Maritime ports represent an important ecosystem for pollutant emissions and, taking into account the ongoing energy transition, need to adopt new solutions to mitigate current emission levels. These emissions are partially avoidable if ships and vessels docked at the port use electric energy to feed their internal power needs instead of using their internal combustion engines. In Europe, there is an ongoing discussion on including such emissions in the European Emissions Trading System which will represent added costs for maritime operators. Onshore Power Supply systems can contribute to the ongoing energy transition by allowing the use of electric power to feed docked ships. As a first step to contribute to the development of Onshore Power Supply solutions, it is necessary to evaluate the added power needs that these systems would represent for the port. This paper presents a methodology that allows port operators to verify, straightforwardly and transparently, their power needs for Onshore Power Supply applications. The methodology is based on the historical data of docked ships at the port or quay level and provides an energy analysis of each type of vessel to determine the power to be installed at the port so that it is possible to supply energy to different types of ships and vessels simultaneously. Additionally, the implemented methodology provides economic and technical decision support factors by comparing the fuel costs with electric power costs, assessing the potential for this transition to Onshore Power Supply. The methodology is validated using a real case study for the port of Lisbon and obtained results demonstrate the potential for the installation of Onshore Power Supply in medium to large-dimension maritime ports.

In this paper, we critically examine the burgeoning role of advanced computational methodologies in deciphering the complex tapestry of farm animal behaviors and emotions. Leveraging digital imaging and artificial intelligence, we unearth nuanced behavioral patterns and micro-expressions, offering predictive insights into animal emotional states. Sound vocalization analysis, often overlooked, emerges as a pivotal tool, decoding intricate communicative nuances and emotional undertones. Cognitive tests, including mirror and bias assessments, challenge long-standing perceptions, revealing surprising depths of animal self-awareness and cognitive sophistication. However, the paper also underscores the imperative of integrating these tools with a profound understanding of animal psyche, ensuring technology serves as an enhancer, not a replacement, of traditional observational methods. This research not only highlights the transformative potential of cognitive computing in animal welfare but also calls for a judicious application, ensuring technology augments, not undermines, the intrinsic value of human-animal interactions and understanding.

In order to meet the diversified rehabilitation needs of people, it is necessary to design a product for active rehabilitation of patients. Existing rehabilitation chairs use intelligent massage, which can cause problems such as large massage area, inability to local massage, large chair size, and inability to meet the continuous use of the damaged parts. In this paper, modular design method and multi-layer evaluation method are used to solve the problems related to rehabilitation chairs. The authors use the questionnaire survey method and the functional technology matrix method to determine the functional requirements of the rehabilitation chair, and then use the multilevel evaluation methods, including the AHP method, entropy weight method main and grey correlation analysis, to optimize the functional solutions of the rehabilitation chair, and finally obtain a chair for the rehabilitation of patients with upper and lower limb disorders. Problems such as generalisation of rehabilitation scope and non-durable use of components were solved, and the purpose of active exercise was achieved. This study verifies that the use of multilevel decision evaluation method can effectively improve the efficiency of programme decision-making, and provides theoretical and practical basis for the design of similar products.

Herpes B virus (BV) is a zoonotic virus which can be transmitted from macaques to humans, which is often associated with high mortality rates. Because macaques often exhibit asymptomatic infections, individuals who come into contact with these animals face unexpected risks of BV infections. Serological test is widely performed to investigate BV infections. However, the assay’s sensitivity and specificity appeared to be inadequate, and it does not necessarily indicate ongoing viral shedding. Here, we developed LAMP and qPCR assays aiming to detect BVs with high sensitivity and specificity in various macaque species and validated them using oral swab samples collected from 97 wild cynomolgus macaques living in Thailand. Our LAMP and qPCR assays detected more than 50 and 10 copies of the target sequences per reaction, respectively. The LAMP assay could detect BV within 25 min, indicating its advantages for the rapid detection of BV. Collectively, our findings indicated that both assays developed in this study exhibit advantages and usefulness for BV surveillance and diagnosis of BV infections in macaques. Furthermore, for the first time, we determined the partial genome sequences of BVs detected in cynomolgus macaques in Thailand. Phylogenetic analysis revealed the species-specific evolution of BV within macaques.

Abstract: Sarcopenia poses a significant challenge to public health and can severely impact the quality of life of aging populations. Despite extensive efforts to study muscle degeneration using traditional animal models, there is still a lack of effective diagnostic tools, precise biomarkers, and treatments for sarcopenia. Zebrafish models have emerged as powerful tools in biomedical research, providing unique insights into age-related muscle disorders like sarcopenia. The advantages of using zebrafish models include their rapid growth outside of the embryo, optical transparency during early developmental stages, high reproductive potential, ease of husbandry, compact size, and genetic tractability. By deepening our understanding of the molecular processes underlying sarcopenia, we may develop novel diagnostic tools and effective treatments that can improve the lives of aging individuals affected by this condition. This review aims to explore the unique advantages of zebrafish as a model for sarcopenia research, highlight recent breakthroughs, outline potential avenues for future investigations, and emphasize the distinctive contributions that zebrafish models offer. Our research endeavors to contribute significantly to addressing the urgent need for practical solutions to the impact of sarcopenia on aging populations, ultimately striving to enhance the quality of life for individuals affected by this condition.

The clinical relationship between diabetes and inflammation is well-established. Various branches of science independently have confirmed that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with Type 2 diabetes mellitus (T2DM). Under diabetic condition, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress and tissue damage are believed to have a role in the development of diabetes. Although the exact mechanism underlying the oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in onset and progression of vascular disease, kidney disease, hepatic injury, pancreas damage and, therefore holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications therapy fails to achieve the normal range for glycated hemoglobin target, signifying treatment resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical in vivo and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision of the future diabetes clinical trials.

Lung cancer is a prevalent and aggressive neoplasm worldwide, contributing to significant mortality rates. Dehydroepiandrosterone (DHEA) constitutes the bulk of the steroid hormone in human plasma, has a robust antiproliferative effect, and induces cell death in various tumor cells. However, its role in lung cancer cells remains unexplored. This study aimed to investigate the influence of DHEA on the proliferation, viability, autophagy, and migration of several lung cancer cell lines, including A549, HCC827, and NCI-H2347. Cell proliferation was assessed through crystal violet staining; cell number and viability were evaluated using trypan blue staining; viability was confirmed by MTT reduction, a method that is also an indicator of metabolic activity; migration was assessed via a wound healing assay. Autophagy was evaluated using a specific kit, while cell death was determined by annexin-V-FITC/propidium iodide staining and caspase-3/7 activity assay. The results indicate that DHEA significantly reduced proliferation, cell number, metabolic activity, and migration in all examined lung tumor cells. These effects correlate with an increased autophagy induced by DHEA. No signs of apoptosis or necrosis were observed across the range of DHEA concentrations used. Although these findings are preliminary, they suggest that DHEA could hold promise as an alternative treatment option for various subtypes of lung cancer.

Background: An analysis of the pages of the WHO website on the influenza pandemic revealed changes in the use of the term "pandemic" that occurred in 2009 and 2011. Materials and methods: Since the cause of the change in the description of a pandemic on the WHO website in 2009 and 2011 is not clear, analyses of the literature related to the epidemics and pandemics, WHO documents, WHO website, and articles published in journals and the Internet have been done.Results: Until early May 2009, the description of the pandemic focused on "enormous numbers of cases and deaths." On May 6, 2009, a new description of the pandemic was published, focusing on the prevalence of the disease, but in 2011 it reverted to the initial one without any comments. From the perspective of the WHO document issued in 2009, the declaration of a swine flu pandemic in June 2009 seemed justified. However, considering the previous pandemic history, common sense, and the consequences of declaring a pandemic for a disease not accompanied by a high number of cases and high mortality, it was a premature move.Conclusion: Since the primary factor hindering the development of a pandemic is the effectiveness of treating infectious diseases, but not a definition of a pandemic, to minimize the likelihood of a new pandemic, it is necessary to improve the quality of special medical education and to study and adapt to modern conditions all effective drugs and methods used in the past.

Background: The high prevalence of learning disabilities among children confirm that learning disabilities are surprisingly common. In absence of routine screening, many children still go undetected with a huge individual and family burden, while at the same time existing interventions are conflicting. The purpose of the study is to report on the design, implementation and evaluation of an innovative pilot intervention aiming to improve the quality of life of the family of students with specific learning disabilities. Method: For the purposes of this study, we used an experimental research design, using two groups (intervention and control). The intervention included four meetings with parents of children from the intervention group. To assess the quality of life of the students' family and the parenting style, the following measuring tools were used. They conducted at times and locations convenient to each participant. The instruments used to measure outcomes were two standard weighted questionnaires, the parenting style questionnaire and the family quality of life questionnaire. Findings: The results showed that the intervention program had significantly positive effects on both parenting style and children’s quality of life. Specifically, a decrease in parental authoritarianism and an increase in parental support were observed. Also, an increase in child-parent interaction, emotional and general well-being was found. Conclusion: The intervention program did improve the quality of life of the children by increasing all the variables related to the measurement of their quality of life.

Protein synthesis has been a very rich target for developing classes of drugs to control prokaryotic and eukaryotic pathogens. Despite the development of new drug formulations, treating human cutaneous and visceral Leishmaniasis still needs significant improvement due to considerable side effects and low adherence to the usual treatment regimen. In this work, we show that the di-substituted urea-derived compound I-17 is effective in inhibiting the promastigote forms and intracellular amastigotes of the Leishmania (L.) amazonensis and L. infantum species, in addition to exhibiting low macrophage cytotoxicity. We also show a potential immunomodulatory effect of I-17 in infected macrophages, which exhibited increased expression of inducible Nitric Oxide Synthase (NOS2) and Nitric Oxide (NO) production. Our data suggest that I-17 and new derivatives of this compound may be helpful in developing new drugs for treating leishmaniasis.

Pancreatic ductal adenocarcinoma (PDAC) is a fatal disease due to early metastatic spread, late diagnosis and the lack of efficient therapies. A major driver of cancer progression and hurdle to successful treatment is the desmoplastic reaction of the tumor stroma, the formation of which is orchestrated by transforming growth factor (TGF)-β. Recent data from pancreatic cancer mouse models have shown that the TGF-β pathway is controlled by transcriptionally active p73 (TAp73) through secretion of biglycan (Bgn) via intermittent expression of the TGF-β signaling intermediates, Smad3 and Smad4. Genetic knockout of TP73, and, as a consequence, deficient induction of Smad3/Dpc4 and secretion of Bgn led to activation of TGF-β signaling through a (Smad-independent) ERK pathway, favoring epithelial-mesenchymal transition (EMT) and cell motility. Except for BGN, these functions of TAp73 have recently been shown to also operate in human PDAC cells and are reminiscent of what we previously observed for the small GTPase, RAC1b. This prompted us to hypothesize that TAp73 and RAC1b are part of the same tumor-suppressive pathway in human PDAC cells. The two objectives of this study, therefore, were to reveal i) if the regulatory interactions between TAp73 and Bgn previously discovered in murine PDAC-derived cells also operate in their human counterparts, and ii) if RAC1b collaborates with TAp73 in these tumor-suppressive activities in human PDAC cells. Using a variety of experimental approaches, including mutual rescue experiments, we were able to show that the previously proposed tumor-suppressive TAp73-Smad4-Bgn signaling also operates in human cells and that RAC1b is as an upstream activator of this pathway. Our findings highlight the complex role of TGF-β in pancreatic tumorigenesis and might have implications for therapeutic approaches targeting this growth factor for inhibition.

Interferons were the original prototype cytokine system discovered in 20th-century research. As the name implies, they were originally thought to be synthesised and secreted between cells. Thanks to technological advances, the processes involved in protein secretion can be explained comparatively more clearly at both the genetic and biochemical levels. The discovery of interferon (IFN) occurred when genetic research was still in its infancy. Franklin and Wilkins discovered the structure and function of deoxyribonucleic acid (DNA) at the same time as Crick and Watson; however, Isaacs and Lindemann, two scientists, described the first IFN in 1957. Mutations can be caused by inherent genetic protein synthesis and during infection as well as within IFN regulation pathways affecting cell proliferation. This remains central to host cell IFN synthesis and effects through IFN protein receptor subunits defined by 6 protein domains. Type II IFN is key to immune cell function secreted by a variety of immune cells, mainly natural killer (NK) as well as T cells. Single–stranded and/or double–stranded RNA/DNA viruses, as well as bacterial infections (e.g., Escherichia coli) and fungal infections (e.g., Aspergillus), also affect IFN regulation. Pathogenic proteins utilise intra/extracellular proteins that sense foreign antigens like Toll–like Receptors (TLRs), affected by mutations within the human cellular IFN transduction pathways. Since the discovery of the third IFN type in 2003, when immune cell phenotypes were further characterised, questions remain about the immunological mechanisms contributing to the regulation of the innate and adaptive host immune system. Alterations in the synthesis of type I/II/III host IFNs can differentially and beneficially alter homeostatic cellular pathways in pathological disease, with type I IFN being synthesised in cancer as well as by homeostatic cells. Therefore, considered here are the overall IFN molecular, cell regulatory mechanisms in the context of immune cell research developments.

Membrane potential generation and maintenance are fundamental parts of membrane theory. However, since its inception, theories and assumptions have remained simple, whereas the amount of knowledge available has only grown. Unfortunately, this simplification and reductionism lead to its loss of validity on both microscopic and macroscopic scales. This article shows that assumptions made outside the context of factual reality lead to contradictions that cannot be compared with science. Membrane theory must be thoroughly revised, taking into account all forgotten and unanswered assumptions and questions to conform to facts and science to maintain credibility.

