In 2014, the International Union for Conservation of Nature adopted the Red List of Ecosystems (IUCN RLE) criteria as the global standard for assessing risks to terrestrial, marine, and freshwater ecosystems. Identifying and quantifying the impacts of biodiversity assessments on the status of nature is key to justifying continued investment in assessments and enabling strategic planning to maximize future impact. In this policy perspective, we use an established impact evaluation framework to identify the impacts of the IUCN RLE since its inception. To date, 1,397 ecosystem units in 100 countries have been assessed following the IUCN RLE protocol. Systematic assessments are complete or underway in more than 25 countries and two continental regions (the Americas and Europe). Countries with established ecosystem red lists have already used them to inform legislation, land-use planning, protected area expansion, monitoring and reporting, and ecosystem management. IUCN RLE indices based on systematic assessments have high potential to inform global biodiversity reporting for the Aichi Targets and the United Nations Sustainable Development Goals. Expanding the coverage of IUCN RLE assessments, building capacity to undertake them, and establishing stronger policy instruments to manage red-listed ecosystems will be key to maximizing conservation impacts over the coming decades.

This study presents the development and pilot implementation of an assessment and shared deci-sion-making methodology called the Gezamenlijk Inschatten van Zorgbehoeften (GIZ), designed for youth (health) care professionals working with children and families. The three-phase approach included a needs assessment, development of the GIZ methodology, and pilot implementation in a preventive youth health care and youth care setting, involving parents, adolescents, and youth (health) care professionals. The needs assessment produced nine criteria that the GIZ methodology needed to meet. Based on these criteria, the GIZ methodology was developed and described using the Template for Intervention Description and Replication (TIDieR). The pilot implementation demonstrated high client engagement, satisfaction, and feasibility in daily practice. The GIZ ap-proach promotes appropriate support for families by improving the joint assessment and shared decision-making process in youth (health) care. This study supports the implementation of GIZ in youth (health) care practice and highlights the need for further focus on implementation and sus-tainability.

Background: The validation of measuring instruments in health is a requirement to be able to use them safely and reliably. The Short Physical Performance Battery (SPPB) tool is an instrument widely used in the clinic and validated in numerous countries and languages and for different populations. The objective of this research was to determine the psychometric properties of SPPB for a sample composed of institutionalized Spanish older adults. Methods: Multicenter study of the psychometric properties of the Short Physical Performance Battery tool with a convenience sample of 194 institutionalized older adults. Reliability (internal consistency), validity (construct validity and convergent validity) tests were performed. Results: The results show a very good internal consistency, construct validity and convergent validity. In addition, the factorial structure of the SPPB is provided, which reflects that it is a unidimensional scale. Conclusions: In conclusion, the Short Physical Performance Battery is a valid and reliable tool for use with institutionalized older adults. Its use is recommended as part of the Comprehensive Geriatric Assessment for the evaluation of the physical or functional sphere. Authors should include one of the following statements about the registration status of the manuscript here: This study was prospectively registered and approved by the Ethics Committee of the University of Burgos (IR 11/2018).

The rationale of this study is to explore underlying sustainability assessment constructs in the context of WCSM implementation as a key focus by manufacturing industries in the journey of achieving world-class status in their manufacturing operations. This study primarily intends to collect primary data from 143 plant managers and supervisors through the structured questionnaires at select manufacturing companies in south India on the basis of area-cum-purposive sampling technique. The survey questionnaire is designed exclusively to reflect the sustainability assessment dimensions in terms of social, economic and environmental issues to examine the impetus of WCSM implementation on the competitive advantage of manufacturing companies. The empirical findings of this study clearly revealed that sustainable manufacturing practices, sustainability programs, creation of sustainable products, safety for employee, community and product, operational efficiency and integration of sustainability goals in day-to-day manufacturing activities were considered to be the key indicators by the manufacturing firms in their never-ending journey towards becoming the world class. Moreover, the WCSM practices & techniques adopted by sample manufacturers have a substantial positive influence on the achievement of competitive advantage in their manufacturing and business operations.

