The paper presents a proposal for an in-house mathematical model of a liquid flat-plate solar collector. The proposed model is a one-dimensional distributed parameter model enabling simulations of the collector operation under arbitrarily variable boundary conditions. The model is based on the solution of energy balance equations for all components of the collector. The formulated differential equations are solved iteratively using an implicit difference scheme. In order to obtain a stable numerical solution, it is necessary to use appropriate steps of the time and spatial division. These were found by comparing the results obtained from the model with the results of the analytical solution available in the literature for the transient state, which constitutes the novelty of the present study. The accuracy of the results obtained from the model was verified experimentally by comparing the measured and the calculated history of the fluid temperature at the outlet of the collector. The calculation of the collector time constant is proposed in the paper as an example of the model practical application. The results of the time constant calculation were compared with the values obtained experimentally on the test stand. This is another novelty of the presented research. The analysed collector instantaneous efficiency was then calculated for selected outdoor conditions. The presented mathematical model can also be used to verify the correctness of the collector operation. Comparing, on an ongoing basis, the measured and the calculated values of the fluid temperature at the collector outlet, conclusions can be drawn about the process of solar glass fouling or glycol gelling. The model's simplicity and the low computational demands enable such comparisons in an online mode.

Measurement uncertainty is typically expressed in terms of a symmetric interval , where denotes the measurement result and the expanded uncertainty. However, in the case of heteroscedasticity, symmetric uncertainty intervals can be misleading. In this paper, a different approach for the calculation of uncertainty intervals is introduced. This approach is applicable when a validation study has been conducted with samples with known concentrations. It will be shown how, under certain circumstances, asymmetric uncertainty intervals arise quite naturally and lead to more reliable uncertainty intervals.

MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of Flight) is a type of mass spectrometry (MS) that has been widely implemented for the rapid identification of microorganisms over the last decade. The accuracy and flexibility of this method has encouraged researchers to implement the analysis of protein spectra obtained by MALDI-TOF for the discrimination of close-related species and bacterial typing. In this study, a standardized methodology based on the detection of species-specific protein peaks from the spectra obtained with MALDI-TOF is described. The methodology was applied to a collection of Cryptococcus spp. (n=70) previously characterized by Amplified Fragment Length Polymorphism (AFLP) and sequencing of the ITS1-5.8S-ITS2 region. An expanded ad-hoc database was also built for their discrimination with MALDI-TOF. This approach did not allow the discrimination of the interspecies hybrids. However, the performance of peak analysis with the application of the PLS-DA and SVM algorithms in a two-step analysis allowed 96.95% and 96.55% correct discrimination of C. neoformans from the interspecies hybrids, respectively. Besides, PCA analysis prior to SVM provided 98.45% correct discrimination of the 3 analyzed species in a one-step analysis. The method is cost-efficient, rapid and user-friendly. The procedure can also be automatized for an optimized implementation in the laboratory routine.

Abstract Background: Premature babies have a greater risk for having health issues after being discharged from the hospital whilst the mother ability to provide premature baby care still has many issues as well. Interventions are needed to be given to mothers at home to improve the ability of mothers to care their premature babies. Methods: Search for articles used the bolean operator of “or” and “and” with the keywords used were “preterm or premature”, “intervention or program”, and “mother and home”. Data based used were Sciencedirect, Ebscohost, PubMed, SAGE, Proquest and Scopus with inclusion criteria using full text in English from 2018 to 2021. There were 428 articles obtained, the articles were then screened by reading the main focus of articles with paying attention to the topic and the suitability of article content and we obtained 13 suitable articles. Results: The interventions at home carried out for mothers and premature babies were divided into two namely the follow-up interventions from the hospital and the interventions carried out at the patient's home. Seven articles about research of interventions that were as a combination from hospital intervention with follow-up hospital intervention plus five full interventions at the patient's home. Interventions were provided through home visits (12 articles) and by telephone (1 article). The results of the article analysis resulted in 4 main themes of intervention for mothers and premature babies, they were health education, counceling, support, and care for premature babies. Conclusion: Quality care is essential for the best health, growth and development of premature babies. Interventions need to be carried out by health workers to ensure the readiness and ability of mothers to care for their babies. Maternal readiness and abilities can be improved by providing health education, counseling, support and care for premature babies.

This study analyses the case study of a deconstruction project called the ‘Whole House Reuse’ (WHR) which aimed, firstly, to harvest materials from a residential house, secondly, to produce new products using the recovered materials, and thirdly, to organize exhibition for the local public to promote awareness on resource conservation and sustainable deconstruction practices. The study applies characterization of recovered materials through deconstruction. In addition to the material recovery, the study assesses the embodied energy saving and greenhouse gas emission abatement of the deconstruction project. Around twelve tonnes of various construction materials were harvested through a systematic deconstruction approach, most which would otherwise be disposed to landfill in the traditional demolition approach. The study estimates that the recovered materials could potentially save around 502,158MJ of embodied energy and prevent carbon emission of around 27,029kg (CO2e). Deconstruction could eventually contribute to New Zealand’s national emission reduction targets. In addition, the project successfully engages local communities and designers to produce 400 new products using the recovered materials and exhibited to the local people. The study concludes that there is a huge prospect in regard to resource recovery, emission reduction, employment and small business opportunities using deconstruction of the old house. The socio-cultural importance of the WHR project is definitely immense; however, the greater benefits of such projects are often ignored and remain unreported to wider audiences as most of the external and environmental costs have not been considered in the traditional linear economy. It is acknowledged that under a favourable market condition and with appropriate support from local communities and authorities, deconstruction could contribute significantly to resource conservation and environmental protection despite its requirement of labour intensive efforts.

This article explores the results of a study on the improvement of the swiftlet house business with the goal of making appropriate legal measures for it. Area surveys, focus groups, and in-depth semi-structured interviews were among the data collection methods used. Swiftlet house entrepreneurs; central and local government officials; and citizens surrounding swiftlet houses significantly contributed to the research. Currently, the swiftlet house business is still illegal in Thailand because swiftlets are considered protected wildlife – protected by the Wildlife Preservation and Protection Act B. E. 2562 (2019). Additionally, it is not permitted to collect, damage, or occupy swiftlet nests without appropriate legal authority to do so. Moreover, there is still no legislation that specifically applies to the swiftlet house business. This study can guide the Thai Government and local governments to develop appropriate laws to govern the swiftlet house industry in Thailand.

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing, and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented as well.

Elovanoids (ELV) are novel lipid mediators synthesized from very long-chain (VLC) omega-3 (n-3) polyunsaturated fatty acids (PUFA), particularly docosahexaenoic acid (DHA) or eicosa-pentaenoic acid (EPA), by the elongase enzyme ELOVL4. ELV have been shown to play a funda-mental role in maintaining brain and retina function, neuroprotection, maintaining the skin's permeability barrier, and sperm function, among other important cellular processes. Furthermore, the methyl ester or sodium salt of ELV-N32 and ELV-N34 have been found to be efficient in re-duced infarct volumes, promoting cell survival and decreasing the alteration of the neurovascular unit in a model of ischemia due to occlusion of the middle cerebral artery. Their bioactivity in-cludes enhancing of anti-apoptotic and pro-survival protein expression combined with the downregulation of pro-apoptotic proteins. House dust mite (HDM) is the most prevalent indoor allergen, and HDM exposure is frequently the cause of allergic respiratory disease, including aller-gic rhinitis and allergic asthma in HDM sensitized individuals. In our study, human nasal epithe-lial cells (HNEpC) were used as an in vitro model for allergy. The cells were challenged with HDM (mixture of Dermatophagoides farinae and D. pteronyssinus extract), with or without treat-ment with ELV-34. Phosphate-buffered saline (PBS) (vehicle) and ELV-34 (500 nM) alone were used as the control. Our findings show that ELV-34 promotes cell viability and reduces cytotoxi-city upon HDM sensitization of HNEpC. ELV-34 treatment significantly reduces the levels of IL-6, IL-1β, IL-8, VEGF, ICAM1, CXCL1 and CCL2, restored the IL-10 level and diminishes the induc-tion of the transcription of inflammatory and senescence genes in HNEpC. Our data also shows that HDM triggered the expression of several key genes in human nasal epithelial cells, including autophagy, unfolded protein response (UPR), Matrix metalloproteinases (MMPs), senescence and inflammation markers. Together, our data reveal a novel pro-homeostatic and cell-protective li-pid-signaling mechanism in nasal epithelial cells that envision novel potential therapeutic targets for the treatment of allergies.

Fires in houses are inevitable and they cause loss of life and major repair costs for the damage structure and contents. There is a clear need to prevent its ignition and spread to adjacent areas. This article presents the steps taken, namely: contacts, data collection, tests, analysis and conclusions regarding the accident resulting from the outbreak and spread of a fire, on December 25, 2020, in a traditional Portuguese house in Arganil, Portugal. The owners and the court requested to carry out an expert opinion by a person with specialized technical-scientific knowledge, which led to this work as an expert. the work consists of carrying out observations and data analysis. Then, the observed and analysed data were laboratory tested in order to consistently identify characteristics that lead to the ignition and propagation of the fire. This work identified construction problems, materials used and heat sources that are responsible for the accident. The conclusions may be used to avoid future incidents or accidents with houses of same construction type.

Mechanical ventilation systems used in houses are designed to reduce carbon dioxide emissions while minimizing the energy loss resulting from ventilation. However, increase in indoor fine particulate (PM2.5) concentration because of external PM2.5, influx through the ventilation system poses a problem. In this study, we analyzed the changes in indoor PM2.5 concentrations via dis-tinguishing between cases of high and low outdoor PM2.5 concentrations, considering the effi-ciency of filters used in residential mechanical ventilation systems. When using minimum effi-ciency reporting value (MERV) 10 filters in the ventilation system, the outdoor PM2.5 concentra-tion was 5 μg/m³; the indoor PM2.5 concentration became 73% after 60 min compared to the ini-tial. When the outdoor PM2.5 concentration was 30–40 μg/m³, the indoor PM2.5 concentration reached 91%. However, when MERV 13 filters were used, the indoor PM2.5 concentration con-sistently dropped to 73–76% regardless of the outdoor PM2.5 concentration. Furthermore, by comparing the established equation with the mass-balance model, the error was confirmed to be within 5%, indicating good fit. This allows the prediction of indoor PM2.5 under various condi-tions when using mechanical ventilation systems, enabling the formulation of strategies to maintain indoor PM2.5 as recommended by the World Health Organization.

After industrialization and the baby boom, many houses have been left vacant in many cities worldwide due to changes in the economy, socie-ty, and urban composition. The increase in vacant houses causes social problems, like the collapse of village communities, damage to urban aes-thetics, risk of crime due to vacant houses, and decrease in the value of real estate. Accordingly, policy attempts and studies to reduce and utilize vacant houses are in progress in various countries. In South Korea, the ratio of vacant houses was 6.4% of all houses as of 2021, and in Jeolla-buk-do, it was 11.6%, which is higher than the national average. Jeollabuk-do conducted a fact-finding survey on countermeasures against va-cant houses; 17,732 vacant houses (2.4%) were surveyed. The urbanization, population, and terrain of Jeollabuk-do, consisting of 14 cities and counties, were considered. The ratios, types, grades, and spatial autocorrelations of vacant houses were analyzed after classification into city (fo-cus, small, and medium) and county (plains and mountains) areas. There were significant differences in the averages of the ratios, grades, and spatial autocorrelations between city and county areas. Therefore, policy establishment for vacant house management and countermeasures re-quires consideration of the areas and types of vacant houses.Keywords: : vacant house; spatial autocorrelation; fact-finding survey

Analysing the human body by direct observation can lead to misinterpretation of underlying trends, whereas in vitro organ models facilitate their understanding. Likewise, in vitro organ models serve as valuable tools for assessing the toxicity of compounds. However, none of the existing models had the features we considered critical for toxicity assessment, so we developed an in vitro liver model for toxicity assessment. We used four different types of primary liver cells: Hepatic sinusoidal endothelial cells, hepatic stellate cells, Kupffer cells and hepatocytes. We cultured them in different combinations of composition and volume of cell medium, hepatocyte proportion of total cells, and addition of extracellular matrix. We added rifampicin, ibuprofen and 5-fluorouracil to this model and observed the microanatomy and physiology changes for a week with preclinical and clinical instruments. Among the different model configurations, we selected the feature combination of the in vitro model that had similar biomarker values to those measured by the clinical instruments used in clinical diagnostics. When we exposed the selected model configuration to rifampicin, ibuprofen and 5-fluorouracil, the viability of Kupffer cells and liver sinusoidal endothelial cells was significantly lower than in the untreated samples. In contrast, we observed negligible viability of hepatocytes compared to the untreated samples. We have built an in vitro liver model that resembles the liver microenvironment and we have analysed it with clinical instrumentation to facilitate the data translation. In this sense, we have established that Kupffer and LSEC cells are suitable candidates for the search for clinical diagnostic markers of liver function.

