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The Internet ofVehicles (IoV) is a crucial technology for Intelligent Transportation Systems (ITS) that integrates vehicles with the Internet and other entities. The emergence of 5G and the forthcoming 6G networks presents an enormous potential to transform the IoV by enabling ultra-reliable, low-latency, and high-bandwidth communications. Nevertheless, as connectivity expands, cybersecurity threats have become a significant concern. The issue has been further exacerbated by the rising number of zero-day (0-day) attacks, which can exploit unknown vulnerabilities and bypass existing Intrusion Detection Systems (IDSs). In this paper, we propose Zero-X, an innovative security framework that effectively detects both 0-day and N-day attacks. The framework achieves this by combining deep neural networks with Open-Set Recognition (OSR). Our approach introduces a novel scheme that uses blockchain technology to facilitate trusted and decentralized federated learning (FL) of the Zero-X framework. This scheme also prioritizes privacy preservation, enabling both CAVs and Security Operation Centers (SOCs) to contribute their unique knowledge while protecting the privacy of their sensitive data. To the best of our knowledge, this is the first work to leverage OSR in combination with privacy-preserving FL to identify both 0-day and N-day attacks in the realm of IoV. The in-depth experiments on two recent network traffic datasets show that the proposed framework achieved a high detection rate while minimizing the false positive rate. Comparison with related work showed that the Zero-X framework outperforms existing solutions.

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The qualitative analysis of farmers’ use of Indigenous knowledge on climate change adaptation across farming systems and agroecological zones of Sierra Leone was conducted using a combination of interpretive phenomenological analysis, Focus Group Discussions, and participant observation, which was analyzed with a qualitative interpretative approach. Farmers respond to climate change through the use of wind and cloud patterns, animal and bird behavior, moon shape, and position of the sun to predict changes in temperature, intensity, drying up of rivers, and frequency of rainfall, as well as the incidence of pests and diseases. Other Indigenous knowledge used by farmers were rotational grazing, migration, crop-livestock integration, and the use of manure for composting with herbal and biological treatment for disease management. The study recommended that in the current context of climate change, the promotion of adaptation strategies should explore the interdependency of different knowledge systems and knowledge hybridity in agriculture.

This study investigates the impact of indigenous consortia of plant-growth-promoting rhizobacteria (PGPR) on the growth of wheat under drought stress and irrigation with treated municipal wastewater (TMWW). Six strains, identified as the most promising candidates, were used to develop two inoculant consortia. The consortium C1 consists of the PGPR strains Bacillus megateriumFR1.11, Brevibacterium frigoritoleransFR1.38, and Microbacterium azadirachtaeFR1.17, while the consortium C2 comprises Bacillus zhangzhouensis O3RR35, Pseudomonas koreensis O3RR25, and Pseudomonas azotoformansO3R15. The two selected consortia significantly improved wheat germination rates (GR), achieving up to 98.3% compared to 60% with single inoculation. The recorded inoculation effectiveness indices of consortium C1 and consortium C2 on wheat growth, denoted as Ic(1,2), indicated that under treated municipal water irrigation, Ic1ranged from 7 to 85% at 100% field capacity (FC) and from 10 to 44% at 40% FC. On the other hand, Ic2ranged from 55 to 213% at 100% FC and from 41 to 302% at 40% FC, suggesting a more favorable inoculation effect with consortium C2 compared to C1. Optimal conditions for wheat growth were estimated applying a statistical approach based on the Box–Behnken design (BBD) and response surface methodology (RSM). The considered factors included C2 inoculum size, TMWW and freshwater (FW) ratio, and soil field capacity. The stepwise screening methodology, combined with statistically based experimental designs, led to the development of an efficient consortium (C2) suitable for use as a biofertilizer tailored to semi-arid conditions and wastewater reuse in agriculture, particularly in arid and semi-arid areas.

In this work, it is designed and synthesized therapeutically active anti-urease agents based on 3-bromosulfanilamide-based acyl thioureas (4a-j)through reaction of brominated sulfanilamide with aromatic acids via isothiocyanate formation and characterized by using FT-IR, 1HNMR, 13C NMR and MS analysis. The freshly prepared compounds were screened for in vitro urease inhibition assay. The derivative 4awith an un-substituted phenyl group showed IC50value of 17.02 ± 0.011 against urease as compared to the standard thiourea (IC50= 21 ± 0.12 µM). Structure activity relationship (SAR) revealed that the electronic and positional effects of substituents on phenyl ring play important role for the inhibition of clinically important enzymes. Additionally, in silico investigation was carried out which demonstrated that the compounds have exhibited polar and nonpolar interaction with the crucial residues in the binding site of urease. The in vitroand in silico studies are in agreement as per kinetics and docking results indicating that the synthesized 3-bromosulfanilamide-based acyl thiourea derivatives may serve as potential hits for the discovery of new urease inhibitors.

•A low frequency of Vγ9Vδ2 T cells in AML is an independent predictor of poor clinical outcome.•These data provide a strong rationale for the development of consolidation protocols aimed at enhancing Vγ9Vδ2 T-cell responses.

