Epidermal Growth Factor Receptor (EGFR) tyrosine kinase is a cell surface receptor whose overexpression has been associated with different types of cancers including brain cancer (glioblastoma multiforme). The ability of the extract of Scutellaria baicalensis to inhibit the proliferation of malignant glioma cells have been reported. Thus, in this study we report the identification of 307 bioactive constituents responsible for the anti-glioblastoma multiforme effect from S. baicalensis using in silico studies such as molecular docking, binding free energy calculations, pharmacophore modelling, induced-fit docking, gene enrichment analysis, molecular dynamic simulations and ADMET predictions. A total of 307 chemical constituents of S. baicalensis were screened and the top 10 scoring compounds indicated different binding affinities ranging from -9.010 to -6.427 kcal/mol towards the EGFR tyrosine kinase; Ganhuangenin, 5,7,2',5'-tetrahydroxyflavone, (2R)-2-(2,6-dihydroxyphenyl)-3,4-dihydro-2H-chromene-5,7-diol, and tenaxin I possess higher binding affinities (-9.010 to -8.649 kcal/mol) compared to the standard ligand, erlotinib having -8.539 kcal/mol. The compounds interacted with amino acids of clinical importance such as MET 769, GLU 738, THR 766 via H-bond. The structural features involved in the interaction with the target were mostly two aromatic rings, H-bond donors and acceptors and some hydrophobic interactions which varies between the ligands. Better docking scores in the induced-fit docking further validates the inhibitory potential of the compounds against the flexible protein. All the top-scoring ligands from S. baicalensis had zero Lipinski violation and also obeyed other drug-likeness rules by Ghose, Veber, Egan, and Muegge with the exception of breviscapine. Interestingly, all the compounds are not likely to be hepatotoxic, mutagenic, or cytogenic, making them potentially safe as anti-cancer agents.

Background: COVID-19 made its debut as a pandemic in 2020; since then, more than 607 million cases and at least 6.5 million deaths have been reported worldwide. While the burden of disease has been described, the long-term effects or chronic sequelae are still being described. Objective: To describe the findings of a current systematic review of the long-term effects related to post-COVID-19 sequelae. Design: A systematic review was carried out in which cohort studies, case series, clinical case reports were included, and the PubMed, Scielo, SCOPUS and Web of Science databases were ex-tracted. Information published 2020 to June 1, 2022, was sought. Results: We reviewed 300 manuscripts during the first step of the literature review process. Then 260 abstracts were analyzed. In the end, we included 32 manuscripts: 9 for pulmonary, 6 for cardiac, 2 for renal, 9 for neurological and psychiatric, and 8 for cutaneous sequelae. Conclusion: Studies show that the most common sequelae are those linked to the lungs, followed by skin, cutaneous and psychiatric alterations. Women report a higher incidence of the sequelae, as well as those with comorbidities and severer COVID-19 history. The COVID-19 pandemic has not only caused death and disease since its apparition but has also sickened millions of people around the globe who potentially suffer from serious illnesses that will continue to add to the list of health problems and further burden healthcare systems around the world.

In recent years, the demand for coffee has increased tremendously. During the production process, green coffee beans are traditionally screened manually for defective beans before they are packed into coffee bean packages; however, this method is not only time-consuming but also increases the rate of human error due to fatigue. Therefore, this paper proposed a lightweight deep convolutional neural network (LDCNN) for the quality detection system of green coffee beans, which combined depthwise separable convolution (DSC), squeeze-and-excite block (SE block), skip block, and other frameworks. To avoid the influence of low parameters of the lightweight model caused by the model training process, rectified Adam (RA), lookahead (LA), and gradient centralization (GC) were included to improve efficiency; the model was also put into the embedded system. Finally, the local interpretable model-agnostic explanations (LIME) model was employed to explain the predictions of the model. The experimental results indicated that the accuracy rate of the model could reach up to 98.38% and the F1 score could be as high as 98.24% when detecting the quality of green coffee beans. Hence, it can obtain higher accuracy, lower computing time, and lower parameters. Moreover, the interpretable model verified that the lightweight model in this work is reliable, providing the basis for screening personnel to understand the judgment through its interpretability, thereby improving the classification and prediction of the model.

Hexane is a solvent used extensively in the food industry for the extraction of various products such as vegetable oils, fats, flavours, fragrances, colour additives or other bioactive ingredients. As it is classified as a "processing aid", it does not have to be declared on the label under current legislation. Therefore, although traces of hexane may be found in final products, especially in processed products, its presence is not known to consumers. However, hexane, and in particular the n-hexane isomer, has been shown to be neurotoxic to humans and has even been listed as a cause of occupational diseases in several European countries since the 1970s. In order to support the European strategy for a toxic-free environment (and toxic-free food), it seemed important to collect scientific information on this substance by reviewing the available literature. This review contains valuable information on the nature and origin of the solvent hexane, its applications in the food industry, its toxicological evaluation and possible alternatives for the extraction of natural products. Numerous publications have investigated the toxicity of hexane, and several studies have demonstrated the presence of its toxic metabolite 2,5-hexanedione (2,5-HD) in the urine of the general, non-occupationally exposed population. Surprisingly, a tolerable daily intake (TDI) has apparently never been established by any food safety authority. Since hexane residues are undoubtedly found in various foods, it seems more than necessary to clearly assess the risks associated with this hidden exposure. A clear indication on food packaging and better information on the toxicity of hexane could encourage industry to switch towards one of the numerous other alternative extraction methods already developed.

This article aims to systematically review the available evidence concerning the relationship between basal metabolism (BM), body composition (BC), and physical activity (PA) with central obesity. The search strategy was carried out using Web of Science, PubMed, Google Scholar, and SciELO following the PRISMA guidelines. The STROBE checklist and the Jadad scale for quality assessment were also used. A total of 1382 studies were initially identified being 25 publications eligible for systematic data extraction. Individual studies showed that adults with waist circumference (WC) above 88 cm in women and above 102 in men had a higher risk of metabolic alterations related to high absolute energy expenditure and less maximum oxygen consumption (VO2 max). Participants with central obesity presented a high percentage of body fat (BF%) between 30.6% and 41.6%. Most of the PA intervention studies reported reductions in WC between 1.3 and 5.8 cm. In conclusion, there is a direct relationship between the components of BM with central obesity and a direct association between central obesity and BF%. PA is a protective factor that needs to be promoted to reduce WC and control central obesity as a public health problem. PROSPERO ID registration: CRD42021232917.

Background: Malnutrition has negative consequences in hospitals, like poor disease recovery, increased mortality, length of hospitalization, readmission, and health care costs.Aims: This review was designed to determine malnutrition prevalence in hospitals located in eastern Mediterranean region (EMR).Study design: To conduct this systematic review, papers, including original articles, related references and conference proceedings on the prevalence of malnutrition in adult hospitalized patients published in international journals and scientific databases from 1 Jan 2017 to 31 Jan 2022 will be included. The following keywords and their alternatives will be used in the literature search: malnutrition, patient, and EMR. The protocol has been registered at PROSPERO (code: CRD42022339426).Methods: After initial screening based on inclusion and exclusion criteria, the full text articles will be read carefully and eligible documents will be selected according to the defined objectives. Afterward, the selected papers will be reviewed for methodological quality and the required information will be extracted. Finally, in case of sufficient data, a meta-analysis will be performed. Screening, selection, quality assessment, and data extraction will be done by at least two independent reviewers.Results: This review is ongoing and will be completed until the end of year 2023.Conclusion: This review aims to provide comprehensive evidence about the prevalence of malnutrition among adult inpatients in EMR hospitals. This can provide regional authorities, health managers and policy makers good information regarding current status to make appropriate decisions for promoting the health status in hospitals.

Flammability was evaluated and the results showed the values of critical flux at extinguishment (CFE) as 49.5kW/㎡ on average, total heat release (Qt) as 0.21MJ on average, and peak heat release rate (Qp) as 0.66kW on average, which satisfied all of the thresholds presented by the IMO. Therefore, flame-retardant plywood, of which the flame-retardant performance was evaluated, was determined to be an applicable finishing material that satisfies fire safety standards.

This paper develops a methodology to control the navigation of an autonomous ship robot from an initial state to a final. To solve the problem the following approach is used: The ship robot system is modelled as a control system of six ordinary differential equations involving six state variables and three control variables. After having computed the system Hamiltonian, the feasible controls for optimality are derived from the normal equations of optimality as functions of the state and costate variables. Such controls are substituted into the state and the costate equations and give a combined control-free state-costate system of ordinary differential equations which is solved numerically by using a developed Matlab computer program. Associated computational simulations are designed and provided to show the reliability of the approach.

Glutamate dehydrogenase (GDH) plays a key role in the metabolism of glutamate, an important compound at a cross-road of carbon and nitrogen metabolism and a relevant neurotransmitter. Despite being one of the first discovered allosteric enzymes, GDH still poses challenges for structural characterization of its allosteric sites. Only the structures with ADP, and at low (3.5 Å) resolution, are available for mammalian GDH complexes with allosteric activators. Here we aim at deciphering structural basis for the GDH allosteric activation, using bovine GDH as a model. For the first time we report a mammalian GDH structure in a ternary complex with the activators leucine and ADP, co-crystallized with potassium ion. An improved 2.4 Å resolution of the GDH complex with ADP is also presented. The ternary complex with leucine and ADP differs from the binary complex with ADP by the conformation of GDH C-terminus, involved in the leucine binding and subunit interactions. The potassium site, identified in this work, may mediate interactions between the leucine and ADP binding sites. Our data provide novel insights into the mechanisms of GDH activation by leucine and ADP, linked to the enzyme regulation by (de)acetylation.

This article aims to identify the current development of cross-border tourism between Vietnam and China. The paper analyzes the perception and strategy of cross-border tourism development in the two countries, especially in the context of China’s implementation of the “Belt and Road Initiative” (BRI). The article emphasizes that Vietnam and China have recently made efforts to promote cross-border tourism development. At the same time, Vietnam and China see cross-border tourism development as a significant part of comprehensive border cooperation between the two countries. However, the development plans for cross-border tourism between the two countries are still mainly on the desk, not yet implemented effectively. Thus, its achievements are relatively modest. Besides, the article emphasizes that the interests of the people living in the border area, especially the Vietnam side, are almost “forgotten” in the development of cross-border travel between the two countries. Besides, the article also analyzes the challenges that the two sides are facing, especially the Vietnam side, in promoting the development of cross-border tourism between the two countries.

Since life on earth developed, parasitic microbes have thrived. Increases in host numbers, or the conquest of a new species, provides an opportunity for such a pathogen to enjoy, before host defense systems kick in, a similar upsurge in reproduction. Outbreaks ‒ caused by ‘endemic’ pathogens ‒ and epidemics ‒ caused by ‘novel’ pathogens ‒ have thus been creating chaos and destruction since prehistorical times. To study such (pre)historic epidemics, recent advances in the ancient DNA field, applied to both archeological and historical remains, have helped tremendously to elucidate the evolutionary trajectory of pathogens. These studies offered new and unexpected insights in the evolution of, for instance, smallpox virus, hepatitis B virus and the plague-causing bacterium Yersinia pestis. Furthermore, burial patterns and historical publications can help in tracking down ancient pathogens. Another source of information is our genome, where selective sweeps in immune-related genes relate to past pathogen attacks, while multiple viruses have left their genomes behind for us to study.

Climate and land use changes are two factors affecting the hydrology of watersheds. The greatest effect of climate change is probably the change in the hydrological cycle, thus water availability for human consumption, industry, and power generation. While the change in land use can cause changes in the hydrological components of the basin, such as evapotranspiration, runoff, and groundwater recharge. From these projections, it is necessary to understand the processes involved in climate change and land use and its impact on water systems. In this context, the objective of this study was to simulate climate change scenarios combined with the land use change and to analyze the impacts on the hydrology in the Piracicaba basin. Two periods were selected based on the preliminary result of detection of the abrupt change point of the annual flow series, using Petitt's non-parameter test. The first period selected prior to the occurrence of the point of the change was from 1985 to 2000. The other period after the point of the change was 2001 to 2015. Land use maps of the years 1990 and 2010 were used to represent the two periods. The results showed a good performance of the SWAT model. The NS (Nash-Sutcliffe coefficient) was 0.88 in calibration for both periods. In the validation, the NS was 0.92 and 0.94 for the first and second periods respectively. We then simulate climate and land use changes scenarios and compare them to the current scenario (baseline). The simulation results showed that the hydrological processes in the Piracicaba basin in the period 1985-2015, had more intense responses to land use change than climate.

Primary systemic treatment (PST) downsizes the tumor and improves pathological response. The aim of this study is to analyze the feasibility and tolerance of primary concurrent radio-chemotherapy (PCRT) in breast cancer patients. Patients with localized TN/HER2+ tumors were enrolled in this prospective study. Radiation is delivered concomitantly during the first 3 weeks of chemotherapy, and it is based on a 15 fractions scheme (40.5Gy/2.7Gy per fraction to whole breast and nodal levels I-IV. Chemotherapy is based on Pertuzumab-Trastuzumab-Paclitaxel followed by anthracyclines in HER2+ and CBDCA-Paclitaxel followed by anthracyclines in TN breast cancers patients. 58 patients were enrolled, 25 patients (43%) were TN and 33 patients HER2+ (57%). With a median follow-up of 24.2 months, 56 patients completed PCRT and surgery. A total of 35 patients (87.5%) achieved >90% loss of invasive carcinoma cell in the surgical specimen. The 70.8% and the 53.1% of patients with TN and HER-2+ subtype respectively achieved complete pathological response (pCR). This is the first study of concurrent neoadjuvant treatment in breast cancer in which three strategies are applied simultaneously: fractionation of RT in 15 sessions, adjustment of CT to tumor phenotype and local planning by PET. The pCR rates are encouraging.