The Oxford English Dictionary includes 17 definitions for the word “model” as a noun and other 11 as a verb. Therefore, context is necessary to understand the meaning of the word model. For in-stance, “model railways” refer to replicas of railways and trains at a smaller scale and a “model student” refers to an exemplar individual. In some cases, a specific context, like cancer research, may not be sufficient to provide one specific meaning of a model. Even if the context is narrowed, specifically to the research related to the tumour microenvironment, a “model” can be understood in a wide variety of ways, from an animal model, to a mathematical expression. This paper presents a review of the different “models” of the tumour microenvironment grouped by the different def-initions of the word into four categories: model organisms, in vitro models, mathematical models, and computational models. Then, the frequency of different meanings of the word “model” related to the tumour microenvironment is measured from the number of entries in the MEDLINE database of the United States National Library of Medicine at the National Institutes of Health. The frequency of the main components of the microenvironment and the organ-related cancers modelled are also assessed quantitatively with specific keywords. Whilst animal models, in particular xenografts and mouse models are the most common used “models”, the number of entries have been slowly de-creasing. Mathematical models, prognostic and risk models follow in frequency and these have been growing in use.

The World Anti-Doping Agency has prohibited gene doping in the context of progress in gene therapy. There is a risk that the artificial regulation of genes using plasmids could be applied for gene doping. However, no gold standard method to detect this has been established. Here, we aimed to develop a method to detect multiple transgene fragments as proof of gene doping. First, gene delivery model mice as a mimic of gene doping were created by injecting firefly luciferase plasmid with polyethylenimine (PEI) into the abdominal cavity. The results confirmed successful establishment of the model, with sufficient luminescence upon in vivo imaging. Next, multiple transgene fragments in the model were detected in plasma cell-free (cf)DNA, blood-cell-fraction DNA, and stool DNA using the TaqMan-qPCR assay, with the highest levels in plasma cfDNA. Using just a single drop of whole blood from the model, we also attempted long-term detection. The results showed that multiple transgene fragments were detected until 11 days. These findings indicate that the combination of plasma cfDNA or just one drop of whole blood with TaqMan-qPCR assay is feasible to detect plasmid-PEI-based gene doping. Our findings could accelerate the development of methods for detecting gene doping in humans.

Carotenoids are common and diverse organic compounds with various functional roles in ani-mals. Except for certain aphids, mites, and gall midges, all animals acquire necessary carotenoids only through their diet. The House fly (Musca domestica) is a cosmopolitan pest insect that populates diverse habitats. Its larvae feed on organic substrates that may vary in carotenoid composition according to their specific content. We hypothesized that the carotenoid composition in the adult House fly’s body would reflect its composition in the larval feed. We reared house fly larvae on substrates that differed in carotenoid composition and characterized the carotenoid composition of the emerging adults. Our results indicate that the carotenoid composition of adult House flies is related to the carotenoid composition in its natal substrate, but does not directly reflect it. We suggest that these findings may be developed to identify sources of House fly in-festations. We also recommend that care should be taken when considering the rearing substrates of House fly larvae used for animal feed.

The built environment sector’s growing impact on climate change is becoming increasingly important due to its share in energy consumption and greenhouse gas emissions. Global efforts have been undertaken to design and develop residential dwellings that aim towards zero energy and carbon emission, but there remains a multitude of obstructions to efficient construction processes. This study is focused on the gaps and barriers that have emerged during the pre-construction phase of a low-environmental-impact Passive House in Fayetteville, Arkansas. The technical, management, regulatory, and supply chain obstacles to the construction of a new three-story residential Passive House are documented to engage knowledge transformation in the design and construction of sustainable buildings of interest to developers and property owners. Primary data are collected by direct observation as well as open-ended interviews and secondary data collected through a literature review to understand the barriers and gaps faced by different key actors during the pre-construction phase in different regions. This local study highlighted the lack of interest, knowledge, and experience in sustainable building design among professionals having a significant influence on the project goals and timeline and was mentioned by participants as a common barrier as well as the inconsistency and inadequacy of regulatory framework of existing building codes to implement sustainable building design. These barriers along with other identified barriers are discussed and recommendations to overcome these barriers are provided.

The study of energy sources has been an awareness of the modern world due to constraints on the current energy worldwide supply chain. The complexity of the theme as well as the consciousness of finite sources also the need of saving energy has become a priority. Although many papers have moved in this direction there is no record of papers studying the variables in a house heating system, which represents the highest energy consumption in many cold countries. This paper explores the energy-saving theme by studying the main variables present in houses’ heating systems in the winter season in cold countries like Canada, Russia, Norway, Iceland, Finland, etc. By using a novel combination of numerical thermal simulation by COMSOLTM and statistical analysis by MiniTabTM , it was possible to design an efficient thermal distribution in a house with the variables of the system by determining their significance and interaction qualitatively.

The New Zealand housing sector is experiencing rapid growth that boosts the national economy but also results in the loss of valuable resources. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: ARIMA and multiple linear regression analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

There is a growing need for novel in vitro corneal models to replace animal-based ex vivo test in drug permeability studies. In this study we demonstrate a corneal mimetic that models the stromal and epithelial compartments of human cornea. Human corneal epithelial cells (HCE-T) were grown on top of a self-supporting porcine collagen-based hydrogel. Cross sections of the multilayers were characterized by histological staining and immunocytochemistry of zonula occludens-1 protein (ZO-1) and occludin. Furthermore, water content and elastic properties of the synthetized collagen type I-based hydrogels were measured. The apparent permeability coefficient (Papp) values of a representative set of ophthalmic drugs were measured and correlated to rabbit cornea Papp values found in the literature. Multilayered structure of HCE-T cells and expression of ZO-1 and occludin in full thickness of multilayer were observed. The hydrogel-based corneal model exhibited excellent correlation to rabbit corneal permeability (r=0.96), whereas insert-grown HCE-T multilayer was more permeable and the correlation to the rabbit corneal permeability was lower (r=0.89). The hydrogel-based human corneal model predicts the rabbit corneal permeability more reliably in comparison to HCE-T cells grown in inserts. This in vitro human corneal model can be successfully employed for drug permeability tests whilst avoiding ethical issues and reducing costs.

This work presents the possibility of using a synthetic membrane for pretracing mucosal penetration studies. The permeability of two types of membranes, porcine oral mucosa and a synthetic Nuclepore membrane, to water was compared. Moreover, the water permeability of membranes modified with waterproofing formulations was measured to study their ability to protect against the penetration of viruses, toxins, etc. A very good correlation was obtained between the transmucosal water loss (TMWL) values of the artificial membrane and the mucosa. These results support the possible use of this synthetic membrane in the screening of the water permeability of formulations. In addition, studies of the permeation of different actives, drugs and biocides through the two membranes were carried out, and these results were compared with their skin permeation data. The synthetic membrane does not seem to discern between compounds in terms of permeability, which could be due to the lack of lipids in the composition of this synthetic membrane. Therefore, Nuclepore alone cannot be used as a model for the release of actives. Additionally, the permeation of caffeine through intact or modified membranes incorporating waterproofing formulations was also studied. In this case, similar permeation profiles through the synthetic membrane and mucosa were found. The results from these assays should lend support to the use of this synthetic membrane when screening formulations to be applied in oral penetration studies.

Preeclampsia is a multifactorial cardiovascular disorder diagnosed after 20 weeks of gestation that is the leading cause of death for both mothers and babies in pregnancy. The pathophysiology remains poorly understood due to variability and unpredictability of disease manifestation when studied in animal models. After preeclampsia, both mothers and offspring have a higher risk of cardiovascular disease (CVD) including myocardial infarction or heart attack and heart failure (HF). Myocardial infarction is an acute myocardial damage that can be treated through reperfusion, however, that therapeutic approach leads to ischemic/reperfusion injury (IRI) often leading to HF. In this review, we compared the current in vivo, in vitro and ex vivo model systems used to study preeclampsia, IRI and HF. Future studies aiming at evaluating CVD in preeclampsia patients could benefit from novel models that better mimic the complex scenario described in this article.

In this paper, we propose a new mathematical model based on the association between susceptible and recovered individual, where the association between susceptible and recovered individual is disturbed by white noise. This model is based on demographic changes and is used for long term behavior. We study the stability of equilibria of the deterministic model and prove the conditions for the extinction of diseases. Then, we investigate and obtain the critical condition of the stochastic epidemic model for the extinction and the permanence in mean of the disease with the white noise. To verify our results, we present some numerical simulations for real data related to disease.

In politics and society, organic farming is widely seen as the ideal way to address the many challenges facing agriculture and food security. In order to examine the extent to which this view is realistic, the impact of organic and conventional farming is compared on the basis of relevant criteria such as land requirements, greenhouse gas emissions, biodiversity, food quality, production and environmental costs, reduced meat consumption, the need for agricultural imports and the global expansion of arable land. Land is considered to be a central factor. Such a comprehensive analysis is necessary to assess the impact of different influencing factors and to provide important suggestions for targeted decision making. Although organic farming has a positive impact on land use in many ways, it quickly reaches its limits. The low yields and high production costs resulting from the limited choice of means of production make organic farming an unsuitable model for the future in a world with limited arable land, a high and growing demand for food, and low incomes for large sections of the population. It can, however, provide significant impetus and contribute important technological knowledge for the further development of agriculture as a whole to meet the complex objectives of sustainability, greenhouse gas mitigation, biodiversity and global food security by incorporating all available technologies. Based on this, a model for responsible, sustainable intensive agriculture is outlined and proposals for an eco-social framework to support this model are put forward.

This study investigates the relationship between housing prices and vacancy rates in Hong Kong, offering insights distinct from previous cross-sectional analyses. Addressing limitations in data availability and methodological approaches, the study examines annual data spanning multiple housing size categories to uncover nuanced dynamics in the housing market. Two major contributions emerge: firstly, the analysis reveals the price elasticity of vacancy, elucidating how housing prices respond to changes in vacancy rates over time. Secondly, by considering housing vacancy changes as outcomes of the interactions between supply and demand, the study challenges the conventional independence assumption between these variables. The results support the hypothesis that housing vacancies exert a negative impact on housing prices, holding other factors constant. These findings have significant implications for policymakers, urban planners, and real estate investors, providing valuable insights for crafting targeted interventions and informing investment decisions.

In view of the problem that the hot and cold loads of mushroom houses are affected by multiple factors such as environment, mushrooms, and equipment, which are difficult to accurately model, this paper proposes a short-term load prediction method based on empirical wavelet transform (EWT) and mixed autoregressive integrated moving average (ARIMA) and convolutional bi-directional short- and long-term attention mechanism (CNN-BiLSTM-Attention). The method first uses the Boruta algorithm to filter the input characteristics, and then uses the EWT method to decompose the mushroom house load data into 4 modal components. Then the Lempel-Ziv method is introduced to divide the modal components into two categories of high and low frequencies, and the CNN-BiLSTM-Attention and ARIMA prediction models are constructed separately. Finally, the two types of prediction results are superimposed and reconstructed to obtain the final load prediction value. The test results show that the Boruta algorithm can effectively filter out the characteristics of key influencing factors. Compared with the Spearman and Pearson correlation coefficient methods, the mean absolute error (MAE) of the prediction results is reduced by 14.72% and 3.75%, respectively; compared with the ensemble empirical mode decomposition (EEMD) method, the EWT method can increase the decomposition and reconstruction error by 103 orders of magnitude, which can effectively improve the prediction accuracy of the model; compared with the individual neural network model, the prediction effect of the model proposed in this paper has obvious advantages, and the MAE, root mean square error (RMSE) and mean absolute percentage error (MAPE) of the prediction results are reduced respectively. 31.06%, 26.52% and 39.27%.

Minimum housing standards aim to safeguard housing rights and enhance residential conditions. Governments develop housing policies, including provision, preservation, and support for welfare programs, guided by the status of households below these standards. Growing nations commonly utilize this approach to decrease the proportion of households not meeting these criteria. In South Korea, the ratio of households below these standards was 4.5% in 2021, down from 16.6% in 2006, as indicated by the initial Korea Housing Survey. However, this downward trend has stalled over the past decade. With the 2004 and 2011 revisions, the standards have been effective for 12 years, yet no longer mirror current housing realities due to ongoing improvements. This study aimed to propose enhancements to Korea’s minimum housing standards. Through analyzing laws, prior research, present household statuses, international cases, and expert insights, recommendations emerged. Categorizing households by size, we developed precise standards covering area, facility, and location aspects. These new standards led to an 8.4% non-compliance rate in 2021. This research’s findings anticipate aiding the revision of minimum housing standards, formulating pragmatic policies for enhancing residential conditions in line with present situations.

With widespread resistance to a limited number of insecticides available for medical and veterinary pests, new insecticides and insecticide synergists are desperately needed in this market space. We assessed the topical toxicity of carvone, menthone, and fenchone compared to permethrin and methomyl against the yellow fever mosquito, Aedes aegypti, and the house fly, Musca domestica. We also evaluated the synergistic potential of the monoterpenoids with permethrin and methomyl. Additionally, we assessed the acetylcholinesterase inhibitory potential of each monoterpenoid compared to methomyl. While all three monoterpenoids performed relatively poorly as topical insecticides (LD50 > 4000 ng/mg on M. domestica; > 6000 ng/mg on Ae. aegypti), they synergized both permethrin and methomyl as well as or better than piperonyl butoxide (PBO). Carvone and menthone yielded synergistic co-toxicity factors (23 and 29, respectively), which were each higher than PBO at 24 h. Acetylcholinesterase inhibition did not appear to explain the toxic or synergistic effects of the three monoterpenoids with IC50 values greater than 1 mM for all, compared to the 2.5 and 1.7 µM for methomyl on Aedes aegypti and Musca domestica, respectively. This study provides valuable monoterpenoid toxicity and synergism data on two pestiferous insects and highlights potential for these chemistries in future pest control formulations.

