Due to the complexity, high-risk, and conservative character of construction companies, advanced digital technologies do not become widely adopted in the short term, while vendors make determined efforts to overcome this and disseminate their technologies. This paper presents the methods of an investigation addressing the extremely complex issues related to the current practices of digital technology adoption in construction. It discusses how construction companies follow a specific logical process linked to need, project objectives, characteristics of the adopting organization, and the characteristics of the new technology to be adopted. The study aims to demonstrate a novel method of data collection and analysis including data and methodological triangulation techniques including the use of NVivo and AHP to explore how companies make the decision to uptake a new technology (e.g. advanced crane, tunnel boring machine or drones) by focusing on customer and vendor activities, their interactions, contributing factors, and people involved in the process. The major original contribution of this paper is to develop an innovative methodological Cube for investigating the Construction Technology Adoption Process (CTAP) covering technology adoption, acceptance, diffusion and implementation concepts. CTAP is a framework that delineates the phases of the process that customer organizations use when deciding to adopt a new digital technology and the parallel vendor activities. The significance of these contributions is that they enable vendors to understand how to match their strategies with customer expectations in each phase of the CTAP. It also provides a benchmark for new construction companies to use the current best practice of decision making. Future research is warranted to more clearly delineate any differences with developing nations or related industries such as mining and property management.

The County of Avon in England was abolished in 1996 and replaced by four unitary planning authorities. Recently the authorities have been working closely to develop a West of England Joint Spatial Plan to facilitate better integration of policies on transport, housing, the environment etc. The Joint Spatial Plan team commissioned a multidisciplinary study to investigate whether the West of England has special characteristics of 'place' that engender shared interest and regional affinity, i.e. ‘sense of place’, to which emerging planning policies might positively respond. In this regard the present article is particularly focused on identifying whether the West of England has unique and unifying landscape characteristics, relating to topography, rural scenery, and flora and fauna, which combine with human experiences to distinguish the Region from adjoining areas. It is concluded that the West of England does indeed have real geographical integrity, being bound on all sides by attractive and prominent landscape features - the Mendip Hills, Cotswold Hills and Severn Estuary – that contribute to a sense of identity and belonging among its inhabitants. The alternating limestone ridges and broad clay vales that prevail across the Region’s heart, combined with low lying flatlands on the Region’s western fringe, provide further contrast with neighbouring regions, reinforcing the emotional bond to the landscape. Furthermore, it is suggested that the inhabitants of the West England show a particularly special environmental consciousness that sets them apart from neighbouring populations, complementing the influence of the physical environment in making the Region a special place to live.

Though Cyber Physical Systems (CPS) become very popular in last the decade, dependability of CPS is still a critical issue and related survey is rare. We try to spell out the jigsaw of technologies and figure out the technical trends of dependable self-managing CPS. This survey first recalls the motivation and the similar concepts. By analyzing four generic architectures, we summarize the common characteristics and related assurance technologies, and propose a more generic environment-in-loop processing flow of CPS and a formal interaction flow between physical space and cyber space. Further, the similarity between correctness and dependability is formally analyzed and the new five research questions of dependable self-managing CPS are presented. Then we review the critical technologies and related correctness verification & validation (V&V) methods, the architectures for dependable self-managing CPS. Further, the detail dependability management and V&V technologies are surveyed, which covers the areas of running-time fault management methods and whole life cycle V&V technologies, maintenance and available tool sets. For holistic CPS development, Modeling techniques and MDE (model driven engineering) based V&V methods are analyzed in detail. Then we complete the jigsaw of technologies and figure out the missing part. Further, we propose the technical challenges and the further direction. To our best knowledge, this is the first comprehensive survey on dependable self-managing CPS development and evaluation.

Milk analysis is critical to determine its intrinsic quality, as well as its nutritional and economic value. Currently, the advancements and utilization of spectroscopy-based techniques combined with machine learning algorithms have made feasible the development of analytical tools and re-al-time monitoring and prediction systems in the dairy ruminant sector. The objectives of the cur-rent review were i) to describe the most widely applied spectroscopy-based and supervised ma-chine learning methods utilized for the evaluation of milk components, origin, technological properties, adulterants, and drugs residues, ii) to present and compare the performance and adaptability of these methods and their most efficient combinations, providing insights into the strengths, weaknesses, opportunities, and challenges of the most promising ones regarding the capacity to be applied in milk quality monitoring systems both at the point-of-care and beyond, and iii) to discuss their applicability and future perspectives for the integration of these methods in milk data analysis and decision support systems across the milk value-chain.

Currently, there are no U.S. Food and Drug Administration (FDA)-approved medical countermeasures (MCMs) for radiation combined injury (RCI), partially due to limited understanding of its mechanisms. Our previous research suggests that endothelial dysfunction may contribute to a poor prognosis of RCI. In this study, we demonstrated an increased risk of mortality, body weight loss and delated skin wound healing in RCI mice compared to mice with skin wound alone or radiation injury (RI) 30 days post-insult. Furthermore, we evaluated biomarkers of endothelial dysfunction, inflammation, and impaired wound healing in mouse at early time points after RCI. Mice were exposed to 9.0 Gy total body irradiation (TBI) followed by skin wound. Samples were collected on days 3, 7, and 14 post-TBI. Endothelial dysfunction markers were measured by ELISA, and skin wound healing was assessed histologically. Our results show that endothelial damage and inflammation are more severe and persistent in RCI compared to wound-alone. Additionally, RCI impairs granulation tissue formation, reduces myofibroblast presence, and delays collagen deposition, correlating with more severe endothelial damage. TGF signaling may plays a key role in this impaired healing. These findings suggest that targeting endothelial dysfunction and TGF-β pathways may provide potential therapeutic strategies for improving delayed wound healing in RCI, which could subsequently influence outcomes such as survival after RCI.

Psychosis in Alzheimer's disease (AD) is a prevalent phenomenon, marked by delusions and hallucinations, along with other neuropsychiatric symptoms such as agitation, depression, anxiety, and apathy. These neuropsychiatric symptoms, also known as behavioral and psychological symptoms of dementia (BPSD), affect up to 97% of Alzheimer's patients. The presence of psychosis in AD significantly impacts patients' daily lives and places a considerable burden on caregivers. The development of AD-related psychosis (ADP) is influenced by a range of factors, including genetic predispositions and life-acquired factors. AD affects cognitive function and various brain regions, resulting in widespread brain atrophy. In addition to its neurological impact, AD can induce pathological physiological changes that serve as biomarkers for ADP. Research efforts have focused on developing pharmacological treatments for psychosis in AD, aiming to minimize side effects. Brexpiprazole has emerged as a promising medication for ADP, alongside other antipsychotics. Treatment approaches for ADP extend beyond pharmacology, incorporating methods such as sensory stimulation and digital therapeutics. This review will explore the characteristics of psychosis in Alzheimer's disease, the pathological underpinnings of ADP, and the current therapeutic landscape, highlighting emerging opportunities for managing this challenging condition.

The relationships between the relative abundances of chemical elements and their second ionization potentials, as well as their condensation temperatures, were analyzed using four published homogeneous abundance surveys of halo and thin disk stars. We selected 932 stars with effective temperatures ranging from 4900 K to 5900 K and used the abundances of 10 chemical elements common across all surveys: Mg, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, and Ni. The correlation coefficients between the relative abundances of these elements and their second ionization potentials and condensation temperatures were investigated in relation to metallicity and the stars' location in the Galaxy. The observed correlations may result from certain physical processes, such as the accretion of interstellar gas onto stellar atmospheres. We also analyzed the dependencies of relative abundances on second ionization potentials based on published abundance patterns in five halo stars. Evidence of charge-exchange reactions in the atmospheres of these stars was found. For more accurate determination of stellar ages from the abundance ratios of radioactive and stable chemical elements in stellar atmospheres, processes such as charge-exchange reactions and dust-gas separation should be considered in future detailed investigations. Additionally, changes in the chemical abundances in the atmospheres of halo stars after crossing the Galactic plane were found to be possible.

The adoption of enterprise social platforms (ESPs) has become increasingly important for small and medium-sized enterprises (SMEs) seeking to enhance communication, collaboration, and knowledge sharing in the digital economy. As digital transformation progresses, the role of ESPs in improving operational efficiency and long-term business performance warrants comprehensive evaluation. This systematic review aims to assess the impact of leading ESPs on SME performance, focusing on their capabilities to improve communication efficiency, interdepartmental collaboration, and cost-effectiveness while highlighting emerging trends such as automation and AI integration. A PRISMA-guided systematic review was conducted, analyzing 18 peer-reviewed studies published between 2014 and 2024. Inclusion criteria comprised English-language publications examining ESP adoption in SMEs, focusing on ESP features and their effects on operational and strategic outcomes. Quantitative analysis of the selected studies revealed that ESPs improve communication efficiency by 20% and enhance interdepartmental collaboration by 25%. While initial implementation costs pose challenges, ESPs contribute to a 15% reduction in operational costs over time. Additionally, trends in automation and AI integration suggest further potential for operational enhancements. The findings indicate that ESPs significantly enhance SMEs' competitiveness and sustainability, offering both immediate operational improvements and long-term strategic growth. Business leaders are encouraged to adopt ESPs to foster agility and innovation while ensuring robust data security measures.

Allogeneic hematopoietic stem cell (HSC) transplants are usually used in cases where patients have active cancerous illness in their bone marrow, but allogeneic transplants can cause graft vs. host disease. If autologous HSCs could be purged of cancer cells, they could then be used for transplantation purposes without concern. It is still controversial whether purging is necessary, but it certainly would alleviate concerns. A novel method of purging is discussed herein that does not require chemotherapy and is targeted for each patient. It could be applied either in vitro or in vivo.

The adoption of Data Networks and Application Programming Interfaces (APIs) has become crucial for small and medium enterprises (SMEs) to streamline operations, improve efficiency, and reduce costs. However, SMEs often face challenges such as resource limitations and security vulnerabilities, which hinder their ability to fully leverage these technologies. This systematic review examines the role of Data Networks and APIs in enhancing operational efficiency within SMEs, focusing on key metrics such as speed, cost reduction, scalability, and security challenges. Following PRISMA 2020 guidelines, we conducted a systematic search across multiple databases including Web of Science, Scopus, IEEE Xplore, and Google Scholar. Studies published between 2014 and 2024, focused on SMEs and addressing the role of Data Networks and APIs in operational efficiency, were included. A total of 49 studies met the inclusion criteria and were analyzed for key outcomes related to operational efficiency, cost-effectiveness, and security risks. The review found that Data Networks and APIs significantly improve operational efficiency by increasing process speed (12% increase), reducing operational costs (8% reduction), and enhancing overall productivity. However, security challenges, particularly related to API vulnerabilities, were a major concern, with cyberattacks on APIs increasing by 400% in Q1 2023 alone. Despite these risks, the benefits of implementing Data Networks and APIs in SMEs, particularly in terms of scalability and real-time data processing, were evident across industries. Data Networks and APIs offer substantial improvements in operational efficiency for SMEs, though security remains a significant challenge. Future efforts should focus on developing security frameworks tailored to SMEs while maintaining the operational benefits of these technologies. Further research is needed to explore scalable and secure API models for SMEs.

Search for the new non-invasive methods of investigating the functioning of human internal organs is an urgent task. One of these methods for assessing the functioning of the human res-piratory system is electromagnetic sensing, based on a significant difference in the dielectric permittivity of muscle tissue and air. During breathing, when the lungs are filled with air, the dielectric permittivity of the lungs decreases, which leads to a change in the level of the elec-tromagnetic signal passing through the body. Results of experiments on recording changes in the level of electromagnetic radiation passing through the human body, performed on an experimental device consisting of eight transmitting and receiving antennas located on opposite sides of the chest have been presented in the article. The possibility of visualizing the measured “pulmonograms” in the form of dynamic two-dimensional images showing the process of filling various parts of the lungs with air has been demonstrated.

Salt marshes in the southern North Sea are part of the UNESCO World Heritage Site Wadden Sea, the largest unbroken system of intertidal sand and mud flats in the world. They provide a very high nature value while significantly contributing to coastal flood and erosion risk management as a nature-based element of flood and erosion risk management systems for the densely populated coastal area. Climate change-induced sea-level rise is a significant concern: An integrated approach to salt marsh management adapted to the effects of climate change necessitates a understanding of the impact of different management strategies. This review commences with a description of the biogeomorphological conditions and processes in salt marshes for a better understanding of the natural dynamics and how they are influenced by management and climate change. In a second step, the impact of salt marshes on hydrodynamic processes and their role as nature-based element of flood and erosion risk management is presented. Management options and implementation methods are discussed and analysed concerning coastal flood management and nature conservation requirements. In conclusion, a targeted salt marsh management needs to consider the initial conditions and the development aims of the specific site integrated in a conceptual framework. Salt marshes have the potential to adapt to sea-level rise, thereby contributing to the long-term protection of coastal areas.

