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Abstract In the field of power systems, the optimization challenge of combined heat and power units economic dispatch (CHPUED) holds immense importance. This study presents an improved Aquila optimization technique (IAQT) that effectively tackles the CHPUED. The primary objective of the enhanced IAQT model is to minimize the overall cost of power generation in CHP systems while satisfying demand and operational constraints. However, to achieve more accurate cost estimations and avoid suboptimal solutions, it is crucial to consider transmission losses in the optimization model. By incorporating transmission losses, the IAQT algorithm can allocate power generation resources more effectively, leading to improved system efficiency and reduced operational costs. The proposed IAQT algorithm addresses the limitations of the standard AQT and introduces novel features to enhance its search capabilities. One key limitation of the standard AQT is its heavy reliance on the best solution found during optimization. To overcome this drawback, the enhanced IAQT model eliminates the dependency on the best solution and enables a more thorough exploration of the search space. Moreover, the algorithm incorporates specific limitations and constraints for each dimension of the newly generated solutions, ensuring their feasibility and validity. The standard AQT and proposed IAQT are tested on CEC 20 benchmark functions. Moreover, the proposed approach is extensively evaluated through experimentation and testing on various scenarios, including 7–48-unit and large 96-unit systems with/without losses. Furthermore, the overall costs for the 7 unit-system are considered including the reserve constraint. The results exhibit the remarkable performance and efficiency of the enhanced IAQT model, outperforming the standard version and several previously reported results. This validation underscores the significant contribution of the study in addressing the CHPUED and highlights its potential for real-world applications.

Abstract Virtual classrooms have recently gained significant consideration in educational institutes and universities due to their potential to encourage and support students’ learning activities. Although recent research has focused extensively on online learning, virtual classrooms and the factors affecting their continuous use have garnered little attention, especially in Arab Gulf countries such as Saudi Arabia. Thus, this study integrates the expectation confirmation model and the information systems success model to assess the factors affecting students’ continuous intention to utilise virtual classrooms in higher education. We examined the effects of information quality, service quality, system quality, confirmation, perceived usefulness, and satisfaction on the continuous intention to utilise virtual classrooms. Data were collected from 441 students and analysed using structural equation modelling “SEM”. SEM is a powerful multivariate approach used increasingly in empirical investigation for evaluating and testing casual relationships. The results revealed that the proposed model demonstrated high explanatory power in explaining students’ continuous intention to utilise virtual classrooms (R2 = 0. 86). Additionally, information quality had a significant effect on confirmation and an insignificant effect on perceived usefulness. System quality affected perceived usefulness and confirmation. Contrary to our expectations, service quality had a significant negative effect on perceived usefulness and confirmation. Additionally, perceived usefulness and confirmation affected students’ satisfaction with using virtual classrooms, and satisfaction affected students’ continuous intention to utilise virtual classrooms. This study contributes to the literature by offering a holistic integrated model that increases the understanding of the factors influencing students’ continuous intention to utilise virtual classrooms, hence aiding in increasing their utilisation. Furthermore, it provides practical implications for enhancing students’ continuous intention to utilise virtual classrooms. Virtual classroom developers must focus on improving the system quality of virtual classrooms. According to our results, higher system quality led the students to perceive virtual classrooms as useful and confirmed their favourable experiences with virtual classrooms. Additionally, providing students with high information quality in virtual classrooms would enhance their confirmation experiences, leading to the continuous intention to utilise virtual classrooms.

The metaverse, an interactive and immersive 3D virtual environment, has recently become popular and is widely used in several fields, including education. However, the successful use of metaverse relies on the extent to which users intend to adopt and use it. Close examination of this critical issue reveals a lack of research that examines the effects of certain factors on users’ intentions toward using metaverses. Thus, this study extends the technology acceptance model by integrating two constructs—perceived system quality and students’ personal innovativeness. Using a survey to collect data, 164 responses were received from students at the University of Ha’il in Saudi Arabia. Two steps in structural equation modelling (SEM) using the AMOS software were applied to analyse the data and test the research hypotheses. The results revealed that perceived system quality had a significant effect on students’ intentions to use metaverses through perceived ease of use. Furthermore, personal innovativeness had a significant effect on students’ intentions through the perceived usefulness of the metaverse. In addition, perceived usefulness affected students’ intentions to use a metaverse. Surprisingly, perceived ease of use had an insignificant effect on students’ intentions to use the metaverse. Although the proposed model and its findings contribute to the technology acceptance model (TAM) literature, the study’s practical value is significant because it can help educational policymakers and authorities to understand the effect of each factor and plan future strategies. Additionally, the findings of this study can assist practitioners, designers, and developers in designing and promoting the utilisation of metaverses.

Cotton is globally known for its high-priority cellulose-rich natural fiber. In addition to providing fiber for the textile industry, it is an important source material for edible oil, livestock feed, and fuel products. Global warming and the growing population are the major challenges to the world’s agriculture and the potential risks to food security. In this context, improving output traits in cotton is necessary to achieve sustainable cotton production. During the last few years, high throughput omics techniques have aided in identifying crucial genes associated with traits of cotton fiber, seed, and plant architecture which could be targeted with more precision and efficiency through the CIRPSR/Cas-mediated genome editing technique. The various CRISPR/Cas systems such as CRISPR/Cas9, CRISPR/nCas9, and CRISPR/Cas12a have been employed to edit cotton genes associated with a wide range of traits including fiber length, flowering, leaf colour, rooting, seed oil, plant architecture, gossypol content, somatic embryogenesis, and biotic and abiotic stresses tolerance, highlighting its effectiveness in editing the cotton genome. Thus, CRISPR/Cas-mediated genome editing has emerged as a technique of choice to tailor crop phenotypes for better yield potential and environmental resilience. The review covers a comprehensive analysis of cotton phenotypic traits and their improvement with the help of the latest genome editing tools to improve fiber, food, feed, and fuel-associated genes of cotton to ensure food security.

The primary objective of this study is to investigate the effects of the Fractional Order Kepler Optimization Algorithm (FO-KOA) on photovoltaic (PV) module feature identification in solar systems. Leveraging the strengths of the original KOA, FO-KOA introduces fractional order elements and a Local Escaping Approach (LEA) to enhance search efficiency and prevent premature convergence. The FO element provides effective information and past expertise sharing amongst the participants to avoid premature converging. Additionally, LEA is incorporated to boost the search procedure by evading local optimization. The single-diode-model (SDM) and Double-diode-model (DDM) are two different equivalent circuits that are used for obtaining the unidentified parameters of the PV. Applied to KC-200, Ultra-Power-85, and SP-70 PV modules, FO-KOA is compared to the original KOA technique and contemporary algorithms. Simulation results demonstrate FO-KOA's remarkable average improvement rates, showcasing its significant advantages and robustness over earlier reported methods. The proposed FO-KOA demonstrates exceptional performance, outperforming existing algorithms by 94.42 %–99.73 % in optimizing PV cell parameter extraction, particularly for the KC200GT module, showcasing consistent superiority and robustness. Also, the proposed FO-KOA is validated of on SDM and DDM for the well-known RTC France PV cell.

