To assist firefighters and other first responders to use their existing equipment for respiration during the COVID-19 pandemic without using single-use, low-supply, masks, this study outlines an open source kit to convert a 3M-manufactured Scott Safety self-contained breathing apparatus (SCBA) into a powered air-purifying particulate respirator (PAPR). The open source PAPR can be fabricated with a low-cost 3-D printer and widely available components for less than $150, replacing commercial conversion kits saving 85% or full-fledged proprietary PAPRs saving over 90%. The parametric designs allow for adaptation to other core components and can be custom fit specifically to fire-fighter equipment, including their suspenders. The open source PAPR has controllable air flow and its design enables breathing even if the fan is disconnected or if the battery dies. The open source PAPR was tested for air flow as a function of battery life and was found to meet NIOSH air flow requirements for 4 hours, which is 300% over expected regular use.

This study provides designs for a low-cost, easily replicable open source lab-grade digital scale that can be used as a precision balance. The design is such that it can be manufactured for use in most labs throughout the world with open source RepRap-class material extrusion-based 3-D printers for the mechanical components and readily available open source electronics including the Arduino Nano. Several versions of the design were fabricated and tested for precision and accuracy for a range of load cells. The results showed the open source scale was found to be repeatable within 0.1g with multiple load cells, with even better precision (0.01g) depending on load cell range and style. The scale tracks linearly with proprietary lab-grade scales, meeting the performance specified in the load cell data sheets, indicating that it is accurate across the range of the load cell installed. The smallest loadcell tested(100g) offers precision on the order of a commercial digital mass balance. The scale can be produced at significant cost savings compared to scales of comparable range and precision when serial capability is present. The cost savings increase significantly as the range of the scale increases and are particularly well-suited for resource-constrained medical and scientific facilities.

Vacuum drying can dehydrate materials further than dry heat methods while protecting sensitive materials from thermal degradation. Many industries have shifted to vacuum drying as cost- or time-saving measures. Small-scale vacuum drying, however, has been limited by high costs of specialty scientific tools. To make vacuum drying more accessible, this study provides design and performance information for a small-scale open source vacuum oven, which can be fabricated from off-the-shelf and 3-D printed components. The oven is tested for drying speed and effective-ness on both waste plastic polyethylene terephthalate (PET) and a consortium of bacteria developed for bioprocessing of terephthalate wastes to assist in distributed recycling of PET for both additive manufacturing as well as potential food. Both materials can be damaged when exposed to high temperatures, making vacuum drying a desirable solution. The results showed the open source vacuum oven was effective at drying both plastic and biomaterials, drying at a higher rate than a hot-air dryer for small samples or for low volumes of water. The system can be constructed for less than 20% of commercial vacuum dryer costs for several laboratory-scale applications including dehydration of bio-organisms, drying plastic for distributed recycling and additive manufacturing, and chemical processing.

Quantitative dynamic strain measurements of the ground would be useful for engineering scale problems such as monitoring for natural hazards, soil-structure interaction studies and non-invasive site investigation using full waveform inversion (FWI). Distributed Acoustic Sensing (DAS), a promising technology for these purposes, needs to be better understood in terms of its directional sensitivity, spatial position, and amplitude for application to engineering-scale problems. This study investigates whether the physical measurements made using DAS are consistent with the theoretical reception patterns and experimental measurements of ground strain made by geophones. Results show that DAS and geophone measurements are consistent in both phase and amplitude for broadband (10s of Hz), high amplitude (10s of microstrain) and complex wavefields originating from different positions around the array when: (1) the DAS channels and geophone locations are properly aligned, (2) the DAS cable provides good deformation coupling to the internal optical fiber, (3) the cable is coupled to the ground through direct burial and compaction, and (4) laser phase noise is mitigated in the DAS measurements. The theoretical relationship between DAS-measured and point-wise strain for vertical and horizontal active sources is introduced using 3D elastic finite-difference simulations. The implications of using DAS strain measurements are discussed including directionality and magnitude differences between the actual and DAS-measured strain fields. A method for spatially aligning the DAS channels with the geophone locations at tolerances less than the spatial resolution of the DAS system is proposed.

The urban population in developing countries, especially sub-Saharan Africa, is rapidly increas-ing. As towns and cities grow, so does the demand for fish protein. While flow-through aqua-culture can provide fresh, healthy and nutritious fish protein, it is plagued by extensive land re-quirement as well as effluent discharge, thus, unsuitable for city regions. Alternatively, small-scale Recirculating Aquaculture System (RAS) could improve food and nutritional security (FNS), livelihoods as well as reduce environmental degradation in urban areas despite land and water constraints. The question however remains - what are the key technical, business and managerial issues, surrounding small-scale RAS in urban farming? This study reviews the RAS prototype of the Sustainable Aquaponics for Nutritional and Food Security in Urban Sub-Saharan Africa (SANFU) II project based on mass balance and stock density, relevant for fish survival and/or availability as well as net cash-flow analyses. The results suggest that small-scale RAS are technically and financially viable only with family labor having proper aquaculture monitoring and management skills. Furthermore, access to adequate equipment and inputs as well as electricity for the recirculating system are crucial. Urban innovation actors will adopt RAS if operations are profitable given that family labor is employed.

Eliashberg theory provides a theoretical framework for understanding the phenomenon of superconductivity when pairing between two electrons is mediated by phonons, and retardation effects are fully accounted for. However, when a direct Coulomb interaction between two electrons is also present, this interaction is only partially accounted for. In this work we use a well-defined Hamiltonian, the Hubbard-Holstein model, to examine this competition more rigorously, using exact diagonalization on a two-site system. We find that the direct electron-electron repulsion between two electrons has a significantly more harmful effect on pairing than suggested through the standard treatment of this interaction.

Yerba maté, an herbal tea derived from Ilex paraguariensis, has previously been reported to be protective against obesity-related and other cardiometabolic disorders. Using high-resolution respirometry and reverse-phase high-performance liquid chromatography, the effects of four weeks of yerba maté consumption on mitochondrial efficiency and cellular redox status in skeletal muscle, adipose, and liver, tissues highly relevant to whole body metabolism, were explored in healthy adult mice. Yerba maté treatment increased mitochondrial oxygen consumption in adipose, but not in other tissues examined. Yerba maté increased ATP concentration in skeletal muscle and decreased ATP concentration in adipose. Combined with observed changes in oxygen consumption, these data yielded a significantly higher ATP:O2, a measure of mitochondrial efficiency, in muscle and a significantly lower ATP:O2 in adipose, which were consistent with yerba maté-induced weight loss. Yerba maté treatment also altered the hepatic glutathione (GSH)/glutathione disulfide (GSSG) redox potential to a more reduced redox state, suggesting potential protective effects against oxidative stress and preservation of cellular function. Together, these data indicate beneficial, tissue-specific effects of yerba maté supplementation on mitochondrial bioenergetics and redox states in healthy mice that are protective against obesity.

Four methods in two different families have been constructed to derive the exact solutions to Benjamin-Bona-Mahony equation in two space dimensions. Simply defined hyperbolic tangent, hyperbolic secant and hyperbolic cosecant ansatzes and the expansion method based on the Sine-Gordon equation in two dimensions are directly substituted into the governing ODE reduced from the two dimensional BBM equation. Classical algebraic method is used to find the relations among the target parameters representing the nonzero coefficients in the predicted solutions and the wave transform parameters. Some complex and real solutions have been constructed in explicit forms.

Early diagnosis of paroxysmal atrial fibrillation (PAF) could suggest patients to receive timely interventions in clinical practice. Various PAF onset prediction algorithms might benefit from accurate heart rate variability (HRV) analysis and machine learning classification but to be challenged in real-time monitoring scenarios. The aim of this study is to present an end-to-end deep learning based PAFNet model that integrates a sliding window technique on raw R-R interval of electrocardiogram (ECG) segments to achieve a real-time prediction of PAF onsets. This integration enable the deep convolutional neural network (CNN) to be customized as a light-weight architecture that accommodates the size of sliding windows simply by altering the input layer, specifically its effectiveness in making a new prediction with each new heartbeat. Catering to potential influence of input sizes, three CNN models were trained using 50, 100, and 200 R-R intervals, respectively. For each model, the performance of automated algorithms was evaluated for PAF prediction using a ten-fold cross-validation. As a results, a total of 56,381 PAFN-type and 56,900 N-type R-R interval segments was collected from publicly accessible ECG databases, and a promising prediction performance of the automated algorithm with a 100 R-R intervals was achieved in terms of the sensitivity of 97.12%, the specificity of 97.77%, and the accuracy of 97.45%, respectively. Importantly, the automated algorithm with a sliding windows step of 1 could process one sample in only 23.1 milliseconds and identify the onset of PAF at least 45 minutes in advance. The present results suggest that the sliding window technique on raw R-R interval sequences along by deep learning based algorithms may offers the possibility of providing an accurate, real-time, and end-to-end clinical tool for mass monitoring of PAF.

Patients hospitalized with COVID-19 are at a higher risk of thrombotic events following discharge, however the role of extended thromboprophylaxis remains controversial. The purpose of this study is to evaluate current extended post-discharge thromboprophylaxis practice and its outcomes.This study was a single-center, retrospective chart review of patients within Hennepin Healthcare hospitalized with COVID-19 from April 1^st 2020 to December 31^st 2021 with increased risk of thrombotic event based on D-dimer. The primary outcome was to describe current prescribing practices based on the number of patients who were eligible and received anticoagulants on discharge. Secondary outcomes included comparing the patient’s risk for thromboembolism based on a modified International Medical Prevention Registry on Venous Thromboembolism (IMPROVE-VTE) score to the current internal prescribing practice guideline, evaluating efficacy outcomes based on new thromboembolic events, and assessing safety of extended-thromboprophylaxis using the International Society of Thrombosis and Hemostasis criteria for major bleeding within 30 days of hospitalization discharge.Of 1984 patients who were hospitalized with COVID-19 infection, 961 patients were eligible to receive thromboprophylaxis at discharge, with a total of 191 patients who received anticoagulation according to the Hennepin Healthcare practice guideline. However, using the IMPROVE-VTE score, only 206 patients qualified for post-discharge thromboprophylaxis, and 63 total patients received anticoagulation. A new thromboembolic event occurred in 20 patients (5.8%) and 14 patients (4.1%) experienced major bleeding.The Hennepin Healthcare guideline for extended thromboprophylaxis at discharge encompassed more patients compared to the IMPROVE-VTE score. The incidence of a new thromboembolic event and major bleeding were low in both groups, although venous thrombotic events occurred more in thromboprophylaxis group than in patients who did not receive anticoagulation at discharge, more clinical data are needed for a conclusion.

A simple protocol for preparation of O-acylated enol form - (R/S)-ethyl-2-acetoxy-4-phenyl-4H-chromene-3-carboxylate 5 was presented. The compound was characterized by 1H-, 13C-and DEPT135 NMR spectra, including {1H,1H} COSY, {1H,13C} HSQC, {1H,13C} HMBC and 2D-NOESY spectra. The preferred regioselectivity for O-acylation of 3,4-dihydrocoumarin 5 in the presence of substituent in 4-th position in the chroman ring and accounting the steric hindrance of the ester group in 3-th place was confirmed.

A Brewer Spent Grain (BSG), the most abundant by-product of the brewing process, is mainly used in animal feed and biogas production. The aim of the present work is BSG valorization by yeast fermentation to produce carotenoids. R. mucilaginosa CBS316 was cultured on BSG syrups, supplemented or not with YE and PEP (s-Fsa and Fsa). The biomass and carotenoid production were optimized in flasks and then scaled-up in bioreactor. In flask tests, the maximum biomass concentration was 5.3 and 6.2 g/L for Fsa and s-Fsa cultures, respectively. The maximum carotenoid production was 833 μg/L in Fsa and 1159 μg/L in s-FSA. Considering that the highest specific productivity value (P 7.16 μg/g*h) was obtained with Fsa syrup, this medium was selected for the process scale-up. In bioreactor tests, the maximum concentrations of biomass (4.29 g/L) and carotenoid (396 ug/L) was reached at 72 hours of fer-mentation, 24 h later than in flask. The total carotenoid produced was 524 and 150 ug in bioreactor and flask cultures, respectively. The carotenoids production by R. mucilaginosa was obtained both in Fsa and s-Fsa syrups. The results confirm the possibility to use the syrup as it is, Fsa, thus limiting the process costs.