The emergence of superhydrophobicity-based antibacterial materials represents a promising approach to upholding surface cleanliness and hygiene, effectively preventing bacterial adhesion. This research describes the synthesis of a superhydrophobic coating with antibacterial and bacteriostatic properties using silica nanoparticles (SiO2 NPs) modified with 1H,1H,2H,2H-Perfluorodecyltriethoxysilane (PFDTES). TEM, XRD, EDS, SEM, and FTIR analyses were conducted to study its morphology and surface characterization. Additionally, the coating was applied on glass substrates using the spray coating method, varying the number of layers to evaluate antibacterial and bacteriostatic properties through turbidimetry and inhibition halo measurement techniques. The durability of the coatings was also assessed by exposing them to outdoor conditions for 35 days. This study aimed to evaluate the antibacterial capacity of the superhydrophobic coating and its weather resistance. The results demonstrate that a superhydrophobic coating with a contact angle ≥150° and a sliding angle ≤10° was successfully synthesized using SiO2 NPs smaller than 10 nm modified with PFDTES. The coating exhibited the ability to inhibit bacterial growth by preventing the adhesion of bacteria such as Escherichia coli and Staphylococcus aureus; moreover, the number of layers correlated with enhanced antibacterial properties. The coating also showed good durability under outdoor conditions. These results support the potential application of superhydrophobic coatings to prevent these bacteria from adhering and growing in areas where they can be harmful.

Sodium phenyl dithiocarbamate (pl-dtc) as a ligand was prepared from the reaction of aniline (C6H5-NH2) and carbon(IV) sulfide (CS2) in the presence of sodium hydroxide via method of one-pot synthesis. Two coordination compounds ([VO(sfz)(pl-dtc)] and [Zn(sfz)(pl-dtc)]) from respective oxovanadium (IV) sulfate hydrate and zinc (II) chloride were prepared with mixed ligands involving sodium sulfadiazine (sfz) and the synthesized pl-dtc crystals, also via the method of one-pot synthesis. Structural analyses of the ligand and coordination compounds were assessed using characterization techniques involving physicochemical parameters and spectral analysis ( FT-IR, UV-Vis and NMR (1H NMR and 13C NMR) to confirm their synthenses and structures. Additionally, pl-dtc crystals which grew from the pl-dtc solution when refrigerated after five days, has its structure confirmed and revealed when subjected to single crystal x-ray crystallography technique. Differences in results of spectral analysis between ligands and their respective coordination compounds confirmed the coordination between ligands and coordination compounds. The in vitro antibacterial studies showed that the ligands had modest activity against Gram positive bacteria: Staphylococcus aureus, while, the coordination compounds had modest activities against the Gram negative bacteria: Escherichia coli when compared with ligand of pl-dtc.

Artificial Intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes.

The human malaria parasite, Plasmodium falciparum, accounts for more than 500,000 deaths worldwide per year. From 2000 to 2019, the malaria global death toll fell from 864,000 to 576,000 deaths; however, progress on reducing this toll has since slowed, with the COVID-19 pandemic contributing to an increase in the mortality rate since 2020. The emergence of widespread resistance in P. falciparum to first-line treatment drugs has highlighted the need for new antimalarial drugs, and smarter approaches, including better combination therapies and mass drug administration. Nevertheless, recent successes of the first malaria vaccine (RTS,S/AS01) and the approval of a second (R21/MM), have renewed the promise of widely applicable vaccines in the future. Since 2015, the Eastern Mediterranean Region has experienced an overall increase in malaria cases and deaths. In the Arabian Peninsula, while most of the Gulf Cooperation Council (GCC) countries have been declared free of indigenous malaria (Bahrain, Kuwait, Qatar, and the United Arab Emirates), malaria is still endemic in two GCC countries (Saudi Arabia and Oman) and its neighbors (Yemen). Furthermore, a number of factors threaten malaria control in this region, at the level of the parasite (antimalarial drug resistance), the mosquito (the emergence of highly invasive species), the environment (climate change and increasing average temperatures), and society (imported malaria). In this review, we assess the current world-wide status of malaria in terms of public health, prevention and treatment, before providing an Arabian regional perspective, with a critical evaluation of the malaria situation in the GCC countries.

This multi-center retrospective study evaluated the diagnostic performance of a deep learning (DL)-based application for detecting, classifying, and highlighting suspected aortic dissections (ADs) on chest and thoraco-abdominal CT angiography (CTA) scans. CTA scans from over 200 U.S. and European cities acquired on 52 scanner models from 6 manufacturers were retrospectively collected and processed by CINA-CHEST (AD) (Avicenna.AI, La Ciotat, France) device. The di-agnostic performance of the device was compared with the ground truth established by the majority agreement of three US board-certified radiologists. Furthermore, the DL-algorithm's time-to-notification was evaluated to demonstrate clinical effectiveness. The study included 1,303 CTAs (mean age 58.8 ± 16.4 years old, 46.7% male, 10.5% positive). The device demonstrated a sensitivity of 94.2% [95% CI: 88.8% – 97.5%] and a specificity of 97.3% [95% CI: 96.2% - 98.1%]. The application classified positive cases by AD types with an accuracy of 99.5% [95% CI: 98.9% – 99.8%] for type A and 97.5 [95% CI: 96.4% – 98.3%] for type B. The application did not miss any type A cases. The device flagged 32 cases incorrectly, primarily due to acquisition artefacts and aortic pathologies mimicking AD. The mean time to process and notify of potential AD cases was 27.9 ± 8.7 seconds. This deep learning-based application demonstrated strong performance in detecting and classifying aortic dissection cases, potentially enabling faster triage of these urgent cases in clinical settings.

Lower respiratory infections (LRI), upper respiratory infections (URI), and nutritional deficiency (ND) in under-5 children from low-middle-income countries has been at a high level for decades, despite efforts that have been realized in some countries. The study used data extracted from the global burden of diseases (GBD) to analyze the trends behavior between 1990 and 2019, and evaluate their association with maternal factors. Between 1990 and 2019, the incidence of LRI decreased between 1.2 percent and 1.3 percent (1.2-1.3%) in different female age groups, and by nearly 1 to 1.3% in those of the male gender. The incidence of URI did not decrease (0.0%) in any of their age groups. ND incidence declined around 0.7 to 4.9% in the under-5 children. LRI declined mostly in the female age groups (1.2 to 1.3%), while ND decreased more in the male gender (0.9 to 4.9%). Maternal risk factors were strongly associated to the incidence of the three conditions with over 90 percent. Maternal prevalence of HIV/AIDS and tuberculosis positively impacted the incidence of LRI, URI, and ND in Chadian under-5 children. Although the incidence of LRI and ND declined, URI incidence remained steady between 1990 and 2019 in Chadian under-5 children. To improve the health and provide a healthy growth of under-5 children, the maternal prevalence of HIV/AIDS and tuberculosis infection should be strongly addressed for a prompt accomplishment of the sustainable development goals.

Incremental control strategies provide undeniable advantages for controlling Uncrewed Aerial Vehicles (UAVs) due to their reduced model dependency and accurate tracking capacities. This is of particular relevance for hybrid UAVs, specially for tail-sitters, which perform complex manoeuvres when transitioning to and from aerodynamic flight. This paper summarizes the research undertaken in the application of the Incremental Nonlinear Dynamics Inversion (INDI) and Incremental Backstepping (IBKS) to a small tail-sitter UAV. After the application of these control strategies in a simulated scenario, the implementation in a Micro-Controller Unit was validated in a Hardware-in-the-Loop scenario. Following such validation, indoor experimental trials were undertaken in order to evaluate the capacity of these controllers to stabilize and control the real aircraft. The stabilization in the flight trials was successfully implemented and allow to conclude that both INDI and IBKS are control strategies suited to control a tail-sitter in vertical flight, providing accurate tracking capabilities under smooth actuation. Furthermore, it was found that the IBKS is significantly more computationally demanding than the INDI, although having a global proof of stability that is of interest in aircraft control.

Understanding speech in noise is particularly difficult for individuals occupationally exposed to noise due to a to a mix between noise-induced auditory lesions and energetic masking of speech signal. For years, the monitoring of conventional audiometric thresholds has been the usual way to check and preserve the auditory function. But the highlighting of supra-threshold deficits, notably speech in noise understanding difficulties, has pointed out the need for new monitoring tools. The present study aims to identify the most important variables that predict speech in noise under-standing in order to suggest a new way of regular monitoring. Physiological (distortion products of otoacoustic emissions, electrocochleography) and behavioral (amplitude and frequency modula-tion detection thresholds, conventional and extended high frequency audiometric thresholds) variables were collected in a population of individuals presenting a relative homogeneous occu-pational noise exposure. Those variables were used as predictors in a statistical model (random forest) to predict scores of three different speech in noise tests and a self-report of speech in noise ability. The extended high frequency threshold appears to be the best predictor and therefore an interesting candidate for a new way of monitoring noise exposed professionals.

In this paper, two double Jordan-type inequalities are introduced based on the papers [1]-[5]. These inequalities generalize the inequalities obtained in [1]-[5]. As a result, some new upper and lower bounds of the sinc function are obtained. This extension of Jordan’s inequality is enabled by considering the corresponding inequalities through the concept of stratified families of functions elaborated in [6]. Based on this approach, some optimal approximations of the sinc function are derived by determining corresponding minimax approximants, also described in the paper [6].

This paper presents an in-depth study of the stress wave behavior propagating in a Rayleigh–Love rod with a sudden cross-sectional area change. The analytical solutions of stress waves are derived for the reflection and transmission propagation behavior at the interface of the cross-sectional area change in the rod, considering inertia and Poisson’s effects. Examples solved by the finite element method are provided to verify the correctness of the analytical results. In addition to the forward analysis of Rayleigh–Love wave propagation in rods impacted by a striker rod, a nondestructive testing method is proposed to conduct the defect assessment in the rod type of the structure component with a sudden cross-sectional area change within a cover medium by using the measured signals at the measurable zone of the rod to be inspected.

The lexical analysis of seminal policy-to-diplomacy documents from the socio-environmental discourse of the last fifty year agendas allowed examining the evolution of five themes: resources/waste, pollution, social and economic development, justice, and health. Contextual affinities were strongest between resources, pollution, and health and are linked to societal trends and pressures. On those grounds, the central role of resource stewardship according to nature’s physical limits is highlighted, and dedicated concepts, analytical frameworks, and methodologies with different degrees of sustainability are analyzed. To reframe the identified social and economic problems, the work proposes criteria and choices that (1) allow to compare the dynamics of socioecological states across the planet, (2) help matching the pace of socioecological change by addressing path dependencies through participation and engagement of communities, and (3) enable stakeholders to make trade-offs and take decisions in specific social, economic, political, and cultural contexts. The prioritization of resource justice and responsibility becomes a societal project : from Wellfare State to commonfare communities.

Cerebellar ataxia, neuronopathy, and vestibular areflexia syndrome (CANVAS) is caused by biallelic pathogenic expansions, or compound heterozygosity with other pathogenic variants in the RFC1 gene. CANVAS is estimated to be underdiagnosed, both because of the lack of formal diagnostic criteria and molecular challenges that translate to lesser access and high cost of routine testing. Our aim was to address the need for making CANVAS genetic testing routine, by designing a streamlined two-step PCR consisting of a short-allele screening PCR and a confirmatory PCR with fragment capillary electrophoresis detection. Exome sequencing of RFC1 was additionally foreseen to resolve potential compound heterozygosity cases. Specificity of our approach was evaluated using ataxia patients with known non-CANVAS diagnoses, and optimized using Southern blot confirmed CANVAS patients. We evaluated our approach by testing patients consecutively referred for clinically suspected CANVAS using first the two-step PCR, followed by exome sequencing. Our approach was able to accurately identify negative and confirm positive cases in prospectively collected suspected CANVAS patients presenting with at least three typical clinical signs. The proposed testing approach provides an alternative method able to clearly distinguish between CANVAS negative and positive cases and can be easily incorporated into the genetic diagnostic laboratory workflow.

Abstract: The establishment of a circular economy in the mining sector, taking advantage of innovations in the exploration and development of hydrocarbon reserves, [ ], their [ ], transportation [ ] and subsequent processing [ ] are significant concerns. The issues surrounding the employment of technology targeted at enhancing environmental safety to increase the productivity of the reproduction process of the natural gas and oil resource base are equally important. The paper discusses the use of green seismic technology of survey to determine the oil and gas potential of the subsoil. A methodological toolkit is proposed for carrying out technical and economic calculations to determine indicators of the environmental and economic efficiency of using innovative resource-saving technology for geological survey in areas densely planted with forests. The purpose of the work is to establish the viability of employing resource-saving technology known as Green Seismic to search for promising hydrocarbon objects in forested areas and determine the expected environmental and economic benefits of geological exploration using the suggested enhanced methodology for their evaluation. The tasks set to achieve the goal were solved using methods of geological and economic assessment of the hydrocarbon raw material potential of territories and water areas, environmental assessment of the negative influence of anthropogenic environmental impact on the natural environment, economic and statistical methods of performing technical and economic calculations to determine performance indicators for the implementation of innovative projects in the field of geological exploration. The novelty of the results obtained lies in the proposed improved algorithm for conducting an environmental and economic assessment of geological exploration for hydrocarbon raw materials, a conceptual description of the Green Seismic technology, systematization of technical, economic, and environmental risks, justification of new regional directions for geological exploration using resource-saving seismic exploration technology.

Glial cells provide physical and chemical support and protection for neurons. Secreted neurotrophic factors, scaffolds and vesicles regulate in addition to normal homeostasis, repair following neural tissue injury or degeneration. We previously demonstrated that human CNS glia have revascularization capacity by inducing endothelial cell sprouting and microchanneling driven by glial cell secreted components. The clinical potential of using secreted factors and vesicles generated by glial cells in conditioned media was shown by their re-normalization of pathological blood vessels and 3D tissue wound healing and remodeling capacity. To identify secreted components of glial cells and how CNS and PNS glial cells differentially regulate neural tissue homeostasis, disease and injury response, we developed a novel culture method for various types of glial cells that allow for isolating and characterizing secreted glial components, free of animal factors and contaminants normally associated with serum-based culture conditions. Our culture method will enable to identify secreted components using ultrasensitive RNA, glycoconjugate and protein analysis technologies. The characterization of glial secreted factors involved microchanneling may help in development of new clinical therapies for glial and neural cells or axons to migrate and reform connections.