The Dst index is the geomagnetic storm index used to measure the energy level of geomagnetic storms, and the prediction of this index is of great significance for the geomagnetic storm study and the solar activity. In contrast to traditional numerical modelling techniques, machine learning, which has emerged in decades ago based on rapidly developing computer hardware and software and artificial intelligence methods, has been unprecedentedly developed in geophysics, especially solar-terrestrial space physics. This study chooses two machine learning models, the LSTM (Long-Short Time Memory, LSTM) and EMD-LSTM model (Empirical Mode Decomposition, EMD), to model and predict the Dst index. By building the Dst index data series from 2018-2023, two models were built to fit and predict the data. Firstly, we evaluated the influences of the learning rate and the amount of training data on the prediction accuracy of the LSTM model, and finally, 10-3 was thought as the optimal learning rate; secondly, the two models were used to predict the Dst index in the solar active and quiet periods, respectively, and the RMSE (Root Mean Square Error) of the LSTM model in the active period is 7.34 nT, the CC (correlation coefficient) is 0.96, those of the quiet period are 2.64nT and 0.97; the RMSE and r of EMD-LSTM model are 8.87nT and 0.93 in active time and 3.29nT and 0.95 in the quiet time. Finally, the prediction accuracy of the LSTM model in short time period is slightly better than the EMD-LSTM model. However, there will be a problem of prediction lag, which the EMD-LSTM model can then solve, and can better predict the geomagnetic storm.

One of the most important problems of geotechnical engineering is the design of pile foundations. Piles are generally designed for vertical and horizontal static loads. However, it is important to design piles against dynamic loads in regions with high seismicity. This study verified a centrifuge experiment obtained from the literature with a finite element program. With the kinematic interaction analyses made for this purpose, the effect of parameters such as layered soil, groundwater, pile stiffness, and earthquake acceleration were investigated numerically. According to the results obtained, it was understood that the earthquake magnitude is the most important parameter in kinematic interaction analyses. In addition, in layered soil conditions, the fact that 75% of the pile length is in the weak soil creates the most unfavorable situation. It has been observed that pile stiffness and groundwater level also have certain effects on the kinematic interaction.

DFT-D3 calculations based on structural X-ray diffraction data obtained for 3-oxo-camphorsulfonyl imine (1), camphorsulfonyl chloride (2) and seven camphor sulfonimines (O2SNC10H13NR, L1-L7) from which L2 (R=4-OHC6H4), L4 (R=4-ClC6H4) and L6 (R=3,5-(CH3)2C6H3) are new, provide information into the intra and inter molecular interactions with concomitant elucidation of the supramolecular arrangement of the compounds. The DFT D3 calculations performed in small clusters of 2 or 3 molecular units reproduce the interactions observed by X-ray analyses showing that as a general trend the structural arrangement of the molecules is driven by electronic rather than by packing parameters. In all compounds the self-assembly of 3D structures involves the sulfonyl imine group ( NSO2) either to establish hydrogen bonds, through the oxygen atoms or non-classic oxygen-aliphatic hydrogen or non-bonding interactions (NBI) which also involve the sulfonyl oxygens. Interestingly, the camphor sulfonimine compounds (L2, L3) having protic groups (R=C6H4X: X=OH, L2 or X=NH2, L3) at the aromatic imine substituents (=NR) present an extra π-π stacking which is absent in the other compounds aromatic derivatives. The X-ray analysis shows that all the reported camphor sulfonimine compounds display the E configuration with respect to the imine substituent (R). The study of the redox behavior of the compounds by cyclic voltammetry allows an insight into the solution properties of the compounds and the rationalization of the molecular interactions that stand in the solid and solution states. Camphor sulfonimine compounds (L) display appropriate binding atoms to coordinate transition metals. The herein results show that monodentate coordination through the nitrogen atom of the sulfonimine 5-membered ring to the {Ag(NO3)} metal center is favored. When this imine nitrogen atom is not itself involved in the Organic Framework DFT-D3 calculations shows that the complexation does not affect the non-covalent interactions that are reproduced in the MOF structure.

Background: As the world tends to recover from the crisis created by the COVID-19 pandemic, vaccines have served as one of the most valuable tools of combat and large-scale immunization has helped to tide over the catastrophe. However, several reports of post -vaccination neurological complications around the globe have surfaced up in recent literature. This study was conducted with an aim to describe the spectrum of neurological ailments requiring hospitalization following COVID-19 vaccination.Methods: An ambispective observational study was carried out from March 2021 to February 2022 at a tertiary care institute with 25 patients who satisfied the inclusion criteria of a new onset neurological illness requiring hospitalization within 4 days to 42 days of vaccination. The patients were duly followed upto months after discharge.Results: The median age of the sample was 36 years and the median latency of onset of neurological events was 14 days. Guillain-Barré syndrome was documented in 11 patients; majority were acute motor axonal neuropathy (45.45%) followed by acute inflammatory demyelinating polyradiculoneuropathy (36.36%) and acute motor sensory axonal neuropathy (18.18%). Central nervous system demyelination was reported in 9 patients; two patients had acute disseminated encephalomyelitis, 2 patients were diagnosed with myelin oligodendrocyte glycoprotein antibody-associated disease, one patient with aquaporin-4 positive neuromyelitis optica spectrum disorder , and the rest were labelled as seronegative central nervous system demyelination. Vascular events were noted in 5 patients comprising of 2 cases each of cerebral venous sinus thrombosis and intracerebral hemorrhage and a case of Moyamoya angiopathy. All patients were conservatively managed and had a complete to partial recovery suggestive of a favorable outcome after 3 months. Conclusion: The pathomechanisms of post -vaccination neurological complications is yet to be elucidatedand any causal association attributable to vaccination warrants further research. Compared to the enormity of the vaccinated population, the adverse effects are miniscule to hinder and discourage vaccination.

Enhanced oil recovery (EOR) refers to the various techniques used to increase the amount of crude oil that can be extracted from an oil field. These techniques are used after the primary and secondary recovery methods have been depleted. There are three main types of EOR: thermal, gas injection, and chemical. EOR techniques can be expensive and complex, but they can help to recover additional oil that would otherwise be left in the reservoir. EOR can also extend the life of an oil field and increase the overall production from a given field. The parameters affecting oil recovery are a major concern in EOR systems, and these parameters need more consideration with the factors affecting them. In this study, the influence of permeability variations on fluid flow in a sandstone reservoir was explored, as well as an up-to-date description of three states of EOR with thorough explanations of the methods utilized and the mechanisms driving their oil recovery application. The difficulties encountered in the use of the different standard EOR Mechanisms were noted, and solutions to these difficulties were proposed. Furthermore, the contemporary trend of adding nanotechnology and its synergistic effects on the stability and efficiency of traditional chemicals for EOR were examined and analysed. Finally, laboratory findings and field initiatives were discussed. The review went into detail about the transport of nanoparticles across reservoirs, as well as the evaluation of EOR, mobility ratio, and fluid displacement efficiency. This review provides thorough information on the uses of improved oil recovery mechanisms for sustainable energy production.

Abstract: The Internet of Things (IoT) has witnessed rapid and widespread adoption across various domains, including transportation, healthcare, education, agriculture, urban planning, smart homes, and more. Despite its transformative potential, this pervasive deployment of IoT devices has introduced new challenges, particularly concerning security and privacy threats such as unauthorized data access and device breaches. The excessive usage of these technological devices, coupled with the absence of robust security and privacy systems for user data, calls for a comprehensive approach to address these issues. In this study, we propose a novel framework designed to analyze, audit, test, and detect potential vulnerabilities within IoT environments and applications. The central components of the proposed framework include a machine learning algorithm for data classification and attack detection, along with the integration of Blockchain technology to enhance security measures. Specifically, the framework performs an in-depth analysis of user data to identify potential security or privacy vulnerabilities. Additionally, it conducts rigorous testing of smart services and automated data-collecting devices. To evaluate the effectiveness of our classification algorithm, we conducted a comprehensive implementation on a real-world IoT dataset. The results showcased the efficiency and accuracy of our approach in detecting and mitigating potential threats. Furthermore, based on our research findings, we provide valuable recommendations for enhancing security and privacy in IoT ecosystems. We also highlight emerging trends in the security and privacy domains, which can serve as valuable insights for researchers and practitioners. In conclusion, our proposed framework offers a robust and proactive approach to address the security and privacy challenges, such as unauthorized data access and device breaches posed by the widespread adoption of IoT devices. By combining machine learning algorithms and Blockchain technology, we contribute to safeguarding user data and fostering a secure environment for IoT applications. This study lays the groundwork for further advancements in the realm of IoT security and privacy, ensuring a safer and more resilient IoT landscape for the future.

Under typical marine conditions of about 80 % relative humidity, evaporation of water from the ocean is an irreversible process accompanied by entropy production. In this article, equations are derived for the latent heat of irreversible evaporation and the related non-equilibrium entropy balance at the sea surface. To achieve this, linear irreversible thermodynamics is considered in a conceptual ocean evaporation model. The equilibrium thermodynamic standard TEOS-10, the International Thermodynamic Equation of Seawater – 2010, is applied to irreversible evaporation under the assumption of local thermodynamic equilibrium. The relevance of local-equilibrium conditions for irreversible thermodynamics is briefly explained. New equations are derived for the mass flux of evaporation and for the associated non-equilibrium enthalpies and entropies. The estimated entropy production rate of ocean evaporation amounts to 0.004 W m^(-2) K^(-1) as compared to the average terrestrial global entropy production of about 1 W m^(-2) K^(-1).

We have previously developed several successful decellularization strategies yielding porcine cardiac extracellular matrices (pcECMs), which exhibit tissue-specific bioactivity and bioinductive capacity when cultured with various pluri- and multipotent stem cells. Here, we studied the tissue-specific effects of the pcECM on seeded human mesenchymal stem cells (hMSCs) phenotype using reverse transcribed quantitative polymerase chain reaction (RT-qPCR) arrays for cardio-vascular related genes. We further corroborated interesting findings at the protein level (flow cytometry and immunological stains) as well as bioinformatically using several mRNA sequencing and protein databases of normal and pathologic adult tissue expression, as well as during human embryonic organogenesis. We discovered that upon seeding of human mesenchymal stem cells (hMSCs) on the pcECM they displayed partial MET toward endothelial phenotypes (CD31+) and morphologies, which were preceded by an early spike (~day 3 onward after seeding) in HAND2 expression at both the mRNA and protein levels compared to plate controls. CRISPR-Cas9 knockout (KO) of HAND2 and its associated antisense long non-coding RNA (HAND2-AS1) regulatory region resulted in proliferation arrest, hypertrophy, and senescent-like morphology. Bioinformatic analyses revealed that HAND2 and HAND2-AS1 are highly correlated in expression, are expressed in many different tissue types albeit at distinct yet tightly regulated expression levels. Deviation (down or up regulation) from these basal tissue expression levels are associated with a long list of pathologies. We thus suggest that HAND2 expression levels may finetune cell plasticity possibly affecting senescence and mesenchymal-to-epithelial transition states, through yet unknown mechanisms. Targeting this pathway may represent a promising new therapeutic approach for a wide range of diseases, including cancer, degenerative disorders, and aging. Nevertheless, further investigations are required to better understand the molecular players involved, potential inducers and inhibitors of this pathway, and eventually potential therapeutic applications.

Covid-19 pandemic has greatly affected the whole world since the beginning and it continues to affect it. The main aim of this study is to show how Covid-19 affect other mortal diseases; cancer, heart diseases, and diabetes in near future. With this purpose two mathematical models are proposed via Ordinary Differential Equations (ODEs); one for the relationship between Covid-19 and cancer and one for the relationship between Covid-19, diabetes and heart diseases. Afterwards, stability analyses of these models are demonstrated. In order to see the effect of parameters on the disease compartments, sensitivity analysis is applied. Results of sensitivity analysis revealed that huge percentage of people are still scared of visiting doctors and this may lead a massive increase in the diagnosis of other diseases for upcoming years. Moreover, figures displayed that there exists a relationship between diabetes and heart diseases. Especially, diabetes patients should be careful about their health situations and take care of their heart. In order to provide these, awareness of people should be developed.

The global construction sector contributes a significant share of total greenhouse gas (GHG) emissions. In Australia, infrastructure activity alone generates 18% of the GHG emissions budget. The use of low-embodied carbon building materials is crucial to achieving sustainability in the construction sector and to fulfill national and international climate goals. Industrial hemp (Cannabis sativa L.) is considered a promising feedstock for sustainable construction materials because of its biogenic carbon content, fast-growing cycles with low agricultural input requirements, and technical functionality which is comparable to traditional materials. This study has applied the life cycle assessment (LCA) guideline of ISO 14040:2006 to estimate the carbon footprint (CF) expressed in carbon dioxide equivalent (CO2eq) emissions of hemp-based building materials in Western Australia. The functional unit is 1 m2 of hemp-based board, and the system boundary includes cradle-to-gate stages, i.e., pre-farm, on-farm, and post-farm activities. The production of 1 m2 of hemp-based board is estimated to be - 2.302 kgCO2eq. Electricity from the public grid for lignin extraction during the post-farm stage is the main contributor to total CO2eq emissions (26%), followed by urea production (14%) during the pre-farm stage. Overall, the use of electricity from the SWIS during the post-farm stage accounts for 45% of total emissions. Sensitivity analysis shows that the CF of hemp-based boards is highly sensitive to the source of energy, i.e., total replacement of the SWIS by solar power decreases the CF from - 2.30 to -6.07 kgCO2eq (164%). The results suggest that hemp-based boards exhibit lower embodied GHG emissions compared to traditional materials, such as gypsum plasterboards.

Objective: There are currently no known treatment methods for ensuring complete recovery from facial nerve damage. Thus, various basic and clinical studies continue to be conducted to achieve this end. As part of this research, autophagy is being investigated for its role in nerve regeneration. Here, we review the existing literature regarding the involvement and signifi-cance of autophagy in facial nerve injury and regeneration. Methods: A comprehensive litera-ture review was conducted to assess the induction and role of autophagy in facial nerve injury and subsequent regeneration. Results: Studies conducted on rats and mice have demonstrated activation of autophagy and expression of related factors in facial and sciatic nerves. Among the most studied of these factors in relation to degeneration and regeneration of facial and sciatic nerves are LC3II/I, PI3K, mTOR, Beclin-1, ATG3, ATG5, ATG7, ATG9, and ATG12. Conclusion: This analysis indicates that autophagy is involved in the process of nerve regeneration follow-ing facial and sciatic nerve damage. Inadequate autophagy induction or failure of autophagy re-sponses can result in regeneration issues after facial or sciatic nerve damage. Animal studies suggest that autophagy plays an important role in facial and sciatic nerve degeneration and re-generation.