Abstract Cotton is one of the most important fiber crops that plays a vital role in the textile industry. Its production has been unstable over the years due to climate change induced biotic stresses such as insects, diseases, and weeds, as well as abiotic stresses including drought, salinity, heat, and cold. Traditional breeding methods have been used to breed climate resilient cotton, but it requires a considerable amount of time to enhance crop tolerance to insect pests and changing climatic conditions. A promising strategy for improving tolerance against these stresses is genetic engineering. This review article discusses the role of genetic engineering in cotton improvement. The essential concepts and techniques include genome editing via clustered regularly interspaced short palindromic repeats (CRISPR) / CRISPR-associated protein 9 (CRISPR-Cas9), overexpression of target genes, downregulation using RNA interference (RNAi), and virus-induced gene silencing (VIGS). Notably, the Agrobacterium-mediated transformation has made significant contributions to using these techniques for obtaining stable transgenic plants.

Abstract Dalbergia sissoo Roxb. (Shisham) is a timber-producing species of economic, cultural, and medicinal importance in the Indian subcontinent. In the past few decades, Shisham's dieback disease caused by the fungus Botryodiplodia theobromae has become an evolving issue in the subcontinent endangering its survival. To gain insights into this issue, a standard transcriptome assembly was deployed to assess the response of D. sissoo at the transcriptomic level under the stress of B. theobromae infection. For RNA isolation, the control and infected leaf tissue samples were taken from 1-year-old greenhouse-grown D. sissoo plants after 20 days of stem-base spore inoculation. cDNA synthesis was performed from these freshly isolated RNA samples that were then sent for sequencing. About 18.14 Gb (Giga base) of data was generated using the BGISEQ-500 sequencing platform. In terms of Unigenes, 513,821 were identified after a combined assembly of all samples and then filtering the abundance. The total length of Unigenes, their average length, N50, and GC-content were 310,523,693 bp, 604 bp, 1,101 bp, and 39.95% respectively. The Unigenes were annotated using 7 functional databases i.e., 200,355 (NR: 38.99%), 164,973 (NT: 32.11%), 123,733 (Swissprot: 24.08%), 142,580 (KOG: 27.75%), 139,588 (KEGG: 27.17%), 99,752 (GO: 19.41%), and 137,281 (InterPro: 26.72%). Furthermore, the Transdecoder detected 115,762 CDS. In terms of SSR (Simple Sequence Repeat) markers, 62,863 of them were distributed on 51,508 Unigenes and on the predicted 4673 TF (Transcription Factor) coding Unigenes. A total of 16,018 up- and 19,530 down-regulated Differentially Expressed Genes (DEGs) were also identified. Moreover, the Plant Resistance Genes (PRGs) had a count of 9230. We are hopeful that in the future, these identified Unigenes, SSR markers, DEGs and PRGs will provide the prerequisites for managing Shisham dieback disease, its breeding, and in tree improvement programs.

Even though asynchronous e-learning has become popular among universities, few studies have examined how students intend to continue using it for their learning. This study proposed a theoretical model that aims to examine the effects of external factors—emotional engagement and peer interaction—and two constructs of technology acceptance model (TAM) on students’ continuous intention to use asynchronous e-learning. A total of 259 students participated in a survey. The data were analysed using two steps in SEM AMOS. confirmatory factor analysis was conducted for assessing model measurement, and structural equation modelling was applied for assessing relationships among constructs and testing hypothesis. The results showed that emotional engagement had a significant effect on students’ continuous intention to use asynchronous e-learning through the perceived ease of use of asynchronous e-learning and not through its perceived usefulness. Furthermore, peer interaction had a significant effect on students’ continuous intention to use asynchronous e-learning. Moreover, the constructs of the technology acceptance model—perceived ease of use and perceived usefulness—had direct and significant effects on students’ continuous intention to use asynchronous e-learning. Several implications and suggestions were discussed.

Abstract Background Fatty acid desaturases (FADs) are involved in regulating plant fatty acid composition by adding double bonds to growing hydrocarbon chain. Apart from regulating fatty acid composition FADs are of great importance, and are involved in stress responsiveness, plant development, and defense mechanisms. FADs have been extensively studied in crop plants, and are broadly classed into soluble and non-soluble fatty acids. However, FADs have not yet been characterized in Brassica carinata and its progenitors. Results Here we have performed comparative genome-wide identification of FADs and have identified 131 soluble and 28 non-soluble FADs in allotetraploid B. carinata and its diploid parents. Most soluble FAD proteins are predicted to be resided in endomembrane system, whereas FAB proteins were found to be localized in chloroplast. Phylogenetic analysis classed the soluble and non-soluble FAD proteins into seven and four clusters, respectively. Positive type of selection seemed to be dominant in both FADs suggesting the impact of evolution on these gene families. Upstream regions of both FADs were enriched in stress related cis-regulatory elements and among them ABRE type of elements were in abundance. Comparative transcriptomic data analysis output highlighted that FADs expression reduced gradually in mature seed and embryonic tissues. Moreover, under heat stress during seed and embryo development seven genes remained up-regulated regardless of external stress. Three FADs were only induced under elevated temperature whereas five genes were upregulated under Xanthomonas campestris stress suggesting their involvement in abiotic and biotic stress response. Conclusions The current study provides insights into the evolution of FADs and their role in B. carinata under stress conditions. Moreover, the functional characterization of stress-related genes would exploit their utilization in future breeding programs of B. carinata and its progenitors.

Conclusion and Recommendations: The magnitude of the unmet need for modern contraceptive methods was higher than both the Ethiopian national and Oromia regional state total unmet need for the general population. Governmental and nongovernmental organizations should increase their efforts to reduce this high magnitude of unmet needs by emphasizing those factors that have a great contribution to unmet needs.

Microcephaly, Guillain-Barré syndrome, and potential sexual transmission stand as prominent complications associated with Zika virus (ZIKV) infection. The absence of FDA-approved drugs or vaccines presents a substantial obstacle in combatting the virus. Furthermore, the inclusion of pregnancy in the pharmacological screening process complicates and extends the endeavor to ensure molecular safety and minimal toxicity. Given its pivotal role in viral assembly and maturation, the NS2B-NS3 viral protease emerges as a promising therapeutic target against ZIKV. In this context, a dipeptide inhibitor was specifically chosen as a control against 200 compounds for docking analysis. Subsequent molecular dynamics simulations extending over 200 ns were conducted to ascertain the stability of the docked complex and confirm the binding of the inhibitor at the protein's active site. The simulation outcomes exhibited conformity to acceptable thresholds, encompassing parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), ligand-protein interaction analysis, ligand characterization, and surface area analysis. Notably, analysis of ligand angles bolstered the identification of prospective ligands capable of inhibiting viral protein activity and impeding virus dissemination. In this study, the integration of molecular docking and dynamics simulations has pinpointed the dipeptide inhibitor as a potential candidate ligand against ZIKV protease, thereby offering promise for therapeutic intervention against the virus.