Background: Cloud-native software systems often have a much more decentralized structure and many independently deployable and (horizontally) scalable components, making it more complicated to create a shared and consolidated picture of the overall decentralized system state. Today, observability is often understood as a triad of collecting and processing metrics, distributed tracing data, and logging. The result is often a complex observability system composed of three stovepipes whose data is difficult to correlate. Objective: This study analyzes whether these three historically emerged observability stovepipes of logs, metrics and distributed traces could be handled more integrated and with a more straightforward instrumentation approach. Method: This study applied an action research methodology used mainly in industry-academia collaboration and common in software engineering. The research design utilized iterative action research cycles, including one long-term use case. Results: This study presents a unified logging library for Python and a unified logging architecture that uses the structured logging approach. The evaluation shows that several thousand events per minute are easily processable. Conclusion: The results indicate that a unification of the current observability triad is possible without the necessity to develop utterly new toolchains.

The current report represents a case of a 77-year-old man with Parkinson’s disease who died three weeks after receiving his third COVID-19 vaccination in January 2022. The patient was first vaccinated in May 2021 with the ChAdOx1 nCov- 19 vector vaccine, followed by two more doses with the BNT162b2 mRNA vaccine in July and December 2021. The family of the deceased requested an autopsy due to the ambivalent clinical features noted before death. The underlying illness (Parkinson’s disease) was confirmed by autopsy. However, no sign of a florid COVID-19 was discovered. Meanwhile, the immunohistochemical staining of the brain and heart revealed previously undiagnosed conditions. The brain, in distinctive, revealed multifocal necrotizing encephalitis with massive inflammatory lymphocyte infiltrates. In addition, the heart showed signs of serious myocarditis. Finally, immunohistochemical staining revealed that the SARS-CoV-2 spike protein was evident in the tissues investigated. Based on these immunohistochemical findings, it appears that the inflammatory changes in the patient's brain tissues are most likely the result of immunological processes. Concurrently, the absence of SARS-CoV-2 nucleocapsid-protein was evidenced, indicating that the detected spike-protein is unrelated to a SARS-CoV-2 infection. If such an infection was the cause of the spike protein, the SARS-CoV-2 nucleocapsid protein would also be detectable. As a consequence, the confirmed presence of the spike protein had to be attributed to the previous vaccination with the BNT162b2 mRNA vaccine that the deceased patient had received.

The efficacy of time-restricted feeding for weight loss has not been established as prior studies were limited by lack of controlled isocaloric designs. This study describes the design and implementation of a controlled feeding study evaluating time-restricted feeding. We designed a randomized, controlled, parallel-arm, feeding study comparing time restricted feeding (TRF) to a usual feeding pattern (UFP) for the primary outcome of weight change. Participants were aged 18-69 years with prediabetes and obesity. TRF consumed 80% of calories by 1300, and UFP consumed ≥50% of calories after 1700. Both arms consumed identical macro- and micro-nutrients, based on a healthy palatable diet. We calculated individual calorie requirements which were maintained throughout the intervention. We randomized 41 participants who all completed the study. The desired distribution of calories across feeding windows in both arms was achieved, as were weekly averages for macronutrients and micronutrients. All randomized participants completed the study. We actively monitored participants and adapted diets to facilitate adherence. We provide the first report, to our knowledge, on the design and implementation of a feeding study that isolated the effect of meal timing on weight, while maintaining constant caloric intake and identical diets during the study period.

Group B Streptococcus (GBS), a commensal in the body, causes a wide range of infectious diseases. The colonisation levels of GBS and its resistance profile to antibiotics provide important information useful for orienting prevention strategies. There is little data available on the subject with determination of resistance phenotypes in Cameroon. We therefore aimed to determine the prevalence of colonization, antibiotic resistance, including patterns of inducible resistance to clindamycin of GBS in Yaounde. To achieve this goal, a prospective cross-sectional study with an analytical component was carried out from the 28th June to the 29th August 2020 at the BIOSANTE laboratory and the Yaounde Gynaeco-Obstetrics and Paediatrics hospital. Vaginal swabs and urine were collected on 163 women. This samples were analysed using 5% defibrinated sheep blood agar and chocolate plus polyvitex agar. The isolates were identified using the morphology of the colony, Gram staining, haemolysis, catalase test and latex grouping test. Antibiotic susceptibility testing was done by disk diffusion method following the recommendations of the ACFSM 2019. The double disk diffusion method was used to identify isolates with clindamycin inducible resistance. Our data was analysed by the software SPSS version 2.1. The results obtained showed that the global prevalence of colonization by GBS was 37% (57/163), 40.35% in non-pregnant women and 59.65% in pregnant women. Pregnancy (P-value = 0.019) and gestational age (P-value = 0.025) constituted the risk factors of maternal colonization by GBS. In addition, the strains of GBS were resistant to all antibiotics tested. A D test showcased that 64.7% of GBS were resistant in a constitutive manner to clindamycin. We also note the presence of M phenotypes. As a whole, our results demonstrate that the rate of GBS colonization in this study was similar or higher than those in the previous report in Cameroon. All this indicates that attention should be paid to this bacterium in the monitoring of antimicrobial resistance and in the care of pregnant women and newborns.

Background/Aim: In clinical practice, uterine lipoleiomyomas are variants of uterine leiomyomas, often found incidentally, and do not require surgical treatment unless patient’s symptomatic. Therefore, these should be clinically differentiated from lesions that need surgical treatment. Conversely, hemangiomas, or blood vessel benign tumors, rarely develop in the uterus; however, many clinical complications such as abdominal pain and excessive vaginal bleeding result from a uterine hemangioma. Hemangiomas can occur at any age and primarily affect pregnant women. Materials and Methods: The oncological properties of uterine lipoleiomyoma and hemangioma in adults were investigated using molecular pathological examination on tissue excised from patients with uterine leiomyoma. Results: Through molecular pathological studies, which included potential biomarkers for uterine mesenchymal tumors, a differential diagnosis was established for this case of mesenchymal tumor. Herein, we report a 54-year-old non-pregnant woman who presented with vaginal bleeding and underwent hysterectomy after detection of a 140 × 100 mm intramural mass diagnosed as a concurrent uterine hemangioma and lipoleiomyoma after molecular histopathologic examinations. Conclusion: As far as we know, this case is the first patient of concurrent uterine hemangioma and lipoleiomyoma. Hence, such occurrence of several types of mesenchymal tumors must be considered in the differential diagnosis of patients with abnormal vaginal bleeding.

Previously, we reported that MTH1 inhibitors TH588 and TH1579 selectively induce oxidative damage and kill Ras expressing or transforming cancer cells, as compared to non-transforming immortalized or primary cells. While this explains the impressive anti-cancer properties of the compounds, the molecular mechanism remains elusive. Oncogenes induce replication stress, re-sulting in under replicated DNA and replication continuing into mitosis, where TH588 and TH1579 treatment cause toxicity and incorporation of oxidative damage. Hence, we hypothesized that oncogene-induced replication stress explains the cancer selectivity. To test this, we overex-pressed c-Myc in human epithelial kidney cells (HA1EB), resulting in increased proliferation, polyploidy and replication stress. TH588 and TH1579 selectively kill c-Myc overexpressing clones, enforcing the cancer cell selective killing of these compounds. Moreover, the toxicity of TH588 and TH1579 in c-Myc overexpressing cells is rescued by transcription, proteasome or CDK1 inhibitors, but interestingly not by nucleoside supplementation. This suggest that cancer selectivity is unrelated oncogene-induced replication stress. We conclude that the molecular toxi-cological mechanisms how TH588 and TH1579 kill c-Myc overexpressing cells have several com-ponents and involves MTH1-independent proteosomal degradation of c-Myc itself, c-Myc driven transcription and CDK activation, and is likely unrelated to oncogene-induced replication stress.

The sustainability of the planet and its inhabitants is in dire danger and is among the highest priorities on global agendas such as the Sustainable Development Goals (SDGs) of the United Nations (UN). Solar energy -- among other clean, renewable, and sustainable energies -- is seen as essential for environmental, social, and economic sustainability. Predicting solar energy accurately is critical to increasing reliability and stability, and reducing the risks and costs of the energy systems and markets. Researchers have come a long way in developing cutting-edge solar energy forecasting methods. However, these methods are far from optimal in terms of their accuracies, generalizability, benchmarking, and other requirements. Particularly, no single method performs well across all climates and weathers due to the large variations in meteorological data. This paper proposes SENERGY (an acronym for Sustainable Energy), a novel deep learning-based auto-selective approach and tool that, instead of generalising a specific model for all climates, predicts the best performing deep learning model for GHI forecasting in terms of forecasting error. The approach is based on carefully devised deep learning methods and feature sets through an extensive analysis of deep learning forecasting and classification methods using ten meteorological datasets from three continents. We analyse the tool in great detail through a range of metrics and methods for performance analysis, visualization, and comparison of solar forecasting methods. SENERGY outperforms existing methods in all performance metrics including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Forecast Skills (FS), Relative Forecasting Error, and the normalised versions of these metrics. The proposed auto-selective approach can be extended to other research problems such as wind energy forecasting and predict forecasting models based on different criteria (in addition to the minimum forecasting error used in this paper) such as the energy required or speed of model execution, different input features, different optimisations of the same models, or other user preferences.

Cytochrome P450 oxidoreductase (POR) is the redox partner of steroid and drug-metabolizing cytochromes P450 located in the endoplasmic reticulum. Mutations in POR cause a broad range of metabolic disorders. The POR variant rs17853284 (P228L) identified by genome sequencing has been linked to lower testosterone levels and reduced P450 activities. We expressed POR wild type and the P228L variant in bacteria, purified the proteins, and performed protein stability and catalytic functional studies. Variant P228L affected the stability of the protein as evidenced by lower unfolding temperatures and higher sensitivity to urea denaturation. A significant reduction of small molecule metabolism was observed with POR P228L while activities of CYP3A4 were reduced by 25%, and activities of CYP3A5, and CYP2C9 were reduced by more than 40% compared to WT POR. The 17,20 lyase activity of CYP17A1 responsible for production of main androgen precursor dehydroepiandrosterone, was reduced to 27% of WT in presence of P228L variant of POR. Based on in silico and in vitro studies we predict that the change of proline to leucine may change the rigidity of the protein, causing conformational changes in POR, leading to altered electron transfer to redox partners. A single amino acid change can affect protein stability and cause a severe reduction in POR activity. Molecular characterization of individual POR mutations is crucial for a better understanding of the impact on different redox partners of POR.

In the context of cognitive radio, smart city and Internet-of-Things, the need of advanced radio spectrum monitoring becomes crucial. However, surveillance of a wide frequency band without using extremely expensive high sampling rates devices is a challenging task. The recent development of compressed sampling approaches offers a promising solution to these problems. In this context, the Modulated Wideband Converter (MWC), a blind sub-Nyquist sampling system, is probably the most realistic approach and was successfully validated in real-world conditions. The MWC can be realized with existing analog components and there exist calibration methods which are able to integrate the imperfections of the mixers, filters and ADCs, hence allowing its use in real-world. The MWC underlying model is based on signal processing concepts such as filtering, modulation, Fourier series decomposition, oversampling and undersampling, spectrum aliasing, and so on, as well as in-flow data processing. In this paper we develop an MWC model which is entirely based on linear algebra, matrix theory and block processing. We show that this approach has many interests: straightforward translation of mathematical equations into simple and efficient software programming, suppression of some constraints of the initial model, and providing a basis for the development of an extremely fast system calibration method. With a typical MWC acquisition device we obtained a speed up of a factor greater than 20 of the calibration computation time, compared with a previous implementation.

Background: Young adults, particularly university students might be at greater risk of developing psychological distress, and exhibiting symptoms of anxiety and depression during the COVID-19 pandemic. Objective: The primary objective of this study was to explore and compare the determinants and predictors of mental health (anxiety and depression) during and after COVID-19 lockdown among university students. Methods: This was an observational, cross-sectional study with a sample size of 417 students. An online survey utilizing International Physical Activity Questionnaire–Short Form (IPAQ-SF), General Anxiety Disorder–7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) was distributed to Universiti Tunku Abdul Rahman students via Google forms. Results: During lockdown, family income [χ² (1, n=124) = 5.155, p=0.023], and physical activity [χ² (1, n=134) = 6.366, p=0.012] were associated with anxiety, while depression was associated with gender [χ² (1, n=75) = 4.655, p=0.031]. After lockdown, family income was found to be associated with both anxiety [χ2 (1, n=111) = 8.089, p=0.004], and depression [χ2 (1, n=115) =9.305, p=0.002]. During lockdown, family income (OR=1.60, p=0.018), and physical activity (OR=0.59, p=0.011) were predictors for anxiety, and gender (OR=0.65, p=0.046) being the only predictor for depression. After lockdown, family income was a predictor for both anxiety (OR=1.67, p=0.011), and depression (OR=1.70, p=0.009). Conclusion: Significant negative effects attributed to the COVID-19 lockdown, and certain factors predisposed to the worsening of mental health status in university students. Family income, physical activity level, and gender were some of the major determinants that influenced the anxiety and depression.

The ability to directly look into genome sequences has opened great opportunities in plant breeding. Yet, the assembly of full-length chromosomes remains one of the most difficult problems in modern genomics. Genetic maps are commonly used in de novo genome assembly and are constructed on the basis of a statistical analysis of the number of recombination rather than physical distance in base pairs. This may affect the accuracy of the ordering and orientation of scaffolds within the chromosome, especially in the region of recombination suppression. Here we report the use of Tyr-FISH for validation of genetic and pseudochromosome maps. For probe design we developed a pipeline that is based on selection of a unique sequence with minimal potential fluorescent background arising from non-specific in situ hybridization. In total of 24 unique genes were located on physical chromosomes 2 and 6. The order of markers has been corrected by integration genetic and cytogenetic maps. Tyr-FISH mapping showed that the order of 23.1% (chromosome 2) and 27.3% (chromosome 6) of the tested genes differed between physical chromosomes and pseudochromosomes. Also the position of the mlh1 gene, which was not on the genetic map, was defined on physical chromosome 2. The results suggest the possibility of Tyr-FISH mapping of any gene that may not be neither on the genetic map nor in the assembly. Hence, Tyr-FISH provides valuable information for the improvement of the genome assembly.