Chlamydia trachomatis (CT) is an obligate intracellular bacterial pathogen known to cause trachoma, sexually transmitted infections, and reactive arthritis. The more serious sequelae of these diseases, blindness from trachoma and pelvic inflammatory disease from chlamydial STD are immunopathological responses to chronic infections. With the abundance of dendritic cells in CT infection sites and their central importance in immune regulation, the susceptibility of dendritic cells to CT infection was investigated in vitro. CT (serovar F) was grown and extracted from HeLa 229 cells for infection of human dendritic cells (DCs). Human DCs were generated from peripheral blood mononuclear cells in the presence of GM-CSF and IL-4. Infected DCs were harvested at 0, 4, 24, and 48 h after infection and immunostained. Results from fluorescence microscopy showed that DC can be infected and can support the growth of CT in vitro. Intracellular elementary and reticulate bodies of CT were detected, and reticulate bodies were shown to multiply over the 48 h-cycle in DC. At 48 h, intracellular elementary bodies were detected in some DCs. These results may provide new insights into the possible participation of DC in sustaining chronic or latent infection, or even dissemination of CT infection to other sites.

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

To address the deficiency of existing relation extraction models in effectively extracting relational triplets pertaining to railway traffic knowledge in Tibet, this paper constructs a Tibet Railway Traffic text dataset and provides an enhanced relation extraction model. The proposed model incorporates subject feature enhancement and relational attention mechanisms. It leverages a pre-trained model as the embedding layer to obtain vector representations of text. Subsequently, the subject is extracted and its semantic information is augmented using an LSTM neural network. Furthermore, during object extraction, the multi-head attention mechanism enables the model to prioritize relations associated with the aforementioned features. Finally, objects are extracted based on the subjects and relations. The proposed method has been comprehensively evaluated on multiple datasets, including the Tibet Railway Traffic text dataset and two public datasets. The results on the Tibet dataset achieves an F1-score of 93.3\%, surpassing the baseline model CasRel by 0.8\%, indicating a superior applicability of the proposed model. On the other hand, the model achieves F1-scores of 91.1\% and 92.6\% on two public datasets, NYT and WebNLG, respectively, outperforming the baseline CasRel by 1.5\% and 0.8\%, which highlights the good generalization ability of the proposed model.

This paper, we examined the technology to maximize the use of renewable energy. The passive ventilation system is expected to reduce the energy consumption of the fan power and the maintenance burden. In addition, the wall-mounted solar air heater can supply thermal energy without using any energy at all. Therefore, we propose a "passive ventilation system with a solar air heater" that combines a passive ventilation system with solar air heater to preheat the air supply and reduce the ventilation load. To evaluate the solar air heater performance in a real environment, we developed a simulation for calculating the heat collection capacity of the solar air heater, and then implemented the system in a real building for verification. Based on the measurement results, the effects of heating load reduction and prediction methods are presented.

In the search for new 2D materials beyond graphene with similar exemplary properties Stanene the new graphene relative was successfully synthesized and characterized in 2016 [14]. This new material which consists of atomically thin tin (Sn) atoms arranged in a hexagonal lattice has shown great promise in gas sensing applications in its pristine, doped and functionalized forms as evidenced by the recent research outputs following its discovery. Researchers have discovered that with its exotic properties it is highly efficient in the detection of the environmentally harmful gases like SO2, NO2, CO2, NH3 and can serve as a multifunctional gas sensor. In this focused and up-to-date review we aim to group the literature on first principles studies of stanene regards to its application for gas sensing and critically examine the success/failures of its multifunctional gas sensing properties as compared to graphene. We systematically present and discusses how structural deformations, defects and doping effect the gas sensing performance. Despite the impressive progress in the field of gas sensing with stanene shown by first principles calculations, many challenges in large scale synthesis, device fabrication and commercialization need to be addressed. The current review can help understand the current status and drawbacks of stanene and identify future directions in this field.

Vitamin D3 deficiency is a global phenomenon, which can be coped with supplementation and food fortification. However, vitamin D3 bioaccessibility may depend on factors, such as matrix composition and interactions throughout the gastrointestinal tract. This research focused on the effect of different matrices on vitamin D3 content during digestion, and the effect of pH on its bioaccessibility. The INFOGEST protocol was employed to simulate digestion. Three different types of commercial supplements, two foods naturally rich in vitamin D3, and three fortified foods were investigated. High-Performance Liquid Chromatography was used to determine the vitamin D3 initial content in supplements and foods, as well as after each digestion stage. Results indicated that foods exhibited higher bioaccessibility indices compared to supplements, and a higher percentage retention at the end of the gastric phase. The pH study revealed a positive correlation between increased gastric pH and the corresponding content of vitamin D3. Interestingly, exposing the matrix to low pH during the gastric phase resulted in an increased intestinal content of D3. Vitamin D3 is more bioaccessible from foods than supplements, and its bioaccessibility is susceptible to changes in gastric pH. Fasting conditions (i.e. gastric pH=1) enhances vitamin’s bioaccessibility.

The poor success rate of preclinical drugs which target the nervous system is related to the highly complex nature of brain physiology and pathophysiology. For in vitro drug screening in this field, the two-dimensional (2D) approach - where cells are incubated in a monolayer - is not physiologically relevant. In contrast, in vivo rodent models are very low throughput and expensive. As such, improved, well-characterised three dimensional (3D) in vitro models should be employed to bridge the gap between 2D in vitro primary screening and rodent models by incorporating aspects of the in vivo brain environment. These key features include the extracellular matrix (ECM) and a multidimensional relationship of supporting cells. In this study, a neural progenitor cell line was differentiated into the main types of cells found in brain, including neurons and astrocytes. This model was designed in a 3D extracellular matrix replacement in a minimalised manner. Different culture formats using multi-well plates were explored and a high-throughput cellular imaging platform was applied. Next, we applied this model to assess neural toxicity of a newly synthesised dual-specificity tyrosine-regulated kinase 1 (DYRK1) inhibitor derived from natural compounds, which is structurally related to a natural DYRK1A inhibitor harmine, K04179. Chemical studies have already shown that K04179 has higher specificity to DYRK1A compared with previously reported DYRK1 inhibitors, such as INDY. We have produced the first report of the biological effects of this new compound on the new 3D minimalised mid-brain model with quantification of both neuronal and astrocyte populations in tandem, revealing differential toxic effects of DYRK1 inhibitor compounds K04179 and INDY on neurons and glia.

Free-of-charge HCV screening in some key populations and in 1969–1989 birth cohorts have been funded in Italy as the first step to diagnosing individuals unaware of their infection. The aim of this study is to use available in-hospital routine screening data to understand the inpatients HCV screening in a region of North Italy. A retrospective search of in-hospital patients tested for HCV-antibody (HCV-Ab) from January 2017 to the end of December 2022, was conducted according to age categories (older than 76 years, birth group 1947-1968; birth group1969-1989 and two other categories with patients younger than 33 years) using the TriNetX network. Of 42,805 in-hospital patients tested, 1,297 (3.03%) resulted HCV-Ab positive. The proportion decreased from 2017 to 2022 (from 2.03% to 0.36%) years). The higher prevalence of HCV-Ab was in patients older than 76 years (5.3%) while, the lowest was in the younger birth cohort (2000-2022, 0.16%). Of 1,297 patients found HCV-Ab positive, only 198 (15.3%) were tested for the presence of HCV RNA. Although the birth cohort 1969-1989 had a lower seroprevalence (1.5%), they represented the most affected age group with 44.4% of HCV RNA positivity. The in-hospital HCV screening including birth cohort 1947-1989 could be a valuable option respect to the screening for birth group 1969-1989 in the general population. Since a high proportion of patients were not tested for HCV RNA during hospitalization, reflex testing promptly ascertaining an active infection could facilitate linkage to care to stop the burden of HCV.

This study aims to evaluate the climate-change response of greening persistently vacant houses and barren sites in deteriorated high-density residential areas in old downtown metropolitan areas. The current status of building demolition sites in Ami-dong and Chojang-dong, Busan Metropolitan City, was examined. In this area, of the 340 vacant houses from 2017, 246 (72.35%) remained persistently vacant till 2020. In 2020, 213 barren sites were neglected after building demolition. Amongst these sites, 177 (83.10%) were paved with concrete. Persistently vacant houses and barren sites were afforested, and the climate-change response was quantified in terms of flood reduction and CO2 mitigation in four scenarios (current, concrete, ground cover plants, and trees). Runoff analysis was performed using the Korea low-impact development model (K-LIDM) to assess flood mitigation. The tree scenario showed average runoff mitigations of 1.71%, 2.38%, and 3.06% in the long-term, 30-year, and 2-year rainfall scenarios, respectively. Additionally, 3058 deciduous broadleaf trees may be planted in the study area to promote CO2 mitigation. Thus, an additional annual carbon fixation of 62,123.78 kg CO2 may be expected. The greening of vacant houses and demolished sites was effective in all aspects of the climate-change response, and tree-based greening exhibited the most significant effect.

Anal stenosis, which develops as a result of aggressive excisional hemorrhoidectomy, especially with the stoutly use of advanced technologies (LigaSure, Ultrasonic Dissector, Laser, etc.), has become common, causing significant deterioration in the patient's quality of life. Although non-surgical treatment is effective for mild anal stenosis, surgical reconstruction is unavoidable for moderate to severe anal stenosis that causes distressing, severe anal pain, and inability to defecate. The problem in anal stenosis, unlike anal fissure, is that the skin does not stretch as a result of chronic fibrosis due to surgery. Therefore, the application of lateral internal sphincterotomy does not provide satisfactory results in the treatment of anal stenosis. Surgical treatment methods are based on the use of flaps of different shapes and sizes to reconstruct the anal caliber and flexibility. This article aims to review the functional results, postoperative care, and complications of these methods.

We continue in this paper to illustrate the implications of the Dual Model of Liquids (DML) by deriving the expression for the isochoric specific heat as function of the collective degrees of freedom available at a given temperature and analyzing its dependence on temperature. Two main tasks will be accomplished. First, we show that the expression obtained for the isochoric specific heat in the DML is in line with the experimental results. Second, the expression will be compared with the analogous one obtained in another theoretical dual model of the liquid state, the Phonon Theory of Liquid Thermodynamics. This comparison will allow to get interesting insights about the number of collective degrees of freedom available in a liquid and on the value of the isobaric thermal expansion coefficient, two quantities that are related to each other in this framework.

Software-In-The-Loop (SITL) simulation tools have been extensively used in development of safety-critical software. Utilizing these tools substantially accelerates software development eliminating potential risks and resource costs of physical experiments. This paper investigates the effects of model specific parameters on the development and testing of custom module in PX4 SITL environment. Models of a fixed-wing unmanned aerial vehicle with vertical takeoff and landing capabilities and steerable sensor platform/gimbal are used as case study for this investigation. The effects of parameters of these aerial vehicle and sensor platform models are taken into consideration in the development of custom module that controls the dynamics of steerable sensor platform mounted on the vehicle model. The work also presents steps necessary to customize PX4 SITL and Gazebo simulation environment to incorporate parameters of the vehicle and sensor platform models in the development and testing process of custom module. Based on these instances, simulation results are obtained and discussed. The results show that reliability of PX4 SITL simulation framework is justified by proper customization and integration of PX4 SITL and Gazebo simulator.

Aggregation of the protein α-Synuclein (αSyn) is a hallmark of Parkinson's disease (PD), dementia with Lewy bodies (DLB) and multiple systems atrophy, and alleviating the extent of αSyn pathology is an attractive strategy against neurodegeneration. The engineered binding protein β-wrapin AS69 binds monomeric αSyn. AS69 reduces primary and secondary nucleation as well as fibril elongation in vitro. It also mitigates aSyn pathology in a mouse model based on intrastriatal injection of aSyn pre-formed fibrils (PFF). Since the PFF-based model does not represent all aspects of PD, we tested here whether AS69 can reduce neurodegeneration resulting from αSyn overexpression. Human A53T-αSyn was overexpressed in the mouse Substantia nigra (SN) by using recombinant adeno-associated viral vector (rAAV). AS69 was also expressed by rAAV transduction. Behavioral tests and immunofluorescence stainings were used as outcomes.Transduction with rAAV-αSyn resulted in αSyn pathology as reported by phospho-αSyn staining and caused degeneration of dopaminergic neurons in the SN. The co-expression of rAAV-AS69 did not reduce αSyn pathology or degeneration of dopaminergic neurons. We conclude that αSyn monomer binding by rAAV-AS69 was insufficient to protect from aSyn pathology resulting from αSyn overexpression.

This study investigates how students' well-being relates to sustainable development and education for sustainability at Prince Mohammad Bin Fahd University, Saudi Arabia. The authors endeavor to answer the question "How Does Students' Well-Being Relate to Sustainable Development Via Education for Sustainable Development?" and four sub-questions. Primary data were collected by semi-structured interviews exploring the viewpoints of twenty female and male students (n=26) aged between 18 and 26. The content analysis results have identified additional well-being and education for sustainability factors that influence sustainable education and, therefore, sustainable development. These antecedents include workload, transparency, grading criteria, fairness, belonging, work-life balance, mental health support, missing emotional intelligence factors, factors related to Education for Sustainable Development, such as instructors' role models, institutional commitment, leadership, and collaboration with government. In addition, the study developed a theoretical model for the relationship between antecedents for Education for Sustainable Development, Education for Sustainable Development, and Sustainable Development in the Saudi context. Finally, the study answers four research questions: What factors contribute to education for sustainable development? What are the antecedents of education for sustainable development? How do university educators contribute to sustainable education? How do the antecedents of education for sustainable development, education for sustainable development, and sustainable development relate?