Abstract Background Plant aquaporins are critical genetic players performing multiple biological functions, especially climate resilience and water-use efficiency. Their genomic diversity across genus Oryza is yet to be explored. Results This study identified 369 aquaporin-encoding genes from 11 cultivated and wild rice species and further categorized these into four major subfamilies, among which small basic intrinsic proteins are speculated to be ancestral to all land plant aquaporins. Evolutionarily conserved motifs in peptides of aquaporins participate in transmembrane transport of materials and their relatively complex gene structures provide an evolutionary playground for regulation of genome structure and transcription. Duplication and evolution analyses revealed higher genetic conservation among Oryza aquaporins and strong purifying selections are assisting in conserving the climate resilience associated functions. Promoter analysis highlighted enrichment of gene upstream regions with cis-acting regulatory elements involved in diverse biological processes, whereas miRNA target site prediction analysis unveiled substantial involvement of osa-miR2102-3p, osa-miR2927 and osa-miR5075 in post-transcriptional regulation of gene expression patterns. Moreover, expression patterns of japonica aquaporins were significantly perturbed in response to different treatment levels of six phytohormones and four abiotic stresses, suggesting their multifarious roles in plants survival under stressed environments. Furthermore, superior haplotypes of seven conserved orthologous aquaporins for higher thousand-grain weight are reported from a gold mine of 3,010 sequenced rice pangenomes. Conclusions This study unveils the complete genomic atlas of aquaporins across genus Oryza and provides a comprehensive genetic resource for genomics-assisted development of climate-resilient rice cultivars.

Abstract Cotton has enormous economic potential providing high-quality protein, oil, and fibre. A large increase in cotton output is necessary due to the world's changing climate and constantly expanding human population. In the past, conventional breeding techniques were used to introduce genes into superior cotton cultivars to increase production and to improve quality. The disadvantages of traditional breeding techniques are their time-consuming, reliance on genetic differences that are already present, and considerable backcrossing. To accomplish goals in a short amount of time, contemporary plant breeding techniques, in particular modern genome editing technologies (GETs), can be used. Numerous crop improvement initiatives have made use of GETs, such as zinc-finger nucleases, transcription-activator-like effector nucleases, clustered regularly interspaced palindromic repeats (CRISPR), and CRISPR-associated proteins systems (CRISPR/Cas)-based technologies. The CRISPR/Cas system has a lot of potential because it combines three qualities that other GETs lack: simplicity, competence, and adaptability. The CRISPR/Cas mechanism can be used to improve cotton tolerance to biotic and abiotic stresses, alter gene expression, and stack genes for critical features with little possibility of segregation. The transgene clean strategy improves CRISPR acceptability addressing regulatory issues associated with the genetically modified organisms (GMOs). The research opportunities for using the CRISPR/Cas system to address biotic and abiotic stresses, fibre quality, plant architecture and blooming, epigenetic changes, and gene stacking for commercially significant traits are highlighted in this article. Furthermore, challenges to use of CRISPR technology in cotton and its potential for the future are covered in detail.

Begomoviruses are contagious and severely affect commercially important fiber and food crops. Cotton leaf curl Multan virus (CLCuMuV) is one of the most dominant specie of Begomovirus and a major constraint on cotton yield in Pakistan. Currently, the field of plant genome editing is being revolutionized by the CRISPR/Cas system applications such as base editing, prime editing and CRISPR based gene drives. CRISPR/Cas9 system has successfully been used against biotic and abiotic plant stresses with proof-of-concept studies in both model and crop plants. CRISPR/Cas12 and CRISPR/Cas13 have recently been applied in plant sciences for basic and applied research. In this study, we used a novel approach, multiplexed crRNA-based Cas12a toolbox to target the different ORFs of the CLCuMuV genome at multiple sites simultaneously. This method successfully eliminated the symptoms of CLCuMuV in Nicotiana benthamiana and Nicotiana tabacum. Three individual crRNAs were designed from the CLCuMuV genome, targeting the specific sites of four different ORFs (C1, V1 and overlapping region of C2 and C3). The Cas12a-based construct Cas12a-MV was designed through Golden Gate three-way cloning for precise editing of CLCuMuV genome. Cas12a-MV construct was confirmed through whole genome sequencing using the primers Ubi-intron-F1 and M13-R1. Transient assays were performed in 4 weeks old Nicotiana benthamiana plants, through the agroinfiltration method. Sanger sequencing indicated that the Cas12a-MV constructs made a considerable mutations at the target sites of the viral genome. In addition, TIDE analysis of Sanger sequencing results showed the editing efficiency of crRNA1 (21.7%), crRNA2 (24.9%) and crRNA3 (55.6%). Furthermore, the Cas12a-MV construct was stably transformed into Nicotiana tabacum through the leaf disc method to evaluate the potential of transgenic plants against CLCuMuV. For transgene analysis, the DNA of transgenic plants of Nicotiana tabacum was subjected to PCR to amplify Cas12a genes with specific primers. Infectious clones were agro-inoculated in transgenic and non-transgenic plants (control) for the infectivity assay. The transgenic plants containing Cas12a-MV showed rare symptoms and remained healthy compared to control plants with severe symptoms. The transgenic plants containing Cas12a-MV showed a significant reduction in virus accumulation (0.05) as compared to control plants (1.0). The results demonstrated the potential use of the multiplex LbCas12a system to develop virus resistance in model and crop plants against begomoviruses.

The influence of different concentrations and nanoparticles’ diameter of silicon dioxide nanoparticles on the Nusselt number enhancement ratio and friction factor for solar thermal collector (STC) was examined numerically. The CFD model was designed to show the influence of the flow of water/SiO2 and pure water inside the pipe on the enhancement of the performance of the STC. Different concentrations of SiO2 nanoparticles are used (ϕ = 1–4%) with several nanoparticle diameters (dp = 20–50 nm). The water/SiO2 and pure water flow under different Reynolds numbers ranging from 5,000 to 30,000. The average Nusselt numbers Nuavg improved by increasing the Reynolds numbers for both fluids. The Nuavg increases with the increase in the concentration of SiO2 nanoparticles. The water/SiO2 with nanoparticle concentration of (ϕ = 5%) and nanoparticle diameter of (dp = 20 nm) has the highest Nusselt number. The Nuavg enhances 25% with water/SiO2 nanofluid flow at Re = 5,000 and 15% flow at Re = 30,000. It is noted that the skin friction factor decreases with the increase in the Reynolds number for both fluids. Water/SiO2 nanofluid has a higher skin friction factor than pure water. The Nuavg improved by 31% at the lowest Reynolds number by using water/SiO2 nanofluid as the working fluid with a change in the concentration of SiO2 nanoparticles from (ϕ = 1%) to (ϕ = 4%) and improved by 42% at the highest Reynolds number of 30,000. The decrease in the nanoparticle diameter led to an increase in the Nusselt number across all Reynolds numbers. The lowest size SiO2 nanoparticles (dp = 20 nm) provides the highest Nusselt number. The lowest size SiO2 nanoparticles (dp = 20 nm) provide the highest ratio of enhancement for the Nusselt number in STC. This investigation has confirmed that the flow of water/SiO2 with AL2O3 nanoparticles of 5% (diameter of 20 nm) has a significant influence on heat transfer enhancement to improve the thermal efficiency of STC.

Abstract The relationship between Gulf Stream (GS) transport and coastal sea level is investigated using monthly GS transport between 1993 and 2019 at Florida Straits and 10 altimeter tracks. The results show that GS transport decorrelates quickly along its path, indicating it is misleading to assume that transport at a particular location represents strength of the GS as a whole. GS transport south of Cape Hatteras is significantly correlated with coastal sea level in South Atlantic Bight from both altimetry and tide gauges. North of Cape Hatteras, sea level changes associated with GS transport decay rapidly away from GS on the onshore side and become negligible approximately 300 km northwest of GS axis. In this region, the correlations between GS transport and sea level are primarily in the deep ocean and rarely on the shelf, indicating that coastal sea level is unlikely to be driven by geostrophic adjustment to changes in GS transport.