Background: The target volume for post-mastectomy radiation therapy (PMRT) in breast cancer patients with reconstruction has been a subject of debate. This study aimed to assess the radiation dose distribution and treatment outcomes associated with different chest wall (CW) delineation according to ESTRO ACROP guideline for patients underwent implant-based reconstruction. Methods: We conducted a retrospective review of breast cancer patients who underwent mastectomy followed by two-stage implant-based breast reconstruction and adjuvant radiation therapy (RT) between 2007 and 2022. The expanders/implants were positioned retropectorally. The chest wall target volumes were categorized into two groups: the prepectoral group, which excluded the deep lymphatic plexus, and the whole expander group. Results: The study included 26 patients, 15 in prepectoral group and 11 in whole expander group. No significant differences were observed in normal organs exposure between the two groups. There was a trend toward a lower ipsilateral lung mean dose in the prepectoral group (10.2 vs. 11.1 Gy, p=0.06). Both groups exhibited limited instances of reconstruction failure and local recurrence. Conclusions: For patients undergoing two-stage expander-implant retropectoral breast reconstruction and PMRT, our data have provided comparable outcomes and normal organs exposure for those omitting the deep lymphatic plexus.

Background: Pro-golfers are increasingly trained scientifically, but swing technique characteristics have not yet been conclusively determined for golf performance. We investigated the relationship between the player's thorax, pelvis and club based on a wireless biofeedback system. We also determined whether thoracic and pelvic changes during different swing phases have different effects on ball striking. Methods: Eight male professionals performed 10 successful full-swing shots using a 5-iron and applied the K-vest wireless biofeedback system for analysis. Results: Peak angular velocities between the pelvis, torso, and clubs were all significantly different (p<0.05) in the men's professional players. All players deviated more from the PGA players range metrics during the preparation stance. Excessive lateral pelvic bending angle, over-rotation, and hyperextension of the trunk were prevalent at the top of the backswing. Conclusions: Most players have an irrational sequence of pelvic, trunk and club rotation times, which is not conducive to improving club head speed and distance. Excessive pelvic rotation in the closed direction at the apex of the backswing is not conducive to maximizing the X-factor. At the moment of striking the ball, maintain a moderate forward trunk lean and full trunk rotation to avoid sports injuries.

Recently, the focus of entity linking research has centered on the zero-shot scenario, where the entity mention to be labeled at the time of testing was never observed during the training phase or may belong to a different domain than the source domain. Current studies have used BERT as the base encoder as it effectively establishes distributional links between source and target domains. The currently available negative sampling methods all use an extractive approach, which makes it difficult for the models to learn diverse and more challenging negative samples. To address this problem, we propose a generative negative sampling method, Adaptive_mixup_hard, which generates more difficult negative entities by fusing the features of both positive and negative samples on top of hard negative sampling and introduces a transformable adaptive parameter W to increase the diversity of negative samples. Next, we fuse our method with the Biencoder architecture and evaluate its performance under three different score functions. Ultimately, experimental results on the standard benchmark dataset Zeshel demonstrate the effectiveness of our method.

OpenToolFlux is an open-source software to estimate soil gas fluxes from gas concentration time-series data generated by automatic chamber systems. This paper describes the physical equipment used as well as software design and workflow. The software is a command-line application that imports tabular time-series data from the analyzer following the instructions specified in a configuration file by the user, performs configurable data-cleaning operations, and outputs a data file with volumetric flux estimates as well as diagnostic plots. The software can be configured according to the specifics of physical equipment and experimental setup and is therefore applicable in a wide range of studies.

This research explored the influence of spatiotemporal variations in phreatic levels and salinity on the patterns and interactions of soil mesofauna communities in a tropical urban coastal wetland. It delineated significant variations in phreatic levels and salinity, with distinct regimes characterizing different habitats and hydroperiods. A total of 120 mesofauna morphotypes across 42 taxa were identified, revealing habitat differences and similarities, and the ecosystem biodiversity. Moderate correlations were established between phreatic levels, salinity, and mesofauna richness and abundance, with habitat type and phreatic level emerging as significant predictors in the regression model. Our findings indicate that shallow phreatic levels in conjunction with oligohaline salinity conditions foster a more favorable abiotic environment, thereby promoting increased biodiversity. The study underscores the dynamic and adaptive nature of mesofauna communities in response to changing environmental conditions, offering valuable insights for effective costal urban wetland management, particularly in the context of multiple stressors such as global and regional climate change, sea level rise, and human activities. The bio-sensor capacity of soil mesofauna emerges as a vital tool for monitoring and facilitating adaptive ecosystem management, thereby ensuring their long-term health and sustainability.

In recent years, a large-scale afforestation campaign has taken place in Inner Mongolia, China, to control desertification and soil erosion. However, the water consumption associated with large-scale afforestation significantly impacts the water resources in Inner Mongolia, resulting in a substantial ecological risk. This study aimed to evaluate the ecological risk of water resources caused by afforestation in the region. In this study, based on land cover data, Normalized Difference Vegetation Index (NDVI) data, and meteorological data, used trend analysis, water balance equation, and Water resources Security Index (WSI) index to analyze the ecological risks of water resources caused by afforestation in Inner Mongolia from 2000 to 2020. The results show that:(1) The afforestation area in Inner Mongolia was 5.37×104 km2 in 2000-2020; (2) Afforestation in arid and semi-arid areas leads to the reduction of water resources. (3) Afforestation reduces water resources in the study area by 0.76×108m3/year; (4) ~76% of afforestation regions face ecological risks of water resources.

This literature review focuses on the development of an ontology for public policy problems in Ethiopia. The study aims to provide a structured representation of concepts, relationships, and knowledge specific to the Ethiopian policy context. The research follows a systematic ontology development process that incorporates domain-specific knowledge and stakeholder involvement.The review begins by describing the steps involved in the ontology development process, including problem identification and scoping, requirement analysis, ontology modeling, and stakeholder involvement. It emphasizes the importance of engaging policymakers, subject matter experts, and researchers throughout the process to validate the ontology and ensure its relevance and effectiveness in addressing Ethiopian policy problems.The application of the developed ontology to specific policy problems is then discussed. Examples include agricultural policy analysis, healthcare policy evaluation, and education policy planning. The review highlights how the ontology can support policy analysis, decision-making, and evaluation by capturing relevant concepts, simulating policy scenarios, and assessing policy impacts.Furthermore, the review identifies potential challenges and limitations in the ontology development process, such as data availability, expert knowledge engagement, and the evolving policy landscape. These challenges need to be addressed to ensure the ontology's accuracy and usability in addressing Ethiopian policy problems.Finally, the review provides suggestions for further research and improvement, such as integrating the ontology with data sources, fostering collaborative ontology development, exploring semantic reasoning and inferencing techniques, and promoting interoperability and standardization. These suggestions aim to enhance the ontology's capabilities and its contribution to the field of ontology development for public policy problems.In conclusion, the development of an ontology for public policy problems in Ethiopia offers a valuable tool for policymakers, researchers, and stakeholders to understand, analyze, and address complex policy challenges. The ontology's relevance and applicability to the Ethiopian context, stakeholder involvement, and support for policy analysis make it a significant contribution to the field of ontology development for public policy.

The type of implant at the fracture site has effects not only from biological perspective but also from mechanical perspective in fracture healing. Biodegradable implants such as magnesium (Mg) based alloys have shown faster secondary bone healing properties as compared to bioinert implants such as titanium (Ti). The general reasoning behind this is the benefit of Mg from biocompatibility perspectives. We study the effect of Ti and Mg as base materials for implants with their different mechanical properties. The focus of our work is on the displacements at the fracture site of the tibia and their influence on the stimulus for bone healing. We have found that in comparison to Ti, Mg implants have minimal stress shielding problem, only which led to better mechanical stimulus at the fracture site.

Background – Mali was one of the first countries in sub-Saharan Africa to initiate a National Schistosomiasis Control Programme (NSCP) in 1982. The WHO's 2021-30 roadmap sets out criteria for eliminating and controlling schistosomiasis as a public health problem. Our study aimed to assess the impact of annual Mass Drug Distribution (MDD) with praziquantel (PZQ) among school-age children in the sentinel sites (SS) of the NSCP. Methods –The study took place at twelve SS in Kayes and Koulikoro regions. Two-round observational cross-sectional studies were carried out in December 2014-2015 and in April 2018 after four to five years of annually MDD. Overall, 2442 schoolchildren aged 7 to 14 were successfully examined. The urine filtration and Kato-Katz method were used for determining Schistosoma haematobium and S. mansoni eggs, respectively. Results –Of the twelve SS treated from 2014-2015, one has achieved the criterion of elimination of S. haematobium as a public health problem (prevalence of heavy intensity infection PHI < 1%) (ie, ≥50 S. haematobium eggs per 10 mL of urine or ≥400 S. mansoni eggs per g of stool), four met the morbidity control criterion (PHI< 5%) while two sites remained confined below the morbidity control criterion (PHI>5%). Five SS had no heavy intensity infection. The prevalence of S. mansoni was less than 1%. Conclusion –The impact evaluation of MDD with praziquantel in the SS of NSCP highlights that MDD has significantly reduced the PHI of schistosomiasis. However, the high prevalence of schistosomiasis or its increase in some sites requires in-depth studies.

Nutraceuticals comprise dietary supplements, functional foods, medicinal foods, and pharmaceuticals. However, to date all these concepts are interpreted in different ways with the rapid increasing knowledge on nutrition, medicine, and plant biotechnology changing the concepts about food, health and agriculture. What matters are the bioactive elements conveyed by foodstuffs as nutrients or non-nutrients, which interfere with human metabolism and have impact on health, aging and well-being. Food, not nutrients, is the fundamental unit in nutrition and edible mushrooms, are fungi that supply unique biological compounds, different from plant or animal origin, which significantly impact on health status. Their influence on medicinal interventions has been known and studied for many years. The role on neurodegenerative disorders has been recently investigated and their significance on many other diseases has been well demonstrated. On this note it is synthesized the more recent knowledge of some edible mushrooms and preparations on Ménière’s disease, a lifelong condition it can develop at any age, but most commonly appearing between 40 and 60 years of age.

The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest to incorporate technologies and methods to determine these homogeneous zones. A case study was conducted in a 3.3 ha vineyard located near Évora, South of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture, pH, organic matter -OM, phosphorous -P2O5, potassium -K2O, sum of the exchange bases -SEB; and cation exchange capacity -CEC) which were determined from 20 soil samples taken in the different MZs. Additionally, validation was also performed using Rasch measures, which were defined based on the formula-tion of the objective and probabilistic Rasch model, integrating the information from the afore-mentioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ. The use of ECa constitutes an efficient technological tool for implementing site-specific man-agement in viticulture, which allows for the improvement of decision-making processes by con-sidering the inherent spatial variability of the soil.

This paper investigates the polarization and heat generation characteristics of batteries under different ambient temperatures and discharge rates by means of using a coupled electric-thermal model. The study found that the largest percentage of polarization is ohmic polarization, followed by concentration polarization and electrochemical polarization. The values of the three types of polarization are generally small and stable under normal-temperature environments and low-discharge rates. However, they increase significantly in low-temperature environments and high-discharge rates and continue to rise during the discharge process. Additionally, ohmic heat generation and polarization generation also increase significantly under these conditions. Reversible entropy heat is less sensitive to ambient temperature but increases significantly with the increase of the discharge rate. Ohmic heat generation and polarization heat generation contribute to the total heat generation of the battery at any ambient temperature, while reversible entropy heat only contributes to the total heat generation of the battery at the end of discharge.

Obesity, characterized by the excessive accumulation of body fat, contributes to a multitude of physiological dysfunctions. This paper explores the complex relationship between obesity and various risk factors and complications, shedding light on critical health implications. Obesity triggers alterations in insulin, leptin, adiponectin, cytokines, and insulin-like growth factors, fostering conditions conducive to cancer initiation. Aberrations in nutrient-dependent intracellular signaling pathways, driven by the excess nutrition characteristic of obesity, contribute to the neoplastic transformation of cells. The Body Mass Index (BMI) correlates directly with adiposity, underlining its significance in cancer risk. Furthermore, insulin and insulin-like growth factors, notably IGF-2, play pivotal roles in this relationship. The expression of IR-A receptors is elevated in cancer. Obesity and cardiovascular diseases share a strong association. Obesity elevates the risk of fatal events like myocardial infarction. High cholesterol levels contribute to atherosclerosis in the aorta and coronary arteries. The severity of coronary artery disease is influenced by plaque formation characterized by calcium deposits. Obesity is also linked to hypertension and increased ventricular mass, exacerbating cardiovascular risks. Hypercholesterolemia and hypertension correlate with a high Body Mass Index (BMI). Obesity is intricately connected to insulin resistance, particularly evident in childhood obesity. It entails a gradual decline in insulin sensitivity, leading to elevated insulin levels in the bloodstream. Insulin resistance is a central factor in the development of Type 2 Diabetes Mellitus. Obesity also results in elevated triglyceride levels and reduced high-density lipoproteins, contributing to atherogenic dyslipidemia and a heightened risk of atherosclerosis. Additionally, obesity is associated with various other disorders, including epilepsy, depression, and neuropsychological problems. Beyond its physiological impact, obesity is associated with significant psychosocial challenges. Studies indicate that individuals with obesity face a higher risk of depressive symptoms, often related to overeating and unhealthy dietary patterns. The social withdrawal tendencies of obese individuals exacerbate these symptoms, with higher rates of depression observed in this group. OSA, a sleep disorder characterized by intermittent breathing cessation during sleep, is strongly correlated with obesity. Approximately 58% of obese individuals experience OSA, with higher Body Mass Index (BMI) associated with an increased risk. Weight reduction has been found to mitigate the severity of OSA and related arrhythmias. Continuous positive airway pressure (CPAP) therapy demonstrates effectiveness in reducing visceral fat accumulation and leptin levels. This comprehensive review underscores the intricate web of health implications associated with obesity, emphasizing the critical need for preventive measures and intervention strategies to address the multifaceted challenges posed by this global health concern.