Robots are being employed more as mediators between therapists and children with autism. This paper proposes a robot-based therapeutic method that uses the NAO robot, a developed mobile application called AutisPlay, a tablet, and a control laptop. The proposed method is implemented in therapeutic sessions at a local autism center. In this research, a study involving nine children diagnosed with autism spectrum disorder is conducted. The researchers and autism therapists agreed on the targeted academic skills. The main goal of this work is to assess the use of robots and mobile applications in improving the academic skills of children with autism. The obtained experimental results are analyzed using statistical measures such as the percentage of correct responses, informal observations of students’ attention to the robot, reported academic progress, and enjoyment of the therapy sessions. Further, the therapeutic sessions are customized to each child's response to the robot and mobile application. The children showed different engagement levels and a variety of progress and achievements. The experimental results show three children acquired the indicating skills, while the remaining children show slow progress in their skill acquisition. Furthermore, seven students enjoyed the interaction with the NAO robot and AutisPlay mobile app during therapy sessions.

The latest developments in virtual reality (VR) are gaining attention in education as they are expected to provide risk-free, hands-on learning experiences. However, the use of VR in laboratory settings is still in its early stages of adoption. Therefore, it remains unclear whether these technologies will be widely adopted to educate students in laboratories, as well as their advantages and disadvantages compared to traditional laboratories. This study aims to map the global scientific publications related to the use of VR for teaching in virtual laboratories. To achieve this, we analyze the global scientific landscape of publications related to the use of VR for teaching students in laboratories. We combined bibliometric and network analysis techniques to analyze the metadata of related research articles published between 1994 and 2022 indexed in the Web of Science Core Collection. Our findings show a rising trend, with almost 65% of all articles published between 2018 and 2022. Leading journals include the Journal of Chemical Education, Computers & Education, and Computers Applications in Engineering Education. Most publications are indexed in the research areas of Education & Educational Research, Computer Science, and Engineering. The United States leads in publications, collaborating mostly with Denmark, Spain, and the United Kingdom. The University of California is the top organization in publications, with Griffith University facilitating knowledge exchange among organizations. By providing an overview of publications related to the use of VR in laboratory education, we hope that this study will be of interest to researchers, educators, and students.

In the present scenario, Sidelobe Level (SLL) is treated as the most important parameter of the antenna array as it assists in suppressing interference and adjacent noise in wireless communication systems. As the maximum SLL value examined higher power wastage in unwanted signal direction, a transmitter of the communication system encounters major hitches. In this article, the optimum design of four various groups of Concentric Circular Antenna Array (CCAA) of the array antenna has been to lower SLL as much as possible. Optimum beam pattern synthesis of the proposed array antenna has been carried out by optimizing the standardized current distribution of the array antenna elements, all elements placed with fixed inter-element spacing. The work proposed algorithm is the Jaya optimization algorithm, the main aim of this technique is to describe the credibility of a currently chosen human social behaviour-based optimization algorithm known as Jaya. This very easy algorithm with lower complexity to synthesize Concentric Circular Antenna Array (CCAA) which is thoroughly utilized in the present scenario communication systems. The obtained results of the Jaya algorithm compared with Particle Swarm Optimization (PSO) and previously published articles. The Jaya algorithm achieved an improved side lobe level reduction as correlated to the PSO algorithm, finally getting results to examine the improved ability of Jaya as the best suitable method and achieve better sidelobe level suppression.

Parkinson’s disease (PD) carries substantial psychosocial burden. Using a database of responses by people with PD reporting up to five “most bothersome problems,” we identified 225 fear-based verbatims, which were organized using the framework method into 26 categories. Commonly-reported fears included uncertainty of progression (n?=?60, 26.7%), fear of future cognitive impairment (n?=?24, 10.7%) and fear of becoming a burden on others (n?=?23, 10.2%). Fears in PD are wide-ranging and can constitute the most bothersome aspect of the condition. These data can be used to design interventions to lessen the psychosocial burden of PD.

This research project aims to increase the employees' cybersecurity awareness by proposing a training program that consists of pre-game and post-game phishing attacks, pre-game and post-game surveys, and an interactive zero-day game with embedded threat scenarios. Furthermore, we propose five flowcharts that simulate common cyberattacks. The zero-day game consists of five levels. The first level trains employees in using complex passwords. Two levels cover the social engineering attacks: one level trains employees about suspicious links and online survey tricks, while the other level trains players about the organization's security policies. The fourth level educates employees about malware spread via repackaged fake applications. The last level educates employees about phishing email attacks. Furthermore, we developed a chatbot inside the game to aid users in playing the different game levels. Additionally, two surveys and two phishing attacks are carried out to assess the employees' knowledge level of cybersecurity threats. The zero-day cybersecurity awareness program is applied to twenty-three employees. Experimental results indicate that the zero-day cybersecurity awareness program is more engaging and effective than traditional awareness programs. Results also indicate that the proposed program accurately measures and improves the employees' cybersecurity awareness level.

