Background: Community-based medical education (CBME) is an essential component of medical education, where primary healthcare physicians (PHPs) play a crucial role. This study explores PHPs' awareness and engagement in CBME and investigates the factors influencing their participation. Methods: This mixed study was conducted in two phases. In the first phase, a qual-itative study was conducted using semi-structured interviews with PHPs, and thematic analysis related to their awareness and engagement in CBME. In the second phase, a quantitative survey was conducted among 72 PHPs pre- and post-training programs. Results: Primary healthcare physicians had a positive attitude toward community-based medical education. The participants have an acceptable level of awareness and engagement, which increased substantially (p-value = 0.03) and (p-value = 0.003), respectively. Logistic analysis indicated that non-Saudi physicians were likelier to participate in the CBME (p-value=0.001). Professions and academic experiences influence their willingness and engagement to participate in CBME (OR= 7.5, p-value=0.001) and (OR=0.21, p-value=0.001), respectively. Conclusion: The study findings highlighted the importance of increased awareness and the factors that enhance PHPs' engagement in CBME. This positive perspective of the PHPs helps build effective partnerships and facilitates the extension of the curriculum to apply CBME.

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data–driven grey–box identification approach provided the physically meaningful nonlinear continuous–time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte–Carlo analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model–based and data–driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

This paper investigates a range of popular differential evolution (DE) configurations to identify components responsible for emergence of structural bias – a recently identified tendency of algorithms to prefer some regions of search space over others, for reasons unrelated to objective function values. Previous work has explored this tendency for genetic algorithms (GA) and particle swarm optimisation (PSO), finding a relationship between population size and extent of structural bias, hence highlighting potential weaknesses of those algorithms. In current article, we focus on DE, extend the investigation to include consideration of an algorithmic component that is often overlooked – constraint handling mechanism. Towards this end, a wide range of DE configurations was tested here. Results suggest that DE is generally robust to structural bias. Unlike the case with GA and PSO, population size seems to have no influence on DE structural bias. Only one of variants studied – DE/current-to-best/1/bin – shows clear signs of bias, however, we show that this effect is mitigated by a judicious choice of constraint handling technique. These findings contribute towards explaining widespread success of DE variants in algorithm comparison studies; its robustness to structural bias represents the absence of a factor that may confound other algorithms.

Background: Simulation plays a crucial role in health studies, as it helps medical students apply their theoretical knowledge in real-life situations. Moulage is one of the techniques that helps in making simulation more realistic or high-fidelity. It uses special effects to emulate wounds for a better understanding of what the wound is like visually. Still, moulage is expensive, time-consuming, resource-intensive, and requires the training of staff, which is why we need to find low-cost substitutes for moulage materials. Method: When searching the database “PubMed” for the terms “Low-cost and Medical moulage”, we retrieved 222 studies, out of which when excluding results not related to low-cost, we obtained 62 studies, from which when removing studies that do not contain information regarding moulage, we found two papers, after referring to citations and cited articles of those papers, we ended up with six studies. Based on the selected articles and additional articles sourced from their reference list, a total of 11 studies were included in the review. Results: We understand that moulage is a technique that helps make simulations come alive, but the resources required to use it are at times, expensive, which is why we need to find methods to do low-cost moulage, and many studies address that it can be as simple as using homemade ingredients. Students from a previous study have talked about their opinions regarding the realistic component of moulage and whether if it is any different from other moulages. Most of the students agreed that the moulage ranked well in face and content validity. However, further innovations must be introduced in the field to be widely spread and lead to newer opportunities. Conclusion: Although the research done under moulage is limited, it is accepted that moulage is helpful for simulation-based studies and that low-cost moulage can help make medical studies a better experience for students studying it. Students have a favorable opinion on the realistic aspect of the low-cost moulage applied to them. Newer methods can be introduced to moulage, and it can be implemented in low-income countries.

This paper presents a novel 3-degrees-of-freedom (3-DOF) haptic master with rubber bands for self-resetting. The mechanical design avoids coupling between three directions mechanically by using three perpendicular axis intersecting at one point. Bevel gear transmission is adopted to increase the compactness of the overall structure. VR-based interactive system is designed and built by incorporating the proposed haptic master. The proposed haptic device can generate force feedback along 3-degree-of-freedom motion using motors and provide command signals to the avatar in the virtual environment. In order to analyze the performance of the developed device in terms of haptic feedback operation, ergonomics assessments are designed and experimentally implemented. Preliminary studies on the influencing factor including the guidance force, the reset force, the speed of the avatar and the arm the length have been conducted. The results of this paper are of great significance for the design of the haptic master and interactive system.

The purpose of the article is to determine the peculiarities of using of teaching elements of research-based training at the Institute of Human Sciences of Borys Grinchenko Kyiv University. Based on the focus group methodology, the authors identify the key methodological characteristics of research-based training, which have been put into basis of analysis of educational programs for the purpose of determining the application of tasks that contribute to the development of research skills of students. The study used a method of focus group. Its purpose was to obtain the necessary information from the participants to describe the methodological basis and justification of methods, forms, indicators, etc. of research-based training system among people who are competent, have experience in this field. After that, the method of "theoretical sampling" was used, which enabled to formulate generalized characteristics according to the results of focus groups. The practical value of the study is determination of the methodological characteristics of research-based training which is the basis for the application of tasks by university teachers that promote the development of research competence of students. The research is one of the first attempts to determine the methodological characteristics of research-based training in Ukraine.

OBJECTIVE: Cervical cancer is a major cause of cancer-related mortality, necessitating effective screening and diagnostic methods. This study aimed to assess the performance of cervicovaginal smear (CVS) and Human papilloma virus (HPV)-DNA cotest. STUDY DESIGN: The pathology results of 225 female patients who underwent HPV-DNA testing with CVS between 2014 and 2022 and were subsequently diagnosed by colposcopic cervical biopsy or second CVS were retrospectively analyzed. RESULTS: CVS samples showed Atypical Squamous Cells of Undetermined Significance (ASCUS), Low-grade squamous intraepithelial lesion (LSIL), High-grade squamous intraepithelial lesion (HSIL) and cervical cancer. Concordance between the first and second diagnoses demonstrated moderate agreement for LSIL. ASCUS cases exhibited a significant correlation with HPV-DNA positivity and higher-grade cervical lesions. In biopsy, sensitivity and specificity for CIN 2 were 67.8% and 67.9%, respectively, while for CIN 3, they were 81.8% and 58.5%. HPV testing showed significant correlation with histopathologic results. In women over 40 years, more intraepithelial lesions were diagnosed compared to younger women (p<0.005). The conventional smear technique proved reliable in detecting high-grade lesions. CONCLUSION: Despite the limitations of our study, our results emphasize the value of HPV-DNA testing to avoid unnecessary interventions and to establish appropriate follow-up strategies.

Cadmium (II) contamination in the environment is an emerging problem due to its acute toxicity and mobility, so it is very urgent to remove this species from industrial wastewater before it is discharged into the environment. Thus, a starch-based activated carbon (AC) with a specific surface area of 1600 m2g-1 is used as an adsorbent for the capturing of toxic Cadmium (II) ions from synthetic solution. The sorbent is characterized by BET, SEM, TEM, XRD, FT-IR, TGA, and zeta potential. The maximum uptake (284 mg g-1) of Cadmium (II) ion is obtained at pH 6. The thermodynamics parameters like ∆G, ∆H, ΔS are found to be -17.42 kJmol-1, 6.49 kJ mol-1, and 55.66 Jmol-1K-1 respectively, revealing that the adsorption mechanism is endothermic, spontaneous, and feasible. The experimental data follows the D-R and Langmuir models well. The mass transfer is controlled by pseudo 2nd order kinetics. Furthermore, the density functional theory simulations demonstrate that the activated carbon strongly interacted with the Cd (II) ion through its various active sites. The adsorption energy noted for all interactive sites is highly negative (-0.45 eV to -10.03 eV), which shows that the adsorption process is spontaneous and stable which is in agreement with the experimental thermodynamics analysis.

Chenodeoxycholic acid (CA) is a naturally occurring bile acid that is produced in the liver from cholesterol. Three CA complexes using Zn(II), Mg(II), and Ca(II) ions were synthesized to examine the chelation tendencies of CA towards these metal ions. The complexation reaction of CA with the metal ions under investigation was conducted with a 1:1 molar ratio (CA to metal) at 60-70°C in natural media (pH 7-8), which consisted of a binary solvent of MeOH and H2O (1:1). The resulting CA complexes were characterized using analytical data (metal, H, C, and Cl, analysis) and spectral data (UV-visible, FT-IR, and 1H NMR) to elucidate the complexes’ structures. The results suggested that CA in anion form utilized oxygen atoms of the carboxylate group (-COO−) to capture Zn(II), Mg(II), and Ca(II) ions. This produced complexes with the general compositions of [Zn(CA)(H2O)Cl], [Mg(CA)(H2O)Cl]H2O, and [Ca(CA)(H2O)Cl]2H2O, respectively. The Kirby-Bauer disc diffusion assay was then used to explore the bioactivity of the CA complexes toward three fungal species, three Gram-positive bacteria, and two Gram-negative bacteria. The Ca(II) and Mg(II) complexes exhibited marked inhibitory effects on the cell growth of the fungal species Aspergillus niger with potency equal to 127% and 116% of the activity of the positive control, respectively. The Zn(II) and Ca(II) complexes strongly inhibited the growth of Penicillium sp., while the Zn(II) and Mg(II) complexes showed strong growth inhibition towards the Gram-negative species Pseudomonas aeruginosa.

Adaptation to the impacts of human induced global heating is inevitable. For a socially just and ecological sustainable adjustment to these new circumstances, we need to draw from diverse knowledge systems while, simultaneously, foster a social-ecological transformation. We approach these concerns through the concept of community-based adaptation (CBA) and discuss remedies. Synergies with feminist knowledge systems and indigenous ways of living show the transdisciplinary essence of CBA. By abstracting from its origin and overlapping disciplines, revealing the social metabolism as a common problem, CBA is prone to achieve more equitable and sustainable adjustments. Transdisciplinarity itself and the current related CBA literature point beyond mere adjustments and call for a redesign of the social metabolism, thereby shifting from adaptation to global heating towards adaptation with nature by focusing on social provisioning. An engagement with transformative adaptation and heterodox economics further shows the potential of CBA to serve as an instrument in support of a social-ecological transformation by addressing root causes of vulnerability and by fostering epistemic justice. Reflecting these points back on the epistemological and ontological assumptions of CBA, the viewpoint proposes critical realism as a guiding philosophy of science to move forward.

How much is religion quantitatively involved in global climate politics? After assessing the role of the Conference of Parties to the United Nations Framework Convention on Climate Change from a normative perspective, this descriptive, transdisciplinary and unconventional study offers the first comprehensive quantitative examination of religious nongovernmental organizations that formally participate in its annual meetings, the largest attempts to solve the climate crisis through global governance. This study finds that although their numbers are growing, only about 3 percent of registered nongovernmental organizations accredited to participate in the conference are overtly religious in nature — and that more than 80 percent of those faith-based groups are Christian. Additionally, this study finds that religious nongovernmental organizations that participate in the conference are mostly from the Global North. The results call for greater participation of religious institutions in the international climate negotiations in order for society to address the planetary emergency of climate change.

Introduction: Dementia is a cognitive decline with patients often exhibit behavioural and psychological symptoms, severely affecting the quality of life and placing a heavy burden on caregivers. Acupressure has reported benefits for dementia. This study aims to critically review the available evidence for its use as a non-pharmacological therapy. Methods: Systematic search of major research databases for human clinical trials using acupressure as an intervention for dementia patients was conducted. Results were synthesised for the effects of acupressure on various outcome measures of interest for dementia.Results: Twelve clinical trials (N=973), including eight randomised control studies, were included in this review. The study sample was predominantly institutionalised residents with moderate to severe dementia. Baihui (GV20), Shenmen (HT7), Fengchi (GB20), Neiguan (PC6), Sanyinjiao (SP6), and Yingtang (EX-HN3) were the most used acupoints for intervention. Acupressure techniques employed in these clinical trials vary greatly with no standardised approach. This review finds inconsistent evidence in the effectiveness of acupressure in reducing agitation and behavioural disturbances. However, the treatment appears to improve their ease of care and reduce physical stress. Affixing acupressure devices on selected acupoints can also potentially improve psychiatric pain, anxiety, and depression. Long-term (6 months) treatment can potentially improve the cognitive function, activities of daily living, and quality of life of patients with mild to moderate dementia. The effect of acupressure on sleep disturbances remains unclear. Conclusion: More high-quality research on acupressure is needed to fill the gaps in knowledge and inform better care for dementia patients in the future.