As a service business models have been ranked by management consultants the management innovation of 2020, and yet are scarcely theorized. Therein, value stipulations in customer contracts lead to the shift from product to service. However, there is no available research about the nature, formula and decisional process about these value stipulations. The motive for this research is to fill in this gap. The goal is to provide first insight about value stipulations in as a service business models: their formula and decisional methodology. The article is a multiple theory building case study on leading platform as a service providers, which aims to contruct the paradigm of the value decision methodology to invest in this technology by purchasing it from dedicated vendors. The methodology works to identify the management instruments involved in the decisional activities to invest in digital technology, where each management instrument is assumed to match an activity at seller and buyer; the sequence of the activities using the Critical Path Method gives the decisional process. Dependent variables are the elements of the as a service business contracts: the customer offering (product-service solution) and the value created, captured and delivered by the solution. Independent variables are given by empirical data analysis. Findings show a relationship between dependent variable value in the as a service business model contracts and independent variables governance objective, strategy, as a service business model type, activity management techniques (roadmap, program, project, operations, lean start-up), capital allocation techniques (equity, debt, options, venture capital typology). If innovation is exploitative, then the customer offering is known and value is determinable via roadmap – project management techniques (program, project, an operations) and capital allocation techniques for precictable environment, If innovation is radical, then the customer offering is not known and value is a target used to architect the solution via lean start-up innovation techniques funded by venture capital. The contribution is a new theoretical construct and deep insight into the practice of digital transformation considering all inherent issues.

We present here a case of complex uterine anomaly – Obstructed HemiVagina with Ipsilateral Renal Agenesis (OHVIRA), also known as Herlyn-Werner-Wunderlich syndrome in a 13-year-old girl with the history of recurrent urinary tract infections (rUTI). In emergency room, trans-abdominal sonography revealed ovarian cyst and renal agenesis, without any suspicion of vaginal obstruction. This led to delay in the diagnosis of this uncommon anomaly. Finally, MRI findings confirmed the presence of OHVIRA syndrome. As the congenital anomalies of kidney and urinary tract (CAKUT) are in almost one third of cases associated with genital malformations, urologist should carefully search for patients with rUTI. The patient underwent simultaneous laparoscopy and vaginoscopy, what was in our opinion the most appropriate therapeutic decision. In this article we are also going to discuss the role of laparoscopy in the management of OHVIRA syndrome as well as other surgical techniques described in the literature.

Life on Earth evolved to accommodate the biochemical and biophysical boundary conditions of the planet millions of years ago. The former includes nutrients, water, and ability to synthesize other needed chemicals. The latter include the 1 g gravity of the planet, radiation, and the geomagnetic field (GMF)of the planet. How complex life forms have accommodated the GMF is not known in detail considering that Homo sapiens evolved a neuro system and a cardiovascular system that develops electromagnetic fields as part of their functioning. In addition, many proteins and physiologic processes utilize Fe ions, an ion that exhibits magnetic properties. Thus, complex organisms such as current humans generate magnetic fields, contain significant quantities of the Fe ion, and also respond to exogenous-supplied static and electromagnetic fields. Whether humans can store information in self-generated magnetic fields remains to be determined. Given the current body of literature, it remains somewhat unclear how Homo sapiens use exogenous magnetic fields to regulate function, and what can happen if the boundary condition of the GMF of Earth is no longer exerting an effect. Proposed deep space flights to destinations such as Mars will provide some insights as space flight could not have been anticipated by evolution. The results of such space flight “experiments” will provide new insights in the role of magnetic fields on human functioning. The outcomes may also have implications for those on Earth as magnetic field influences may play a role in developmental conditions such as autism and senescence-associated conditions such as dementia when integration of the biological and biophysical aspects of humans of humans are required for effective functioning. This review will discuss the involvement of magnetic fields on various normal and disturbed processes in humans while on Earth and then further discuss potential outcomes when the GMF is no longer available to impact host systems. Thus, the GMF of the Earth has been present throughout evolution but details of its role in human functions still remain to be elucidated.

China is striving to leverage the power of science and technology to green its agriculture while increasing grain productivity. In this context, this study presents the green growth rate of agriculture from the DEA-based Green Total Factor Productivity (GTFP) indicator, together with the growth rate of grain yields, and applies it to the case of Jiangsu, a major grain-producing province with a well-developed economy. It is found that Jiangsu's agriculture has generally performed well in the implementation of the two major national strategies of green development and grain security, especially in the northern Jiangsu, which is a major grain-producing area. In contrast, the phased fluctuations of green growth in agriculture in Southern Jiangsu are more pronounced, with even negative green growth occurring during the green agriculture movement. Much of the volatility in agricultural green growth at the provincial, subregional, municipal level comes from the effects of the movement of the green technology frontier led by best practitioners. Accordingly, the possibility of improving the weak state of the catch-up effect on green growth is explored from the perspective of the Chinese government-led agricultural science and innovation system; it also traces the green agricultural initiatives in the main grain-marketing areas that have failed to deliver the expected green growth, and recommends a review of such policies and refinement of the GTFP Index tool for assessing sustainable green growth.

The burgeoning field of Urban Air Mobility (UAM) promises transformative solutions to urban transportation challenges, with the potential to revolutionize cargo logistics in metropolitan areas. This research investigates the role of tiltrotor technology as a pivotal enabler of seamless UAM integration for efficient cargo transportation within urban environments. The study delves into the existing challenges within UAM, such as infrastructure limitations and the need for adaptable aerial vehicles that can navigate confined spaces while maintaining payload capacity. Tiltrotor Unmanned Aerial Vehicles (UAVs) are examined as a solution to these challenges due to their unique capabilities, combining vertical takeoff and landing (VTOL) with efficient forward flight. This research evaluates the potential of tiltrotor UAVs for urban cargo transportation, focusing on their operational efficiency, safety, and economic viability. Furthermore, the study explores the potential impact of tiltrotor technology on urban cargo logistics, considering factors such as reduced congestion, shorter delivery times, and environmentally sustainable operations. Real-world case studies and practical implementation strategies are discussed, shedding light on the importance of integration of tiltrotor UAVs into existing cargo transportation networks.The findings of this research underscore the transformative potential of tiltrotor technology in enhancing UAM for cargo transportation within urban areas. The study contributes valuable insights to the ongoing discourse on UAM integration and lays the groundwork for future developments in autonomous aerial cargo delivery systems.

Online and offline shopping trip have different impacts on various aspects of urban life, such as e-commerce, transportation systems, and sustainability. Therefore, it is important to evaluate the factors that influence their choices. We use a hybrid machine learning model that combines a gray wolf optimization algorithm and a deep convolutional neural network to estimate shopping trip based on a survey of 1,000 active e-commerce users who made successful orders in both online and offline services in the last 20 days of 2021 in areas 2 and 5 of Tehran. The gray wolf optimization algorithm performs feature selection and hyperparameter tuning for the deep convolutional neural network, which is a powerful deep learning model for image recognition and classification. The results show that our model achieves an accuracy of 97.81% with an MSE of 0.325 by selecting seven out of ten features. The most important features are delivery cost, delivery time, product price, car ownership. In addition, comparing the performance of the proposed method with other methods showed that the proposed algorithm with an accuracy of 97.81%, the accuracies of the single deep learning model, MLP neural network, decision tree, and KNN models were 95.63%, 90.0%, 86.49%, and 80.16%, respectively.

This comprehensive treatise is written for the special occasion of the author’s 70th birthday. It presents his lifelong endeavors and reflections with original reasoning and re-interpretations of the most critical and misleading issues in thermodynamics; since now, we have the advantage to look at the historical developments more comprehensively and objectively than the pioneers. Starting from Carnot (grand-father of thermodynamics-to-be) to Kelvin and Clausius (fathers of thermodynamics), and other followers, the most relevant issues are critically examined and put in historical and contemporary perspective. From original reasoning of energy forcing and displacement to logical-proofs of the fundamental laws, to ubiquity of thermal motion and heat, and indestructibility of entropy, including new concept of “thermal roughness” and inevitability of dissipative irreversibility, to “dissecting Carnot true reversible-equivalency” and critical concept of “Carnot-Clausius heat-work equivalency (CCHWE)” regarding interchangeability of heat and work, and to demonstrating “no hope” for the “challengers” of the Second Law of thermodynamics, among others, are offered. It is hoped that the novel contributions presented will enhance comprehension and resolve some of the fundamental issues, as well as promote collaboration and future progress.

Following the 2001 end to negotiations on a legally binding protocol, Biological and Toxin Weapons Convention (BWC) states parties (SPs) developed entrenched positions about the necessity of a verification regime, hindering progress on treaty aims. This study aimed to facilitate dialogue on verification-related issues outside the context of those positions, using the term "assurance" to represent the degree of certainty that SPs are meeting their treaty obligations. From August 2020-July 2021, 36 interviews were conducted—16 SPs' delegations and 20 subject matter experts, representing 20 countries—and interview content was analyzed utilizing a mixed methods approach, including quantitative metrics on qualitative interview content. Interviewees' views on verification, compliance, and related concepts varied widely. Efforts by SPs to achieve common understanding on these topics could facilitate concrete progress in these important areas. While no single mechanism is sufficient to achieve verification or assess compliance, packages of mechanisms could increase assurance. There was general support for implementing assurance mechanisms, even in the absence of a comprehensive, legally binding protocol or verification regime, even among SPs for which that is the primary goal. Avenues to increase assurance among BWC stakeholders merit further discussion in the Intersessional Programme following the 9^th BWC Review Conference.

The spin magnetic moments and spin g factors (g_s = -2) of electron, muon and tau are explained based on the electric charges (EC) and lepton charges (LC) in terms of the three-dimensional quantized space model. The spin g factors of electron, muon and tau are g_s = -2 which is the sum of the EC g factor (g_EC = -1) and the LC g factor (g_LC = -1). The spin g factor (g_s = -2) of the electron is predicted by the Dirac’s equation. The orbit g factors of electron, muon and tau are g_L = g_EC = -1 from the EC g factor (g_EC = -1) without the contribution of the LC g factor (g_LC = -1). The spin g factors of the elementary fermions are calculated from the equation of g_s = g_EC + g_LC + g_CC where g_EC = EC/|EC|, g_LC = LC/|LC| and g_CC = CC/|CC|. For example, the spin g factors of the neutrinos and dark matters are g_s = -1. The spin g factors of the u and d quarks are g_s = 0 and g_s = -2, respectively. The g factor problem of neutrinos with the non-zero LC charges are solved by the LC Coulomb force of F_c(LC) ≈0. It is, for the first time, proposed that the binary motion (fluctuations) of the m_EC and m_LC masses for the electron, muon and tau leptons make the anomalous g factor. This binary motion could be originated from the virtual particle processes including the photons. Also, the weak force (beta) decay is closely related to the binary motion of the m_EC and m_LC for the electron, muon and tau leptons.

Space-time evolution of our universe is explained by using the 3-dimensional quantized space model (TQSM) based on the 4-dimensional (4-D) Euclidean space. The energy (E = cDtDV), charges and energy density (|q| = r = cDt) and absolute time (ct) are newly defined based on the 4-D Euclidean space. The photon flat space with the constant energy density of r = cDt_q is proposed as the dark energy (DE). The dark energy is separated into the n DE and photon DE which create the new photon spaces with the constant energy density of r = cDt_q. The v DE is from the n pair production by the CPT symmetry and the photon DE is from the photon space pair production by the T symmetry. The vacuum energy crisis and Hubble’s constant puzzle are explained by the photon space with the n DE and photon DE. The big bang and inflation of the primary black hole is connected to the accelerated space expansion and big collapse of the photon space through the universe evolution. The big bang from the nothing is the pair production of the matter universe with the positive energy and the partner anti-matter universe with the negative energy from the CPT symmetry. Our universe is the matter universe with the negative charges of electric charge (EC), lepton charge (LC) and color charge (CC). This first universe is made of dark matter -, lepton -, and quark - primary black holes with the huge negative charges which cause the Coulomb repulsive forces much bigger than the gravitational forces. The huge Coulomb forces induce the inflation of the primary black holes, that decay to the super-massive black holes and particles.

For analysis tasks, time counts are of interest — values recorded at some, usually equidistant, points in time. The calculation can be performed at various intervals: after a minute, an hour, a day, a week, a month, or a year, depending on how much detail the process should be analyzed. In time series analysis problems, we deal with discrete-time, when each observation of a parameter forms a time frame. The same can be said about the behavior of Covid-19 over time.In this paper, we solve the problem of predicting Covid-19 diseases in the world using neural networks. This approach is useful when it is necessary to overcome difficulties related to non-stationarity, incompleteness, unknown distribution of data, or when statistical methods are not completely satisfactory. The problem of forecasting is solved with the help of the analytical platform Deductor Studio, developed by specialists of the company Intersoft Lab of the Russian Federation. When solving this problem, appropriate methods were used to clean the data from noise and anomalies, which ensured the quality of building a predictive model and obtaining forecast values for tens of days ahead. The principle of time series forecasting was also demonstrated: import, seasonal detection, cleaning, smoothing, building a predictive model, and predicting Covid-19 diseases in the world using neural technologies for 30 days ahead.