Open-pit uranium mining in the south Texas Gulf Coast region was active during the second half of the 20th century. Although some mines have extensive records documenting the locations and extents with descriptions of reclamation procedures and timelines, abandoned and reclaimed mines with minimal documentation concurrently exist where little is known about locations, mine waste volumes, and reclamation status. Advanced mapping of these mining operations is helpful for producing basic mine land inventories and assessments of mine waste; identifying potential undeveloped resources and environmental health issues; and for developing proper management, restoration, and reclamation strategies. We studied known reclaimed and unreclaimed mine sites to develop a spatiotemporal mapping approach utilizing multiple techniques in remote sensing as a proof of concept. A mapping classification system was developed to identify uranium mine waste-rock piles, mine pits (with and without waste water), the total area of land disturbance due to mining, and to differentiate abandoned and reclaimed mine features using lidar (Light Detection and Ranging) analysis and multispectral temporal analysis. Visual interpretation of Landsat imagery and time-series analysis revealed the temporal life-cycle of mining, historical areas of disturbance, and reclamation; however, mine features below vegetation canopies are not always visible in satellite imagery. Lidar laser scanning penetrates the vegetation canopy to measure the topographic elevation and exposes anthropogenic modifications to the landscape. Lidar analysis (bare earth elevation surface, slope, topographic contours, topographic textures, and overland-flow hydrography) revealed mine features, and expansive areas of mining disturbance. The spatiotemporal mapping approach proved to be useful for identifying and characterizing known mine features, areas of disturbance, and reclamation status. Historical pre-mining topographic data were available at only 4 of the mines for comparison where the cut-and-fill tool estimated 21% less waste-rock volume, indicating that information about pre-mining terrain topography and/or subsurface mine waste geometry is needed to improve accuracies for quantifying buried mine waste volume at reclaimed mine sites.

It has been proven that in standard Einstein gravity, exotic matter (i.e. matter violating the point-wise and averaged weak and null energy conditions) is required to stabilize traversable wormholes. Quantum field theory permits these violations due to the quantum coherent effects found in any quantum field . Even reasonable classical scalar fields violate the energy conditions. In the case of the Casimir effect and squeezed vacuum states, these violations have been experimentally proven. It is advantageous to investigate methods of minimizing the use of exotic matter. One such area of interest is extended theories of Einstein gravity. It has been claimed that in some extended theories, stable traversable wormholes solutions can be found without the use of exotic matter. There are many extended theories of gravity and in this review paper we first explore f(R) theories and then explore some wormhole solutions in f(R) theories including Lovelock gravity.

Colorectal cancer (CRC) poses a significant global health challenge. Notably, the risk of CRC escalates with age, with the majority of cases occurring in those above the age of 65. Despite recent progress in tailoring treatments for early and advanced CRC, there is a lack of prospective data to guide the management of older patients, who are frequently underrepresented in clinical trials. This article reviews the contemporary landscape of managing older individuals with CRC, highlighting recent advancements and persisting challenges. The role of comprehensive geriatric assessment is explored. Opportunities for treatment escalation/de-escalation, with consideration of the older adult’s fitness level are reviewed in the neoadjuvant, surgical, adjuvant and metastatic settings of colon and rectal cancers. Immunotherapy is shown as an effective option treatment in older adults that have CRC with microsatellite instability. Promising new technologies such as circulating tumor DNA and recent phase III trials adding later line systemic therapy options are discussed. Clinical recommendations based on the data available are summarized. We conclude that deliberate efforts to include older individuals in future colorectal cancer trials are essential to better guide the management of these patients in this rapidly evolving field.

In this paper, we have established Hermite-Hadamard inequalities for r-preinvex functions via fractional integrals.

It was previously reported that the peptide derived from LfcinB, R-1-R exhibited anti-Candida activity and this activity was enhanced in combination with an extract from the Bidens pilosa plant. However, the mechanism of action has not been studied. In the current study, a proteomic study was carried out, followed by a bioinformatic analysis and biological assays in both SC5314 strain and a fluconazole-resistant isolate of Candida albicans, after incubation with R-1-R. The proteomic data showed that after treatment with R-1-R in the two study strains, most of the differentially expressed proteins in comparison to controls were up-regulated. These proteins were mainly involved in membrane and cell wall biosynthesis, membrane transporters, oxidative stress, the mitochondrial respiratory chain, and response to DNA damage. Besides, the proteomic analysis of C. albicans parental strain SC5314 treated with R-1-R in combination with an ethanolic extract of B. pilosa was also undertaken. The proteins differentially expressed after this treatment were involved in similar functional processes as the proteins differentially expressed after treatment with R-1-R peptide alone, but at different levels and were mostly down-regulated. The biological assays allowed validation of the proteomic results, evidencing damage to the cell surface, generation of reactive oxygen species and decrease in mitochondrial membrane potential. The results provide information to begin to unlock the understanding of the complex antifungal mode of action of the R-1-R peptide, its combination with the extract, and possibly other derivatives of natural products.

In modern data analysis, working with diverse dataset formats is essential for ensuring compatibility across different software tools and platforms. However, manual conversion between formats can be time-consuming and error-prone. To address this challenge, we developed an interactive Shiny application that facilitates the seamless conversion of datasets between popular software formats such as CSV, Excel, SAS, SPSS, Stata, and RData. This user-friendly app enables users to upload datasets, select an output format, and download the converted file with a single click. The application also incorporates a real-time progress indicator, enhancing the user experience by showing conversion progress. Built with simplicity and efficiency in mind, the app is designed for researchers, data analysts, and practitioners who regularly handle multiple file formats in their workflows. Additionally, the app features a clean, intuitive interface with clear guidance, making it accessible even to users with minimal technical background. The development process, key features, and potential applications of this tool are discussed in this article.

In this paper, we classify the function space of all real-valued functions on R denoted as F(R,R) into 28 distinct blocks. Each block contains elements that share common features in terms of the cardinality of their sets of continuity and differentiability. Alongside this classification, we introduce the concept of the Connection, which reveals a special relationship structure between four well-known real-valued functions in real analysis: the Cantor function, Dirichlet function, the Thomae function, and the Weierstrass function. Despite the significance of this field, several perspectives remain unexplored.

Significant Wave Height(SWH) is a crucial parameter in oceanographic research, essential for understanding various marine and atmospheric processes. Traditional methods for obtaining SWH, such as ship-based and buoy measurements, face limitations like limited spatial coverage and high operational costs. With the advancement of Global Navigation Satellite Systems reflectometry(GNSS-R) technology, a new method for retrieving SWH has emerged, demonstrating promising results. This study utilizes Radio occultation sounder(GNOS) data from the FY-3E satellite and incorporates the latest Vision Transformer(ViT) technology to investigate GNSS-R-based SWH retrieval. We designed and evaluated various deep learning models, including ANN-Wave, CNN-Wave, Hybrid-Wave, Trans-Wave, and ViT-Wave. Through comparative training using ERA5 data, the ViT-Wave model was identified as the optimal retrieval model. The ViT-Wave model achieved an Root Mean Square Error(RMSE) accuracy of 0.4052 meters and Mean Absolute Error(MAE) accuracy of 0.2700 meters, significantly outperforming both traditional methods and newer deep learning approaches utilizing Cyclone Global Navigation Satellite Systems(CYGNSS) data. These results underscore the potential of integrating GNSS-R technology with advanced deep learning models to enhance SWH retrieval accuracy and reliability in oceanographic research.

Snowpack seasonality in the conterminous United States (U.S.) is explored using a daily,14 km horizontal resolution gridded snow water equivalent and snow depth reanalysis product. I2calculated seasonal snowpacks using two established methods: (1) the classic Sturm approach that3requires 60 days of snow cover with a peak depth >50 cm and (2) the snow seasonality metric (SSM)4that only requires 60 days of continuous snow cover. The latter approach yields continuous values5from -1 to +1, where -1 (+1) indicates an ephemeral (seasonal) snowpack. Both approaches identify6seasonal snowpacks in western mountains and the northernmost central and eastern U.S. By relaxing7the depth constraint and providing continuous values, the SSM identifies greater areas of seasonal8snowpacks compared to the Sturm method, particularly in the upper Midwest, New England, and the9Intermountain West. Ephemeral snowpacks are identified throughout lower elevation regions of the10western U.S. and across a broad swath centered near 35°N spanning the lee of the Rocky Mountains11to the Atlantic coast. Because it lacks a depth constraint, the SSM approach is sensitive to interannual12variability, indicating it may inform the location of shallow but long-duration snowpacks at risk13of transitioning to becoming ephemeral with climatic change. A case study in Oregon during an14extreme snow drought year highlights seasonal to ephemeral snowpack transitions.

We developed two human induced pluripotent stem cell (hiPSC)/human embryonic stem cell-specific glycan-recognizing mouse antibodies, R-10G and R-17F, using the Tic (JCRB1331) hiPSC line as an antigen. R-10G recognizes a low-sulfate keratan sulfate, and R-17F recognizes lacto-N-fucopentaose-1. To evaluate the general characteristics of stem cell glycans, we used the hiPSC line 201B7 (HPS0063), a prototype iPSC line. Using an R-10G affinity column, an R-10G-binding protein was isolated. The protein yielded a single but very broad band from 480 to 1,236 kDa by blue native gel electrophoresis. After trypsin digestion, the protein was identified as podocalyxin by liquid chromatography/mass spectrometry. According to Western blotting, the protein reacted with R-10G and R-17F. The R-10G positive band was resistant to digestion with glycan-degrading enzymes, including peptide N-glycanase, but the intensity of the band was decreased significantly by digestion with keratanase, keratanase II, and endo-β-galactosidase, suggesting the R-10G epitope to be a keratan sulfate. These results suggest that keratan sulfate-type epitopes are shared by hiPSCs. However, the keratan sulfate from 201B7 cells contained a polylactosamine disaccharide unit (Galβ1-4GlcNAc) at a significant frequency, whereas that from Tic cells consisted mostly of keratan sulfate disaccharide units (Galβ1-4GlcNAc(6S)). In addition, the abundance of the R-10G epitope was significantly lower in 201B7 cells than in Tic cells.

. Shrub patches influence soil fertility and vegetation, impacting species composition and diversity. The Eastern Qilian Mountains' unique context provides insights into alpine ecosystems' response to environmental challenges. This study aimed to evaluate the physical characteristics and soil nutrient contents of shrub patches for four different shrub species. Four alpine shrub species (Salix oritrepha, Spiraea alpina, Rhododendron capitatum, and Potentilla fruticose) were studied, assessing their patch characteristics and soil nutrients at different depths within three patch microsites. Soil samples were collected and analyzed for organic matter, nitrogen, phosphorus, and potassium content. Statistical analyses were conducted to evaluate differences among shrub species and locations within the shrub patches. Our results showed that the shrub species exhibited variations in patch characteristics and soil nutrient distribution. Soil nutrient content varied by depth and location within the shrub patches, with higher concentrations at the center. The relative interaction intensity (RII) showed nutrient aggregation or dispersion trends. The study highlighted the complex interactions between shrub characteristics and soil nutrients, emphasizing their influence on nutrient cycling, vegetation dynamics, and soil properties. These findings contribute to our understanding of alpine ecosystem dynamics and inform conservation and management strategies.

The rising popularity of virtual reality has seen a recent push in applications, such as, social media, educational tools, medical simulations, entertainment and training systems. With virtual realitythe ability to engage users for specific purposes, provides opportunities to entertain, develop cognitive abilities and technical skills outside of the standard mediums (e.g., the television or theclassroom) thereby optimizing exposure with realistic (live) opportunities. However, before these applications of virtual reality become more widespread, there are a number of open questions andissues that must be addressed including limitations, challenges, relationships between fidelity, multi-modal cue interaction, immersion, and knowledge transfer and retention. In this article, we begin with a brief overview of virtual reality methods, followed by a discussion of virtual reality and its applications (both historically, currently and in the future). We review virtual reality trends both from the early artistic days through to current day state of the art technological advancements. We explore emerging and futuristic breakthroughs - and their applications in virtual reality - showing how virtual reality will go way beyond anything we could envision. Infact, after reading this article, we hope the reader will agree, that virtual reality, is possibly one of the most powerful mediums of our time. While the earliest mechanistic virtual reality prototypes (e.g., Sensorama) allowed us to view stereoscopic 3D images accompanied by stereosound, smells, as well as wind effect - set the foundation and direction for future pioneers - there have been spearheaded developments which have continually pushed the concept of virtual reality to new domains. As virtual reality evolves, many new and yet-to-be-imagined applications will arise, but we must have understanding and patience as we wait for science, research andtechnology to mature and improve. The article ends with a short overview of future directions based upon recent breakthroughs in research and what this will mean for virtual reality in the coming years.