Droplet-based microfluidics has revolutionized numerous fields such as biomedical research, pharmaceuticals, drug discovery, food engineering, flow chemistry, and cosmetics. This paper presents a comprehensive study focusing on the detection and characterization of droplets with volumes in the nanoliter range. Leveraging the precise control of minute liquid volumes, we introduced a novel spectroscopic On-Chip microsensor equipped with integrated microfluidic channels for droplet generation, characterization, and sensing, simultaneously. The microsensor, designed with Interdigitated-Ring-Shaped Electrodes (IRSE) and seamlessly integrated with microfluidic channels, offers enhanced capacitance and impedance signal amplitudes, reproducibility, and reliability in droplet analysis. We were able to make analyses of droplets length in the range 1.0-6.0 mm, velocity 0.66-2.51 mm/s, droplet volume 1.07nL-113.46nL. Experimental results demonstrated that the microsensor's has a great performance in terms of droplet size, velocity, and length, with a significant signal amplitude of capacitance and impedance, and real-time detection capabilities, thereby highlighting its potential for facilitating microcapsule reactions and enabling on-site real-time detection for chemical and biosensor analyses on-chip.

Domestic abuse and stalking in higher education (HE) have been overlooked in research in comparison to sexual harassment and sexual violence. This article reports on survey data from 725 students at a UK university using measures of ‘dating violence’ – physical and psychological violence from an intimate partner – and stalking from a US survey instrument (the Administrator Researcher Campus Climate Collaborative (ARC3) survey). According to this measure, 26% of respondents had been subjected to ‘dating violence’ and 16% to stalking behaviours. However, these findings need to be contextualised within a critical discussion of the use of the ARC3 survey tool in the UK context. The ARC3 questions on ‘dating violence’ focus on physical and ‘psychological violence’; the questions therefore omit further types of domestic abuse under UK definitions. In relation to stalking, US definitions – as captured in the ARC3 survey instrument – define specific behaviours. By contrast, in the UK stalking involves behaviours that engender fear or distress in a pattern of behaviour over time. These differences mean that the ARC3 modules on stalking and ‘dating violence’ would need to be significantly adapted to be suitable for use in the UK context.

Most recent university campuses follow the North American model, built on city limits or countryside, with large separate buildings in open green spaces. Studies suggest that prevalence and severity of mental health issues among university students are increasing over the past decade in most countries. University services were created to face this growing problem, however individual based interventions have limited effects on mental health and well-being of a large population. Our aim was to verify if and how the natural environment in Campuses is focused on programs to cope with the issue of mental health and well-being among students. Systematic review of literature was undertaken with search in Scopus and LILACS with the keywords “green areas” AND “well-being” AND “Campus”, following PRISMA guidelines. As a result, 32 articles were selected. Research on the topic is recent, mostly in the USA, Bulgaria, and China. Most studies used objective information on campuses’ greenness and/or university students’ perception. Mental health was usually measured by validated scores. Findings of all the studies indicated positive association between campus greenery and well-being of students. We conclude that there is a large potential for use of university campuses in programs and sites for students´ restoration and stress relief.

Innovation is rapidly growing and affecting various industries, including hydrocarbon processing. This study aims to conduct a comprehensive and organized review of the literature on innovation ecosystems and their performance. It will examine existing definitions of innovation ecosystems and related concepts and identify metrics and indicators for measuring innovation and entrepreneurial ecosystems. The term "innovation ecosystem" has gained considerable attention from scholars and practitioners over the past fifteen years. Despite the proliferation of research in this area, there are concerns about its fragmented knowledge base. While previous reviews have highlighted the theoretical connections between innovation ecosystems and related concepts, there is still a need for a more comprehensive understanding of the current state of innovation ecosystem research. The study used a systematic literature review approach that combines bibliographic coupling and content analysis methods, drawing on over 100 studies to identify five streams of current innovation ecosystem research: technology innovation, platform innovation ecosystems, regional development, innovation ecosystem conceptualization and theorization, and entrepreneurship and innovation. The study's contribution lies in decoding the intellectual structure of current innovation ecosystem research and providing targeted recommendations for future research.

Acute lymphoblastic leukemia (ALL) is a blood cancer that primarily affects children but also adults. It is due to the malignant proliferation of lymphoid precursor cells that invade the bone marrow and can spread to extramedullary sites. ALL is divided into B cell (85%) and T cell lineages (10 to 15%); rare cases are associated with the natural killer (NK) cell lineage (<1%). To date, the survival rate in children with ALL is excellent while in adults continues to be poor. Despite the therapeutic progress, there are subsets of patients that still have high relapse rates after chemotherapy or hematopoietic stem cell transplantation (HSCT) and an unsatisfactory cure rate. Hence, the identification of more effective and safer therapy choices represents a primary issue. In this review, we will discuss novel therapeutic options including bispecific antibodies, antibody-drug conjugates,chimeric antigen receptor (CAR)-based therapies, and other promising treatments for both pediatric and adult patients.

The main objective of this work is the design and implementation of self-adaptive capabilities in wireless sensors by applying control engineering and model-based design methodologies. It has been addressed the problem related to the changes in the flow of data packets through the network connection and the excess energy consumption that this causes in these devices. To design the solution, a systemic characterization of the scheduling and execution process of embedded tasks on the device has been carried out. This means defining cause-effect relationships in the system and its modelling theoretically and/or experimentally. In turn, these models facilitate the design of control strategies to improve the dynamic behavior of the system. As a solution, a self-adaptation strategy based on feedforward control algorithm has been designed and developed, which has been applied to improve the dynamic behavior and resource consumption. The developed solution has been satisfactorily evaluated experimentally.

In the software development process, the decision-maker (DM) has a range of problems inherent to its function. Wrong choices during software planning can bring great risk to the project. Therefore, the planning of software releases to be delivered to the customer should be well done. This is not an easy task because releases are made up of many requirements that contain complex variables that must be considered, such as precedence, cost, requirement stability, among other features that make the requirements-selection process challenging. To make this process less exhaustive, DM can use tools that facilitate this work. In software engineering, we can find fields of research specialists in this context, such as Search-Based Software Engineering (SBSE). The SBSE makes use of advanced metaheuristics to search for optimal solutions or the closest to it. In this work, we try to use another field of research to solve this same problem type, the Verbal Decision Analysis (VDA). To do this, we elaborate a workflow that will use the same source data, execute two solutions using the two search fields (SBSE and VDA) and compare the results. In the end, we evaluated and commented on the results.

Hot rolling tests of a low-alloy steel were conducted at a rolling temperature of 850 ℃ under different lubrication conditions, including benchmarks (dry condition and water) and water-based nanolubricants containing different concentrations of nano-TiO₂ from 1.0 to 8.0 wt%. The effects of nanolubricants on rolling force, surface roughness, thickness of oxide scale and microstructure were systematically investigated through varying nano-TiO₂ concentrations. The results show that the application of nanolubricants can decrease the rolling force, surface roughness and oxide scale thickness of rolled steels, and refine ferrite grains. In particular, the nanolubricant containing an optimal concentration (4.0 wt%) of nano-TiO₂ demonstrates the best lubrication performance, owing to the synergistic effect of lubricating film, rolling, polishing and mending generated by nano-TiO₂.

The aim of this paper is to contribute to the body of knowledge about Project-Based Learning (PBL) methodology in higher education by describing and analysing interrelations between competencies, and their contribution to knowledge transfer (KT) and students’ rating of the project. The sample consisted of 464 students from the Universities of Huelva (N=347; 74.8%) and Murcia (N= 117; 25.2%), enrolled in the second year of a degree in either Infant or Primary Education. Data was collected through a self-administered questionnaire comprising a total of 53 items measuring General, Specific and Transversal competencies, as well as students’ rating of the project. Competencies were selected from the course programmes for the degrees in Infant and Primary Education. Preliminary results showed that competencies were moderately to highly acquired after PBL, and that students reported notable KT as well as a positive assessment of the project. KT showed a high degree of association with students’ ratings and was established as a key factor in learning and learner satisfaction in higher education.

Background and Objectives: Treatment for antineutrophil cytoplasmic antibody-associated vasculitis (AAV) must deal with immunosuppression as well as infections associated with compromised immune system, such as tuberculosis (TB). Our aim was to overcome the gap in the literature concerning the risk of incidental TB after diagnosis of AAV. Materials and Methods: This retrospective population-based cohort study was based on the data from the National Health Insurance Research Database in Taiwan. We used a novel algorithm to identify patients with newly diagnosed granulomatous polyangiitis (GPA) or microscopic polyangiitis (MPA) between January 1, 2000 and December 31, 2012. The primary outcome was risk of incidental TB. Cox proportional hazard models were used to evaluate the association between AAV and incidental TB. Results: A total of 2,257 patients with AAV and a propensity-score matched cohort of 9,028 patients were studied. Overall, patients with AAV were at a 1.48x higher risk of contracting incidental TB than were patients in the matched cohort (adjusted HR 1.48; 95% confidence interval [CI], 1.02-2.15). Note that the highest risk of contracting incidental TB was in the first two years following a diagnosis of AAV, with a nearly 1-fold increase in risk (adjusted HR, 1.91; 95% CI, 1.01-3.60). Female AAV patients were 3.24x more likely than females without AAV to develop TB (adjusted HR 3.24; 95%CI, 1.85-5.67). Conclusion: Patients with AAV face an elevated risk of contracting incidental TB, particularly within the first two years after AAV diagnosis. The risk of contracting TB is higher among female AAV patients than among females without AAV.

Taking a typical forest underlying surface as the research area, this study employed the unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including tree height and canopy radius, which were used to improve the Noah-MP land surface model conducted in Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of CN-Din forest followed a Weibull distribution. The replacement of the parameters by these observed UAV would result in the Noah-MP model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux which could decrease up to -11% in the midday while increase up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately deliver the heterogeneity for the underlying surface.

The growing population with changing consumption patterns in developing countries is causing significant challenges with regards to solid waste management. Plastic wastes are particularly problematic, with single-use plastics leaking into the environment, including the marine environment, at an unprecedented rate. Approximately 80 percent of ocean plastics come from land-based sources or about 8 million tons are dumped into the ocean every year. Thailand was identified as one of the top 10 countries ranked by mass of mismanaged plastic wastes, with more than 60,000 tons per year entering the ocean through multiple outlets, including rivers. In the environment, plastic wastes can be degraded into small sizes (less than 5 mm), called microplastics (MPs), which could contaminate the ecosystems and the food chain, including foodstuffs and water supply. Tap water samples collected from a water supply treatment plant and Academic Institutions 1 and 2 in central Thailand were found to contain MPs about 304 ±90, 270 ±109 and 386 ±102 particles/L, respectively. In addition, MPs concentrations of 211 ±70 and 122 ±60 particles/L were also found in drinking water samples collected from commercial bottled water and membrane filtration water, respectively. The MPs sizes of 0-50 µm were most abundant in both the tap and drinking water samples whose shapes were mainly fragments and fiber. These data indicated potential health risks to the people who consume these water sources, and recommendations for health impacts minimization were proposed.

Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of our world. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness characteristic, biometrics systems will become also vulnerable, privacy being one of the most important challenge. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The following work paper represents an effort to present the main cryptographic techniques and algorithms that can give us the possibility to raise a certain level of secureness for privacy. We will show their own challenges (strengths and weaknesses). We will demonstrate how we can use the most common and well-known techniques and algorithms in order to get a maximum efficiency and a high level in assuring the integrity of the biometrics data.

Financial markets require a great deal of decision making from the investors and market makers. One metric that can help ease the process of decision making is investment risk which can be measured in two parts; systematic risk and idiosyncratic risk. Clear understanding of the volatilities in each risk component can be a powerful signal in recognizing the right assets to maximize the investment returns. In this paper, we focus on the idiosyncratic volatility values and pre-calculate the idiosyncratic volatility values for 31,198 members of NYSE, Amex and Nasdaq markets for the trades occurring between January 1963 and December 2019. Utilizing a subset of dataset, limited to Nasdaq100 index, we consider the application of machine learning techniques in predicting the idiosyncratic volatility values using the raw trade data to explore a data extension option for the future market trade records that have not yet occurred. We offer a deep learning based regression model and compare it with traditional tree-based methods on a small subset of our per-calculated idiosyncratic volatility dataset. Our analytical results show that the performance of the deep learning techniques is much more robust in comparison to that of the traditional tree-based baselines.