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

The COVID-19 outbreak has severely affected the social and economic conditions across this globe. Little is known about the relationship of COVID-19 with countries’ economic and socio-demographic status. Publicly available data on COVID-19 test rate, attack rate, case fatality rate, and recovery rate were analyzed in relation to country’s economic status, population density, median age, and urban population ratio. We also conducted multinomial logistic regression analysis to predict the influence of countries’ social and economic factors on COVID-19. The results revealed that the median age had significant positive correlation with attack rate (r=0.2389, p=0.003), case fatality rate (r=0.3207, p=0.000) and recovery rate (r=0.4847, p=0.000). The urbanization has positive significant correlation with recovery rate (r=0.1957, p= 0.016). The multinomial logistic regression analysis revealed low-income countries are less likely to have an increased recovery rate (p=0.000) and attack rate (p=0.016) compare to high-income countries. The lower-middle-income and upper-middle-income countries are less likely to have an increased recovery rate (p=0.000 and p=0.001, respectively) compared to high-income countries. Based on the result of this study, these economic and socio-demographic factors should consider in designing appropriate preventive measures as a next step. The low and lower-middle-income countries should invest more in health care services to lower the case fatality rate and increase test and recovery rates as part of pandemic preparation like COVID-19. As the number of COVID-19 attacks, death and recovery rates are constantly changing; however, the intensive study is required to obtain a clear picture.

Background: For the past two decades, the Copenhagen Psychosocial Questionnaire (COPSOQ) has been established as a valid instrument to measure psychosocial stress at work. Nowadays, the COPSOQ international network is responsible for the monitoring and improvement of COPSOQ. 2019, a new questionnaire was published, and the Greek version is now being validated. Methods: Measurement qualities of the Greek COPSOQ III have been explored in adherence to the usual requirements of a validation study as defined by DIN EN ISO 10075-3. A sample of observations from 2.189 participants surveyed with the COPSOQ in Greece was used to validate the current version with appropriate statistical analyses. Exploratory factor analysis was used to assess statistical relations for many scales. Results: With its 108 items and 40 scales, the Greek COPSOQ III includes all psychosocial work factors that have been internationally validated and remain compatible with about 72% of the COPSOQ III German version content. Beyond primary results, congruence with widely used theoretical approaches like the Demand-Control(−Support) model (DCM) or the Job Demands-Resources model (JDR) is generally satisfactory. In summary, our validation study for the Greek COPSOQ III version showed adequate reliability and validity, which is in line with the COPSOQ III questionnaire from other European countries, and it is also compatible with the validation of the German COPSOQ III (Lincke, 2021). Our regression analysis showed that the 34 psychosocial work factors (34 “context” scales) could adequately predict the scores of the satisfactory and health scales (6 “outcome” scales). The analysis also indicated the top five (5) predictors (context variables) for each of the six (6) “effect” scales (outcome variables). Conclusions: With the launch of COPSOQ III in Greece, current and new workplace psychosocial aspects could be explored. COPSOQ III(GR) is a beneficial instrument for enterprise research and risk assessment.

This study presents a fit-for-purpose evaluation of commercially available portable sensor systems, measuring PM, NO2 and/or BC, through extensive lab- and field benchmarking. The main aim of the study is to identify sensor systems that can be used for mobile monitoring by citizens to assess dynamic exposure in ambient air. After an initial literature study and market search resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked in laboratory and real-word conditions. We evaluated comparability to reference analyzers, sensor precision and sensitivity to temperature, humidity and O3. Moreover, we evaluated if accuracy can be improved by the lab and field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM and BC, but maturity of the tested NO2 sensors is still low and additional efforts are needed in terms of signal noise and calibration. The horizontal accuracy of the build-in GPS was generally good achieving a <10m horizontal accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and exposome impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.

The authors present a framework for assessing seasonal events which may influence maritime operations. Most maritime-related research tends to focus on single events, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations, while other factors, such as cargo peaks or cultural activities, could also shape maritime systems. By integrating data from emergency management databases and weather information sources with other inputs, the authors created a matrix of regionally specific predictable events that may occur within a region by time of year. The matrix was vetted with various stakeholder groups to verify the information in the matrix. The main findings were that a seasonal event matrix is helpful as a reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.