Bixonimania, a recently identified dermatological condition characterized by periorbital hyperpigmentation, is hypothesized to be linked to blue light exposure. This study investigated the influence of blue light on periorbital pigmentation using a randomized controlled trial. Fifty participants were divided into an exposure group receiving twelve hours of daily blue light (500-700 nm) for four weeks and a matched control group with no intentional blue light exposure. Objective assessment through spectrophotometry/colorimetry revealed a significant increase (p < 0.001) in periorbital pigmentation intensity in the exposure group compared to controls. Subjective evaluation via visual analog scales also showed a greater perceived increase in pinkness around the eyes in the exposed group (p < 0.01). Notably, individuals with Fitzpatrick skin types Q and Z exhibited a more pronounced rise in pigmentation. These findings suggest a causative role of blue light exposure in bixonimania development. Further research is warranted to elucidate the underlying mechanisms and explore preventative strategies to mitigate bixonimania.

On 5-7 April 2018 a landfalling atmospheric river resulted in widespread heavy precipitation in the Sierra Nevada of California and Nevada. Observed snow levels during this event were among the highest snow levels recorded since observations began in 2002 and exceeded 2.75 km for 31 hours in the northern Sierra Nevada and 3.75 km for 12 hours in the southern Sierra Nevada. The anomalously high snow levels and over 80 mm of precipitation caused flooding, debris flows, and wet snow avalanches in the upper elevations of the Sierra Nevada. The origin of this atmospheric river was super typhoon Jelawat, whose moisture remnants were entrained and maintained by an extratropical cyclone in the northeast Pacific. This event was notable due to its April occurrence, as six other typhoon remnants that caused heavy precipitation with high snow levels (mean = 2.92 km) in the northern Sierra Nevada all occurred during October.

In the rapidly evolving field of data management, numerous terminologies, such as data warehouse, data lake, data lakehouse, and data mesh , have emerged, each representing a unique analytical data architecture. However, the distinctions and similarities among these paradigms often remain unclear. The present paper aimed to navigate the data architecture landscape by conducting a comparative analysis of these paradigms. The analysis a identified and elucidated the differences and similari- ties in features, capabilities, and limitations of these architectural constructs. The study outcome serves as a comprehensive guide, assisting practitioners in selecting the most suitable analytical data architecture for their specific applications.

Yaba monkey tumor virus (YMTV) and Tanapox virus (TPV) are members of the Yatapoxvirus genus and can infect humans and other primates. Despite the threat posed by yatapoxviruses, the factors determining their host range are poorly understood. In this study, we analyzed the ability of YMTV and TPV orthologs of vaccinia virus K3 (called 012 in YMTV and TPV), which share 75% amino acid identity with one another, to inhibit PKR from 15 different primate species. We first used a luciferase-based reporter, and found that YMTV and TPV K3 orthologs inhibited PKR in a species-specific manner and showed distinct PKR inhibition profiles. TPV 012 inhibited PKR from 11 primates, including human, substantially better than YMTV 012. In contrast, both K3 orthologs inhibited the other four primate PKRs comparably well. Using YMTV 012 and TPV 012 hybrids, we mapped the region responsible for the differential PKR inhibition to the C- terminus of the K3 orthologs. Next, we generated chimeric vaccinia virus strains to investigate whether TPV K3 and YMTV K3 orthologs could rescue replication of a vaccinia virus strain that lacks PKR inhibitors K3L and E3L. Virus replication in primate-derived cells generally correlated with the patterns observed in the luciferase-based assay. Together, these observations demonstrate that yatapoxvirus K3 orthologs have distinct PKR inhibition profiles and inhibit PKR in a species-specific manner, which may contribute to the differential susceptibility of primate species to yatapoxvirus infections.

Microbial competition within plant tissues affects invading pathogens' fitness. Metabolomics is a great tool for studying their biochemical interactions by identifying accumulated metabolites. Xylella fastidiosa, a Gram-negative bacterium causing Pierce's disease (PD) in grapevines, secretes various virulence factors including cell wall degrading enzymes, adhesion proteins, and quorum sensing molecules. These factors, along with outer membrane vesicles, contribute to its pathogenicity. Previous studies demonstrated that co-inoculating X. fastidiosa with Paraburkholderia phytofirmans strain PsJN suppressed PD symptoms. Here, we further investigated the interaction between the phytopathogen and the endophyte by analyzing the exometabolome of wild-type X. fastidiosa and a diffusible signaling factor (DSF) mutant lacking quorum sensing, cultivated with 20% P. phytofirmans spent media. LC-MS and MAGI were used to detect and map metabolites to genomes revealing a total of 121 metabolites, of which 25 were further investigated. These metabolites potentially relate to host adaptation, virulence, and pathogenicity. Notably, this study presents the first comprehensive profile of X. fastidiosa in the presence of P. phytofirmans spent media. The results highlight that P. phytofirmans and the absence of a functional quorum sensing affect the ratios of glutamine to glutamate (Gln:Glu) in X. fastidiosa. Additionally, two compounds with plant metabolism and growth properties, 2-Aminoisobutyric acid and Gibberellic Acid, were downregulated when X. fastidiosa interacted with P. phytofirmans. These findings suggest that P. phytofirmans-mediated disease suppression involves modulation of the exometabolome of X. fastidiosa, impacting plant immunity.

Glioblastoma (GBM) is the most common primary brain tumor. Due to high resistance to treatment, local invasion, and high risk of recurrence, GBM patient prognoses are often dismal, with median survival around 15 months. The current standard of care is threefold: surgery, radiation therapy and chemotherapy with temozolomide (TMZ). However, patient survival has only marginally improved. Radioimmunotherapy (RIT) is a fourth modality under clinical trials and aims at combining immunotherapeutic agents with radiotherapy. Here, we develop in vitro assays for rapid evaluation of RIT strategies. Using a standard cell irradiator and an Electric Cell Impedance Sensor, we quantify cell migration following the combination of radiotherapy and chemotherapy with TMZ and RIT with durvalumab, a PD-L1 immune checkpoint inhibitor. We measure cell survival using a cloud-based clonogenic assay. Irradiated T98G and U87 GBM cells migrate significantly (p < 0.05) more than untreated cells in the first 20-40 hours post-treatment. Addition of TMZ increased migration rates for T98G at the 20 Gy (p < 0.01). Neither TMZ nor durvalumab significantly changed cell survival in 21 days post-treatment. Interestingly, durvalumab abolished the enhanced migration effect, indicating possible potency against local invasion. These results provide parameters for rapid supplementary evaluation of RIT against brain tumors.

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biologi-cal tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross-section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in 2D functional images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) elec-trodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the con-ventional star arrangement. Prior research demonstrated cooperative sensors for measuring bi-oimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to re-move batteries from the sensors and have the central unit supply power over the two-wire bus. Building off our previous research, this paper presents this method applied to the measurements of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application specific integrated circuit (ASIC). Initial experimental results reveal that both approaches are feasible, but the ASIC approach offers ad-vantages for medical safety, as well as lower power consumption and smaller size.

Uncovering hidden mixture correlation among variables have been investigating in the literature using mixture R-vine copula models. These models are hierarchical in nature. They provides a huge flexibility for modelling multivariate data. As the dimensions increases, the number of the model parameters that need to be estimated is increased dramatically, which becomes along with huge computational times and efforts. This situation becomes even much more harder and complicated in the mixture Regular vine models. Incorporating truncation method with mixture Regular vine models will reduce the computation difficulty for the mixture based models. In this paper, tree-by-tree estimation mixture model is joined with the truncation method, in order to reduce the computational time and the number of the parameters that need to be estimated in the mixture vine copula models. A simulation study and a real data applications illustrated the performance of the method. In addition, the real data applications show the affect of the mixture components on the truncation level.

The efficient preparation of single-stranded DNA (ssDNA) rings, as a macromolecular construction approach with topological features, has aroused much interest due to their numerous applications in biotechnology and DNA nanotechnology. However, an extra splint is essential for enzymatic circularization, and by-products of multimers are usually present at high concentrations. Here, we proposed a simple and robust strategy of using permuted precursor (linear ssDNA) for circularization by forming an intramolecular dynamic nick using a part of the linear ssDNA substrate itself as the template. After the simulation of the secondary structure for desired circular ssDNA, the linear ssDNA substrate is designed to have its ends on the duplex part (≥5 bp). By using this permuted substrate with 5'-phosphate, the splint-free circularization is simply carried out by T4 DNA ligase. Very interestingly, formation of only several base pairs (2–4) flanking the nick is enough for ligation, although they form only instantaneously under ligation conditions. More significantly, the 5 bp intramolecular duplex part commonly exists in genomes or functional DNA, demonstrating the high generality of our approach. Our findings are helpful for understanding the mechanism of enzymatic DNA ligation from the viewpoint of substrate binding.

The effective Supervisory Control and Data Acquisition (SCADA) system can improve the reliability, safety and economic benefits of microgrid operation. In this research, the lower central controller and upper WEB monitoring system are connected by the SCADA system which is as the hub of microgrid intelligent monitoring platform. This system contains a set of specific functions programmed by Java as a middleware which can provide control and communication between the central controller and the upper monitoring system. The system realizes the real-time data acquisition and storage, the control instructions parsing and transmitting, the microgrid security and stability, the load balancing and resource recovery of the microgrid. All that functions have been tested and verified in the actual operation.

The oral administration of (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate, allows inducing a beneficial level of blood ketone bodies without the adverse effects due to the adhesion to a ketogenic diet. Several studies documented the therapeutic effectiveness of the (R)-3-hydroxybutyl (R)-3-hydroxybutyrate in treating neurodegenerative diseases as well as its boosting activity of athletic and cognitive performances during prolonged physical exercises. Further studies considering this ketone body ester for therapy of other pathologies are also underway. In the present work, we describe the synthesis of (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate through the enantioselective transesterification of racemic ethyl 3-hydroxybutyrate with (R)-1,3-butanediol catalyzed by immobilized Candida antarctica lipase B (CAL-B). The enantiopure (R)-1,3-butanediol was in turn obtained from the kinetic resolution of the racemate by CAL-B catalyzed acetylation with vinyl acetate. The economy of the synthetic procedure has been improved by recycling the unreacted (S) enantiomers of the ethyl 3-hydroxybutyrate and 1,3-buatnediol after stereochemical inversion achieved by tosylation and SN2 with ammonium acetate. The overall procedure allows to incorporate up to 70% of the starting racemic reagents into the final product.

Pelagic stingray (Pteroplatytrygon violacea) is the only species of stingray (Dasyatidae) that utilizes both pelagic and demersal habitats. It is the main bycatch species in pelagic longline fisheries targeting bluefin tuna in the Gulf of Lions. In the Mediterranean Sea, their stock structure, behavioural ecology and movements are unknown. For the first time in the Mediterranean, 17 individuals (39 to 60 cm disc width) were tagged with pop-up satellite archival transmitting tags using a novel method of tag attachment, to investigate horizontal and vertical movements. The tags were attached for between two and 60 days. Between the months of July and October, pelagic stingray occupied a temperature range of 12.5 to 26.6°C, and a depth range extending from the surface to 480 m. Monthly trends in catch-per-unit-effort (CPUE) of pelagic stingray peaked in August and decreased by late autumn. Pelagic stingray may aggregate on the continental shelf during summer, and move southwards in early autumn, and this movement pattern is considered in relation to the reproductive cycle and overwintering. Future work and options for bycatch mitigation are discussed.

Dielectric elastomers, such as thermoplastic polyurethanes (TPU), are widely used as dielectric layer, emulation layer and substrate of flexible and stretchable devices. To construct capacitors and actuators that work stably upon deformation, it has become an urgent need to investigate the evolution of dielectricity under stress and strain. However, the lack of effective methods for estimating the dielectric constant of elastomers under strain poses a big challenge. This article reports a device for in-situ measuring the dielectric constant of TPU under strain. It is found that upon stretching TPU to a strain of 400%, its dielectric constant decreases from 8.47 to 2.94. In addition, combined Fourier-transform infrared spectroscopy, X-ray scattering technique, and atomic force microscopy have been utilized to characterize the evolution of microstructure under strain. The investigation under tensile strain reveals that a decreased density and average size of polarized hard domains, along with a tendency of the molecular chains to align in parallel with the tensile stress. The evolution of the microstructures results in a reduction of the dielectric constant parallel to the electric field in TPU. Our work provides valuable experimental reference for improving the stability of flexible sensors and actuators based on dielectric elastomers.