This review article deals with the pathways of cellular and global molybdate distribution in plants, especially with a full overview for the model plant Arabidopsis thaliana. In its oxidized state as bioavailable molybdate, molybdenum can be absorbed from the environment. Especially in higher plants, molybdenum is indispensable as part of the molybdenum cofactor (Moco), which is responsible for functionality as a prosthetic group in a variety of essential enzymes like nitrate reductase and sulfite oxidase. Therefore, plants need mechanisms for molybdate import and transport within the organism, which is accomplished via high-affinity molybdate transporter (MOT) localized in different cells and membranes. Two different MOT-families were identified. Especially legumes like Glycine max or Medicago truncatula have an increased numbers of MOT1-family members for supplying their symbionts with molybdate for nitrogenase activity. In Arabidopsis thaliana especially, the complete way of molybdate through the plant is traceable. Not only the uptake from soil by MOT1.1 and its distribution to leaves, flowers and seeds by MOT2-family members was identified, but also inside the cell the transport trough the cytoplasm and the vacuolar storage mechanisms depending on glutathione were described. Finally, supplying the Moco biosynthesis complex by MOT1.2 and MOT2.1 was demonstrated.

Mutations in epidermal growth factor receptor (EGFR) occur in about 48% of Asian and 19% of Western patients with lung adenocarcinoma (LUAD), leading to its constitutive activation and subsequent uncontrolled cell proliferation. To counteract this, tyrosine kinase inhibitors (TKIs) have been developed, targeting EGFR activity. However, the emergence of metastases and resistance mutations often undermines the durability of the treatment response. Knowledge-based mechanistic models that replicate existing clinical trial outcomes, tailored to specific population characteristics, provide invaluable assistance in designing future clinical trials. These models are particularly effective in identifying optimal responders to specific treatments, thereby enhancing therapeutic efficacy. We have developed physiologically based pharmacokinetic (PBPK) models for gefitinib and osimertinib, representing two distinct generations of EGFR TKIs, to accurately simulate the drugs’ distribution within the primary tumor and metastatic sites following oral administration. These models were integrated with a pathophysiological mechanistic model of EGFR-mutant LUAD, enabling the representation of the effects of both gefitinib and osimertinib on EGFR activation-induced signaling pathways. This comprehensive model outputs detailed evolutions of the primary tumor and each metastatic site, facilitating the evaluation of patient progression in alignment with RECIST guidelines (version 1.1). Notably, the model encapsulates the heterogeneity within the tumor, through the representation of various subclones, each characterized by unique mutation profiles, thereby reflecting differential responses to treatment. Calibration of the model was achieved using publicly available data from the NEJ002 and FLAURA clinical trials. Rigorous visual predictive checks and statistical tests were employed to ensure the proper behavior of the model. The model adeptly replicated the time to progression observed in real clinical trials in EGFR-mutant LUAD patients receiving gefitinib or osimertinib as first-line therapy. In addition, the model was able to reproduce the results from a retrospective study comparing gefitinib and osimertinib, a study that was not used to inform the model. With a consistent virtual population as a reference, the combined model facilitated a comparative analysis of the efficacy of both treatments, thereby underscoring its utility in evaluating therapeutic strategies. The faithful replication of real-world data significantly enhances the credibility of our model, rendering it a vital investigational tool for deriving pertinent insights and informing treatment strategies, particularly in identifying optimal responders to various generations of EGFR TKIs. Following its consecutive prospective validations in the FLAURA2 and MARIPOSA trials, the model is poised to facilitate the generation of synthetic control arms in future clinical trials. This advancement promises a more nuanced analysis of covariate relationships, especially when comparing investigational treatments to established standards of care. Additionally, it potentially reduces the required patient cohort size in such trials, optimizing resource utilization.

An extension of the models used to generate fractal traffic flows is presented by means of the formulation of a model that considers the use of one-dimensional chaotic maps. Based on the disaggregation of the temporal series generated by the model, a valid explanation of behavior of the values of Hurst exponent is proposed and the feasibility of their control from the parameters of the proposed model is shown.

We compare Chiral Perturbation Theory (ChPT) and the Linear Sigma Model (LSM) as realizations of low energy QCD for light mesons in a chirally imbalanced medium. The relations between the low-energy constants of the Chiral Lagrangian and the corresponding constants of the Linear Sigma Model are established as well as the expressions for the decay constant of $\pi $-meson in the medium and for the mass of the $a_0$. In the large $N_c$ count taken from QCD the correspondence of ChPT and LSM is remarkably good and give a solid ground for search of chiral imbalance manifestation in pion physics. A possible experimental detection of chiral imbalance (and therefore a phase with Local Parity Breaking) is outlined in the charged pion decays inside the fireball.

The Model-View-Controller (MVC) architecture, a cornerstone of modern software engineering, offers a robust framework for developing dynamic user interfaces. This paper conducts a broad analysis of MVC’s deployment across various sectors, emphasizing its critical role in technological advancement and market integration. By examining implementation strategies in web development, mobile applications, and enterprise solutions, the study illustrates how MVC enhances application manageability, promotes efficient code reuse, and facilitates parallel development. The paper explores the adoption of MVC principles within major technologies such as Java, .NET, and JavaScript frameworks, underlining its widespread acceptance. Additionally, the analysis covers the preferential use of MVC frameworks within diverse market sectors including technology enterprises, educational institutions, e-commerce, and financial services, which leverage MVC for superior data management and user experience. Emerging trends such as the shift towards the Model-View-ViewModel (MVVM) architecture and the integration of MVC with artificial intelligence and machine learning technologies are also discussed. This comprehensive review not only reaffirms MVC’s enduring relevance but also its adaptive evolution in response to emerging technological demands and market needs.

Non-alcoholic fatty liver (NAFLD) is a metabolic disorder related with a chronic lipid accumulation within the hepatocytes. This disease is the most common liver disorder worldwide and it is estimated that is present in up to 25% of the world's population. However, the real prevalence of this disease and the associated disorders is unknown mainly because reliable and applicable diagnostic tools are lacking. It is known that the level of albumin, a pleiotropic protein synthetized by hepatocytes, is correlated with the correct function of the liver. The development of a complementary tool that allow the direct, sensitive, and label-free monitoring of albumin secretion in hepatocyte cell culture can provide insight about the mechanism and drugs action in NAFLD. With this aim, we have developed a simple integrated plasmonic biosensor based on gold nanogratings from periodic nanostructures present in commercial Blu-ray optical disc. This sensor allows the direct and label-free monitoring of albumin in a 2D fatty liver disease model under flow conditions using highly specific polyclonal antibody. This technology avoids both the amplification and blocking steps showing a limit of detection within pM range (≈ 0.39 ng/mL). Thanks to this technology, we identified the optimal fetal bovine serum (FBS) concentration to maximize the lipid accumulation within the cells. Moreover, we discovered that at third day from lipids challenge, the hepatocytes increased the amount of albumin secreted. These data demonstrate the ability of hepatocytes to respond to the lipid stimulation releasing more albumin. Further investigation needed to unveil the biological significance of that cell behaviour.

The classical Lotka-Volterra predator-prey model is globally stable and uniformly persistent. However, in real-life biosystems extinction of species due to stochastic effects is possible. In this paper, we consider the classical Lotka-Volterra predator-prey model under stochastic perturbations. For this model, using an analytical technique based on the direct Lyapunov method and a development of the ideas of R.Z. Khasminskii, we find the precise sufficient conditions for the stochastic extinction of one and both species and the precise necessary conditions for the stochastic system persistence. The stochastic extinction occurs via a process known as the stabilization by noise of the Khasminskii type, and, in order to establish the sufficient conditions for extinction, we found the conditions for the stabilization. The analytical results are illustrated by numerical simulations. {\bf Keywords:} stochastic perturbations, white noise, Ito's stochastic differential equation, the Lyapunov functions method, stability in probability, stabilization by noise, stochastic extinction, persistence.

Much remains to be understood for delayed ultraweak photon emission (UPE) from organism in association with oxidative burst following external perturbation, a phenomenon that has been experimented for over three decades. Delayed UPE often decays hyperbolically; yet, it is not uncommon to have delayed UPE that reveals first-order kinetic patterns characterized by single-exponential, double exponential, or multi-exponential changes. Some delayed UPEs also presented transient patterns that are characteristic of second-order responses. A soliton-based photon-storage model has addressed the hyperbolic decaying pattern of delayed UPE; however, there are questions outstanding regarding modeling other non-hyperbolic kinetics as well as the large range of temporal scales of delayed UPE that can vary from 8.5 microseconds to many hours. This work proposes an alternative, phenomenological model-framework for interpreting the various kinetic patterns of delayed UPE following stress. The delayed UPE is considered to be governed by two sequential phases: a stress-transfer phase that transforms the external stress to photo-genesis for emitting photons, and a photon-diffusion phase that transmits the photons emitted by the photo-genesis to the surface of organism for being detected as delayed UPE. Time-resolved photon diffusion analysis reveals that any delayed UPE in organism with a delay time >100ns cannot be addressed by the inherent temporal spread that realistic tissue scattering will cause. A slow stress-transfer phase is thus required to explain the delay time-scales of delayed UPE at a minimum of 8.5 µs as reported experimentally. The stress-transfer phase is hypothesized to carry the following types of responses: single or multiple 1st-order low-pass, single 2nd-order low-pass with various damping factors, and single 2nd-order band-pass with various damping factors. A single 1st–order low-pass response with a time-varying kinetic rate is also analyzed. The responses of these modeled pathways to bolus and step inputs demonstrate that a kinetic pattern other than the exact single-exponential one may have multiple causes.

The development of reliable predictive algorithm for house price as the housing market is a stand-out among the most involved regarding valuing the price and continues to fluctuate, is constantly a need for socio-economic advancement and welfare of citizen. In this paper, we develop machine learning algorithms for forecasting UK housing Price, and find an optimal algorithm that forecasts housing price accurately on the premises of the presence of many features or covariates. After applying correlation analysis to remove correlated variables in order to avoid multicollinearity, thereby increasing the statistical power, a novel method of using regression analysis to first of all understand and select statistically significant features for the various regions in England based on North South divide is adopted. These features are then used in the machine learning algorithm to further increase the statistical power of the algorithm, increase the level of accuracy for each of them and ultimately increase the predictive values for the algorithms. The model construction involves 3 stages: 1- correlation analysis to identify and remove correlated variables thereby avoiding multicollinearity and increasing the statistical power of the linear regression, 2 - using linear regression to determine variables that are statistically significant and 3 - building the machine learning algorithms based on the variables that are statistically significant from the linear regression. A comprehensive dataset of UK Paid housing Price from 2010 to 2019 was linked to a number of other datasets to generate a total 21 variables or features used for the models. Catboost, Gradient Boosting, Bagging, Random Forest, Extra Tree all achieved the excellent models performance result in all the regions considered. The comparison of the seven models showed that Extra Tree algorithm consistently achieved the best performance in term of level of accuracy in all the regions. K-Nearest Neighbours (KNN) is the only algorithm with less than 50% level of accuracy. Noticeably, the regions considered had varying or differing insignificant variables, implying that although many variables are common (statistically significant) to all the regions, there are regional differences and impact when modelling or predicting housing prices. This study validates the practicability of developing a machine learning methodology for the prediction of housing price. This research offers a reference for future house price prediction based on machine learning.

Large volume bone defect regeneration is complex and demands time to complete. Several regeneration phases with unique characteristics including immune responses follow, overlap, and interdepend on each other and, if successful, lead to the regeneration of the organ bone's form and function. However, during traumatic, infectious, or neoplastic clinical cases, the intrinsic bone regeneration capacity may exceed, and surgical intervention is indicated. Scaffold-guided bone regeneration (SGBR) has recently shown efficacy in preclinical and clinical studies. To investigate different SGBR strategies over periods of up to 3 years we have established a well characterized large segmental tibial bone defect ovine model, for which we have developed and optimized immunohistochemistry (IHC) protocols. We present an overview of the immunohistochemical characterization of different experimental groups in which all ovine segmental defects were treated with a bone grafting technique combined with a three-dimensionally printed medical-grade polycaprolactone-tricalcium phosphate (mPCL-TCP) scaffold. The qualitative data set is based on osteoimmunological findings gained from IHC analyses of over >350 sheep surgeries over the past two decades. Our systematic and standardized IHC protocols enabled us to gain further insight into the complex and long-drawn-out bone regeneration processes, which ultimately proved to be a critical element for successful translational research.

The relaxation process of lithium batteries caused by load variation is considered. It is shown that such processes have strong dependence on internal physical and chemical processes and battery technical conditions. Theoretical expressions of the relaxation process caused by a step-like load variation have been obtained for 1^st and 2^nd order equivalent electrical circuits. The experimental investigations show that the obtained models fit the real relaxation processes and the behavior of the identified parameters could be explained by specific features of physical and chemical processes within the lithium battery. It should be noted that the obtained results can be generalized for a different type of electrochemical power source. The proposed approach makes it possible to provide means for electrochemical power source characterization and diagnostic, the main advantages of which are good time localization of measurement procedures and inexpensive apparatus implementation.