To scientifically and effectively evaluate the service capacity of expressway service areas (ESAs) and improve the management level of ESAs, we propose a method for the recognition of vehicles entering ESAs (VeESAs) and estimation of vehicle dwell times using ETC data. First, the ETC data and their advantages are described in detail, and then the cleaning rules are designed according to the characteristics of the ETC data. Second, we established feature engineering according to the characteristics of VeESA, and proposed the XGBoost-based VeESA recognition (VR-XGBoost) model. Studied the driving rules in depth, we constructed a kinematics-based vehicle dwell time estimation (K-VDTE) model. The field validation in Part A/B of Yangli ESA using real ETC transaction data demonstrates that the effectiveness of our proposal outperforms the current state of the art. Specifically, in Part A and Part B, the recognition accuracies of VR-XGBoost are 95.9% and 97.4%, respectively, the mean absolute errors (MAEs) of dwell time are 52 s and 14 s, respectively, and the root mean square errors (RMSEs) are 69 s and 22 s, respectively. In addition, the confidence level of controlling the MAE of dwell time within 2 minutes is more than 97%. This work can effectively identify the VeESA, and accurately estimate the dwell time, which can provide a reference idea and theoretical basis for the service capacity evaluation and layout optimization of the ESA.

Background: Anemia is one of the most frequent diseases worldwide, affecting a third of the general population. Anemia in general and in particular, iron-deficient anemia (IDA), has been associated to a higher risk of thrombotic manifestations, including ischemic stroke and cerebral venous thrombosis (CVT), as well as systemic extra cerebral arterial and venous thrombosis. Despite these data, anemia is seldom considered as an etiological factor of stroke. Methods: An individual case encompassing all known neurovascular and systemic arterial and venous thrombotic manifestations related to IDA is presented with the focus on clinical reasoning issues in the diagnostic pathways, starting from the neuroradiological signs. The main questions have been identified and addressed in a narrative review of the most relevant data in the literature from a pragmatic and clinical viewpoint. Results and Discussion: The presented case concerns a 46 years old man admitted to the Stroke Unit because of acute is-chemic stroke with multiple thrombi in large intracranial and extracranial vessels, multifocal ischemic lesions in several arterial territories and the concurrent finding of asymptomatic CVT, pulmonary embolism with lung infarction and aortic thrombosis. An extended diagnostic work-up excluded the main etiologies (arterial dissection, cardiac embolism, genetic and acquired prothrombotic disorders, as cancer and antiphospholipid syndrome), except for a severe IDA, such as to require blood transfusions followed by anticoagulant therapy for the several thrombotic manifestations. Neuroimaging and systemic vascular findings have been analyzed and the main issues proposed by the case in the diagnostic pathway have been identified and discussed in a pragmatic clinical road map reviewing the data provided by the literature. Conclusions: IDA is a common but treatable condition that, independently or synergically, may increase the risk of thrombotic events. The diagnostic and therapeutic approach has not yet defined and each case should be individually addressed in a pragmatic clinical road map.

Background Nitrous Oxide (N₂O) is a dissociative anaesthetic that is sometimes used recreationally. The prevalence of N₂O use is difficult to quantify but appears to be increasing. Research on N₂O harms and application of harm reduction strategies are limited. The aim of this mixed method systematic review was to collate and synthesise the disparate body of research on recreational nitrous oxide use to inform harm reduction approaches tailored for young people. Methods To identify publications reporting recreational use of N₂O, a search of public health, psychology and social science databases was conducted. Databases included PubMed, CIHNAL, PsycINFO, Scopus and Web of Science. Gray literature and Google advanced search were also used. Due to limited published literature on the recreational use of N₂O, no limit was placed on publication date or study type. A thematic synthesis extracted descriptive and analytical themes from the selected studies. Quality appraisal was conducted using the CASP Tool for Qualitative studies and the Joanna Briggs Institute case report assessment tool Results The search retrieved 407 reports. Thirty-four were included in the final analysis including sixteen case reports. The included studies were primarily concerned with raising awareness of the apparently increasing use and subsequently increasing harms of recreational N₂O use. There was limited reference to policy or legislative responses in any published studies, no suggestions for harm reduction strategies or application of service level responses. In general, individuals lack awareness of N2O related harms. Conclusion The review found three key areas that deserve further consideration including: 1) policy, 2) service delivery, and 3) harm associated with N₂O use. We recommend a top-down (policy) and bottom-up (services delivery/services users) approach to harm reduction for N₂O use which also includes further consultation and research with both groups. Future research could explore young people’s experience of N₂O use including benefits and problems to inform contextually relevant harm reduction strategies.

Close to half (45.4%) of 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined on the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

Invasive weeds cause significant crop yield and economic losses in agriculture. The highest in-direct impact may be attributed to the role of invasive weeds as virus reservoirs especially within the commercial growing areas. The new tobamovirus tomato brown rugose fruit virus (ToBRFV), recently identified in the Middle-East, overcomes the Tm-22 resistance allele in the cultivated tomato varieties grown in greenhouses. In this study, we determined the role of invasive weed species as potential hosts for ToBRFV and pepino mosaic virus (PepMV). Out of all tested weed species, the invasive species So-lanum elaeagnifolium and S. rostratum, mechanically inoculated with ToBRFV, were positive for To-BRFV in both enzyme linked immunosorbent assay (ELISA) and RT-PCR tests. S. rostratum was also positive for PepMV. No conspicuous phenotype was observed on ToBRFV infected S. elaeagnifolium plants suggesting a hostplant associated defense response. S. rostratum plants inoculated with either ToBRFV alone or a mixture of ToBRFV and PepMV-IL, contained high ToBRFV levels. In addition, when inoculated with ToBRFV or PepMV-IL disease symptom manifestations were observed in S. rostratum plants and the symptoms were exacerbated upon mixed infections with both viruses. The distribution and abundance of both Solanaceae species increase the risks of virus transmission between species.

Infectious bronchitis virus (IBV) is a highly variable RNA virus that affects chickens worldwide. Due to its inherited tendency to suffer point mutations and recombination events during viral replication, emergent IBV strains have been linked to nephropathogenic and reproductive disease that are more severe than the typical respiratory disease, leading, in some cases, to mortality, severe production losses, and/or unsuccessful vaccination. QX and DMV/1639 strains are examples of the above-mentioned IBV evolutionary pathway and clinical outcome. In this study, our purpose was to systematically compare whole genomes of QX and DMV strains looking at each IBV gene individually. Phylogenetic analyses and amino acid site searches were performed in datasets obtained from GenBank accounting for all IBV genes and using our own relevant sequences as a basis. The QX dataset studied is more genetically diverse than the DMV dataset, partially due to the greater epidemiological diversity within the five QX strains used as a basis compared to the four DMV strains from our study. Historically, QX strains have emerged and spread earlier than DMV strains in Europe and Asia. Consequently, there are more QX sequences deposited in GenBank than DMV strains, assisting in the identification of a larger pool of QX strains. It is likely that a similar evolutionary pattern will be observed among DMV strains as they develop and spread in North America.

Digital medicine based on the integration of all medical data of a particular patient, has become a reality today, thanks to information technology. Traditional medical examinations can be supple-mented by assessment results of the oxidative-anti-oxidative (OAO) status of the body [1]. Elec-trochemical sensors are able to not only determine the integral indicators of the OAO system of the body, but also to depict details of the processes occurring in the system. The main obstacle to the widespread use of electrochemical sensors in medical diagnostics is the extremely small amount of the received information in comparison with tens of thousands of known human dis-eases. The problem can be eliminated only by rethinking the purpose of electrochemical measure-ment within the framework of thermodynamics of information processes and information theory. In the information paradigm of electrochemical analysis of biological fluids, a sample is considered as an electrochemical message created by a sensor. The purpose of electrochemical measurement is to obtain information in a volume sufficient to identify the sample composition within the range of possible concentrations of its components. The fundamentals of the thermodynamics of infor-mation processes are considered and conclusions that are of practical importance for the devel-opment of electrochemical sensors and analyzers are derived. It is shown that potentiostatic con-trol of the sensor is physically impacted by the electromechanical instability of the electrical double layer, which is the main source of sensor signal noise. Estimates are of a minimum amount of an-alytical signal information required for identification of a sample of a known composition, such as a biological fluid, are provided. Examples of highly informative analytical signals for flowing and stationary samples are presented. Problems related to the visualization of such signals are noted.

Electric vehicles offer a means to reduce greenhouse gas emissions in passenger transport. The availability of reliable charging infrastructure is crucial for the successful uptake of electric vehicles in dense urban areas. In a pilot project in the city of Hamburg, Germany, public charging infrastructure is equipped with a reservation option providing exclusive access for local residents and businesses. The present paper combines quantitative and qualitative methods to investigate the effects of the newly introduced neighborhood charging concept. We use a methodology combining a quantitative questionnaire survey and qualitative focus group discussions as well as the analyses of charging infrastructure utilization data. Results show that inner-city charging and parking options are of key importance for (potential) users of electric vehicles. Hence, the neighborhood concept is rated very positively. Providing guaranteed charging and parking facilities are therefore likely to increase the stock of EVs. On the other hand, these could to a large extent be additional cars with consequential disadvantages. The study shows that openly accessible infrastructure is presently utilized much more intense than the exclusive option. Consequentially, the concept evaluated should be part of an integrated approach managing parking and supporting efficient concepts like car sharing.

It is one of the central goals of cognitive neuroscience to understand how structure and function relate in the brain. We review how cognitive function characterization has been approached in the past. In addition, we examine the ongoing efforts, as well as the implications for the future. Clinical studies on patients with lesions have provided key insights into the relationship between brain areas and behavior over the past century. We describe cognitive function according to localization considering these early efforts for characterization. We chose a perceptual-cognitive function, namely body perception, to describe our current efforts. Using body perception as an example, we summarize contemporary techniques. Finally, we outline the trajectory of current progress into the future and discuss the implications for clinical and basic neuroscience.

Background: Hypereosinophilic syndromes (HES) are a group of relatively rare disorders in which neurological manifestations are not uncommon including ischemic stroke. The hypothesized pathophysiological mechanisms are hypercoagulability, cardioembolism (mainly mediated by myocardial involvement) and damage to the endothelium. A variable ischemic pattern has been described, including an association of territorial and border zone ischemic stroke. Methods: Three patients who presented to our department with acute stroke were selected aiming to show these three different mechanisms inferred from the stroke pattern on brain Magnetic Resonance Imaging (MRI) and to simultaneously illustrate the three main causes of HES. Results and Discussion: The first patient is a 55-year-old man with an abrupt onset of aphasia due to an acute ischemic stroke involving the left parietal lobule and the angular gyrus; recent lab test had shown hypereosinophilia. An extensive workup excluded primary and secondary causes of hy-pereosinophilia so a diagnosis of idiopathic hypereosinophilia was formulated and he was treated with high doses of steroids. The second patient had severe hypereosinophilia and developed multiple small scattered ischemic lesions, mainly in watershed zones. The history of severe asthma and recurrent sinusitis supported the diagnosis of EGPA (Eosinophilic Granulomatosis with Polyangiitis); considering the severe clinical conditions and the presumptive role of hypereo-sinophilia in determining her symptoms, steroid treatment was promptly started, with good clinical response. The third patient also presented with multiple metachronous ischemic lesions, both in cortical and watershed distribution and marked eosinophilia; the diagnostic work-up found an ovarian cancer. She was treated with steroids and then underwent surgery and adjuvant chemotherapy. Conclusions: HES should be considered in stroke etiological evaluation, although it is a rare disorder, and border zones pattern on neuroimaging is quite suggestive. A thorough research of the sources of hypereosinophilia should be performed to select the appropriate therapy.

In this paper, we study the deflection angle for wormhole-like static aether solution by using Gibbons and Werner technique in non-plasma, plasma and dark matter mediums. For this purpose, we use optical spacetime geometry to calculate the Gaussian optical curvature, then implement the Gauss-Bonnet theorem in weak field limits. Moreover, we compute the deflection angle by using a technique known as Keeton and Petters technique. Furthermore, we analyze the graphical behaviour of the bending angle ψ with respect to the impact parameter b, mass m as integration constant and parameter q in non-plasma and plasma mediums. We examine that deflection angle is exponentially increasing as direct with charge. Also, we observe that for small values of b, ψ increases and for large values of b the angle deceases. We also considered an analysis to the shadow cast of the wormhole relative to an observer at various locations. Comparing it the the Schwarzschild shadow, shadow cast is possible for wormhole as r<2m. At r>2m, the Schwarzschild is larger. As r → ∞, we have seen that the behavior of the shadow, as well as the weak deflection angle, approaches that of the Schwarzschild black hole. Overall, the effect of plasma tends to decrease the value of the observables due to the wormhole geometry.

Africa’s water needs are often supported by eutrophic waterbodies dominated by cyanobacteria posing health threats to riparian populations from cyanotoxins, and Lake Victoria is no exception. In two embayments of the lake (Murchison Bay and Napoleon Gulf), cyanobacterial surveys were conducted to characterize the dynamics of cyanotoxins in lake water and water treatment plants. Forty-six cyanobacterial taxa were recorded and out of these 14 were considered potentially toxigenic (i.e., from the genera Dolichospermum, Microcystis, Oscillatoria, Pseudanabaena and Raphidiopsis). A higher concentration (ranging from 5-10 µg MC-LR equiv. L-1) of microcystins (MCs) was detected in Murchison Bay compared to Napoleon Gulf, with a declining gradient from the inshore (max. 15 µg MC-LR equiv. L-1) to the open lake. In Murchison Bay, an increase either in Microcystis sp. biovolume and MC was observed over the last two decades. Despite high cell densities of toxigenic Microcystis and high MC concentrations, the water treatment plant in Murchison Bay efficiently removed the cyanobacterial biomass, intracellular and dissolved MC to below the lifetime guideline value for exposure via drinking water (&lt; 1.0 µg MC-LR equiv. L-1). Thus, the potential health threats stem from the consumption of untreated water and recreational activities, along the shores of the lake embayments. MC concentrations were predicted from Microcystis cell numbers regulated by environmental factors such as solar radiation, wind speed in the N-S direction and turbidity. Thus, an early warning through microscopical counting of Microcystis cell numbers is proposed to better manage health risks from toxigenic cyanobacteria in Lake Victoria.