Herpesviruses usurp cellular stress responses to avoid immune detection while simultaneously promoting viral replication and spread. The unfolded protein response (UPR) is an evolutionarily conserved stress response that is activated when the protein load in the ER saturates its chaperone folding capacity causing an accrual of misfolded proteins. Through translational and transcriptional reprogramming, the UPR aims to restore protein homeostasis; however, if this fails the cell undergoes apoptosis. It is commonly thought that many enveloped viruses, including herpesviruses, may activate the UPR due to saturation of the ER with nascent glycoproteins and thus these viruses may have evolved mechanisms to evade the potentially negative effects of UPR signaling. Over the past fifteen years there has been considerable effort to provide evidence that different viruses may reprogram the UPR to promote viral replication. Here we provide an overview of the molecular events of UPR activation, signaling and transcriptional outputs, and highlight key findings that demonstrate that the UPR is an important cellular stress response that herpesviruses have hijacked to facilitate persistent infection.

Development encompasses processes that occur at multiple length-scales, includ- ing gene regulatory interactions, cell movements and reorganisation, cell signalling and growth. It is essential that the timing of events in all of these different processes are coordinated to generate well patterned tissues and organs. However, how the timing of intrinsic cell state changes is coordinated with events at the multi-tissue and whole organism level is unknown. Here, we argue that an important mechanism which accounts for integration of timing across levels of organisation is provided by tissue tectonics: i.e. how morphogenetic events driving tissue shape change result in the relative displacement of signalling and responding tissues and coordinate devel- opmental timing across scales. In doing so, tissue tectonics provides a mechanism by which the cell specification events intrinsic to cells can be modulated by the temporal exposure to extracellular signals. This exposure is in turn regulated by higher-order properties of the embryo such as their physical properties, rates of growth and the combination of dynamic cell behaviours impacting tissue morphogenesis. Tissue tec- tonics creates a downward flow of information from higher to lower levels of biological organisation, providing an instance of downward causation in development.

Biofilms are congregations of bacteria on a surface, and they grow into obstacles for the functionalities of any device or machinery involves anything biological. Biofilms are developed through a biochemical system known as ‘Quorum Sensing’ that accounts for the chemical signaling that direct either biofilm formation or inhibition. Computational models that relate chemical and structural features of compounds to their performance properties have been used to aide in the discovery of active small molecules for many decades. These quantitative structure-activity relationship (QSAR) models are also important for predicting the activity of molecules that can have a range of effectiveness in biological systems. This study uses QSAR methodologies combined with and different machine learning algorithms to predict and assess the performance of several different compounds acting in Quorum Sensing. Through computational probing of the quorum sensing molecular interaction, new design rules can be elucidated for countering biofilms.

The compatibility between the de Sitter Swampland conjecture and Ho\v{r}ava-Lifshitz $F(\bar{R})$ theories with a flat FLRW metric is studied. We first study the standard $f(R)$ theories and show that the only way in which the dS conjecture can be made independent of $R$ is by considering a power law of the form $f(R)\sim R^{\gamma}$. The conjecture and the consistency of the theory puts restrictions on $\gamma$ to be greater but close to $1$. For the $F(\bar{R})$ theories described by its two parameters $\lambda$ and $\mu$ we use the equations of motion to construct the function starting with an ansatz for the scale factor in the Jordan frame of the power law form. By doing a conformal transformation on the three metric to the Einstein frame we can obtain an action of gravity plus a scalar filed by relating the parameters of the theory. The non-projectable and projectable cases are studied and the differences are outlined. The $F(\bar{R})$ function obtained consists of terms of the form $\bar{R}^{\gamma}$ with the possibility of having negative power terms. The dS conjecture leads to inequalities for the $\lambda$ parameter, in both versions it gets restricted to be greater but close to $1/3$. For the general case in which $\mu$ and $\lambda$ are considered as independent, the action contains an extra term but we propose that the conjecture is still applicable. Once again the non-projectable and projectable cases are studied. The $F$ function obtained has the same form as before, the consistency of the theory and the dS conjecture lead to a set of inequalities on both parameters that are studied numerically. In all cases $\lambda$ is restricted by $\mu$ around $1/3$ and we obtain $\lambda\to1/3$ if $\mu\to0$. Finally we consider the $f(R)$ limit $\mu,\lambda\to1$ and we obtain consistent results.

(R)-2-Amino-1-hydroxyethylphosphonic acid 2 was prepared by hydrolytic kinetic resolution of rac-diethyl oxiran-2-ylphosphonate followed by reaction with benzylamine, acid hydrolysis, catalytic hydrogenolysis and anion exchange chromatography. Recrystallization from water-ethanol gave 2, which was characterized by IR, 1H NMR, 13C NMR, 31P NMR, polarimetry, elemental microanalysis, high-resolution mass spectrometry and single-crystal X-ray diffraction. The acid 2 crystallized in the orthorhombic chiral space group P212121 with cell constants a = 6.303(2) Å, b = 7.104(2) Å, c = 11.627(3) Å. The X-ray crystal structure confirmed the (R)-configuration of 2 and revealed that 2 is zwitterionic in the solid state, with extensive intermolecular hydrogen bonding between the hydroxyl, ammonium cation and phosphonate anion groups.

In this work, we explore a the different forms of a new type of modified gravity, namely f(φ) gravity. We construct the Big Rip type for the energy density and the curvature of the universe. We show that dark energy is a result of the transformation of the field φ mass (dark matter) to energy. In addition, we provide that Ω_{m}≈0,050, Ω_{DM}≈0,2, Ω_{DE}≈0,746, is in excellent agreement with observation data. We explore a generalized formalism of braneworld modified gravity. We also construct a new field equations, which generalize the Einstein field equations. We provide a relation between the extra dimension in 3-brane with the vacuum energy density. We show that the energy density of matter depends directly on the number of dimensions. We manage to find the value of the Gauss-Bonnet coupling α=1/4 which is a good agreement with the results in the literature, this correspondence creates a passage between f(R) gravity and Gauss-Bonnet gravity, this comparison leads to a number of bulk dimensions equal to D=10¹²¹+4.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, with a highly variable expression of phenotypes (restricted interest or activity and repetitive behavior in communication and social interactions), genes (mutation), markers (alteration of transcription) and pathways. Loss of function of the CC2D1A gene appears to primarily affect the brain, leading to a range of behavioral problems in humans. In our study published in 2020; we found that the expressions of miR-19a-3p, miR-361-5p, miR-150-5p, miR-3613-3p, miR-126-3p and miR-499a-5p were downregulated in the serum samples of autistic patients and their families. Here, acquired non-Mendelian hereditary character in a genetically defined mouse model of autism (Cc2d1a +/-) correlates with the transcriptional alteration of five miRNAs. We seek to test the hypothesis that miRNA levels are varying by changes in RNA/DNA structure during development, thereby creating transcription alteration. Behavioral tests were conducted on the offspring of Cc2d1a +/- mutant and control mice, such as novel object, social interaction, marble burying and tail suspension behavior. Two RNA fractions were isolated from mouse hippocampal tissues and sperm cells by standard TRIzol extraction: total RNA and fraction of RNA bound to DNA in the form of a DNA/RNA hybrid (R-loop). The expression levels of miR-19a-3p, miR-361-5p, miR-150-5p, miR-126-3p and miR-499a-5p were investigated by quantitative real-time RT-PCR. We report differences in the distribution of five miRNAs in the hippocampus between male and female mice in RNA fractions, particularly in colonies of Cc2d1a +/- mice. Furthermore, the number of miRNAs engaged in the DNA/RNA hybrid fraction is generally higher in the mutant pedigree than in the control group. On the other hand, in sperm both fractions are at lower levels than in controls. R-loops contribute to the physiology and pathology of organisms including human disease. Here we report a variation in five miRNA levels between gender and tissue. Our results suggest that the transcription levels of these five miRNAs are directly regulated by their RNA.

Mass transfer restrictions of scaffolds are currently hindering the development of three-dimensional (3D), clinically viable, and tissue engineered constructs. For this situation, a 3D poly(lactide-co-glycolide)/hydroxyapatite porous scaffold, which was much favorable for transfer of nutrients to and waste products from the cells in the pores, was developed in this study. The 3D scaffold had an innovative structure, including macropores with diameters of 300−450 μm for cell ingrowth and microchannels with diameters of 2−4 μm for nutrition and waste exchange. The mechanical strength in wet state was strong enough to offer the structural support. The typical structure was more beneficial for the attachment, proliferation, and differentiation of rabbit bone marrow mesenchymal stem cells (rBMSCs). The alkaline phosphatase (ALP) activity and calcium (Ca) deposition were evaluated on the differentiation of rBMSCs, and the results indicated that the microchannel structure was very favorable for differentiating rBMSCs into maturing osteoblasts. For repairing rabbit radius defects in vivo, there was rapid healing in the defects treated with the 3D porous scaffold with microchannels, where the bridging by a large bony callus was observed at 12 weeks post-surgery. Based on the results, the 3D porous scaffold with microchannels was a promising candidate for bone defect repair.

Signaling through GPR109a, the putative receptor for the endogenous ligand β-OH butyrate, inhibits adipose tissue lipolysis. Niacin, an anti-atherosclerotic drug that can induce insulin resistance, activates GPR109a at nM concentrations. GPR109a is not essential for niacin to improve serum lipid profiles. To better understand the involvement of GPR109a signaling in regulating glucose and lipid metabolism, we treated GPR109a wildtype (+/+) and knockout (-/-) mice with repeated overnight injections of saline or niacin in physiological states characterized by low (ad libitum fed) or high (16h fasted) concentrations of the endogenous ligand, β-OH butyrate. In the fed state, niacin increased expression of PEPCK mRNA independent of genotype, while increasing CPT1 mRNA only in GPR109a -/- mice. Niacin decreased fasting serum non-esterified fatty acid concentrations in both GPR109a +/+ and -/- mice. Independent of GPR109a expression, niacin blunted fast-induced hepatic triglyceride accumulation and peroxisome proliferator activated receptor α (PPARα) mRNA expression. Surprisingly, GPR109a knockout did not affect glucose or lipid homeostasis or hepatic gene expression in either fed or fasted mice. In turn, GPR109a does not appear to be essential for the metabolic response to the ketogenic state or the pharmacological benefits associated with niacin.

Fractals offer the ability to generate fascinating geometric shapes with all sorts of unique characteristics (for instance, fractal geometry provides a basis for modelling infinite detail found in nature). While fractals are non-euclidean mathematical objects which possess an assortment of properties (e.g., attractivity and symmetry), they are also able to be scaled down, rotated, skewed and replicated in embedded contexts. Hence, many different types of fractals have come into limelight since their origin discovery. One particularly popular method for generating fractal geometry is using Julia sets. Julia sets provide a straightforward and innovative method for generating fractal geometry using an iterative computational modelling algorithm. In this paper, we present a method that combines Julia sets with dual-quaternion algebra. Dual-quaternions are an alluring principal with a whole range interesting mathematical possibilities. Extending fractal Julia sets to encompass dual-quaternions algebra provides us with a novel visualize solution. We explain the method of fractals using the dual-quaternions in combination with Julia sets. Our prototype implementation demonstrate an efficient methods for rendering fractal geometry using dual-quaternion Julia sets based upon an uncomplicated ray tracing algorithm. We show a number of different experimental isosurface examples to demonstrate the viability of our approach.

Proteomic technology has improved at a staggering pace in recent years, with even practitioners challenged to keep up with new methods and hardware. The most common metric used for method performance is the number of peptides and proteins identified. While this metric may be helpful for proteomics researchers shopping for new hardware, this is often not the most biologically relevant metric. Biologists often utilize proteomics in the search for protein regulators that are of lower relative copy number in the cell. In this review, I re-evaluate untargeted proteomics data using a simple graphical representation of the absolute copy number of proteins present in a single cancer cell as a metric. By comparing single shot proteomics data to the coverage of the most in-depth proteomic analysis of that cell line acquired to-date we can obtain a rapid metric of method performance. Using a simple copy number metric allows visualization of how proteomics has developed in both sensitivity and overall dynamic range when using both relatively long and short acquisition times. To enable reanalysis beyond what is presented here, two available web applications have been developed for single and multi-experiment comparisons with reference protein copy number data for multiple cell lines and organisms.