Light enables vision and exerts widespread effects on physiology and behaviour, including regulating circadian rhythms, sleep, hormone synthesis, affective state, and cognitive processes. Appropriate lighting in animal facilities may support welfare and ensure that animals enter experiments in a controlled physiological and behavioural state. Proper consideration of light during experimentation - both when it is explicitly employed as an independent variable and as a general feature of the environment - has the potential to provide more informative experimental designs and more reliable outcomes, contributing to Reduction and Refinement, helping to ensure more ethical animal use, and improving data quality. As such, it is unfortunate that ambient light for animals is typically quantified in units (lux) designed for human observers. We report the consensus views of an expert working group, with expertise spanning mammalian photobiology, neurobiology and animal husbandry and welfare, convened in February 2023 to agree upon metrics for light appropriate for non-human mammals and their application to improve animal welfare and the quality of animal research. We conclude that species-specific versions of the recently standardised a-opic metrology represent the best available approach to quantifying light. We provide methods for measuring these quantities; practical guidance for their implementation in husbandry and experimentation; and quantitative guidance on appropriate light exposure for laboratory mammals.

Towards better understanding of factors controlling carbon (C) exchange between inland waters and atmosphere, we addressed inorganic carbon cycle in semi-arid lakes of Central Eurasia, subjected to strong impact of on-going climate change. For this, we assessed the hydrochemical vari-ability and quantified its control on formation of authigenic carbonate minerals, occurring within the upper layer of sediments in 43 semiarid lakes located in the southwest of Western Siberia (Central Eurasia). Based on measurements of pH, total dissolved solids (TDS), cationic and anionic composition, dissolved organic and inorganic C, as well as textural and mineralogical characterization of bottom sediments using X-ray diffraction and scanning electron microscopy, we demonstrate that lake water pH and TDS are primarily controlled by both lithological and climatic context of the lake watershed. We have not revealed any direct relationships between lake morphology and water chemistry. The most common authigenic carbonates scavenging atmospheric CO2 in the form of insoluble minerals in lake sediments were calcite, aragonite, Mg-calcite, dolomite and hydro-magnesite. The calcite was the most common component, aragonite mainly appears in lakes with sediments enriched in gastropod shells or artemia cysts, while hydromagnesite was most common in lakes with high Mg/Ca molar ratios, as well at high DIC concentrations. The relationships between mineral formation and water chemistry established in this study can be generalized to a wide suite of arid and semi-arid lakes in order to characterize current status of inorganic C cycle and predict its possible modification under on-going climate warming such as water temperature rise and change of hydrological connectivity, primary productivity and nutrient regime.

We review the topological gauge theory description of Josephson junction arrays (JJA), fabricated systems which exhibit the superconductor to insulator transition (SIT). This description revealed the topological nature of the phases appearing at the SIT and lead to the discovery of a new state of matter, the superinsulator, characterized by an infinite resistance, even at finite temperature, due to linear confinement of electric charges. This discovery is particularly relevant for the physics of superconducting films with emergent granularity, which are modeled by JJA, and share the same phase diagram.

Trans-arterial radioembolization (TARE) is a form of radiation therapy performed for hepatocellular carcinoma (HCC) via selective intra-arterial injection of Yttrium-90 loaded microspheres. This was a multicenter retrospective study of consecutive patients with HCC who underwent TARE between July 2009 and May 2019. Using pre-treatment computed tomography imaging, the total cross-sectional area (cm2) of the abdominal skeletal muscle at the third lumbar vertebra was measured. The skeletal muscle index (SMI) was calculated by normalizing the muscle area to patient height. In total, 347 patients (median age, 65 years; 284 male) were included in the study. A total of 108 (31.1%) patients had portal vein tumor thrombus (PVTT) and 126 (36.3%) were classified as sarcopenic. The median overall survival (OS) was 28.1 months (95% CI, 24.8-35.7) and median progression-free survival was 8.0 months (95% CI, 6.4-9.4). Multivariate Cox regression analysis revealed that sarcopenia (hazard ratio [HR], 1.36; 95% CI, 1.00-1.85, p = 0.05), PVTT (HR, 1.82; 95% CI, 1.33-2.49, p &lt; 0.01), alpha-fetoprotein (AFP) (≥200 ng/mL) (HR 1.41; 95% CI, 1.04-1.92, p = 0.03), and albumin-bilirubin grade (2-3) (HR 1.74; 95% CI, 1.24-2.43, p &lt; 0.01) were independently associated with poor OS. TARE provided favorable long-term outcomes for patients with advanced HCC. Pre-treatment sarcopenia independently associated with survival, suggesting its utility as a surrogate biomarker for identifying TARE candidates.

Abstract: This study observes the characteristics and influencing factors of carbon fluxes of the Momoge salt marsh ecosystem over four years, which behaves as a CO2 sink. The daily, seasonal, and interannual variations of CO2 fluxes in the Momoge salt marshes were observed using the eddy covariance method and compared with various environmental factors. An overall daily “U” shaped distribution was observed, with uptake during the day (negative values) and release at night (positive values). Annually, the carbon fluxes in the study area roughly exhibit a “V” shape. Carbon fluxes during the non-growing season predominantly showed positive values, indicating the release of CO2 into the atmosphere. Photosynthetically active radiation was the primary influencing factor affecting hourly and daytime variations in net ecosystem exchange (NEE) during the growing season, while temperature was the main factor influencing nighttime NEE dynamics. Air temperature, soil temperature, photosynthetically active radiation, precipitation, and water level all had significant impacts on daily net CO2 exchange. At the monthly scale, larger values of soil temperature, air temperature, photosynthetically active radiation, and aboveground biomass correspond to a stronger carbon absorption capacity of the ecosystem. Overall, temperature remains the primary factor for carbon fluxes in the Momoge wetlands.

Biochars are often proposed as a strategy for long-term carbon sequestration. Nevertheless, application of pyrolysed feedstock, particularly along with exogenous organic matter, may affect carbon dynamics in soil through introduction of labile carbon pools and stimulation of extracellular enzymes activity. The main aim of this research was to evaluate the influence of biochars and unprocessed organic amendments addition in two agricultural soils on the dissolved organic carbon (DOC) content and activity of three enzymes involved in carbon turnover. In the incubation experiment, activity of dehydrogenase, β-glucosidase, cellulase and DOC content were measured on day 30, 60, 90, 180 and 360. Addition of biochars stimulated the activity of dehydrogenase and β-glucosidase, while cellulase was suppressed. Fresh biomass amendment enhanced activity of the enzymes through priming effect. DOC content tended to be the highest in treatments with high enzyme activity, suggesting that DOC introduced with amendments acted as a source of energy for microbes. Our findings support the hypothesis that biochar properties and presence of exogenous organic matter affect microbial response in soil, what might be crucial for carbon sequestration potential of biochar. However, long-term studies are recommended to fully understand the mechanisms that determine response of soil biota to biochar addition.

In recent years, the high-frequency abnormal price fluctuations of small-scale agricultural products have been detrimental to market stability. The traditional method based on statistical data of production factors can no longer accurately predict abnormal price fluctuations. Taking scallions as a case, the paper identifies price influencing factors from massive network information, and analyzes the causes and changing characteristics of price fluctuations from four perspectives: market supply, economic environment and market sentiment, and attention. Initially, the study employs an LDA topic model to extract factors from online sentiment data over the past four years, including market supply and demand, economic conditions, related agricultural prices, and market attention. Subsequently, using the SO-PMI algorithm to expand domain-specific lexicons and employing semantic and sentiment analysis with syntactic parsing, the study aims to improve the accuracy of sentiment quantification in text analysis. Furthermore, cointegration and Granger causality tests validate the significant impact of these factors on scallion price fluctuations, mitigating spurious regression issues. Finally, by employing a TVP-VAR model, the study compares the impulse responses and shock magnitudes of various factors in different time and spatial dimensions. It also delves into the mechanisms of heterogeneous impacts and trends in scallion prices, considering the corresponding socio-economic context and public sentiment events within specific time windows, thereby providing valuable decision-making insights for the healthy development of agricultural markets.

Coalescence of nanowires and other three-dimensional structures into continuous film is desirable for growing low dislocation density III-nitride and III-V materials on lattice-mismatched substrates, and interesting from the fundamental viewpoint. Here, we develop a growth model for vertical nanowires which, under rather general assumptions on the solid-like coalescence process within the Kolmogorov crystallization theory, results in a morphological diagram for the asymptotic coverage of a substrate surface. The coverage is presented as a function of two variables, the material collection efficiency on the top nanowire facet a, and the normalized surface diffusion flux of adatoms from the NW sidewalls b. The full coalescence of nanowires is possible only when a=1 regardless of b. At a&gt;1, which is usual for vapor-liquid-solid growth with a catalyst droplet, nanowires can only partly merge but never coalesce into continuous film. These results can be used for predicting and controlling the degree of surface coverage by nanowires and three-dimensional islands by tuning the surface density, droplet size, adatoms diffusivity, and geometry of the initial structures in the vapor-liquid-solid, selective area or self-induced growth processes in different epitaxy techniques.

Sepsis is a life-threatening complication of an infectious process that results from excessive and uncontrolled activation of the host's pro-inflammatory immune response to a pathogen. Lipopolysaccharide (LPS), also known as endotoxin, which is a major component of the Gram-negative bacteria outer membrane, plays a key role in the development of Gram-negative sepsis and septic shock in humans. To date, no specific and effective drug against sepsis has been developed. This review summarizes data on LPS-binding proteins from marine invertebrates (ILBPs), that inhibit LPS toxic effects, and are of interest as potential drugs for the sepsis treatment. The structure, physicochemical properties, antimicrobial and LPS-binding/neutralizing activity of these proteins and their synthetic analogues are considered in details. Problems that arise during clinical trials of potential anti-endotoxic drugs are discussed.

In recent years the study of the teacher-student relationship in the teaching-learning processes in physical education has had great emphasis. Previous studies have shown that the use of the Spectrum of teaching Styles can enhance intrinsic motivation, enjoyment, adherence to physical activity and physical activity levels in children and adolescents. The present study aims to assess if a physical education (PE) intervention based on the variations in teaching styles, with reference to production ones, can also have positive effects on physical fitness. The sample involved 4 primary school classes (n = 124 children, mean age = 8-10 years) recruited from the SBAM (Health, Wellness, Food Education and Movement at School) Project in Apulia, Southern Italy. Classes were randomly assigned to Experimental Group (EG) and Control Group (CG). EG followed a 5months experimental intervention based on the variation of teaching styles, while CG performed regular PE lessons. Physical fitness test was assessed with Standing Long Jump (SLJ), Medicine Ball Throw 1kg (MBT), and 20m sprint (20m), while two validated questionnaires were used to evaluate physical self-perception (PSP) and enjoyment. A 2x2 (intervention group x time) ANOVA was carried out to assess significant difference and interaction effect pre (t0) and post (t1) intervention protocol. Data analysis showed a significant improvement of physical fitness in both EG and CG, while PSP and enjoyment increased only in EG. Moreover, significant interaction (p&lt;. 05) effects were found for 20m sprint, PSP and Enjoyment with low effect size (η2 ~. 20). The results of the present study highlight the effectiveness of a PE intervention based on the variation of teaching styles in improving physical fitness, self-perception, and enjoyment. Moreover, the use of production teaching styles significantly impacts self-perception and enjoyment, that are important mediating factors for guarantee better adherence to physical activity.

The aim in this paper is the presentation of the influence of modification of polypropylene (PP) fibres on sorption capabilities of fibres. Modification of PP fibres were made with inorganic additives in the mass with a view to improving silicate composites – in construction. The prepared modified PP fibres were compared with pure PP fibres and their mechanical and thermomechanical properties were evaluated. And we wanted to evaluate and compare the sorption capabilities of these fibres using the Washburn method. However, the obtained results led us to the conclusion that the given method rather points to the excellent transport properties of PP fibres, as if it evaluated the sorption of the fibres.

Gliomas, the most prevalent and lethal form of brain cancer, are known to exhibit metabolic alterations that facilitate tumor growth, invasion, and resistance to therapies. Peroxisomes, essential organelles responsible for fatty acid oxidation and reactive oxygen species (ROS) homeostasis, rely on the receptor PEX5 for the import of metabolic enzymes into their matrix. However, the prognostic significance of PEX5 for glioma patients remains unclear. We developed a robust prognosis model based on PEX5-dependent signature. This signature not only serves as a robust prognosis model capable of accurately predicting outcomes for glioma patients but also effectively distinguishes several clinicopathological features, including the grade, isocitrate dehydrogenase (IDH) mutation, and 1p19q codeletion status. Furthermore, we developed a nomogram that integrates the prognostic model with other clinicopathological factors, demonstrating highly accurate performance in estimating patient survival. Patients classified into the high-risk group based on our prognostic model exhibit an immunosuppressive microenvironment. Finally, we validated that the peroxisomal localization of the signature genes depends on PEX5 and demonstrated that PEX5 is required for cell growth, migration and invasion of glioma cells. These findings identify the PEX5-dependent signature as a promising prognostic tool for gliomas.

Histone modifications, especially H3K27 and H3K36 methylations, are crucial for epigenetic regulation and are often dysregulated in cancer. In a comprehensive analysis of 11,194 patient samples across 32 cancer types, we identified significant genomic alterations in H3K27 and H3K36 modifiers, with the most common being in KDM6B, BRPF1, KDM6A, SETD2, and NSD1. Patients with these alterations also frequently exhibited mutations in genes like TP53 and PIK3CA. Moreover, the presence of these histone modifier alterations correlated with poorer overall survival, emphasizing their potential as both oncogenic drivers and prognostic markers in various cancers.