The biology of sexual orientations has intrigued people for generations. Many models have been providing insights to that topic, but there are still unanswered questions. In humans, sexual orientation has a learned component. Humans have to learn cues by which they identify the sex of their mates, and cues of the emotional messages that those mates broadcast. Many of those cues depend on arbitrary societal conventions. The cues are learned automatically and subconsciously during childhood, based on non-sexual experiences. When sexual orientation emerges at puberty, the youngsters cannot tell how and when they have acquired it. A model that deals with those phenomena is presented. A basic tenet of the model is that a sexual orientation is determined by the innate wirings of the brain. The model describes how the brain learns cues for identifying the sex of the mate, and cues for identifying emotional messages that the mate broadcasts. The learning mechanism is conditioning. The unconditioned stimulus is human voice. The unconditioned responses are the triggers of the physical and emotional manifestations of sexual activity. The model suggests that innate connections from auditory detectors of men’s and women’s voice onto brain centers that trigger sexual activities, such as the hypothalamus, determine the sexual orientation that emerges at puberty. Innate connections from those auditory centers to emotional centers, such as the amygdala, determine the learned emotional cues. It is also proposed that during evolution, the roles of the chemosensory system in identifying mates were taken over by the auditory system.

The role of γδ T cells in vertebrate immunity is still an unsolved puzzle. Species such as humans and mice display a low percentage of these T lymphocytes (i.e., “γδ low species”) with a restricted diversity of γδ T cell receptors (TR). Conversely, artiodactyl species (i.e., “γδ high species”) ac-count for a high proportion of γδ T cells with large γ and δ chain repertoires. The genomic organisation of the TR γ (TRG) and δ (TRD) loci has been determined in sheep and cattle, noting that a wide number of germline genes that encode for γ and δ chains characterise their genomes. Taking advantage from the current improved version of the genome assembly, we have investigated the genomic structure and gene content of the dromedary TRD locus, which, as in the other mammalian species, is nested within the TR alpha (TRA) genes. The most remarkable finding was the identification of a very limited number of variable germline genes (TRDV) compared to sheep and cattle, which supports our previous expression analyses for which the somatic hypermutation mechanism is able to enlarge and diversify the primary repertoire of dromedary δ chains. Furthermore, the comparison between genomic and expressed sequences reveals that D genes, up to four incorporated in a transcript, greatly contribute to the increased diversity of the dromedary δ chain antigen binding-site.

The subject of this article is the dynamics of water in a soil pedostructure sample whose internal environment is subjected to a potential gradient created by the departure of water through surface evaporation. This work refers entirely to the results and conclusions of a fundamental theoretical study focused on the molecular thermodynamic equilibrium of the two aqueous phases of the soil pedostructure. The new concepts and descriptive variables of the hydro-thermodynamic equilibrium state of the soil medium, which have been established at the molecular level of the fluid phases of the pedostructure (water and air) in a previous article, are recalled here in the systemic paradigm of hydrostructural pedology. They allow access to the molecular description of water migration in the soil and go beyond the classical mono-scale description of soil water dynamics. We obtain a hydro-thermodynamic description of the soil's pedostructure at different hydro-functional scale levels including those relating to the water molecule and its atoms. The experimental results show a perfect agreement with the theory, validating at the same time the systemic approach which was the framework.

This article presents and discusses analytical data on the scientific publication record from 1910 to 2020 on two topics: "climate" and "climate change/global warming/climate emergency". The goal is to visualize how the publication record on these two topics has evolved over time, from different classification perspectives (year, country, source and organization). Three hypotheses are tested using data collected from Web of Science and various graphical representations of the data. It is found that research output related to the Earth’s contemporary changing climate overtook that of general climate research in 2011, and the publication ratio has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics, and conversely less significant differences in terms of organizations publishing these works. Differentiation factors that affect the level of research output and engagement on the climate challenge include: island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as “climate emergency”.

This paper uses the numerical results of surveys sent to Huelva’s (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households’ clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (CART) to determine which hierarchy of variables/factors/ independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva’s households to use water more efficiently.

Ultrafast laser 3D lithography based on non-linear light-matter interactions, widely known as multi-photon lithography (MPL), offers unrivaled precision rapid prototyping and flexible additive manufacturing options. 3D printing equipment based on MPL are already commercially available, yet there is still no comprehensive understanding of factors determining spatial resolution, accuracy, fabrication throughput, repeatability, and standardized metrology methods for the accurate characterization of the produced 3D objects and their functionalities. The photoexcitation mechanisms, spatial-control or photo-modified volumes, and the variety of processable materials are topics actively investigated. The complexity of the research field is underlined by limited understanding and fragmented knowledge of light-excitation and material response. Research to date has only provided case-specific findings on photoexcitation, chemical modification, and material characterization of the experimental data. In this review, we aim to provide a consistent and comprehensive summary of the existing literature on photopolymerization mechanisms under highly confined spatial and temporal conditions, where, besides the excitation and cross-linking, parameters such as diffusion, temperature accumulation, and the finite amount of monomer molecules start to become of critical importance. Key parameters such as, photoexcitation, polymerization kinetics, and the properties of the additively manufactured materials at the nanoscale in 3D are examined, whereas, the perspectives for future research and as well as emerging applications are outlined.

With the unceasing advancement in wide-bandgap (WBG) semiconductor technology, the minimal reverse-recovery charge Qrr and other more powerful natures of WBG transistors enable totem-pole bridgeless PFC to become a dominant solution for energy storage systems (ESS). This paper focuses on design and implementation of a control structure for a totem-pole boost PFC with newfangled enhancement-mode Gallium Nitride (eGaN) FETs, not only to simplify the control implementation, but also to achieve high power quality and efficiency. The converter is designed to convert a 90-264-VAC input to a 385-VDC output for a 2.6-kW output power. Lastly, to validate the methodology, an experimental prototype is characterized and fabricated. The uttermost efficiency at 230 VAC attains 99.14%. The lowest total harmonic distortion in the current (ITHD) at high line condition (230 V) reaches 1.52% while the power factor gains 0.9985.

Reciprocal Personal/Public Protection (RPPP) featured with source control is introduced, Mask Discriminating Mouth and Nose (MDMN) is employed to serve the purpose, which includes polymer based mouth cover with optional nose cover. The new knowledge that mouth is a primary, active and dominant source of the virus has been well established, which is the base of MDMN. Source classification and related source control tools are discussed, mouth cover is recommended as the tool prioritized to use. Liquid droplets is identified as a hard issue related to mask, liquid droplets, mask fitting, comfort and facial recognition constitute real challenges of mask in addition to efficiency, All of these have been addressed with MDMN. Comparisons between MDMN and masks/face covering are taken on four aspects: efficiency and efficacy, tolerance and comfort, cost and waste, and civil rights and public interest. Mouth cover is recommended to replace the face covering and act as both a personal tool and a public utensil, mouth cover with nose cover can provide better protection than N95 etc. RPPP with MDMN, could be an alternative for lockdown, a parallel strategy to vaccine, and a collectively living way during the pandemic era. MDMN, featured with high efficiency protection, high degree comfort, easy wearing, tight-fitting, easy facial recognition & communication, reusability, cost-effective, environment friendly and scale manufacturing more readily and widely etc., is a simple and sustainable solution, which is essential for ordinary people to keep wearing it properly for protection.

To predict how the COVID-19 pandemic progresses, we developed a systematic method for predicting disease outcomes. In the method, we evaluate how personal disease outcomes are mainly affected by viral concentration and exposure time and four defense mechanisms: human innate immunity/host response, acquired immune response, inflammation resolution and micro circulation, and the available space in the thorax cage. By considering how pandemic measures affect viral exposure and those mechanisms, we found many pandemic measures are misused or abused to deliver long-term adverse impacts. We noted that lifestyles have been changed as a result of movement restriction measures. By using the method, we found that altered lifestyles are predicted to raise infection rate, disability and death risks in the future. We show that a person can use personal, environmental, emotional factors to reduce infection rate and death risk. To prove the validity of this finding, we extensively examined medical research models, holistic and reductionist models, epidemiological models, disease risk factors, etc, and found that population methods are unfit for studying holistic health, statistical population does not exist in most clinical trials, mathematical models were misused for studying disease properties for a population, mathematical equations for modeling personal diseases are beyond human ability to solve, statistical models are misused, population-derived treatments are inherently dangerous to patients, vaccines have limited benefits due to unique lung structure and rapid RNA mutation, and immune system damage is caused by fast viral replication rate. We found that altering biological properties to improve the defense mechanisms could prevent a super majority of deaths and prevent the virus from reaching a point to damage the immune system. For vulnerable persons, such measure is a viable strategy for surviving from the pandemic. As a whole, holistic personalized medicine is more powerful than population-based reductionist treatment by one to several orders of magnitudes. We urge people do their parts to force the medical establishment to abandon population treatment models that are responsible for failure of medicine and dissemination of misleading and factually wrong information on the effectiveness of medical treatments.

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV- 2). The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as, deep learning, in (i) rapid disease detection from x-ray/computerized tomography (CT)/ high-resolution computed tomography (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) identification of the epicenter in each country/state and forecasting the disease from social networking data, (iv) prediction of drug-protein interactions for repurposing the drugs, and (v) socio-economic impact and prediction of future relapses, has attracted much attention. In the present manuscript, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real time polymerase chain reaction (qRT-PCR) and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, possibility of future relapses and socio-economic impact are also discussed. We inspect how the virus transmits depending on different factors, such as, population density and mobility among others. We depict how AI-based mobile app for contact tracing and surveys can prevent the transmission. A modified deep learning technique can assess affinity of the most probable drugs to treat COVID-19. Here a few effective antiviral drugs, such as, Geneticin, Avermectin B1, and Ancriviroc among others, have been reported with their appropriate validation from previous investigations.

A novel effective vibrational mode was discovered in the conventional transducer with an array of orthogonal (square) regular piezoelectric rods in 1-3 piezocomposite, containing the damping backing and front matching layers. The operational resonance in the structure was determined as the Surface Acoustic Wave (SAW) on the backing boundary excited by the adjacent piezo-rods, with its frequency typically near 3 times lower the fundamental half-lambda conventional piezocomposite resonance. Pulse-echo sensitivity and transmitting sound-pressure-level (SPL) in air showed that the signal strength is roughly comparable to the industrial similar air transducers at the frequency range 100…700 kHz, where at these frequencies the lateral and longitudinal piezoelement dimensions in the conventional transducer design are typically close to each other causing interference with unwanted coupling modes. As was determined theoretically and proved in experiments, the backing SAW resonance effect in the transducer performance is inherent just to the regular periodic 1-3 piezocomposite structure, and does occur neither with randomly located/oriented piezo-rods, nor in the homogeneous piezo-plate at least with the same lateral cross-section as the connected to it backing. The purpose of the article is to investigate a newly discovered operational vibrational mode of a SAW type in 1-3 regular piezocomposite, other than piezoelectric resonance. The investigated phenomena can improve the transceiver sensitivity, bandwidth, providing lower drive voltage, and smaller and lighter weight ultrasonic transducers. Based on the piezocomposites with thickness’ 1…1.5 mm (rod resonance near 2…3 MHz), pillar width 0.2…0.8 mm, kerf width 0.1…0.4 mm, the transceivers with an operating frequency from 140 kHz to 650 kHz were designed and fabricated with a conventional backing of a mixture of high-density tungsten powder and epoxy, and a matching layer of a mixture of low-density glass bubbles and epoxy. Experimental evaluation of their acoustical performance showed expected characteristics suitable for practical applications.

Objective: In this pilot study, we described the gross motor development of infants aged 4 to 24 months with congenital heart disease (CHD) and assessed through a systematic develop­mental screening programme, with individualised motor interventions. Methods: Thirty infants who had cardiac repair underwent gross motor evaluations using the AIMS at 4 months, and the Bayley-III at 12 and 24 months. Results: Based on AIMS, 80% of 4-month-old infants had a delay in gross motor development and required physical therapy. Gross motor abilities significantly improved by 24 months. Infants who benefited from regular physiotherapy tended to show better improvement in motor scores. Conclusion: Our study highlights the importance of early motor screening in infants with CHD and suggests a potential benefit of early physical therapy in those at-risk. Further research is needed to assess the effectiveness of systematic developmental screening and individualized inter­vention programmes at identifying at risk patients, and their impact on developmental outcomes.

The burdens of malnutrition, protein and micronutrient deficiency, and obesity cause enormous costs to society. Crop nutritional quality has been compromised by the emphasis on edible yield and through the loss of biodiversity due to the introduction of high-yielding uniform cultivars. Heirloom crop cultivars are traditional cultivars grown for a long time (> 50 years), and whose heritage has been preserved by regional, ethnic or family groups. Heirlooms are recognized for their unique appearance, names, uses and historical significance. They are gaining in popularity because of their unique flavors and cultural significance to local cuisine, and their role in sustainable food production for small-scale farmers. As a contrast to modern cultivars, heirlooms may offer a welcome alternative in certain markets. Recently, market channels have emerged for heirloom cultivars in the form of farmer-breeder-chef collaborations and seed savers organizations. There is therefore urgent need to know more about the traits available in heirloom cultivars, particularly for productivity, stress tolerance, proximate composition, sensory quality and flavor. This information is scattered and the intention of this review is to document some of the unique characteristics of heirloom cultivars that may be channeled into breeding programs for developing locally adapted high value cultivars.