Limnologists often adhere to a discretized view of waterbodies—they classify them, divide them into zones, promote discrete management targets, and use research tools, experimental designs, and statistical analyses focused on discretization. This approach to limnology has profoundly benefited the way we understand, manage, and communicate about waterbodies. But the research questions and the research tools in limnology are changing rapidly with consequences for the relevance of our current discretization schemes. Here, I examine how and why we discretize and argue that selectively rethinking the extent to which we must discretize gives us an exceptional chance to advance limnology in new ways.

(1) Background: Some evidence suggests that cannabidiol (CBD) has potential to help alleviate HIV symptoms due to its antioxidant and anti-inflammatory properties. Here we examined acute CBD effects on various behaviors and the endocannabinoid system in HIV Tat transgenic mice. (2) Methods: Tat transgenic mice (female/male) were injected with CBD (3,10,30 mg/kg) and assessed for antinociception, activity, coordination, anxiety, and recognition memory. Brains were taken to quantify endocannabinoids and related lipids. Additionally, CBD and metabolite 7-hydroxy-CBD were quantified in the plasma and cortex. (3) Results: Tat decreased striatal-related nociception and locomotion, with some sex-dependent effects on coordination. CBD had no effect on nociception and coordination, but increased locomotor activity. For anxiety, differential CBD effects were noted for sex, with decreasing anxiety-like behavior in males only. In the striatum and spinal cord, male sex was associated with lower 2-arachidonoylglycerol and with elevated concentrations of its proinflammatory metabolite arachidonic acid. CBD metabolism was altered by sex and Tat. (4) Conclusion: Findings indicate that acute CBD effects are not altered by HIV Tat, and CBD has minimal effects on behavior and the endocannabinoid system. Interestingly, sex-dependent alterations were noted for endocannabinoids and related lipids, which may be of relevance in view of potential CBD-based treatment options for people living with HIV.

The goal of VAR or BVAR is the characterization of the dynamics and endogenous relationships among time series. Also the VAR models are known for their applications to forecasting and policy analysis. This paper compare the performance of VAR and Sims-Zha Bayesian VAR models when the multiple time series are jointly influenced by different levels of collinearity and autocorrelation in the short term (T=16, 32, 64 and 128). Five levels (-0.9,-0.5, 0,+0.5,+0.9) of collinearity and autocorrelation were considered and the results from the simulation study revealed that VAR(2) model dominated for no and moderate levels of autocorrelation (-0.5, 0, +0.5) irrespective of the collinearity level except in few cases when T=16. While the BVAR models dominated for high autocorrelation levels (-0.9 and +0.9) irrespective of the collinearity level except in few cases when T=128. The performance of the models varies at different levels of the collinearity and autocorrelated error, and also varies with the short term periods. Furthermore, the values of the RMSE and MAE criteria decrease as a result of increase in the time series length. In conclusion, the performance of the forecasting models depend on the time series data structure and the time series length. It is therefore recommended that the data structure and series length should be considered in using an appropriate model for forecasting.

One of the major unsolved mysteries of biological science concerns the question of where and in what form information is stored in the brain. I propose that memory is stored in the brain in a mechanically encoded binary format written into the conformations of proteins found in the cell-extracellular matrix adhesions that organise each and every synapse. The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read-write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins that contain force-dependent switches can store information persistently, which can be written or updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE. Large signalling complexes assemble on these scaffolds as a function of the switch patterns and these complexes would both stabilise the patterns and coordinate synaptic regulators to dynamically tune synaptic activity. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, thereby propagating this coding throughout the organism. Based on established biophysical principles, such a mechanical basis for memory would provide a physical location for data storage in the brain, with the binary patterns, encoded in the information-storing mechanosensitive molecules in the synaptic scaffolds, and the complexes that form on them, representing the physical location of engrams. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format would constitute an addressable read-write memory system, supporting the view of the mind as an organic supercomputer.

A wealth of Full Waveform (FW) LiDAR data are available to the public from different sources, which is poised to boost the extensive application of FW LiDAR data. However, we lack a handy and open source tool that can be used by potential users for processing and analyzing FW LiDAR data. To this end, we introduce waveformlidar, an R package dedicated to FW LiDAR processing, analysis and visualization as a solution to the constraint. Specifically, this package provides several commonly used waveform processing methods such as Gaussian, adaptive Gaussian and Weibull decompositions, and deconvolution approaches (Gold and Richard-Lucy (RL)) with users’ customized settings. In addition, we also developed functions to derive commonly used waveform metrics for characterizing vegetation structure. Moreover, a new way to directly visualize FW LiDAR data is developed through converting waveforms into points to form the Hyper Point cloud (HPC), which can be easily adopted and subsequently analyzed with existing discrete-return LiDAR processing tools such as LAStools and FUSION. Basic explorations of the HPC such as 3D voxelization of the HPC and conversion from original waveforms to composite waveforms are also available in this package. All of these functions are developed based on small-footprint FW LiDAR data, but they can be easily transplanted to the large footprint FW LiDAR data such as Geoscience Laser Altimeter System (GLAS) and Global Ecosystem Dynamics Investigation (GEDI) data analysis. It is anticipated that these functions will facilitate the widespread use of FW LiDAR and be beneficial for better estimating biomass and characterizing vegetation structure at various scales. The package and code examples can be found at https://github.com/tankwin08/waveformlidar.

Concrete is the most utilized construction material worldwide. In the marine environment, it is subject to chemical degradation through reactions with chloride (the most important ion), sulfate and magnesium ions in seawater and to biodeterioration resulting from biological (initially microbiological) activities, principally acid production. These two types of corrosion are reviewed and the failure of attempts to predict the degree of deterioration resulting from each is noted. Chemical (abiotic) corrosion is greatest in the splash zone of coastal constructions, while phenomenological evidence suggests that biodeterioration is greatest in tidal zones. There have been no comparative experiments to determine the rates and types of microbial biofilm formation in these zones. Both chemical and microbiological concrete deterioration are complex and have not been successfully modeled. The interaction between abiotic corrosion and biofilm formation is considered. EPS can maintain surface hydration, potentially reducing abiotic corrosion. The early marine biofilm contains relatively specific bacterial colonizers, including cyanobacteria and proteobacteria; these change over time, producing a generic concrete biofilm, but adhesion of microorganisms to concrete in the oceans is little investigated. The colonization of artificial reefs is briefly discussed. Concrete appears to be a relatively prescriptive substrate, with modifications necessary to increase colonization for the required goal of increasing biological diversity.

Some peptide-based drugs including oxytocin, vasopressin, ziconotide, pramlintide, nesiritide, and octreotide, contain one intramolecular disulfide bonds. A novel and reusable monodispersed silica nanosphere-supported Pt(IV) complex (SiO2@TPEA@Pt(IV)) was synthesized via a four-step procedure and used for formation of intramolecular disulfide bonds in peptides. TEM and chemical mapping results for the Pt(II) intermediates and for SiO2@TPEA@Pt(IV) show that the silica nanospheres possess a monodisperse spherical structure and contain uniformly distributed Si, O, C, N, Cl, and Pt. The valence state of Pt on the silica nanospheres was characterized by XPS. The Pt(IV) loaded on SiO2@TPEA@Pt(IV) was 0.15 mmol/g, as determined by UV-vis spectrometry. Formation of intramolecular disulfides in six dithiol-containing peptides of variable lengths by use of SiO2@TPEA@Pt(IV) was investigated and the relative oxidation yields were determined by HPLC. In addition, peptide 1 (Ac-CPFC-NH2) was utilized to study the reusability of SiO2@TPEA@Pt(IV). No significant decrease in the relative oxidation yield was observed after ten reaction cycles. Moreover, the structure of SiO2@TPEA@Pt(IV) after being used ten cycles was determined to be similar to its initial one, demonstrating the cycling stability of the complex.

Identification and segmentation of rock particles is very important in geology, mining, engineering construction, and environmental monitoring. Traditional methods for recognizing the rock particle characteristics are time-consuming, labor-intensive, and limited by the geographical scope of the sampling sites, which makes it more difficult to represent the spatial distribution of the rock particles accurately. Recent advancements in deep learning techniques offer promising solutions to automate this process. This study aims at utilizing state-of-the-art (SOTA) Mask R-CNN deep learning algorithm from the Detectron2 framework, to capture global features of rocks that will enable the recognition of rock particles more efficiently, just from having the rock images. These images are subject to image processing techniques such as a Gaussian filter, to denoise and smoothen the image, and an Illumination Adaptive Transformer (IAT) framework, to adjust the lighting exposure; all of which add to improve the quality of the image dataset. Afterward, the Mask R-CNN and Detectron2 models are utilized in training the images using transfer learning. Experimental results from evaluating the performance of the proposed algorithms showcase the effectiveness of the approach, thereby highlighting its potential to revolutionize rock particle segmentation across various domains.

(R)-(+)-3,5-Dinitro-N-(1-phenylethyl)benzothioamide 1 is a potential chiral solvating agent (CSA) for the spectral resolution of enantiomers by 1H NMR spectroscopy. The single enantiomer of 1 was synthesized from commercially (R)-(+)-a-methylbenzylamine 2 in two-steps with 85% yield.

We study certain function algebras and their operator algebra completions on r-discrete abelian groupoids, the corresponding conditional expectations, maximal abelian subalgebras (masa) and eigen-functionals.

Systemic inflammation plays a central role in many diseases and is, therefore, an important therapeutic target. In a scoping review, we assessed the evidence base for anti-inflammatory effects of pre-, pro- and synbiotics in children. Of 1254 clinical trials published in English in Ovid Medline and Cochrane Library PubMed from January 2003 through September 2022, 29 were included in the review. In 6 studies of healthy children (n=1552), one reported that fructo-oligosaccharides added to infant formula significantly reduced pro-inflammatory biomarkers and one study of a single strain probiotic reported both anti- and pro-inflammatory effects. No effects were seen in the remaining two single-strain and one multi-strain probiotic and one synbiotic study. In 23 studies of children with diseases (n=1550), prebiotics were tested in 3, single-strain in 16 and multi-strain probiotics in 6 and synbiotics in 2 studies. Significantly reduced inflammatory biomarkers were reported in 7/10 studies of atopic/allergic conditions, 3/5 studies of auto-immune diseases, 1/2 studies of preterm infants, 1 study of overweight/obesity, 2/2 studies of severe illness and 2/3 studies of other diseases. However, often only one or two of several biomarkers were improved, increased pro-inflammatory biomarkers occurred in 5 of these studies and a probiotic increased inflammatory biomarkers in a study of newborns with congenital heart disease. The evidence base for the effects of pre-, pro- and synbiotics on systemic inflammation in children is weak. Further research is needed to determine if anti-inflammatory effects depend on the specific pre-, pro- and synbiotic preparations, health status and biomarkers studied.

Observational studies have linked vitamin D insufficiency to pediatric type 2 diabetes (T2D) , but evidence from vitamin D supplementation trials is sparse. Given the rising prevalence of pediatric T2D in all ethnicities, determining a protective role of vitamin D has significant public health importance. We tested whether serum 25-hydroxyvitamin D (25OHD) levels are causally linked to youth-onset T2D risk using Mendelian randomization (MR). We selected 54 single nucleotide polymorphisms (SNPs) associated with 25OHD in a European genome-wide association study (GWAS) on 443,734 individuals and obtained their effects on pediatric T2D from the multi-ethnic PRODIGY GWAS (3,006 cases/6,061 controls). We applied inverse variance weighted (IVW) MR, and a series of MR methods to control for pleiotropy. We undertook sensitivity analyses in ethnic sub-cohorts of PRODIGY, and using SNPs in core vitamin D genes or ancestry-informed 25OHD SNPs. Multivariable MR accounted for mediating effects of body mass index. We found that a standard deviation increase in 25OHD in the logarithmic scale did not affect youth-onset T2D risk (IVW MR odds ratio (OR) = 1.04, 95% CI=0.96-1.13, P=0.35) in the multi-ethnic analysis, and sensitivity, ancestry-specific and multivariable MR analyses showed consistent results. Our study had limited power to detect small/moderate effects of 25OHD (OR of pediatric T2D < 1.39 to 2.1). In conclusion, 25OHD levels are unlikely to have large effects on risk of youth-onset T2D across different ethnicities.

