (ROS), this study reports methodologies for investigation of the effects of synthesis conditions on the characteristics of Y₂O₃:Eu@SiO₂ NP. Transmission electronic microscope (TEM) revealed that the NP core diameter was linearly, positively correlated with condensation time (R2 = 0.7357, p < 0.05) and linearly, negatively correlated with urea concentration (R2 = 0.958, p < 0.05). The addition of cetyltrimethylammonium bromide (CTAB) during core synthesis demonstrated enhanced particle dispersion. Silica coating via APTES-1 and TEOS-3 conditions resulted in Y₂O₃:Eu@SiO₂ NPs that generated the highest ROS, with 8.7-fold and 8.9-fold increase respectively in relative fluorescence intensity at 8 Gy irradiation compared to a 5.2-fold increase in PBS under the same condition. In vivo evaluation using 18F-fluorothymidine positron emission tomography (18F-FLT PET) of mouse xenografts of a human prototypical cancer (ovarian) revealed a 55% reduction in tumor proliferation of radiation-sensitive CAOV3 tumors treated with Y₂O₃:Eu@SiO₂ NPs compared to a 19% reduction in tumor proliferation of radiation-resistant SKOV3 tumors on the fourth day post-treatment. Taken together, these findings suggest Y₂O₃:Eu@SiO₂ NPs can serve as effective photosensitizers for XPDT and their performance characteristics can be optimized by selecting synthesis conditions and parameters to deliver the desirable therapeutic effects, offering novel approaches to circumventing many of the limitations of conventional PDT in the treatment of cancer.

As the demand of heating and air conditioning is increasing day by day due to getting a comfortable life, for that reason, the market for heat pump and air conditioning systems or both, is seeing a steady increase in low global warming potential. All researchers on heat pump and air conditioning systems are searching for environmentally friendly refrigerants. However, a significant number of contemporary refrigerants (HCFCs) have the potential to cause global warming and ozone depletion, such as those found in heat pump air conditioning systems. Using more environmentally friendly refrigerants, including hydrocarbon and blend refrigerant mixtures, is one way to lower GWP and Ozone depletion potential. This study examines the performance of several alternative refrigerants, including R32, R134A, R410A, R22, and R290. In order to examine the performance of R290, theoretical and simulation results are compared on various refrigerants while taking into account a number of performance parameters, including the refrigerant energy efficiency ratio, mass flow rate, coefficient of performance, cooling capacity, and compressor work for one ton of refrigeration (1TR) air conditioners. One player with a very low GWP is R290. However, the only drawback is that it can catch fire and is hazardous to use in split-type commercial heat pump air conditioning applications. The environmental and thermo physical properties of HC-290 are significantly better than those of other materials, according to theoretical and simulation studies utilizing Cool Pack software, hence it is a viable replacement.

The prediction of an extremely severe cyclonic storm (ESCS) is one of the challenging issues due to increasing intensity and its life period. In this study, an ESCS Fani that developed over Bay of Bengal region during 27 April - 4May, 2019 and made landfall over Odisha coast of India is investigated to forecast the storm track, intensity and structure. Two numerical experiments (changing two air-sea flux parameterization schemes; namely FLUX-1 and FLUX-2) are conducted with the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) model by using a moving nest with fine horizontal resolution about 3 km. The high resolution (25 km) NCEP operational Global Forecast System (GFS) analysis and forecast datasets are used to derive the initial and boundary conditions, the ARW model initialized at 00 UTC 29 April 2019 and forecasted for 108 hours. The forecasted track and intensity of Fani is validated with available India Meteorological Department (IMD) best-fit track datasets. Result shows that the track, landfall (position and time) and intensity in terms of minimum sea level pressure (MSLP) and maximum surface wind (MSW) of the storm is well predicted in the moving nested domain of the WRF model using FLUX-1 experiment. The track forecast errors on day-1 to day-4 are ~ 47 km, 123 km, 96 km, and 27 km in FLUX-1 and ~54 km, 142 km, 152 km and 166 km in Flux-2 respectively. The intensity is better predicted in FLUX-1 during the first 60 h followed by FLUX -2 for the remaining period. The structure in terms of relative humidity, water vapor, maximum reflectivity and temperature anomaly of the storm is also discussed and compared with available satellite and Doppler Weather Radar observations.