This study compares the effects of lecture-based instruction and process-oriented guided inquiry learning (POGIL)-based instruction on the self-efficacy performance of Grade 12 students. A quasi-experimental, pretest-posttest design was adopted to investigate and assess the impact of POGIL-based instruction versus lecture-based instruction on students’ performance as measured by three types of cognitive outcomes; Knowing, Applying and Reasoning (KAR). Two government high schools in Alain were selected as research sites, one for the boys and one for the girls. The total number of participants was approximately 110 students (N=110); 54 were assigned to treatment groups (25 girls and 29 boys), and 56 were assigned to control groups (27 girls and 29 boys). The treatment group was taught a circular motion unit in physics using POGIL-based instruction, while the control group was taught the unit using lecture-based instruction. The study's findings showed statistically significant differences between students of the control group and the treatment group in favour of the latter regarding their science performance, self-efficacy and science-related attitudes. Moreover, positive correlations were found between participants’ performance at the KAR test, self-efficacy and scientific attitudes towards scientific inquiry after the intervention. In conclusion, it is recommended to shift teaching towards POGIL-based instruction due to its positive impact on students’ performance and self-efficacy. It is also suggested to replicate the study to include government and private schools, elementary and high schools, teachers and advisors.

Beef has one of the highest climate footprints of all foods, and therefore the hamburger has been targeted for substitution by numerous plant-based alternatives. However, many consumers find the taste of these alternatives lacking, and thus we proposed a hybrid meat and plant-based burger as a lower threshold alternative for these consumers. The burger was made from 50% meat (beef and pork, 4:1) and 50% plant-based ingredients, including texturised legume protein and had a climate footprint less than half that of a beef burger. Texture and sensory properties were evaluated instrumentally and through a consumer survey (n = 381) using the check-all-that-apply (CATA) method. Moisture properties indicated a significantly juicier eating experience for the hybrid compared to a beef burger, which was supported by the CATA survey. From texture profile analysis the hybrid burger was significantly softer and less cohesive than a beef burger. Despite having different CATA term profiles overall liking of the hybrid and a beef burger were not significantly different. Penalty analysis indicated that “meat flavour”, “juiciness”, “spiciness”, and “saltiness” are the most important attributes for a burger. In conclusion, consumers may be open to reducing their meat consumption by way of hybrid meat and plant-based products.

This study aimed to evaluate the impact of selected pregnancy pathologies statistically depending on overweight/obesity and excessive maternal weight gain during pregnancy on women who gave birth in the years 2013–2015 at the Second Department of Gynecology and Obstetrics at the University Hospital in Bratislava, Slovakia. In a retrospective study, we analyzed data gathered from the sample, which consisted of 7,122 women. Our results indicate a positive statistical dependency of the groups of women with overweight and obesity and gestational hypertension (adjusted odds ratio [AOR]=15.3; 95% CI 9.0−25.8 for obesity), preeclampsia (AOR=3.4; 95% CI 1.9−6.0 for overweight and AOR=13.2; 95% CI 7.7−22.5 for obesity), and gestational diabetes mellitus (AOR=1.9; 95% CI 1.2−2.9 for overweight and AOR=2.4; 95% CI 1.4−4.0 for obesity). A higher incidence of pregnancies terminated by cesarean section was observed in the group of obese women. Gestational weight gain above the IOM (the Institute of Medicine) recommendations was associated with a higher risk of pregnancy terminated by C-section (AOR=1.2; 95% CI 1.0−1.3), gestational hypertension (AOR=1.7; 95% CI 1.0−2.7), and infant macrosomia (AOR=1.7; 95% CI 1.3−2.1). Overweight and obesity during pregnancy significantly contribute to the development of pregnancy pathologies and increased incidence of cesarean section. Systematic efforts to reduce weight before pregnancy through pre-pregnancy dietary counseling, regular physical activity, and healthy lifestyle should be the primary goal.

Flooding during the rainy season poses a significant threat to the city of Hargeisa, impacting the well-being of both its residents and the local ecosystems. This research focuses on urban flood control, with a specific emphasis on finding sustainable solutions for managing large stream in Hargeisa. The study identifies five key dimensions, including infrastructure, transportation, environmental soil, life, and property, as critical factors in addressing the issue. By employing a comparative method and collecting data through closed-ended questions, the research aims to analyze and weigh eleven potential solutions, seeking to identify the most effective approaches. The findings of the study indicate that constructing a dam emerges as a promising and sustainable solution, with a weightage of 70 percent. This highlights the potential of a dam in mitigating the impact of floods in the region. Additionally, considering the government's economic capacity, the implementation of check dams is identified as another viable option, with a weightage of 95 percent for reducing the flood power of the stream. These solutions offer practical and effective measures to address the recurring problem of flooding in Hargeisa. To support future decision-making and planning, the research underscores the need for establishing a comprehensive rainfall data database. This database would store relevant information on rainfall patterns, enabling better understanding and prediction of flood events. The study emphasizes the importance of collaboration between local government authorities, environmental organizations, and stakeholders to develop and implement effective flood control strategies. This research provides a systematic approach that can inform and benefit regional and global researchers, policymakers, and municipal governments in their efforts to address urban flood control challenges, not only in Hargeisa but also in similar contexts worldwide.

Alberta Cancer Exercise (ACE) is an exercise oncology program that transitioned from in-person to online delivery during COVID-19. The purpose of this work was to understand participants’ experiences in both delivery modes. Specifically, survivors' exercise facilitators and barriers, delivery mode preference, and experience with program elements targeting behaviour change were gathered. A retrospective cohort design using explanatory sequential mixed methods was used. 57 participants completed a survey, and 19 subsequent, optional interviews were conducted. Most participants indicated preferring in-person programs (58%), followed by online (32%), and no preference (10%). There were significantly fewer barriers (i.e., commute time) (p<0.01), but also fewer facilitators (i.e., social support) (p<0.01), to exercising online. Four themes were generated from the qualitative data surrounding participant experiences in both delivery modes. Key differences in barriers and facilitators highlighted a more convenient experience online relative to a more socially supportive environment in-person. For future work that includes solely online, focusing on building social support and a sense of community will be critical to optimizing program benefits. Beyond the COVID-19 pandemic, results of this research will remain relevant as we aim to increase the reach of online exercise oncology programming to more underserved populations of individuals living with cancer.

Olfactory ensheathing cells (OECs) are the glial cells that accompany axons from the olfactory epithelium to their targets in the olfactory bulb. They possess unique features that have made them the subject of much study as being potentially useful in cell-based therapeutic approaches to CNS repair. Investigation of OECs has demonstrated antigenic and morphological heterogeneity in their population. No marker specific to and selective for OECs have yet been identified, and many of the markers used are variably expressed by other glial cells. Even among OECs, these markers appear to vary in vivo (depending on their anatomical location, contact with other cells, and developmental timing) and in vitro. The variation across the population of OECs has compromised their isolation and characterization. It has also made the task of identifying meaningful subpopulations - with greater or lesser therapeutic utility - dependent on identifying the source of their variability. Such information would aid in both the harvest and experimental manipulation of OECs to optimize their therapeutic effect. One way to understand the nature of this variability is to seek its potential causes in vivo. This must begin with an examination of the structure of the olfactory nerve. Here, the structure and development of the primary olfactory projection are thoroughly reviewed with an emphasis on OECs and the cells with which they make contact. The relevant experimental results are also discussed. The weight of anatomical evidence indicates that the structural variations described in different locations and across species are mostly the result of spatiotemporal developmental factors. As such, the formation of the olfactory projection is mediated primarily by the source tissue, the olfactory epithelium. Cell-autonomous development is common elsewhere, and suits the evolutionary age and importance of olfaction, as well as its continued regenerative capacity. Our findings provide a more systematic anatomical understanding of this nerve. That understanding indicates that variation in axon ensheathment by OECs is an inherent feature arising from the flexibility of the ensheathing program. This perspective, along with the anatomical data reviewed here, can inform more carefully controlled laboratory investigations designed to uncover the detailed mechanisms governing OEC biology.

The feedback collection and analysis has remained an important subject matter since long. The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis. However, the student expresses their feedback opinions on online social media sites, which need to be analyzed. This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews. Our technique computes the sentiment score of student feedback reviews and then applies fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level. The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers.

Water scarcity challenges have necessitated the adoption of water-saving techniques in protected and nom-protected farming. This study aimed to assess the performance of a water-saving soil-less cultivation technique and to compare it with conventional soil-based cultivation in protected farming. The soilless technique used local gravel and a mixture of peat-moss, humin-substrate, and perlite in ratios of 4:3:1.5. Three irrigation regimes were imposed using emitters 8Lh-1 design discharge (D1) emitters with 6Lh-1 design discharge (D0.75) and 4Lh-1 de-sign discharge (D0.5) for the two cultivation methods during the growth cycle of tomato by drip irrigation. The vegetative growth, fruit yield and water consumption were measured and water productivity was determined. Moreover, an economic assessment was carried out by estimating and comparing economic coefficients for the two cultivation methods. Estimated coefficients include revenues, net profit, benefit-cost ratio, break-even levels of production and prices, revenues over variable cost, and revenues on investment. The tomato fruit yield under soil-based cultivation overtopped the yield under soilless cultivation. The water productivity under the soilless cultivation was almost twice that (24.3 kg m-3) of the soil-based cultivation (15.5 kg m-3). The soilless cultivation saved 50% of irrigation water applied by the conventional soil-based method, saving energy and soil from deterioration. Revenues and net profits stimulated by higher yield coupled with lower variable cos supported the soil-based cultivation. The economic assessment showed that both cultivation methods were economically viable. However, the soil-based cultivation method was more profitable due to its higher fruit yield. Overall, the results of this study suggest that the soilless cultivation technique is a viable option for wa-ter-saving cultivation. However, the soil-based cultivation method is still more profitable due to its higher fruit yield

The combined efect of shape and electrostatic complementarities (Sc, EC) at the interface of the interacting protein partners (PPI) serves as the physical basis for such associations and is a strong detterminant of their binding energetics. EnCPdock (https://www.scinetmol.in/EnCPdock/) presents a comprehensive web-platform for the direct conjoint comparative analyses of complementarity and binding energetics in PPIs. It elegantly interlinks the dual nature of local (Sc) and non-local complementarity (EC) in PPIs using the Complementarity Plot. It further derives an AI-based ∆G_binding with a prediction accuracy comparable to the state-of-the-art. This book-chapter presents a practical manual to conceptualize and implement EnCPdock with its various features and functionalities, collectively having the potential to serve as a valuable protein engineering tool in the design of novel protein interfaces.

In order to provide a new direction for the diagnosis and treatment of gastric cancer, the differentially expressed blood-based miRNAs in gastric carcinoma were obtained and analyzed from the datasets GSE113486, GSE112264 and GSE113740 by the SangerBox, the miRNA - target genes prediction, GO and KEGG functional enrichment analyses with DAVID 6.8, and the STRING database with Cytoscape, respectively. The correlation between the key miRNAs expression and the prognosis and diagnostic value of gastric cancer patients were detected by survival prognosis and ROC curve. QRT-PCR was used to detect the possible key miRNAs expression in human blood species. The dataset GSE108307 which shows the miRNAs affected by H. pylori infection was analyzed by GEO2R. The expression level of CagA and the clinically used gastric cancer markers were detected in human blood species for contrast. Five key blood-based miRNAs were determined, including hsa-miR-124-3p, hsa-miR-125a-3p, hsa-miR-29b-3p, hsa-miR-4276, and hsa-miR-575.The detection in human blood species as well as the cross analysis with H. pylori infection and clinically used markers expression suggested the importance and efficacy of the specific miRNAs in the early diagnosis and monitoring of gastric carcinoma. The study identified potential novel blood miRNA biomarkers of gastric cancer by bioinformatics and human blood species detection, which may give a new possibility of the important biomarkers for the diagnosis and prognosis of gastric cancer.