A key barrier to the development of vaccines that induce broadly neutralizing antibodies (bnAbs) against human immunodeficiency virus (HIV) and other viruses of high antigenic diversity is the design of priming immunogens that induce rare bnAb-precursor B cells. The high neutralization breadth of the HIV bnAb 10E8 makes elicitation of 10E8-class bnAbs desirable; however, the recessed epitope within gp41 makes envelope trimers poor priming immunogens and requires that 10E8-class bnAbs possess a long heavy chain complementarity determining region 3 (HCDR3) with a specific binding motif. We developed germline-targeting epitope scaffolds with affinity for 10E8-class precursors and engineered nanoparticles for multivalent display. Scaffolds exhibited epitope structural mimicry and bound bnAb-precursor human naive B cells in ex vivo screens, protein nanoparticles induced bnAb-precursor responses in stringent mouse models and rhesus macaques, and mRNA-encoded nanoparticles triggered similar responses in mice. Thus, germline-targeting epitope scaffold nanoparticles can elicit rare bnAb-precursor B cells with predefined binding specificities and HCDR3 features.

•CD33/CD123 NANOBODY TCE kills single and double-positive cells, outperforming single-targeting TCE in a subset of AML samples.•CD33/CD123-TCE efficiently kills AML cells in a mouse model and targets cells in nonhuman primates without signs of cytokine release.

In this study, Dynamic Shear Rheometer (DSR) and Fourier Transform Infrared (FTIR) spectroscopy tests were performed on 35-50 and 70-100 penetration-graded asphalts. Both tests were performed on specimens at three different ageing states: unaged, short-term aged using the standard rolling thin film oven (RTFO) device, and long term aged by placing RTFO residue in the pressure aging vessel (PAV) apparatus. The tests were accomplished to quantify how ageing affects the results of both tests, namely the complex shear modulus for the DSR test and the carbonyl, sulfoxide, and ageing indices for the FTIR spectroscopy test. Both sets of measurements confirm that the harder asphalt stays harder than the softer asphalt after undergoing ageing, but the rate of hardness is higher for the softer asphalt. For instance, on average, PAV ageing was found to increase the amplitude of the shear complex modulus, from the unaged state, by 4.3 times and by 6.2 times for the 35-50 and 70-100 asphalts, respectively. It was also found that ageing decreases the phase angle for asphalt and the decrease is more pronounced for the softer asphalt (70-100) than the harder one (35-50). This was attributed to more maltenes content in the softer asphalt that transform into asphaltenes during ageing. Correlation coefficient between FTIR signals from the same samples revealed that FTIR spectroscopy as used in this research has an excellent repeatability. The repeatability was also confirmed using measures of dispersion such as the coefficient of variation, which was found not to exceed the 1.2%. The 35-50 asphalt was found to have more C=O and S=O links than the 70-100 asphalt since it showed more absorbance in the carbonyl and sulfoxide bands. These links are thought to make the asphalt physically harder. An analysis of variance study revealed that ageing is a statistically significant factor as measured using ageing indices calculated from FTIR spectroscopy data with the index AIFTIR being the most sensitive to ageing among all considered indices. Empirical power equations with high coefficient of determination values were established to predict DSR results from FTIR index values, which was possible since both types of measurements show the same trend with ageing.

Understanding the interplay between bright and dark exciton states is crucial for deciphering the luminescence properties of low-dimensional materials. The origin of the outstanding brightness of lead halide perovskites remains elusive. Here, we analyze temperature-dependent time-resolved photoluminescence to investigate the population mixing between bright and dark exciton sublevels in individual CsPbBr3nanocrystals in the intermediate confinement regime. We extract bright and dark exciton decay rates and show quantitatively that the decay dynamics can only be reproduced with second-order phonon transitions. Furthermore, we find that any exciton sublevel ordering is compatible with the most likely population transfer mechanism. The remarkable brightness of lead halide perovskite nanocrystals rather stems from a reduced asymmetry between bright-to-dark and dark-to-bright conversion originating from the peculiar second-order phonon-assisted transitions that freeze bright–dark conversion at low temperatures together with the very fast radiative recombination and favorable degeneracy of the bright exciton state.

Medical research has focused on improving diagnosis through medical imaging in recent decades. Computer Assisted Diagnosis (CAD) systems have been developed to help doctors identify suspicious areas of interest, particularly those with cancer-like characteristics. CAD systems employ various algorithms and techniques to extract important numerical measurements from medical images that clinicians can use to evaluate patient conditions. This study proposes a statistical classification-based approach to efficient brain cancer detection. The proposed approach operates in three stages: first, Gradient Vector Flow (GVF) Snake models and mathematical morphology techniques retrieve regions of interest. The second stage characterizes these regions using morphological and textural parameters. Finally, a Bayesian network uses this description as input to identify malignant and benign cancer classes. We also compared the performance of the Bayesian network with other popular classification algorithms, including SVM, MLP, KNN, Random Forest, Decision Tree, XGBoost, LGBM, Gaussian Process, and RBF SVM. The results showed the superiority of the Bayesian network for the task of brain tumor classification. The proposed approach has been experimentally validated, with a sensitivity of 100% and a classification accuracy of over 98% for tumors, demonstrating the high efficiency of cancer cell segmentation.