The Double U-pipe ground heat exchanger, recognized for its straightforward process, cost-effectiveness, high heat exchange efficiency, and low thermal resistance, stands as the predominant ground heat exchanger type in today's shallow geothermal energy development and utilization. Recent years have seen significant research into the heat transfer influencing factors and heat exchange performance of Double U-pipe ground heat ex-changers via experimental testing methods. Yet, studies integrating numerical simulation with in-situ testing have been less frequent. Drawing on the cylindrical heat source model theory and the outcomes of regional in-situ thermal response tests, this paper develops a Double U-pipe ground heat transfer model by establishing physical, mathematical, and heat transfer geometric models. It assesses the impact of varying inlet temperatures, flow rates, and initial ground temperatures on heat exchange efficiency under heating conditions. The results validate the precision of the double U-pipe ground heat exchanger model based on in-situ testing. They show that enhancing the temperature differential between the inlet and initial temperatures, elevating the initial ground temperature, and moderately increasing the flow rate can boost the system's heat exchange efficiency.

Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: 3100 VABBs were retrospectively reviewed among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients’ features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate analysis. Finally, we developed a predictive multivariable model based on the features which were significantly associated with the univariate analysis outcome. Results: the upgrade rate to invasive carcinoma was 10.8 %. At univariate analysis, the risk of upgrade was significantly lower in the absence of post- biopsy residual lesion (p<0.001), age > 50 (p=0.029), and in presence of low-grade DCIS only in specimens with microcalcifications (p=0.002). According to the final multivariable model, the predicted probability of diagnostic underestimation for a patient with all the three favourable features selected at univariate analysis was 1% (95% CI: 0.3%-4%). Conclusions: An easy to use predictive model of radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.

The provision requirement of 10% openings of the total floor area stated in the Uniform Building by Law 1984 Malaysia has been practiced by designers for building plan submission approval. However, the effectiveness of thermal performance in landed residential buildings, despite the imposition by the by-law, has never been empirically measured and proven. Although terraced houses in Malaysia have dominated 40.9% of the total property transaction in 2019, such mass production with typical designs hardly provides its occupants with thermal comfort due to the static outdoor air condition and lack of external windows, where the conventional ventilation technique does not work well, even for houses with an air well system. Consequently, the occupants need to rely on mechanical cooling, which is a high energy-consuming component contributing to outdoor heat dissipation and therefore urban heat island effect. Thus, encouraging more effective natural ventilation to eliminate excessive heat from the indoor environment is critical. Since most of the research focuses on simulation modelling lacking sufficient empirical validation, this paper drawing on field measurement investigates natural ventilation performance in terraced housing with an air well system. More importantly, the key concern as to what extent the current air well system serving as a ventilator is effective to provide better thermal performance in the single storey terraced house is to be addressed. By adopting an existing single storey air welled terrace house, the existing indoor environmental conditions and thermal performance were monitored and measured using scientific equipment, namely HOBO U12 air temperature and air humidity, the HOBO U12 anemometer and the Delta Ohm HD32.3 Wet Bulb Globe Temperature meter for a six-month duration. The findings show that the air temperature of the air well ranged from 27.48°C to 30.92°C, while the mean relative humidity were from 72.67% to 79.25%. The mean air temperature for a test room (single sided ventilation room) ranged from 28.04°C to 30.92°C with a relative humidity of 70.16% to 76%. These empirical findings are of importance, offering novel policy insights and suggestions to potentially revising the existing building code standard and by laws; since the minimum provision of 10% openings has been revealed to be less effective to provide a desired thermal performance and comfort, mandatory compliance with, and the necessity for, the bylaw requirement should be revisited and further studied.

Background and Objective: Intimate relationships hold significant importance during emerging adulthood. This study aimed to investigate the critical determinants of perceived well-being in friendship relationships during emerging adulthood.Method: Using a quantitative approach, a sample of 726 undergraduate students from the Ferdowsi University of Mashhad were selected through convenience sampling. They completed the Interpersonal Behaviors Questionnaire (IBQ), the Compassionate and self-image goals scale (CSIGS), the Basic Need Satisfaction in Relationships Scale (BNS-RS), the Interpersonal Needs Questionnaire (INQ-10), Friendship Self-Regulation Questionnaire (SRQ-F), Interpersonal Behaviors Questionnaire-Self (IBQ-self), State Level Subjective Vitality Scale (SVS-SL), the Perceived Relationship Quality Component (PRQC), and the Basic Empathy Scale (BES). Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM).Results: The results indicated that the critical determinants in predicting perceived well-being in friendship relationships were, in order, goals in friendship relationships, friendship self-regulation, perceived support of basic psychological needs by friends, satisfied basic psychological needs, frustrated psychological needs, and supporting the basic psychological needs of friends.Conclusion: The findings demonstrate that self-determination theory (SDT) provides a coherent framework for explaining perceived well-being in friendships.

To both survive and develop continuously, enterprises must overcome many kinds of competition and challenges. Cultivating employees' active and sustainable organizational citizenship behavior is important for enterprises to successfully cope with turbulence and uncertain events during their development. In this study, we investigated the development level of and factors influencing employees' organizational citizenship behavior in current organizations. By using the Belief in a Just World Scale, Organizational Citizenship Behavior Scale, and Interpersonal Intelligence Scale, we investigated 230 employees from 15 different enterprises. The results showed that belief in a just world, interpersonal intelligence, and organizational citizenship behavior were significantly positively correlated. Interpersonal intelligence played a moderating role between belief in a just world and organizational citizenship behavior; the organizational citizenship behavior of individuals with high interpersonal intelligence increased with the strengthening of the belief in a just world, and this increase was larger than that experienced by individuals with low interpersonal intelligence. This meant that under a certain level of belief in a just world, a high level of interpersonal intelligence was more conducive to promoting employees' sustainable organizational citizenship behavior.

Circulating tumor cells (CTCs) in the peripheral blood are the precursors to distant metastasis but the underlying mechanisms are poorly understood. This study aims at understanding the molecular features within CTCs in relation to their metastatic potential. Using in vitro CTC models, in which breast cancer cell lines are cultured in non-adherent conditions simulating the microenvironment in the blood stream, we found that suspension culture resulted in resistance to TNF-related apoptosis inducing ligand (TRAIL)-mediated cell death. Such a resistance was directly correlated with a reduction in surface and total levels of DR5 protein. In the non-adherent state, cells underwent rapid autophagic flux characterized by an accumulation of autophagosome organelles. Notably, DR5 was translocated to autophagosomes and underwent lysosomal degradation. Our data suggest that CTCs may evade TNF cytokine mediated immune surveillance through downregulation of DR expression. The data warrants further studies in cancer patients to find the status of DRs and other molecular features within primary CTCs in relation to disease progression or chemoresistance.

Background &amp; Aim: Drug sustainability (DS) is a surrogate marker for treatment efficacy. We aimed to compare the DS of two main biologics used to treat moderate-to-severe ulcerative colitis (UC), infliximab (IFX) and vedolizumab (VDZ), in a real-world setting. Methods: We conducted a retrospective cohort study at a tertiary medical center in Israel. We included patients treated between Dec 1st, 2017, and May 1st, 2021, who were followed for up to 300 weeks. DS was defined as corticosteroid, surgical, and hospitalization-free treatment. Results: 217 patients with UC were included. VDZ had a significantly longer median DS of 265.6 weeks compared to IFX's 106.5 weeks (p=0.001) in treatment-naïve patients, even when adjusting for disease severity (HR 0.55 95 CI 0.3-0.98, p=0.042). In treatment-experienced patients, DS was comparable between IFX and VDZ (p=0.593). Conclusion: VDZ showed significantly longer DS in treatment-naïve patients with UC compared to IFX, also when adjusted for disease severity. There was no difference in DS between VDZ and IFX in treatment-experienced patients and patients switching from one drug to another. VDZ may be a suitable first-line treatment for biologic-naïve patients with moderate-to-severe UC.

Background: Cancer has been one of the most critical health problems during the past decades which require serious consideration, especially in developing countries. Methods: 80 parents of the children with different types of cancers were studied via both questionnaire and person-to-person interview after announcing their informed consent. Results: The highest delay in patients' initial referral was due to the following factors: lack of attention or ignoring the first symptoms, delay in referring to the physician, low economic status and even lack of family support for the patient. In addition, visiting several doctors after the initial diagnosis, uncertainty about the first proposed method, and high cost of treatment can be mentioned as the main causes of delays in the start of treatment. Conclusion: Education plays an important role in identifying the signs of cancer. In addition, proper relationship and cooperation between the health system and physicians as well as provision of adequate information to patients could lead to the long-term cooperation of these patients in continuing their treatment.

In this article, we analyse the determinants of Regulatory Quality-RQ for 193 countries in the period 2011-2020. We use a database from ESG-Environment Social Governance of the World Bank. We apply OLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that the variables that have the most positive impact on RQ, among others, are “GHG Net Emission”, “Mean Drought Index”, and “Heat Index”. We also found that the variables that have the most negative impact on RQ are among others “Renewable Energy Consumption”, “Voice and Accountability” and “Rule of Law”. Furthermore, we have applied the k-Means algorithm optimized with the Elbow Method and we find the presence of five clusters. In adjunct, we confront eight machine learning algorithms to predict the value of RQ and we found that the best predictor is Polynomial Regression. The predictive level of RQ for the analysed countries is expected to diminish of -1,29%. In the end, we present a network analysis with the Euclidean distance and we found the presence of a structure of seven networks using augmented data.

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This research focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It extended the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thai recruitment practices. The study explores the factors influencing users' intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literatures and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in Bangkok metropolitan area supplied comprehensive responses. The research reveals that several factors, including Perceived Value, Perceived Autonomy, Effort Expectancy, and Facilitating Conditions, significantly impact the intention to adopt AI for recruitment. While Social Influence and Trust in AI Technology do not have a direct influence on intention, Social Influence directly affects Perceived Value. Trust in AI Technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

Recently, several research groups have reported on anomalous enhancement of the self-field critical currents, Ic(sf,T), at low temperatures in superconductor/Dirac-cone material/superconductor (S/DCM/S) junctions. Some papers attributed the enhancement to the low-energy Andreev bound states arising from winding of the electronic wave function around DCM. In this paper, Ic(sf,T) in S/DCM/S junctions have been analyzed by two approaches: modified Ambegaokar-Baratoff and ballistic Titov-Beenakker models. It is shown that the ballistic model is an inadequate tool to analyze experimental data from S/DCM/S junctions. The primary mechanism for limiting superconducting current in S/DCM/S junctions is different from the conventional view that the latter is the maximum value within the order parameter phase variation. Thus, there is a need to develop a new model for self-field critical currents in S/DCM/S systems.

The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels as well as their orchestration and links are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof of concept study cases. Personalized simulations over the actual anatomy of a patient have been carried out. The hypermodel has also applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin based clinical decision support system and the core of future in silico trial platforms, although additional retrospective adaptation and validation is necessary.

In the rapidly evolving field of real estate economics, the prediction of house prices continues to be a complex challenge, intricately tied to a multitude of socio-economic factors. However, traditional predictive models have often overlooked the spatial interdependencies that play a vital role in shaping housing prices. This study applies Graph Neural Networks (GNNs) on Open Statistics Knowledge Graphs to model spatial dependencies and predict house prices across Scotland’s 2011 data zones. To this end, integrated statistical indicators are retrieved from the official Scottish Open Government Data portal. The three representative GNN algorithms employed - ChebNet, GCN, and GraphSAGE - demonstrate higher prediction accuracy than traditional models, including the tabular-based XGBoost and a simple Multi-Layer Perceptron (MLP). In addition, local and global explainability are employed to increase transparency and trust in the predictions made by the most accurate GNN - GraphSAGE. The global feature importance is determined by a logistic regression surrogate model while the local, region-level understanding of the GNN predictions is achieved through the use of GNNExplainer. Explainaibility results are compared with those from a previous work that applied the XGBoost machine learning algorithm and the SHapley Additive exPlanations (SHAP) explainability framework on the same dataset. Interestingly, both global surrogate model and the SHAP approach underscored the Comparative Illness Factor, a health indicator, and the ratio of detached dwellings as the most crucial features in the global explainability. In the case of local explanations, while both methods showed similar results, the GNN approach provided a richer, more comprehensive understanding of the predictions for two specific data zones.

Current article presents the study of psychological wellbeing of adolescents (n=168, age 15-17) gifted in math, humanities and sports and educated in advanced programs for gifted children. Theoretical framework of this study is eudemonic concept of psychological wellbeing by C. Ryff. Psychological wellbeing is measured with Ryff wellbeing scales in Russian adaptation by L.V. Zhukovskaya and E.G. Troshikhina. The study is aimed at understanding differences in psychological wellbeing of gifted teenagers connected to gender and type of giftedness. The results suggest that general wellbeing score did not differ for adolescents with different types of giftedness or of different genders. Separate components of psychological wellbeing, such as purpose in life and self-acceptance, are influenced by activity connected to the talent. Gender differences are subjected to age-specific trends of personal development in adolescence. Type of giftedness might reinforce these trends.

The temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of outside world. In line with this hypothesis, I present a mechanistic model of mutually connected processes that encode the inner space and time. The model is used to elaborate the binding mechanism between two sets of processes representing the inner space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between the binding strength and noise. The spectral entropy is used to characterize the noise effects on the systems of processes when the binding strength is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems have similar entropy values for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows to conclude that the binding mechanism is noise-resilient.