Recently, Li et al [1] investigated the nonlinear Langevin equations existence including two fractional orders with infinite-point boundary conditions. It has shown that the outcomes given it does count on the solution form for which it has boundary values. It means that their solution needs more to be in the final step. In current work, we will have discussion about the existence and uniqueness for the same boundary conditions by investigating the closely explicit solution form that has no boundary values. Numerical example is supported to have more vision to compare the between new and previous results. It turns out that our results are superior.

Accurate forecast of tail water level (TWL) is of great importance for the safe and economic operation and management of hydropower stations. The predictive performance is significantly influenced by the backwater effect of downstream hydropower stations and tributaries, but the explicit quantification method of the backwater effect is lacked. In this study, a deep learning model based forecasting framework for TWL predictions is established and applied to forecast TWL of Xiangjiaba (XJB) hydropower stations, which is influenced by the backwater effect of downstream tributaries including Hengjiang River (HJR) and Minjiang River (MJR). Firstly, the lag time of the backwater effect of HJR and MJR is analyzed based on the permutation importance. The results demonstrate that the lag time of backwater effect on the TWL of XJB is 5-7 hours for the HJR and 1-2 hours for the MJR. Then, the runoff thresholds of the HJR and MJR for impacting the TWL of the XJB station are obtained by scenario comparison, and the results show that the thresholds of HJR and MJR are 700 m3/s and 7000 m3/s respectively. Finally, the deep learning methods based TWL forecasting model is established based on the lag time and threshold analysis. The model is used to forecast the TWL in future 48 hours. The results show that the forecasting model has a good predictive performance with 98.22% of absolute errors less than 20 cm. The mean absolute error over the validation dataset is 5.27 cm and the maximum absolute error is 63.35 cm.

Radio astronomical observations at millimeter and submillimeter wavelengths are a very important tool of astrophysical research. However, there is a huge area in the northern Eurasia, including the whole Russian territory, which lacks sufficiently large radio telescopes effectively operating at these wavelengths. In this review we describe our long-term efforts to find suitable sites for such radio telescopes in this area, that is, sites with good atmospheric transparency at millimeter and submillimeter waves. We describe methods and instruments used for measurements and evaluations of the atmospheric opacity. They include special radiometric systems, which are used for estimations of the atmospheric opacity from the sky brightness measurements. Evaluation of the precipitable water vapor from such measurements by the artificial neural network is discussed. Alternative approaches use global atmospheric models and signals of the Global Navigation Satellite Systems. To date, a long-term radiometric monitoring has been performed at several candidate sites and atmospheric conditions for many sites have been evaluated using global atmospheric models. Several sites with the best atmospheric transparency at millimeter and submillimeter wavelengths have been selected. They can be effectively used for astronomical observations at least in the major atmospheric transparency windows at 1.3 mm and 0.85 mm. These results can be also used for space communications and radar systems.

U-Net, based on a deep convolutional neural network (CNN), has been clinically used to au-to-segment normal organs and potentially target volumes. However, CNNs with local geometric dependencies may limit the accuracy of segmentation. Additionally, the performance of CNNs can vary depending on the selection of network hyper-parameters, which was mitigated by the proposition of nnU-Net. We chose a vision transformer architecture called VT U-Net, which features a self-attention excluding the convolution layer, to overcome the limitations of CNNs by utilizing global geometric information of images. The VT U-Net v.2 became more powerful thanks to the adaptive hyper-parameter optimizer embedded in nnU-Net. However, despite leveraging the benefits of nnU-Net, VT U-Net v.2 still had additional network hyper-parameters that needed to be optimally chosen. Accordingly, among various hyper-parameters, this study attempted to find the optimal combination of the patch size and the embedded dimension regarding the transformer. From the 4-fold cross-validation, the modified VT U-Net v.2 showed the highest average performance for planning target volume (PTV) segmentation among the investigated networks. Though nnU-Net was based on convolution layers, the adaptive hyper-parameter optimizers turned out to enhance the performance. It was also confirmed that network hyper-parameters affected the segmentation accuracy of vision transformers.

High-quality optical Fano resonances, which exist in a spherical dielectric microparticle in the spatial configurations of the "whispering-gallery modes" (WGMs) and recently are referred to as the “super-resonances”, possess extremal sensitivity not only to the micro-cavity size and shape but also to the optical properties of the particulate material. The increase in the power of light radiation coupling into a super-resonance can lead to the manifestation of strong optical nonlinearity of the resonator material due to the cubic nonlinearity (optical Kerr effect) and generation of free electron plasma in certain regions of the spherical microcavity. In fact, an optically linear medium of the resonance cavity transforms into a Drude-Kerr-type medium with a strong dependence on input laser intensity. With the help of the finite-elements numerical simulations, we theoretically analyze the transformations of the resonant contour for a number of high-quality WGMs excited in a lanthanum-glass microsphere exposed to an optical radiation of different intensity. We show that in a certain input intensity range, the competition of Kerr and plasma optical nonlinearities can stop and even reverse the Stokes shift of the super-resonance observed in a pure Kerr medium. Additionally, optical ionization and plasma generation within the mode volume significantly reduce the strength of the magnetic super-resonance and lead to its spoiling and frequency splitting.

: In the automotive industry, high-strength plates have been increasingly used to reduce the vehicle body weight due to stringent regulations on fuel economy and safety. Such plates achieve tensile strengths as high as 1.5 GPa owing to the hot-stamping process. However, these plates suffer from scale generation and surface decarburization because of the surface oxidation of the material. Recently, studies on materials subjected to high-frequency induction heating have reported strength improvement owing to the coil shape and cooling method. This study presents the surface temperature changes, mechanical properties, and microstructures of boron steels subjected to longitudinal heating, which uses eddy currents generated from high-frequency induction heating. The surface temperature data were analyzed under different high-frequency induction heating powers (15, 18, 21, 24, 27, and 30 kW) and distances from the specimen (6, 9, and 15 mm). The mechanical properties and microstructures were also analyzed in different high-frequency induction heating coil directions. The correlations between the high-frequency induction heating power and the distance from the specimen with the maximum tensile strength were determined.

Despite the impressive performance of deep neural networks on many different vision tasks, they have been known to be vulnerable to intentionally added noise to input images. To combat these adversarial examples (AEs), improving the adversarial robustness of models has emerged as an important research topic, and research has been conducted in various directions including adversarial training, image denoising, and adversarial purification. Among them, this paper focuses on adversarial purification, which is a kind of pre-processing that removes noise before AEs enter a classification model. The advantage of adversarial purification is that it can improve robustness without affecting the model’s nature, while another defense techniques like adversarial training suffer from a decrease in model accuracy. Our proposed purification framework utilizes a Convolutional Autoencoder as a base model to capture the features of images and their spatial structure. We further aim to improve the adversarial robustness of our purification model by distilling the knowledge from teacher models. To this end, we train two Convolutional Autoencoders (teachers), one with adversarial training and the other with normal training. Then, through ensemble knowledge distillation, we transfer the ability of denoising and restoring of original images to the student model (purification model). Our extensive experiments confirm that our student model achieves high purification performance(i.e., how accurately a pre-trained classification model classifies purified images). The ablation study confirms the positive effect of our idea of ensemble knowledge distillation from two teachers on performance.

We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (USFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD) and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least-squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in 3-fold cross-validation repeated five times. We decided to use the model based on both parameters to estimate the ultrasound fat fraction (USFF). The correlation between USFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, USFF could differentiate between <5% vs. ≥ 5% and < 10% vs. ≥ 10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC) accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. In conclusion, USFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose ≥ 5% and ≥ 10% steatosis in both NAFLD and MAFLD. Therefore, USFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors.

Proposed study aims to investigate the digital transformation of Greek small and medium enterprises (SMEs), with a particular focus on their digital maturity and the strategic and organizational factors contributing to digital transformation. The research issue of digital transformation is attracting considerable interest among academics and business practicians since COVID-19 accelerated the procedure of implementing Industry’s 4.0 principles all over global economies. Quantitative research on 147 Greek SMEs revealed most important issues on how these businesses implement digital transformation, factors accelerating or decelerating the process, barriers and expected outcomes. Research enlights how SMEs face the transition to digital business and reveals the factors that can facilitate the whole process. Results can be valuable for stakeholders enabled to digital transformation process from both business and academic point of view, while there exist aspects that can contribute to policy makers / motivation developers in state’s level as well.

Fibrodysplasia Ossificans Progressiva (FOP) is an enigmatic, ultra-rare genetic disorder characterized by progressive heterotopic ossification, wherein soft connective tissues undergo pathological transformation into bone structures. This incapacitating process severely limits patient mobility and poses formidable challenges for therapeutic intervention. Predominantly caused by missense mutations in the ACVR1 gene, the disorder has hitherto defied comprehensive mechanistic understanding and effective treatment paradigms. This write-up offers a comprehensive overview of the contemporary understanding of FOP's complex pathobiology, underscored by advances in molecular genetics and proteomic studies. We shed light on targeted therapy, spanning genetic therapeutics, enzymatic and transcriptional modulation, stem cell therapies, and innovative immunotherapies. We also focused on the intricate complexities surrounding clinical trial design for ultra-rare disorders like FOP, addressing fundamental statistical limitations, ethical conundrums, and methodological advancements essential for the success of interventional studies. We advocate for the adoption of a multi-disciplinary approach that converges bench-to-bedside research, clinical expertise, and ethical considerations to tackle the challenges of ultra-rare diseases like FOP and comparable ultra-rare diseases. Overall, this article serves a dual role: as a definitive scientific resource for ongoing and future FOP research and as a call to action for innovative solutions to address methodological and ethical challenges that impede progress in the broader field of medical research for ultra-rare conditions.

The hybrid method proposed in the study, ANFIS-GWO, combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) with Grey Wolf Optimization (GWO) for the diagnosis of liver disorders. ANFIS is a powerful tool that combines the advantages of neural networks and fuzzy logic to create a hybrid model capable of handling complex and uncertain data. GWO is a metaheuristic optimization algorithm inspired by the social behaviour of grey wolves. In the ANFIS-GWO method, the hyperparameters of ANFIS are optimized using GWO. This optimization process aims to fine-tune the ANFIS model based on the available dataset, which consists of 7 characteristic attributes and 354 samples related to liver diseases. By adopting the hyper-parameters, the ANFIS-GWO method enhances the overall performance and accuracy of the diagnostic system. To evaluate the effectiveness of the ANFIS-GWO intelligent medical system, the study employs classification accuracy, sensitivity, and specificity analysis. Classification accuracy measures the overall correctness of the system in predicting liver disease cases. Sensitivity refers to the system’s ability to correctly identify individuals with liver disorders, while specificity measures its ability to correctly identify those without liver disorders. Experimental results demonstrate that the performance of the ANFIS-GWO method surpasses that of traditional Fuzzy Inference Systems (FIS) and ANFIS models that do not undergo an optimization phase. This suggests that the integration of GWO optimization significantly improves the diagnostic accuracy of the ANFIS model for liver disease diagnosis.

The rapid adoption of hydrogen as an eco-friendly energy source has necessitated the development of intelligent power management systems capable of efficiently utilizing hydrogen resources. However, guaranteeing the security and integrity of hydrogen-related data has become a significant challenge. This paper proposes a pioneering approach to ensure secure hydrogen data analysis through the integration of blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. By combining blockchain with intelligent power management systems, the efficient utilization of hydrogen resources becomes feasible. The utilization of smart contracts and distributed ledger technology facilitates secure data analysis, real-time monitoring, prediction, and optimization of hydrogen-based power systems. The effectiveness and performance of the proposed approach are demonstrated through comprehensive case studies and simulations. Notably, our prediction models, including ABiLSTM, ALSTM, and ARNN, consistently delivered high accuracy with MAE values of approximately 0.154, 0.151, and 0.151, respectively, enhancing the security and efficiency of hydrogen consumption forecasts. The blockchain-based solution offers enhanced security, integrity, and privacy for hydrogen data analysis, thus contributing to the advancement of clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines potential future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, with a specific focus on secure hydrogen data analysis and intelligent power management systems.

Super Typhoon Saola came very close to Hong Kong on 1 and 2 September 2023, necessitating the issuance of No. 10 hurricane signal, the highest tropical cyclone warning signal, in Hong Kong. While there were widespread damages in Hong Kong, no people were killed in the event with effective early warning. It is rare that a super typhoon came very close to Hong Kong and this paper is the first part in the series of the documentation of Saola to summarize the interesting observations of Saola near Hong Kong for future reference by weather forecasters, including sur-face observations, upper air observations, microburst alert from weather radars, and turbulence intensity based on spectral width measurement of radars.

Temporal lobe epilepsy is a common, chronic disorder with spontaneous seizures that is often refractory to drug therapy. A potential cause of temporal lobe epilepsy is primary brain injury, making prevention of epileptogenesis after the initial event an optimal method of treatment. Despite this, no preventive therapy for epilepsy is currently available. The purpose of this study was to evaluate the effects of anakinra, lamotrigine, and their combination on epileptogenesis using the rat lithium-pilocarpine model of temporal lobe epilepsy. The study showed that the treated and untreated animals showed no significant difference in the number and duration of seizures. However, the severity of seizures was significantly reduced after treatment. Anakinra and lamotrigine, alone or in combination, significantly reduced neuronal loss in the CA1 hippocampus compared to the control group. However, the drugs administered alone were found to be more effective for CA3 than their combination. The treatment alleviated the impairments in activity level, exploratory behavior and anxiety, but had a relatively weak effect on TLE-induced impairments in social behavior and memory. The efficacy of the combination treatment did not differ from that of anakinra and lamotrigine monotherapy. These findings suggest that anakinra and lamotrigine, alone or in combination, may have clinical utility in preventing epileptogenesis.