The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), etiological agent of the novel coronavirus disease 2019 (COVID-19), has spread since December 2019, resulting in massive health and economic crisis worldwide. While efforts to stop the pandemic are crucial, collecting epidemiological data to help manage current and future pandemics will be important. In addition to humans, serological and molecular based studies have demonstrated SARS CoV-2 exposure in several wild, domestic and farmed animals. For examples Shriner and the team showed serologically an exposure of 40% to the white deer living in close proximity to urban centers. Additional reports have also emerged of susceptibility of animal’s species like cats, ferrets, raccoon dogs, cynomolgus macaques, rhesus macaques, white-tailed deer, rabbits, Egyptian fruit bats, and Syrian hamsters to SARS-CoV-2 infection.. It’s worth emphasizing that these reports are based on experimental data mostly derived from Europe, USA, South America and parts of Asia. In limited instances natural infections of SARS-CoV-2 have been reported in pet dogs, cats, tigers, lions, snow leopards, pumas, gorillas at zoos and farmed mink and ferrets. The presence of the virus in animal species and an understanding of whether these are natural or recent human to animal transmissions is important. It’s possible that such transmission could passage the virus or subject the virus to a different immunological pressure thereby helping with the development of viral variants in addition to being a host for future reservoirs of the virus. In Kenya SARS-CoV-2 was first detected on March 12th 2020 from imported human cases of persons who had travelled from the United States. This was followed by detection of imported cases majorly from China, Sweden and United Kingdom. Later infections were confirmed in Nairobi and Mombasa suggesting further cases of disease importations through the major ports of entry. However, no comparable data on animal exposure have hitherto been generated in Kenya. To address this key concern, we focused on three objectives; 1) development of a robust antibody ELISA based on crude SARS-CoV-2 lysate. 2) SARS-CoV-2 serology of domestic animals in Kenya. 3) Corroboration of the crude lysate based seroprevalence data and a commercial ELISA kit based on the Spike receptor binding domain (RBD) antigen. Our sample set included camel sera (both pre- & post outbreak sera), as well as sera from cats and dogs collected at the peak of the pandemic. Our results using the ELISA based on crude SARS-CoV-2 lysate indicated SARS-CoV-2 antibodies in camels (71%, N=145), cats 11% (N=16) and dogs (81%, N=36) with varying titer levels. These findings were comparable to those obtained using the commercial ELISA kit based on the spike RBD antigens. In summary, the data warrants two key conclusions: (i) we have demonstrated that the crude lysate ELISA allows for SARS-CoV-2 antibody detection, and given its potential to offer robust detection could be applied for initial mass screening (ii) although the current study cannot disentangle the relative contributions of antigenic cross-reactivity, pre-pandemic exposure to SARS-CoV-2 or human-animal transmission, it nonetheless demonstrates for the first time the prevalence of SARS-CoV-2 like antibodies in domestic and wild animals in Kenya. Our findings set the scene for further research into the prevalence of SARS-CoV-2 in domestic and wild animals to understand their potential epidemiological implications.

External stressors strongly increase cardiovascular activity and induce metabolic changes that ensure the availability of glucose and oxygen as part of a co-ordinated stress response. Exposure to stress during early life appears to have an exaggerated long-term effect on this response, leading to an increased risk or cardiometabolic disorders. Here we demonstrate that acute stress induced glucose release is impacted by the early life environment in rodent maternal deprivation and early-life infection models and this was validated in our EpiPath human early-life adversity cohort. In all three models differences in baseline blood glucose levels after ELA exposure were sex dependent. The human ELA model showed higher levels of basal glucose in females, similar to the mouse infection and rat maternal deprivation models. We anticipated that the stress induced glucose rise would be a GC dependent process. However, the kinetics of stress-induced glucose release, peaking 15-28 minutes before cortisol suggest that it is a GC-independent process. We confirmed this by administering an escalating dose of cortisol to a health human cohort, and the inability of an intravenous GC bolus induce a glucose rise in man confirms that it is a rapid, GC independent, process.In conclusion, we provide a novel perspective on the mechanisms behind stress related metabolic changes and highlights the importance of collecting early life data as a measure to understand an individual’s metabolic status in a better light.

State transition in the multiple-levels system has the great potential applications in the quantum technology. In this article we employ a deterministic approach in complex space to analyze the dynamics of the 1s-2p electron transition in the hydrogen atom. The electron’s spin motion is embodied in the framework of quantum Hamilton mechanics that allows us to examine the transition dynamics more precisely. The transition is driven by an oscillating electric field in the z-direction. The electron’s transition process can be visualized by monitoring its motion in the complex space. The quantum potential and the total energy proposed in this paper provide new indices to observe the dynamic changes of electrons in the transition process.

In the present study we introduce a deterministic mathematical model in order to study the interaction between the human immune system and a virus, like COVID 19. The mathematical analysis is based on the tools of dynamical systems theory, by modeling the interactions between the immune system and the virus, using a predator-prey method and following the ideas of G. Moza, from \cite{TGV}. It will be obtained some conclusions with medical relevance and the main three of them are the followings: 1) A deficiency of a single type of immunity in the early stages of virus proliferation, may lead to a large virus multiplication and the human body can loses the fight against this virus; 2) If the level of all components of the immunity system are at the normal threshold from the first moment of the infection and the immune system kill the virus at higher rate than the rate of virus reproduction, then the human body has the ability to stop the multiplication of the virus and liquidate it, that means the virus will be destroyed; 3) If the level of at least one type of immunity can be increased beyond the normal threshold, by medical interventions (like vaccination) in the early stages of virus infection, then the immune system has a better chance to win the fight with the virus.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known globally as COVID-19, originated in December 2019 in Wuhan, Hubei province in China and has rapidly spread across the globe ever since. The first recorded case in sub-Saharan Africa was in Nigeria, on the 25th February, 2020. The virus continues to spread, and new variants of the disease have emerged, the number of deaths and new infections in the countries of sub-Saharan Africa has been relatively low compared to predictive models. This could be due to several factors, such as slower transmission dynamics of the virus, a lower-case fatality rate, or a lack of testing or reliable data. Whilst this may also, in part, be due to the robustness of the nations' public health responses, there is scarce reporting on the specifics of this. However, emerging research has demonstrated that various environmental factors could influence virus transmission. The study adopted collected meteorological data that was critically analysed and discussed. The impact of three factors in the context of sub-Saharan African nations: temperature, ultraviolet (UV) exposure and pre-existing infection with Plasmodium (malaria) were discussed. These factors were discussed critically in light of the reduced rates of transmission and mortality observed.

Complex problem-solving (CPS) tasks have become an increasingly popular tool for understand-ing and assessing cognitive ability. These tasks have been repeatedly shown to be predictors of academic and workplace success above and beyond traditional measures of general intelligence and fluid intelligence. To date, there has been little exploration of the underlying mechanisms that drive this additional predictive utility. In this study, we examined the role of a variety of non-cognitive personality and investment traits that could drive performance on CPS tasks. Adult participants (n = 152) were recruited via M-Turk and completed a battery of personality and in-vestment trait measures, a measure of general mental ability, and a 61-trial microworlds-style CPS task. Generalised linear mixed-effects models revealed a wide variety of personality and in-vestment traits influenced task performance above and beyond general mental ability. Specifical-ly, two clusters of traits emerged as important determinants of performance: one cluster that in-fluenced the capacity to deal with the introduction of system randomness (Conscientiousness and Extraversion) and one cluster that influenced the capacity to deal with the introduction of system delays (NFC, Learning Goal Orientation, and Intellect). These findings suggest that CPS tasks do capture more than just general mental ability and may be good predictors of academic and workplace success because they tap into both cognitive ability and the motivation and willingness to engage in cognitive exploration and mental effort.

Intercropping systems can flexibly use resources such as sunlight, heat, water, and nutrients in time and space, improve crop yield and land utilization rates, effectively reduce continuous cropping obstacles and the occurrence of diseases and insect pests, and control the growth of weeds. Thus, intercropping is a safe and efficient ecological planting mode. The legume–cereal intercropping system is the most common planting combination. Legume crops fix nitrogen from the atmosphere through their symbiotic nitrogen fixation abilities, and the fixed nitrogen can be transferred to and utilized by cereal crops in various ways. The symbiotic nitrogen fixation efficiency of legume crops was improved by reducing the inhibition of soil nitrogen on nitrogenase activity through competitive absorption of soil nitrogen. However, the effects of nitrogen transformation and distribution in intercropping systems, and microbial community structure characteristics on nitrogen transfer need to be further explored. In this review, ⅰ) we present the transformation and distribution of nitrogen in the legume–cereal intercropping system; ⅱ) we describe the soil microbial community characteristics in intercropping systems; and ⅲ) we discuss the advantages of using modern biological molecular techniques to study soil microorganisms. We conclude that intercropping can increase the diversity of soil microorganisms, and the interaction between different plants has an important impact on the diversity and composition of the bacterial and fungal communities. The extensive application of modern biological molecular techniques in soil microbial research and the great contribution of intercropping systems to sustainable agriculture are particularly emphasized in this review.

The blood brain barrier (BBB) is an essential component in regulating and maintaining the homeostatic microenvironment of the central nervous system (CNS). During the occurrence and development of glioblastoma (GBM), BBB is pathologically disrupted with markedly increased permeability. Due to the obstruction imposed by the BBB, strategies currently employed for GBM therapeutics still obtain a very low success rate and lead to systemic toxicity. Moreover, chemotherapy could promote pathological BBB functional restoration, accompanied with a prominent decrease of intracerebral therapeutics transportion during GBM multiple administration, resulting in chemotherapy failure for GBM treatment. The effective delivery of therapeutics into the brain still faces with severe challenges. Regulation of pathological BBB for enhanced transporting of therapeutics across the barrier may provide new opportunities for effective and safe treatment of GBM. This article reviews the structure and function of BBB in physiological state, the mechanisms underlying BBB pathological fenestration during the development of GBM, and the therapeutic strategies of GBM based on BBB intervention and therapeutic drugs transporting across the BBB.

Background: Dengue is the most common arthropod-borne sickness worldwide, impacting at least 50 million people each year. The dengue virus has four primary serotypes. Infection with one serotype confers homotypic immunity but not heterologous immunity, and secondary infections may be more severe. Although blood transfusions and organ donations have also been observed, the Aedes aegypti mosquito is the primary vector for the transmission of dengue. Infection causes a continuum of clinical illness, from asymptomatic infection to dengue fever, DHF, and dengue shock syndrome (DSS).Aim: To assess the presence of anti DENV IgG and anti DENV IgM antibodies specific to the four dengue serotypes in blood donor service donors and the importance of pre-donation screening in routine blood collection procedures.Method: 3 mL of peripheral venous blood from 507 blood donors was collected in tubes with BD vacutainer gel tube for serum separation after epidemiological records were reviewed. After that, serum was separated and tests were performed by SD Bioline Dengue Duo. Participants in the study completed a social and epidemiological questionnaire that contained information such as age, gender, and dengue diagnosis.Result: Out of the 507 blood samples that were taken, 473 (93.3%) came from male blood donors, while the remaining 34 (6.7%) belonged to female blood donors. The ratio of males to females is 13.91 to 1. The age range is 18–60 years, and the mean and standard deviation are both 27.7 and 6.5. 183 of the 507 samples produced anti DENV IgG positivity, while 324 did not. The ratio of positive to negative was 1.25:2.Conclusion: According to the findings of this study, quantitative methods for determining the presence of anti-dengue antibodies or detecting the dengue virus in blood donors in endemic areas should be devised in order to ensure the quality of blood transfusions.

Pompeii was connected to the great Serino aqueduct under the principate of Augustus. From that moment on, water became not only a precious resource for the inhabitants but also their true social indicator. It is no coincidence, in fact, that the concentration of sumptuous dwellings is in Regio VI, the district closest to the aqueduct reservoir (castellum aquae in Latin) and the one most equipped with piezometric towers, the first of the network, the ones that would never leave the decorative fountains of the peristyles dry. From this observation follows the original possibility of considering the water network a factor that contributed to designating the morphology of urban neighbourhoods and blocks.

By solving a Marchenko equation, Green's functions at an arbitrary (inner) depth level inside an unknown elastic layered medium can be retrieved from single-sided reflection data, which are to be collected at the top of the medium. So far, an exact solution could only be obtained if the medium obeys stringent monotonicity conditions and if all forward-scattered (non-converted and converted) transmissions between the acquisition level and the inner depth level are known a-priori. We introduce an alternative Marchenko equation by revising the window operators that are applied in its derivation. We also introduce an auxiliary equation for transmission data, which are to be collected at the bottom of the medium, and a coupled equation, which is based on both reflection and transmission data. We show that the joint system of the Marchenko equation, the auxiliary equation and the coupled equation can be succesfully inverted when broadband reflection and transmission data are available. This results in a novel methodology for elastodynamic Green's function retrieval from two-sided data. Apart from these data, our approach requires P- and S-wave transmission times between the inner depth level and the top of the medium, as well as two angle-dependent amplitude scaling factors, which can be estimated from the data by enforcing energy conservation.