Genetic testing allows for identification of germline DNA variations which are associated with a significant increase in risk of developing breast and ovarian cancer. Detection of a BRCA1 or BRCA2 pathogenic variant triggers several clinical management actions, which may include increased surveillance and prophylactic surgery for healthy carriers or treatment with PARP inhibitor therapy for carriers diagnosed with cancer. Thus, standardized validated criteria for annotation of BRCA1 and BRCA2 variants according to their pathogenicity are necessary to support clinical decision making and ensure improved outcomes. Upon detection, variants whose pathogenicity can be inferred by the genetic code are typically classified as pathogenic, likely pathogenic, likely benign, or benign. Variants whose impact on function cannot be directly inferred by the genetic code are labeled as Variants of Uncertain Clinical Significance (VUS) and are evaluated by multifactorial likelihood models that use personal and family history of cancer, segregation data, prediction tools, and co-occurrence with a pathogenic BRCA variant. Missense variants, coding alterations that replace a single amino acid residue with another, are a class of variants for which determination of clinical relevance is particularly challenging. Here, we discuss current issues in variant classification by following a typical life cycle of a BRCA1 missense variant through detection, annotation and information dissemination. Advances in massively parallel sequencing have led to a substantial increase in VUS findings. Although comprehensive assessment and classification of missense variants according to their pathogenicity remains the bottle neck, new developments in functional analysis, high throughput assays, data sharing, and statistical models are rapidly changing this scenario.

ABSTRACT Ethiopia is a developing country, where majority of the population lives in rural areas without access to electricity. 83% of the total population of the country use traditional biomass energy as a basic source of energy. In contrast, the country is endowed with sufficient renewable energy resources which can be used as a standalone electric energy supply system for electrifying remote areas of the country. These resources are mainly micro hydropower and wind which can be used individually or the best combination of one another. The application of hybrid renewable energy system has become an important alternative solution for rural electrification program. The Modeling and control of a hybrid PV-Wind-Hydro DG system is also addressed. Dynamic models for the major system components, namely, wind energy conversion system, PV energy conversion system, hydro, inverter, and overall fuzzy logic controller units are developed. Then, a simulation model for the proposed hybrid power system has been developed using MATLAB /Simulink environment. This is done by creating subsystem sets of the major dynamic component models and then assembling into a single aggregate model. The overall power management strategy for coordinating and/or controlling the different energy sources is also presented in the thesis work. Generally there are 800 households with total electric demand of 71.6KW.To satisfy this demand 52%, 35% and 13% is to be contributed from wind/hydro/solar respectively. To use the power economically fuzzy logic controller is used. The controller monitors the demand and the available sources and then switches to the appropriate power supply according to the written rules. Simulations have been carried out to verify the system dynamic performance using a practical load profile and weather data. The result shows that the overall power management strategy is effective and the load demand is balanced. To complete this work, a grid extension from the closest substation has been compared with hybrid system. Cost of the grid extension is estimated based on the data obtained from EEP office. This is done in order to compare the cost of the designed hybrid power system against the cost of grid extension. The result shows that breakeven grid extension distance to be 23.9km which indicates that grid extension is preferable.

One important motivation for the implementation of the Water Framework Directive is the creation of non-market environmental benefits such as improved ecological quality, or greater opportunities for open-access river recreation via microbial pollution remediation. Pollution sources impacting on ecological or recreational water quality can be uncorrelated but non-market benefits arising from riverine improvements are typically conflated within benefit valuation studies. Using stated preference choice experiments, we seek to disaggregate these sources of value for different river users, thereby allowing decision makers to understand the consequences of adopting alternative investment strategies. Our results suggest anglers derive greater value from improvements to the ecological quality of river water, in contrast to swimmers and rowers for whom greater value is gained from improvements to recreational quality. We also find three distinct groups of respondents: a majority preferring ecological over recreational improvements, a substantial minority holding opposing preference orderings and a small proportion expressing relatively low values for either form of river quality enhancement. As such, this research demonstrates that the non-market benefits which may accrue from different types of water quality improvements are nuanced in terms of their potential beneficiaries and, by inference, their overall value and policy implications.

Whereas waste management research has focused on mostly urban municipalities in South Africa, not much is known about the current performance of waste management services from the perspective of community residents in rural municipalities. This study reports on the status and effectiveness of waste management practices from the perspective of community residents in the Umkhanyakude and Zululand Districts in the rural areas of the KwaZulu-Natal province of South Africa. Making use of structured questionnaires, primary data was obtained by interviewing 333 respondents representing households in the study area. Results have revealed several shortfalls in the provision of municipal waste management services, except for solid waste removal from households (66%), and management of landfill sites (41%). The degree of dissatisfaction for waste management services rendered was very high (97.3%). Furthermore, the majority (61.4%) of respondents were not willing to participate in waste segregation due to lack of appropriate knowledge and infrastructure. The study also pinpointed some benefits associated with waste minimization, as well as barriers constraining effective waste recycling. Based on these findings, there is a dire need for transforming current waste management practices toward increased recycling rates by creating more environmental awareness and a supporting infrastructure.

This article explores the enduring influence of colonial legacies on the economic development of the Americas, tracing their historical roots and contemporary repercussions. By examining a comprehensive range of historical and modern research, the article analyzes how colonial institutions, policies, and labour systems have profoundly shaped the economic trajectories of countries across the region. Central to the discussion is the lasting impact of colonial-era practices, such as the mining mita in Peru, and how factor endowments have influenced inequality and development patterns. The article further investigates the broader implications of these findings for understanding the deep-seated origins of economic disparities and the formidable challenge of overcoming colonial legacies in the present day. Special attention is given to the role of inclusive institutions, regional cooperation, and the intersection of culture and identity in fostering more equitable economic and social progress. Through this analysis, the article provides valuable insights into the historical foundations of contemporary economic imbalances and offers policy recommendations for addressing these persistent legacies.

This review explores the transformative role of artificial intelligence (AI) in the entire winemaking process, from viticulture to bottling, with a particular focus on enhancing food safety and traceability. It discusses AI’s applications in optimizing grape cultivation, fermentation, bottling, and quality control, while emphasizing its critical role in managing microbiological risks such as mycotoxins. The review aims to show how AI technologies not only refine operational efficiencies but also raise safety standards and ensure traceability from vineyard to consumer. Challenges in AI implementation and future directions for integrating more advanced AI solutions into the winemaking industry will also be discussed, providing a comprehensive overview of AI's potential to revolutionize traditional practices.

We propose a new approach to extending the notion of commutator and Lie algebra to algebras with ternary multiplication laws. Our approach is based on ternary associativity of the first and second kind. We propose a ternary commutator, which is a linear combination of six (all permutations of three elements) triple products. The coefficients of this linear combination are the cube roots of unity. We find an identity for the ternary commutator that holds due to ternary associativity of the first or second kind. The form of the found identity is determined by the permutations of the general affine group GA(1,5)⊂S5. We consider the found identity as an analogue of the Jacobi identity in the ternary case. We introduce the concept of a ternary Lie algebra at the cubic root of unity and give examples of such an algebra constructed using ternary multiplications of rectangular and three-dimensional matrices. We point out the connection between the structure constants of a ternary Lie algebra with three generators and an irreducible representation of the rotation group.

A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view. Additionally, a set of performance metrics is introduced to evaluate virtual aperture effectiveness and beamwidth loss factors. The study employs the desirability function and explores optimization strategies for the partial sharing of antenna elements in multi-mode radar applications. A novel machine learning initialization approach is introduced for rapid convergence. Observations include the potential for peak-to-sidelobe ratio (PSLR) reduction in dense arrays and insights into GSA feasibility and performance compared to uniform arrays. The study validates the efficacy of the proposed framework through simulated and measured results. The study underscores the importance of effective sparse array processing in multi-target scenarios and highlights the advantages of the proposed design framework, offering clarity on sparse array efficiency and applicability in processing hardware providing clarity on its advantages over uniform and nonuniform arrays.

Deploying search and rescue (SAR) dogs in disaster situations is crucial for effective rescue missions. This study delves into the challenges and obstacles encountered during the use of SAR dogs, particularly focusing on the earthquake that hit Turkey in February 2023. By employing a case study approach, the research explores various factors that impact the efficiency and safety of SAR dog operations, such as environmental conditions, equipment needs, cultural perceptions, and logistical hurdles. Environmental conditions such as extreme weather, hazardous materials, and unstable structures present significant risks to both the dogs and their handlers. The adequacy of equipment, including protective gear and medical supplies, is critical for ensuring the safety and efficiency of rescue operations. Logistical challenges, including the transportation and care of dogs in disaster zones, further complicate their deployment. Cultural barriers also play a crucial role, as perceptions of dogs vary widely across different communities, potentially affecting the acceptance and integration of canine units in rescue efforts. The case study of the earthquake in Turkey highlights these issues, showcasing the successes and setbacks experienced by international rescue teams. The findings indicate that although SAR dogs are invaluable in locating survivors, they face significant dangers, including hazardous materials, extreme weather, and physical injuries. Additionally, cultural differences and logistical issues complicate their deployment. This paper highlights the necessity for improved training, protective measures, and international standards to ensure SAR dogs' well-being and effectiveness in disaster response efforts. The study's implications suggest that addressing these challenges can markedly enhance the preparedness and resilience of SAR teams, leading to more efficient and safer rescue operations in future disaster scenarios.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

Artificial Intelligence (AI) is revolutionizing decision-making procedures in healthcare information systems (HIS), increasing the efficacy, accuracy, and personalization of healthcare. Notwithstanding remarkable progresses, yet there remain gaps in the holistic comprehension and implication of AI-driven technologies across various HIS scenarios. These gaps, consisting limited integration of AI across a variety of HIS parts and inadequate emphasize on interpretability and privacy, motivate our study to conduct a structured evaluation of recent AI applications in this domain. In this study, we present a novel taxonomy for the AI implication in medical decision-making. We analyzed 30 articles and categorized them into six groups including: Clinical Decision Support Systems (CDSS), Predictive Analytics, Natural Language Processing (NLP), Computer-Aided Diagnostics (CAD), Robotic-Assisted Surgery, and Virtual Health Assistants (VHAs/chatbots). Our study aims to propose a holistic perspective of the fast evolving perspective of AI in HIS. The majority of the investigated studies were published from 2023 and 2022, with Springer as the leading publisher (33%). Python and MATLAB were the most well-known simulation languages, applied in 48% and 20% of the papers, respectively, reflecting the technical trends in the area. By emphasizing on pivotal criteria like interpretability, accuracy, and privacy, this research aims to elucidate the crucial issues and development driving AI-driven decision-making in HIS.

This article presents a combined route and path planning strategy to guide Skid-Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity, and ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrated the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

A testable hypothesis with quantitative predictions is put forward, proposing that strong acids produced on land are a major cause of increasing atmospheric pCO2. Our modelling analysis of reactions by dissolved inorganic carbon shows that increasing atmospheric CO2 could be caused thermodynamically by falling land surface pH values. This hypothesis challenges the imbalance assumed between the global uptake of CO2 by photosynthesis and emissions of CO2 from all sources, including the combustion of fossil fuels. Strong acids generated by oxygen from reduced nitrogen and sulphur emits CO2 almost stoichiometrically from dissolved bicarbonate in the pH range of most global soils from pH 6.5 to above 8. Each general decrease of aqueous pH value of 0.01 units from acidification of surface water potentially increases the pCO2 in the atmosphere by about 7 ppmv. Contrary to prevailing assumptions that CO2 emissions from combusting fossil fuels can remain in the atmosphere for more than a millennium, such emissions may be partly nullified by global greening from enhanced rates of photosynthesis as well as oceanic absorption. The surface pH value of the ocean has been shown to decrease as atmospheric pCO2 rises. Therefore, our qualitative estimates of increasing atmospheric CO2 driven by irreversible acidification on land are critical and need broad scale validation. To the extent that significant acidification of the land is occurring, through export of alkaline produce, the use of artificial nitrogen fertilisation and possible other causes, the prevailing methods of reducing CO2 emissions will fail. However, these acidifying processes on land have not been considered by previous biogeochemical reviews. Despite counter measures, including carbon capture and geological storage, the increasing Keeling curve for pCO2 may continue to rise because zero carbon policies do not address such a major cause. This hypothesis can be tested by in situ experiments in neutral soils and water, designed to compare CO2 emissions under the acidifying conditions described in this article with those when corrective counter measures are applied.