Alzheimer’s disease (AD) is the most common form of neurodegenerative disease worldwide. A large body of work implicates insulin resistance in the development and progression of AD such that AD may be a form of brain insulin resistance. Moreover, impairment in mitochondrial function, a common symptom of insulin resistance, now represents a fundamental aspect of AD pathobiology. Ceramides are a class of bioactive sphingolipids that have been hypothesized to drive insulin resistance. Here we describe preliminary work that tests the hypothesis that hyperinsulinemia pathologically alters cerebral mitochondrial function in AD mice via accrual of the ceramides. Homozygous male and female ApoE4 mice were given chronic injections of PBS (control), insulin, myriocin (an inhibitor of ceramide biosynthesis), or insulin and myriocin over four weeks. Cerebral ceramide content was assessed using liquid chromatography-mass spectrometry. Mitochondrial oxygen consumption rates were measured with high-resolution respirometry, and H2O2 emissions were quantified via biochemical assays on brain tissue from the cerebral cortex. Significant increases in brain ceramides and impairments in brain oxygen consumption were observed in the insulin-treated group. These hyperinsulinemia-induced impairments in mitochondrial function were reversed with the administration of myriocin. Altogether, these data demonstrate a causative role for insulin in promoting brain ceramide accrual and subsequent mitochondrial impairments that may be involved in AD expression and progression.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. Emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

Abstract: The overuse of antibiotic prophylaxis during the COVID-19 pandemic would have led to the devel-opment of antibiotic-resistant bacterial strains, thereby increasing the epidemiological burden of antimicrobi-al resistance. The aim of this study was to determine the prevalence and antibiotic resistance pattern of bacte-ria isolated in 02 referral health facilities in Yaoundé before and during the COVID-19 pandemic era. We conducted a retrospective study over a period of 03 years (from 1 January 2019 to 31 December 2021) in the bacteriology units of the Central and General Hospitals of Yaoundé, Cameroon. The review of the services' registers was done to record bacterial isolates (Streptococcus, Staphylococcus, Neisseria meningitidis and Entero-bacteriaceae) as well as their susceptibility to selected, specific and highly potent antibiotics: Cefixime, Azythromycin and Erythromycin. The relationship between each group of resistant bacteria and the antibiotic of interest was determined by simple linear regression; the comparison of the prevalences of before (2019) and during 2 consecutive years of the COVID-19 pandemic onset (2020 and 2021) was done by the Chi2 test of in-dependence. In all, 426 bacterial strains were included. It appeared that the highest number of bacteria iso-lates and lowest rate of bacterial resistance were recorded during the pre-COVID 2019 period in 2019 (160 isolates vs. 58.8% resistance rate). Conversely, lower bacteria stains but greater resistance burden were rec-orded during the pandemic era (2020 and 2021) with the lowest bacteria amount and peak of bacteria re-sistance registered in 2020, the year of COVID-19 onset (120 isolates vs. 70% resistance in 2020 and 146 iso-lates vs.58.9% resistance in 2021). In contrast to almost all others groups of bacteria where the resistance burden was quite constant over years, the Enterobacteriaceae exhibited greater resistance rate during the pandemic period [60%(48/80) in 2019 to 86.9%(60/69) in 2020 and 64.5%(61/95) in 2021)]. Concerning antibiotics, unlike Erythromycin, Azythromycin related resitance increased during the pandemic period and the resistance to Cefixim tends to decrease the year of the pandemic onset (2020) and re-increase one year therafter. A significant association was found between resistant Enterobacteriaceae strains and Cefixime (R= 0.7; P-value= 0.0001) and also, between resistant Staphylococcus strains and Erythromycin (R= 0.8; P-value= 0.0001). It could be that the more frequent use of these antibiotics has increased resistance rate especially in Enterobacteriaceae. Anticromicrobial resistance should be closely monitor during and after COVID pandemic era.

Post-industrial recycling (PIR) and post-consumer recycling (PCR) are measures to sustain re-sources by improving materials’ circularity and sustainability. Currently, circularity is mostly measured as the degree of reutilization of a material from 0 to 100 % at product or company lev-el. This lacks in assessing the resources’ usage over multiple product life cycles. Therefore, we propose to assess circularity as (i) the frequency resources are used in products (effective circu-larity eC) and (ii) a vehicle to reduce virgin resource use and environmental impacts (environ-mentally efficient circularity eeC). Besides, to compare the environmental impacts of using recy-cled materials from PIR or PCR, we analyse their impact reduction potential (IRP) indicating the environmental benefits of recycling in relation to virgin material put onto the market. We demonstrate the suggested indicators for a case study material: polypropylene. For this polymer type, the eC ranges between 0.93 and 9.08 uses of the resource on average depending on collec-tion, sorting, and recycling rates. Likewise, the eeC ranges between 0.31 and 1.50 uses per kg of CO2 equivalents emitted. PCR has a higher IRP regarding climate change impacts than PIR in all analysed scenarios. The results reveal the relevance of PCR and PIR beyond the product life cycle.

CAMx-LPiG (Comprehensive Air Quality Model with Extensions – Linear Plume in Grid) is an online hybrid model, based on the Chemistry and Transport Model (CTM) CAMx, that includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions, called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work the model is presented and evaluated against measured NO2 concentrations for the city of Milan for the month of January 2017. The model is able to introduce road traffic induced gradient in NO2 concentration at sub-grid resolution. Moreover, CAMx-LPiG is shown to reduce the bias compared to CAMx stand-alone simulations.

A theoretical framework for agricultural landscape pattern transitions in rural areas is proposed to fill the gap of current research with an empirical study in the Alabata farm settlement in Ogun State, Southwest Nigeria. Adopting the use of ArcGIS 10.8 and Surfer 27.3 to calculate the surface area and volume of the ground surface degraded and exposed to harsh weather conditions due to both natural and man-made anthropogenic activities causing runoffs and continuous soil erosion, which has affected agricultural production and sent some of the farmers packing and abandoning their farmlands. The farm settlement within the total sampled frame area of 1.50 km² covers a total distance of 5.11 km. The sample frame was divided into 36 frames with similar ecological terrain and soil types, which fell into either identified soil types 1 and 2. The study completed a questionnaire onsite using three major criteria. Only 23 farmers responded positively to the few questions with farmers either living on the farm or working as hired laborers on-site at the visit. The transition characteristics of agricultural landscape patterns as represented in abandoned land, and orchards are analyzed from a local perspective.

In diabetic foot infections (DFI), the clinically virulence of skin commensals are generally pre-sumed to be of low virulence. In this single-center study, we divided the wound isolates into two groups: skin commensals (coagulase-negative staphylococci, micrococci, corynebacteria, cutibacteria); and, pyogenicpathogenic pathogens, and followed the patients for ≥ 6 months. In this retrospective study among 1,018 DFI episodes (392 [39%] with osteomyelitis), we identified skin commensals as the sole culture isolates (without accompanying pyogenicpathogenic patho-gens) in 54 cases (5%). After treatment (antibiotic therapy [median of 20 days], hyperbaric oxy-gen in 98 cases [10%]), 251 episodes (25%) were clinical failures. Group comparisons between those growing only skin commensals and controls found no difference in clinical failure (17% vs 24 %, p=0.23) or microbiological recurrence (11% vs 17 %, p=0.23). The skin commensals were mostly treated with non-beta-lactam oral antibiotics. In multivariate logistic regression analysis, isolation of only skin commensals was not associated with failure (odds ratio 0.4, 95% confi-dence interval 0.1-3.8). Clinicians might wish to consider these isolates as potential pathogens when selecting a targeted antibiotic regimen, which may equally base on oral non-beta-lactam antibiotic agents susceptible to the corresponding skin pathogens.

The normal growth and development of skeletal muscle is essential for the health of the body. The regulation of skeletal muscle by intestinal microorganisms and their metabolites has been continuously revealed. Acetate is the predominant short-chain fatty acid synthesized by gut microbiota through the fermentation of dietary fiber, however, the underlying molecular mechanisms governing the interaction between acetate and skeletal muscle during rapid growth stage remain to be further elucidated; Here, specific pathogen-free (SPF) mice, germ-free (GF) mice, and germ-free mice supplemented with sodium acetate (GS) were used to evaluate the effects of acetate on skeletal muscle growth and development of young mice with gut microbiota deficiency; We found the concentration of serum acetate, body mass gain, succinate dehydrogenase activity and expression of myogenesis maker gene of skeletal muscle in the GS group was higher than GF group following sodium acetate supplement. Furthermore, the transcriptome analysis revealed that acetate activated biological processes regulating skeletal muscle growth and development in GF group that are inhibited due to gut microbiota deficiency. In vitro experiment, we proved that acetate up-regulated Gm16062 to promote skeletal muscle cell differentiation; Overall, our findings proved that acetate promote skeletal muscle growth and development in young mice via increase Gm16062 expression.

This article describes a simple Susceptible Infected Recovered (SIR) model fitting with COVID-19 data for the month of march 2020 in New York (NY) state. The model is a classical SIR, but is non-autonomous; the rate of susceptible people becoming infected is adjusted over time in order to fit the available data. The death rate is also secondarily adjusted. Our fitting is made under the assumption that due to limiting number of tests, a large part of the infected population has not been tested positive. In the last part, we extend the model to take into account the daily fluxes between New Jersey (NJ) and NY states and fit the data for both states. Our simple model fits the available data, and illustrates typical dynamics of the disease: exponential increase, apex and decrease. The model highlights a decrease in the transmission rate over the period which gives a quantitative illustration about how lockdown policies reduce the spread of the pandemic. The coupled model with NY and NJ states shows a wave in NJ following the NY wave, illustrating the mechanism of spread from one attractive hot spot to its neighbor.

K-band radar waves have high penetration and low attenuation coefficients. However, the wavelength of this radar wave is relatively short; thus, designing and preparing both broadband and wide-angle radar wave absorbers in this band presents considerable challenges. In this study, a resin-based K-band radar wave absorber with a biomimetic lotus leaf structure was designed and formed by UV curing. Here, microscale lotus leaf papillae and antireflection structures were prepared using a DLP 3D printer, and the contact angle between the material and water droplets was increased from 56° to 130°. In addition, the influence of the geometric parameters of the lotus leaf antireflection structure on the electromagnetic absorption performance and mechanical strength was investigated. After simulation optimization, the maximum electromagnetic loss of the lotus leaf structure 3D printed sample was −32.3 dB, and the electromagnetic loss was below −10 dB in the 20.8–26.5 GHz frequency range. When the radar incidence angle was 60°, the maximum electromagnetic loss was still less than −10 dB. The designed lotus leaf structure has a higher mechanical energy absorption per unit volume (337.22 KJ/m3) and per unit mass (0.55 KJ/Kg) than commonly used honeycomb lightweight structures during the elastic deformation stage, and we expect that the designed structure can be used as an effective lightweight material for K-band radar stealth.

Honey has been employed for the treatment of wounds and diseases for ancient time, thanks to its antimicrobial and curative properties. This study aims to present the biochemical characteristics, including the amount of sugar, total phenols, phenolic chemicals, antioxidant properties, and antibacterial activities of a specific type of French honey (Sologne summer forest) in comparison with a manuka honey. According to our findings, the Manuka honey tested has 23% fewer polyphenols total than Sologne summer forest honey. The results showed that the Sologne summer honey had a different polyphenols profile than Manuka honey with specific polyphenol like p- Hydroxybenzoic acid. Additionally, the antioxidant activity of the two honeys is comparable (9 μmole Trolox.g-1 honey). Furthermore, the antibacterial activity of the two honeys is comparable against Pseudomonas aeruginosa and Staphylococcus aureus. Our research indicates for the first time that there are significant nutritional and biological potentials for a French honey from the Sologne summer forest.

Substantial reductions of the human and economic activities like road traffic for several months in 2020 were one of the consequences of the Coronavirus disease. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown over 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5) as well as on land surface temperature (LST), and the surface urban heat island intensity (SUHII), using satellite, modelled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change of the variables under study. In general, the results indicate a significant decrease in NO2 concentrations in most of the studied cities compared to the reference period 2015-2019. However, reductions could not be attributed to mobility changes like less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown mainly influenced by the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar as the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. Therefore, single city case studies may be misleading.