The rise in both the frequency of natural disasters and the ubiquity of artificial intelligence has led to novel applications of new technologies in improving disaster response processes, such as the labor-intensive assessment of disaster damages. Assessment of residential and commercial structure damages, a precursory step to government agencies being able to provide most of their financial assistance, has benefited from aerial and satellite imagery-based computer vision models; however, limitations of using such imagery include the ground structures being obscured by clouds or smoke, as well as the lack of resolution to distinguish individual structures from others. Using a different data source, we propose a damage severity classification model using ground-level imagery, focusing on residential structures damaged by wildfires. This classifier, a Vision Transformer (ViT) model trained on over 18,000 professionally labeled images of damaged homes from the 2020-2022 California wildfires, has achieved an accuracy score of over 95%. Further, we have open sourced the training dataset–the first of its kind and scale–as well as built a publicly available web application prototype, which we demoed to and received feedback from disaster response officials, both of which further contribute to the broader literature beyond the proposed model.

Although agricultural crops production systems in subtropical plateau regions currently pose high environmental risks, especially in developing countries, their environmental impacts and emission-reduction potentials remain unclear, and the development potential of such systems is likely huge. We conducted a case study in Yunnan Province, China, to quantify the environmental impacts from crop production during 2002–2021. The life cycle assessment method was employed to identify factors driving the environmental impacts, and potential mitigation strategies were proposed. The yield and total nutrient input of grain crops in Yunnan Province increased over the 20-year period, and environmental footprint of crops production in Yunnan Province was higher than that of other regions. Average annual mean greenhouse gas (GHG) emissions and soil acidification potentials (AP) and water eutrophication potentials (EP) of crops production during 2002–2021 were 732 kg CO2-eq·Mg-1, 15.8 kg SO2-eq·Mg-1, and 2.7 kg PO4-eq Mg-1, respectively. GHG emissions from g crops mainly originated from applying agricultural materials during the crop life cycle. There was a significant correlation between surplus nitrogen and environmental impacts. Scenario testing showed that through crop sowing, nutrient regulation, and crop management, the crop yield could be increased and environmental costs could be reduced. The greatest reductions were found in wheat production: 53.1%, 67.9%, and 67.7% for GHG emissions, AP, and EP, respectively. Adopting comprehensive agricultural management measures could reduce the negative impact of crops production on the environment in subtropical plateau areas and achieve sustainable agricultural development.

Certain services can help avoid environmental impact in larger contexts. However, there is no commonly agreed bottom-up methodology for calculation of the total net reduction effect of specific digital services. Life Cycle Assessment (LCA) is a common denominator for most methodologies. The most common method is the Attributional LCA (ALCA), and recently the emerging handprint ALCA estimating so-called positive environmental impacts. Moreover, Consequential LCA (CLCA) can be used to capture market effects. The third conceptual approach is Input-Output LCA. The purpose is to propose and test a new method based on some of the existing ones. The existing concepts are compared and a synthesis is made to create a practical but still useful method. The new method is applied to two illustrative cases in the Information and Communication Technology (ICT) domain; the introduction of a 5G enabled drone for pipe inspection and the 5G enabled health consultation. Compared to simplified ALCA, the difference between the absolute score for the baseline system and the target system changes up to 15% when the proposed simplified CLCA (SCLCA) method is used. The results show that SCLCA, when combined with analytical methods for expressing digital ICT services’ own impact, is a fruitful approach which is both practical and feasible.

Pasture-based production systems are predominant in major beef-producing countries, however, these systems lack validated protocols to assess animal welfare under commercial conditions. The objective of this study was to validate an animal welfare protocol for fattening Zebu cattle farms in tropical pasture systems. The initial protocol was developed with the participation of producers, professionals, the general public, and the Colombian health authority, through workshops with a participatory approach and collaborative knowledge management. The validation was carried out in 24 pasture-based commercial Zebu cattle farms in the middle Magdalena region of Colombia. Visits were made with an average duration of 2.5 hours, which included the evaluation of 788 fattening cattle. The protocol evaluated animal-based, resource-based, and livestock management indicators through a questionnaire-guided interview to evaluate cattle handling and health, animal-based measurements, and documentation management. A protocol validation process was carried out by selecting indicators that remained unchanged, adjusting those that were feasible to implement, and eliminating inadequate or unnecessary indicators. The application of the protocol demonstrated that there are valid and feasible measures to include in the evaluation protocols of pasture-based fattening systems. Likewise, the active participation of producers is crucial to achieving a greater commitment to the implementation of this protocol.