The phycological diversity of Dictyotales, macroalgal species with great biotechnological potential, is still unknown in Alagoas, Brazil. Therefore, we carried out a phenological survey of Dictyotales and provided ecological comments. Samples were collected at four stations during the dry season (November and December 2013 and January 2014) and the rainy season (May–July 2014). Eighteen species were identified, five of which were recorded for the first time in Alagoas (Canistrocarpus crispatus, Dictyopteris jamaicensis, D. polypodioides, Dictyota pinnatifida and Padina antillarum). Canistrocarpus cervicornis and Dictyopteris delicatula made the highest biomass contribution in all the stations in both seasons. The stations studied showed differences between them, except for stations with less anthropogenic interference and offer greater local species diversity. This highlights that in Maragogi and Pajuçara Stations aspects of urbanization could negatively affect the Dictyotales community, such as the disappearance of endemic species. Sporophyte phase and fertility showed differences between stations and seasons. In both analyses, the rainy season collected the most of the records. The analysis of richness showed that the rainy season had higher values. Thus, the rainy season is the time when Dictyotales invest in reproduction and we find higher biodiversity. Therefore, phenological studies, biodiversity research and commercial research of Dictyotales should take place during the rainy season.

Language is not abstracted from reality but responds to emerging changes. Arabic-Hebrew contact among Palestinians in Israel offers a fertile background for a study of sociopolitical conflicts, given the unique civil and national status of Palestinian citizens of Israel, a polity defined and perceived as a Jewish state. The current article focuses on Arabic-Hebrew contact in Israel. More specifically, it describes Hebraic, the formation of a “new variety” – Arabic mixed with Hebrew in the linguistic repertoire of Palestinian Arabs, citizens of Israel. The linguistic characteristics and the motives that led to its creation are described. The sociolinguistic reflections in relation to identity are introduced to provide explanations for its formation and its meaning.

The Child Health and Mortality Prevention Surveillance (CHAMPS) Network programme undertakes post-mortem minimally invasive tissue sampling (MITS), together with collection of ante-mortem clinical information, to investigate causes of childhood deaths across multiple countries. We aimed to evaluate the overall contribution of pneumonia in the causal pathway to death and the causative pathogens of fatal pneumonia in children aged 1–59 months enrolled in the CHAMPS Network.

AbstractThis research delves into the evolving landscape of sport media broadcasting in the MENA region, emphasizing the dynamics of sports program consumption in Algeria. It highlights the rising influence of Over-The-Top (OTT) technologies, particularly focusing on cost-effective IPTV services. The study aims to unravel the shifts in sports event consumption, employing the Technology Acceptance Model (TAM) alongside a mixed-methods approach surveying both technophile and technophobic individuals. This investigation seeks to uncover distinct consumption trends and underlying motivations driving media choices in these divergent groups. Key findings indicate a widening disparity in consumption patterns and preferred technological mediums between tech-savvy and tech-averse individuals. Moreover, it underscores the critical impact of socio-economic factors in escalating the adoption of affordable or free sports program mediation, whether through legitimate or illicit means. Additionally, the study sheds light on emerging sports program mediation forms, predicting future broadcaster adaptations to cater to the needs of the digitally connected new generation.

The deadliest forms of skin cancer, melanomas have a large fatality rate. In the United States of America, 196,060 new cases of melanoma are anticipated in 2020. In the past, many automated methods for diagnosing skin lesions have been proposed, but they have not yet proven to be very accurate. Based on skin cells’ exposure to sunlight, aberrant skin cell development frequently results in skin cancer. Ultraviolet radiation, viruses, bacteria, chemicals, and fungi are the main contributors to skin conditions. The creation of a precise computer-aided system for diagnosing breast cancer is of tremendous clinical importance. An improved machine learning framework has been developed in this research to detect skin lesions or skin cancer. Hence it is important to segment and classify the skin lesion. The research utilizes the fruit fly optimization algorithm and machine learning framework to segment and classifies skin disease and cancer. This platform's central idea is to use the fruit fly optimization algorithm (FOA) to improve two crucial SVM variables and create an FOA-based SVM (FOA-SVM) for the diagnosis of skin cancer. The integrative approach not only improves accuracy but also provides important data for more accurate classification.

Abstract:The population of St. Kitts and Nevis is predominately of African descent. Illness and death are most attributable to chronic non-communicable diseases such as diabetes, heart disease, hypertension and cancer in the adult population. Under the direction of the St. Kitts and Nevis Ministry of Health, health services are provided by public hospitals and community health centers with significant collaboration related to patient care and follow up. Emphasis is placed on primary care and prevention. The Federation of St. Kitts and Nevis has set aggressive goals for improving its health care standards by 2015. Historically, the islands have been affected by hurricanes, earthquakes and floods, and natural disasters are a constant threat to public health. During January Term in 2009 and 2010, a group of predominantly undergraduate and some graduate University of Virginia students completed a course on disaster preparedness and health care in St. Kitts and Nevis. This paper reflects their assessment of public health and disaster preparedness in the Federation.