The integration of cloud computing and business intelligence enables analytics solutions through cloud environments. Despite the fears about issues such as security, privacy, and loss of data control issue, many enterprises are increasingly adopting cloud business intelligence (cloud BI). The interest in cloud BI is greatest among businesses and organisations. Yet, the extant literature reveals that little research related to the factors impacting the adoption of cloud BI at the level of organisations. This study aims to identify key factors that impact the adoption and utilisation of cloud BI, focusing on organisational level, which will serve as valuable resources for organisations, helping them to implement cloud BI adoption securely and efficiently in business operations. Wymer and Regan's criteria are used as the basis for analysis. From the results of the study, it is evident that there are 18 factors that significantly impact the adoption and continual usage of cloud BI services in organisations: Complexity, Privacy, Competitive pressure, Security, Government support, Availability, Relative advantage, Culture, Management support, Observability, Regulatory support, Technology readiness, Type of system, Organisation size, Trialability, Effective adaptable solutions, Compatibility, and Scalability. The findings can help Organisations, cloud BI service providers, and governments to develop cloud BI adoption strategies.

We present a new suite of numerical simulations of the star-forming interstellar medium (ISM) in galactic disks using the TIGRESS-NCR framework. Distinctive aspects of our simulation suite are (1) sophisticated and comprehensive numerical treatments of essential physical processes including magnetohydrodynamics, self-gravity, and galactic differential rotation, as well as photochemistry, cooling, and heating coupled with direct ray-tracing UV radiation transfer and resolved supernova feedback and (2) wide parameter coverage including the variation in metallicity over $Z^{\prime} \equiv Z/{Z}_{\odot }\sim 0.1-3$ , gas surface density Σ _gas ∼ 5–150 M _⊙ pc ^−2 , and stellar surface density Σ _star ∼ 1–50 M _⊙ pc ^−2 . The range of emergent star formation rate surface density is Σ _SFR ∼ 10 ^−4 –0.5 M _⊙ kpc ^−2 yr ^−1 , and ISM total midplane pressure is P _tot / k _B = 10 ^3 –10 ^6 cm ^−3 K, with P _tot equal to the ISM weight ${ \mathcal W }$ . For given Σ _gas and Σ _star , we find ${{\rm{\Sigma }}}_{\mathrm{SFR}}\propto Z{{\prime} }^{0.3}$ . We provide an interpretation based on the pressure-regulated feedback-modulated (PRFM) star formation theory. The total midplane pressure consists of thermal, turbulent, and magnetic stresses. We characterize feedback modulation in terms of the yield ϒ, defined as the ratio of each stress to Σ _SFR . The thermal feedback yield varies sensitively with both weight and metallicity as ${{\rm{\Upsilon }}}_{\mathrm{th}}\propto {{ \mathcal W }}^{-0.46}Z{{\prime} }^{-0.53}$ , while the combined turbulent and magnetic feedback yield shows weaker dependence ${{\rm{\Upsilon }}}_{\mathrm{turb}+\mathrm{mag}}\propto {{ \mathcal W }}^{-0.22}Z{{\prime} }^{-0.18}$ . The reduction in Σ _SFR at low metallicity is due mainly to enhanced thermal feedback yield, resulting from reduced attenuation of UV radiation. With the metallicity-dependent calibrations we provide, PRFM theory can be used for a new subgrid star formation prescription in cosmological simulations where the ISM is unresolved.

Voigt profile (VP) decomposition of quasar absorption lines is key to studying intergalactic gas and the baryon cycle governing the formation and evolution of galaxies. The VP velocities, column densities, and Doppler b parameters inform us of the kinematic, chemical, and ionization conditions of these astrophysical environments. A drawback of traditional VP fitting is that it can be human-time intensive. With the coming next generation of large all-sky survey telescopes with multiobject high-resolution spectrographs, the time demands will significantly outstrip our resources. Deep learning pipelines hold the promise to keep pace and deliver science-digestible data products. We explore the application of deep learning convolutional neural networks (CNNs) for predicting VP-fitted parameters directly from the normalized pixel flux values in quasar absorption line profiles. A CNN was applied to 56 single-component Mg ii λ λ 2796, 2803 doublet absorption line systems observed with HIRES and UVES ( R = 45,000). The CNN predictions were statistically indistinct from those of a traditional VP fitter. The advantage is that, once trained, the CNN processes systems ∼10 ^5 times faster than a human expert fitting VP profiles by hand. Our pilot study shows that CNNs hold promise to perform bulk analysis of quasar absorption line systems in the future.

Increased environmental consciousness and demand for sustainable materials have encouraged the use of more renewable and environmentally acceptable resources as reinforcement, for the natural fiber like the (Pineapple Leaf Fiber) PALF and Kenaf fiber material. These materials are natural fiber which are environmental friendly and biodegradable. This environmental friendly resources has been a demand in all industries including the aerospace industry. So, this project is to develop a drone frame kit made up of natural fiber. There are very less studies on the drone frame kit made up of natural fiber. Drones are mostly made up of synthetic fiber which is not biodegradable. Three designs of the drone frame kit had been designed by Fusion 360 software where the best frame kit with least stress distribution, least total deformation and least strain will be chosen to develop the frame. Ansys simulation can be used to analyze the frame kits for the finite element analysis. In the Ansys simulation the static structural part had been chosen to make the analysis where few boundary conditions added, and the mesh dependency test was done to get the best result. PALF and Kenaf had be chosen to be analyzed because those natural fiber having high tensile strength compared to other natural fiber. So as the project is to build a drone, there had been an idea of developing the frame kit natural fiber like the PALF and the Kenaf material. In conclusion, each and every design having their own uniqueness where the best design with least stress was the design with circular shape.

Combined Heat and Power Units Economic Dispatch (CHPUED) is a challenging non-convex optimization challenge in the power system that aims at decreasing the production cost by scheduling the heat and power generation outputs to dedicated units. In this article, a Kepler optimization algorithm (KOA) is designed and employed to handle the CHPUED issue under valve points impacts in large-scale systems. The proposed KOA is used to forecast the position and motion of planets at any given time based on Kepler’s principles of planetary motion. The large 48-unit, 96-unit, and 192-unit systems are considered in this study to manifest the superiority of the developed KOA, which reduces the fuel costs to 116,650.0870 USD/h, 234,285.2584 USD/h, and 487,145.2000 USD/h, respectively. Moreover, the dwarf mongoose optimization algorithm (DMOA), the energy valley optimizer (EVO), gray wolf optimization (GWO), and particle swarm optimization (PSO) are studied in this article in a comparative manner with the KOA when considering the 192-unit test system. For this large-scale system, the presented KOA successfully achieves improvements of 19.43%, 17.49%, 39.19%, and 62.83% compared to the DMOA, the EVO, GWO, and PSO, respectively. Furthermore, a feasibility study is conducted for the 192-unit test system, which demonstrates the superiority and robustness of the proposed KOA in obtaining all operating points between the boundaries without any violations.