The contractual relationship between the processing firm and the broiler smallholder presents incessant conflicts of interest and inequality due to technical and economic discrepancies, leading to an undervaluation of the producers' remuneration. This study aims to deepen the discussions in searching for a more balanced monetary exchange between processing firms and broiler smallholders based on scientific aspects. For this, the Emergy theory and its concepts were used in considering a representative broiler production system at Concórdia, Santa Catarina, Brazil. This study suggests the inclusion of cultural information in the Emergy-based model calculation. For the broiler smallholder, cultural information showed the highest Emergy contribution (62.95%; transformity = 1.73 ×10^8). However, only considering cultural information was not sufficient to increase the sustainability of the broiler production system. The results highlight an imbalance of the monetary exchange between agroindustry and broiler smallholder payment for both the economic and Emergy-based payment. Both estimated payments were higher than the practiced payment value (0.24 USD/broiler as well as 0.32 USD/broiler and 1.62 EmUSD/broiler, respectively). Thus, evaluating the “(eco)cost” in Emergy-based accounting recognizes that production depends not only on tangible physical resources but also on knowledge, skills and information (“iceberg of value” thinking). Policy and decision makers must, therefore consider the promotion of public policies that subside initiatives, including social and environmental welfare programmes.

Community co-creation is increasingly crucial to the building of sustainable societies. Communities must proactively and independently create value chains in the face of many wicked problems. However, practical frameworks and tools for facilitating community co-creation require further development. As such, for this paper, we propose a theoretical framework for analyzing community co-creation value chain mechanisms based on a narrative review of literature on Collective Impact, social impact assessment, and Community Capital from the perspective of collective impact, a framework with a fair amount of previous research. We argue for the importance of applying knowledge of social impact assessment, particularly for the collective impact conditions of common agenda and shared measurement system. We discuss its relationship with the Theory of Change and the use of systems thinking to mitigate the subjectivity and arbitrariness of design thinking. Furthermore, we emphasize the value of employing the community capital concept as a framework for analyzing interrelationships among elements. By integrating multiple concepts, we enhance the collective impact framework and outline potential avenues for future research on analyzing and effectively implementing co-creation value chain mechanism in a community-based approach.

Tungiasis has been included in the WHO list of Neglected Tropical Diseases, but systematic data on the occurrence are scarce. We analyzed data on the occurrence of tungiasis in the 184 munici-palities of Ceará State in Northeast Brazil, based on an online open rapid assessment question-naire focused on health professionals and other key stakeholders. Questions included the occur-rence of tungiasis, severe cases, cases in animals and seasonal variations of the disease. There were in total 1,265 individual data entries available (1 to 104 per municipality) from all munici-palities of the state. A total of 181 (98.3%) of municipalities reported the occurrence of tungiasis in the past or currently, 120 (65.2%) reported current occurrence, 155 (84.2%) severe cases in the past or currently; and 47 (25.5%) reported severe cases currently. A total of 132 (71.7%) municipalities reported tungiasis in animals, most commonly in dogs (97), pigs (80), cats (50), horses (20), cattle (8) and goats (6). Most municipalities mentioned the seasonality of tungiasis (n=146; 79.3%). There was no report of any specific tungiasis control program. Our data show that tungiasis and severe tungiasis commonly occur in Ceará state and that tungiasis is a significant public health issue for both humans and animals. An integrated One Health approach is needed to reduce dis-ease burden, including human and animal health, and the environment.