We report recent enhancements of the online atomic database at the Ohio State University, NORAD-Atomic-Data, that provides various parameters for radiative and collisional atomic processes dominant in astrophysical plasma. NORAD stands for Nahar Osu RADiative. The database belongs to the data sources, especially for the latest works, of the international collaborations of the Opacity Project and the Iron Project. The contents of the database are calculated values for energies, oscillator strengths, radiative decay rates, lifetimes, cross sections for photoionization, electron-ion recombination cross sections and recombination rate coefficients. We have recently expanded NORAD-Atomic-Data with several enhancements over those reported earlier. They are as follows. i) We continue to add energy levels, transition parameters, cross sections for atoms and ions with their publications. ii) Recently added radiative atomic data contains significant amount of transition data for photo-absorption spectral features corresponding to x-ray resonance fluorescence effect, prominent wavelength regions of bio-signature elements, such as phosphorus ions, and emission bumps of heavy elements, such as of lanthanides, that may be created in a kilonova event. We are including iii) collisional data for electron-impact-excitation, iv) experimental data for energies and oscillator strengths for line formation, v) experimental cross sections for photoionization that can be applied for benchmarking and other applications, and vi) introduction of a web-based interactive feature to calculate spectral line ratios at various plasma temperature and density diagnostics, starting with our recently published data for P II. We presented summary description of theoretical backgrounds for the computed data in the earlier paper. With introduction of experimental results, we present summary description of measurement of high resolution photoionization cross sections at Advanced Light Source of LBNL synchrotron set-up and briefly discuss other set-ups. These additions should make NORAD-Atomic-Data more versatile for various applications. For brevity, we provide information on the extensions and avoid repetition of data description of the original paper.

Synthetic fiber ropes are frequently used as mooring lines in floaters supporting Floating Offshore Wind Turbines (FOWTs) due to their various advantages. Damages in these lines can lead to the disruption of the FOWTs normal operation and thus their early detection is crucial. Currently, this damage detection problem has been investigated exclusively for FOWT chain mooring lines. This study focuses on the damage detection in FOWT synthetic mooring lines under varying environmental-operational conditions (EOCs) via two types of vibration-based Structural Health Monitoring methods: those based on Multiple Models and those based on a single Functional Model. The methods are based on multivariate AutoRegressive or on scalar Transmittance Function (TF) AutoRegressive with eXogenous input models. All methods are evaluated through a Monte Carlo study involving 390 simulations with a 10MW wind turbine mounted on the semi-submersible OO-Star wind floater and two damage scenarios (10%, 14% stiffness reduction) to a single mooring line. The results using acceleration signals from only two measuring positions on the mooring line, indicate the great potential for robust SHM in FOWTs synthetic mooring lines with the TF model-based methods successfully detecting the considered early stage damage scenarios, even for EOCs not encountered in the methods training.

Abstract: Extensive research shows nurses’ work environment to be particularly stressful. This study develops, explores, and psychometrically tests a new profession specific ques-tionnaire identifying generalized and specific resistance resources, that make it possible to measure resources to manage work-related stress. An exploratory study design was em-ployed. The questionnaire was developed inspired by the MEASURE approach and the salutogenic theory of health. Building on the results from a literature review of nursing re-search and salutogenesis, supplemented by twelve interviews with hospital nurses, an item pool was generated. A first version was pilot tested in a group of nurses who were studying to become specialist nurses. A second version of the questionnaire was psycho-metrically tested on nurses in close patient care (n = 475), analysed using Principal Com-ponent Analysis as the extracting technique to identify the underlying structure of the questionnaire. The Principal Component Analysis revealed a four-component model of 19 items. “Manageability as a resource for handling the workload” was the strongest compo-nent, accounting for 21 % of the explained variance. “Contacts with patients as resources for nurses’ job satisfaction” (17.8 %). “Professional attitudes are labelled as resources to nursing” (15 %). “Colleagues are important resources for remaining in the nursing profes-sion” (11 %). The structure of the questionnaire indicates its usefulness in clinical practice for measuring resistance resources.

We propose a new theory beyond the standard model of elementary-particle physics. Employing the concept of a quantized spacetime, our theory demonstrates that the zero-point energy of the vacuum alone is sufficient to create all the fields, including gravity, the static electromagnetic field, and the weak and strong interactions. No serious undetermined parameters are assumed. Furthermore, the relations between the forces at the quantum-mechanics level is made clear. Using these relations, we quantize Einstein’s gravitational equation: Beginning with the zero-point energy of the vacuum, and after quantizing Newtonian gravity equation, we combine the energies of a static electromagnetic field and gravity in a quantum spacetime. Applying these results to the Einstein gravity equation, we substitute the energy density derived from the zero-point energy in addition to redefining differentials in a quantized spacetime. This is how we derive the quantized Einstein gravitational equation without assuming the existence of macroscopic masses. For the weak interaction, by considering plane-wave electron and the zero-point energy, we obtain a wavefunction that represents a β collapse. In this process, from a different point of view than Weinberg-Salam theory, we derive the masses of the W and Z bosons and the neutrino, and we calculate the radius and lifetime of the neutron. For the strong interaction, we previously reported an analytical theory for calculating the mass of a proton by providing a specific linear attractive potential obtained from the zero-point energy, which agrees well with the measurements. In the present study, we further calculate the strong interaction between two nucleons, i.e., the mass of the pi-meson. The resulting calculated quantities agree with the measurements, which verifies our proposed theory.

Here we mathematically model black holes following dynamics similar to RC electrical model, focusing on their similarities at the singularity. We use this mathematically modelling to hypothesize the origin and growth of a black Hole. Or model consists of several steps defined by: (1) the formation of a black hole following general relativity equations; (2) growth of the black hole modelled as a resistance-capacitance-like electrical circuit. Based on the mathematical modeling of a black hole following dynamics similar to an RC circuit, for a circular motion with constant acceleration, in which the condition is fulfilled, Vt = ω r, we are going to calculate the amount of dark matter in the Milky Way galaxies and the Andromeda galaxy and subsequently the rotation curve of both galaxies to compare them with observed or measured values.

In this study, we considered the structural stability, electronic properties, and phonon dispersion of the cubic (c-ZrO₂), tetragonal (t-ZrO₂), and monoclinic (m-ZrO₂) phases of ZrO₂. We found that the monoclinic phase of zirconium dioxide is the most stable among the three phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic properties. The smallest negative modes were found for m-ZrO₂. Our analysis of the electronic properties showed that during the m–t phase transformation of ZrO₂, the Fermi level first shifts by 0.125 eV toward higher energies and then decreases by 0.08 eV in the t–c cross-section. The band gaps for c-ZrO₂, t-ZrO₂, and m-ZrO₂ are 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35, and 16.15 mol. %Y₂O₃ onto the m-ZrO₂ structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO₂ and an increase in its defectiveness. The doping-induced and concentration-dependent phase transition of zirconium dioxide under the influence of yttrium oxide was studied, after which the position of the Fermi level changes and the energy gap decreases. It has been established that, not only for pure systems but including those doped with Y₂O₃, the main contribution to the formation of the conduction band is made by the p-states of electrons. The t-ZrO₂ (101) and t-YSZ (101) surface models were selected as optimal surfaces for water adsorption based on a comparison of their surface energies. An analysis of the mechanism of water adsorption on the surface of t-ZrO₂ (101) and t-YSZ (101) showed that H₂O on unstabilized t-ZrO₂ (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of -0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom. The calculations showed that ab initio research methods are capable of describing the mechanism of phase transitions of materials under the influence of alloying. That is, by optimizing the parameters of DFT calculations, it is possible to observe the effects of doping on other physical and chemical properties of materials, which are still beyond the scope of quantum chemical modeling. The obtained results complement the database of research works carried out in the field of the application of biocompatible zirconium dioxide crystals and ceramics in green energy generation and can be used in designing humidity-to-electricity converters and creating solid oxide fuel cells based on ZrO₂.

Growing incidence of myopia worldwide justifies the search for efficient methods of myopia prevention. Numerous pharmacological, optical, and lifestyle measures have already been utilized, but there remains a need to explore more practical and predictable methods for myopia control. This paper presents a review of the latest literature on preventing the progression of myopia using Defocus Incorporated Multiple Segments Spectacle Lenses (DIMSsl), Repeated Low-level Red-Light Therapy (RLRL), and the combination of low-dose atropine (0.01%) with orthokeratology lenses.

The reason for excessive multidecade deflections is still unclear after 70 years of the cantilever method that has been applied in building large-span segmental concrete bridges. The failure of the Koror-Babeldaob bridge gives the author a clue that the reason might be the boundary condition. The asymmetric properties of the bearing and prestress tendon draw the author’s attention. To understand the process of stress redistribution, the virtual stiffness method which is derived from the principle of minimum potential energy was created, and the phenomenon the author suggested named Material Inelasticity and Prestress Loss Coupling Effect is discovered. The unexplainable excessive deflection and prestress loss are found in the new load model. The calculation of excessive deflection is discussed. The new model fits the experience well. The optimization design methods and construction key points are proposed.

Eco-innovation denotes developing green practices using environmentally friendly innovative approaches or technologies. Although, eco-innovation has been broadly applied in different in-dustries, such as low-carbon production and manufacturing, how to implement such innovation in education for sustainable development (ESD) has rarely been studied. Therefore, this research considered a reflective and cooperative learning approach to science, technology, engineering, arts, and math (STEAM) education. A case study examined Wanluan Township of Pingtung County in southern Taiwan. Four departments’ students and teachers at Meiho University were involved in situated learning. Students of hospitality management played farm owners who en-gaged in organic agriculture to produce food and beverages. These agricultural products were farm-to-table, cooked and served for customers in a natural dining setting through the students’ teamwork. Students of tourism, sports & leisure management, and food science & nutrition played tourists in a self-guided travel context, who engaged in acts such as visiting buildings to understand heritage while observing that the houses were still in use a dwelling. This encouraged reflection on the importance of cultural preservation. According to the results from the role-play farm owners and tourists, eco-innovation can represent a sustainable marketing strategy for im-proving the local-community economy and can be implemented in a practical situation in STEAM. The goal of ESD for 2030 — societal transformation — is to foster students’ responsible behavior and attitudes in a personally authentic manner, thereby fostering sustainability learning and understanding.

In addition to its use as a food additive, sesame is also very popular in conventional drugs because of its antifungal, anticancer, analgesic, antioxidant, and antiproliferative, vitamin B and E supplier, serum cholesterol and blood pressure-lowering, wound healing potential. In this study, the cytotoxicity, wound healing, and anticancer (antiproliferation) properties of the ex-tract obtained from in vitro cultures of Sesamum orientale L. cv. "Gökova" were investigated using in L929 fibroblast, MCF-7 breast, and A549 lung epithelial cell lines. In our study, the cisplatin was also used as a control group to compare the anticancer efficacy of our plant extract. The IC50 values obtained from cell treatments were 922.73 µg.ml-1 (plant extract) and 33.09 µg.ml-1 (cispla-tin) for A549 µg.ml-1, 1837.07 µg.ml-1 (plant extract) and 19.27 µg.ml-1 (cisplatin) for MCF-7, and 154.70 µg.ml-1 (plant extract) for L929, respectively. The subcytotoxic doses of the treated plant extract provided the healing of artificially created wounds on L929 fibroblast cell cultures within 48 hours. For the evaluation of the anticancer activity, it was also determined that transcriptomic analyzes of BCL-XL gene, which is negatively correlated with apoptotic pathway, and Cas3 and Cas9 genes, which are positively correlated with apoptotic pathway, showed a statistically sig-nificant increase in A549 and MCF-7 cell lines treated with plant extract or cisplatin. In the light of the results obtained from the present study, it was seen that sesame plant extract may have wound healing potential at decreasing doses and anticancer activity potential at increasing dos-es. The present study can be a useful resource for the development of a drug with wound healing and/or antiproliferative potential, with applications to be made in different cell lines in the future.

In 1937,German mathematician L.Collatz proposed a conjeture:for any positive integer,if it is even,divide it by 2;if it is odd,multiply it by 3 and 1 to get an even number;keep going on and on, the final result is 1.This paper gives a sequence classification of odd numbers,and gives 1-1 mapping of odd numbers and odd number sequences,and uses these results to give a proof of this conjecture.

In synthetic diamond plate, the intrapulse correlated dynamics of self-phase modulation and spontaneous Raman scattering by optical phonons were for the first time directly investigated for tightly focused (focusing numerical aperture NA = 0.25) positively-chirped visible-range ultrashort laser pulses with variable durations (0.3-9.5 ps) and energies, transmitted through the sample. The observed modulation of the transmitted light spectra and Stokes Raman scattering spectra for the different pulse durations were related to nonthermal excitation of nonlinear phonon polarization and its eventual picosecond-scale suppression due to thermal decay of optical phonons on the timescale of electron-phonon thermalization in the material.

In this paper a new double-nozzle technique for in-gas-jet laser resonance ionization spectroscopy is proposed. The functionality of this new technique we explored by detailed gas dynamic and Monte Carlo atom-trajectory simulations, which results are presented and discussed. The results of similar computer simulations for JetRIS setup (as a typical representative of the conventional nowadays in-gas-jet technique) are presented and discussed as well. The direct comparison of calculation results for proposed new technique with the conventional one shows that the double-nozzle technique has many advantages compared with that one used in the JetRIS setup at GSI for future high-resolution laser spectroscopic study of heaviest elements. To fully implement the proposed new technique to all existing (or under construction) setups for in-gas-jet laser resonance ionization spectroscopy, it will be enough just replace the used their supersonic nozzle by the miniature double-nozzle device described in the paper.

The influence of linear and nonlinear modes of ADC driver on the operational amplifier (Op-Amp), which has different values of maximum output voltage slew rate, on the effective number of bits of ADC is considered. It is shown that the effective number of bits of ADC when op-amps on bipolar transistors with input signal amplitudes exceeding 50-100 mV is determined by the nonlinear modes of its input differential stage.