Crown of thorns starfish (Acanthaster planci) are coral predators with advantages of having toxicity in their venom and tissue regeneration capabilities. With all these characteristics, only a handful of studies have highlighted the association of microorganisms with this organism. Crown of thorns starfish are common in Fiji and their analyses of microbial diversity for secondary metabolites could be of great interest to the scientific community. This study is an attempt to investigate Fijian-based A. planci for their venom and associated actinomycetes antibacterial activity and further identify the type of enzymes present in the crude venom extract. The CoTS venom extract (0.192 g) harbor enzymes such as gelatinase, caesinase, and amylase. An abundant and potent actinomycete strain, represented as FJA1 showed antibacterial activity against Enterococcus faecium with an inhibition zone of 10 mm. Moreover, all pathogenic test microorganisms were resistant against concentrations of 500 µg and 1 mg of A. planci venom extract.

The accumulation of foam cells in arterial intima and the accompanied chronic inflammation are considered major causes of neoatherosclerosis and restenosis. However, both the underlying mechanism and effective treatment for the disease are yet to be uncovered. In this study, we combined transcriptome profiling of restenosis artery tissue and bioinformatic analysis to reveal that NLRP3 inflammasome is markedly upregulated in restenosis and that several restenosis re-lated DEGs are also targets of mulberry extract, a natural dietary supplement used in traditional Chinese medicine to improve liver vitality. Further pathway enrichment analysis identified MAPK signaling pathway to be involved in the inflammatory response of foam cells. Consistently, immunofluorescence microscopy shows co-localization of NLRP3 with CD68+ macrophages. We then evaluated the efficacy of mulberry extract in inhibiting both the formation of foam cells and their inflammatory response. We demonstrated that mulberry extract suppresses the formation of ox-LDL induced foam cells, possibly by upregulating the cholesterol efflux genes ABCA1 and ABCG1 to inhibit intracellular lipid accumulation. In addition, mulberry extract dampens NLRP3 inflammasome activation by stressing the MAPK signaling pathway. Collectively, our mecha-nistic and functional studies unveil the therapeutic value of mulberry extract in neoatherosclerosis and restenosis treatment by regulating lipid metabolism and inflammatory response of foam cells.

Sun glint, i.e., direct solar radiation reflected from a water surface, negatively affects the accuracy of ocean color retrieval schemes if entering the field-of-view of the observing instrument. Herein, a simple and robust method to quantify the sun glint contribution to top-of-atmosphere (TOA) reflectances in the visible (VIS) and near-infrared (NIR) is proposed, exploiting concomitant observations of the sun glint’s morphology in the shortwave infrared (SWIR) characterized by reflectance contrasts typically higher than those resulting from other in-water or atmospheric processes. The proposed method, termed Glint Removal through Contrast Minimization (GRCM), requires high spatial resolution (ca. 10–50 m) imagery to resolve the sun glint’s characteristic morphology, meeting additional criteria on radiometric resolution and temporal delay between the individual band’s acquisitions. It has been applied with good success to a selection of Landsat 8 (L8) Operational Land Imager (OLI) scenes encompassing a wide range of environmental conditions in terms of observation geometry and glint intensity, as well as aerosol and Rayleigh optical depth. The method proposed herein is entirely image based and does not require ancillary information on the sea surface roughness or related parameters (e.g., surface wind), neither the presence of clear water areas in the image under consideration. Limitations of the proposed method are discussed, and its potential for sensors other than OLI and applications beyond glint removal is sketched.

The contribution deals with the selection of progressive methods and technologies to improve the management of production processes in the industrial area. The first chapter of the contribution summarises the theoretical starting points for the management of production processes and their progressive concepts. Chapter 2 deals with the analysis of the current state of play in the use of methods and technologies in production management and summarise its problem areas. Chapter 3 presents the design of a system for selecting the appropriate method and technology to improve the management of the production process. The system presented is designed from data collection blocks, a benchmark for the performance of industrial enterprises' production processes, and data mining to gain knowledge of the impact of the methods and technologies used on the performance of production processes. The last block of the system allows the presentation of the obtained results, which sets out the recommendation for the choice of progressive method and technology. The system is partially verified in the last chapter of the contribution.

The athletic performance and safety of racehorses is influenced by hoof-surface interactions. This intervention study assessed the effect of eight horseshoe-surface combinations on hoof acceleration patterns at impact and foot-off in 14 galloping Thoroughbred racehorses retired from racing. Aluminium, barefoot, GluShu (aluminium-rubber composite) and steel shoeing conditions were trialled on turf and artificial (Martin Collins Activ-Track) surfaces. Shod conditions were applied across all four hooves. Tri-axial accelerometers (SlamStickX, range ±500 g, sampling rate 5000 Hz) were attached to the dorsal hoof wall (x: medio-lateral, medial=positive; y: along dorsal hoof wall, proximal=positive; z: perpendicular to hoof wall, dorsal=positive). Linear mixed models assessed whether surface, shoeing condition or stride time influenced maximum (most positive) or minimum (most negative) accelerations in x, y and z directions, using ≥40,691 strides (significance at p&lt;0.05). Day and horse-rider pair were included as random factors and stride time as a covariate. Collective mean accelerations across x, y and z axes were 22–98 g at impact and 17–89 g at foot-off. Mean stride time was 0.48 ± 0.07 s (mean ± 2 s.d.). Impact accelerations were larger on turf in all directions for forelimbs and hindlimbs (p≤0.015), with the exception of forelimb z-minimum, and in absolute terms maximum values were typically double minimum values. Surface-type affected all foot-off accelerations (p≤0.022), with the exception of hindlimb x-maximum; for example, there was an average increase of 17% in z-maximum across limbs on the artificial track. Shoe-type influenced all impact and foot-off accelerations in forelimb and hindlimb datasets (p≤0.024), with the exception of hindlimb impact y-maximum. Barefoot hooves generally experienced the lowest accelerations. Stride time affected all impact and foot-off accelerations (p<0.001). Identifying factors influencing hoof vibrations on landing and hoof motion during propulsion bears implication for injury risk and racing outcomes.

Studies have previously described the occurrence of multidrug-resistant (MDR) Escherichia coli in human and veterinary medical settings, livestock, and, to a lesser extent, in the environment and food. While they mostly analyzed foodborne E. coli regarding phenotypic and sometimes genotypic antibiotic resistance and basic phylogenetic classification, we have limited understanding of the in vitro and in vivo virulence characteristics and global phylogenetic contexts of these bacteria. Here, we investigated an E. coli strain (PBIO3502) isolated from a pork sausage in Germany in 2021 in-depth. Whole-genome sequence analysis revealed sequence type (ST)58, which is an emerging international high-risk clonal lineage. In addition to its MDR phenotype that mostly matched the genotype, PBIO3502 demonstrated pronounced virulence features, including in vitro biofilm formation, siderophore secretion, serum resilience, and in vivo mortality in Galleria mellonella larvae. Along with the genomic analysis indicating close phylogenetic relatedness of our strain with publicly available, clinically relevant representatives of the same ST, these results suggest the zoonotic and pathogenic character of PBIO3502 with the potential to cause infection in humans and animals. Also, our study highlights the necessity of the One Health approach while integrating human, animal, and environmental health, as well as the role of meat products and food chains in the putative transmission of MDR pathogens.

In northern Thailand, the problem of small particulate matter happens every year, with the pri-mary source being agricultural weed burning and wildfire. The tourism industry is strongly impacted and has been the spotlight for the past few years. Thus, the study aims to investigate the effect of small particulate matter on tourism and related SMEs in Chiang Mai, Thailand. The data was collected from 286 entrepreneurs in the tourism and related SMEs sectors. The data was analyzed using data mining and association rule techniques. The study revealed that small particulate matter has a considerable impact on customer factors, especially the number of customers has decreased. Operational factors and prod-uct/service factors are also affected by the dust in the form of adjustments to keep the business running and the protection of the health of employees and customers. Certainly, financial factors are affected by the small particulate matter situation, both lower revenues and higher costs.

Video segmentation is crucial in a variety of practical applications especially in computer visions. Most of recent works in video segmentation are focusing on Deep learning based video segmentation, there are rooms for improvement in respect of the evolutionary algorithms. This paper aims to propose the novel method to video segmentation by using the optimization of segmentation parameters based on ensemble-based random forest and gradient boosting decision tree. The experimental results show Pareto front of segmentation parameters (hue, brightness, luminance, and saturation). Our optimization model yields accuracy: 85% +/-8.85 % (micro average: 85.00 %), average class precision: 84.88%, and average class recall: 85%. We also show the video segmentation results based on our optimization method and compare our results with Kinect-based video segmentation.

Port cities’ sustainable development can start from innovation in maritime culture to build new urban visions based on the goals of Agenda 2030 and oriented towards local and international cooperation. In the international debate innovative strategies on cultural heritage enhancement contaminate the research and production contexts of ports. In addition, numerous cities have implemented creative and cultural responses to climate change and environmental sustainability. Creativity and cultural heritage enhancement can guide the definition of new trajectories of sustainable urban development, particularly in port-city interaction areas. In Europe, port-city interaction areas have been transformed into laboratories of cultural and creative experimentation for the sustainable management of cultural heritage and the urban quality of public spaces. In this perspective, the paper, starting from the studies developed on the main measurement frameworks of creative cities and sustainable development policies, aims to investigate the possibility of developing a "Port-cities Creative Heritage Enhancement" approach to assess and plan possible cultural and creative transformations of historical-architectural buildings, industrial archaeologies and symbolic urban spaces in the port-city interaction areas of Naples.

In this paper, industrial structure distortion, two-way FDI and carbon emission intensity are brought into a unified research framework, and based on China's panel data from 2011 to 2020, empirical tests are conducted employing Exploratory Spatial Data Analysis (ESDA), spatial econometric model and intermediary effect test. The results show the following. Firstly, China's industrial structure distortion index shows a downward trend. The industrial structure distortion index is the highest in the west, followed by the middle, and the lowest in the East. Secondly, the relationship between carbon emission intensity and economic development shows a "decoupling" effect and keeps decreasing year by year. The spatial disparity is remarkable, showing the pattern of "the east leading, the middle catching up and the west lagging ". At the provincial level, except in Xinjiang province, the carbon emission intensity of other provinces showed different degrees of decline. In terms of spatial distribution, the polarization characteristics of carbon emission intensity are significant, and the traditional spatial distribution pattern has been broken. Thirdly, there is a positive spatial correlation between China's industrial structure distortion, two-way FDI and carbon emission intensity. The distortion of industrial structure will not only lead to the increase of local carbon emission intensity but also produce reverse spillover to adjacent areas. IFDI and OFDI provide a strong driving force for the decline of carbon emission intensity. IFDI promotes the decline of carbon emission intensity in adjacent areas, while OFDI will increase the carbon emission intensity in surrounding areas. The interaction of IFDI and OFDI can significantly reduce the carbon emission intensity of local and adjacent areas. Fourthly, the results of intermediary effect analysis show that two-way FDI is the two channels of industrial structure distortion affecting carbon emission intensity. Industrial structure distortion can affect the transmission mechanism of carbon emission intensity by affecting two-way FDI.

The number of children diagnosed with autism spectrum disorder (ASD) has increased substantially over the past two decades with current research unable to fully account for this dramatic increase in prevalence. One explanation proposes that both intrinsic (e.g., genetic) and extrinsic (e.g., environmental) risk factors may be involved in the etiology of ASD. The goal of this review paper is to explore modifiable pathways for intervention in children at risk for ASD, specifically examining how early social experience may be correlated with epigenetic change in genes associated with autism. We present an innovative model which proposes that polygenic risk and social experience (via epigenetic mechanisms) may both contribute to the observed ASD phenotype. Previous research on genetic, environmental, and epigenetic mechanisms implicated in the etiology of ASD will be reviewed, with an emphasis on the oxytocin receptor gene, which is epigenetically altered by early social experience, plays a crucial role in mammalian social and cognitive development, and is associated with both genetic and epigenetic risk for ASD. Identifying intrinsic (e.g., genetic) and extrinsic (e.g., social experience) risk markers for ASD, a combination of which has not previously been examined, would transform our understanding of this condition, facilitate earlier identification of ASD risk, and guide early intervention efforts. This may have a far-reaching impact on individuals with ASD, their families, and society.

One of matrix equalities composed of multiple products of matrices and their generalized inverses is given by $A_1B_1^{-}A_2B_2^{-} \cdots A_kB_k^{-}A_{k+1}= A$ where $A_1$, $B_1$, $A_2$, $B_2$, $\ldots$, $A_k$, $B_k$, $A_{k+1}$, and $A$ are given matrices of appropriate sizes, and $B_1^{-}$, $B_2^{-}$, $\cdots$, $B_k^{-}$ are generalized inverses of matrices. The cases for $k = 1, 2$ and their special forms were properly approached in the theory of generalized inverses of matrices. In this note, the author presents an algebraic procedure to derive explicit necessary and sufficient conditions for the equality with $k = 3$ to always hold using certain rank equalities for the block matrices constructed by the given matrices, and then mention a key step of extending the previous work to a general situation.

[Research Objective] In the context of the rapid development of digital governance, understanding and analyzing the burden level of digital tools in the process of serving digital governance from multiple perspectives is an important prerequisite for improving the capacity and accuracy of government digital governance, promoting sustainable public participation, and maximizing digital value in the new era. [Research Method] By constructing a model of the burden of digital tools caused by technical, organizational and environmental factors on the public based on the TOE framework, using SPSS for data testing based on 275 research questionnaires, and using fuzzy set qualitative comparative analysis (fsQCA) to explore the linkage ways and paths of the burden-increasing effect of digital tools in a holistic perspective. [Research findings] does not constitute a necessary condition for high levels of digital tool affordances under a single condition, but improving users' digital literacy plays a more general role in optimising the efficiency of digital tool use. According to the results, there are five dominant patterns that have a significant impact, i.e. the driving paths that lead to high levels of digital tool affordability are characterised by a "homogeneous approach". In the cross-group study, significant differences were found in the driving paths of high digital tool affordability by group, depending on the level of digital tool mastery. This paper suggests that the government should continue to pay attention to affordability levels, rationalise the use of financial resources, improve the level of digital tool adaptation, and innovate the existing performance evaluation system for digital governance indicators.