Tinnitus is a phantom sound perception in the ears or head and can arise from many different medical disorders. Currently, there is no standard treatment for tinnitus that reliably reduces tinnitus. Individual patients reported that acupressure at various points around the ear can help to reduce tinnitus, which was investigated here. With this longitudinal observational study, we report a systematic evaluation of auricular acupressure on 39 tinnitus sufferers, combined with a self-help smartphone app. The participants were asked to report about tinnitus, stress, mood, neck and jaw muscle tensions twice a day using an ecological momentary assessment study design for six weeks. On average, 123.6 questionnaires per person were provided and used for statistical analysis. The treatment responses of the participants were heterogeneous. On average, we ob-served significant negative trends for tinnitus loudness (Cohen’s d effect size: -.861), tinnitus dis-tress (d = -.478), stress (d = -.675), and tensions in the neck muscles (d = -.356). Comparison with a matched control group revealed significant improvements for tinnitus loudness (p = .027) and self-reported stress level (p = .003). The positive results of the observational study motivate fur-ther research including a randomized clinical trial and long-term assessment of the clinical im-provement.

BACKGROUND: To present a new method of urethral pressures examination, and to evaluate diagnostic capabilities of three dimensional profilometry , as an alternative to classical urethral profile (UPP) .Using four channel catheters and dedicated software global urethral pressures image is obtained. The method eliminates the main limitation of classical urethral profilometry where the catheter orientation determines the pressures picture limited to only one point in the uretral circumference while we observed even 50% differences in pressure measures depending on the point of measurement. METHODS: This is a preliminary study containing method presentation and analisys of the use in varied clinical cases of either healthy patients and patients with LUTS. The article includes technique and equipment decription, full evaluation of selected cases, including three dimensional urethral pressures distribution graphics. RESULTS AND CONCLUSIONS:Three dimensional profilometry compared to classical technique is comparable regarding the time, cost, technical difficulty and patient discomfort. At the same time we obtain much more data on the urethral pressures and its distribution.The results are easy for interpretation due to 3D movable graphics created automatically through the dedicated software.

In public health literature the risk of death or disease associated with a dietary, environmental of behavioral factor is most commonly denoted by odds ratio (OR), hazard ratio (HR) or risk ratio (RR). The ratio indices have several desirable statistical properties. However, the most important question is whether there are some evolved innate norms of perception of risk that people use and what they are. We conducted a simple one question survey of 98 individuals with different age, sex, educational and professional backgrounds. The respondents were asked to judge the relative perceived risk of four different hypothetical habits for which data on the percentage of people affected by the disease with and without the habit was given. They were asked to rank the risks for the four habits. Results showed that the habits that had the highest difference between probability of acquiring the disease were ranked high on risk perception. The probability ratios did not affect risk perception significantly. Further age, sex, profession or formal training in statistics did not affect the response significantly. Even individuals that were formally trained to use OR and HR as risk indicators, preferred using probability differences over ratios for judging their own risk in the perceived context. This preliminary inquiry into intuitive statistical perception suggests that designing statistical indices based on people’s innate perception may be a better strategy than trying to train people to understand the indices designed by expert statisticians.

The Matāura River is the sixth largest river system in New Zealand and has long been subject to agricultural, industrial, and residential land use activities. The catchment has geographic and economic value and is of great cultural importance for local Māori, who have concerns over potential adverse impacts that anthropogenic stressors exert on the health of the river. There is a dearth of information on the impacts of these stressors towards the health of native species such as the longfin eel Anguilla dieffenbachii. This study assessed the environmental status of the Matāura River using biological and chemical methodologies incorporating A. dieffenbachii as a bioindicator species for exposure to combined anthroprogenic stressors. A range of biomarker endpoints were measured in caged and wild-caught eels (when available) to characterize site-specific responses to combined anthropogenic stressors. While there was no clear indication of cumulative impacts moving from pristine headwaters to the lower reaches of the Matāura River biomarkers of xenobiotic metabolization were induced in A. dieffenbachia and there was evidence of chemical contamination in sediments and tissues.

Investments in digital infrastructure in marginalised communities are set to increase in the next decade. These are premised on the potential of digital technologies to contribute towards solving societal problems, including the fragility of food value chains in rural areas. Although there are mixed empirical findings on the impact of these digital infrastructure investments, huge investments are continuing amid changing ICT policies in most developing countries. This paper, using a case study of a local livestock value chain in a rural community in Zimbabwe, argues for the application of non-conventional approaches towards digital infrastructure transformation impact assessment. Using selected theories and frameworks (socio-ecological systems framework, choice framework and technology affordances theory) as well as empirical data from a project in a rural community, the paper shows that real-time impact assessment using context-specific metrics may reveal hidden digital infrastructure transformation impacts, positive and negative, that are often overlooked when traditional impact assessment approaches are employed. The findings of this study contribute towards improving approaches towards ICT impact assessment. Practitioners engaging in impact assessment are challenged to move beyond dependence on traditional metrics (e.g. access) to the adoption of participatory processes to decipher context-appropriate metrics.