We aimed to estimate the proportion of the population infected with SARS-CoV-2 in the first year of the pandemic. The study population consisted of outpatient adults with mild or no COVID-19 symptoms, and was divided into subpopulations with different levels of exposures. Of the subpopulation without known previous COVID-19 contacts 4143, of the subpopulation with known COVID-19 contacts 594 persons were investigated. IgG- and IgA-seroprevalence and RT-PCR positivity were determined in context with COVID-19 symptoms. We hope to have contributed to the understanding of the significance of the asymptomatic and mild infections in the long persistence of the pandemic.

Safe sample transport is of great importance for infectious diseases diagnostics. Various treatments and buffers are used to inactivate pathogens in diagnostic samples. At the same time, adequate sample preservation, particularly of nucleic acids, is essential to allow an accurate laboratory diagnosis. For viruses with single-stranded RNA genomes of positive polarity, such as foot-and-mouth disease virus (FMDV), however, naked full-length viral RNA can itself be infectious. In order to assess the risk of infection from inactivated FMDV samples, two animal experiments were performed. In the first trial, six cattle were injected with FMDV RNA (isolate A22/IRQ/24/64) into the tongue epithelium. All animals developed clinical disease within two days and FMDV was reisolated from serum and saliva samples. In the second trial, another group of six cattle was exposed to FMDV RNA by instilling it on the tongue and spraying it into the nose. The animals were observed for 10 days after exposure. All animals remained clinically unremarkable and virus isolation as well as FMDV genome detection in serum and saliva were negative. No transfection reagent was used for any of the animal inoculations. In conclusion, cattle can be infected by injection with naked FMDV RNA, but not by non-invasive exposure to the RNA. Inactivated FMDV samples that contain full-length viral RNA carry only a negligible risk of infecting animals.

The object of this work is to determine the correlation on the Nusselt number on the individual rows of a four-row tubular finned heat exchanger with continuous fins with a staggered tube arrangement using CFD modelling. Correlations for calculating Darcy-Weisbach friction factors on individual tube rows were also determined. Relationships for the Nusselt number and friction factor derived for the entire exchanger based on CFD modelling were compared with those available in the literature determined using experimental data. The maximum relative differences between the Nusselt number for a four-row exchanger determined experimentally and by CFD modelling are in the range from 22% for a Reynolds number based on a tube's outside diameter of 1,000 to 30% for a Reynolds number of 13,000. The maximum relative differences between the friction factor for a four-row exchanger determined experimentally and by CFD modelling are in the range of 50% for a Reynolds number based on a tube outer diameter of 1,000 to 10% for a Reynolds number of 13,000. The CFD modeling performed shows that in the range of Reynolds numbers based on hydraulic diameters from 150 to 1,400, the Nusselt number for the first row in a four-row finned heat exchanger is about 22% to 15% higher than the average Nusselt number for the entire exchanger. In the range of Reynolds number changes based on hydraulic diameter from 2,800 to 6,000, the Nusselt numbers on the first and second rows of tubes are close to each other. Correlations on Nusselt numbers and friction factors derived for individual tube rows can be used in the design of plate-fin and tube heat exchangers used in equipment such as air-source heat pumps, automotive radiators, air-conditioning systems and in air hot-liquid coolers. In particular, the correlations can be used to select the optimum number of tube rows in the exchanger.

High dietary phosphate intake and poor adherence to phosphate-binding-therapy elevate the risk of hyperphosphatemia in maintenance hemodialysis (HD; MHD) patients. Therefore, chronic kidney disease-related mineral and bone disorder (CKD-MBD) indicators increase; consequently, risks of CKD-MBDs and inflammation are elevated. This double-blind, randomized control trial intervention study was designed to investigate the possibility of reducing blood CKD-MBD indicators and modulating inflammatory indicators by consuming low-phosphate (LP) meals accompanied by a minimum dose of a calcium-based phosphate binder (CaCO3). MHD patients were recruited and randomly assigned to an LP meal group (LP group) or a control group. After initial data collection, blood collection, and dietary counseling, subjects were asked to consume a washout diet for 1 week. During the washout diet period, subjects consumed their usual diet but took 1 tablet of calcium carbonate (1CaCO3) as a phosphate binder with each meal. After the washout diet period, subjects in the LP group and control group respectively consumed LP meals and regular meals twice a day for 1 week. Meat in the LP meals was boiled before the regular cooking process, but meat in control meals was not. All meals were supplied by a central kitchen so that the contents of phosphate and other nutrients could be identified. In total, 40 MHD patients completed the study program. After 1 week of the dietary intervention, the blood Ca x P product and dietary phosphate had significantly decreased in the LP group compared to the control group (p<0.05). The LP group had significantly lower variations in dietary phosphate intake, blood calcium, Ca x P product, and tumor necrosis factor (TNF)-α than the control group by comparing differences between after the dietary intervention and the baseline (△after intervention - baseline, p<0.05). The increase in dietary phosphate intake (△3rd - 2nd dietary phosphate intake) augmented the increase in the TNF-α level by 6.24-fold (odds ratio [95% confidence interval]: 6.24 [1.12~34.92], p<0.05). These results highlighted the conclusion that LP meals accompanied by a minimum dose of CaCO3 downregulated pro-inflammation by reducing CKD-MBD indicators which was triggered by decreasing dietary phosphate intake.

The World Health Organization identifies alcohol as a cause in several neoplasias of the oro-pharynx cavity, esophagus, gastrointestinal tract, larynx, liver, or female breast. This study re-views ethanol's nonoxidative and oxidative metabolism and one-carbon metabolism that en-compasses both redox and transfer reactions that influence crucial cell proliferation machinery. Ethanol favors the uncontrolled production and action of free radicals that interfere with the maintenance of essential cellular functions. We focus on the generation of protein, DNA, and lipid adducts that interfere with the cellular processes related to growth and differentiation. Ethanol's effects on stem cells responsible for building and repairing tissues are reviewed. Cancer stem cells suffer disturbances related to the expression of cell surface markers, enzymes, and transcription factors after ethanol exposure with consequent dysregulation of mechanisms related to cancer metastasis or resistance to treatments. Our analysis aims to underlie and discuss potential targets that show more sensitivity to ethanol's action and identify specific metabolic routes and metabolic realms that may be corrected to recover metabolic homeostasis after pharmacological interven-tion. Specifically, research should pay attention to reestablish metabolic fluxes by fine-tuning the functioning of specific pathways related to one-carbon metabolism and antioxidant processes.

The verticals of 5G, such as the automotive, smart grid and smart cities sectors, will bring lots of new sensors and IoT devices requiring Internet connectivity. Most of these machine-type terminals will be sparsely distributed, covering a very large geographical area and, from time to time, will have to update their software, firmware and/or other relevant data. Given this situation, one viable solution to implement the “Over-the-Air” update of these IoT terminals can be with the aid of GEO satellite systems. However, due to the ultra-dense radio frequency reuse that contemporary High-Throughput Satellite (HTS) systems implement in the access link to serve the IoT terminals, the use of a time-packed Free Space Optical (FSO) link represents a practical solution to avoid the bottleneck that the satellite gateway experiences in the feeder link. The performance of both Detect-and-Forward and Decode-and-Forward relaying strategies are studied, assuming that the single-carrier M-PAM symbols that are transmitted on the optical feeder link are mapped into M-QAM symbols that modulate the multiple subcarriers of the OFDM-based radio access link. In addition, the benefits of encapsulating the NB-IoT frames into DVB-S2(X) satellite frames is also analyzed in detail. The effects of the impairments introduced in both optical feeder and radio access links are characterized in detail, and the end-to-end error correction capabilities of the Modulation and Coding Schemes (MCS) defined in the contemporary releases of the NB-IoT and DVB-S2(X) standards are studied for different working regimes.

Early reports demonstrated the presence of cells with stem-like properties in bone marrow, with these cells having both hematopoietic and mesenchymal lineages. Over the years, various investigations have purified and characterized mesenchymal stromal/stem cells (MSCs) from different human tissues as cells with multi-lineage differentiation potential under the appropriate conditions. Due to their appealing characteristics and potential, MSCs are leveraged in many applications including medicine, oncology, bioprinting and as recent as treatment of COVID-19. To date, reports indicate mesenchymal stromal/stem cells have varied differentiation capabilities into different cell types and demonstrate immunomodulating and anti-inflammatory properties. Reports indicate that different MSCs microenvironments or niche and the resulting heterogeneity may influence their behavior and differentiation capacity. The potential clinical applications of mesenchymal stromal/stem cells have led to an avalanche of research reports on their properties and hundreds of clinical trials being undertaken. The future looks bright and promising for mesenchymal stem cell research with many clinical trials under way to prove their utility in many applications and in the clinic. This report provides an update on the potential broader use of mesenchymal stromal/stem cells, review early observations of the presence of these cells in the bone marrow and their magnificent differentiation capabilities and immunomodulation.

Newly characterising 245 Italian and Albanian HCV-2 NS5B sequences collected between 2001 and 2016 was used to reconstruct the origin and dispersion pathways of HCV-2c. The tree of a subset of these sequences aligned with 247 publicly available sequences was reconstructed in spatio-temporal scale using the Bayesian approach, and the effective replication number (Re) was estimated using the birth-death model. Our findings show that HCV-2c was the most prevalent subtype in Italy and Albania, and that GT2 originated in Guinea Bissau in the XVI century and spread to Europe in the XX century. The HCV-2c subtype had two internal nodes respectively dating back to the 1930s and 1950s having as most probable locations Ghana and Italy, respectively. Phylodynamic analysis revealed an exponential increase in the effective number of infections and Re in both Italy between the 1950s and 1980s, and Albania between the 1990s and the early 2000s. It seems very likely that HCV-2c reached Italy from Africa at the time of the second Italian colonisation (1936-1941), but did not reach Albania until the period of dramatic migration to Italy in the 1990s.

According to the current European and Italian scenario related to urban re-generation, cultural and landscape heritage, valorisation is being also enhanced by the activation of innovative processes. These involve the development of methodologies and tools that are able to address decision-making processes among low entropy economy, complex values and creative practices. In this perspective, the research aims to investigate the possibilities of developing a Cultural Heritage Low Entropy Enhancement (CHLEE) approach by considering how the complex values of cultural heritage can vary not only through a physical transformation of spaces but also through a program of uses and activities able to produce new values, where the human experience is essential. This type of model modifies the objectives that characterise the valorisation of cultural heritage and landscape, recognising that the fruition is no longer “consumerist” but “experiential”. A crucial role is represented by the heterogeneity of creative practices that contribute to the identificationidentifying and implementation ofimplementing innovative management and governance models. The present paper explores the components of creative regenerative processes, based upon the ex-post evaluation of some Italian experiments, across the PROMETHEE-GAIA multi-criteria method, to understand how creative experiences are building innovation ecosystem thanks to low entropy economy and improve the ex-ante evaluation for new strategies and policies.

Several problems of radiative transfer are yet unsolved because of the difficulties of the calculations involved in them, especially if the intervening shapes are geometrically complex. The main goal of our investigation in this domain is to convert the formulas that were previously derived, into a graphical interface based on the projected solid-angle principle. Such procedure is now feasible by virtue of several widely diffused programs for Algorithms Aided Design (AAD). Accuracy and reliability of the process is controlled by means of the analytical software DianaX developed at an earlier stage by the authors. With this new approach the often cumbersome procedure of lighting and thermal exchange calculations can be simplified and made available for the neophyte, with the undeniable advantage of reduced computer time.

Tiger nut (Cyperus esculentus) is an edible perennial grass-like plant that has long been recognized for its health benefits as it is rich in fiber, protein, vitamins, minerals and natural sugars. It can be eaten raw, roasted or made into a refreshing milk which is very nutritive and healthy for consumption. There were several efforts to mass-produce the locally prepared tiger nut milk in our locality, but the fact that it has a shorter shelf-life, brings about a hindrance. The main objective of the present study is to unveil the cause for the easily spoilage of tiger nut milk and device ways to promote its production using different treatments. Tiger nut milk products were prepared using different methods; water soaked tiger nut milk (WSTM), toasted tiger nut milk (TTM), methanol soaked tiger nut milk (MSTM), and the pasteurised tiger nut milk (PTM). Each of these milk proucts prepared was divided into two portions; the first portion is treated with an antibiotic preservative, Nisin and the second portion was left untreated. The two portions were further divided into two; one stored at refrigerating temperature and the other at room temperature, making four different treatments per mixture and a total of 16 samples. These samples were subjected to proximate analysis; protein, fat, moisture, ash and carbohydrate. The chemical composition of the samples was significantly (P < 0.05) affected by processing treatment. All the samples had high moisture content, and a considerable amount of fat. The preservative treated samples that received pasteurized treatment were found to stay more than a week with fair quality. Findings from the study shows that the chemical characteristics of the various milk products were significantly affected by the different processing treatments.