Correct modelling and estimation of solar cell characteristics are crucial for effective performance simulations of PV panels, necessitating the development of creative approaches to improve solar energy conversion. When handling this complex problem, traditional optimisation algorithms have significant disadvantages, including a predisposition to get trapped in certain local optima. This paper develops the Mantis Search Algorithm (MSA), which draws inspiration from the unique foraging behaviours and sexual cannibalism of praying mantises. The suggested MSA includes three stages of optimisation: prey pursuit, prey assault, and sexual cannibalism. It is created for the R.TC France PV cell and the Ultra 85-P PV panel related to Shell PowerMax for calculating PV parameters and examining six case studies utilising the one-diode model (1DM), two-diode model (1DM), and three-diode model (3DM). Its performance is assessed in contrast to recently developed optimisers of the neural network optimisation algorithm (NNA), dwarf mongoose optimisation (DMO), and zebra optimisation algorithm (ZOA). In light of the adopted MSA approach, simulation findings improve the electrical characteristics of solar power systems. The developed MSA methodology improves the 1DM, 2DM, and 3DM by 12.4%, 44.05%, and 48.88%, 28.96%, 43.19%, and 55.81%, 37.71%, 32.71%, and 60.13% relative to the DMO, NNA, and ZOA approaches, respectively. For the Ultra 85-P PV panel, the designed MSA technique achieves improvements for the 1DM, 2DM, and 3DM of 62.05%, 67.14%, and 84.25%, 49.05%, 53.57%, and 74.95%, 37.03%, 37.4%, and 59.57% compared to the DMO, NNA, and ZOA techniques, respectively.

Background: Cardiovascular diseases (CVDs) are the leading non-communicable cause of morbidity and mortality worldwide. This study aimed at determining the association of metabolic risk factors with ischemic heart disease (IHD) and heart failure (HF). Methods: A cross-sectional study including 104 participants was conducted in three major hospitals between October 2020 and October 2021. All adult patients of either gender, over the age of 35, attending the CVD screening program at the family medicine clinics of the hospitals were included in the study. The physician collected demographic details, history of CVD, diabetes or hypertension, and current medication. Each patient's body mass index (BMI) was calculated, electrocardiogram (ECG) and blood tests were done. Univariate and multivariate logistic regressions were checked. Results: The mean age of the participants was 47.6 (SD = 13.5) years. Diabetes and hypertension had increased odds of IHD by 129 (CI = 6.20 – 2698.42, P = 0.002) and 195 (CI = 13.87 – 2743.11, P < 0.001) times, respectively. Diabetes mellitus (Chi2 = 11.93, P < 0.001) and hypertension (Chi2 = 14.74, P < 0.001) had significant association with HF. Dyslipidemia was significantly associated with IHD (OR = 12.41, CI = 1.15 – 134.12, P = 0.038) and high-grade HF (OR = 14.91 CI = 3.61 – 61.40, P < 0.001). Conclusion: Age, dyslipidemia, diabetes, hypertension, and left ventricular hypertrophy have significant association with IHD or HF among the study population.

The cross-industry concept of Digital Twin promises numerous benefits in areas such as product customization and predictive maintenance, but many companies often struggle to determine a starting point. Digital Twin use cases are abundant, but efforts and stakeholder benefits are difficult to estimate when developing and implementing Digital Twin applications. This paper proposes a management approach to Digital Twin use case prioritization suitable for planning Digital Twin applications at an early phase of development. Considering stakeholder satisfaction, infrastructure scalability, and effort for implementation and maintenance, we present a methodology to determine the most impactful Digital Twin use cases requiring low effort and high scalability. Tools and related methods from the fields of software development, innovation, process engineering, and product development are described, and the methodology is discussed with regard to these and other research works. An example from mechatronic product development at Siemens Healthineers Innovation Think Tank validates the approach.

The Digital Twin concept promises numerous applications across industries and its physical twin’s entire life cycle. Although numerous architectures have been proposed to develop and describe the setup of Digital Twin applications, current Digital Twin architectures do not address the versatile cross-industry character of the Digital Twin concept, its safety, security, and privacy aspects, and are often use case-specific and inflexible. We propose a three-dimensional Digital Twin reference architecture model for application across industries, considering functionality, dependability, and life cycle aspects. Our model provides practitioners a common platform to develop and discuss Digital Twin applications of different complexities and dependability aspects along varying life cycles and independent of the industry. Its applicability is validated and showcased by examples from the fields of mechatronic products, healthcare, construction, transportation, astronautics, and the energy sector. We compare our reference architecture model to existing architectures, discuss its advantages and limitations, and position the model within previous literature.

Radiography is one of the most widely used imaging techniques in the world. Since its inception, it has continued to evolve, leading to the development of intelligent and automated radiography systems that are able to perceive parts of their environment and respond accordingly. However, such systems do not provide a complete view of the examination space and are therefore unable to detect multiple objects and fully ensure the safety of patients, staff and equipment during the execution of the movement. In this paper, we present a system architecture based on ROS (Robot Operating System) to solve these challenges and integrate an autonomous X-ray device. The architecture retrieves point clouds from range sensors placed at specific locations in the examination room. By integrating different subsystems, the architecture merges the data from the different sensors to map the space. It also implements downsampling and clustering methods to identify objects and later distinguish obstacles. A subsystem generates bounding boxes based on the detected obstacles and feeds them to a motion planning framework (MoveIt!) to enable collision avoidance during motion execution. At the same time, a subsystem implements a deep neural network model (PointNet) to classify the detected obstacles. Finally, the developed system architecture provided promising results after being deployed in a Gazebo simulated examination space and on a use case test platform.

An unprecedented array of new observational capabilities are starting to yield key constraints on models of the epoch of first light in the Universe. In this Letter we discuss the implications of the UV radiation background at cosmic dawn inferred by recent JWST observations for radio experiments aimed at detecting the redshifted 21 cm hyperfine transition of diffuse neutral hydrogen. Under the basic assumption that the 21 cm signal is activated by the Ly α photon field produced by metal-poor stellar systems, we show that a detection at the low frequencies of the EDGES and SARAS3 experiments may be expected from a simple extrapolation of the declining UV luminosity density inferred at z ≲ 14 from JWST early galaxy data. Accounting for an early radiation excess above the cosmic microwave background suggests a shallower or flat evolution to simultaneously reproduce low- and high- z current UV luminosity density constraints, which cannot be entirely ruled out, given the large uncertainties from cosmic variance and the faint-end slope of the galaxy luminosity function at cosmic dawn. Our findings raise the intriguing possibility that a high star formation efficiency at early times may trigger the onset of intense Ly α emission at redshift z ≲ 20 and produce a cosmic 21 cm absorption signal 200 Myr after the Big Bang.