The chemical reaction between the quinolone antibiotic oxolinic acid (OA) and Fe(III), Zn(II), Ca(II), and Mg(II) ions results in the formation of metal-based complexes with the following formulas: [Fe(OA)(H2O)2Cl2]2H2O, [Zn(OA)(H2O)Cl]2H2O, [Ca(OA)(H2O)Cl], and [Mg(OA)(H2O)Cl]. We used analytical (C, N, H, Cl, metal analysis) and spectral (FT-IR, 1H NMR, UV-visible) data to structurally characterize the synthesized metal-based complexes of the OA molecule. We found that the OA molecule utilizes the two oxygen atoms of the carboxylate group and the pyridone C=O group to bind the investigated metal ions. The morphological properties of the synthesized OA complexes were assessed using X-ray powder diffractometry (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The biological properties, specifically antibacterial and antifungal activity, of the synthesized complexes were evaluated in vitro using the Kirby-Bauer disc diffusion protocol with five bacterial and three fungal strains. The complex containing Ca(II) ions exhibited remarkable antibacterial and antifungal activity against all tested microbial strains, surpassing or equaling the potency of the standard drugs (streptomycin for antibacterial assays and ketoconazole for antifungal assays).

Topological indices are invariant numerical fields of a graph that give facts about the structure of graphs and are found to be very helpful in predicting the physical properties of aluminophosphates. The characteristics of the aluminophosphates are similar to those of zeolites. Two examples of current applications are natural gas dehydration and humidity sensor. New frameworks are being synthesised by researchers in chemistry and materials science. There are many layers and holes in these substances. In this study, Vertex version of distance-based topological indices, the entropy of topological indices and their numerical analysis are explained.

Diabetes mellitus, a metabolic disorder that is persistent in nature, is identified by an elevated concentration of glucose in the bloodstream. The disease has become a major public health problem, affecting millions of people globally, and is associated with significant morbidity and mortality. The increasing prevalence of diabetes and the lack of effective therapeutic interventions have led to the exploration of alternative and complementary forms of therapy, including ethnomedicine. Ethnomedicine is the study of traditional medical systems and the medicinal plants used by Indigenous communities. In other words, Ethnomedicine refers to the traditional medical practices and beliefs of a particular cultural or ethnic group. The most popular example of traditional medicine is the use of Aloe vera for the treatment of various diseases such as sunburn, cuts, burns, hypertension, diabetes, and jaundice for thousands of years [1]. In recent years, there has been increasing interest in the potential role of ethnomedicine in the management of diabetes, given its widespread use in many communities and its potential to offer cost-effective and culturally acceptable treatment options. It encompasses a range of traditional healing practices, including herbalism, acupuncture, and massage therapy. Despite the inconsistencies, there is growing evidence to suggest that certain ethnomedical practices may be effective in the management of diabetes [2,3]. For example, several studies have shown that certain herbal remedies, such as cinnamon, ginseng, and bitter melon, may have potential benefits in terms of improving glucose control and reducing the risk of complications associated with diabetes. Evidence-based ethnomedicine is an approach that applies scientific principles and methods to evaluate the efficacy and safety of traditional medical practices. This approach is crucial in the development of effective and safe ways to treat diabetes. To date, there have been numerous studies conducted to examine the efficacy and safety of various ethnomedical interventions for diabetes, including herbal remedies, dietary changes, and physical activity [4]. However, it is important to note that not all ethnomedical interventions for diabetes have been thoroughly evaluated, and many remain unproven. Furthermore, some interventions may be associated with significant risks, particularly in terms of drug interactions and adverse effects. As such, it is crucial that any ethnomedical interventions for diabetes be carefully evaluated using rigorous scientific methods and that patients be advised to consult with their healthcare provider before using any such interventions. It is important to note that the results of these studies have been mixed, with some showing promising results, while others have failed to demonstrate significant benefits. In this chapter, the evidence-based current state of ethnomedicine for diabetes was reviewed. We first provide an overview of diabetes and its pathophysiology, followed by a discussion of traditional medicinal practices used to treat the disease. We then present a systematic review of the scientific literature on the use of ethnomedicine for diabetes, focusing on herbal remedies and dietary interventions. Our review found that several medicinal plants offered promising results to treat all types of diabetes. For example, Gymnema sylvestre, a traditional Indian herb, has been shown to reduce blood glucose levels and improve insulin sensitivity [5]. Additionally, the use of bitter melon (Momordica charantia) has been shown to reduce fasting blood glucose levels and improve glucose tolerance in individuals with type 2 diabetes [6]. Another important aspect of ethnomedicine for diabetes is the use of dietary interventions [7]. Traditional diets, such as the Mediterranean diet, have been shown to have beneficial particularly in terms of improving glycaemic control, reducing the risk of cardiovascular disease, and insulin sensitivity [8]. Additionally, the use of low-carbohydrate diets, such as the ketogenic diet, has been shown to improve glycaemic control in individuals with type 2 diabetes [9]. Traditional medicine has a long history of treating the symptoms and managing the condition. However, the efficacy and safety of these traditional practices have not always been scientifically tested, and there is a lack of standardization and regulation in the production and use of traditional remedies for diabetes. This creates a challenge for healthcare providers and patients, who need to ensure that the treatments they use are safe and effective. Additionally, there is a need for further research to understand the mechanisms by which traditional remedies may be effective in managing diabetes and to determine the optimal dosage and administration methods [9]. Finally, it is also important to understand that the use of traditional remedies may interact with conventional medications, leading to adverse effects; for example, the use of Chinese traditional medicine, known as “herb ginseng,” for the treatment of various health conditions, including diabetes sometimes cause the side effect such as dizziness, confusion, and fainting while interacting with the anti-diabetic medications [10]. Therefore, it is important to approach the use of ethnomedicine for diabetes with caution and under the guidance of a qualified healthcare professional. In conclusion, evidence-based ethnomedicine offers a promising approach to the treatment of diabetes. While further research is needed to fully understand the mechanisms and safety of these interventions, the results to date suggest that traditional remedies and dietary interventions have the potential to be effective in the management of this disease. However, it is important to approach the use of ethnomedicine for diabetes with caution and under the guidance of a qualified healthcare professional and to continue to conduct rigorous scientific research to fully understand the benefits and risks associated with these interventions.

Low-dimensional carbon-based (LDC) materials have attracted extensive research attentions in electrocatalysis because of their unique advantages such as structural diversity, low cost, and chemical tolerance. They have been widely used in a broad range of electrochemical reactions to relief environmental pollution and energy crisis. Typical examples include hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), carbon dioxide reduction reaction (CO₂RR), and nitrogen reduction reaction (NRR). Traditional “trial and error” strategies seriously slowed down the rational design of electrocatalysts for these important applications. Recent studies show that the combination of density functional theory (DFT) calculations and experimental research is capable of accurately predicting the structures of electrocatalysts, thus could reveal the catalytic mechanisms. Herein, current well-recognized collaboration methods of theory and practice are reviewed. The history of modern DFT, commonly used calculation methods, and basic functionals are briefly summarized. Special attention is paid to descriptors that are widely accepted as a bridge links the structure and activity, and the breakthroughs for high-volume accurate prediction of electrocatalysts. Importantly, correlating multiple descriptors are used to systematically describe the complicated interfacial electrocatalytic processes of LDC catalysts. In addition, machine learning and high-throughput simulations are crucial in assisting the discovery of new multiple descriptors and reaction mechanisms. This review will guide the further development of LDC electrocatalysts for extended applications from the aspect of DFT computations.

Malnutrition and dental caries in early childhood remain persistent and intertwined global health challenges, particularly for indigenous and geographically-remote populations. To examine the prevalence and associations between early childhood dental caries, parent-reported mouth pain and malnutrition in the Amazonian region of Ecuador, we conducted a cross-sectional study of the oral health and nutrition status of 1,407 children from birth through age 6 in the “Alli Kiru” program (2011-2013). We used multivariate regression analysis to examine relationships between severe caries, parent-reported mouth pain measures, and nutritional status. The prevalence of dental caries was 65.4%, with 44.7% of children having deep or severe caries, and 33.8% reporting mouth pain. The number of decayed, missing and filled teeth dmft) increased dramatically with age. Malnutrition was prevalent, with 35.9% of children stunted, 1.1% wasted, 7.4% underweight, and 6.8% overweight. As mouth pain increased in frequency, odds for severe caries increased. For each unit increase in mouth pain frequency interfering with sleeping, children had increased odds for underweight (AOR: 1.27; 95% CI: 1.02 – 1.54) and decreased odds for overweight (AOR: 0.76; 95% CI: 0.58 – 0.97). This relationship was most pronounced among 3-6 year-olds. Early childhood caries, mouth pain and malnutrition were prevalent in this sample of young children. Parent-reported mouth pain was associated with severe caries, and mouth pain interfering with sleeping was predictive of poor nutritional status. We demonstrate the utility of a parsimonious parent-reported measure of mouth pain to predict young children’s risk for severe early childhood caries and malnutrition, which has implications for community health interventions.

The microstructural evolution, thermodynamics and kinetics of Mo-21%Tm₂O₃ (mass fraction, %) powder mixtures during ball milling were investigated using X-ray diffraction and transmission electron microscopy. Ball milling induced Tm₂O₃ to be decomposed and then dissolved into Mo crystal. The supersaturated nanocrystalline solid solution of Mo (Tm, O) was obtained after 96 h of ball milling. The elements of Mo, Tm and O were distributed uniformly in the ball-milled particles. Based on the semi-experimental theory of Miedema, a thermodynamic model was developed to calculate the driving force of phase evolution. There was no chemical driving force to form a crystal solid solution of Tm atoms in Mo crystal or an amorphous phase because the Gibbs free energy for both processes was higher than zero. For Mo-21%Tm₂O₃, it was mechanical work, not negative heat of mixing, that provided the driving force to form supersaturated nanocrystalline Mo (Tm, O) solid solution.

Fossil-based plastics are significant contributors to global warming through CO₂ emissions. For more sustainable alternatives to be successful, it is important to ensure that consumers become aware of the benefits of innovations such as bio-based plastics, in order to create demand and a willingness to initially pay more. Given that consumer attitudes and (inaccurate) beliefs can influence the uptake such new technologies, we investigated participants’ attitudes towards fossil-based and bio-based plastic, their perceived importance of recycling both types of plastic, their willingness to pay, and their perceptions of bio-based plastic in four studies (total N = 961). The pre-registered fourth study experimentally manipulated information about bio-based plastic and measured willingness to pay for different types of plastic. The results suggest participants hold very favourable attitudes and are willing to pay more for bio-based products. However, they also harbour misconceptions, especially overestimating bio-based plastic’s biodegradability, and they find it less important to recycle bio-based than fossil-based plastic. Study 4 provided evidence that educating consumers about the properties of bio-based plastic can dispel misconceptions, retain a favourable attitude and a high willingness to pay. We found mixed evidence for the effect of attitudes on willingness to pay, suggesting other psychological factors may also play a role. We discuss how attitudes and misconceptions affect the uptake of new sustainable technologies such as bio-based plastics and consumers’ willingness to purchase them.

Background: Endometriosis is a female chronic inflammatory disease in which endometrial tissue develops outside the uterine cavity. It is a complex pathology, that significantly contributes to morbidity in premenopausal women, leading to chronic pain, infertility, and subfertility negatively impacting the physical, and emotional well-being and overall quality of life. The public health burden of endometriosis remains elusive and challenging to determine, and this uncertainty can lead to inadequate healthcare services and treatments. Objective: To estimate the incidence and prevalence of endometriosis in Italy using the hospital discharge records database. Population-based retrospective study. Nationwide between 2011 and 2020. Methods: From the National Hospital Discharge Database were selected all admissions with a diagnosis of endometriosis (ICD-9-CM, codes 617.x), supported by the presence of a procedure code of laparoscopy or any other surgical procedure allowing direct visualisation of the lesions. Main outcomes measures Incidence and prevalence of endometriosis were estimated for the entire 2010-2020 period and by individual year, analysing the time trend and variability in different geographical areas of Italy. Results: A total of 134,667,646 women aged 15–50 years with one or more hospitalisations for endometriosis in all Italian hospitals. The incidence of endometriosis in Italy during this period was 0.839 per 1000 women (CI95% 0.834-0.844), exhibiting a statistically significant decreasing trend over the years. A discernible north-south gradient was observed, with higher rates documented in the northern regions. The prevalence rate stood at 14.0 per 1000 during the same period, and a similar north-south geographical gradient was identifiable in the prevalence rates as well. Conclusions: The utilization of national-level hospital data enables the generation of incidence and prevalence data for endometriosis without variations in methods and definitions, facilitating the evaluation of temporal trends and regional comparisons. Understanding and quantifying this phenomenon is essential for appropriate healthcare planning in various Italian regions.