In contemporary sociological discourse, social trust emerges as a fundamental determinant in catalyzing positive socio-economic interactions. The nexus between social relationships and the inherent trust within them is quintessential for the holistic well-being of individuals. The current research undertook a rigorous examination of the variations in generalized trust levels across distinct age cohorts. For this empirical investigation, a dataset comprising 2,232 observations, exclusively from the United States, was meticulously sourced from the World Value Survey.The empirical findings elucidated a significant disparity in generalized trust levels across age cohorts. Notably, the geriatric demographic manifested elevated levels of generalized trust in juxtaposition to their younger counterparts. Such an observation posits the hypothesis that the construct of trust may indeed possess an age-related dimensionality. Furthermore, a robust statistical analysis accentuated the significance of these observed disparities. The divergences in trust levels across age cohorts retained their statistical significance even post the incorporation of confounding variables such as gender, socio-economic status, educational attainment, ethnic lineage, and religious affiliations. This seminal finding underscores the imperative for further academic explorations into the intricate dynamics of trust within the socio-cultural fabric of our society.

Deep networks-based hashing has gained significant popularity in recent years, particularly in the field of image retrieval. However, most existing methods only focus on extracting semantic information from the final layer, disregarding valuable structural information that contains important semantic details crucial for effective hash learning. To address this limitation and improve image retrieval accuracy, we propose a novel deep hashing method called Deep Supervised Hashing by Fusing Multiscale Deep Features (DSHFMDF). Our approach involves extracting multiscale features from multiple convolutional layers and fusing them to generate more robust representations for efficient image retrieval. Experimental results on CIFAR10 and NUS-WIDE datasets demonstrate that our method surpasses the performance of state-of-the-art hashing techniques.

The objective of this was to evaluate the effects of organic fertilization on biomass production in Urochloa spp. pastures, and the soil biological and physical properties in the Colombian Amazon region. Three pastures crops (Urochloa decumbens, Urochloa humidicola and Urochloa brizantha) with 5 years old were examined in a hill landscape. A randomized complete blocks design covering an area of 5005 m2, with 1 m separation between units to minimize edge effects. Highly significant differences in Urochloa spp. biomass production were observed before and after organic fertilization (i.e., initial time: 992.19±97.66 kg DM ha-1 vs. final time: 1920.94±155.44 kg DM ha-1 vs.), but not between different fertilization treatments. The interaction between the treatment and time was significant for total density (p=0.0300) and richness (p=0.0300) of soil macrofauna. Furthermore, the interaction between treatment and soil depth was significant for bulk density (p=0.0187). The linear mixed effects analysis showed that soil bulk density and penetration resistance were lower in 0 - 10 cm depth than that observed in 10 - 20 depth and 20 - 30 cm depth. Overall, the application of organic fertilizers had a significant and positive effect on Urochloa spp. forage biomass and on the physical and biological properties of soils that had historically been affected by extensive livestock farming in a deforested hill landscape in the Colombian Amazon region.

Soil washing is a rapid and efficient method for heavy metals removal. In this study, in order to prove the feasibility of leaching remediation technology for remediation of lead-contaminated soil around a smelter, intermittent oscillating washing tests and extensive continuous tests were conducted to remediate Pb contaminated soils. Plant growth tests with wheat (Bainong Aikang 58) were also conducted to investigate the effects of leaching on plant growth and the Pb content of stems and leaves. The results revealed that in soils, Pb mainly exists in the forms of PbCO3, Pb5(PO4)3Cl2, PbSO4, and in small amounts of PbS. The intermittent oscillating washing tests showed that a lower liquidsolid(L/S) ratio and a higher leaching temperature and time were related to increased Pb removal efficiency. The Pb removal efficiency rates in the oscillating washing tests and the extensive continuous tests were 72.50% and 69.94%, respectively. In addition, the chemical and physical characteristics of the soil were basically unchanged after the leaching regimes. The results of the plant growth tests showed that the leaching regimes did not have a negative effect on the survival rate and growth of the wheat, and the heavy metal contents of the stem and leaf were effectively reduced. This study provides a reference for the large-scale remediation of contaminated soils.

Triangles are an ever present feature in nature, which the building construction industry duly echoes. However, an exact expression intended to offer the radiant field due to any triangle in an upright or inclined position had not been identified by previous research. In this case, the author has been able to solve by direct integration, the canonical expression of radiative transfer. This result alone confers a myriad of possibilities that had been inconceivable before, for studying in detail the three-dimensional heat transfer behavior of volumes and figures in which triangles do manifest, such as fins, windows, roof-gables and louvers of various kinds. Typically, shading devices, when tilted, give rise in their extremes to rhomboidal shapes which were difficult to take into account or had to be subject to discretization and subsequent Monte Carlo methods in order to perform an approximate calculation of their emission. This implied a lengthy and inexact procedure that induced many errors and consumed computing time. We can now avoid all the former downsides due to the advances hereby presented. As the novel expression can be converted into an algorithm it will be advantageously employed for simulation. This significant finding dovetails in the intricate puzzle of radiated heat and we believe that their consequences will greatly affect the conception and design of HVAC devices, aircraft manufacturing and specifically building or lighting industries among others.

Along with the economic growth, the companies must contribute to social progress and promote environmental sustainability in equal harmony. Sustainable human resource management (SHRM) strategies make it possible to attain the economic, social and environmental goals of a firm. In this regard, a survey method is discussed using the literature review and online questionnaire to identify the main factors/indicators during the SHRM evaluation of manufacturing firms in India. Uncertainty is commonly occurred in the assessment of SHRM factors. As a generalized version of fuzzy sets, single-valued neutrosophic set (SVNS) has been demonstrated as a valuable tool to illustrate the indeterminate, inconsistent and uncertain data of realistic decision-making problems. Considering the idea of SVNSs, this study develops a hybrid multi-criteria group decision-making (MCGDM) approach for assessing the SHRM of manufacturing firms under uncertainty settings. For this purpose, an SVN-alternative ranking order method accounting for two-step normalization (AROMAN) is proposed based on VIFI-score function-based decision experts’ (DEs’) weighting tool and integrated criteria weight-determining model to solve the MCGDM problems with fully unknown DEs and criteria weights. In this regard, we develop new SVN-distance measure to compute the degree of difference between SVNSs. Some examples are presented to demonstrate the efficacy of developed measure over the existing ones. In addition, new criteria weight-determination model is presented with the integration of objective weights through IVIF-distance measure-based model and subjective weights through ranking comparison (RANCOM) tool on SVNSs. The proposed ranking method is applied to an empirical study of SHRM assessment for manufacturing firms in India, which shows its applicability and feasibility. In this study, the evaluation criteria are characterized into social, environmental and economic aspects with DE’s opinions. Comparative and sensitivity analyses are made to show the strength and steadiness of presented approach. This study provides an innovative MCGDM analysis framework, which makes a significant contribution to the SHRM assessment problem under indeterminate, inconsistent and uncertain setting.

Water deficit (drought) is still one of the most important stress factors affecting not only yields, but also production quality. Breeders are focusing on breeding cultivars and crop lines that are more resistant to water shortages. In addition to breeding, for example, for the size of the roots and changes in the color of the leaves, focus on changing the morphotype i.e. long chaff, multirowed ear. It is predicted that wheat genotypes with a morphotype change should be more drought tolerant. Therefore, our research focused on the study of changes in the physiological parameters of wheat (cv. ´Bohemia´) with a changed morphotype (genotypes ´284-17´ [long chaff] and genotype ´29-17´ [multirowed ear]) in relation to exposure to drought. Pigment content, photosynthesis and transpiration rate, water potential were measured in plants irrigated and affected by water deficit. Water deficit was shown to have a statistically significant effect on transpiration rate, photosynthetic rate, water potential and total chlorophyll content. Furthermore, the influence of the genotype on the observed parameters and on the effect of water deficit was demonstrated. Due to the fact that cv. ´Bohemia´, increases during such periods of transpiration, so for this reason it is not suitable for dry areas. Genotype ́29-17 ́ appears promising with respect to drought resistance.

Purpose: This study builds upon an established effective training method to investigate the advantages of high variability phonetic identification training for enhancing lexical tone perception and production in Mandarin-speaking pediatric cochlear implant (CI) recipients, who typically face ongoing challenges in these areas. Method: Thirty two Mandarin-speaking children with CIs were quasi-randomly assigned into the training group (TG) and the control group (CG). The sixteen TG participants received five sessions of high variability phonetic training (HVPT) within a period of three weeks. The CG participants did not receive the training. Perception and production of Mandarin tones were administered before (pretest) and immediately after (posttest) the completion of HVPT via lexical tone recognition task and picture naming task. Both groups participated in the identical pretest and posttest with the same time frame between the two test sessions. Results: TG showed significant improvement from pretest to posttest in identifying Mandarin tones for both trained and untrained speech stimuli. Moreover, perceptual learning of HVPT facilitated trainees’ lexical tone production as rated by a cohort of 10 Mandarin-speaking adults with normal hearing. In contrast, CG did not exhibit significant changes in either perception or production. Conclusion: The results represent initial evidence of HVPT-induced transfer of perceptual learning to lexical tone production in CI users, which supports the application of this speech training protocol to aural rehabilitation practice.

Management of a healthcare unit demands high prerequisites. It is a challenging organizational job for the healthcare decision-makers or leaders to tackle biomedical threats and deliver care service to huge number of affected populations in different demographic area. Health administration take innovative strategies to provide fundamental and life-saving services to the patients, when keeping the safety of the frontline medical workers is undoubtedly a priority. COVID-19 pandemic has changed the overall functioning of the healthcare system globally with alteration in the health decision-making protocols. Through this article, I have elucidated the challenges of healthcare along with today’s managerial paradigms to tackle the problems and run the system in a regulated manner.

Nigeria's upstream oil and gas sector is extensively contributing to the economic growth of the country, but the sector is plagued with challenges around corporate social responsibility (CSR) and taxation practices. Petroleum Industry Act (PIA) is introduced to tackle these challenges towards promoting sustainable development in Nigeria. The aim of this study is to explore the PIA’s provisions on CSR and taxation, identify the Act’s implementation challenges and improvement opportunities, propose an integrated framework for monitoring and evaluating the PIA’s impact on CSR and taxation over time, and recommend measures for enhancing PIA’s impact on CSR and taxation support for sustainable development in Nigeria's upstream oil and gas sector. This study adopts the qualitative desk review method to analyze existent literature, reports, and documents regarding PIA’s provisions on CSR and taxation. Findings reveal that the PIA’s provisions greatly emphasize CSR initiatives and taxation transparency in improving responsible ethical business behaviour. An integrated framework for monitoring and evaluating PIA’s impact over time is developed. This study concludes that the PIA's provisions can balance CSR and taxation practices for sustainable development. The study’s recommendations include using the integrated framework as a structured strategy for monitoring and evaluating the PIA’s impact. This study contributes to the discussion on the imperatives of ethical business practices and regulatory frameworks for sustainable development drive in the oil and gas sector.

Endovascular techniques are currently considered as a first line treatment options for lower limb chronic limb-threatening ischemia (CLTI), defined by the presence of ischemic rest pain and severe tissue loss such as ulcers or gangrene. Although the technical success rate of endovascular revascularization is high, in specific patients with advanced infrapopliteal disease and absence of run-off tibial vessels ("desert foot"), the chance of successful revascularization is minimal. In order to avoid primary amputation several treatment option are currently being investigated, including different strategies such as gene therapy or venous arterialization techniques. This review focuses on the percutaneous deep venous arterialization technique, recently introduced in everyday clinical practice, as a promising, minimally invasive treatment option for limb salvage in CLTI patients presenting with “desert foot”.

The paper reports an analytical study of two problems of Rayleigh-Bénard convection(RBC): one in a Newtonian liquid occupying an axi-symmetric cylindrical enclosure(CE) and second in a two-dimensional rectangular enclosure(RE). Linear stability analysis is employed to obtain information on the onset of convection in terms of a critical Rayleigh number, Ra, as a function of the aspect ratio, Ro. The nature and the flow structures of the convective cells, at the onset of convection, are predicted theoretically by plotting the streamlines for different values of Ro. Not so shallow(Ro&lt;1 or Ro≪1), and very shallow enclosures(Ro≫1) are considered. Concepts of cell-width and the wave number are respectively used in these two types of enclosures. An explicit analytical expression for the number of cells as a function of Ro is obtained theoretically. Exact prediction of the critical value of Ra, viz., Rac, as a function of Ro is also made. These are new findings in the case of both CE and RE. The fundamental differences between the problems of CE and RE are also highlighted.

ABSTRACTBackground: Crohn's disease (CD) is a chronic inflammatory bowel disorder with limited treatment options. Mitochondrial dysfunction has been implicated in CD pathogenesis, and mitochondrial-based interventions have emerged as a potential therapeutic avenue. This systematic review aimed to assess the efficacy of mitochondrial-based interventions in the management of CD.Methods: A systematic search of multiple databases was conducted to identify relevant studies in accordance with the PRISMA protocol. Inclusion criteria encompassed studies investigating mitochondrial-targeted interventions in CD patients. Methodological quality and risk of bias assessments were performed. Data synthesis involved both quantitative meta-analysis and qualitative narrative synthesis.Results: A total of 23 studies were included in this review, comprising randomized controlled trials, observational studies, and case reports. Mitochondrial-based interventions encompassed nutraceuticals, probiotics, exercise, and dietary modifications. However, the overall quality of evidence was moderate, primarily due to methodological limitations in some studies.Conclusion: This systematic review suggests that mitochondrial-based interventions hold promise as adjunctive therapies for CD management. They appear to contribute to clinical remission and amelioration of disease activity. Nevertheless, the moderate quality of evidence underscores the need for further well-designed clinical trials to substantiate these findings and delineate optimal intervention strategies.

Heat transfer fluids are used in various industrial systems to maintain them in perfect operating conditions. Extensive research efforts have been dedicated to enhance the thermal properties of these heat transfer fluids to improve their efficiency. Developing nanofluids is a potential candidate for such enhancements. This study investigates the impact of incorporating TiO2 nanoparticles into two types of oils: transformer oil (NYTRO LIBRA) and virgin coconut oil (manufactured by Govi Aruna Pvt. Ltd.) at different temperatures and with varying volume fractions. The nanofluids were prepared using a two-step method by adding CTAB (Cetyltrimethylammonium bromide) surfactant. To minimize nanoparticle agglomeration, this study employed relatively low-volume fractions. Thermal properties by means of thermal conductivity, thermal diffusivity, and volumetric heat capacity were measured in accordance with ASTM (American Society for Testing and Materials) standard methods, using a multifunctional thermal conductivity meter (LAMBDA thermal conductivity meter). The measured thermal conductivity values were compared with theoretical models and previous research findings. It was confirmed that the modification of thermal properties was enhanced by doping TiO2 nanoparticles with different volume fraction.