Objective:This study aimed to retrospectively reveal the seroprevalence of Toxoplasma gondii (T. gondii) in pregnant women with routine pregnancy follow-up.Methods:Anti-T. gondii IgM-IgG antibody values of pregnant women aged 16-49 years, who had routine pregnancy follow-up in January-December 2019 were analysed retrospectively.Results:Of the 1.832 serum samples, in which the anti-T. gondii IgG test was studied, 28.7% were found to be positive, 70.4% were negative and 0.9% was found to be suspicious. For anti-T. gondii IgM, 0.7% of the 1.844 serum samples were evaluated as positive, 99.5% as negative and 0.1% as suspicious. The positivity rates was observed to increase as age decreases in anti-Toxoplasma IgM (r=0.144, p=0.001), and the positivity rates increase as the age increases in the anti-Toxoplasma IgG (r=0.061, p=0.001). In the nationality evaluation, the anti-T. gondii IgM and IgG positivity rates were observed to be higher in Syrian pregnant women compared to Turkish pregnant women.Conclusion:In our study, a significant portion of pregnant women were observed to be non-immune to the agent, and therefore informing these people about the protection methods from the parasite in order to prevent infection occurrence is important.

Power flow is the backbone for power system operation and control. Power system balancing, where supply of energy has to equal demand all time, is a very important operation constraint for electric power systems. In recent years, penetration of Distributed Energy Resources (DERs) especially Renewable Energy Sources (RESs) into the distribution system has increased. RESs are known by their intermittent behavior in nature. Hence, as the number of these RESs increases, the sudden frequent change in power flow increases. Therefore, new obstacles to the operation and control of power systems arise. Power distribution system is also sparse and large system. Moreover, most traditional power flow solutions are based on iterative techniques which obviously take time. Therefore, computation time is a real problem when finding power flow solutions at distribution system especially with the unpredictability of RESs. To overcome these problems, a real-time linearized three-phase AC Power Flow (ACPF) model at distribution system is proposed. In this paper the linearized ACPF at distribution system is molded as follows. First Quasi linearized ACPF equations are developed for short period of time based on Newton's Raphson (NR) method. Second sparse reordering algorithm techniques are used to reorder the node numbering of the power distribution system to reduce computational time. Then, simulation on IEEE 4 bus power system and IEEE 37 bus power distribution system are presented to validate the proposed model. Furthermore, Monte Carlo simulation is used to test the robustness of the proposed model.

Industry 4.0 and digital transformation will likely come with an era of changes for most manufacturers and tech industries, and even healthcare delivery will likely be affected. A few trends are already foreseeable such as an increased number of patients, advanced technologies, different health-related business models, increased costs, revised ethics, and regulatory procedures. Moreover, cybersecurity, digital invoices, price transparency, improving patient experience, management of big data, and the need for a revised education are challenges in response to digital transformation. Indeed, forward-looking innovation about exponential technologies and their effect on healthcare is now gaining momentum. Thus, we developed a framework, followed by an online survey, to investigate key areas, analyze and visualize future-oriented developments concerning technologies and innovative business models while attempting to translate visions into a strategy toward healthcare democratization. When forecasting the future of health in a short and long-term perspective, results showed that digital healthcare, data management, electronics, and sensors were the most common predictions, followed by artificial intelligence in clinical diagnostic and in which hospitals and homes would be the places of primary care. Shifting from a reactive to a proactive digital ecosystem, the focus on prevention, quality, and faster care accessibility are the novel value propositions toward democratization and digitalization of patient-centered services. Longevity will translate into increased neurodegenerative, chronic diseases, and mental illnesses, becoming severe issues for a future healthcare setup. Besides, data privacy, big data management, and novel regulatory procedures were considered as potential problems resulting from digital transformation. However, a revised education is needed to address these issues while preparing future health professionals. The “P4 of health”, a novel business model that is outcome-based oriented, awareness and acceptance of technologies to support public health, a different mindset that is proactive and future-oriented, and an interdisciplinary setting to merge clinical and technological advances would be key to a novel healthcare ecosystem. Lastly, based on the developed framework, we aim to conduct regular surveys to capture up-to-date technological trends, sustainable health-related business models, and interdependencies. The engagement of stakeholders through awareness and participation is the key to recognizing and improving healthcare needs and services.

5G is the next-generation mobile cellular network that offers significant advantages over other wireless network technologies, such as data throughput, latency, real-time multicasting, ad hoc peer-to-peer, and data encryption, to name a few. A critical sector for potentially disruptive 5G solutions is healthcare and its current IoMT infrastructure. This paper analyses the current pain points associated with the general radiology workflow for X-ray imaging in terms of user interfaces and network technologies. By understanding this workflow and the modern 5G technology standards, we have designed a system-level architecture for a private 5G network within a hospital that includes additional services over the core and a different architecture for telecommunication networks. In addition, we have designed a lower-level architecture for a 5G collimator interfacing use case, with a network protocol stack designed for use case realization. With these 5G architectures implemented, a new, novel radiology workflow, was visualized, with clear benefits arising from the 5G innovations highlighted. We also highlighted the resulting limitations of the current design and outlined the next development steps and hypothesized future visions.

A Digital Twin is an auspicious cross-industry concept in the era of digitalization, which promises a wide range of benefits such as efficiency improvements, predictions of future opportunities and challenges, and respective recommendations. At present, a variety of definitions and terms exist, causing increasing confusion among practitioners and users. Here we address this need for consolidation with a holistic view of the Digital Twin concept across industries. We analyze classification models and Digital Twin terms in academia and industry in order to propose a 5-dimension cross-industry Digital Twin applications model. This model, based on the core three-part Digital Twin concept introduced by Grieves in 2002, enables ease of understanding and cross-industry classification and development of applications within the concept of the Digital Twin. The proposed model consists of the dimensions scope of the physical entity, feature(s) of the physical entity, form of communication, scope of the virtual entity, and user-specific outcome/value created.

Pandemi virus Covid-19 yang merebak di tanah air sejak awal Maret 2020 merubah hampir semua sendi kehidupan, termasuk kaktifitas pendidikan. Proses belajar mengajar harus beralih dari rumah masing-masing siswa dengan bantuan teknologi informasi. Kegiatan belajar dari rumah tersebut memerlukan pendampingan orang tua. Oleh karenya, orang tua berperan lebih dalam mendampingi anak-anaknya. Artikel ini bertujuan mengidentifikasi berbagai peran orang tua dalam pembentukan karakter anak di masa pandemic Covid-19 ditinjau dari aspek pendidikan Islam. Dengan pelacakan kepustakaan (library research) dan mengafirmasi pernyataan beberapa orang tua siswa yang diwawancarai, penelitian ini menyimpulkan bahwa orang tua berperan lebih dalam membentuk karakter anak menunju insan paripurna, yakni berperan sebagai pendidik (educator), fasilitator, motivator, pendamping dan pengawas, serta sebagai figur yang dicontoh anak (al-uswah al-hasanah). Selain itu, orang tua memiliki tantangan lebih dalam membimbing dan mengawasi anak selama masa belajar dari rumah akibat penggunaan gadget yang terkadang disalahgunakan oleh anak.