Chitosan is a copolymer of β-glucosamine and N-acetylglucosamine. Recent experiments showed that the degree and pattern of acetylation along the chitosan chain modulate the biological and physicochemical properties; however, the molecular mechanism is unknown. Here we apply the de novo all-atom molecular dynamics (MD) simulations to study chitosan’s self-assembly process at different degrees of acetylation and two different acetylation patterns. The simulations revealed that the 10-mer chitosan chains with 50% acetylation in either block or alternating patterns associate to form ordered nanofibrils comprised of mainly antiparallel chains in agreement with the fiber diffraction data of deacetylated chitosan. Surprisingly, regardless of the acetylation pattern, the same intermolecular hydrogen bonds mediate the fibril sheet formation while water-mediated interactions stabilize the sheet-sheet stacking. Moreover, the acetylated units are involved in forming the strong intermolecular hydrogen bonds (NH–O6 and O6H–O7), which offers an explanation for the experimental observation that increased acetylation lowers chitosan’s solubility. Taken together, the present study provides the atomic-level understanding the role of acetylation plays in modulating chitosan’s physiochemical properties, contributing to the rational design of chitosan-based materials with the ability to tune by its degree and pattern of acetylation. Additionally, we disseminate the improved molecular mechanics parameters that can be applied in MD studies to further understand chitosan-based materials.

The process of Targeted Opinion Word Extraction (TOWE), a critical component of aspect-based sentiment analysis (ABSA), revolves around identifying opinionated words linked to specific aspect-terms within sentences. Existing deep learning approaches, while effective, often overlook the syntactic structure of sentences, a factor that previous studies have identified as beneficial for TOWE. In this study, we introduce the Syntactic-Enhanced Deep Learning Model (SEDLM) that integrates syntactic structures into deep learning frameworks for TOWE. Our approach leverages syntax-driven opinion potential scores and syntactic inter-word connections, enhancing model performance. Additionally, we introduce an innovative regularization strategy aimed at distinguishing word representations in TOWE tasks. Our comprehensive analysis reveals that SEDLM sets new benchmarks in performance across multiple standard datasets.

The implementation of Boolean functions using Nano crossbar- based switching lattices has been suggested as a substitute for conventional CMOS-based approaches in digital circuits . This alternative may satisfy the needs of future electronic designs, con- sidering the expected end of Moore’s law. This study introduces CVM, a Crossbar-based circuit Verification through Modeling tech- nique

In this work, the inhibition properties of new bio-based lignine ILs on the corrosion of mild steel in an aqueous solution of 0.01 M NaCl were investigated by Potentiostatic Electrochemical Impedance Spectroscopy (PEIS), Cyclic Potentiodynamic Polarization (CPP). Moreover, the surface was characterized using SEM, EDS, and optical profilometry. The influence of cation and anion on the inhibitor properties and a possible synergistic effect were investigated. The IL choline syringate showed a promising performance, reducing the corrosion current after 24-hour immersion in 0.01 M sodium chloride, from 1.66 µA/cm2 for the control to 0.066 µA/cm2 with 10 mM of the IL present. In addition to the performance as a corrosion inhibitor, both components of this IL also meet or exceed current additional desired properties of such compounds, being readily available, economically efficient, and well tolerated in organisms and the environment.

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

Over recent decades, therapeutic proteins have had widespread success in treating a myriad of diseases. Glycosylation, a near universal feature of this class of drugs, is a critical quality attribute that significantly influences the physical properties, safety profile and biological activity of therapeutic proteins. Optimizing protein glycosylation, therefore, offers an important avenue to developing more efficacious therapies. In this review, we discuss specific examples of how variations in glycan structure and glycoengineering impacts the stability, safety, and clinical efficacy of protein-based drugs that are already in the market as well as those that are still in preclinical development. We also highlight the impact of glycosylation on next generation biologics such as T cell-based cancer therapy and gene therapy.

As a radiant light source within the dynamic range of most spacecraft payloads, the moon pro-vides an excellent reference for on-orbit radiometric calibration. This research hinges on the pre-cise simulation of lunar spectral irradiances and the Earth-based Moon observation geometry. The paper leverages the Hapke model to simulate the temporal changes in lunar spectral irradi-ances, utilizing datasets obtained from Lunar Reconnaissance Orbiter Camera (LROC). The re-search also details the transformation process from the lunar geographic coordinate system to the instantaneous projection coordinate system, thereby delineating the necessary observational geometry. The insights offered by this study have the potential to enhance future in-orbit space-craft calibration procedures, thereby boosting the fidelity of data gathered from satellite obser-vations.

Orbit and clock products are used in real-time GNSS precise point positioning without knowing their quality. This study develops a new approach to detect orbit and clock errors through comparing geometry-free and geometry-based wide-lane ambiguities in PPP model. The reparameterization and estimation procedures of the geometry-free and geometry-based ambiguities are described in detail. The effects of orbit and clock errors on ambiguities are given in analytical expressions. The numerical similarity and differences of geometry-free and geometry-based wide-lane ambiguities are analyzed using different orbit and clock products. Furthermore, two types of typical errors in orbit and clock are simulated and their effects on wide-lane ambiguities are numerically produced and analyzed. The contribution discloses that the geometry-free and geometry-based wide-lane ambiguities are equivalent in terms of their formal errors. Although they are very close in terms of their estimates when the used orbit and clock for geometry-based ambiguities are precise enough, they are not the same, in particular, in the case that the used orbit and clock, as a combination, contain significant errors. It is discovered that the discrepancies of geometry-free and geometry-based wide-lane ambiguities are coincided with the actual time-variant errors in the used orbit and clock at the line-of-sight direction. This provides a quality index for real-time users to detect the errors in real-time orbit and clock products, which potentially improves the accuracy of positioning.

Decision-making using evidence-based practice (EBP) is generally universally accepted by nurses. Such acceptance may affect the personnel’s behaviour towards patients, which is also demonstrated by taking into consideration the patient’s preferences, including the patient’s spiritual needs, in the care plan. The provision of such care requires the development of an attitude of approval and an adequate level of communicative competence, which will enable the actual implementation of the EBP. The purpose of our study was to assess the perception of spirituality and the nurse’s role in providing spiritual care, as well as the perception of the significance of communication skills in the approval of EBP in professional practice. A multi-centre cross-section study was conducted on a population of 1176 participants (459 undergraduate (Bachelor programme, BP) and 717 postgraduate students (Master programme, MP)) from 10 medical universities in Poland. Three tools were used in the study to evaluate the participants’ approach: Evidence-Based Practice Competence Questionnaire (EBP-COQ), The Spirituality and Spiritual Care Rating Scale (SSCRS), and Communication Skills Attitude Scale (CSAS). Structural equation modelling was used for the analysis. An analysis of structural equations revealed the presence of positive relationships of the attitude to spiritual care and the role of communicative competences with the approach to EBP regardless of the cohort. A significant difference was found related to the influence of age on the attitude toward learning communicative competences. The approval in this respect was observed to decrease with age in the MP group. Increasing approval of EBP requires strengthening the approach to activity-centred spiritual care, with the simultaneous development of a positive attitude towards learning communicative competences. The model reveals the need to integrate a humanistic approach with EBP, which can be achieved by planning different interventions in different groups of recipients: nurses, academic teachers and students.

The aim of this study was to introduce a new activity-based balance index by using accelerometer data. Twenty-seven junior soccer players from the Iranian premier league were selected. Four functional tests, consisting of one leg stance, dynamic Y balance, running and dribbling tests, were conducted to assess the players’ balance, activity and skill. During these four tests, besides their relative scores, the acceleration of their body center was also recorded. Activity-based balance index (ABI) was calculated using these acceleration data. The results showed positive correlations between ABI and both static and dynamic balance scores. Additionally, negative correlations were found between ABI and dribbling scores, which demonstrate the agility required for this skill. It seems that this new index achieves the evaluation of both the balance and the skill level of soccer players. Perhaps this is a new way of talent identification and also a re-development of balance tests from traditional to modern.

: Consumption of plant-based milk replacers has increased in recent years due to health benefits, benefits attributed mainly to the content of phenolic compounds, fatty acids, or bioactive compounds with antioxidant activity. In this context, we proposed to obtain two types of less studied plant-based beverages, namely lupine and chickpea beverages, as well as the possibility of getting these beverages using germinated seeds and even obtaining probiotic drinks through fermentation with Lactobacillus plantarum 299v. To evaluate the quality of the obtained products, we determined their content of proteins, fatty acids, organic acids, volatile compounds, and phenolic compounds. We evaluated the antioxidant activity of the obtained herbal drinks, and a load of probiotic microorganisms present after the fermentation process. Both lupine and chickpea drinks have the desired properties, high content of fatty acids and phenolic compounds, that bring probiotic benefits.

A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of Agent-based Complex Systems—ACS science—has a significant potential to handle such challenges. The advantages of ACS science for sustainability are addressed by way of identifying the key elements and challenges in sustainability science, the generic features of ACS, and the key advances and challenges in modeling ACS. Artificial intelligence and data science promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.

Wearable assistant devices play an important role in daily life for people with disabilities. Those who are hearing impaired may face dangers while walking or driving on the road. The major danger is their inability to hear warning sounds from cars or ambulances. Thus, the goal of this study is to develop a wearable assistant device for the hearing impaired to recognize emergency vehicle sirens on the road using edge computing. An EfficientNet-based fuzzy rank-based ensemble model was proposed to classify seven audio sounds, including human vocalizations and emergency vehicle sirens. This model was embedded in an Arduino Nano 33 BLE Sense development board. The audio files were respectively obtained from the CREMA-D dataset and Large Scale Audio dataset of emergency vehicle sirens on the road, with a total number of 8756 files. The seven audio sounds included neutral vocalization, anger vocalization, fear vocalization, happy vocalization, car horn sound, siren sound, and ambulance siren sound. The audio signal was converted into a spectrogram by the short-time Fourier transform as the feature. When one of the car horns, sirens, or ambulance sirens was detected, the wearable assistant device presented alarms through vibration and messages on the OLED panel. The performances of the EfficientNet-based fuzzy rank-based ensemble model in offline computing achieved an accuracy of 97.1%, precision of 97.79%, sensitivity of 96.8%, and specificity of 97.04%. In edge computing, the results were an accuracy of 95.2%, precision of 93.2%, sensitivity of 95.3%, and specificity of 95.1%. Thus, the proposed wearable assistant device has the potential benefit of helping the hearing impaired avoid traffic accidents.

Graphene-based nanomaterials (GNMs), including graphene, graphene oxide, reduced graphene oxide, and graphene quantum dots, may have direct anticancer activity or be used as nanocarri-ers for antitumor drugs. GNMs usually enter tumor cells by endocytosis and can accumulate in lysosomes. This accumulation prevents drugs bound to GNMs from reaching their targets, sup-pressing their anticancer effects. A number of chemical modifications are made to GNMs to facili-tate the separation of anticancer drugs from GNMs at low lysosomal pH and to enable lysosomal escape of drugs. Lysosomal escape may be associated with oxidative stress, permeabilization of the unstable membrane of cancer cell lysosomes, release of lysosomal enzymes into the cytoplasm, and cell death. GNMs can prevent or stimulate tumor cell death by inducing protective autopha-gy or suppressing autolysosomal degradation, respectively. Furthermore, because GNMs prevent bound fluorescent agents from emitting light, their separation in lysosomes may enable tumor cell identification and therapy monitoring. In this review, we explain how the characteristics of the lysosomal microenvironment and the unique features of tumor cell lysosomes can be exploited for GNM-based cancer therapy.