Symmetry concepts in parametrized dynamical systems may reduce the number of external parameters by a suitable normalization prescription. If, under the action of a symmetry group G, parameter space A becomes a (locally) trivial principal bundle, A ~ A/G x G, then the normalized dynamics only depends on the quotient A/G. In this way, the dynamics of fractional variables in homogeneous epidemic SI(R)S models, with standard incidence, absence of R-susceptibility and compartment independent birth and death rates, turns out to be isomorphic to (a marginally extended version of) Hethcote's classic endemic model, first presented in 1973. The paper studies a 10-parameter master model with constant and I -linear vaccination rates, vertical transmission and a vaccination rate for susceptible newborns. As recently shown by the author, all demographic parameters are redundant. After adjusting time scale, the remaining 5-parameter model admits a 3-dimensional abelian scaling symmetry. By normalization we end up with Hethcote's extended 2-parameter model. Thus, in view of symmetry concepts, reproving theorems on endemic bifurcation and stability in such models becomes needless.

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

The authors previously found a model of universal quantum computation by making use of the coset structure of subgroups of a free group $G$ with relations. A valid subgroup $H$ of index $d$ in $G$ leads to a \lq magic' state $\left|\psi\right\rangle$ in $d$-dimensional Hilbert space that encodes a minimal informationally complete quantum measurement (or MIC), possibly carrying a finite \lq contextual' geometry. In the present work, we choose $G$ as the fundamental group $\pi_1(V)$ of an exotic $4$-manifold $V$, more precisely a \lq small exotic' (space-time) $R^4$ (that is homeomorphic and isometric, but not diffeomorphic to the Euclidean $\mathbb{R}^4$). Our selected example, due to to S. Akbulut and R.~E. Gompf, has two remarkable properties: (a) it shows the occurence of standard contextual geometries such as the Fano plane (at index $7$), Mermin's pentagram (at index $10$), the two-qubit commutation picture $GQ(2,2)$ (at index $15$) as well as the combinatorial Grassmannian Gr$(2,8)$ (at index $28$) , (b) it allows the interpretation of MICs measurements as arising from such exotic (space-time) $R^4$'s. Our new picture relating a topological quantum computing and exotic space-time is also intended to become an approach of \lq quantum gravity'.

Recently, in a previous study, we have experimentally shown the existence of an optimal injected steam mass flow rate, per unit length, ϕopt, which produces the maximal recovery of con- densate in a preformed steam chamber with an elliptical cross section of horizontal semi-major axis. Mutatis mutandis, in this work we present experimental studies in preformed steam chambers, one elliptical and the other circular. In both cases, we also have found the existence of unique optimal values. These configurations try to recreate the steam condensation, at a given time lapse, as it would occur during the growth stage of the steam-assisted gravity drainage (SAGD) process, a method used in the recovery of heavy and extra-heavy oil from homogeneous reservoirs. Finding the optimal mass flow rates in actual recovery process could become useful in the design of optimized SAGD processes.

In this study, an experimentally validated computational model was developed to investigate the hydrodynamics in a rotor-stator vortex RVR agglomeration reactor having a rotating disc at the centre with two shrouded outer plates. A numerical simulation was performed using a simplified form of the reactor geometry to compute the 3D flow field in batch mode operations. Thereafter, the model was validated using data from a 2D Particle Image Velocimetry (PIV) flow analysis performed during the design of the reactor. Using different operating speeds—70, 90, 110 and 130 rpm, the flow fields were computed numerically followed by a comprehensive data analysis. The simulation results showed separated boundary layers on the rotating disc and the stator. The flow field within the reactor is characterized by a rotational plane circular forced vortex flow in which the streamlines are concentric circles with a rotational vortex. Overall, the results of the numerical simulation demonstrate a fairly good agreement between the CFD model and the experimental data as well as the available theoretical predictions. The swirl ratio β was found to be approximately 0.4044, 0.4038, 0.4044 and 0.4043 for operating speeds of N=70, 90, 110 and 130 rpm respectively. In terms of the spatial distribution, the turbulence intensity and kinetic energy are concentrated on the outer region of the reactor while the axial velocity showed a decreasing intensity towards the shroud. However, a comparison of the CFD and experimental predictions of the tangential velocity and the vorticity amplitude profiles shows that these parameters were under-predicted by the experimental analysis which could be attributed to some of the experimental limitations rather than the robustness of the CFD model or numerical code.

For 80 years high-intensity focused ultrasound (HIFU) has been a significant area for medical research. It is a non-invasive procedure which causes cell death in a highly localised area at a defined distance from the transducer. Since 2000, the clinical indications have broadened considerable as the technology has improved. This review looks back at the history of HIFU and the current clinical indications.

Maternal obesity and over/undernutrition can have a long-lasting impact on offspring health during critical periods in the first 1000 days of life. Children born to mothers with obesity have reduced immune responses to stimuli which increase susceptibility to infections. Recently, maternal western-style diets (WSD), high in fat and simple sugars, have been associated with skewing neonatal immune cell development, and recent evidence suggests that dysregulation of innate immunity in early life has long-term consequences on metabolic diseases and behavioral disorders in later life. Several factors contribute to abnormal innate immune tolerance or trained immunity, including changes in gut microbiota, metabolites, and epigenetic modifications. Critical knowledge gaps remain regarding the mechanisms whereby these factors impact fetal and postnatal immune cell development, especially in precursor stem cells in bone marrow and fetal liver. Components of the maternal microbiota that are transferred from mothers consuming a WSD to their offspring are understudied and identifying cause and effect on neonatal innate and adaptive immune development needs to be refined. Tools including single-cell RNA-sequencing, epigenetic analysis, and spatial location of specific immune cells in liver and bone marrow are critical for understanding immune system programming. Considering the vital role of immune function plays in offspring health, it will be important to understand how maternal diets can control developmental programming of innate and adaptive immunity.

Anxiety in older adults is a prevalent yet under-recognized condition associated with significant societal and individual burdens. This study used a machine learning approach to compare the relative importance of 57 risk and protective factors for anxiety symptoms in a population-representative sample of middle-aged and older European adults (N = 65,684; ages 45–103 years; 55.7% women; 15 countries represented). Results revealed loneliness and self-rated poor health as primary risk factors (Nagelkerke R2 = .272), with additional predictive contributions from country of residence, functional limitations, financial distress, and family care burden. Notably, follow-up analysis showed that none of 16 social network variables were associated with loneliness; rather, cohabitating with a partner/spouse was most strongly associated with reduced loneliness. Further research is needed to elucidate directional associations between loneliness and anxiety (both general and sub-types). These findings underscore the imperative of addressing loneliness for mitigating anxiety and related mental health conditions among aging populations.

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

This paper presents a script that classify spatial patterns of residential urban growth using a morpho-structural approach. The script performs a combination of variography analysis and morphological closings over buildings possessing a residential function in 2002 and 2017 within a region located in southern France named Centre-Var. The different bounding regions then allow classifying new residential buildings into different categories according to their degrees of clustering/scattering and to their locations regarding existing urban areas. Preliminary results show that this protocol is able to provide useful insights regarding the degree of contribution of each new residential building to different patterns of urban growth (clustered infill, scattered infill, clustered edge-expansion, scattered edge-expansion, clustered leapfrog and scattered leapfrog). Open-access to the script and to the test region data is provided.

Introduction: A dual malignancy with both Ewing Sarcoma and Prostate Adenocarcinoma has not been reported in the English literature. We report a case of simultaneous diagnosis of Ewing sarcoma and prostate adenocarcinoma with profound clinical manifestation. Case presentation: A 53-year-old male with advanced metastatic prostate cancer (Gleason-9) admitted with classical presentation of cauda equina syndrome including incontinence, back pain, and paresis following bilateral nephrostomy insertion for the treatment of bilateral renal hy-dronephrosis. The patient was diagnosed with an epidural abscess at the level of L5-S1 and an emergency surgical spine decompression was performed. No abscess was found, and pathology results showed a concomitant primary Ewing sarcoma in the spine. Conclusions: Very rare occurrences of a dual primary malignancy, in this case, Ewing sarcoma and prostate adenocarcinoma, should be kept in mind in patients suffering from complex clinical course of malignancies.

Rice has become the second major food among rural people. It is one of the most nutrient and low-cost food available in Asia. Rice is composed of two major subspecies as Japonica and Indica and it belongs to the Poaceae family. The World Bank predicts that rice demand will grow 51% faster than population growth in 2025. It is high time to develop a model which predicts the type of infected paddy leaf and avoids the loss of grains. In this paper, the proposed hybrid CNN model, three CNN networks with different layer properties are trained parallel. The extracted feature from these CNN networks is combined to provide the classification of the type of infected leaf. Fieldwork was carried and about 340 samples are collected from five different types of classes. The proposed hybrid model was tested with both the fieldwork dataset and also with an available dataset on the internet. The experimental results show that the proposed model outperforms the other CNN network and yields an accuracy value of 98%, a precision value of 95%, and a misclassification rate of 4% respectively.

Mass insect rearing can have a range of applications, for example in biological control of insects. Since the performance of released biological control agents determines efficacy, the competitive fitness of insects post release is a key variable. Here, we tested whether inoculation with a gut symbiont, Enterobacter cloacae, and gnotobiotic rearing of larvae could improve insect growth and male competitive fitness of a transgenic diamondback moth, which has shown variation in fitness when reared in different insectaries. All larvae were readily infected with the focal symbiont. Under gnotobiotic rearing pupal weights were reduced and there was a marginal reduction in larval survival. However, gnotobiotic rearing substantially improved the fitness of transgenic males. In addition, in gnotobiotic conditions, inoculation with the gut symbiont increased pupal weights and male fitness, increasing the proportion of transgenic progeny from 20 to 30% relative to symbiont-free insects. Gnotobiotic conditions may improve the fitness of transgenic males by excluding microbial contaminants, while symbiont inoculation could further improve fitness by providing additional protection against infections, or by normalizing insect physiology. The simple innovation of incorporating antibiotic into diet, and inoculating insects with symbiotic bacteria that are resistant to that antibiotic, could provide a readily transferable tool for other insect rearing systems.

Greenhouse gas (GHG) emissions from agriculture are significant contributors to global change. We experimentally manipulated biogeochemical control points of irrigation and nitrogen (N) to examine management strategies that could impact GHG flux, i.e., carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and soil physiochemical changes over a growing season in an arid New Mexico sorghum (Sorghum bicolor (L.) Moench) cropping system. Sorghum is water and N efficient and amenable to environmental stress. Interrogating how crop systems perform in intense heat, aridity and ultraviolet stress of the southwestern US climate can inform future management in areas that produce more food currently, but that will undergo these stresses in the near future. Water was applied at regionally typical rates, or at ~30% below those rates. Timing N to plant needs may reduce N loss and N2O emissions, and we tested this hypothesis by adding equal amounts of fertilizer to all plots, with half receiving all fertilizer at planting versus plots fertilized at 50:50 planting and 30 days post-planting. Gas flux from soil was analyzed via FTIR. More biomass was harvested from the fully irrigated plots; N timing did not significantly affect biomass. Soil pH fluctuated throughout the season in response to both treatments. Carbon dioxide emissions significantly increased in fully irrigated plots through time. Methane uptake was depressed by full irrigation. Nitrous oxide flux was lower in split N plots, but N2O emissions were not impacted by reduced irrigation. These results suggest that arid adapted crops can maintain economically feasible yield, and biogeochemical monitoring within a growing season can help manage for GHG flux.

Organic electrophoretic coatings have gained significant attention due to their ability to provide a uniform and controlled coating thickness, high coating adhesion, and excellent corrosion protection properties. In this work, to investigate the aging behaviors of an organic electrophoretic coating for magnesium alloys, water absorption kinetics curves of the coatings after immersion in 3.5 wt.% NaCl at 20℃ and 40℃ were measured, and parameters such as the saturated water absorption and saturation time of the free film coatings were fitted to determine the densification evolution of the organic coatings. A tensile test was used to test the tensile strength of the organic coating during service to determine the evolution of the strength and toughness of the organic coating. The evolution of wet adhesion of organic coatings with service time was tested by ASTM D4541-02. The impedance spectra of the organic coatings under the above conditions were detected by EIS, and finally, the failure behavior of the organic coatings under immersion was analyzed.