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In Tunisia, buildings often grapple with excessive cooling and high energy consumption due to traditional summer cooling systems. Eco-friendly alternatives like solar cooling and dehumidification systems are gaining interest in their ability to manage temperature and humidity efficiently. This research addresses the challenge of implementing evaporative desiccant solar cooling systems across Tunisia, a country with diverse climates, from the Mediterranean north to arid desert landscapes in the south. A structured approach is used, collecting data from seventeen cities during the summer season. A prototype solid desiccant cooling system adapted to Tunisia's climate is designed and tested. Tunisia is classified into three climate zones. Zone, one encompasses the north–south coastal region with high summer humidity of over 40% and temperatures of 25–30 °C. It requires a sophisticated approach, combining desiccation-cooling with humidification for thermal comfort. Zone two pertains to regions with summer temperatures over 30 °C and humidity from 30 to 40%. A subtle air-drying element enhances comfort. Zone three deals with areas where summer temperatures reach 35 °C, and humidity remains below 30%. This unique air conditioning approach focuses on moisture without air drying, ensuring thermal comfort. This research highlights the potential of evaporative desiccant solar cooling systems to enhance comfort and reduce energy consumption across various climates.

Two of nature’s recurring binding motifs in metalloproteins are the CxxxCxxC motif in radical SAM enzymes and the 2-His-1-carboxylate motif found both in zincins and α-ketoglutarate and non-haem iron enzymes. Here we show the confluence of these two domains in a single post-translational modifying enzyme containing an N-terminal radical S-adenosylmethionine domain fused to a C-terminal 2-His-1-carboxylate (HExxH) domain. The radical SAM domain catalyses three-residue cyclophane formation and is the signature modification of triceptides, a class of ribosomally synthesized and post-translationally modified peptides. The HExxH domain is a defining feature of zinc metalloproteases. Yet the HExxH motif-containing domain studied here catalyses β-hydroxylation and is an α-ketoglutarate non-haem iron enzyme. We determined the crystal structure for this HExxH protein at 2.8 Å, unveiling a distinct structural fold, thus expanding the family of α-ketoglutarate non-haem iron enzymes with a class that we propose to name αKG-HExxH. αKG-HExxH proteins represent a unique family of ribosomally synthesized and post-translationally modified peptide modifying enzymes that can furnish opportunities for genome mining, synthetic biology and enzymology.

Nigella sativaseed oil is widely used as an anti-inflammatory, antioxidant, and anticancer agent. However, its insolubility in aqueous media and low stability limit its practical biological applications. The aim of this study was to formulate and characterize Nigella sativaseed oil (NO) using β-cyclodextrin (β-CD). The preparation of the inclusion complexes was carried out by co-precipitation method and then validated by Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), differential scanning calorimetry (DSC), and dynamic light scattering (DLS). The encapsulation efficiency of the inclusion complexes formed was about 80.4% and 88.2% for the two ratios studied, 1:2 and 1:4 (w:w), respectively. The study showed that the Nigellaoil encapsulation preserved the antioxidant activity against DPPH and, in particular, enhanced the antibacterial activity against Salmonella typhimurium, Staphylococcus aureus, and Bacillus cereusby a factor reaching fourfold. A minimum inhibitory concentration similar to that of ampicillin (0.078 mg/mL) was observed against Salmonella typhimuriumwhen the complex β-CD/NO 1:4 (w:w) was used. The cytotoxicity study showed that the oil encapsulation in β-CD retained its anti-proliferative activity against HeLa cancer line cells. Using SwissADME prediction, the pharmacokinetic profile of all identified oil compounds was evaluated to define their absorption, distribution, metabolism, and excretion (ADME) properties. The results support the use of encapsulated Nigellaoil for active food packaging or pharmaceutical formulations.

Tripartite motif (TRIM) family members participate in a variety of cellular activities, such as intracellular signaling, development, cellular death, protein quality control, immunological defense, waste degradation, and the emergence of cancer. These proteins usually act as E3 ubiquitin ligase. The final line of resistance against infectious viruses is a cytosolic ubiquitin ligase and antibody receptor called TRIM containing 21. TRIM21, a protein with a tripartite structure, has been linked to autoimmune erythematosus, Sjogren’s disorder, and innate immunity. TRIM21 may either promote the formation of specific cancer-activating proteins, resulting in their proteasomal degradation, or it may do neither, depending on the kind of cancer and cancer-causing trigger. The current research has shown that the antiviral action of TRIM mostly depends on their role as E3-ubiquitin ligases and a significant portion of the TRIM family mediates the transmission of innate immune cell signals and the subsequent production of cytokines. We highlighted the function of TRIM family members in various inflammatory diseases.

In this paper, we are interested in flow-rack automated storage/ retrieval systems (AS/RS), which are compact AS/RS. For this configuration of AS/RS we propose a new storage method based on machine learning (ML), i.e., ML method that assigns to each incoming load a position in the rack, in such a way, that the retrieval time of this same load will be optimal. In other words, we tidy out the loads inside the rack, In order to facilitate access to each type of loads. Consequently, the total (average) retrieval time in the system is minimised. The choice of ML is mainly due to the fact that the output, which is the minimisation of the average retrieval time, cannot be expressed as a function of the input, which is the choice of the most appropriate cell, for the storage of each incoming load. We compared the proposed model results with other basic storage methods. The obtained results were very satisfactory.