The aim of this study is to examine an efficient and environmental friendly process for hydrolyzing starch, an industrial-derived by-product of the potato processing industry, and to use the produced hydrolysates as substrates for methane production. A full factorial experiment was designed and the optimal concentrations of FeSO4·7H2O, H2O2 and temperature were determined obtaining a yield of 99.5%, with a total carbohydrates content equal to 28.65 g, when the input parameters were at their high level: FeSO4·7H2O 1.00g/L, H2O2 0.51 g/L and temperature 70.0oC. The hydrolysis kinetics were also examined revealing that temperature was the most important factor among the three optimization parameters. Furthermore, biodegradability tests were carried out to measure the methane production potential from the produced hydrolysates. The specific methanogenic activity was reached 0.669 g CODCH4/gVSS-day proving the effectiveness of the hydrolysis process and highlighting the potential of this food manufacturing by-product for bioenergy production. A preliminary cost analysis showed that a small investment for utilizing the starch in an existing wastewater treatment facility of a potato processing industry becomes profitable before the end of the 3rd year obtaining a NPV 37.5% higher than the NPV of the current utilization scenario.

A series of novel substituted isoxazolidine derivatives was synthesized through 1,3-dipolar cycloaddition reactions of α-aryl-N-methyl nitrones with various ethylene moieties, resulting in the formation of isoxazolidine derivatives. The structures of the synthesized compounds were characterized using spectroscopic methods. The [3+2] cycloaddition (32CA) reactions of α-aryl-N-methyl nitrones with diverse ethylene substituents were computed employing Density Functional Theory (DFT) at the B3LYP/6–31G(d) level, upgrading bond parameters. An investigation of the electron localization function (ELF) unveiled the zwitterionic nature of α-aryl-N-methyl nitrones, devoid of pseudoradical or carbenoid centers. Utilization of CDFT indices enabled the prediction of global electronic flux from the strongly nucleophilic α-aryl-N-methyl nitrones to the varied electrophilic ethylene functionalities. Molecular docking and molecular dynamics simulations were conducted on the isoxazolidine derivatives against the EGFR receptor (PDB: 4ZAU). In silico assessment of the synthesized isoxazolidines involved molecular docking, wherein the compound with the highest docking score was subjected to molecular dynamics simulations. Compound 11a, out of the thirty isoxazolidine derivatives, displayed the most substantial binding energy, yielding a g score of -6.57 kcal/mol. These observations highlighted the functional role of amide NH2 and NO2 in the binding process with the target protein, influencing its activity. Furthermore, prediction of ADME drug-likeness properties was performed to identify a suitable candidate.

Tomato pomace (TP), an agricultural industrial waste product from the tomato processing industry, was valorized by being used as a rearing substrates for Tenebrio molitor (L.). This study evaluated bran-based diets with increasing tomato pomace (0%, 27%, 41% and 100%). Protein sources, as brewer’s spent grain and yeast, are used in TP27 and TP41 diets, respectively, to ensure equal protein content to control diet (TP0). Results showed larval survival, larval and pupal weight no different between diets; however, growth time significantly increases in TP100 compared at all diets. The feed conversion rate progressively increases from 2.7 to 4.3, respectively from TP0 to TP100. Conversely, Lycopene and β-Carotene increases in the larvae. Fatty acid composition improves by increasing polyunsaturated fatty acids (mainly -Linoleic acid). Although the best nutritional quality was obtained in T100, the TP41 is the optimal diet for balance between larval performance and qualitative improvement of larvae. Therefore, tomato pomace is suitable for the formulation of mealworm diets, even in high dosages when supplemented with sustainable protein sources.

New complexes of manganese(II) hexafluoroacetylacetonate [Mn(hfac)2] with 2-(1-R-3-pyrazol-4-yl)-4,4,5,5-tetramethyl-2-imidazoline-3-oxide-1-oxyl (R = CHF2, CH2CH2F, CH2CHF2 or CH2CF3) were synthesised and characterised structurally and magnetically. All complexes were prepared under similar conditions. Nonetheless, their crystal structures were considerably different. Depending on the structure of fluorinated alkyl substituent R, the complexation reaction led to complexes of three types: chain-polymeric complexes with the head-to-head or head-to-tail motif and complexes of molecular structure. All complexes show strong antiferromagnetic behaviour in a high-temperature region (150−300 K) and weak ferro- or antiferromagnetic exchange interactions at low temperatures. The stronger antiferromagnetic exchange, –101.7 ± 1.5 or –136 ± 10 cm–1, –82.3 ± 1.3 cm–1 and –87.4 ± 1.3 cm–1, was attributed to the magnetic interaction in three- or two-spin clusters: {&gt;N∸O–Mn2+–O∸N&lt;} or {&gt;N∸O–Mn2+}, respectively. The weaker antiferromagnetic interaction, –0.005, between three-spin clusters or ferromagnetic interactions, 0.18–0.81 cm–1, between two-spin clusters are realised through the pyrazole ring or intermolecular contacts.

Barley is an important crop grown on almost 49 Mha worldwide in 2021 and is particu-larly significant in Europe where powdery mildew is the most frequent disease on sus-ceptible varieties. The most suitable way for protecting crops is exploiting genetic re-sistance. However, the causal agent Blumeria hordei is an extremely adaptable pathogen. The aims of this research were to increase our knowledge of the rapidly changing path-ogen population and detect rare virulences. Random samples of the pathogen were ob-tained from the air by means of a mobile spore sampler. Spores were collected by driv-ing across the Czech Republic in 2019, 2021 and 2023 and 299 isolates were analyzed on 121 host varieties. No infection occurred on 35 differentials, rare virulence was recorded on 31 varieties and a higher virulence frequency was found on 55 differentials. A core set of differentials along with four additional varieties distinguish 295 pathotypes (Simple Index = 0.987) and virulence complexity of isolates varied from 4 to 19 with an average 10.39. The detection of new virulences, the increasing frequency of previously rare viru-lences and high pathotype diversity as well as high virulence complexity confirm that using nonspecific durable resistance is crucial for successfully breeding commercial va-rieties.

This study investigates the contribution of nano-alumina (nA: 1-3wt.% binder) to the performance of silica fume (SF-10%) blended mortar in ternary blended mortar. The fresh (workability, setting time) and hardened properties (compressive strength and thermal resistance (300 °C for 1 h)), were examined. Nano alumina (nA) contributed positively to the consistency of SF blended mortar such that similar workability could be achieved with OPC when 3% nA was added. The initial and final setting time of 180 and 220 mins were recorded in SF blended mortar and reduced by 18.4 and 21.8%, respectively by adding 3%nA. The optimum mixture that contained 10%SF and 2%nA had 3-d and 28-d compressive strengths of 28 and 43.2 MPa. In the absence of nA, this reduced by 14.3% and 29.4% while it reduced by 25.2% and 16.7%, respectively in OPC mortar. The main products characterizing SF-nA ternary blended binder with dense microstructural density were nepheline and tobermorite. Besides, it is more susceptible to carbonation despite its superior performance in thermal resistance when compared to SF blended and OPC mortars.

Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. This study investigated the molecular evaluation of a new mango cultivar ‘Azeem Chaunsa’ using a set of the most effective 50 hyper-variable polymorphic SSR markers. Highly specific DNA fingerprints were identified in the genome of this mango cultivar, ‘Azeem Chaunsa’ compared with three standard cultivars such as Sindhri, Samar Bahisht (S.B) Chaunsa and Sufaid Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. An agglomerative hierarchical clustering method was used to construct dendrogram based on the ‘Unweighted Pair- Group Method with Arithmetic Mean’ (UPGMA). The genetic similarity coefficients were recorded between the mangos cultivars ranged from 0.49 to 0.67. Cultivar identification (CID) evaluates association among standard cultivars and Azeem Chaunsa and further concludes significant variations. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future mango breeding programmes in the context of climate change.

Dietary habits, including meal frequency, meal timing, and skipping meals, have been extensively studied due to their association with the development of non-communicable diseases (NCDs). This study describes dietary habits, meal timing, meal frequency, skipping meals, and late-night eating in Kuwaiti adults. The Kuwait National Nutrition Surveillance System data was utilized to reach the objectives of this study. The findings reveal that approximately 50% of the adults in Kuwait eat after 10 p.m., 29% skip breakfast, and 9.8% skip dinner. Furthermore, adults in Kuwait consume 4.4 meals per day on average. Women skip breakfast more often and have extended night fasting than men (p&lt;0.001). Married adults skip breakfast and dinner less than unmarried adults (p&lt;0.001). In conclusion, this descriptive study provides valuable insights into the dietary habits of Kuwaiti adults, emphasizing the importance of further investigating the association between meal timing, meal frequency, and the prevalence of NCDs in Kuwait.

The Korean water deer (WD), the dominant wildlife species in South Korea, is classified as vul-nerable on the IUCN Red List. Beside their several unique characteristics, they have a lower in-cidence of tick bites compared to other Cervidae species, particularly roe deer (RD). In natural environments, ticks exhibit questing behavior by waiting on grasses to climb onto host's hair coat. They use sensory organs to detect signals such as body temperature and chemicals from the host's skin, then move to preferred feeding location. Therefore, we conducted a comparative analysis of the skin tissue and hair features of both species to compare the factors leading to lower incidence of tick bites in WD. Notably, WD had significantly larger blood vessels, sebaceous glands, and sweat glands which maintain the barrier functions of the skin (p≤0.004), irregular scale surfaces in hair cuticles, and stiff and 2.83-times thicker primary hair diameter (p<0.001). Each parameters made the ticks difficult to move onto the epidermis of WD. To our knowledge, this is the first report which is focused on the comparative analysis for skin and hair feature in WD and RD. We suggest that these differences may attribute to evade tick bites in WD.

The recently identified Mulberry Mosaic Dwarf-associated Virus (MMDaV), associated with mosaic dwarf symptoms in Chinese mulberry leaves, is a newly discovered member of the Geminiviridae family. The MMDaV genome, a single or twin circular single-stranded DNA molecule measuring approximately 2.5-3.0 kb, encodes five proteins and two hypothetical proteins, including a coat protein (CP) and movement protein (MP). The co-evolutionary dynamics between viral and host codon usage significantly impact viral survival, fitness, immune evasion, and evolutionary pathways. This study applied bioinformatic analyses to examine the codon usage bias in thirty MMDaV genomes collected from mulberry leaves in four distinct Chinese provinces. We aimed to understand the drivers of preferred synonymous codon usage. The Effective Number of Codons (ENC) analysis revealed significant regional variations among MMDaV isolates, allowing their classification into two main categories: the southern China HNZX strain and the eastern China HDZX strain. The codon preference analysis displayed a viral preference for using A/U as the terminal base, indicating a bias towards A/U over G/C. Using a combination of position-specific base composition, ENC-Plot, RP2-Plot, Neutral plot, and correspondence analysis, we found that mutational pressure and natural selection substantially influence codon usage and drive MMDaV evolution. Our findings shed light on the complex interplay between MMDaV and its mulberry host and offer crucial insights into the virus's adaptive and evolutionary mechanisms.

We studied Ni2FeSi, Co2FeSi and Co2MnSi -based full Heusler alloy glass-coated microwires with the same geometric aspect ratio ρ ≈ 0.50 ± 0.01 prepared using Taylor-Ulitovsky method. The fabrication of X2YZ; (X = Co &amp; Ni, Y = Fe &amp; Mn and Z = Si) based glass coated microwires with fixed aspect ratio is a quite challenging due to the different samples preparation conditions. The XRD analysis shows nanocrystalline microstructure for all the samples. Space group Fm3¯m (FCC) with disordered B2 and A2-types for Ni2FeSi and Co2FeSi and ordered L21-type for Co2MnSi are observed. The change in the positions of Ni, Co and Mn, Fe in X2YSi resulted in a variation in the lattice cell parameters and the average grain size of the sample. Room temperature magnetic behavior shows a dramatic change depending on the chemical composition, where Ni2FeSi-MWs shows the highest coercivity (Hc) compared to Co2FeSi-MWS and Co2MnSi-MWs. The Hc –value of Ni2FeSi-MWs is 16 times higher than that of Co2MnSi-MWs and 3 times higher than that of Co2FeSi-MWS. Meanwhile, the highest reduced remanence is reported for Co2FeSi-MWS (Mr =0.92), , being about 0.33 and 0.22 for Ni2FeSi-MWs and Co2MnSi-MWs, respectively. From the analysis of the temperature dependence of the magnetic properties (Hc and Mr) of X2YZ-MWs we deduced that Hc shows a stable tendency for Co2MnSi-MWs and Co2FeSi-MWs, meanwhile two flipped points are observed for Ni2FeSi-MWs where the behavior of Hc changes with temperature. For Mr monotonic increase by decreasing the temperature is observed for Co2FeSi-MWs and Ni2FeSi-MWs and roughly stable for Co2MnSi-MWs. The thermomagnetic curves at low magnetic field show irreversible magnetic behavior for Co2MnSi-MWs and Co2FeSi-MWs and regular ferromagnetic behavior for Ni2FeSi-MWs. The current result illustrates the ability to tailor the structure and magnetic behavior of X2YZ-MWs at a fixed internal stresses, i.e., with fixed aspect ratio. Additionally, a different behavior was revealed in X2YZ-MWs depending on the degree of ordering and elements distribution. The tunability of magnetic properties of X2YZ-MWs makes them suitable for sensing applications.