With Internet of Things (IoT) gaining presence throughout different industries a lot of new technologies have been introduced to support this undertaking. Implications on one such technology, wireless systems allowed for the use of different communication methods to achieve the goal of transferring data reliably, with more cost efficiency and over longer distances. Anywhere from a single house with only a few IoT devices such as a smart light bulb or a smart thermostat connected to the network, all the way to a complex system that can control power grids throughout countries, IoT has been becoming a necessity in everyday lives. This paper presents an overview of the devices, systems and wireless technologies used in different IoT architectures (Healthcare, Vehicular Networks, Mining, Learning, Energy, Smart Cities, Behaviors and Decision Making), their upbringings and challenges to this date and some foreseen in the future.

The urgency to address the adverse impacts of climate change on livelihoods and ecosystems has seen an increase in global driven initiatives. However, shifting vulnerabilities associated with land use resource based adaptation and maladaptive feedback loops they create have been given low attention. Policy discourses that frame adaptation as a local responsibility and bias towards reducing industrial Greenhouse gas (GHG) emissions at the expense of Agricultural emissions across scale are thought to account for the undesirable situation. This calls for a reflective policy framework and climate policy innovation. We provide counter arguments using Drivers, Pressure, State, Impact, Response (DPSIR) model and telecoupling principles to suggest use of resilience as an integrative lens in visualising the proposal. Using a case study on resource constrained smallholder dairy production systems, western Kenya, we analyse the critical issues in the context of decision making and environmental externalities. The effect of price risks on dairy cattle feeding strategies and ultimately carbon footprints and ecoefficiencies were examined through methane simulation and gross margin analysis (GM). The lowest ecoefficiency was associated with exclusively local coping strategies i.e. Maize Stover (Ms), while the highest ecoefficiency was observed in feeding strategies that utilise external resources and/or legume fodders. We conclude that management of externalities need to capture institutional, economic processes and incentive systems, as well as organizational and policy coherence to shape the interests and behaviour of individual land user. In particular, policy innovation should focus on price and market risks as critical factors that mediate actor decision making at implementation level as they impact GHG emissions which transcend individual decision boundaries.

Abstract: The objective of these studies was to determine the dependence of the distribution of the microwave field into a grain layer and the efficiency of energy transfer from the magnetron into the grain layer, via a waveguide, on the moisture content. The subject of the research was a semicircular waveguide with slot radiators that supply a microwave field to the grain surrounding the waveguide. The change in the directional diagram of the microwave field in the longitudinal direction of the waveguide was studied using CST Microwave Studio 2019 software. It was found that the change in the moisture content of the processed grain leads to a significant change in both the radiation and total efficiency values of the waveguide. For instance, the radiation efficiency of the waveguide decreases by 15.1% (from 68.729 dB to 58.294 dB) when the moisture content of the processed grain increases from 14% to 26%. The total radiation efficiency also decreases (from 11.27 dB to 21.7 dB). In this case, not only the value of the radiation efficiency but also the shape of its dependence on the magnetron radiation frequency change. Data were obtained on the change in the Q-factor for resonators in which grain layers are processed, depending on the variation in grain moisture content.

The numerous biological activities of phenothiazine and sulphonamide derivatives, especially their antibacterial qualities, have attracted so much interest. In this study, the synthesis and characterization of phenothiazine-3-sulphonamide derivatives and evaluation their antimicrobial activity against the following pathogenic microorganisms is reported. Two gram-positive bacteria; (Staphylococcus aureus, and Streptococcus pyogenes), two gram-negative bacteria; (Escherichia coli, and Salmonella typhi) as well as one fungus (Aspergillus fumigatus) were used while ciprofloxacin, gentamycin and ketoconazole served as standard drugs. The synthesis of the derivatives was achieved through a base catalyzed the reaction of 4-chloroaniline with 1-naphthylamine to form 1-(naphthalen-1-yl) benzene-1,4-diamine. This intermediate was then treated with sulphur and iodine to yield the phenothiazine derivative while subsequent treatment of the phenothiazine compound with sulphonyl chlorides gave the final products. The synthesized compounds were characterized via proton nuclear magnetic resonance (1HNMR), carbon-13 nuclear magnetic resonance (13C NMR) and Fourier-transform infrared (FTIR) spectroscopic techniques. The minimum inhibitory concentration (MIC) of each compound was then determined using the agar well diffusion method. To predict the binding energies and patterns of the synthesized compounds with target proteins of the above mentioned microorganisms, molecular docking simulations were run using Autodock Vina software (version 4.2). The spectra data of the compounds for FTIR, 1H NMR and 13C NMR (δ) spectral data were consistent with the assigned structures of the synthesized compounds. The binding energies (kcal/mol) for in silico antimicrobial studies were in the range -5.1 to -7.6 kcal/mol. The MIC values were in the range -3.5 to 1.0 mg/L. The results of the in vitro test revealed that the synthesized compounds exhibits promising antimicrobial activity, and showed excellent bactericidal and fungicidal activities. The results obtained showed that the synthesized compounds possess drug-like properties and are good starting materials for drug production.

Background: Redo mitral valve surgery is the standard of care for failed mitral bioprostheses or recurrence of mitral regurgitation after repair. Nonetheless, catheterbased valve-in-valve (ViV) or valve-in-ring (ViR)-procedures increasingly become viable alternatives in high risk subpopula-tions. Despite reported good initial results, only little is known about longer-term outcomes. The present series report long-term outcomes of transcatheter mitral ViV- and ViR-procedures. Methods: All consecutive patients (n=54) undergoing transcatheter mitral ViV- or ViR-procedures for failed bioprostheses or recurring regurgitation after mitral repair were retrospectively en-rolled in the time period between 2011 and 2021. The mean age was 76.5 ± 6.5 years, and 30 (55.6%) of the patients were male. The procedures were done using a commercially available balloon-expandable transcatheter heart valve. Clinical and echocardiographic follow-up data were obtained out of the hospital’s database and analyzed. Follow-up reached up to 9.9 years with a total of 164.3 patient-years. Results: A total 25 patients received a ViV- and 29 patients a ViR-procedure. Both groups were at high surgical risk with an STS-PROM of 5.9 ± 3.7 % in ViV- and 8.7 ± 9.0% in ViR-patients, respectively (p<0.01). The procedures itself were mainly unevent-ful with no intraoperative deaths and a low conversion rate (n=2/54; 3.7%). VARC-2 procedural success was low (ViV 20.0% and ViR 10.3%; p=0.45), which was either driven by high rates of transvalvular pressure gradients “>5mmHg” (ViV 92.0% and ViR 27.6%; p<0.01) or residual regurgitation “>trace” (ViV 28.0% and ViR 82.7%; p<0.01). ICU-stay was prolonged in both groups (ViV 3.8 ± 6.8 days and ViR 4.3 ± 6.3 days; p=0.96) with acceptable hospital stay (ViV 9.9 ± 5.9 days and ViR 13.5 ± 8.0 days; p=0.13). Despite 30-days mortality was acceptable (ViV 4.0% and ViR 6.9%; p=1.00), the mean posthospital survival time was disappointingly low (ViV 3.9 ± 2.6 years and ViR 2.3 ± 2.7 years; p<0.01). Overall survival I the entire group was 33.3%.Cardiac reasons for death were frequent in both groups (ViV 38.5% and ViR 52.2%). Cox-regression analysis identified ViR-procedures as a predictor of mortality (HR 2.36, CI 1.19 - 4.67, p=0.01). Conclusions: Despite acceptable immediate outcomes in this high-risk subpopulation, long-terms results are discouraging. Transvalvular pressure gradients as well as residual regurgitations remained drawbacks in this real-world population. The indication for catheterbased mitral ViV- or ViR-procedures thoughtfully must be made in consideration of conventional redo-surgery or conservative treatment.

In an effort to discover an effective and selective antitumour agent, synthesis and anti-cancer potential of 4-(pyridin-4-yl)-6-(thiophen-2-yl)pyrimidin-2(1H)-one (SK-25), which has been reported earlier by us with significant cytotoxicity towards MiaPaCa-2 malignant cells, with an IC₅₀ value of 1.95 μM and was found to instigate apoptosis. In the present study, the antitumour efficacy of SK-25 was investigated on Ehrlich ascites tumour (solid), Sarcoma 180 (solid) tumour and Ehrlich ascites carcinoma. The compound was found to inhibit tumour development by 94.71% in Ehrlich ascites carcinoma (EAC), 59.06% in Ehrlich tumour (ET, solid) and 45.68% in Sarcoma-180 (solid) at 30 mg/kg dose. Additionally, SK-25 was established to be non-toxic at a maximum tolerated dose of 1000 mg/kg in acute oral toxicity in Swiss-albino mice. Computer-based predictions also show that the compounds could have an interesting DMPK profile. The current study provides insight for further investigation of the antitumour potential of the molecule.

In this paper, we discuss major issues of mathematics teaching and learning in Nepal. The issues coming from theories such as social and radical constructivism suggest that teachers are not trained to use such approach in teaching mathematics, and there is a lack of teaching aids and materials and technological tools. The issues related to social aspects are gender issues, language issues, social justice issues, and issues related to the achievement gap. The cultural issues are related to the diversity of language and ethnicity. The issues related to political aspects are equity and access, economic status, pedagogical choice, and professional organizations and unions. The issues related to technology include the technological skills, use of technology, and affordance. Finally, we suggest that all the stakeholders should pay attention to resolving these issues by improving the curriculum, training teachers, resourcing the classroom with locally made and new technological tools.

We propose a model for gravity based on the gravitational polarization of space. With this model, we can relate the density parameters within the Friedmann model, and show that dark matter is bound mass formed from massive dipoles set up within the vacuum surrounding ordinary matter. Aggregate matter induces a gravitational field within the surrounding space, which reinforces the original field. Dark energy, on the other hand, is the energy density associated with gravitational fields both for ordinary matter, and bound, or induced dipole matter. At high CBR temperatures, the cosmic susceptibility, induced by ordinary matter vanishes, as it is a smeared or average value for the cosmos as a whole. Even though gravitational dipoles do exist, no large scale alignment or ordering is possible. Our model assumes that space, i.e., the vacuum, is filled with a vast assembly (sea) of positive and negative mass particles having Planck mass, called planckions, which is based on extensive work by Winterberg. These original particles form a very stiff two component superfluid, where positive and negative mass species neutralize one another already at the submicroscopic level, leading to zero net mass, zero net gravitational pressure, and zero net entropy, for the undisturbed medium. It is theorized that the gravitational dipoles form from such material positive and negative particles, and moreover, this causes an intrinsic polarization of the vacuum for the universe as a whole. We calculate that in the present epoch, the smeared or average susceptibility of the cosmos equals, , and the overall resulting polarization equals, . Moreover, due to all the ordinary mass in the universe, made up of quarks and leptons, we calculate a net gravitational field having magnitude, . This smeared or average value permeates all of space, and can be deduced by any observer, irrespective of location within the universe. This net gravitational field is forced upon us by Gauss’s law, and although technically a surface gravitational field, it is argued that this surface, smeared value holds point for point in the observable universe. A complete theory of gravitational polarization is presented. In contrast to electrostatics, gravistatics leads to anti-screening of the original source field, increasing the original value, , to, , where is the induced or polarized field. In the present epoch, this leads to a bound mass, , where is the sum of all ordinary source matter in the universe, and equals the relative permittivity. A new radius, and new mass, for the observable universe is dictated by the density parameters in Friedmann's equation, and Gauss’s law. These lead to the very precise values, , and, , respectively, somewhat larger than current less accurate estimates.

The Particle-In-Cell (PIC) method has been developed in order to investigate microscopic phenomena, and with the advances of computing power, newly developed codes have been used for several fields such as astrophysical, magnetospheric, and solar plasmas. PIC applications have grown extensively with large computing powers available on supercomputers such as Pleiades and Blue Waters in the US. For astrophysical plasma research PIC methods have been utilized for several topics such as reconnection, pulsar dynamics, non-relativistic shocks, relativistic shocks, relativistic jets, etc. PIC simulations of relativistic jets have been reviewed with the emphasis on the physics involved in the simulations. This review summarizes PIC simulations, starting with the Weibel instability in slab models of jets, and then focuses on global jet evolution in helical magnetic field geometry. In particular we address kinetic Kelvin-Helmholtz instabilities and mushroom instabilities.

Engineering of drug nanocarriers combining fine-tuned mucoadhesive/mucopenetrating properties is currently being investigated to ensure more efficient mucosal drug delivery. Aiming to improve the transmucosal delivery of hydrophobic drugs, we designed a novel kind nanogel produced by the self-assembly of amphiphilic chitosan graft copolymers ionotropically crosslinked with sodium tripolyphosphate. In this work, we synthesized for the first time chitosan-g-poly(methyl methacrylate) nanoparticles thiolated by the conjugation of N-acetyl cysteine. First, we confirmed that both non-crosslinked and crosslinked nanoparticles in the 0.05-0.1% w/v concentration range display very good cell compatibility in two cell lines that are relevant to oral delivery, Caco2 cells that mimic the intestinal epithelium and HT29-MTX cells that produce mucin. Then, we evaluated the effect of crosslinking, nanoparticle concentration and thiolation on the permeability in vitro utilizing monolayers of (i) Caco2 and (ii) Caco2:HT29-MTX cells (9:1 cell number ratio). Results confirmed that the ability of the nanoparticles to cross Caco2 monolayer was affected by the crosslinking. In addition, thiolated nanoparticles interact more strongly with mucin, resulting in a decrease of the apparent permeability coefficient (Papp) compared to the pristine nanoparticles. Moreover, for all the nanoparticles, higher concentration resulted in lower Papp suggesting indicating that the transport pathways could undergo saturation.