This paper gives an overview of the large-scale tectonic styles encountered in orogens worldwide. Thin-skinned and thick-skinned tectonics represent two end member styles recognized in mountain ranges. Both styles are encountered in former passive margins of continental plates. Thick-skinned style including the entire crust and possibly the lithospheric mantle are associated with intracontinental contraction. Delamination of subducting continental crust and horizontal protrusion of upper plate crust into the opening gap occurs in the terminal stage of continent-continent collision. Continental crust thinned prior to contraction is likely to develop relatively thin thrust sheets of crystalline basement. A true thin-skinned type requires a detachment layer of sufficient thickness. Thickness of the décollement layer as well as the mechanical contrast between décollement layer and detached cover control the style of folding and thrusting within the detached cover units. In subduction-related orogens, thin- and thick-skinned deformation may occur several hundreds of kilometers from the plate contact zone. Basin inversion resulting from horizontal contraction may lead to the formation of basement uplifts by the combined reactivation of pre-existing normal faults and initiation of new reverse faults. In most orogens thick-skinned and thin-skinned structures both occur and evolve with a pattern where nappe stacking propagates outward and downward

The optimization of guide vane closing schemes (OGVCS) of pumped storage hydro unit (PSHU) is the research field of cooperative control and optimal operation of pumped storage, wind power and solar power generation. This paper presents a OGVCS model of PSHU considering the rise rate of the unit rotational speed and the specific node pressure of each hydraulic unit, as well as various complicated hydraulic and mechanical constraints. OGVCS model is formulated as a multi-objective optimization problem to optimize conflictive objectives, i.e., unit rotational speed and water hammer pressure criteria. In order to realize the efficient solution of the OGVCS model, an enhanced multi-objective bacterial-foraging chemotaxis gravitational search algorithm (EMOBCGSA) is proposed to solve this problem, which adopts population reconstruction, adaptive selection chemotaxis operator of local searching strategy and Elite archive set to efficiently solve the multi-objective problem. Especially, novel constraints-handling strategy with eliminating and local search based on violation ranking is used to balance various hydraulic and mechanical constraints. Finally, simulation cases of complex extreme operating conditions (i.e., load rejection and pump outage) of ‘single tube-double units’ type PSHU system are conducted to verify the feasibility and effectiveness of the proposed EMOBCGSA in solving OGVCS problem. The simulation results indicate that the proposed EMOBCGSA can provide lower rise rate of the unit rotational speed and smaller water hammer pressure than other method established recently while considering various complex constraints in OGVCS problem.

The increasing demand for operational efficiency in small and medium-sized manufacturing enterprises (SMEs) has sparked interest in Lean Six Sigma (LSS) methodologies. LSS integrates Lean’s waste elimination focus with Six Sigma’s variability reduction, offering a comprehensive framework for process improvement. Despite its potential, SMEs face unique challenges in implementing LSS, such as financial limitations and resistance to change. This systematic review evaluates the application of LSS in SMEs, analyzing its impact on operational, financial, and quality performance across different industries and geographical regions. The study identifies key success factors, barriers, and research gaps while proposing regression models to predict financial gains associated with LSS adoption. The review followed PRISMA guidelines, sourcing literature from SCOPUS, Web of Science, and Google Scholar published between 2014 and 2024. The inclusion criteria targeted studies involving LSS implementation in manufacturing SMEs. Data extraction included study characteristics, methodologies, and outcomes. A risk of bias assessment was conducted using the Newcastle-Ottawa Scale. The synthesis involved descriptive statistics, effect measures, and sensitivity analyses. Out of 150 initially identified studies, 109 met the inclusion criteria. The findings demonstrate that LSS implementation significantly improves operational performance, with 77.98% of studies showing reductions in cycle time and defect rates. Financial outcomes, including cost savings and ROI, showed moderate to large effects, with 63.58% of the reviewed studies reporting cost reductions. Quality improvements were noted across studies, particularly in First Pass Yield, with 67% of studies demonstrating enhanced quality metrics. The geographic distribution indicated strong research activity in India (23.85%), the United States (6.42%), and Europe (5.50%). Both developed (46.79%) and developing (45.87%) economies contributed extensively. Key barriers included resource constraints (reported in 45% of studies) and resistance to change (noted in 31%). LSS offers substantial benefits for SMEs, driving process efficiency, cost reduction, and quality improvements. However, challenges such as limited resources and organizational resistance must be addressed for successful adoption. This review provides insights into best practices, highlights research gaps, and suggests areas for future investigation, emphasizing the need for customized LSS strategies tailored to the unique contexts of SMEs.

Integrated photovoltaic-fuel cell (IPVFC) systems have the potential to contribute to sustainable energy production for grid and off-grid applications. While there are studies focusing on fundamental science and designs for IPVFC systems, there are scarcely studies that have focused on the manufacturability of IPVFC systems, which is certainly the pathway for commercialisation of the systems. This study explores manufacturing strategies that can be considered for exploiting a family of eleven IPVFC systems. A survey and systems thinking were used to investigate the potential modularisation and supply chain management to achieve optimal lean and agile manufacturing strategy. Results show that the Photovoltaic-Thermal-Separate Converter/Inverter-Battery System received 25% of the responses. The optimal manufacturing strategy depends on the overall business strategy of the firm. Although 17% preference for System 1 is significant compared to four members of the family of IPVFC systems (Systems 2, 6, 8 and 9) that received only 2% of the responses, it indicates that there is a likelihood that the demand for System 1 will be among the top 42% of the total demand. Overall, this study provides new insights on how the family of IPVFC systems can contribute to realising greater access to clean energy, by extension contributing to the net-zero efforts using solar energy and solar hydrogen.

A mass mortality event of Asian seabass Lates calcarifer juveniles occurred in Zhuhai, the main Asian seabass cultured area in mainland China. The fish samples were pooled for pathogen identification and both high viral loads of ISKNV and NNV were detected by real-time microfluidic quantitative PCR. Immunohistochemistry and immunofluorescence showed that strong ISKNV signals were examined in spleen and liver, while strong NNV signals were detected in brain and eye. The multi-tissue homogenates were inoculated into MFF-1 cell and SSN-1 cell, respectively. After several viral passages, both ISKNV and NNV were purely isolated from each other, and designated as ASB-ISKNV-23 and ASB-NNV-23, respectively. The whole genome sequences of ASB-ISKNV-23 and ASB-NNV-23 were determined and annotated. The result showed that ASB-ISKNV-23 and ASB-NNV-23 are composed of 112,236 bp and 4,538 bp, respectively. Phylogeny analysis showed that ASB-ISKNV-23 belongs to ISKNV-II sub-genotype and ASB-NNV-23 belongs to RGNNV genotype. Collectedly, coinfection of ISKNV-II and RGNNV were firstly documented in mass mortality of Asian seabass in mainland China. Importantly, both ISKNV-II and RGNNV were purely isolated using two different permissive cell lines. Our study provides useful information for better understanding the complex pathogenesis regarding the coinfection with ISKNV and NNV in farmed fish.

In this paper, we investigate the so-called electronic dressed states, a unified quasiparticle resulting from the interaction between electrons in a two-dimensional material with an off-resonance optical dressing field. If the frequency of this field is much larger than all characteristic energies in the system, such as the Fermi energy or bandgap(s), the electronic band structure is affected by radiation so that some important properties of the electron dispersions could be modified in a way desirable for practical applications. For example, a circularly polarized light can be used to vary the bandgap of Dirac materials: it opens a gap in graphene and other metallic and semimetallic lattices, or modifies the magnitude of an existing gap. This will either enhance or reduce a gap, depending on its initial value as well as properties of a host material. Here, we consider gaped dice and Lieb lattices as samples, and put forward a full theoretical model to reveal how these electronic states are deformed by an elliptically-polarized irradiation with a focus on generation and modification of a bandgap.

One of the most prevalent and deadly types of cancer is breast cancer. The value and effectiveness of the current pharmacological therapy are, however, constrained. Using computational methods and publicly available data, the current study set out to identify the genes and molecular pathways linked to breast cancer. It also looked into potential treatments for the disease that would target these molecular processes. In this study, we mined genes that were strongly associated with breast cancer using text mining and GeneCodis. Using STRING and Cytoscape, protein-protein interaction (PPI) study was carried out. Candidate medications were then derived based on the drug-gene interaction study of the final genes. 2,658 genes linked to breast cancer were found by our investigation using text mining searches. Out of which 166 genes have been taken which are relevant to breast cancer. Ten genes representing ten pathways—which a total of ten proteins could target—were found by gene enrichment analysis. We have taken Holy Basil as our lead as it contains various bioactive compounds such as flavonoids, terpenoids, and phenolics, which have shown antioxidant, anti-inflammatory, and anticancer properties. For this analysis we choose the molecular docking technique to check the effects of different chemical constituents of Holy Tulsi on breast cancer targeted protein and compare their results. We’ve performed the molecular docking in between chemical constituents of Holy Basil and the targeted proteins and determined the binding affinity with the help of PyRx and BIOVIA Discovery studio software. Anti-mitotic activity of Pisum sativum using tulsi extract to check the cytotoxicity effect was done. To determine the toxicity level of the extract on rat liver was performed in the end. In conclusion, investigating candidate medications that target the genes/pathways relevant to breast cancer in order to uncover possible treatments may be accomplished through drug discovery employing in silico text mining and pathway analysis technologies along with the wet lab experimentation with plants and preclinicals.

: Cybersecurity has become a critical area in the digital field in recent years. The expansion of networks has revolutionised the way network structures are organised and managed. However, with increased connectivity and the growing complexity of modern networks, the threat of cyber-attacks has become more intense. As technology continues to advance, it brings both opportunities and challenges. One of the major challenges is the need to secure networks and sensitive data from various malicious activities. Traditional networks have evolved to include Software Defined Network (SDN), which offers a more flexible and programmable framework. Researchers should focus on detecting attacks in SDN because SDN networks are becoming more popular and attractive targets for clients due to their programmability and dynamic nature. The centralised controller, known as the backbone of an SDN, becomes a single point of failure and a potential target for attackers if not properly secured. Researchers need to emphasise the detection of attacks in SDN in order to mitigate these risks. By understanding the potential vulnerabilities and attack methods specific to SDN, researchers can develop effective detection approaches and propose countermeasures. This methodology helps protect the network from potential threats and minimises the impact of successful attacks. Therefore, this survey paper provides a review of Intrusion Detection Systems (IDSs) in Software-Defined Networks (SDN) to provide a thorough understanding of SDN security issues.

In this study we introduce the new classes $\mathcal{M}_{\alpha}(\sin)$ and $\mathcal{M}_{\alpha}(\cos)$ of $\alpha$-convex functions associated with sine and cosine functions. Also, we obtain the initial coefficient bounds for the first five coefficients of the functions that belong to these classes. Further, we determine the upper bound of Zalcman functional for the class $\mathcal{M}_{\alpha}(\cos)$ for the case $n=3$, showing that the Zalcman conjecture holds for this value. Moreover, the problem of the Fekete-Szeg\H{o} functional estimate for these classes is studied.

This feature study attempts on setting a granules involving mesoscopic matter-aggregation context as a problem of passing locally by the matter-aggregating system from classical stochastic (mesoscopic limit) to a quantum description (nanoscale quantum-size effect limit). A d-dimensional entropy-production aggregation of the granules-involving matter is considered in terms of a (sub)diffusive realization. It turns out that when taking a full d-dimensional pathway of the aggregation toward the nanoscale, one is capable of disclosing a Heisenberg type (diffusional) relation, setting up an upper uncertainty bound for the (sub)diffusive very slow granules-including environment that matches the quantum limit of h/2pm (m– average mass of a granule; h – the Planck’s constant) for the diffusion coefficient of the aggregation, likely first proposed by Fürth in 1933, and qualitatively foreseen by Schrödinger some years before, both in the context of a diffusing particle cluster. The classical-quantum passage uncovered here, also termed insightfully the quantum-size effect (as borrowed from the quantum dots’ parlance), works properly for the three-dimensional (d=3) case, making use of a substantial physical fact that the (nano)granules interact readily via their surfaces with the also granular surroundings in which they are immersed. This natural observation is embodied in the basic averaging construction of the diffusion coefficient of the aggregation of interest. Certain, possibly biomedical, applications of the model can also be viewed by prospective inspection of tiny inhomogeneities in nanofibrillar and/or lamellar matter for which certain numerical realizations are plausible to prepare based on thorough nanoscale experiments.

In this paper, based on the symmetrical reliability theory, a research method for the safety factor of overall overturning stability of continuous beam bridge under carbon fiber reinforced polymers (CFRP) during cantilever and horizontal rotation construction is proposed. Under the premise that the given target reliability index is known, the method solves the overall overturning stability safety factor of continuous beam bridge under carbon fiber reinforced polymers during cantilever and horizontal rotation construction by using the symmetrical reliability analysis theory and considering the randomness of structural parameters. This method is used to calculate the safety factor and the design reinforcement aera of CRFP of overturning stability and the design reinforcement aera of CRFP of a continuous beam bridge, and the parameters are analyzed. The calculation results show that the randomness of parameters will have a great impact on the overall safety factor and the CRFP aera of overturning stability of cantilever and horizontal rotation construction of continuous beam bridge, and ignoring the influence of randomness of parameters will lead to overestimation of the overall safety factor and underestimation of the CRFP aera of overturning stability of cantilever and horizontal rotation construction of continuous beam bridge.

The paper presents the main experimental capabilities of the automatic system for the study of the interaction between porous media and atmosphere. This system is one of the possible variants of patent 2-241-477. The paper shows the result of a drying and wetting study of a tailings sample. The sample is 32 cm in height and 29 cm in diameter. The saturation and drying process was carried out at 26 degrees Celsius at the sample surface, an air velocity of 2 m/s and a relative humidity of 60%. The recharge applied to the column surface was 0.3 cm3/cm2/minute. The results show the effectiveness of the system in controlling the spatial-temporal variation of different physical properties of the porous medium in the vertical and surface profile. The controlled variables include volumetric water content, suction, relative humidity, sample weight variation due to recharge or drying, shrinkage, temperature, etc. The experiment shows how the tailings saturate very quickly but dry very slowly. Tailings consolidation occurs in the drying and wetting processes, being higher in the first one.