This study was designed to extend the literature on multicomponent interventions for the children of deaf adults (CODA) population. This study used two evidence-based behavior intervention strategies: pre-session pairing (PSP) and independent group contingency (GC). These strategies have been successfully used to decrease off-task behavior in elementary school children with various abilities and diverse backgrounds. However, the research on multicomponent interventions has yet to examine their effects on the CODA population in inclusive classrooms. This study used a concurrent multiple baseline design across participants with an ABC sequence to examine teacher-implemented PSP with independent GC in reducing the off-task behavior of three CODAs in an inclusive classroom at a public elementary school. The results show that the intervention successfully decreased off-task behavior for all participating CODAs. The results suggest that CODAs can adapt to classroom rules and expectations when PSP and independent GC are systematically applied to them in classrooms.

The recent covid crisis has proven important lessons for academia and industry regarding digital reorganization. Among fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and over. Moreover, drug development is a costly and time-consuming business, and only a minority of approved drugs return the revenue that exceeds the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper will review the most significant research on artificial intelligence in the de novo drug design for COVID-19 pharmaceutical research.

Over the last decade, a significant literature has emerged that advocates the potential of different Additive manufacturing (AM) technologies and printable polymeric materials. Nevertheless, large scale printing and complex geometric shapes, with curvatures and non-planar layer deposition, are a challenging process for the traditional gantry-based machine. The 3 degrees of freedom cartesian configuration restricted their capability to planar layered printing and restricted part dimensions. To date, many researchers have used industrial robots to overcomes this limitation. This review gives the reader a good overview of the FDM technique due to its scalability, cost efficiency and a wide range of material printability. A strong emphasis is laid on the PLA and PLA-based composites as promising materials for the FDM process applications. The second part of this paper links the successful use of these materials in the traditional printing process to large scale printing using the robot-based FDM process. This survey presents representative setups for robot-based AM and works that have been used these setups for non-planar material deposition. Finally, we conclude this paper by identifying opportunities for realizing new functional capabilities by exploiting robot-based AM, and we also present the future trends in this area.

The use of Information Communication Technologies (ICT) in education brings up new possibilities of promoting the learning and health experiences. In this sense, education contexts of 21st century must consider these two areas of knowledge, especially their integration. This article presents learning practices developed with mobile devices and games, in order to improve learning and well-being in children and adolescents undergoing cancer treatment in non-formal educational setting. The methodology is based on qualitative case studies with content-based data analysis, involving informal interviews and observation methods. The study considers data from 5 patients who participated in the research between 2015 and 2019. The results demonstrate a positive influence of the practices with mobile technologies and games in terms of learning and in the well-being feeling of patients during the treatment.

To develop a lower-cost, excellent performance, and environmentally friendly phe-nol-formaldehyde (PF) resin, soybean meal was used to modify PF resin, and soybean meal-phenol-formaldehyde (SMPF) resins were prepared. Their physicochemical properties and curing performance were investigated, showing that SMPF resins have higher curing tempera-tures than PF resin. The Fourier transform infrared spectroscopy (FTIR) results indicated that the cross-linking reaction occurred between the amino groups of soybean protein and the hy-droxymethyl phenol. Moreover, with the addition of soybean meal, the viscosity of SMPF in-creased while the gel time decreased. It is worth mentioning that SMPF-2 resin has favorable viscosity, short gel time, low curing temperature (135.78 °C), and high water resistance and bonding strength (1.01 MPa). Finally, all the plywoods bonded with SMPF resins have good water resistance and bonding strength, which could meet the Standard (GB/T 17657-2013, type I) for plywood. The optimized SMPF resins showed the potential application to replace part of PF resin in the wood industry.

Rapid haemostasis during surgery is essential when one wants to reduce the duration of opera-tions, reduce the need for transfusions, and above all when one wants to achieve better patient management. The use of haemostatic agents, sealants and adhesives improves the haemostatic process by offering several advantages, especially in vascular surgery. These agents vary widely in their mechanism of action, composition, ease of application, adhesion to wet or dry tissue, im-munogenicity and cost. The most used are cyanoacrylate-based glues (Glubran 2) or polysaccharide hydrogel-microsphere powder (AristaTMAH). This work is based on a retrospective study carried out on a sample of patients with different vascular diseases (FAV, pseudoaneurysm and PICC application) in which two different haemostatic sealants were used. The aim was to assess the safety, the advantages and the ability of both sealants to activate the haemostatic process at the affected site, also in relation to their chemical-physical characteristics. The obtained results showed that the application of Glubran 2 and AristaTMAH as surgical wound closure systems is effective and safe as the success achieved was ≥94% on anastomoses of FAV; 100% on stabilization of Picc catheters; ≤95% on pseudoaneurysms.

This study critically analyses the realities and experiences of gender-based harassment in cyberspace, and aims to unveil the shadows that shroud this phenomenon. It discloses the online spaces that disseminate detrimental attitudes towards women, despite their physical absence. Cyber violence has become a global issue and it causes significant economic and societal consequences. Recognizing and dealing with the adverse effects caused by demeaning cyber gender harassment is essential. The study raises questions to explore the kind of cyberbullying offences that are brought on by misogynistic inclinations in online environments and the experiences of the women who have gone through cyberbullying. This study uses semi-structured interviews and the IPA technique of the analysis of data to thoroughly examine the unique experiences of cyber harassment victims by applying a qualitative research approach. The study looks into various misogynistic cyber harassment offences and analyses women's accounts. Due to obstacles to justice, cyber violence and harassment replicate physical problems like spousal abuse and sexual harassment. A constant assault of intimidation and harassment results from the traditionally male-dominated character of cyberspace, which affects women's social, economic, and psychological well-being. Participants related horrifying tales of families' indifference and law enforcement officials' trivialization. Mental health problems increase isolation and prevent involvement in academic and professional activities. Women's well-being is exacerbated by societal blaming and secondary victimization. This brief analysis clarifies the intricacies of gender-based harassment in cyberspace and emphasizes the urgent need for efficient solutions to address this widespread issue.

Lactobacillus plantarum has been observed to play a crucial role in shaping the sensory properties of chili sauce. However, the specific taste-active metabolites responsible for the desirable flavor profile of chili sauce remain inadequately characterized. This study employed a combination of metabolomics and web-based computational tools analysis to investigate the dynamic changes in taste-active metabolites during chili sauce fermentation. Initially, metabolites were rapidly annotated using a feature-based molecular network, leading to the tentative annotation of 206 metabolites, of which a significant proportion had not been previously reported. Subsequently, the VirtualTaste tool identified dihydrosphingosine, lactic acid, isoleucine, phytosphingosine, and gluconic acid as potential taste markers for quality control. Finally, pathway enrichment analysis revealed that these components were primarily associated with amino acid tRNA, phenylalanine, tyrosine, and tryptophan biosynthesis, as well as sphingolipid metabolism. This study provides valuable insights into the mechanisms underlying the formation of the distinctive flavor of chili sauce.

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types.

The study aims to evaluate the Quorum Sensing (QS) system inhibition against some Gram-positive and Gram-negative bacteria detected by molecular modeling of R. cathartica L. plant extract. R. cathartica L. methanol extract was evaluated in vitro. The research was carried out for the possible role and mechanism of R. cathartica L. The antibacterial activity of R. cathartica L. seed extract on some Gram-positive and Gram-negative strains was evaluated using culture-based and computational analysis. Gentamicin (CN; 30 µg/ml, Bioanalyse) was used as an antibacterial control of the extract on the production potential of QS-dependent virulence factors on Pseudomonas aeruginosa PAO1 was investigated. Phytochemical analysis resulted in the identification of 23 phenolic phytochemicals. R. cathartica L. extract was observed to have antimicrobial activity against Gram-positive and Gram-negative bacteria at different rates (11.3 mm-16 mm). The inhibitory effect of R. cathartica L. extract on P. aeruginosa PAO1 (elastase 61%, pyocyanin 18%, and biofilm 61%) was recorded moderately. Phytochemical analysis revealed that the main component of the extract is kaempferol. Therefore, the binding potential of kaempferol on QS system receptors was investigated via molecular docking. Computational analysis showed that kaempferol can inhibit the QS system by preventing competitive ligands from connecting to LasR. This study explored the activity and mechanism of action for a new green alternative against resistance. might provide a mechanism for R. cathartica L. seed extract components and thus provide a new avenue for using R. cathartica L. seed extract as a green antibacterial agent.

The protection of grapevine from the diseases is now particularly focused on the development of environmentally friendly strategies. Although sulphur is not in itself a toxic substance, a large use towards powdery mildew, in organic vineyards especially, may cause problems to environment, health and safety of viticultural workers and plant phytotoxicity. The activity on powdery mildew of sulphur applied at doses reduced up to 50% in tank mixtures with silicates and Equisetum arvense based products, never tested on grapevine, was assessed. Two-year trials were carried out applying the products every 7-9 days in the period of greatest risk for spring ascosporic infections, in two organic vineyards in the Abruzzo region, Italy. The effectiveness towards the disease of the mixtures was demonstrated, often to a greater extent than that of full-dose sulphur, normally used in the vineyards. Furthermore, in vines treated with the mixtures, increases in yield quantity and quality, such as higher contents of soluble solids and lower levels of total acidity, have been shown. Due to the strong efficacy demonstrated on the leaves, silicon-based products + sulphur mixtures can also be recommended in eradicative applications, aimed at reducing the inoculum of the disease. The great activity of the mixtures demonstrated in this study suggests confirmation through further investigations on different cultivars and vine-growing areas at different levels of infection, also testing the effectiveness of individual silicon products against the disease.

A growing number of health conscious consumers are looking for animal protein alternatives with similar texture, appearance, and flavor. There has been a lot of interest in meat analogs as potential meat substitutes. However, research and development still needs to find any alternative non-meat materials. The objective of the current research was to develop fungi minced meat alternative (FMMA) from edible mushrooms. Pleurotus Sajor-caju (SC) was used as the starting material. SC mushroom was selected for starting materials based on high protein content (41.99%.) and sensory attributes. Chickpea flour was used to improve the textural properties by mixing with SC mushroom at a ratio of 0:50, 12.5:37.5, 25:25, 37.5:12.5, and 50:0 (w/w). Textural and sensory attributes suggest that SC mushroom to chickpea at a ratio of 37.5:12.5, shows higher acceptability of FMMA with the protein content up to 47%. Beetroot extract 0.2% (w/w), and 5% (w/w) canola oil showed the most acceptable color parameters and consumer acceptability. This research suggested that SC mushroom with 12.5% chickpea flour, 0.2% beetroot extract and 5% canola oil could be suitable ingredients for the mushroom-based FMMA.

The objective of the study was to investigate the gap between data and evidence-based decisions among healthcare professionals considering the enormous amount of individual and aggregate data collected. Our study assessed the capacity, skills, and knowledge of the Ministry of Health leadership staff to understand data management, analysis, utilization, and dissemination. Three key components were assessed: 1) Knowledge through true/false questions, 2) Level of Skill (and Competency) using a Likert scale, and 3) Understanding of Key Concepts and Tools based on a Likert scale. The 183 study respondents were diverse healthcare professionals from Kenya, Tanzania, and Rwanda. Majority of respondents had not received any training on data management, analysis, interpretation, and utilization techniques, further there was a significant difference between those who had received training versus those who had not(p=0.005). The respondents were competent in work-related experiences but lacked skills and knowledge on: data concepts and tools, study designs, and types of data analysis. These findings explain the gap between data management, analysis, utilization, and dissemination among health professional’s cadre. To enhance service delivery and optimal provision of health care, it is imperative to have all health care professionals receive a well-designed training on data management, analysis, interpretation, and utilization.

Recently, interest in STEM education has grown among researchers and educators, also considering the skills required to address the challenges of the 21st century. Supporting learning in STEM subjects is an open challenge, especially during secondary education, which is reflected in the implementation of innovative pedagogical practices, including approaches focused on Game-Based Learning (GBL). This study analyzed the main issues addressed by research on game-based educational approaches applied to STEM teaching and learning in secondary school and their evolving trends. A text analysis of abstracts published in the past decade was conducted using T-lab software. The “Word Analysis” function was used for preliminary visual mapping; then the “Specificity Analysis” and “Thematic Analysis of Elementary Contexts” functions were applied to explore changes in research directions and to map the themes covered by the most recent studies. The results showed that the implementation of games in STEM disciplines is a promising area of inquiry. A shift in research directions also emerged, currently more focused on studying how GBL can foster engagement and the emotional component of learning. Adapting to rapidly changing technology and integrating essential skills such as coding and computational thinking are additional challenges that the research community is facing.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.

Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based architecture to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data is extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimizes the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimizing computational performance compared to other models.