Surface tension-driven self-alignment is a promising technique to align millimeter-scale components with a high accuracy of a few microns. It is based on liquid capillary forces moving and aligning a solid component on its receiving pad. Using molten solders as the liquid is a promising way to bond, connect and align a chip with its substrate. Micro-solar cells soldering experiments for micro-concentrator photovoltaics have been carried out. It has been found experimentally that the solder volume, the receiving pad size and the initial placement of the chip have an impact on the placement accuracy. In this work, an analytical and a numerical model of the capillary forces during self-alignment are built to improve the understanding of the experimental results. Guidelines to reach a high placement accuracy are presented. In practice, low solder volumes, receiving pads smaller than the chip and an initial chip displacement of about 10% of the chip size yield a higher placement accuracy. [2023-0153]

New grid management schemes have created exciting opportunities for end customers to maximize their utility by becoming active participants. In particular, Transactive Energy Systems (TES) allow customers to cooperate and negotiate in energy markets, increasing social welfare. These interactions also reduce demand-side uncertainties and simplify grid balancing at different levels. In TES, it is beneficial to employ forward contracts because they establish conditions for future energy supply, allowing grid maintainers to plan a cost-effective operation. Thus, end customers interact in local retail markets in advance to agree on service conditions that fulfill their needs. This paper presents a comprehensive analysis of the risks involved in those forward contracts with the aim of providing valuable information to participants. The TES environment modifies the typical risks of electricity contracts due to the information exchange in the negotiation and execution stages. Indeed, reliable data and realistic forecasting assumptions become a primary concern for each participant since they constitute the main threat of contract defaulting. Risk management strategies are presented in bow-tie and Ishikawa diagrams to elicit the decisions for market participants. Case study results demonstrate that forecasting errors impact the conditional value at risk of the contracts, in proportion to the demand uncertainty.

Background: The study focuses on the vibrational characteristics of double-walled carbon nanotubes (DWCNTs) within a polymer matrix, using the theory of strain gradient elasticity. Purpose: The aim is to understand how the mechanical properties of DWCNTs and the polymer matrix change with temperature and how small-scale effects affect wave propagation in DWCNTs, especially in their free transverse vibration behavior. Method: The research derives governing equations for modeling the free transverse vibration of DWCNTs using the nonlocal Euler–Bernoulli beam model. This method takes into account temperature variations and the van der Waals forces between the inner and outer nanotubes. Results and Conclusions: The analysis provides insights into how temperature and inter-nanotube interactions impact the vibrational characteristics of DWCNTs embedded in polymer matrices. This comprehensive understanding is achieved through incorporating various factors into the study. The study underscores the importance of considering small-scale effects and inter-nanotube interactions in understanding the vibrational behavior of DWCNTs in polymer matrices, contributing to the broader field of nanomaterials research.

Choline is an essential nutrient that the human body needs in vast quantities for cell membrane synthesis, epigenetic modification and neurotransmission. The brain has a particularly high demand for choline, but how it enters the brain remains unknown1–3. The major facilitator superfamily transporter FLVCR1 (also known as MFSD7B or SLC49A1) was recently determined to be a choline transporter but is not highly expressed at the blood–brain barrier, whereas the related protein FLVCR2 (also known as MFSD7C or SLC49A2) is expressed in endothelial cells at the blood–brain barrier4–7. Previous studies have shown that mutations in human Flvcr2cause cerebral vascular abnormalities, hydrocephalus and embryonic lethality, but the physiological role of FLVCR2 is unknown4,5. Here we demonstrate both in vivo and in vitro that FLVCR2 is a BBB choline transporter and is responsible for the majority of choline uptake into the brain. We also determine the structures of choline-bound FLVCR2 in both inward-facing and outward-facing states using cryo-electron microscopy. These results reveal how the brain obtains choline and provide molecular-level insights into how FLVCR2 binds choline in an aromatic cage and mediates its uptake. Our work could provide a novel framework for the targeted delivery of therapeutic agents into the brain.

Fine particulate matter (PM2.5) resulting from wildland fire is a significant public health risk in the United States (U.S.). The existing stationary monitoring network and the tools used to alert the public of smoke conditions, such as the Air Quality Index or NowCast, are not optimized to capture actual exposure concentrations in impacted communities given that wildland fire smoke plumes have characteristically steep exposure concentration gradients that can vary over fine spatiotemporal scales. In response, we developed and evaluated a lightweight, universally attachable mobile PM2.5monitoring system to provide supplemental, real-time air quality information during wildfire incidents and prescribed burning activities. We retroactively assessed the performance of the mobile monitor compared to nearby (100–1500 m) stationary low-cost sensors and regulatory monitors using 1 minute averaged data collected during two large wildfires in the western U.S. and during one small, prescribed burn in the Midwest. The mobile measurements were highly correlated (R2> 0.85) with the stationary network during the large wildfires. Further, 1 minute averaged mobile measurements differed from three collocated stationary instruments by <25% on average for fourteen out of fifteen total passages. For the small, prescribed burn, rapidly changing conditions near the fire border complicated the comparison of mobile and stationary measurements but the spatial maximum concentrations measured by both instruments were consistent. In general, this work highlights the value of using portable sensor technologies to address the monitoring challenges presented by dynamic wildland fire conditions and demonstrates the value in combining mobile monitoring with stationary data where possible.