The transport and entanglement of photons is becoming prominent in optics applied to information and quantum computing, where the angular momentum of light stands out in the exchange and inversion of quantized states, with prospects for several technological applications, such as the transport and storage of quantum information. In order to contribute to the understanding of quantized states in photon-matter interaction, we describe a quantized state equation in multidimensional Hilbert space for the diagnosis of OAM states, where probabilities arise in a relativistic setting. It was found that the classical-relativistic variability of the probabilities constitutes a resultant capable of describing the quantized states of light, where the state variable is the variation of the angular momentum of the photon, capable of estimating the orbital angular momentum inversion points at angular incidence. It was found that the chances of finding the quantized states of light at angular incidence can be treated by purely relativistic probabilities, explaining that when both states have equal chances of being found and the angular momentum variation is zero, the source-observer synchronizations occur at the step of increasing relativistic regime of the photon dynamics. We found that the relativistic effect from the perspective of the source referential is able to alter the chances of an event occurring, dilating and contracting the probabilities of finding a quantized state of light at angular incidence.

A hybrid smart process and material design system for nanoimprinting is proposed, which combines with a learning system based on experimental and numerical simulation results. Instead of carrying out extensive learning experiments for various condition, the simulation learning results are partially complimented where the results can be theoretically predicted by numerical simulation. In other word, the lacking data in experimental learning are complimented by simulation-based learning results. Therefore, the prediction of nanoimprint results under various conditions without experimental learning could be realized even for unknown materials. In this study, material and process design for a low-temperature nanoimprint process using glycerol-containing polyvinyl alcohol are demonstrated. Experimental results under limited conditions are learned to investigate optimum Glycerol concentrations and process temperatures. On the other hand, simulation-based learning is used to predict the dependence on press pressure and shape parameters. The prediction results for unknown Glycerol concentrations agreed well with the follow-up experiments.

Staphylococcus aureus is a major food-borne pathogen. The ability of S. aureus to produce biofilm is a significant virulence factor triggering its persistence in hostile environments. In this study, we screened a total of 420 different food samples and human hand swabs to detect S. aureus and to determine their biofilm formation ability. Samples analyzed were meat, milk, egg, fish, fast foods, and hand swabs. S. aureus were detected by culturing, staining, biochemical, and PCR. Biofilm formation ability was determined by Congo Red Agar (CRA) plate and Crystal Violet Microtiter Plate (CVMP) tests. The icaA, icaB, icaC, icaD, and bap genes involved in the synthesis of bio-film-forming intracellular adhesion compounds were detected by PCR. About 23.81% (100/420; 95% CI: 14.17-29.98%) samples harbored S. aureus as revealed by detection of the nuc gene. CRA plate revealed 20% of S. aureus isolates as strong biofilm producers, while 69% and 11% as in-termediate and non-biofilm producers, respectively. By the CVMP staining method, 20%, 77%, and 3% of the isolates were found strong, intermediate, and non-biofilm producers. Furthermore, 21% of S. aureus isolates carried at least one biofilm-forming gene, where icaA, icaB, icaC, icaD, and bap genes were detected in 15%, 20%, 7%, 20%, and 10% of the S. aureus isolates, respectively. Bivariate analysis showed high significant correlations (p<0.001) between any of the two adhesion genes of S. aureus isolates. To the best of our knowledge, this is the first study in Bangladesh describing the detection of biofilm-forming S. aureus from foods and hand swabs with molecular-based evidence. Our findings suggest that food samples should be deemed a potential reservoir of biofilm-forming S. aureus that indicates a potential public health significance.

The Covid-19 pandemic and the initial focus on handwashing measures have again highlighted the importance of water access as an essential service in protecting human health. Yet, especially in southern cities, uneven geographies of water access – often mediated by fragmented and unequal infrastructure systems – may hamper the fight against infectious diseases. The spread of SARS-CoV-2 presented a dilemma for water providers as well as residents in water-deprived urban areas as they had to adhere to new hygiene standards and requirements, despite limited access to basic water infrastructure. Therefore, a deeper understanding of pandemic urban waterscapes – the infrastructure and governance systems as well as everyday practices and technologies – is necessary for ongoing debates on (post-) pandemic or zoonotic cities. In our paper, we focus on changes in urban (water) governance and government water projects in Nairobi since early 2020. We show that Covid-19 has contributed to changes in Nairobi’s waterscape but only in conjunction with recent changes in the city’s overall governance structure. However, if these waterscape changes lead to greater equity in water access, and if they have helped to curb the spread of SARS-CoV-2, is more than questionable.

In 2020, students of Pakistan had to adapt to the online environment for the very first time. This study aims to analyze the perceptions of medical, dental, and allied health students about online education in Pakistan. A descriptive, cross-sectional study was done to assess the level of acceptance of undergraduate students. A pre-validated questionnaire regarding demographics, past-experience of e-learning, advantages disadvantages of e-learning, and general perception of students towards e-learning was distributed. Descriptive statistics were computed for demographics, Mann-Witney-U test was used to compare the differences of perceptions between pre-clinical year and clinical years students. Kruskal-Wallis test was applied to compare the results of three specialties of students. Chi-square was used to compare overall category-wise positive and negative responses of students. 1200 students participated in the study. The major advantage identified by all students was the ‘comfortable environment’ in which they studied online. The major disadvantage selected by preclinical year students was ‘anxiety due to social isolation’ and that chosen by clinical year students was ‘lack of patient interaction’. Overall, 72% of students had a negative perception of e-learning. Student-teacher training, student counselling sessions, and innovative techniques need to be introduced to enhance student engagement and reduce pandemic stress.

Objective: Radiomics and deep transfer learning are two popular technologies used to develop computer-aided detection and diadnosis (CAD) schemes of medical images. This study aims to investigate and compare advantages and potential limitations of applying these two technologies in developing CAD schemes. Methods: A relatively large and diverse retrospective dataset including 3,000 digital mammograms is assembled in which 1,496 images depict malignant lesions and 1,054 images depict benign lesions. Two CAD schemes are developed to classify breast lesions. The first scheme is developed using four steps namely, applying an adaptive multi-layer topographic region growing algorithm to segment lesions, computing initial radiomics features, applying a principal component algorithm to generate an optimal feature vector, and building a support vector machine classifier. The second CAD scheme is built based a pre-trained residual net architecture (ResNet50) as a transfer learning model to classify breast lesions. Both CAD schemes are trained and tested using a 10-fold cross-validation method. Several score fusion methods are also investigated to classify breast lesions. CAD classification performance is evaluated by the area under ROC curve (AUC). Results: ResNet50 model-based CAD scheme yields AUC = 0.85±0.02, which is significantly higher than radiomics feature-based CAD scheme with AUC = 0.77±0.02 (p < 0.01). Additionally, fusion of classification scores generated by two CAD schemes does not further improve classification performance. Conclusion: This study indicates that using deep transfer learning is more efficient to develop CAD schemes and enables to yield higher lesion classification performance than CAD schemes developed using radiomics-based technology.

Despite the remarkable success of SARS CoV-2 vaccines, the rise of variants, some of which are more resistant to the effects of vaccination, highlights the potential need for additional COVID-19 vaccines. We used the Multiple Antigen Presenting System (MAPS) technology, in which proteins are presented on a polysaccharide polymer to induce antibody, Th1, Th17 and CD8+ T cell responses, to engineer a novel vaccine targeting SARS CoV-2. This vaccine contains a fragment of the spike (S) protein receptor-binding domain (RBD) sequence of the original D614G strain and was used to immunize nonhuman primates (NHP) for assessment of immunological responses and protection against SARS CoV-2 challenge. The SARS CoV-2 MAPS vaccine generated robust neutralizing antibodies as well as Th1, Th17 and cytotoxic CD8 T-cell responses in NHPs. Furthermore, MAPS-immunized NHPs had significantly lower viral loads in the nasopharynx and lung compared to control animals. Taken together, these findings support the use of the MAPS platform to make a SARS CoV-2 vaccine. The nature of the platform also could enable its use for the inclusion of different variants in a single vaccine.

The present study shows a methodology for analyzing and designing a cylindrical packed-bed reactor considering stationary and dynamic models. The design comprises the reactor's stationary and dynamic governing differential equations for mass and heat transfer under multi-dimensional approaches. The results included simulation of concentration, temperature, and reaction rate profiles via the 1-D and 2-D differential equations solution with FlexPDE software. The analysis was complemented with a scaled 3-D dynamic model implemented in COMSOL Multiphysics. Both FlexPDE and COMSOL Multiphysics relied on the finite element technique to solve the governing differential equations. The simulated concentration and temperature profiles from both FlexPDE and COMSOL models were compared to experimental data gathered from literature (specifically from a Fischer-Tropsch process to produce low-molecular-weight hydrocarbons in a configuration of cylindrical packed-bed reactors). Simulated concentration and temperature profiles from the 2-dimensional dynamic model and the COMSOL model were in good agreement with the trend observed in experimental data. Finally, the predicted reaction rate profiles from the COMSOL model and the 2-dimensional dynamic model followed the temperature trend, thus reflecting the temperature dependence of the reaction.

Steel fibers (SF) and polyolefin (PF) are widely used for shotcrete, especially in tunnelling. Both SF and PF and have shown to meet the standards in order to reduce or substitute the conventional steel mesh as reinforcement of concrete showing mechanical and productive advantages. This study sought the analysis and assessment of the mechanical properties of fiber reinforced shotcrete, comparing in-situ with laboratory results. This was performed with low and high fiber dosages of SF and PF as well as a combination of them (hybrid mixtures). A total of seven mixtures, two of steel, two of polyolefins, two hybrids and a control mixture were manufactured at laboratory and in situ. By performing tests according to EN 14651 and slabs according to EN 14488-5, it was possible to characterize the residual flexural strengths (fRj), and energy absorption capacity (E25mm) in slabs. In addition, a fracture surface analysis was performed, and the orientation factor was obtained. This allowed the authors to quantify the loss of residual strength on site and correlate it with the fiber content and positioning. Moreover, some relationships between beam and slab tests were found, allowing to correlate the most relevant type of tests in the field of fiber reinforced concrete.

Background: Only few pediatric reports exist regarding the prevalence, cause and evolution of liver and renal injury in patients with anorexia nervosa (AN). The aim of this study is to describe the prevalence and the risk factors of hepatic and renal failure at admission and during hospitalization, especially during refeeding in a cohort of hospitalized adolescents with AN.Methods: In a retrospective cohort study of adolescents with AN in a single hospital of Marseille from 2013 to 2019, we compared four groups on admission: elevated aminotransferases (AT)/normal AT and renal injury/no renal injury to analyze the differences between them (demographic factors, anthropometric factors, disease duration, initial prescribed calories, speed of refeeding, aminotransferase level, glomerular filtration rate). We observed the evolution of AT and renal injury for these four groups during refeeding (by the increase of kilocalories). Results: A total of 29 subjects with AN met eligibility criteria (age: 14.2 years, female (86.2%), BMI at admission (Z-score= -2.8 standard deviation (SD)) with elevated AT (20.7 %) and renal injury (13.8 %) on admission. Lower Z-score BMI (-4.05 vs -2 SD, p = 0.013), lower expected weight for height (69% vs 76%, p = 0.034) and longer disease duration (2.1 vs 0.9 years, p =0,032) were significantly associated with elevated liver enzymes at admission. Lower Z-score BMI (-3.35 vs -2.5 SD, p = 0.002), lower expected weight for height at admission (69% vs 74,5%, p = 0.002) and loss of weight before admission (0.66 vs à 0.20 kg per day, p = 0.002) were associated with renal injury at admission. Time nadir BMI (13.5 vs 6.5 days, p = 0.034) and duration of hospitalization (55 vs 41 days, p = 0.036) were longer in elevated enzymes on admission group. During refeeding, liver enzymes (95% confidence interval (CI), odds ratio (OR) aspartate aminotransferase: -0.07 [-0.11; -0.03] and OR alanine aminotransferase: -0.16 [-0.27; -0.06]) and renal injury (95% CI, OR creatinine: -0.013 [-0.017; -0.008]) have normalized with the increase of calories, with significant association.Conclusions: The results of this study suggest that degree of malnutrition is associated with liver and renal injury on admission. Theses failures disappeared with refeeding. In the future, prospective multicentric studies could examine evolution of renal and hepatic failure undergoing refeeding in large pediatric cohort of AN.

Microgrids are becoming popular nowadays because they provide clean, efficient, and low-cost energy. To use the stored energy in times of emergency or peak loads, microgrids require bulk storage capacity. Since microgrids are the future of renewable energy, the energy storage technology employed should be optimized to generate electricity. Batteries play a variety of essential roles in daily life and are used at peak hours and during a time of emergency. There are different types of batteries i.e., lion batteries, lead-acid batteries, etc. Optimal battery sizing of microgrids is a challenging problem, that limits modern technologies such as electric vehicles, etc. It is important to know different battery features such as battery life, battery throughput, and battery autonomy to get optimal battery sizing for microgrids. Mixed-integer linear programming (MILP) is an established technique for the integration and optimization of different energy sources and parameters for optimal battery sizing. A new MILP based dataset is introduced in this work. Support vector machine (SVM) is the machine learning application used to estimate the optimum battery size. The impact of feature selection algorithms on the proposed machine learning-based model is evaluated. The performance of the six best-performing feature selection algorithms is analyzed. The experimental results show that the feature selection algorithms improve the performance of the proposed methodology. Ranker search shows the best performance with a Spearman’s rank-ordered correlation constant of 0.9756, linear correlation constant of 0.9452, Kendall correlation constant of 0.8488 and root mean squared error of 0.0525.