Healthcare providers as well as medical technologists lay a strong focus on clinical conditions for patient centric care delivery. Currently, the challenges are to (1) obtain a consolidated view of various stakeholders and pain points for the entire disease lifecycle, (2) identify interdependencies between different stages of the disease, and (3) prioritize solutions based on customer needs. A structured approach is required to address clinical needs across disease care plans tailored to different geographies and ethnicities. Innovation Think Tank (ITT) teams across multiple locations formed focus groups to elaborate the pathways of 22 global diseases, selected based on ranking of associated economic burden and threat to life. Ideation sessions were held to identify pain points and find innovative solutions. Additionally, inputs were taken from co-creation sessions at universities worldwide. The optimization and design of infographics and care plan was done based on the key information gathered—facts and figures, stakeholders, pain points and solutions. Finally, validation was obtained from clinical and technology experts globally. A disease pathway framework was created to develop pathways for 22 global diseases. Over 1,500 pain points were collected and about 1,900 ideas were proposed. The approach was applied to optimize its application to 30 product and portfolio definition projects over 2 years at Siemens Healthineers, as well as co-creation programs with universities and hospitals. The disease pathway framework provides a unique foundation for extensive collaboration among multiple stakeholders, through information sharing and delivering high-quality solutions based on the identified problems and customer needs.

Stripe rust is a continuous threat to wheat crop all over the world. It causes considerable yield losses in wheat crop every year. Continuous deployment of adult plant resistance (APR) genes in newly developing wheat cultivars is the most judicious strategy to combat this disease. Herein, we dissected the genetics underpinning stripe rust resistance in Pakistani wheat germplasm. An association panel of 94 spring wheat genotypes was phenotyped for two years to score the infestation of stripe rust on each accession and was scanned with 203 polymorphic SSRs. Based on D´ measure, linkage disequilibrium (LD) exhibited between loci distant up to 45 cM. Marker-trait associations (MTAs) were determined using mixed linear model (MLM). Total 31 quantitative trait loci (QTLs) were observed on all 21 wheat chromosomes. Twelve QTLs were newly discovered as well as 19 QTLs and 35 previously reported Yr genes were validated in Pakistani wheat germplasm. The major QTLs were QYr.uaf.2AL and QYr.uaf.3BS (PVE, 11.9%). Dissection of genes from the newly observed QTLs can provide new APR genes to improve genetic resources for APR resistance in wheat crop.

Cotton being the major fiber crop across the world is exposed to numerous biotic and abiotic stresses. Genetic transformation of cotton is vital to meet the world's food, feed and fiber demands. Genetic manipulation by randomly transferring the genes emanate variable gene expression. Targeted gene insertion by latest genome editing tools results in predictable expression of genes at a specified location. Gene stacking technology emerged as an adaptive strategy to combat biotic and abiotic stresses by integrating 2-3 genes simultaneously and at a specific site to avoid variable gene expression at diverse locations. This study explains the development of cotton's founder transformants to be used as a base line for multiple gene stacking projects. We introduced Cre and PhiC31 mediated recombination sites to specify the locus of incoming genes. CRISPR-Cas9 gene was integrated for developing CRISPR based founder lines of cotton. Cas9 gene along with gRNA was integrated to target Rep (replication) region of cotton leaf curl virus. Replication region of virus was specifically targeted to diminish further proliferation and preventing the virus to develop new strains. To successfully develop these primary transformants, a model transformation system has been optimized with the red color visualization (DS-Red). Following red color transformation system, three baselines with recombination specified site (Rec), targeted replication region (Rep) and Cas9 founder lines have been developed. These founder transformants are useful for developing recombinase mediated and CRISPR/Cas9 based originator lines of cotton. Moreover, these transformants will set up a base system for all the recombinase mediated gene stacking projects.

It has been claimed that traditional models struggle to explain the tentative detection of the 21 cm absorption trough centered at z ∼ 17 measured by the EDGES collaboration. On the other hand, it has been shown that the EDGES results are consistent with an extrapolation of a declining UV luminosity density, following a simple power law of deep Hubble Space Telescope observations of 4 < z < 9 galaxies. We here explore the conditions by which the EDGES detection is consistent with current reionization and post-reionization observations, including the neutral hydrogen fraction at z ∼ 6–8, Thomson-scattering optical depth, and ionizing emissivity at z ∼ 5. By coupling a physically motivated source model derived from radiative transfer hydrodynamic simulations of reionization to a Markov Chain Monte Carlo sampler, we find that it is entirely possible to reconcile existing high-redshift (cosmic dawn) and low-redshift (reionization) constraints. In particular, we find that high contributions from low-mass halos along with high photon escape fractions are required to simultaneously reproduce cosmic dawn and reionization constraints. Our analysis further confirms that low-mass galaxies produce a flatter emissivity evolution, which leads to an earlier onset of reionization with a gradual and longer duration, resulting in a higher optical depth. While the models dominated by faint galaxies successfully reproduce the measured globally averaged quantities over the first one billion years, they underestimate the late redshift-instantaneous measurements in efficiently star-forming and massive systems. We show that our (simple) physically motivated semianalytical prescription produces results that are consistent with the (sophisticated) state-of-the-art THESAN radiation-magnetohydrodynamic simulation of the reionization.

We explore the role of galactic feedback on the low-redshift Ly α (Ly α ) forest ( z ≲ 2) statistics and its potential to alter the thermal state of the intergalactic medium. Using the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) suite, we explore variations of the AGN and stellar feedback models in the IllustrisTNG and Simba subgrid models. We find that both AGN and stellar feedback in Simba play a role in setting the Ly α forest column density distribution function (CDD) and the Doppler width ( b -value) distribution. The Simba AGN jet feedback mode is able to efficiently transport energy out to the diffuse IGM, causing changes in the shape and normalization of the CDD and a broadening of the b -value distribution. We find that stellar feedback plays a prominent role in regulating supermassive black hole growth and feedback, highlighting the importance of constraining stellar and AGN feedback simultaneously. In IllustrisTNG, the AGN feedback variations explored in CAMELS do not affect the Ly α forest, but varying the stellar feedback model does produce subtle changes. Our results imply that the low- z Ly α forest can be sensitive to changes in the ultraviolet background, stellar and black hole feedback, and that AGN jet feedback in particular can have a strong effect on the thermal state of the IGM.

This research aims to document and analyze the maritime cultural heritage held by the fishing communities in the Kepulauan Sangkarrang district, Makassar city. Maritime cultural heritage encompasses various aspects, such as traditional knowledge of navigation, fishing techniques, traditional tools, and religious practices related to maritime activities. The research methods include field surveys, in-depth interviews, participatory observations, and document analysis. The collected data will be qualitatively analyzed to identify cultural patterns associated with the maritime life of the fishing communities. This research aims to uncover the maritime cultural heritage of the fishing communities in Kepulauan Sangkarrang Subdistrict, Makassar City, Indonesia. The main results include a profound understanding of local maritime traditions and their history, as well as an increased historical awareness among the local community. The primary conclusion is that the preservation of maritime culture can support sustainable tourism development and community empowerment. This research has the potential to make a significant contribution in the context of science and maritime cultural preservation.

The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N -body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Ly α spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N -body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io .

Genetic diversity is the base of any genetic improvement breeding program aimed at stress breeding. The variability among breeding materials is of primary importance in the achievements of a good crop production. Herein, 105 wheat genotypes were screened against drought stress using factorial completely randomized design at seedling stage to determine the genetic diversity and traits association conferring drought tolerance. Analysis of variances revealed that all the studied parameters differed significantly among all genotypes, indicating the significance genetic variability existed among all genotypes for studied indices. The 10 best performance genotypes G1, G6, G11, G16, G21, G26, G39, G44, G51, and G61 were screened as drought tolerant, while five lowest performance genotypes G3, G77, G91, G98, and G105 were screened as drought susceptible. Root length, chlorophyll a, chlorophyll b, and carotenoid contents were significantly correlated among themselves which exhibited the importance of these indices for rainfed areas in future wheat breeding scheme. Shoot length exhibited non-significant and negative association with other studied traits, and its selection seems not to be a promising criteria for this germplasm for drought stress. Best performance genotypes under drought stress conditions will be useful in future wheat breeding program and early selection will be effective for developing high yielding and drought tolerant wheat varieties.