The detection performance of small objects in remote sensing images has not been satisfactory compared to large objects, especially in low-resolution and noisy images. A generative adversarial network (GAN)-based model called enhanced super-resolution GAN (ESRGAN) showed remarkable image enhancement performance, but reconstructed images usually miss high-frequency edge information. Therefore, object detection performance showed degradation for small objects on recovered noisy and low-resolution remote sensing images. Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we applied a new edge-enhanced super-resolution GAN (EESRGAN) to improve the quality of remote sensing images and used different detector networks in an end-to-end manner where detector loss was backpropagated into the EESRGAN to improve the detection performance. We proposed an architecture with three components: ESRGAN, EEN, and Detection network. We used residual-in-residual dense blocks (RRDB) for both the ESRGAN and EEN, and for the detector network, we used a faster region-based convolutional network (FRCNN) (two-stage detector) and a single-shot multibox detector (SSD) (one stage detector). Extensive experiments on a public (car overhead with context) dataset and another self-assembled (oil and gas storage tank) satellite dataset showed superior performance of our method compared to the standalone state-of-the-art object detectors.

As the outbreak of coronavirus disease 2019 (COVID-19) is continuously increasing in India, so epidemiological modeling of COVID-19 data is urgently required for administrative strategies. Time series and is capable to predict future observations by modeling the data based on past and present data. Here, we have modeled the epidemiological COVID-19 Indian data using various models. Based on the collected COVID-19 outbreak data, we try to find the propagation rule of this outbreak disease and predict the outbreak situations in India. For India data, the time series model gives the best results in the form of predication as compared to other models for all variables of COVID-19. For new cases, new deaths, total cases and total deaths, the best fitted ARIMA models are as follows: ARIMA(0,2,3), ARIMA(0,1,1), ARIMA(0,2,0) and ARIMA(0,2,1). Based on time series analysis, we predict all variables for next month and conclude that the predictive value of Indian COVID-19 data of total cases is more than 20 lakhs with more than 43 thousand total deaths. The present chapter recommended that a comparison between various predictive models provide the accurate and better forecast value of the COVID-19 outbreak for all study variables.

The livelihood of most of the fishers in Indian Sundarbans is dependent on Penaeus monodon post larvae fishing. These post larvae collectors are socially backward lacking economic security. The activity of collecting Penaeus monodon post larvae for rearing in aquaculture, destroy other aquatic species. Many other juveniles of shellfish and fin fish were destroyed in the process of collection of Penaeus monodon post larvae. The removal of juveniles before they reach maturity disturbs the ecological chain by hampering breeding processes and may cause extinction of some fish species in the long run. The present study is an attempt to estimate the economic value of juveniles destroyed in the collection of (Penaeus monodon) post larvae. In total 32 species were identified in P.monodon the post larval by-catch. The economic loss is assessed based on estimating biomass by taking a length-weight relationship from published literature. Further, the paper illustrates how does a profit enterprise is linked with natural resource exploitation. The paper explores government policy and nature conservation issues for social justice and effective conservation.In conclusion, suggestions are given to reduce the burden of livelihood on natural resources to the extent of exploitation and to strengthen institution and policy-making considering socio-ecological vulnerabilities of the area.

To utilize heterosis and combining ability for grain yield and its attributing traits along with three physiological traits viz., leaf area index, chlorophyll fluorescence and chlorophyll content in bread wheat (Tritium aestivum L.) the crosses were attempted during rabi, 2019-20 in a half diallel mating scheme among 8 wheat varieties and the study was carried out during rabi, 2020-21 at Block No. D-13 field of Mahua block, Simradha research farm, Rani Lakshmi Bai Central Agricultural University, Jhansi. Analysis of variance showed significant differences for treatments. Based on per se performance the hybrids NW 5054 x PBW 723 (23.3 g), and HI 1544 x NIAW 34 (23.14 g), were identified for the higher grain yield. The hybrid HI 544 x NIAW 34 (18.41 %) was identified as the best heterotic cross for grain yield per plant and its component traits. The hybrids HI 1544 x NIAW 34 (3.40) and HI 1544 x GW 322 (2.76), as well as the parents HD 3086 (21.85) and PBW 723 (20.68), were identified as superior economic hybrids and parents based on SCA/GCA effects, per se performance for grain yield per plant, and its component trait in bread wheat. Days to heading, flag leaf length, biological yield per plant, harvest index, number of grains per spike, 1000 grain weight, spike length, leaf area index, chlorophyll fluorescence, and chlorophyll content were all positively correlated with grain yield per plant.