Wounds are structural and functional disruptions of the skin that occur because of an accident. Chronic wounds are caused by a breakdown in the finely coordinated cascade of events that occurs during wound healing. Wound healing is a long process that split into at least three continuous and overlapping processes: an inflammatory response, a proliferative phase that leads to tissue repair, and third one is tissue remodeling. Therefore, wound healing studies are extensively studied to develop techniques that can achieve maximum recovery with minimum scar. Several growth hormones and cytokines secreted at the wound site tightly regulate wound healing processes. The traditional approach for wound management has been represented by topical treatments. Metal nanoparticles (e.g., silver, gold, zinc) are increasingly being employed in dermatology due to their favorable effects on wound healing, as well as in treating and preventing bacterial infections. The development of wound dressings materials has now been used to overcome the issues of external environments. The impregnated nanomaterials have provided moist environment that removes the exudates and avoid maceration. This review highlights the mechanism and focus on the current advancement of various nanoparticles impregnation material for wound healing process that can protect wound from infection and maintain the optimum exchange of gases.

Mycobacterium tuberculosis is a leading cause of human mortality worldwide and the emergence of drug-resistantstrains, demands the discovery of new classes of antimycobacterials that can be employed in the therapeutic pipeline. Previously, a secondary metabolite Chrysomycin A, isolated from Streptomyces sp. OA161 was shown to have potent bactericidal activity against drug-resistant clinical isolates of M. tuberculosis and different species of mycobacteria. The antibiotic inhibits the mycobacterial topoisomerase I and DNA gyrase leading to bacterial death, but the mechanisms that could cause resistance are currently unknown. To further understand the resistance mechanism, spontaneous resistance mutants were isolated and subjected to whole-genome sequencing. Mutation in a Tet^R family transcriptional regulator MSMEG_1380 was identified in the resistant isolates and was close to an operon encoding membrane protein MSMEG_1381 and MSMEG_1382. Sequence analysis and modeling studies indicated that they are components of the Mmp family of efflux pumps and over-expression of either the operon or individual genes conferred resistance to chrysomycin A, isoniazid, and ethambutol that are in TB therapy. Our study highlights the role of membrane transporter proteins in conferring multiple drug resistance and the utility of recombinant strains overexpressing membrane transporters in the drug screening pipeline.

The COVID-19 pandemic has caused significant medical and psychological challenges worldwide, and not only exceeded the capacity of hospitals and intensive care units but also an individuals’ ability to cope with life. Health-care workers have continued to provide care for patients despite exhaustion, fear of transmission to themselves and their family, illness or death of friends and colleagues, and losing many patients. They have also faced additional stress and anxiety due to long shifts combined with unprecedented population restrictions, including personal isolation. In this study, we study the effect of an app-based Yoga of Immortals (YOI) intervention on mental health of healthcare workers. In this study, the health care workers were digitally recruited, and their psychological parameters were measured using validated questionaries. The participants were randomly grouped into control and test groups. The validated psychological measures were the Patient Health Questionnaire-8 (PHQ-8), Insomnia Severity Index (ISI) and generalized anxiety disorder (GAD-7) scales. The digital YOI intervention significantly reduced the anxiety, depression symptoms, and insomnia in healthcare workers of all age groups. In contrast, there was no improvement in the control group. This study details the effectiveness of an app-based YOI intervention in healthcare workers.

Prediction of protein-ligand binding affinities is crucial for computational drug discovery. A number of deep learning approaches have been developed in recent years to improve the accuracy of such affinity prediction. While the predicting power of these systems have advanced to some degrees depending on the dataset used for model training and testing, the effects of the quality and quantity of the underlying data have not been thoroughly examined. In this study, we employed erroneous datasets and data subsets of different sizes, created from one of the largest databases of experimental binding affinities, to train and evaluate a deep learning system based on convolutional neural networks. Our results show that data quality and quantity do have significant impacts on the prediction performance of trained models. Depending on the variations in data quality and quantity, the performance discrepancies could be comparable to or even larger than those observed among different deep learning approaches. In particular, the presence of proteins during model training leads to a dramatic increase in prediction accuracy. This implies that continued accumulation of high-quality affinity data, especially for new protein targets, is indispensable for improving deep learning models to better predict protein-ligand binding affinities.

At present, there are no hardware or biochemical systems allow to assess the severity of post-COVID syndrome in vivo. The hardware of the proposed biotechnical system is based on routine transthoracic electrical impedance rheography, which makes it possible to register the frequency characteristics of the patient's bioimpedance response to controlled stress stimulation, thereby simultaneously fixing the characteristics of his productive heart, the state of the hemomicrocirculatory bed, the efficiency of the gas transport function of his blood, and also reliably assess personal reactivity and adaptive potential. Subsequent mathematical approximation of the obtained biometric data by an original neural network makes it possible to rank the results obtained and automatically generate a program of medical rehabilitation for a particular patient, depending on the severity of his post-COVID syndrome. The study results proved two reliable physiological signs confirming the presence of latent post-COVID complications: a decrease in the base impedance value for light exercise and an increase in the length of the systolic arc of the rheocardiogram.

Dry eye disease (DED) most commonly caused by evaporative subtypes and mainly induced by meibomian gland dysfunction (MGD). Intense pulsed light (IPL) combined with meibomian gland expression (MGX) is noninvasive treatment for improvement of ocular discomfort symptoms and MGD. In this prospective study between November 2020 and May 2022, the patients met the criteria of both ocular surface disease index (OSDI) ≥13 scores and standardized patient evaluation of eye dryness (SPEED)≥ 8 scores were enrolled in Kaohsiung Veteran General Hospital. Three separate treatment sessions of IPL therapy combined with MGX administered to the lower lids with an interval of 28 days. Further tear film assessment included lipid layer thickness (LLT), tear meniscus height (TMH), non-invasive tear break-up time (NIBUT), meibomian gland loss (MGL) either beforeor after 1st and 3rd IPL therapy combined with MGX. Besides, lissamine green staining and pain scores were also recorded. We totally enrolled 37 patients of 74 eyes. Men accounted for 18.92% (7/37). The mean age was 54.51 ± 11.72 years. The mean OSDI scores were 58.12 ± 22, while the SPEED scores were 17.03 ± 5.98. The mean Schirmer’s test was 3.66 ± 2.43 mm. After three sessions IPL treatment with MGX, the OSDI, SPEED, LLT, TMH, MGL, MGXS and pain scores were significantly improved. For the MGX scores (MGXS) ≤20 group, MGL and lissamine green scores showed significant improvements. For the MGXS >20 group, TMH and dry spot rate revealed statistically improvement. Noninvasive IPL therapy with MGX statistically improved not only dry eye symptoms but also tear film assessments.

In this study, the dependence between Bitcoin (BTC) and economic policy uncertainty (EPU) of USA and China is estimated by applying latest methodology of quantile cross-spectral dependence. The findings indicate a positive return interdependence between BTC and EPU is high in short-term, and this dependence decreases as investment horizons increase from weekly to yearly. The information on above interdependence is also extracted by applying wavelet coherence analysis and the estimation results suggest that correlation between BTC and EPU is positive during short-term investment horizon. Furthermore, more diversification benefits of BTC can be obtained during USA-EPU as compared to China-EPU.

The fatigue life of concrete is affected by many interwoven factors whose effect is nonlinear. Be-cause of its unique self-learning ability and strong generalization capability, the Bayesian regu-larized backpropagation neural network (BR-BPNN) is proposed to predict concrete behavior in tensile fatigue. The optimal model was determined through various combinations of network parameters. The average relative impact value (ARIV) was constructed to evaluate the correla-tion between fatigue life and its influencing parameters (maximum stress level Smax, stress ratio R, static strength f, failure probability P). ARIV results were also compared with other factor as-sessment methods (weight equation and multiple linear regression analyses). Using BR-BPNN, S-N curves were then obtained for the combinations of R=0.1, 0.2, 0.5; f=5, 6, 7MPa; P=5%, 50%, 95%. The tensile fatigue results under different testing conditions were finally compared for compatibility. It was concluded that Smax has the most significant negative effect on fatigue life; the degree of influence of R, P, and f, which positively correlate with fatigue life, decreases suc-cessively. ARIV is confirmed as a feasible way to analyze the importance of parameters and could be recommended for future applications. The tensile fatigue performance of plain concrete under different stress states (flexural tension, axial tension, splitting tension) does not differ sig-nificantly. Besides utilizing the valuable fatigue test data scattered in the literature, insights gained from this work could provide a reference for subsequent fatigue test program design and fatigue evaluation.

The supramolecular aggregation processes occurring on metallic (aluminum and gold) surfaces in aqueous solutions of bovine serum albumin (BSA) during drying were studied using advanced scanning electron microscopy (SEM). The possible mechanism for the formation of amazing intricate fractal structures on metallic surfaces was proposed based on the analysis of SEM images, size distribution diagrams and EDX-scanning elements distribution maps.

The purposes of this study are to analyze the groundwater quality of Ogallala Aquifer and evaluate the hydrological characteristics in the southern High Plains region of the Permian Basin, Texas. Levels of chloride, fluoride, nitrate, pH, selenium, and total dissolved solids (TDS) were analyzed through the years 1990-2016. A total of 133 wells were collected from the Texas Water Development Board (TWDB) which is an open database by the US government. Statistical analysis was utilized to evaluate the groundwater quality and propose trends. The average levels of the contaminants were compared to their respective Maximum Contaminant Levels (MCL) by the Environmental Protection Agency (EPA). Potential human health risks that each contaminant possesses were described. Possible sources of each contaminant were discussed with oil/gas activities, agricultural practices, and other human actions impact its conditions. This research provides important information for groundwater quality of Ogallala aquifer and contributes on understanding the response to development in the Permian Basin, Texas.

As one of the most appealing edible mushrooms, the quality of Flammulina velutipes can be affected by the cultivation substrate, which has an impact on the mushroom umami taste and nutrients. In our study, the effect of mushroom root fermentation broth (MRFB) based substrate on umami taste and nutrients of F. velutipes were evaluated; four proportions of MRFB was conducted (CK 0%, E1 6.7%, E2 13.4%, E3 20.1%). Results indicated that MRFB was an effective nutrient supplement for mushroom cultivation substrate. E2 and E3 showed higher crude fiber, crude fat, soluble protein, and soluble sugar. Compared to CK, the content of monosodium glutamate-like (MSG-like) amino acids, essential amino acids, total amino acids and total 5'-nucleotides in E2 and E3 were higher. The equivalent umami concentration (EUC) values in E1, E2 and E3 were 1.70, 2.43 and 1.56 times of CK, respectively. Higher umami, saltness and sweetness taste values were found in E2. Thereby, it signified that better umami and richer nutrients were achieved by using substrate with proper volume of MRFB, especially, E2 with 13.4% of MRFB. Overall, better mushroom quality could be derived from the application of MRFB in cultivation. MRFB was a favorable nutrient supplement for Flammulina velutipes cultivation substrate.

Early stroke diagnosis remains a big challenge in healthcare partly due to the lack of reliable diagnostic blood biomarkers, which in turn leads to increased rates of mortality and disability. Current screening methods are optimised to identify patients with a high risk of cardio-vascular disease, especially among the elderly. However, in young adults and children, these methods suffer low sensitivity and specificity and contribute to further delays in their triage and diagnosis. Accordingly, there is an urgent need to develop reliable blood biomarkers for triaging patients suspected of stroke in all age groups, especially children and young adults. This review explores some of the existing blood biomarkers, as single biomarkers, or biomarker panels, and examine their sensitivity and specificity for predicting stroke. A review was performed on PubMed and Web of Science for journal articles published in English during the period 2001 to 2021 which contained information regarding biomarkers of stroke. In this review article, we provide comparative information on the availability, clinical usefulness, and time-window periods of eight single blood biomarkers and six biomarker panels that have been used for predicting stroke in emergency situations. The outcomes of this review can be used in future research for developing more effective stroke biomarkers.

In experimental physics, we understand time as the duration of material changes that run into space. This fact is the standpoint for our model of time-invariant space in which causality is only a principle and not a physical actuality, and entropy runs only in space and not in time. Time is merely a duration of entropy that is increasing in time-invariant space. Time is entering existence when measured by the observer. In time-invariant space, motion happens only in space and not in time which means that also in open timelike curves motion happens only in space and not in time.

Antibodies constitute a major component of serum on protein mass basis. We also know that the structural diversity of these antibodies exceeds that of all other proteins in the body and they react with an immense number of molecular targets. What we still cannot quantitatively describe is, how antibody abundance is related to affinity, specificity and cross reactivity. This ignorance has important practical consequences: we also do not have proper biochemical units for characterizing polyclonal serum antibody binding. The solution requires both a theoretical foundation, a physical model of the system, and technology for the experimental confirmation of theory. Here we argue that the quantitative characterization of interactions between serum antibodies and their targets requires systems-level physical chemistry approach and generates results that should help create maps of antibody binding landscape.

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions like context familiarity influences affective feelings and is linked to cardiac-brain interactions. Hence to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that cardiac-brain interaction is dependent on familiarity such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.

The use of improved agricultural technologies has been reported as the major strategy to increase agricultural production, increased household incomes and addressing poverty. However, adoption of such improved technologies by smallholder coffee farmers has been slow and this has contributed to the low coffee productivity in the country and the poor performance of the coffee sub sector. The study was meant to examine the effect of institutional factors including extension services, access to market and access to credit on technology adoption among smallholder coffee farmers in Kanungu District, Uganda. The study collected both quantitative and qualitative data from 289 smallholder coffee farmers and 8 key informants respectively in major coffee growing sub counties in Kanungu district. The study revealed that access to extension services and access to market have a positive significant influence on agricultural technology adoption while access to market has no significant influence on agricultural technology adoption. The study concluded that there is a positive significant relationship between institutional factors and technology adoption among smallholder coffee farmers in Kanungu district.