The regeneration of the high-yielding multilocular types has not been attempted, although successful regeneration and transformation in brassica have been done. Here, we report efficient regeneration and transformation protocols for two B. rapa genotypes; UAF11 and Toria. The B. rapa cv UAF11 is a multilocular, non-shattering, and high-yielding genotype, while Toria is the bilocular type. For UAF11 8 shoots and for Toria 7 shoots, explants were observed on MS supplemented with 3 mg/L BAP + 0.4 mg/L NAA + 0.01 mg/L GA3 + 5 mg/L AgNO3 + 0.75 mg/L Potassium Iodide (KI), MS salt supplemented with 1 mg/L IBA and 0.37 mg/L KI produced an equal number of roots (3) in UAF11 and Toria. For the establishment of transformation protocols, Agrobacterium-mediated floral dip transformation was attempted using different induction media, infection time, and flower stages. The induction medium III yielded a maximum of 7.2% transformants on half-opened flowers and 5.2% transformants on fully opened flowers in UAF11 and Toria, respectively, with 15 min of inoculation. This study would provide the basis for the improvement of tissue culture and transformation protocols in multilocular and bilocular Brassica genotypes.

The typical curriculum of training and educating future clinicians, biomedical engineers, health IT, and artificial intelligence experts lacks needed twenty first-century skills like problem-solving, stakeholder empathy, curiosity stimulation, entrepreneurship, and health economics, which are essential generators and are pre-requirements for creating intentional disruptive innovations. Moreover, the translation from research to a valuable and affordable product/process innovation is not formalized by the current teachings that focus on short-term rather than long-term developments, leading to inaccurate and incremental forecasting on the future of healthcare and longevity. The Stanford Biodesign approach of unmet clinical need detection would be an excellent starting methodology for health-related innovation work, although unfortunately not widely taught yet. We have developed a novel lecture titled HealthTec Innovation Design (HTID) offered in an interdisciplinary setup to medical students and biomedical engineers. It teaches a future-oriented view and the application and effects of exponential trends. We implemented a novel approach using the Purpose Launchpad meta-methodology combined with other innovation generation tools to define, experiment, and validate existing project ideas. As part of the process of defining the novel curriculum, we used experimentation methods, like a global science fiction event to create a comic book with Future Health stories and an Innovation Think Tank Certification Program of a large medical technology company that is focused on identifying future health opportunities. We conducted before and after surveys and concluded that the proposed initiatives were impactful in developing an innovative design thinking approach. Participants' awareness and enthusiasm were raised, including their willingness to implement taught skills, values, and methods in their working projects. We conclude that a new curriculum based on HTID is essential and needed to move the needle of healthcare activities from treating sickness to maintaining health.

Abstract Downstream of Cape Hatteras, the Gulf Stream (GS) is bounded to the north by a sharp temperature front known as the North Wall (NW). Previous studies have generally assumed that variations of the NW and GS are equivalent. Using satellite sea surface height to identify the GS and the 15 °C isotherm at 200‐m depth to represent the NW, this paper examines their similarities and differences during 1993–2016. The NW and GS are geographically close and vary similarly only to the west of 71°W. Downstream of that, they rapidly diverge—and the variances of their latitudes increase by more than a factor of 2—as the GS flows past the New England Seamounts. Evidence is presented to show that the difference in properties of the NW and the GS is related to the presence of mesoscale eddies in the region separating them.

The purpose of this study was to investigate the effects of circadian rhythm on anaerobic performance and body temperature determined through three different methods. Ten elite male taekwondo athletes (average age: 23.9±2.7 years, height: 178.7±4.9 cm, body mass: 72.1±7.8 kg, training experience: 12.5±4.9 years) participated in the study. The body temperatures of the participants were measured in the morning of the first day, (between 09:00-10:00 a.m.), and in the early evening (between 16:00-17:00 p.m.) through three different methods (Core body temperature, tympanic temperature, and skin surface temperature). The participants performed Wingate test (WT) both in the morning and in the early evening. Core body temperature was significantly higher in early evening than it was in the morning (p lt;0.05), while tympanic and skin surface temperatures remained unchanged (p gt;0.05). However, there was no significant difference between morning and early evening for peak power, mean power, and fatigue index values (p gt;0.05). As a result, a significant increase was observed in core body temperature in early evening compared to morning, but this increase did not show a positive effect on anaerobic performance.

Fish is a fundamentally healthy food, loaded with essential nutrients, high protein content, vitamin D, and omega-three fatty acid. Mislabeling is a common problem in the fish industry that causes an imbalance in prices and fluctuation in the market. DNA barcoding is a potential technique for authentication of mislabeled and misidentified fish species. In this study, 11 freshwater and 6 marine fish species were used for DNA barcoding and further authentication using the mitochondrial cytochrome b (Cyt b) gene. Cyt b was amplified using PCR, producing an average read length of 1,141 bp. The obtained sequences were compared to the National Center for Biotechnology Information database (NCBI) using the Basic Local Alignment Search Tool (BLAST). The average AT content (55.20%) was higher than the average GC content (44.78%) in marine and freshwater fish species. The mean genetic Kimura 2-parameter distances for species, genus, families, and orders were 0.311, 0.308, 0.023, and 0.337, respectively. Phylogenetic tree analysis revealed that most of the freshwater fish species clustered together due to the fact that they were in the same order or family, while the marine fish species clustered distantly. Single nucleotide polymorphism (SNP) analysis of all species in the study revealed distinct features regarding unique sites. All fish species could be identified based on their unique SNP profiles. Based on SNP data, DNA sequence based QR codes were developed for accurate identification of fish species. This is the first study to develop DNA-based QR barcodes for proper authentication of species during the chain of custody using simple technology.

Abstract Advances in Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated system (CRISPR/Cas9) has dramatically reshaped our ability to edit genomes. The scientific community is using CRISPR/Cas9 for various biotechnological and medical purposes. One of its most important uses is developing potential therapeutic strategies against diseases. CRISPR/Cas9 based approaches have been increasingly applied to the treatment of human diseases like cancer, genetic, immunological and neurological disorders and viral diseases. These strategies using CRISPR/Cas9 are not only therapy oriented but can also be used for disease modeling as well, which in turn can lead to the improved understanding of mechanisms of various infectious and genetic diseases. In addition, CRISPR/Cas9 system can also be used as programmable antibiotics to kill the bacteria sequence specifically and therefore can bypass multidrug resistance. Furthermore, CRISPR/Cas9 based gene drive may also hold the potential to limit the spread of vector borne diseases. This bacterial and archaeal adaptive immune system might be a therapeutic answer to previous incurable diseases, of course rigorous testing is required to corroborate these claims. In this review, we provide an insight about the recent developments using CRISPR/Cas9 against various diseases with respect to disease modeling and treatment, and what future perspectives should be noted while using this technology.