Communicating about sex is important in generating positive perceptions about one’s sexual and romantic life. The last decade has provided insight into the theoretical applications on sex communication research. While the focus on extant research focuses on the psychological processes’ individuals employ to talk about sex, no theoretical framework exists that identifies key constructs that provides a parsimonious understanding about the communicative processes of sex and sexuality. This review sought to identified key constructs that are suitable to develop a sex talk theory. In the current project, we reviewed 24 studies including 8,698 participants (Mage = 24.98) that applied a theoretical framework to sex research. This review identified three salient constructs (e.g., disclosure, cognitive, and relational and behavioral) that are important for a sex talk theory. Last, this review indicated that scholarship should explain the relationships between the key constructs. We provided several recommendations that scholars should take when developing a theory in sex communication research.

The stellar winds of the central stars of planetary nebulae play an essential role in planetary nebulae shaping. In the interacting stellar winds model, the fast stellar wind injects energy and momentum which are transfered to the nebular envelope through an X-ray-emitting hot bubble. Together with other physical processes, such as the ionization of the nebular envelope, the asymmetrical mass-loss in the AGB, and the action of collimated outflows and magnetic fields, the presurized hot gas determines the expansion and evolution of planetary nebulae. \emph{Chandra} and \emph{XMM-Newton} have provided us with detailed information of this hot gas. Here in this talk I will review our current understanding of the effects of the fast stellar wind in the shaping and evolution of planetary nebulae and give some hints of the promissing future of this research.

Oxidative stress (OS) occurs from excessive reactive oxygen species or a deficiency of antioxidants – primarily endogenous glutathione (GSH). There are many illnesses, from acute and post-COVID-19, diabetes, myocardial infarction, to Alzheimer’s disease, that are associated with OS. These dissimilar illnesses are in order, a viral infection, a metabolic disorder, an ischemic event, and a neurodegenerative disorder. OS may be an early initiator or a significant promotor of their progressive pathophysiologic processes. Consequently, addressing initial OS-related pathology may avoid subsequent severe and irreversible complications. Early intervention would modulate multiple factors, including cytokine stimulation, complement dysregulation, immuno-thrombosis, fibrosis, and autoimmunity. Past clinical studies that addressed OS have had equivocal results. It may be due to the use of ineffective antioxidants, an untimely delay in their use, or an inefficient delivery system. Experimental studies have used antioxidants that are not available for clinical trials. Although GSH can significantly reduce OS, its exogenous use is hampered by the lack of an effective delivery system. By incorporating GSH into cyclodextrin (CD) through nanotechnology, there is recent evidence that exogenous GSH can be delivered more effectively to prevent or mitigate injury from OS [1]. Future studies using the GSH/cyclodextrin (GC) complex will be needed to confirm its effectiveness and, hopefully, offer a path to treat many sub-optimally managed or currently untreatable illnesses.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at &lt; .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p &lt; .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p &lt; .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

This manuscript reviews three case studies from Brazil, Panama, and Portugal that illustrate Nature-based Solutions. The Tijuca Forest in Rio de Janeiro is a remarkable story of centuries of forest management that today is recognized as a UNESCO World Heritage Site. The Panama Canal Watershed produces water for Canal operations, electricity generation, and drinking water for half the country´s population. Traditional windmills and weirs near streams in the Alentejo Region, Portugal, have largely been abandoned due to the damming of the Guadiana River. Yet today, weirs are increasingly recognized for their important contribution to water provisioning in this dry region. All have a primary goal related to water provisioning, yet their ecosystem benefits are multiple. The cases offer important lessons for adaptation to climate change, cultural benefits from traditional human activities, and concerns about social equity.