Despite more than hundred years of research since Sir Sherrington’s studies on reflexes, his questions are still somehow unanswered. On what anatomical stage do the play of spinal reflex interaction take place? What are the physiological properties of this anatomical substrate? In this paper, we address these questions in light of the most advanced theory of motor control and the anatomical discoveries on the fascia that are changing how we think about control of action and perception. There are two sides of the problem: the neurological (reflex) connections that are at the base of movement, and the anatomical substrate that regulates and coordinates the movement. We recently advanced a hypothesis on how these two elements are connected and how they interplay. Here we further explain the concept of the somatic equilibrium point – SEP – and its central role in movement control and coordination. It is our belief that the concept of SEP explains how the neuro-mechanical control of movement is organized at peripheral level. At this level, intrafusal and extrafusal muscle fibres are combined in myofascial units, organized in anatomical directions. Myofascial units are closed systems whose behaviour can be affected by neural (voluntary) control or changes in external forces. SEPs represent the intrinsic equilibrium of the myofascial units, and are connected through the continuum of the fascia so that mechanical transfer of tension from segment to segment pre-adjust muscle fibers length and hence their excitation level. This is how coordination between segments is achieved. Finally, we suggest SEPs create the neurological representation of the referent configuration for action, and configurations are linked to the architecture of the fascial system.

Inverse problems of recovering surface fluxes on the boundary of a domain from pointwise observations are considered. Sharp conditions on the data ensuring existence and uniqueness of solutions in Sobolev classes are exposed. They are smoothness conditions on the data, geometric conditions on the location of measurement points, and the boundary of a domain. The proof relies on asymptotics of fundamental solutions to the corresponding elliptic problems and the Laplace transform. The problem is reduced to a linear algebraic system with a nondegerate matrix.

Petrochemicals, which convert oil and gas into products such as plastics, are fundamental to modern societies. Chemists recognize their role in the design of materials and the adverse effects that these may have on the environment, preventing sustainable development. Several methodological frameworks and sustainability assessment approaches have been developed to evaluate the resources used in the petrochemical sector in terms of environmental costs. A combination of Life Cycle Assessment and Emergy Accounting - to assess the environmental support for resource use - is applied in this study of the PET production chain in Europe. The Unit Emergy Values of several intermediates are calculated or updated to facilitate discernment of the quality of energy used and the processes' efficiency. Several routes for synthesizing renewable para-xylene and ethylene glycol from biomass are discussed and confronted with the efforts focused on recycling and recovering the final product providing concurrently a procedure and a valuable data set for future CP actions. The results show that understanding the efficiencies changing across the production chain may help stakeholders make wise choices as to where and when interventions to promote a circular economy are most effective along a petrochemical production chain.

Porcine circovirus type 2 (PCV2) is responsible for a number of porcine circovirus associated diseases (PCAD) that can severely impact domestic pig herds. For a non-enveloped virus with a small genome (1.7 kb ssDNA), PCV2 is remarkably diverse, with 8 subtypes (a-h). New subtypes of PCV2 can spread through migration of wild boars, which are thought to infect domestic pigs and spread further through the domestic pig trade. Despite a large swine population, the diversity of PCV2 subtypes in Ukraine has been undersampled, with few PCV2 genome sequences reported in the past decade. To gain a deeper understanding of PCV2 subtype diversity in Ukraine, samples of blood serum were collected from wild boars (n = 107) that were hunted in Ukraine during the November-December 2012 hunting season. We found 34/107 (31.8%) prevalence of PCV2 by diagnostic PCR. For domestic pigs, liver samples (n = 16) were collected from a commercial market near Kharkiv in 2019, of which 6/16 (37%) were positive for PCV2. We sequenced the genotyping locus ORF2, a gene encoding the PCV2 viral capsid (Cp), for 11 wild boar and 6 domestic pig samples in Ukraine using an Oxford Nanopore MinION device. Of 17 samples with resolved subtypes, PCV2 subtype b was most common in wild boar (10/11, 91%), while domestic pigs were infected with subtypes b and d. We also detected subtype b/d and b/a co-infections in wild boar and domestic pigs, respectively, and subtype f in a wild boar from Poltava for the first time in Ukraine. Building a maximum likelihood phylogeny, we identified a sublineage of PCV2 subtype b infections in both wild and domestic swine, suggesting a possible epizootic cluster and ecological interaction in northeastern Ukraine.

Climate change is the long-term shift in global weather patterns, largely caused by anthropogenic activity of greenhouse gas emissions. Global climate temperatures have unmistakably risen and naturally-occurring climate variability alone cannot account for this trend. Human activities are estimated to have caused about 1.0 °C of global warming above the pre-industrial baseline and if left unchecked, will continue to drastically damage the Earth and its inhabitants. Globally, natural disasters and subsequent economic losses have become increasingly impactful as a result of climate change. Both wildlife ecosystems and human habitats have been negatively impacted, from rising sea levels to alarming frequency of severe weather events around the world. Attempts towards alleviating the effects of global warming have often been at odds and remain divided among a multitude of strategies, reducing the overall effectiveness of these efforts. It is evident that collaborative action is required for avoiding the most severe consequences of climate change. This paper evaluates the main strategies (industrial/energy, political, economic, agricultural, atmospheric, geological, coastal, and social) towards both mitigating and adapting to climate change. As well, it provides an optimal combination of seven solutions which can be implemented simultaneously, working in tandem to limit and otherwise accommodate the harmful effects of climate change. Previous legislation and deployment techniques are also discussed as guides for future endeavors.

In this study, divalent Yb2+-doped silica fiber was fabricated using rod-in-tube technology. The fiber core of Yb2+-doped silica glass was prepared by high-temperature melting technology under vacuum conditions. The spectroscopic properties of the Yb2+-doped glass and fiber were studied. The experiments indicate that divalent Yb2+-doped glass has a high quantum efficiency and superbroadband fluorescence in the visible region with an excitation wavelength of 405 nm. In additionally, the results suggest that Yb2+-doped fiber has a potential for application in visible fiber laser and fiber amplification.

The location and number data of individual fruit trees are critical for planting area investigation, fruit yield prediction, and smart orchard management and planning. These data are conventionally obtained through manual investigation and statistics with time-consuming and laborious effort. Object detection models in deep learning used widely in computer vision could provide an opportunity for accurate detection of individual fruit trees, which is essential for rapidly obtaining the data and reducing human operations errors. This study proposes an approach to detecting individual fruit trees and mapping their spatial distribution by integrating deep learning with unmanned aerial vehicle (UAV) remote sensing. UAV remote sensing collected high-resolution true-color images of fruit trees in the experimental pomelo tree orchards in Meizhou city, South China. An image dataset of deep learning samples of individual pomelo trees (IPTs) was constructed through visual interpretation and field investigation based on the fruit tree images captured by UAV remote sensing. Four different scales of YOLOv5 (YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) for object detection were selected to train, validate, and test on the image dataset of pomelo trees. The results show that the average precision (AP@0.5) of the four YOLOv5 models for validation reach 87.8%, 88.5%, 89.1%, and 90.7%, respectively. The larger the model scale, the higher the average accuracy of the detection result of validation. It suggests that YOLOv5x is a preferred high-accuracy model among the YOLOv5 family and is suitable to realize the detection of IPTs. The number of the IPTs in the study area was counted using YOLOv5x, and their spatial distribution map was made using the non-maximum suppression method and ArcGIS software. This study will provide primary data and technical support for smart orchard management in Meizhou city and other fruit-producing areas.

The COVID-19 pandemic affects all parameters, especially health care professionals, drugs and medical supplies. The KERRA is a mixed medicinal plant capsule that is used for the treatment of patients with high fever with food and drug administration approved by FDA Thailand. Recently, KERRA showed quicker recovery for COVID-19 patients. Therefore, it is possible that some ingredients in KERRA could inhibit SARS-CoV-2. In this study, two important replication-related enzymes in SARS-CoV-2, a main protease and an RNA-dependent RNA polymerase (RdRp), were used to study the effect of KERRA. The results showed that KERRA inhibited the SARS-CoV-2 main protease and SARS-CoV-2 RdRp with IC50 values of 49.91 ± 1.75 ng/mL and 36.23 ± 5.23 µg/mL, respectively. KERRA displayed no cytotoxic activity on macrophage cells at concentrations lower than 1 mg/mL and exhibited anti-inflammatory activity. Additionally, KERRA was against a feline coronavirus (feline infectious peritonitis [FIP]) infection with an EC50 value of 134.3 g/mL. This study supports the potential use of KERRA as a candidate drug for COVID-19.

The great pipefish Syngnathus acus is one of the most representative European syngnathid, being highly associated with seagrass and macroalgal beds. Surprisingly, the ecology of this ovoviviparous marine fish has received scanty attention. The population inhabiting three sites on Cíes Archipelago (Atlantic Islands National Park, NW Spain) was monitored in 2017-2018 for spatial and temporal changes in abundances, reproduction traits, trophic niche occupancy and dietary regimes across reproduction states through an isotopic (δ13C and δ15N) approach. Abundances were highly variable across seasons and sites, decreasing significantly from mid-autumn. The population consisted almost exclusively of large adults that migrate by the end of the breeding season, which extended from mid-spring to summer. Operational sex ratios suggest that the species is sex-role reversed. S. acus is a secondary consumer (Trophic position= 3.36 ± 0.05) preferring amphipods but displaying annual and seasonal dietary plasticity. Mature fish were less selective than immatures (especially females) with a higher preference for amphipods (36-68%) in the former. The second most preferred prey were carideans, copepods or isopods, depending on the year and reproduction state. Overall, the wider trophic niches in females and immature specimens compared to males and mature fish would indicate a higher variability in both the use of prey resources and/or their origin. The present study highlights the trophic plasticity and unique features of S. acus population in Cíes Archipelago, especially regarding the outstanding size of the fish and the exceptional occurrence of breeders.

Road vehicles are a large contributor to Nitrogen Oxides (NOx) pollution. The routine road-side monitoring stations, however, may underrepresent the severity of personal exposure in urban areas, because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at local level. This study deploys a 10 cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic, by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at constant speed may generate momentary road-side concentrations of NOx as high as 1.25 mg/m3, with 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

This research aims to investigate the carbon fiber reinforced polymer (CFRP) when subjected to tensile, bending, and compression. Half of the specimens are also subjected to water to find out how water influences. The CFRP is created using a combination of carbon fiber layers and epoxy resin Bisphenol A Epichlorohydrin with hardener and is formed using the vacuum infusion method. From the water absorption test, it was found that the average weight gain of the specimens was 2.9% and the lowest value was at 0.6%, it was concluded that the increase in wet specimen weight was not too significant and water absorption tended to be slow. Mechanical testing ob-tained the highest average tensile stress, bending stress, compressive stress, and modulus of elasticity of 195 MPa, 295 MPa, 96 MPa, and 8914 MPa were from dry specimens while the lowest average values were 146 MPa, 286 MPa, 81 MPa, and 6160 MPa from wet specimens. The results of micro-photo observations on the tensile test fracture show that the specimen has a XGM fracture character with delamination and splitting fractures happening in multiple areas. In the bending test, the specimens experienced buckling fracture due to the fiber breaking and the inability of the matrix to withstand the additional stress. Shear fracture happened during the compressive test. In conclusion, water absorption has a bad impact towards the composite strength.

A major challenge in the clinical management of patients with mesial temporal lobe epilepsy (MTLE) is identifying those who do not respond to antiseizure medication (ASM), allowing for the timely pursuit of alternative treatments, such as epilepsy surgery. Here, we investigated changes in plasma metabolites as biomarkers of pharmacoresistance in patients with MTLE. Furthermore, we used the metabolomics data to gain insights into the mechanisms underlying MTLE and response to ASM. We performed an untargeted metabolomic method using magnetic resonance spectroscopy and multi- and univariate statistical analyses to compare data obtained from plasma samples of 28 patients with MTLE compared to 28 controls. The patients were further divided according to response to ASM: 20 patients were refractory to treatment, and eight were responsive to ASM. We only included patients using carbamazepine in combination with clobazam. We compared the group of patients with controls and found that the profiles of glucose (p = 0.01), saturated lipids (p = 0.0002), isoleucine (p = 0.0001), β-hydroxybutyrate (p = 0.0003), and proline (p = 0.02) were different in patients compared to controls (p &lt; 0.05). In addition, lipoproteins (p = 0.05), lactate (p = 0.05), glucose (p = 0.05), unsaturated lipids (p = 0.05), isoleucine (p = 0.05), and proline (p = 0.05), could discriminate between the two groups of patients classified according to response to ASM. The identified metabolites were linked to different biological pathways related to cell energy metabolism, and pathways linked to inflammatory processes and the modulation of neurotransmitter release and activity in MTLE. In contrast, we found that pyruvate metabolism may be linked to resistance to ASM. In conclusion, in addition to insights into the mechanisms underlying MTLE and the response to treatment with ASM, our results suggest that plasma metabolites may be used as biomarkers of disease and response to ASM in patients with MTLE. These findings warrant further studies exploring the clinical use of metabolites to assist in decision-making when treating patients with MTLE.

The article presents a bibliometric analysis of conference proceedings 2019-2021 indexed in Scopus and related to the topic "Artificial Intelligence and Energy". The relevance of the topic is considered in the context of the energy transition and the application of artificial intelligence for the rational use of energy resources. A comparative analysis of the publication activity of researchers from Russia, China, India, the United States, and Indonesia on the topic in question is given. Methodologically, the emphasis for determining the subject is not on the co-occurrence of keywords, but on the clustering of documents based on the thesis that the titles of publications most briefly and fully reveal the content of the publication and allow the subject specialist to do a relevant selection of publications necessary for their research. Two tools were used in this work: Carrot2 and Clustering App (CSV Explorer). It is shown that Russian researches are characterized by the tendency of prevailing engineering problems and insufficient attention is paid to environmental, economic and social problems of using AI in the energy sector. Studies from China and the United States are of the greatest informative interest, both in terms of the relevance of their topics and the actuality of their content. Studies from India and Indonesia are more general in nature; of interest are the efforts of these countries to engage in global scientific activities.