Since smart cities aim at becoming self-monitoring and self-response systems, their deployment relies on close resource monitoring through large-scale urban sensing. The subsequent gathering of massive amounts of data makes essential the development of event filtering mechanisms that enable the selection of what is relevant and trustworthy. Due to the rise of mobile event producers, location information has become a valuable filtering criterion as it not only offers extra information on the event described but also enhances trust on the producer. Implementing mechanisms that validate the quality of location information becomes then imperative. The lack of such strategies in cloud architectures compels the adoption of new communication schemes for IoT-based urban services. To serve the demand for location verification in urban event-based systems (DEBS), we have designed three different fog architectures that combine proximity and cloud communication. Moreover, we have successfully assessed their performance using network simulations with realistic urban traces.

Hepatic carboxylesterase 1(CES1) metabolizes many prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aim to develop a semi-physiologically based pharmacokinetic model(Semi-PBPK model) to simultaneously predict pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis(LC) patients. Six prodrugs(enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. The parameters including organ blood flows, plasma binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate(GFR) and gastrointestinal transit rate were introduced into the simulation. Pharmacokinetic profiles of these drugs and their active metabolites were simulated in 100 virtual subjects. The developed semi-PBPK model, following validation in healthy subjects, was extrapolated to LC patients. Most of the observations are within the 5% and 95% quantile of simulations from 100 virtual patients. The estimated AUC and Cmax are within 0.5-2-fold of observation. The sensitivity analysis showed that the decreased plasma exposure of active metabolite due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model has successfully predicted pharmacokinetics of CES1 substrates and their metabolites in healthy subjects and LC patients, which assists in tailoring dosages of CES1 substrates in LC patients.

Cost-effective community engagement is needed to address causes of mental illness related to social issues (i.e. isolation, stigma and lack of purpose) that are typically outside the scope of healthcare. This pilot study evaluated the relationship between clinical healthcare resources and a community-based social engagement organization in a medium-sized community in the midwestern US. Analyses were based on a retrospective longitudinal comparison of clinical visit frequency from two cohorts that joined the Momentum Center for Social Engagement (MC) and either frequently participated (Engaged; n = 9) or had extenuating circumstances limiting participation (Non-engaged; n = 3). The frequency of >1800 visits to the member’s primary mental healthcare provider were compared during the period from November 2016 - May 2021. Engaged MC members reduced frequency of regular visits to their primary mental healthcare provider by 50%, while Non-engaged MC members maintained clinical visit frequency. The financial value of reduced healthcare visits and associated wellbeing improvements was estimated to be $1.0 million, 95% CI: [$0.6-1.4 million], or roughly four times the budget received by the MC from the healthcare provider. Thus, the MC appears to be a valuable approach to improving mental health in conjunction with existing community healthcare services. Clinical implications include considering the unique MC-style community-based support as a component of practice.

This study explores the impact of the ‘pre-intervention effects’ of a community-based interventions. This refers to participatory research processes and parallel publicity in the media on changes in alcohol use and relevant mechanisms (rules and norms about alcohol, accessibility of alcohol in a formal setting) among adolescents before any intervention is implemented. In a quasi-experimental study, adolescent data were collected twice by means of self-report among adolescents living in two municipalities (control and experimental condition). Regression analysis showed pre-intervention main effects on adolescents’ perceived accessibility of alcohol in a formal setting. Moreover, among adolescents aged 15 years and older, the normative decline in strictness of rules and norms was less steep in the experimental condition compared to the control condition. Also, adolescents aged 14 years and younger in the experimental condition reported more weekly drinking compared to their peers in the control condition. No differential effects across gender were found. To conclude, applying a co-creational approach in the development of an intervention, not only contributes to more effective interventions in the end, but involvement of and discussions in the community at the start of intervention planning are contributing to changes in targeted factors. This implies that public discussions about the development of intervention strategies should be considered as an essential feature of co-creation in community-based interventions.

Environmental concerns, among other causes, are leading to meat replacement in the diet by healthy, nutritious and tasty foods. Alternative protein sources of plant origin can be an alternative to meat, but their low biological value proteins can be a problem. Novel foods, such as insect meals, can meet currently consumer demands. Therefore, this research has developed innovative prototypes of analogue burgers with animal and vegetable proteins. Concerned about health and allergies, a prototype incorporating soya to satisfy coeliacs was developed. An iterative and heuristic process was carried out to test the product development feasibility. The main raw materials used were insect flour (Tenebrio molitor), seitan and soya. In addition, oat and sodium alginate were used as binders. Shelf-life of the new product was evaluated by physicochemical (pH, aw, moisture, colour, acidity and peroxide index) and sensory analysis (quantitative analysis -QDA-). The production of the burger analogues was feasible. Product characterisation showed significant differences (p < 0.05) among samples for organoleptic properties, highlighting texture changes. Using a multivariate model, it was established “The best before date” at 7 days for all developed prototypes, conditioned by microbial growth. Finally, the spoilage model indicated an important contribution to bacterial growth with a notable modification in the pastiness and hardness of the burger analogues developed.

COVID-19 is a well-known respiratory disease spreading worldwide since January 2020, causing many deaths and massive pressure on health systems. This pandemic’s appearance compromised the health services’ sustainability and quality as many procedures were postponed or even canceled out, with an expected increase of adverse events like nosocomial infections, in-hospital deaths, and the worsening of the patients’ clinical status. Therefore, assessing whether the healthcare providers’ performance has changed is paramount. In this case, we evaluated the public hospitals in Portugal as the leading secondary health care providers in the country, which in turn has been highly affected by the pandemic. To this end, we developed a network Data Envelopment Analysis model serially relating efficiency and effectiveness. Using 2,795 observations from public hospitals and 18 variables, we observed consistent drops in efficiency when the pandemic started, followed by a recovery to levels above the pre-pandemic ones. Regarding effectiveness, we observed a positive trend during the evaluated period. In short, these results allow us to conclude that, apart from the great resilience of public healthcare providers, the Portuguese State was not prepared for a pandemic like COVID-19, but still the actions taken (including massive vaccination) were beneficial.

Carbon offsetting is currently a major tool in managing carbon emissions and the drive to Net-Zero. This study aims to identify the offsetting potential of existing conservation schemes, and whether carbon offsetting credits could potentially finance the continued management of the conservation activities. The results from Dorset, in the UK indicate that many existing conservation schemes in woodland, heathland and grasslands can not only enhance biodiversity but also capture significant amounts of carbon. We show that the cost per additional tonne of carbon sequestered as a result of conservation activities varies considerably between different conservation projects. On average, the cost of this offsetting is £80 per tonne CO2e sequestered and ranging between £120 and £0 depending on the project and whether existing biodiversity grants would be available. However, this figure was based on adapting and refining existing conservation projects, and did not involve expensive factors such as purchase of land, which make the prices potentially unrealistic. While the costs identified are higher than many offsetting schemes at present, it could present a useful option for those wishing to localise their offsetting, and could be combined with biodiversity credits or other credit schemes to make the higher costs more attractive.

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

Wetlands benefits can be summarized but are not limited to their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Over the past few decades, remote sensing and geographical information technologies has proven to be a useful and frequent applications in monitoring and mapping wetlands. Combining both optical and microwave satellite data can give significant information about the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing data from different sensors, such as radar and optical remote sensing data, can increase the wetland classification accuracy. In this paper we investigate the ability of fusion two fine spatial resolution satellite data, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, for mapping wetlands. As a study area in this paper, Balikdami wetland located in the Anatolian part of Turkey has been selected. Both Sentinel-1 and Sentinel-2 images require pre-processing before their use. After the pre-processing, several vegetation indices calculated from the Sentinel-2 bands were included in the data set. Furthermore, an object-based classification was performed. For the accuracy assessment of the obtained results, number of random points were added over the study area. In addition, the results were compared with data from Unmanned Aerial Vehicle collected on the same data of the overpass of the Sentinel-2, and three days before the overpass of Sentinel-1 satellite. The accuracy assessment showed that the results significant and satisfying in the wetland classification using both multispectral and microwave data. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, with an overall classification accuracy of approximately 90% in the object-based classification. Compared with the high resolution UAV data, the classification results give promising results for mapping and monitoring not just wetlands, but also the sub-classes of the study area. For future research, multi-temporal image use and terrain data collection are recommended.

Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.

Cells are influenced by several biomechanical aspects of their microenvironment, such as substrate geometry. According to the literature, substrate geometry influences the behavior of muscle cells; in particular, the curvature feature improves cell proliferation. However, the effect of the substrate geometry on the myogenic differentiation process is not clear and needs to be further investigated. Here, we show that the 3D co-printing technique allows the realization of substrates. To test the influence of the co-printing technique on cellular behavior we realized linear polycaprolactone substrates with channels in which a fibrinogen-based hydrogel loaded with C2C12 cells was deposited. Cell viability and differentiation were investigated up to 21 days in culture. The results suggest that this technology significantly improves the differentiation at 14 days. Therefore, we investigate the substrate geometry influence by comparing three different co-printed geometries – linear, circular, and hybrid structures (linear and circular features combined). Based on our results, all structures exhibit optimal cell viability (&gt; 94%) but the linear pattern allows to increase the in-vitro cell differentiation, in particular after 14 days of culture. This study proposes an endorsed approach for creating artificial muscles for future skeletal muscle tissue engineering applications.

Background: There is poor evidence about sensitivity to chemotherapy according to microsatellite instability (MSI)/mismatch repair (MMR) status in endometrial cancer (EC). Methodology: The RAME study is a retrospective analysis aiming to assess response to chemotherapy in MSI-high (h) /deficient (d) MMR and MSI- low (l)/proficient (p)MMR EC patients. Primary endpoints were recurrence-free survival (RFS) for patients with localized disease and progression-free survival (PFS) and overall survival (OS) in patients with advanced/recurrent disease. Results: 312 patients treated between 2010-2022 in 4 high volume Multicenter Italian Trial in Ovarian cancer and gynecological malignancies (MITO) centers were selected. 239 patients had endometrioid EC (76.6%), 151 had FIGO stage I at diagnosis (48.9%) and 71 were MSI-h/dMMR (22.8%). Median age was 65 (range 31–91) years. Among patients with localized disease, median RFS was 100.0 months (95%CI 59.4–140.7) for MSI-l/pMMR and 120.9 months (60.0-181.8) for MSI-h/dMMR (p=0.39). Seventy-seven patients received first-line chemotherapy for advanced/recurrent disease. Patients with MSI-h/dMMR ECs had a significantly worse OS (p=0.039). In patients receiving platinum-based chemotherapy, no statistically significant difference in PFS (p=0.21) and OS (p=0.057) were detected, although PFS and OS were numerically longer in the MSI-l/pMMR population. Conclusion: Patients with metastatic MSI-h/dMMR EC receiving first-line chemotherapy had a significantly worse OS.

K417G Ni-based superalloy is widely used in aeroengine turbine blade for its excellent properties. However, the aeroengine rotor blade zigzag crown appears early failure frequently, which is because of the wear problems occurring in the working process. Laser forming repairing (LFR) is a promising technique to repair these damaged blades. Unfortunately, the laser formed Ni-based superalloys with high content of (Al + Ti) have a high cracking sensitivity. In this paper, the crack characterization of the LFRed K417G, the microstructure, microhardness and tribological properties of the coating before and after laser remelting are presented. The results show that the microstructure of as-deposited K417G consists of γ phase, γ′ precipitated phase, γ + γ′ eutectic and carbide. Cracking mechanisms including solidification cracking, liquation cracking and ductility dip cracking are proposed based on the composition of K417G and processing characteristics to explain the cracking behavior of the K417G superalloy during LFR. After laser remelting, the microstructure of the coating has been refined, and the microhardness and tribological properties has been improved. Laser remelting can decrease the size of the cracks in the LFRed K417G but not the number. Therefore, laser remelting can be applied as an effective method for strengthening coating and as an auxiliary method for controlling cracking.

This paper presents an approach to teacher identity heritage as result of the implementation of a research device created through Arts-based Research (ABR) methods, specifically with video elicitation and video essay used as research tools. Two main objectives were raised. The first one, to establish the real relevance of focusing performance on teacher identity. The second one, testing a new methodological proposal specifically designed for this purpose, but still useful in other contexts where heritage identity is as present as in teaching. The device, Body-camera, involves a process that allows new ways to understand the creation of identities using video to encourage the production of new meanings by visual and oral data. The participants were teachers in training during their internship period. Some notions about teachers' identity heritage were revealed, and also preserved, firstly, through personal perspectives by video elicitations and secondly, through collective perspectives by video essays. Both are video structures used in ABR which mix creative experience, memories, life experiences, relationships and links that shape the teachers’ professional identity.