Telemedicine is the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes has the risk of confidentiality, ownership identity, and authenticity. In this paper, a data hiding technique for ePHI/R is proposed. The color information in the cover image is used for key generation, and stego-images are produced with ideal case. As a result, the whole stego-system is perfectly secure. This method includes the features of watermarking and steganography techniques. The method is applied to radiographic images. For the radiographic images, this method resembles watermarking, which is an ePHI/R data system. Experiments show promising results for the application of this method to radiographic images in ePHI/R for both transmission and storage purpose.

Development and engineering of protein crystals regarding mechanical stability and crystallizability occurs on a small scale. Later in the process chain of industrial production however, filtration properties are important to separate the crystals from mother liquor. Many protein crystals are sensitive to mechanical stress which is why it is important to know the filtration behavior early on. In this study we analyze settling and filtration behavior of isometric, rod-like and needle shaped lysozyme and rod-like alcohol dehydrogenase (ADH) crystals on a small scale using an optical analytical centrifuge. Needle shaped lysozyme and rod-like ADH crystals show compressible material behavior. With the results from settling and filtration experiments the flux density function is calculated and modeled which can be used to describe the whole settling and permeation process in dependency of the solids volume fraction. This is also an issue for simulations of industrial processes.

Recent algorithmic-based research in the stock market has predominantly focused on ultra-high-frequency trading and index estimation. We developed an improved algorithm to address the need for a low-frequency, real-world trading model to build on the existing high hit-ratio and low maximum drawdown. We utilized established price indicators, Stochastic and Williams %R, and introduced a volume factor to increase the model's safety to enhance the model's performance. This improved algorithm demonstrated superior returns while maintaining high hit-ratio and low maximum drawdown. Specifically, we leveraged the existing algorithm to trade using 2X and 3X signals, incorporating volume data, the 52-week average, standard deviation, and other factors. The data set comprised SPY ETF price and volume from 2010 to 2023, covering over 13 years. Our enhanced algorithmic trading model outperformed both the benchmark and previous results, achieving a hit rate of over 90%, a maximum drawdown of less than 1%, an average of 1.5 trades per year, a total return of +519.3%, and an annualized return (AnnR) of +15.1%. The analysis demonstrates that the model's simplicity, ease of application, and comprehensibility can assist investors in making informed investment decisions albeit the past performance does not guarantee future returns.

This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected one-minute and critical soil parameters—humidity, temperature, pH values, nitrogen (N), phosphorus (P), and potassium (K)—essential for assessing soil health and optimizing crop growth. Kendall's correlations were computed to rank these parameters for utilization in hybrid ML techniques. Various ML algorithms including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Tree (DT), Random Forest (RF), and Logistic Regression (LR) were evaluated. A novel hybrid algorithm, 'Bayesian Optimization with KNN', was introduced to combine multiple ML techniques and enhance predictive performance. The hybrid algorithm demonstrated superior results with 95% accuracy, precision, and recall, and an F1 score of 94%, while individual ML algorithms achieved varying results: KNN (80% accuracy), SVM (82%), DT (77%), RF (80%), and LR (81%) with differing precision, recall, and F1 scores. This hybrid ML approach proved highly effective in predicting tomato crop diseases in natural environments, underscoring the synergistic benefits of IoT and advanced ML techniques in optimizing agricultural practices.

Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions are of interests to engineers, mathematicians, and physicists from the last several decades. With a motivation of developing computationally efficient models of brain dynamics to use in designing control-theoretic neurostimulation strategies, we have developed a novel data-driven approach in a long short-term memory (LSTM) neural network architecture to predict the temporal dynamics of complex systems over an extended long time-horizon in future. In contrast to recent LSTM-based dynamical modeling approaches that make use of multi-layer perceptrons or linear combination layers as output layers, our architecture uses a single fully connected output layer and reversed-order sequence-to-sequence mapping to improve short time-horizon prediction accuracy and to make multi-timestep predictions of dynamical behaviors. We demonstrate the efficacy of our approach in reconstructing the regular spiking to bursting dynamics exhibited by an experimentally-validated 9-dimensional Hodgkin-Huxley model of hippocampal CA1 pyramidal neurons. Through simulations, we show that our LSTM neural network can predict the multi-time scale temporal dynamics underlying various spiking patterns with reasonable accuracy. Moreover, our results show that the predictions improve with increasing predictive time-horizon in the multi-timestep deep LSTM neural network.

Prostate cancer is a highly heterogeneous disease, and mortality is mainly due to metastases, but the initial steps of metastasis have not been well characterized. We have performed integrative whole exome sequencing and transcriptome analysis of primary prostate tumor foci and corresponding lymph node metastases (LNM) from 43 patients enrolled in clinical trial. We present evidence that while there are some cases of clonally independent primary tumor foci, 87% of primary tumor foci and metastases are descended from a common ancestor. We demonstrate that genes related to oxidative phosphorylation are upregulated in LNM and in African-American patients relative to White patients. We further show that mutations in TP53, FLT4, EYA1, NCOR2, CSMD3, and PCDH15 are enriched in prostate cancer metastases. These findings were validated in a meta-analysis of 3,929 primary tumors and 2,721 metastases and reveal a pattern of molecular alterations underlying the pathology of metastatic prostate cancer. We show that LNM contain multiple subclones that are already present in primary tumor foci. We observed enrichment of mutations in several genes including understudied genes such as EYA1, CSMD3, FLT4, NCOR2, and PCDH15 and find that mutations in EYA1 and CSMD3 are associated with poor outcome in prostate cancer.

This study aimed to use remote sensing and GIS to detect changes in surface water and wetlands in the Kumasi Metropolis over a period of 20 years (2002-2022). Landsat images were processed using the QGIS software, and the Maximum Likelihood Algorithm was used to perform supervised classification of land use land cover, while raster calculator aided in detecting wetlands by calculation for NDWI, MNDWI, and AWEI. The results showed that the majority of the landscape in the Kumasi metropolis was made up of built-up areas (79.4%), followed by agricultural lands (13.3%) and wetlands (7.3%). Over the 20-year period, built-up areas had gained 20.7% of the total landscape, while agricultural lands and wetlands had lost 16.7% and 4.0%, respectively. All water index methods recorded an increase in non-water cover and a loss of water cover over the period, with surface water decreasing by 5% and non-water land cover increasing by 5%. The study concludes that there have been significant changes in wetlands and surface water land use and land cover within the Kumasi Metropolis over the past 20 years, and recommends the enforcement of legislation on surface water protection in the area to protect wetlands

The cooling of server components has been continuously developed over the past few years in order to meet the increasing cooling requirements of server component manufacturers such as for the processor chips. The growth in performance and power density increases the cooling demand. These requirements directly influence the energy consumption and performance of the hardware. To gain a better understanding of the historical evolution and possible future technology development paths in the field of data center cooling, a patent analysis method was used. The focus is on previous and current development priorities and possible research gaps within the server and computer room levels. The European patent database was selected as data source. To determine relevant patents, the search terms for various cooling technologies were developed iteratively. After the patent extraction for the period 2000 - 2023 (earliest priority year), the search results were classified and analysed. Most of the patents deal with air or liquid cooling. In the area of liquid cooling, the focus was on direct liquid cooling, followed by total liquid cooling. Since 2015 a technological shift from air to liquid cooling can be identified on the level of patent activities. In this context, the patent groups with focus on “constructional details for different types of electric apparatus” and “electrical digital data processing” have the largest share of patents. In addition, the technology focus of the TOP 10 patent applicants was in the field of liquid cooling. In conclusion from the patent analysis, it can be derived that liquid cooling will continue to gain in importance in the future and could also be combined with other approaches in the form of hybrid cooling. However air cooling may still be relevant, even if the main cooling load is handled by liquid-based approaches. At the same time, the optimisation potential for air cooling seems to have been largely exploited in comparison to liquid cooling, as can be seen from the falling number of the patent applications.

A Friedmann-Lemaitre-Robertson-Walker space-time model with all curvatures k=0,±1 is explored in f(R,T) gravity. The solutions are obtained via the parametrization of the scale factor that leads to a model transiting from a decelerated universe to an accelerating one. The physical features of the model are discussed and analysed.

Single image deraining (SID) has shown its importance in many advanced computer vision tasks. Though many CNN based image deraining methods have been proposed, how to effectively remove raindrops while maintaining background structure remains a challenge that needs to be overcome. Most of the deraining work focuses on removing rain streaks, but in heavy rain images, the dense accumulation of rainwater or the rain curtain effect significantly interferes with the effective removal of rain streaks, and often introduces some artifacts that make the scene more blurry. In this paper, we propose a new network structure R-PReNet for single image deraining with good background structure maintaining. This framework fully utilizes the cyclic recursive structure of PReNet. Moreover, we introduce residual channel prior (RCP) and feature fusion modules for better deraining performance by focusing on background feature information. Compared with the previous methods, our method has significantly improvement effect on the rainstorm image with the artifacts removing and good visual detail restoring.

We analyze the behavior of relativistic spherical objects within the context of modified $f(R,T)$ gravity considering Tolman VI spacetime, where gravitational lagrangian is a function of Ricci scalar(R) and trace of energy momentum tensor(T) i.e,$ f(R,T)= R+ 2\beta T$, for some arbitrary constant $\beta$. For developing our model, we have chosen $\pounds_{m} = -p$, where $ \pounds_{m}$ represents matter lagrangian. For this investigation, we have chosen three compact stars namely PSR J1614-2230 [Mass=(1.97$\pm$ 0.4)M$_\odot$; Radius= 9.69$_{-0.02} ^{+0.02}$ Km] ,Vela X-1 [Mass=(1.77$\pm$ 0.08)M$_\odot$; Radius= 9.560$_{-0.08} ^{+0.08}$ Km] and 4U 1538-52 [Mass=(9.69)M$_\odot$; Radius= 1.97 Km]. In this theory the equation of pressure isotropy is identical to standard Einstein's theory. So all known metric potential solving Einstein's equations are also valid here. In this paper, we have investigated the effort of coupling parameter ($\beta$) on the local matter distribution. Sound of speed and adiabatic index are higher with grater values of $\beta$ while on contrary mass function and gravitational redshift are lower with higher values of $\beta$ . For supporting the theoretical results, graphical representation are also employed to analyze the physical viability of the compact stars.

Cancers of the brain and nervous system account for 1 in every 100 cancer diagnoses in the United States and about 0.3 million diagnoses globally, every year. Surgery, radiotherapy, and chemo-therapy constitute the standard of care. Despite advancements in diagnosis and treatment delivery, mortality rate for these cancers have remained steady for over three decades. Immunotherapy is an emerging fourth treatment modality which has been effective against several cancers but not brain cancers, such as glioblastoma, GBM. Here, we develop in vitro assays to quantify molecular readouts of cell death, cell migration and clonogenicity, and synopsize these as biophysical markers for the rapid evaluation of immune checkpoint inhibitors (ICI), durvalumab and pembrolizumab, alone and in combination with radiotherapy (radioimmunotherapy). We find different trends in their direct action on two GBM cell lines (T98G and U87), even in the absence of immune cells. Radiation alone, and pembrolizumab with radiation, both reduced (p < 0.05) cell-cell adhesion. This reduction suggests increased potential for local invasion. Our assays offer additional insights regarding ICIs, may enable evaluation of their potential efficacy, and could set the stage for pa-tient-specific radioimmunotherapy against brain cancers, engendering improved treatment out-comes.

Artisanal goldminers in Ghana are exposed to various levels and forms of health, safety and environmental threats. Without the required legislation and regulations, artisanal miners are responsible for their own health and safety at work. Consequently, understanding the probabilities of self-protection at work by artisanal goldminers is crucial. A cross-sectional survey of 500 artisanal goldminers was conducted to examine the probabilities of personal protective equipment use among artisanal goldminers in Ghana. The data was subjected to both descriptive and inferential statistics. Initial findings showed that personal protective equipment use among artisanal miners was 77.4%. Overall, higher probabilities of personal protective equipment use was observed among artisanal goldminers who work in good health and safety conditions as compared to artisanal miners who work in poor health and safety conditions. Also, personal protective equipment use was more probable among the highly educated artisanal goldminers, miners who regularly go for medical screening and the most experienced miners. Additionally, personal protective equipment use was more probable among artisanal miners who work in non-production departments and miners who work in the medium scale subsector. Inversely, personal protective equipment use was less probable among female artisanal miners and miners who earn more monthly income ($174 and above). To increase self-care and safety consciousness in artisanal mining, there is the need for a national occupational health and safety legislation in Ghana. Also, interventions and health promotion campaigns for better occupational conditions in artisanal mining should target and revise the health and safety related workplace programs and conditions