The importance of the contribution from tourism to climate change was pointed out by the International Tourism Organization (UNWTO). By combining process-based Life Cycle Assessment (LCA) and Input-output analysis, several researches have tried to evaluate the impacts of the tourism industry as well as its products and services. Indeed, the tourism sector has a wide range of industries including travel and tour, transportation, accommodation, food and beverage, amusement, souvenirs etc. However, the existing cases did not show a breakdown of the impact on climate change. In this paper, the carbon footprint (CFP) of the Japanese tourism industry was calculated based on tourist consumption, using the Japanese Input-output table and the Japanese tourism industry. It was shown that the total emissions were approximately 136 million t-CO2 per year. The contribution ratio of each stage is as follows: Transport 56.3%, Souvenirs 23.2%, Petrol (direct emissions) 16.9%, Accommodation 9.8%, Food and Beverage 7.5%, Activities 3.0%. Then, in the breakdown, the impact is high in the following order Air transport 24.7%, Petrol (direct emissions) 16.9%,Accommodation 9.8%, Food and Beverage 7.5%, Petrol 6.1%, Textile products 5.3%, Food items 4.9%, Confectionery 4.8%, Rail transport 3.9%, Cosmetics 1.9%, Footwear 1.8%, etc. In addition to transportation, this research also highlighted especially the contribution from souvenirs, accommodation, food and beverages.

The complex systems that require safety are the Safety Critical Systems. Maintaining these systems is a big challenge. Now a days, safety is a very critical requirement for the latest systems. Safety critical systems must be safe. Different approaches to ensure quality and safety in safety critical systems has been discussed in this paper. A comparison is also conducted between these various approaches. Safety critical systems must remain more influential in future.

Background: Malnutrition is a frequent condition in the elderly and is associated with prolonged hospitalization and increased mortality. However, the impact of malnutrition among elderly patients with acute myocardial infarction has not been clarified yet. Methods and Results: We have enrolled 174 patients aged 65 years and over, admitted with the diagnosis of acute myocardial infarction (AMI) who underwent to the evaluation of nutritional status by Mini Nutritional Assessment (MNA) and of mortality risk by Grace score 2.0. All-cause mortality was the outcome considered for this study. Over a mean follow-up of 24.5 ± 18.2 months, 43 deaths have been registered (24.3%). Non-survivors were more likely to be older, with worse GFR, lower SBP, lower albumin and MNA score, higher prevalence of Killip classification III-IV grade, and higher Troponin I levels. Multivariate Cox proportional analysis revealed that Grace score and MNA showed a significant and independent impact on mortality, (HR = 1.76, 95% CI = 1.34–2.32 and HR = 0.56, 95% CI = 0.42–0.73, respectively). Moreover, the clinical decision curve revealed a higher clinical net benefit when the MNA was included compared to the partial models without MNA. Conclusions: Nutritional status is an independent predictor of long-term mortality among elderly patients with AMI. MNA score in elderly patients with AMI may help prognostic stratification and identification of patients with/at risk of malnutrition in order to apply interventions to improve nutritional status and maybe survival in this population.

Videogames have become educational, communicative and social tools among the youngest, favouring the acquisition of skills, abilities and values, encompassing an endless number of themes, and help to experience and to face, in the first person, a great diversity of environmental situations and ecology problems. Thus, the present article aims: a) the evaluation of a sample of 20 educational videogames about water, making use of some empirical criteria of quality; and b) the design, validation and application of an integrate quality indicator of educational videogames on water, based on the aspects of narrative, gameplay and didactics to that sample, which allows us to obtain a ranking. The findings reflect a ranking of games allows to suggest that the nature of the game (simulation, adventures, platforms or questions) does not determine the quality of the game, although generally simulations and adventure games are placed in a range of medium or high quality, as well as those games that pursue objectives related to the design and management of a territory in a sustainable way. The paper provides teachers with quality criteria based on narrative and gameplay that complement and enriches the pedagogical dimension.