Physics behind collimated highly directional nature of lasers, and factors that keep the seven coloured waves that form white light together during their journey from Sun to Earth, in the face of the natural disruptive forces, is not fully understood. Energy levels were measured, in terms of alterations in induced current and voltage, in beams from a red laser, white LED light and the Sunlight before and during their disruption by diffusers (frosted glass for the lasers) and diffractors (diffraction grating for the white light) using a photovoltaic solar cell panel attached to a digital multimeter. Results show that disruption of the beams results in release of extra energy named as ‘Latent Light Binding’ Energy’. It is hypothesized that the ‘binding’ energy keeps laser waves firmly bound together both end-on and side-on enabling laser beams to travel long distances in collimated manner. Likewise, the 7 coloured waves that constitute white light are kept together, probably side-on, in their journey from the Sun to the Earth. The observation that diffraction of sunbeam is associated with increased power generation provides a new lead to improve harnessing of solar energy, where, currently, the focus is mainly on improving efficiency of photovoltaic cell.

In this article, I estimate the value of “Individual Using Internet”-IUI in the context of Environmental, Social and Governance-ESG database of the World Bank. I use data from 193 countries for the period 2011-2020. I found that among others the value of IUI is positively associated to “Methane Emissions” and “People Using Safely Managed Sanitation Services” and negatively associated among others to “Fossil Fuel Energy Consumption” and “Renewable Energy Consumption”. I apply the k-Means algorithm for the clusterization optimized with the Elbow Method and we find the presence of three clusters. Finally, I confront eight machine-learning algorithms to predict the future value of IUI. I found that the best predictive algorithm is Linear Regression and that the value of IUI is expected to decrease on average of 0.30% for the analysed countries.

Piceatannol is a naturally occurring polyphenolic compound that is widely found in grapes, blueberries, mushrooms, passion fruit and other edible fruits and vegetables. It has a variety of biological activities and pharmacological effects, including anti-inflammatory, antioxidation, antiaging, antiviral, antitumor, anticancer, antiatherosclerosis, antiparasitic, immunoregulatory, and cardiovascular protection effects. The aim of this study was to investigate the antiherpesvirus effects of piceatannol. Pseudorabies virus (PRV) belongs to the family Herpesviridae. PRV has a wide host range and can cause cytopathic effects (CPEs) in PK-15 cells. Therefore, PRV was used as a model to study the antiherpesvirus effect of piceatannol. In this study, we evaluated the antiviral activity of piceatannol against PRV in vitro and in vivo. The results showed that piceatannol could reatrain PRV multiplication in PK-15 cells in a dose-dependent manner. The 50% inhibitory concentration (IC50) was 0.0307 mg/mL, the IC50 was 0.0307 mg/mL, and the selectivity index (SI, CC50/IC50) was 3.68. The addition of piceatannol at different stages of PRV infection inhibited the viral adsorption and intracellular replication phases of PRV. Piceatannol significantly reduced the expression levels of the IE180, EP0, UL29, UL44, US6 and UL27 genes of PRV within 48 h, significantly reduced the expression levels of the PRV gB and gD proteins, and reduced PRV-induced apoptosis. Molecular docking showed that piceatannol had good binding activity with the PRV gB and gD proteins. The results of animal experiments in vitro indicated that piceatannol could delay the onset of disease, improve the survival rate of the mice (14.3%), reduce the viral load in the brain and kidney of the mice, alleviate the pathological changes in the mouse tissues and organs, and increase the levels of TNF-α, IEN-γ and IL-4 in the serum of the mice. These data indicate that piceatannol has good anti-PRV activity in vitro and in vivo, indicating that it could be a novel antiherpesvirus infection agent in the future.

Diabetes mellitus is a global health issue that necessitates the development of novel therapeutic approaches. Today numerous experimental methods have been used and set up to evaluate novel drugs with antidiabetic effects. In addition, several research studies have been done to induce diabetes under in vitro and in vivo conditions, but only a small number of these efforts are currently in a usable stage. This review aims to provide useful guidance for researchers who seek to evaluate the antidiabetic potential of drugs, agents, or new medications using the standard methods published by authorities and academics worldwide organizations and research centers. In this review, we collected 132 relevant articles from prominent databases such as PubMed, ScienceDirect, Scopus and others to summarize in vitro and in vivo experimental validation of antidiabetic treatment from 1943 to present.

Leishmaniasis is a vector-borne parasitic infection caused by the bite of female Phlebotomine sandflies. World Health Organization (WHO) estimates 100,000 cases to be reported annually on a global scale, moreover, 13 million people were infected between 2010 and 2015 worldwide. Treatment of leishmaniasis by conventional synthetic compounds is met by challenges pertaining to adverse effects which call for the discovery of newer anti-leishmanial molecules. This study was performed to evaluate the effect and modes of action of a sesquiterpene alcoholic molecule Farnesol on Leishmania major, the causative agent of Zoonotic Cutaneous leishmaniasis. The cytotoxic effect of Farnesol against L. major promastigotes, amastigotes and macrophages was assessed by MTT test and counting. The IC50 on promastigotes by Farnesol on L. major was evaluated by flow cytometry. In the findings, Promastigotes were reduced at 167 µM/mL & the mean numbers of L. major amastigotes in macrophages were significantly decreased in exposure to Farnesol at 172 µM/ml. In addition, Farnesol demonstrated no cytotoxicity on macrophages as the IC50 value was 945 µM/ml; it induced significant apoptosis dose-dependent on L. major promastigotes. In silico protein-ligand binding analyses indicated the effect of Farnesol in perturbation of the ergosterol synthesis pathway of Leishmania with attributes suggesting inhibition of Lanosterol-α-demethylase, the terminal enzyme of ergosterol synthesis machinery. Findings from flow cytometry reveal the role of farnesol in apoptosis-induced killing in promastigotes. Farnesol was effective at very lower concentrations when compared to Paromomycin. Further studies are crucial to evaluate the therapeutic potentials of Farnesol alone and in combination with other conventional drugs using clinical settings.

The pore-throat radius of shale oil reservoir is extremely small, and it is difficult to accurately obtain the absolute permeability and oil-water two-phase relative permeability of actual oil reservoir through conventional core experiments. However, these parameters are very important for reservoir numerical simulation. In this paper, a method for characterizing flow parameters based on pore network model that considers differential pressure flow and diffusion flow is proposed. Firstly, a digital core was reconstructed using focused ion beam scanning electron microscopy (FIB-SEM) from the Gulong shale reservoir in the Songliao Basin, China, and a pore network model was extracted. Secondly, quasi-static single-phase flow and two-phase flow equations considering diffusion were established in the pore network model. Finally, pore throat parameters, absolute permeability, and oil-water two-phase permeability curves were calculated, respectively. The results show that the pore throat distribution of Gulong shale reservoir is mainly concentrated in the nanometer scale, the mean pore radius is 87 nm, the mean throat radius is 41 nm, and the mean coordination number is 3.97; The calculated permeability considering diffusion is 0.000124mD, which is approximately twice the permeability calculated without considering diffusion; The irreducible water saturation of the Gulong shale reservoir is approximately 0.26, and the residual oil saturation is approximately 0.73. The method proposed in this paper can provide an important approach for characterizing the flow parameters of similar shale oil reservoirs.

We estimate the value of Research and Development Expenditures as a percentage of GDP-RDE in the context of Environmental, Social and Governance-ESG model. We use the ESG World Bank database. We analyze data from193 countries in the period 2011-2020. We apply a set of econometric techniques i.e. Pooled Ordinary Least Squares-OLS, Panel Data with Random Effects, Panel Data with Fixed Effects, Weighted Least Squares-WLS. We found that the level of RDE is positively associated, among others, to “Nitrous Oxide Emissions” and “Scientific and Technical Journal Articles”, and negatively associated, among others to “Heat Index 35”, “Maximum 5-day Rainfall”. Furthermore, we perform a cluster analysis with the application of the k-Means algorithm optimized with the Elbow Method. The results show the presence of four clusters. Finally, we confront eight different machine-learning algorithms to predict the future value of RDE. We find that Linear Regression is the best predictive algorithms. RDE is expected to growth on average of 0.07% for the analysed countries.

Influenza virus strain A/South Africa/3626/2013 (H1N1)pdm09 (SA-WT) is a non-mouse-adapted model strain, which has naturally high pathogenic properties for mice. It has been suggested that the high pathogenicity of this strain for mice could be due to the three strain-specific substitutions in the polymerase complex (Q687R in PB1, N102T in PB2, and E358E/K heterogeneity also in PB2). To evaluate the role of these replacements, SA-WT was passaged five times in mouse lungs, and the genome of the mouse-adapted version of the SA-WT strain (SA-M5) was sequenced. SA-M5 lost E358E/K heterogeneity and retained E358, which is the prevalent amino acid at this position among H1N1pdm09 strains. Besides, in the hemagglutinin of SA-M5, two heterogeneous substitutions (G155G/E and S190S/R) were identified. Both viruses, SA-M5 and SA-WT, were compared for their toxicity, ability to replicate, pathogenicity, and immunogenicity for mice. In mice infected with SA-M5 or SA-WT strains, toxicity, virus titer in pulmonary homogenates, and mouse survival did not differ significantly. Contrarily, an increase in the immunogenicity of SA-M5 compared to SA-WT was observed. This increase could be due to the substitutions G155G/E and S190S/R in the HA of SA-M5. The prospects for using SA-M5 in studying the immunogenicity mechanisms were also discussed.

Nowadays, according to spectacular improvement in health care and biomedical level, a tremendous amount of data is recorded by hospitals. In addition, the most effective approach to reduce disease mortality is to diagnose it as soon as possible. As a result, data mining by applying machine learning in the field of diseases provides good opportunities to examine the hidden patterns of this collection. An exact forecast of the mortality after heart surgery will cause Successful medical treatment and fewer costs. This research wants to recommend a new stacking predictive model after utilizing the random forest feature importance method to foresee the mortality after heart surgery on a highly unbalanced dataset by using the most practical features. To solve the unbalanced data problem, a combination of the SVM-SMOTE over-sampling algorithm and the Edited-Nearest-Neighbor under-sampling algorithm is used. This research compares the introduced model with some other machine learning classifiers to ensure efficiency through shuffle hold-out and 10-fold cross-validation strategies. In order to validate the performance of the implemented machine learning methods in this research, both shuffle hold-out, and 10-fold cross-validation results indicated that our model had the highest efficiency compared to the other models. Furthermore, the Friedman statistical test is applied to survey the differences between models. The result demonstrates that the introduced stacking model reached the most accurate predicting performance after Logistic Regression.

This article explores the relationship between convex functions defined on integers ($\mathbb{Z}$) and their extension to real numbers ($\mathbb{R}$). We introduce key definitions and investigate the hypothesis that there exists a unique convex curve within this family of functions, leading to a proof by contradiction. Our findings highlight the preservation of convexity as functions transition from integers to real numbers.

Among the alternatives pointed out as able to make livestock a more efficient activity and reduce its environmental impact, the use of feeds with high digestibility and the use of non-conventional fodder species can be highlighted. Tithonia diversifolia (Hemsl.) A. Gray (TD) has already gained attention as a feed for ruminants. Nonetheless, there has been little discussion about the impacts of this plant on the rumen dynamics that lead to better animal performance. The aim of this study was to assess how increasing levels of TD could affect ruminal microbial biomass synthesis, degradability, and in vitro gas production (IVGP) of diets. Four diets were evaluated: a control diet (TD0: 400 g kg-1 soybean meal and corn grain, and 600 g kg-1 Tifton 85 hay (Cynodon spp)) and three increasing levels of TD (TD9: 90, TD27: 270, and TD45: 450 g kg-1 – dry matter basis) as a replacement for dietary roughage. A 96-hour IVGP assay was carried out and five incubation times (2, 4, 10, 24, and 96 hours) were used for degradability determination. Gas produced, methane (CH4), degradability of organic matter (IVDOM), short-chained fatty acid (SCFA) production, partitioning factor (PF), and microbial biomass (MB) were evaluated among treatments. There was no significant effect (P&gt;0.05) between TD inclusion and IVGP at most incubation times; only at 6 hours of incubation did gas production increase linearly with TD inclusion (R2=0.19; P&lt;0.05). TD inclusion had no effects on CH4. IVDOM increased linearly with TD inclusion at 6 and 10 hours, with TD45 being more degradable than the control diet at 6 hours only. There was a positive linear relationship (R2=0.20; P&lt;0.05) between TD inclusion and PF. TD45 had significantly higher PF values than the control. MB also increased linearly (R2=0.30; P&lt;0.05) with TD inclusion, and all diets with TD had significantly more MB than the control diet. The inclusion of TD at the levels used in this work was revealed to have a positive impact on microbial protein synthesis, which could be related to the higher microbial efficiency of increased substrate quality.