Recently, e-commerce companies have been adopting and continuously enhancing personalized product recommendation systems, and there is active research in this field within academia. However, personalized product recommendations in offline retail stores have not yielded significant outcomes thus far. Especially for small-format offline retail businesses like convenience stores, where customer information might be limited, providing personalized product recommendations poses even greater challenges. To address this issue, this study aimed to find a solution by shifting the perspective on recommendation methods and altering the target of recommendations in existing personalized recommendation models. In this study, recommending products that customers need in an offline store was defined as suggesting products that should be introduced and displayed within the store. In other words, the recommendation focus shifted from individuals to the stores themselves. This recommendation system proposes products that individual stores have not yet introduced but are anticipated to be purchased by customers among the products managed by the headquarters. Building upon this, we devised a store-based product recommendation system. The widely used user-based collaborative filtering model, a common technique in existing recommendation systems, was adapted into a store-based collaborative filtering model. Furthermore, various rules and logic pertinent to store operations and business considerations for convenience stores were integrated to implement this store product recommendation system. The accuracy and effectiveness of the system were demonstrated through its application in actual convenience stores. Results from the pilot implementation of the system showed that 88% of the newly recommended products in individual stores were sold based on one week of sales data, and the sales revenue was 1.75 times higher than the average sales revenue of those products across the entire company. Survey results on business owners' satisfaction yielded a score of 4.2 out of 5, indicating a high level of contentment. Additional observed effects included the expansion of product range and reduction in order lead times. However, 12% of the total recommended SKUs did not sell within one week, and 34% of the SKUs did not meet the overall average sales quantity. This research holds significance in extending the scope of personalized recommendation studies from primarily online platforms to offline retail businesses like convenience stores. It provides tangible methodologies and outcomes that can be implemented in real-world settings through the construction and validation of an actual system. The study also suggests avenues for future research to address some of the identified limitations.

Purpose: School-age children with autism spectrum conditions (ASC) often experience difficulties in speech-in-noise (SiN) perception, leading to increased listening effort that impacts their well-being and academic performance. This study aimed to investigate the SiN processing challenges faced by Mandarin-speaking children with ASC and its impact on their listening effort. Methods: Participants completed sentence recognition tests in both quiet and noisy conditions, with a steady-state noise masker presented at 0 dB signal-to-noise ratio in the noisy condition. We compared recognition accuracy and task-evoked pupil responses from 23 Mandarin-speaking children with ASC to 19 age-matched neurotypical (NT) counterparts to gauge their behavioral performance and listening effort during these auditory tasks. Results: The ASC group demonstrated notably decreased accuracy in noise compared to their NT peers, suggesting poorer SiN perception. Pupillometric data further revealed significantly larger peak dilations in the ASC group than in the NT group under comparable conditions. Importantly, the ASC group's peak dilation in quiet mirrored the NT group's in noise. However, the ASC group exhibited shorter peak latencies and reduced mean dilations than the NT group in similar conditions. Such patterns indicate the ASC group might initially experience a heightened cognitive load but utilize fewer cognitive resources as the task continued, indicating an atypical allocation of cognitive resources and a potential tendency towards relatively superficial and automated auditory processing. Conclusion: Our findings highlight the unique SiN processing challenges children with ASC face, underscoring the importance of a nuanced, individual-centric approach for interventions and support.

Recanalization poses challenge in coil embolization for cerebral aneurysms. Establishing predictive models for post-embolization recanalization is important for clinical decision-making. However, conventional statistical and machine learning (ML) models may overlook critical parameters during the initial selection process. In this study, we automated the identification of significant hemodynamic parameters using a PointNet-based deep neural network (DNN), leveraging their inherent 3D features. Further feature analysis was conducted utilizing saliency mapping, an explainable artificial intelligence (XAI) technique. The study encompassed the analysis of velocity, pressure, and wall shear stress (WSS) in both pre- and post-coiling models derived from computational fluid dynamic (CFD) simulations for 59 aneurysms. Velocity was identified as the most pivotal parameter, supported by the lowest P-value from statistical analysis and the highest area under the curves (AUROC)/precision-recall curves (AUPRC) values from DNN model. Moreover, visual XAI analysis revealed robust injection flow zones with notable impingement points in pre-coiling models, as well as pronounced interplay between flow dynamics and the coiling plane were important 3D features in identifying the recanalized aneurysms. The combination of DNN and XAI was found to be an accurate and explainable approach not only at predicting post-embolization recanalization but also at discovering unknown features in the future.

The hybridization of conventional thermal power plants by incorporation of renewable energy systems has witnessed widespread adoption in recent years. This trend aims not only to mitigate carbon emissions but also to enhance the overall efficiency and performance of these power generation facilities. However, calculating the performance of such intricate systems using fundamental thermodynamic equations proves to be both laborious and time-intensive. Nevertheless, possessing accurate and real-time insights into their performance is of utmost significance to ensure optimal plant operation, facilitate decision-making, and streamline power production planning. In this paper, we delve into the application of machine learning techniques, particularly hybrid methodologies, to predict the performance of power plants. Specifically, we employ three approaches: the Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS optimized via Particle Swarm Optimization (ANFIS-PSO), and the ANFIS optimized through Genetic Algorithm (ANFIS-GA). These techniques are alternatively applied to a complex hybrid thermal power plant, namely an Integrated Solar Combined Cycle Power Plant (ISCCPP). This ISCCPP comprises a steam turbine section, a gas turbine section, and a concentrated solar power system utilizing troughs as collectors. The energy transfer fluid, in conjunction with exhaust from the gas turbine section, heats water within a vessel or steam generator, producing steam to propel the steam turbine's rotor. Electricity generation is facilitated by both gas and steam turbines, which are coupled to a generator. The findings of this study underscore the accuracy and appropriateness of ANFIS-based models in evaluating and predicting the performance of intricate hybrid power plants. The ANFIS model exhibited an impressive overall coefficient of correlation of 0.9991. Notably, the integration of evolutionary algorithms (PSO and GA) into the ANFIS framework elevated model performance, yielding correlation coefficients of 0.9994 for ANFIS-PSO and 0.9997 for ANFIS-GA. It is noteworthy that ANFIS-GA demonstrated superior predictive capability. The modeling framework developed in this research offers valuable support to designers, energy managers, and decision-makers. It provides a robust and dependable tool to assess the performance of hybrid thermal power plants, which are poised for a global surge in numbers amid the ongoing energy transition.

There is a substantial lack of data relating to the hygrothermal traits of existing buildings and building materials. Moisture analysis in building envelopes is 1D (one-dimensional), and 2D and 3D effects and feedback can be neglected. Many European standards treat a moisture percentage in building envelopes as surface and interstitial moisture condensation, such as BS EN ISO 10211, BS EN ISO 13788, BS EN ISO 15148, and BS EN 15026. In this manuscript, there was a tendency to capture a relative quantity of superficial moisture, by metering spots on the inner and outer surface of wall lining systems with a moisture meter. The metering specimens were the buildings with different envelopes: a wooden hut-house, a masonry building and a building partially sheeted in stone. The referent heights on wall linings, for taking the moisture data were specified as 50 cm for a wooden and masonry building and 80 cm for a stone-sheeted building, from the ground. The obtained numeric results were palpable with no regard to the current state of the weather outside. The listed conclusions highlight the significance of a well-tailored building envelope, and its dependence on weather, junctions, gaskets, appropriate materials, etc.

Lucid dreaming is a dream in which one is aware that they are dreaming while dreaming as well as being able to influence the dream. It is utilized in scientific research to explore dreaming, in clinical context to treat nightmares, and in private settings to have fun, solve problems, and to train various skills. In this paper, based on an interview with a lucid dreamer, a fascinating, yet hardly described way to use lucid dreaming in sports and martial arts is presented. The dreamer used his lucid dreams to explore new movements and new possibilities in martial arts. For the interview, the guide from Schädlich and Erlacher [1] was used. The interviewee’s lucid dream experience is compared to interviews of other lucid dreamers and their experience and to contemporary research on lucid dreams. While the potential of lucid dreaming is explored, the interviewee also mentions the possible shortcomings of lucid dreaming.

Chenopodium quinoa Willd (quinoa), a member of the Amaranthaceae family, is an allotetraploid annual plant, endemic to South America. The plant of C. quinoa presents significant ecological plasticity with exceptional adaptability to several environmental stresses, including salinity. The resilience of quinoa to several abiotic stresses, as well as its nutritional attributes have led to significant shifts in quinoa cultivation worldwide over the past century. This work first defines germination sensu stricto in quinoa where the breakage of the pericarp and the testa is followed by endosperm rupture (ER). Transcriptomic changes in early seed germination stages lead to unstable expression levels in commonly used reference genes that are typically stable in vegetative tissues. Noteworthy, no suitable reference genes have been previously identified specifically for quinoa seed germination under salt stress conditions. This work aims to identify these genes as a prerequisite step for normalizing qPCR data. To this end, germinating seeds from UDEC2 and UDEC4 accessions, with different tolerance to salt, have been analyzed under conditions of absence (0 mM NaCl) and in the presence (250 mM NaCl) of sodium chloride. Based on relevant literature, six candidate reference genes: Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Monensin sensitivity1 (MON1), Polypyrimidine tract-binding protein (PTBP), Actin-7 (ACT7), Ubiquitin-conjugating enzyme (UBC), and 18S ribosomal RNA (18S), were selected and assessed for stability using the RefFinder Tool encompassing the statistical algorithms geNorm, NormFinder, BestKeeper, and ΔCt in the evaluation. The data presented supports the suitability of CqACT7 and CqUBC as reference genes for normalizing gene expression during seed germination under salinity stress. These recommended reference genes can be valuable tools for consistent qPCR studies in quinoa seeds.

In the theoretical treatment of crystallization it is commonly assumed that relaxation processes of the liquid proceed fast as compared to crystal nucleation and growth processes. Actually, it is supposed that the liquid is located always in the metastable state corresponding to the current values of pressure and temperature. However, near and below the glass transition temperature, Tg, this condition is commonly not fulfilled. In such cases, in the treatment of crystallization, deviations of the state of the liquid from the respective metastable equilibrium state have to be accounted for in determining the kinetic coefficients governing the crystallization kinetics, the thermodynamic driving force of crystallization, and the surface tension of the aggregates of the newly evolving crystal phase including the surface tension of critical clusters affecting considerably the crystal nucleation rate. These factors may considerably influence the course of the overall crystallization process. A theoretical analysis of the resulting effects is given in the present paper by numerical solutions of the J(ohnson)–M(ehl)–A(vrami)–K(olmogorov)–equation employed as the tool to model the overall crystallization kinetics and by analytical estimates of the crystallization peak temperatures in dependence on cooling and heating rates. The results are shown to be in good agreement with experimental data. Possible extensions of the theory to be explored in future analysis are anticipated.

Background and Objective: There is a paucity of literature comparing unilateral instrumented transforaminal lumbar interbody fusion (UITLIF) with bilateral instrumented TLIF (BITLIF) regarding radiological alignment, including the coronal balance, even though UITLIF might have asymmetric characteristics in the coronal plane. This retrospective study aimed to compare the clinical and long-term radiological outcomes of 1-level UITLIF and BITLIF in lumbar degenerative diseases (LDD). Materials and Methods: Patients who underwent 1-level UITLIF with two rectangular polyetheretherketone (PEEK) cages or BITLIF with ≥ 5 years of follow-up at a single hospital were included. We compared the clinical and radiological outcomes between the UITLIF and BITLIF. Results: In total, 63 and 111 patients who underwent UITLIF and BITLIF, respectively, were enrolled. The median follow-up was 85.55 months (range: 60–130). The UITLIF group had a significantly shorter operation time (185.0 [170.0–210.0] vs. 225.0 [200.0–265.0], p &lt; 0.001) and lower estimated blood loss (300.0 [250.0–500.0] vs. 550.0 [400.0–800.0], p &lt; 0.001) than BITLIF group. Regarding the clinical outcomes, there were no significant differences in the intermittent claudication score (p = 0.495) and Kirkaldy–Willis criteria (p = 0.707) at 1 year postoperatively. The interval changes of the local coronal Cobb angle at the index level, L1-S1 lordotic angle, and coronal off-balance from the immediate postoperative radiograph to the last follow-up were not significantly different (p = 0.687, p = 0.701, and p = 0.367, respectively). Conclusion: UITLIF with two rectangular PEEK cages is a viable option for providing comparable clinical outcomes and radiological longevity to BITLIF in 1-level LDD. In addition, UITLIF has advantages over BITLIF in terms of operative time and blood loss.

This research examines the fire resistance of geopolymer composites (GCs), formulated using alka-li-activated metakaolin and aluminum powder. The production method involves spray-coating carbon steel plates with fresh GCs, followed by a 28-day curing period at room temperature. Sub-sequently, fire performance and aging tests are conducted to evaluate fire resistance. The study investigates GC properties, including apparent density, bending strength, compression strength, thermal conductivity, porosity, and production cost. Morphological changes before and after fire and aging tests are analyzed using scanning electron microscopy (SEM). Results demonstrate GC foams' outstanding thermal insulation, providing up to 75 minutes of fire resistance with a 6 mm coating, reducing temperatures by 300 °C compared to uncoated steel. GCs exhibit a density of 670 kg/m³, thermal conductivity of 0.166 W/m·K, 68% porosity, and cost efficiency at 250 dollars per cubic meter. This study underscores the potential of foamed geopolymer coatings for effective and economical surface protection.

The current deformation and stable state of slopes with historical shatter signs is a concern for engineering construction. Suspected landslide scarps were discovered at the rear edge of the slope of the Genie in the Sichuan-Tibet transportation corridor during a field investigation. In order to qualitatively determine the current status of the surface deformation of this slope, this paper uses high-resolution optical remote sensing, airborne LiDAR and InSAR technologies for comprehensive analysis. The interpretation of high-resolution optical and airborne LiDAR data revealed that the rear edge of the slope exhibits three levels of scarps. However, no deformation was detected with the D-InSAR analysis of ALOS-1 radar images from 2007 to 2008 or with the Stacking-InSAR and SBAS-InSAR processing of Sentinel-1A radar images from 2017 to 2020. A geological model of the slope was established in combination with field investigation stipulating that the slope is composed of steep anti-dip layered dolomite limestone and that the scarps at the rear edge of the slope were caused by historical shallow toppling. Further research is recommended to determine the extent of toppling deformation and evaluate the slope stability under the disturbance of tunnel excavation.