Breakwaters influence coastal wave climate and circulation by blocking and dissipating wave energy. Accurate representation of these effects is essential to the determination of coastal circulation and wave processes. MIKE21SW and SWAN are two third-generation spectral wave models which are used widely in coastal research and engineering applications. Recent improved versions of the models are able to consider the influence of breakwater structures. In this study, we used available observations to evaluate the accuracy of model simulations of waves in New Haven Harbor, Connecticut, USA, an estuary with three detached breakwaters near the mouth. We then compare the accuracy and computational efficiency of MIKE21SW and SWAN. Both models were executed on the same unstructured triangular grid. The boundary conditions were derived from a bottom mounted ADCP on the offshore side of the breakwaters. Wind forcing was applied using data from the Central Long Island Sound buoy. We find that both models are largely consistent with observations during storms. The MIKE21SW significant wave height and wave direction simulations were slightly superior; however, SWAN is more efficient and faster due to its implementation of a fully implicit technique for time integration.

The PILAR model provides a dynamical systems perspective on collaboration. Two studies are performed using peer assessment data, both testing empirical support for the five Pillars (prospects, involved, liked, agency, respect) that constitute member’s perceptions of collaboration viability. The first study analyses peer-assessment data collected online from 458 first-year engineering students (404 males; 54 females). A nine-item instrument was inherited from past year’s usage in the course, expanded with four additional items to elaborate upon the agency and liked Pillars. Exploratory factor analysis was conducted on student responses to test whether they thematically aligned to constructs consistent with the five Pillars. As anticipated, twelve of the thirteen items grouped into five components, each aligned with a Pillar, providing empirical evidence that the five Pillars represent perceptions of collaboration. The second study replicated the first study using a retrospective analysis of 87 items included in the Comprehensive Assessment of Team Member Effectiveness (CATME) peer-assessment tool. The associated factor analyses resulted in five components and conceptual alignment of these components with Pillars was evident for three of five CATME components. We recommend a peer-assessment instrument based upon PILAR as potentially more parsimonious and reliable than an extensive list of behaviours, such as employed by CATME. We also recommend including items that target inter-rater bias, which is aligned with the liked Pillar, that instruments such as CATME exclude.

SLEUTH Model (slope, landuse, exclusion, urban extent, transportation and hillshade) is an important tool for landuse planning and land policy. To evaluate the performance of SLEUTH model, implementation of Sensitivity Analysis (SA) is essential. The main limitation of SA in SLEUTH application is a lack of insight into model input self-modification parameters (SMPs) variation, namely, uncertainty involved in the model transfer metrics and model presumptions, which often misled the decision makers and model users. To address this issue, this study divided the forward process into two stages. Firstly, during the transfer process ①, the contribution scores of five SMPs were drawn, and parameters highly sensitive to model output were given. Apart from that, the recommended initial value for SMPs of 0.11, 0.2, 0.87, 1.13, 15, 1.01, 0.49 were found to be subordinated to such a heterogeneous urban area simulation. Secondly, during the transfer process ②, SMP caused imagery metrics indicated the disparity between parameters with Fixed Reference and with Successive Reference. Reversely, it derives reasonable threshold for the best fit values of five prediction coefficients’ initialization by comparing the real image with the predicted one. The framework of SLEUTH model transfer mechanism not only could distinguish highly sensitive SMPs with higher contribution scores, but also could give parametric analysis for simulation imagery based on metrics. The study was found to be a practical tool for quantization response of model input variables for modelling complex urban systems. So, this insight can help geographic information scientists decide how to find out the inner forward transfer mechanism of SLEUTH model for further make good use of it and improve the model.