Oxalate, a compound produced by many edible plants and as a terminal metabolite in the liver of mammals, is a toxin that has a detrimental role to human health. Humans and other mam-mals do produce the enzymatic machinery to degrade oxalate. However, numerous oxa-late-degrading bacteria reside in the mammalian gut and thus provide an important function for hosts. The current review focuses on the environmental factors that influence the efficacy of pro-biotic oxalate-degrading bacteria, relative to oxalate metabolism. We describe the mechanism of oxalate catabolism and its consumption by obligate and facultative anaerobic oxalate-degrading bacteria, in both in vitro and in vivo environments. We also explore the environmental variables that impact oxalate degradation. Studies on single species degrade oxalate have not shown a strong impact on oxalate metabolism especially in high oxalate conditions such as consumption of foods high in oxalate (such as coffee and chocolate for humans or halogeton in animal feed). Considering effective variables which enhance oxalate degradation could be used in application of effective probiotic as a therapeutic tool in individuals with hyperoxaluria. This study indicates probiotics can be considered a good source of naturally occurring oxalate degrading agent in human colon

Bioactive fractions were isolated from the leaves extract of Kalanchoe pinnata and subjected to scrutiny for their prospective anti-obesity properties. An array of in vitro phytochemical, antioxidant, and enzyme inhibition assays were executed, which dis-cerned fractions F1 and F2 as the most effective fractions. These fractions were sub-sequently studied through in vivo experiments, affirming that F2 as the most potent fraction. Further characterization of F2 was conducted via HPTLC MS-MSn tech-niques. The outcomes demonstrated that F2 produced a notable anti-obesity effect in obese mice, reducing their body weight and lipid metrics, and leading to advanta-geous changes in their organs. An analytical examination of F2 revealed the existence of four principal compounds, which were subsequently subjected to in silco molecular docking and dynamic analysis, confirming their aptitude for binding to selected pro-teins. These findings imply that the utilization of Kalanchoe pinnata leaves could pro-vide a promising therapeutic strategy for the treatment of obesity.

Knowledge about ecological conditions and processes in centers of endemism (CoEs) is still limited with respect to various systematic groups of organisms, ecosystem types, ecological conditions and ecosystem functions. Endemics and CoEs play a prominent role in nature conservation monitoring and management, and in the organization of zoos, aquaria and botanical gardens. We review the meaning of different groups of organisms and indicators for the characterization of endemic-rich regions, the importance of heterogeneity in space, continuity in time, isolation and ex-situ management for the survival of endemic and threatened species. Currently, conversion of land cover and land use change are the most important causes of biodiversity decline and extinction risk of endemic and endangered species concentrated in CoEs. These are followed by climate change, including severe weather, and then natural processes such as volcanism, landslides or tsunamis. For conservation purposes the management of zoos, aquaria, botanical gardens, of regional land use, and social aspects of the diversity of endemics and CoEs have to be taken into account as well. We need better answers to questions about the relationship between ecoregions, CoEs and regional awareness of biodiversity, which is linked with human culture including the management of zoos, aquaria and botanical gardens, aesthetics, wellbeing, health and trade.

Introduction: The combination of Virtual Screening (VS) techniques with in vivo screening in the zebrafish model is currently being used in tandem for drug development in a faster and more efficient way. Areas covered: We review the different virtual screening techniques, the use of zebrafish as a vertebrate model for drug discovery and the synergy that exists between them. Expert opinion: We highlight the advantages of combining virtual and zebrafish larvae screening for drug discovery. On the one hand, VS is a faster and cheaper tool for searching active compounds and possible candidates for therapy than in vivo screening when processing large compound libraries. On the other hand, zebrafish larvae form a vertebrate model which allows in vivo screening of large amounts of the compounds. Importantly physiology and chemical response are mostly conserved between zebrafish and mammals. The availability of the transgenic and mutant zebrafish lines allows an analysis of a specific phenotype upon treatment along with toxicity, off-target effect, side effects, and dosage. Advantages of VS, in vivo whole animal approach screening, and the screening combinations are also reviewed.

Human eye is a specialized organ with complex anatomy and physiology, because it is characterized by different cell types with specific physiological functions. Given the complexity of the eye, ocular tissues are finely organized and orchestrated. In the last few years many in vitro models have been developed, in order to meet the 3Rs principle (Replacement, Reduction and Refinement) for eye toxicity testing. This procedure is highly necessary to ensure that the risks associated with ophthalmic products meet appropriate safety criteria. In vitro preclinical testing is now a well-established practice of significant importance for evaluating the efficacy and safety of cosmetic, pharmaceutical, and nutraceutical products. Along with in vitro testing, also computational procedures, herein described, for evaluating the pharmacological profile of potential ocular drug candidates including their toxicity, are in rapid expansion. In this review the ocular cell types and functionality are described providing an overview about the scientific challenge for the development of three-dimensional in vitro models.

Salmonid alphavirus strain 3 is responsible for outbreaks of pancreas disease in salmon and rainbow trout in Norway. Although the extensive amount of research on SAV3 focused mainly on the heart and pancreas (of clinical importance), tropism and pathogenesis studies of the virus in other salmon tissues are limited. Here, we used a combination of RT-qPCR (Q_nsp1 gene) and in situ hybridization (RNAscope®) to demonstrate the tropism of SAV3 in situ in tissues of Atlantic salmon, employing a challenge model (by cohabitation). In addition, as previous results suggested that pseudobranch may harbor the virus, the change in the expression of different immune genes upon SAV3 infection (RT-qPCR) was focused on the pseudobranch in the current study. In situ hybridization detected SAV3 in the heart, pseudobranch, gills, pyloric caeca, and pancreas after virus infection, with the heart ventricle showing the most extensive infection. Furthermore, the detection of the virus at different adipose tissues associated with the internal organs of the salmon, suggests a specific affinity of SAV3 to adipocyte’s components. The innate immune response to SAV3 in the pseudobranch after infection dominated over the adaptive responses, yet it did not mitigate the infection in that tissue. The early detection of SAV3 in the pseudobranch after infection, along with the persistent low infection over the experimental course, suggests a pivotal role of the pseudobranch in SAV3 pathogenesis in Atlantic salmon.

This comprehensive study delves into the implementation and effectiveness of the flipped classroom model in engineering EMI (English as a Medium of Instruction) courses in Taiwan. Situated within the strategic framework of Taiwan's Bilingual Nation 2023 policy, this research aims to enhance the global competitiveness of Taiwan's semiconducting manufacturing engineering sector. The study’s primary focus is on understanding the perceptions and learning outcomes of EFL (English as a Foreign Language) students in engineering courses. Through a methodical approach using descriptive statistics and chi-square tests, the study analyzes data from 33 junior engineering students specializing in mechanical and mechatronic fields. The findings highlight a significant positive influence of the flipped classroom model on various aspects of student learning, including increased engagement, heightened creativity, and enhanced problem-solving skills. Additionally, the study emphasizes the critical role of timely L1 support in facilitating effective learning in EMI settings. These outcomes not only demonstrate the flipped classroom's viability as a sustainable educational approach but also provide crucial insights for educators and policymakers. By aligning cutting-edge teaching methods with the evolving needs of engineering education, this study contributes to the discourse on educational innovation. It ultimately guides the development of future engineering programs that cater to diverse student needs and fosters the cultivation of skilled engineering professionals.

Pulmonary hypertension (PH) has a high mortality, and few treatment options. Adaptive immune mediators of PH in mice challenged with antigen/particulate matter (antigen/PM) has been the focus of our prior work. We identified key roles of type 2 and type 17 responses in C57BL/6 mice. Here, we focused on type 2 response related cytokines, specifically Resistin-like-molecule (RELM)α, a critical mediator of hypoxia-induced PH. Because of strain differences in the immune responses to type 2 stimuli, we compared C57BL/6J and BALB/c mice. A model of intraperitoneal antigen sensitization with subsequent, intranasal challenges with antigen/PM (ovalbumin and urban ambient PM2.5) or saline was used in C57BL/6 and BALB/c wild type or RELMα-/- mice. Vascular remodeling was assessed by histology, right ventricular (RV) pressure, RV weights and cytokines were quantified. Upon challenge with antigen/PM2.5, both C57BL/6 and BALB/c mice developed pulmonary vascular remodeling; these changes were more prominent in the C57BL/6 strain. Compared to wild type mice, RELMα-/- had significantly reduced pulmonary vascular remodeling in BALB/c, but not in C57BL/6 mice. RV weights, RV IL-33 and RV ST2-IL-33-receptor were significantly increased in BALB/c wild type mice, but not in BALB/c-RELMα-/- or in C57BL/6-wild type or C57BL/6-RELMα-/- mice. RV systolic pressures (RVSP) were higher in BALB/c compared to C57BL/6J mice, and RELMα-/- were not different from their respective wild type controls. In BALB/c mice, RELMα was a key contributor to antigen/PM2.5 induced pulmonary vascular remodeling, RV thickening and RV cytokine responses, highlighting the significance of the genetic background. The RELMα-/- animals demonstrated significantly decreased expression of RELMβ and RELM which makes these mice comparable to a situation where human RELMα levels would be significantly modified, as humans only have one RELM molecule.

This study was to designed to develop sorafenib-loaded polymeric nanoparticles, surface-modified with pluronic F-127 for the effective treatment of hepatocellular (HCC) and renal cell carcinomas (RCC). Poly lactic coglycolic acid (PLGA) was used to encapsulate different concentrations of sorafenib by a simple modified solvent evaporation method applying pluronic F-127 as a surfactant and coating agent. The preformulation and characterization studies were conducted to evaluate the incompatibilities among sorafenib, PLGA and pluronic F-127, and physicochemical properties of the formulations, respectively. The sizes of the coated and plain PLGA nanoparticles were ~140 ± 14.7 nm and ~ 120 ± 10.1 nm, respectively. It has been confirmed from the in vitro release studies that PLGA sustained the release of sorafenib, avoiding the initial burst release, while the in vivo studies demonstared that surface-modified nanoparticles have greater affinity in the target aorgans than plain PLGA nanoparticles and free drug keeping the dose constant (20 mg/kg body weight). The delivery of sorafenib-loaded polymeric PLGA nanoparticles into the target tissues and their pharmacokinetic parameters have been improved significantly compared to the reported formulations.

The pinning force density FpJc,B=Jc×B (where Jc is the critical current density and B is the applied magnetic field) is one of the main parameters that characterize the resilience of a superconductor to carry a dissipative-free transport current in an applied magnetic field. Kramer (1973 J. Appl. Phys. 44 1360), and Dew-Hughes (1974 Phil. Mag. 30 293) proposed a widely used scaling law for the pinning force density amplitude: FpB=Fp,max×p+qp+qppqq×BBc2p×1-BBc2q, where Fp,max, Bc2, p, and q are free-fitting parameters. Since the late 1970-s till now, several research groups have reported experimental data on the dependence of Fp,max on the average grain size, d, in Nb3Sn-based conductors. Godeke (2006 Supercond. Sci. Techn. 19 R68) proposed that the dependence obeys the law Fp,maxd=A×ln1d+B. However, this scaling law has several problems, for instance, the logarithm is taken from a non-dimensionless variable, and Fp,maxd&lt;0 for large grain sizes, and Fp,maxd→∞ for d→0. Here, we reanalysed the full inventory of publicly available Fp,maxd data for Nb3Sn conductors and found that the dependence can be described by Fp,maxd=Fp,max0×exp-dδ law, where the characteristic length, δ, varies within a remarkably narrow range, that is, δ=175±13 nm, for samples fabricated by different technologies. The interpretation of the result is based on the idea that the in-field supercurrent flows within a thin surface layer (thickness of δ) near the grain boundary surfaces (similar to London’s law, where the self-field supercurrent flows within a thin surface layer with a thickness of the London penetration depth, λ, and the surface is a superconductor-vacuum surface). An alternative interpretation is that δ represents the characteristic length of the exponential decay flux pinning potential from the dominant defects in Nb3Sn superconductors, which are grain boundaries.

In this review we look at the developments in the field of artificial intelligence (A.I) and their current impact as well as future implications in the field of cardiology, we as physicians and cardiologists have tried to put our perspective on the rapidly evolving field, In light of the fact that many of the healthcare workers and professionals across the world still find the concept of A.I quite complicated, elusive and somewhat paradoxical, we have tried to simplify the concept of artificial intelligence and make it easy for everyone to understand from all walks of life. The Databases utilized for our review are PubMed, PubMed Central, Google Scholar. The Keywords used for our Data Search are “Artificial Intelligence”, “A.I Cardiology”, “A.I in Cardiovascular Medicine”, “Machine Learning in Cardiology”. We screened all relevant since inception till March 25th and included 44 relevant articles after careful consideration into our paper. We have discussed the implementation of and scope of artificial intelligence across a broad spectrum of applications including cardiovascular imaging and diagnostics like electrocardiograms, echocardiograms, cardiac CT/MRIs to novel cardiac monitoring devices, CRISPR gene editing in cardiology and implementation of artificial intelligence in the field of Cardiovascular Bioprinting. This is the initial review in a series of reviews regarding A.I in Cardiology.

In this research paper, we address the critical role of data security in the rapidly evolving FinTech sector. We explore the challenges and strategies for establishing robust data security systems, emphasizing the consequences of data breaches and common vulnerabilities. The paper highlights the efficacy of technologies like encryption, blockchain, and cloud security, supported by real-world case studies from leading FinTech companies. Additionally, we examine regulatory frameworks and standards essential for maintaining data security. Concluding with the proposal of an integrated security system model, the paper underscores the synergy between technological innovation, regulatory compliance, and proactive risk management in the FinTech industry