LR004 is a novel chimeric (human/mouse) monoclonal antibody developed for the treatment of advanced colorectal carcinoma with detectable epidermal growth factor receptor (EGFR) expression. We aimed to investigate the preclinical pharmacokinetics (PK) and in vivo biodistribution of LR004. The PK profiles of LR004 were initially established in rhesus monkeys. Subsequently, 125I radionuclide-labeled LR004 was developed and its binding activity to the EGFR antigen were evaluated. Furthermore, the biodistribution, autoradiography, and NanoSPECT/CT of 125I-LR004 in xenograft mice bearing A431 tumors were examined. The PK data revealed a prolonged half-life and nonlinear PK characteristics of LR004 within the dose range of 6–54 mg/kg. The radiochemical purity of 125I-LR004 was approximately 98.54%, and iodination of LR004 did not affect its specific binding activity to the EGFR antigen. In a classical biodistribution study, 125I-LR004 exhibited higher uptake in highly perfused organs than in poorly perfused organs. Prolonged retention properties of 125I-LR004 in tumors were observed at 4 and 10 days. Autoradiography and NanoSPECT/CT confirmed the significant accumulation and sustained retention of 125I-LR004 at the tumor site in xenograft mice. These findings demonstrated the adequate tumor targeting capabilities of 125I-LR004 in EGFR-positive tumors, which may improve dosing strategies and future drug development.

There is an international concern for reducing energy consumption and protecting the environment in the construction industry. The energy efficiency of a building depends on the thermal resistance of concrete, and utilizing concrete products with elevated thermal resistance can enhance this aspect. This study analyzes the impact of perlite, as an addition, on the physico-mechanical properties of concrete, with the aim of identifying perlite concrete products that will respond to the improvement of the heat transfer resistance of the building envelope. The study examines the effect of replacing different amounts of concrete aggregates with perlite in percentages of 10%, 20%, 30%, and 100%. The results show that substituting sand with perlite improves the thermal performance of concrete, but its mechanical properties are negatively affected. The research carried out highlighted that perlite can be successfully introduced in the production of concrete blocks used for external non-bearing wall panels, the outstanding feature being the reduction of energy consumption in buildings. Overall, the paper identifies an efficient and environmentally friendly way of using perlite in the construction industry, enhancing the energy efficiency of buildings while minimizing the environmental footprint caused by the construction industry.

Predictive maintenance (PM) algorithms are widely applied for detecting operational anomalies on industrial processes to trigger maintenance before a possible breakdown; however, much less focus has been devoted to the use of such PM predictions as feedback in automated process control mechanisms. They usually integrate preventive solutions to protect the machines, usually causing downtimes. The premise of this study is to develop a holistic adaptive process scheduling mechanism that incorporates PM analysis as a safety component to optimize the operation mode of an industrial process toward preventing breakdowns while maintaining its availability and operational state, thereby reducing downtimes. As PM is largely a data-driven approach; hence, relies on the setup, we first compare different PM approaches and identify a one-class support vector machine (OCSVM) as the best performing option for the anomaly detection on our setup. Then, we propose a novel pipeline to integrate maintenance predictions into a real-time adaptive process scheduling mechanism. It schedules for the most suitable operation, i.e., optimizing for machine health and process efficiency, according to the abnormal readings. To demonstrate the pipeline on action, we implement our approach on a small-scale conveyor belt system utilizing our Internet of Things (IoT) framework. The results show that our PM-based adaptive process control provides an efficient process with less or no downtime. We also conclude that a PM approach does not provide sufficient efficiency without its integration into an autonomous planning process.

Background: This year has seen the emergence of two major crises, a significant increase in frequency and severity of hurricanes and the COVID-19 pandemic. However, little is known as to how each of these two events have impacted the other. A rapid qualitative assessment was conducted to determine the impact of the pandemic on preparedness and response to natural disasters and the impact of past experiences with natural disasters in responding to the pandemic. Methods: Semi-structured interviews were conducted with 26 representatives of 24 different community-based programs in southern Louisiana. Data were analyzed using procedures embedded in the Rapid Assessment Procedure – Informed Community Ethnography methodology, using techniques of immersion and crystallization and focused thematic analysis. Results: The pandemic has impacted the form and function of disaster preparedness, making it harder to plan for evacuations in event of a hurricane. Specific concerns included being able to see people in-person, providing food and other resources to residents who shelter in place, finding volunteers to assist in food distribution and other forms of disaster response, competing for funds to support disaster-related activities, developing new support infrastructures, and focusing on equity in disaster preparedness. However, several strengths based on disaster preparedness experience and capabilities were identified, including providing a framework for how to respond and adapt to COVID and integration of COVID response with their normal disaster preparedness activities. Conclusions: Although prior experience has enabled community-based organizations to respond to the pandemic, the pandemic is also creating new challenges to preparing for and responding to natural disasters.

In this manuscript, an automated framework dedicated to design space exploration and design optimization studies is presented. The framework integrates a set of numerical simulation, computer-aided design, numerical optimization, and data analytics tools using scripting capabilities. The tools used are open-source and freeware, and can be deployed on any platform. The main feature of the proposed methodology is the use of a cloud-based parametrical computer-aided design application, which allows the user to change any parametric variable defined in the solid model. We demonstrate the capabilities and flexibility of the framework using computational fluid dynamics applications; however, the same workflow can be used with any numerical simulation tool (e.g., a structural solver or a spread-sheet) that is able to interact via a command line interface or using scripting languages. We conduct design space exploration and design optimization studies using quantitative and qualitative metrics, and to reduce the high computing times and computational resources intrinsic to these kinds of studies, concurrent simulations and surrogate-based optimization are used.

This study proposes a novel hybrid machine learning approach for modeling of rainfall-induced shallow landslides. The proposed approach is a combination of an instance-based learning algorithm (k-NN) and Rotation Forest (RF), state of the art machine techniques that have seldom explored for landslide modeling. The Lang Son city area (Vietnam) is selected as a case study. For this purpose, a spatial database for the study area was constructed, and then, was used to build and evaluate the hybrid model. Performance of the model was assessed using Receiver Operating Characteristic (ROC), area under the ROC curve (AUC), success rate and prediction rate, and several statistical evaluation metrics. The results showed that the model has high performance with both the training data (AUC = 0.948) and the validation data (AUC = 0.848). The results were compared with those obtained from soft computing techniques i.e. Random Forest, J48 Decision Trees, and Multilayer Perceptron Neural Networks. Overall, the performance of the proposed model is better than those obtained from the above methods. Therefore, the proposed model is a promising tool for landslide modeling. The research result can be highly useful for land use planning and management in landslide prone areas.

Intersectoral and intermunicipal cooperation are still underdeveloped spheres of public and economic development policies. Academic discussions are invariably focused on pro-competitive activities, the economic efficiency of which is not always sufficient. In this paper the authors attempt to identify factors leading to cooperation between local government authorities and economic entities, focusing on examples from the forest and wood-based sector in Poland. These processes are analysed in the framework of the New Institutional Economy, both in the theoretical and practical context.

Within an amplicon-based metagenomic study of Archaea, Fungi, and Bacteria in Livingston Island, Maritime Antarctica, in many of the samples antagonisms between these three super kingdoms were observed under the form of an inversely proportional dependence of the richnesses of the three types of microorganisms. This was quantified - based on the observed numbers of the total tags and the numbers of the operational taxonomic units (OTUs), as well as based on four alpha diversity parameters – the Shannon, the Simpson, the Chao1, and the ACE indices. We found that the most discriminative results in the antagonism measuring were observed in the comparison of the numbers of the OTUs and the ACE community richness estimator. The antagonism between Archaea and Fungi was strongest, followed by that of Archaea and Bacteria. The Fungi-Bacteria antagonism was slightly detectable. Pearson and Spearman correlation analysis also showed a statistically significant negative correlation between the fungal and archaeal effective tags, while the correlation between archaeal and bacterial diversity was positive. Indications of the order of primary microbial succession in barren ecological niches were also observed, demonstrating that Archaea and Bacteria are the pioneers, followed by Fungi which in time would displace Archaea.

Evidence-based data for endometriosis management are limited. Experiments are excluded without adequate animal models. Data are limited to symptomatic women and occasional observations. Hormonal medical therapy cannot be blinded if recognised by the patient. Randomised controlled trials are not realistic for surgery since a variable disease with low numbers. Each diagnosis and treatment is an experiment with an outcome and experience is Bayesian updating from the past. If the experience of many is similar, this has more value than an opinion. The combined experience of a group of endometriosis surgeons was used to discuss problems in the management of endometriosis. Considering endometriosis as several genetically/epigenetically different diseases is important for medical therapy. Imaging cannot exclude endometriosis and diagnostic accuracy is limited for superficial lesions, deep lesions, and cystic corpora lutea. Surgery should not be avoided for emotional reasons. Shifting infertility treatment to IVF without considering fertility surgery is questionable. The concept of complete excision should be reconsidered. Surgeons should introduce quality control and teaching should move to explain why it is done. The perception of information has a personal bias. These are the major problems in the management of endometriosis identified by the combined experience of endometriosis surgeons.

Polymeric wet-strength agents are important additives used in the paper industry to improve the mechanical properties of paper products, especially when they come in contact with water. These agents play a crucial role in enhancing the durability, strength, and dimensional stability of paper products. The aim of this review is to provide an overview of the different types of wet-strength agents available and their mechanisms of action. We will also discuss the challenges associated with the use of wet-strength agents and the recent advances in the development of more sustainable and environmentally friendly agents. As the demand for more sustainable and durable paper products continues to grow, the use of wet strength agents is expected to increase in the coming years.

Nickel based superalloys finds extensive usage in manufacturing of intricate part shapes in gas turbine, aircraft, submarine, and chemical industries owing their excellent mechanical property and heat resistant abilities. However, machining of such difficult-to-machine alloys up to the desired accuracy and preciseness is a complex task owing to a rapid tool wear and failure. In view of this, present work proposes an experimental investigation and optimization of process parameters of the cryogenic assisted turning process during machining of Nimonic C-263 super alloy with a multilayer CVD insert. Taguchi’s L-27 orthogonal array is used plan the experiments. Effect of input parameters viz. cutting speed (N), cutting feed (f), depth of cut (d) are studied on responses viz. surface roughness (SR), nose wear (NW) and cutting forces (F) under hybrid cryogenic (direct+indirect) machining environment. A scanning electron microscope (SEM) analysis is carried out to explore the post-machining outcomes on the performance measures. The multiple responses are converted in to single response and ranked according to Taguchi based gray relational grade (TGRG). Feed rate (f) is found to be the most influential parameter from the analysis of variance of GRG. The means of GRG for each level of process parameters are used to improve the optimal process parameters further. Finally, the confirmative experiment is performed with these optimal set of process parameters which showed an improvement of 9.34% in the value of GRG. The proposed work can be beneficial to choose ideal process conditions to enhance the performance of turning operation.

The expedited development of drugs targeting gene products associated with insulin resistance holds the potential to enhance our comprehension of type 2 diabetes mellitus (T2DM). The virtual screening based on a three-dimensional (3D) protein structure has been expected as potential technique to accelerate a development of molecular target drugs. Among the targets implicated in insulin resistance, genetic characterization and protein function of Grb14 have been clarified without contradiction. The Grb14 gene displays notable variations in T2DM, and its gene product known to inhibit the function of the insulin receptor (IR) by directly binding to the tyrosine kinase domain. In the present study, a virtual screening, based on 3D structure of IR tyrosine kinase domain (IRβ) in complex with part of Grb14, was conducted to find compounds that can disrupt the complex formation between Grb14 and IRβ. First, ten compounds were selected from 154,118 compounds via hierarchical in silico structure-based drug screening, composed of grid docking-based and genetic algorithm-based programs. The experimental validations suggested that the one compound can affect blood glucose level. The molecular dynamics simulations and co-immunoprecipitation analysis showed that the compound did not completely suppress the protein–protein interaction between Grb14 and IR, though competitively bound to IR with the tyrosine kinase pseudosubstrate region in Grb14.