BackgroundThe use of virtual reality (VR) is increasing in palliative care. However, despite increasing interest in VR, there is little evidence of how this technology can be implemented into practice.AimsThis paper aims to: (1) explore the feasibility of implementing VR therapy, for patients and caregivers, in a hospital specialist inpatient palliative care unit and a hospice, and (2) to identify questions for organisations, to support VR adoption in palliative care.MethodsThe Samsung Gear VR system was used in a hospital specialist palliative inpatient unit and a hospice. Patients and caregivers received VR distraction therapy and provided feedback of their experience. Staff completed a feedback questionnaire to explore their opinion of the usefulness of VR in palliative care. A public engagement event was conducted, to identify questions to support implementation of VR in palliative care settings.ResultsFifteen individuals (12 (80%) patients and 3 (20%) caregivers) participated. All had a positive experience. No adverse effects were reported. Ten items were identified for organisations to consider ahead of adoption of VR in palliative care. These were questions about: the purpose of VR; intended population; supporting evidence; session duration; equipment choice; infection control issues; content choice; setting of VR; person(s) responsible for delivery and the maintenance plan.ConclusionsIt is feasible to use VR therapy in palliative care; however, further evidence about its efficacy and effectiveness is needed. Palliative care practitioners considering VR use should carefully consider several factors, to ensure that this technology can be used safely and effectively in clinical practice.

Temperature sensing is extremely important factor for many biomedical applications toward a prompt and accurate medical control and examination. The purpose of this work is to investigate theoretically the design of novel single mode tapered fiber Bragg gratings (TFBGs) with maximum temperature sensitivity to be used in biomedical field. The parameters which govern the functionality of TFBGs were studied in order to optimize the temperature sensitivity. Coupled mode theory (CMT) and transfer matrix method were applied to analyze TFBG structure. A numerical analysis was performed to investigate the mechanical properties of TFBGs and the cladding diameter on temperature sensitivity. Herein, the TFBGs are assumed to a reflection Bragg wavelength around 1550 nm and are inscribed in single mode fiber (Corning SMF-28). The results show that the temperature sensitivity of TFBGs at optimized parameters could reach14.83pm/∘C, which is superior to those of conventional fiber Bragg gratings with the same parameters (∼11.87pm/∘C). Moreover, the effect of taper ratio on sensitivity was investigated in this study. The findings also demonstrate that the sensor sensitivity can be adjusted with variation to the taper ratio. From the results, it is confirmed that the sensitivity of TFBGs was improved by reducing linearly the fiber diameter up to 15 μm compared to uniform FBGs ones, achieving the highest temperature sensitivity.

Objectives: To investigate the clinical and epidemiological factors associated with severe COVID-19 cases in hospitalized patients across two emirates within the United Arab Emirates (UAE). Methods: A retrospective observational analytical study analysed data from 738 medical records and conducted 573 in-depth interviews with patients hospitalized across multiple healthcare centers in the UAE, between 29 January 2020 and 14 October 2021. Regression analysis predicted risk factors for COVID-19 severity. Results: Main risk factors identified were crowding (aOR 1.919; 95%CI 1.144, 3.221), obesity (aOR 2.383; 95%CI 1.332, 4.263), diabetes (aOR 11.14; 95%CI 2.653–46.797), severe dehydration (aOR 3.219; 95%CI 2.161, 4.795), cough or sore throat (aOR 1.607; 95%CI 1.032, 2.502), shortness of breath (aOR 1.921; 95%CI 1.294, 2.853), increased days from symptom onset to admission (aOR 1.055; 95%CI 1.006, 1.105), elevated ANC (aOR 1.263, 95%CI 1.121, 1.424), and AST/SGOT (aOR 1.055, 95% CI 1.016, 1.095). Protective factors included smoking (aOR 0.367; 95%CI 0.182, 0.740), first dose of COVID-19 vaccination (aOR 0.595; 95%CI 0.377, 0.93), higher oxygen saturation (aOR 0.853; 95%CI: 0.801, 0.907) and elevated ALC (aOR 0.540; 95%CI 0.323, 0.905). Conclusion: Identifying risk factors is crucial for high-risk individuals who may require closer monitoring to improve their outcomes. This can provide guidance for surveillance systems and early detection strategies to mitigate the impact of future outbreaks.

For children with autism spectrum disorder (ASD), innovative computer-assisted solutions can provide useful teaching, learning, and support tools. Speech, video, narrative, and a mix of 2D/3D images of virtual objects shown on screens and mobile phones can help to improve the learning experience. Augmented Reality (AR) presents a valuable technology for achieving certain educational objectives. This study presents a gesture and voice-based learning framework for children with ASD that offers interactivity, engagement, and visual support during school/cognitive therapy sessions. The proposed prototype was designed to increase children's engagement and focus during the session and achieve a high level of social interaction and inclusion. It was implemented in accordance with the requirements of specialists from regional rehabilitation centres for children with ASD and structured activities and AR-based games were defined. A multi-baseline feasibility pilot study was carried out with 18 children, aged 2–12 years, diagnosed with ASD and with learning difficulties (concentration and language development problems, social interaction and inclusion), and 3 therapists/parents. Preliminary qualitative and quantitative results show significantly higher engagement and concentration time using the proposed AR-computer system compared to a non-computer condition. In addition to improved receptive vocabulary and social interaction for the children, the prototype reduces teacher workload while engaging the children.

This paper presents a numerical study combining different passive measures to improve the energy efficiency of a building. These measures include night ventilation and physical design such as building materials, thermal insulation as well as window configuration combined with winter and summer solar shading. The study focuses on a basic classroom prototype that complies with the Algerian buildings. It took the city of Constantine in Algeria as a case study for the warm temperate climate of the Mediterranean regions. The results show that adopting such passive measures reduces the building's energy demand from 67.5 to 15.7 kWh/m2for heating and from 7.7 to 5.7 kWh/m2for cooling. This leads to an annual reduction of 53.8 kWh/m2, or an energy saving of 72% per year. Furthermore, CO2emissions were reduced by 72% passing then from 1772 to 499 kg/year. Thus, a correlative reduction between energy demand and carbon footprint is observed. The economic analysis shows that life cycle costs are influenced by energy prices in different countries and that the profitability of these measures strongly depends on whether these prices are subsidised or not.

Due in part to climate change, wildfire activity is increasing, with the potential for greater public health impact from smoke in downwind communities. Studies examining the health effects of wildfire smoke have focused primarily on fine particulate matter (PM2.5), but there is a need to better characterize other constituents, such as hazardous air pollutants (HAPs). HAPs are chemicals known or suspected to cause cancer or other serious health effects that are regulated by the United States (US) Environmental Protection Agency. Here, we analyzed concentrations of 21 HAPs in wildfire smoke from 2006 to 2020 at 309 monitors across the western US. Additionally, we examined HAP concentrations measured in a major population center (San Jose, CA) affected by multiple fires from 2017 to 2020. We found that concentrations of select HAPs, namely acetaldehyde, acrolein, chloroform, formaldehyde, manganese, and tetrachloroethylene, were all significantly elevated on smoke-impacted versus nonsmoke days (P< 0.05). The largest median increase on smoke-impacted days was observed for formaldehyde, 1.3 μg/m3(43%) higher than that on nonsmoke days. Acetaldehyde increased 0.73 μg/m3(36%), and acrolein increased 0.14 μg/m3(34%). By better characterizing these chemicals in wildfire smoke, we anticipate that this research will aid efforts to reduce exposures in downwind communities.

To evaluate follow-up after implantation of a sacral nerve modulation implantable pulse generator (IPG) and to investigate the reasons and risk factors for follow-up discontinuation.

Abstract: Copper-rich deposits associated with magmatism at the Oued Belif -Ain El Araar area in North-western Tunisia fit into the geodynamic framework of the Tell-Rif orogenic belt of North Africa that extends westward to the Betic Cordilleras in Spain at the african and european plate boundary. The deposits have been considerably studied. However, the prevailing conditions of pressure, volume, temperature and composition (P-V-T-X) of the mineralizing fluids are still elusive. In this study, three types of fluid inclusions were distinguished for the mineralized facies: primary polyphase brine inclusions (Type I: liquid + vapor + halite + sylvite), primary sylvite (Type II-a: liquid + vapor + sylvite) and halite (Type II-b: liquid + vapor + halite) bearing inclusions and biphasic secondary vapor-rich and liquid-rich inclusions (Type III: liquid + vapor). Raman spectroscopy show that Type I and II a-b inclusions are in the CO2–H2O–NaCl–KCl, CO2–H2O–NaCl and CO2–H2O–KCl systems, whereas Type III pertains to the CO2–H2O system. Estimations of Pressure-Temperature fluid trapping conditions, for all mentioned inclusions, demonstrate a physicochemical fluid evolution from the highest temperature brine inclusions (Tt= 500°C; Pt= 980 bars), related to the porphyry phase, to the low temperature biphasic inclusions (Tt= 131°C; Pt= 221 bars) related the latest epithermal phase .The coexistence of liquid-rich and vapor-rich inclusions homogenizing at lower temperatures, confirms the establishment of boiling conditions responsible of Au–(Ag) enrichment in the last mineralizing phases. Comparable temperature conditions in similar magmatic related deposits are also mentioned in southern Spain (Rodalquilar gold mine, e.g., Arribas et al., 1995) where the mineralizing fluid temperatures mentioned vary from 175°C for epithermal deposits to more than 400°C for porphyry ones. The geochemical behavior of trace element indicates positive anomalies in mobile elements (hygromagmaphiles), those linked to Au, granitophiles (mainly W and Mo) and chalcophiles indicating a supply of metals of deep origin and mineralizing fluids with marked magmatic differentiation.

Arterial spin labeling (ASL) is a magnetic resonance perfusion technique that allows for quantification of cerebral blood flow (CBF) without the use of contrast or radiation. Several applications of ASL have been described in diagnosis of strokes and stroke mimics, intracranial tumors, and other conditions. Various vascular anomalies exhibit specific CBF patterns that correlate with different signal intensities on ASL. In this case-based review, we demonstrate the utility of ASL in diagnosis and surveillance of vascular anomalies in the intracranial compartment.