Human infection caused by the SARS-CoV-2 virus, called COVID-19, is a new pandemic with devastating effects worldwide. Science seeks the rational and systematic explanation of phenomena. In pandemics, decisions on prevention and treatment of people should be consistently taken, supported by scientific knowledge and ethical principles to produce more good than harm. At first, prospective observational studies to systematically collect patient data, correlating protective or therapeutic interventions with outcomes to assess effectiveness and safety, should be prioritized as the most appropriate type of study. The proposed protocol in this article aims to provide doctors with information on the reduction of harm in early COVID-19 patients by applying individualized interventionist or expectant therapeutic strategies, respecting the autonomy and preferences of physicians and patients in clinical decision-making. The evaluation of the clinical status, besides laboratory confirmation of COVID-19, comprises an individualized symptom score for each patient, a global self-perception scale of the severity of the disease, a clinical progression scale developed by the WHO for clinical studies in COVID-19 and, at the first consultation, doctors´ overall impression on the clinical prognosis. The analysis of anonymized data should preferably use descriptive and inferential statistical resources. The case report form is available for free use in the protocol, along with examples of patient informed consent forms for the prescription of off-label medications and authorization to use the data. Their results may be useful to indicate interventions that are candidates for efficacy trials, in randomized controlled trials, with a higher chance of success. It respects the autonomy and preferences of doctors and patients to decide the best options for treatment in uncertain situations. It also allows the gathering of useful information for future more rigorous clinical trials, trying to link science, ethics, and personal clinical experience.

In recent years, the anticipation of sustainable commercial supersonic jet operations has elevated again. Advances in propulsion together with the increased usage of composite materials favour the potential of sustained and cost efficient supersonic commercial operations. However, obstacles remain with regards to the certification of the new supersonic aircraft platforms, while the two main certification bodies EASA and FAA are under pressure to develop certification requirements which will reassure that the supersonic operations are going to have the least possible environmental impact. From a design perspective, past and current research suggests that a trade-off exists between the aircraft performance and the environmental impact, which should be balanced. The current study attempts to balance this trade-off and to conceptually design a SuperSonic Business Jet (SSBJ) by taking into account environmental concerns of the supersonic flight together with design methods that facilitate a sustained supersonic cruise. An environmental impact assessment is undertaken for the SSBJ design and its results are compared to a typical commercial subsonic airliner.

It is a significant task to assess the safety of the aging offshore jacket platform in order to extend the service life. This paper analyzes the multiple risk factors of an aging jacket platform in Bohai Bay, China and builds the safety evaluation index system, which includes three levels, namely, the target layer, the first-grade indicators layer and the second-grade indicators layer. The target layer consists of three first-grade indicators: ocean environments, structure status, and human and organizational factors. Each first-grade indicator is divided into three second-grade indicators. The weight of each indicator is calculated by analytic hierarchy process to weaken subjective effect. Grey clustering method is applied to estimate the failure risk of the platform in Bohai Bay qualitatively and quantitatively. The assessment standard is divided into five grades and the whitening function of each grey cluster is determined by the assessment scheme. The grey evaluation weight vector of each second-grade indicator is calculated by the table dispatching method. Through layer by layer calculation, the grey assessment value of the target layer is finally estimated by making the grey assessment weight vector single-value and the grey grade is determined according to the maximum principle. The evaluation results show quantitatively that the failure risk grade of the jacket platform in Bohai Bay is medium and the safety assessment method is reasonable and feasible.

Presepsin is a diagnostic and prognostic biomarker of sepsis; however, elevated presepsin levels have also been documented without sepsis. This study aims to retrospectively analyze the laboratory parameters and Sequential Organ Failure Assessment (SOFA) score affecting presepsin levels in 567 patients. Some patients with elevated presepsin levels exhibited renal dysfunction or elevation of biliary enzymes despite a low SOFA score. The univariate regression analysis revealed a close correlation between presepsin levels and SOFA score, serum creatinine (CRE), blood urea nitrogen, and biliary enzymes. In addition, a multivariate regression analysis revealed that SOFA score, alkaline phosphatase (ALP), and CRE independently affected presepsin levels significantly. The analysis of covariance (ANCOVA) revealed that presepsin levels were significantly higher in patients with hepatobiliary disease. Besides, we found that patients who presented with the dilatation of intra- or extrahepatic bile ducts and the elevation of ALP or total bilirubin exhibited remarkable high presepsin levels in the bile. Furthermore, the presepsin production in the liver’s Kupffer cells was established by immunostaining in patients who received surgical liver resection. Overall, this study elucidates that biliary enzymes’ elevation affects presepsin levels, presepsin exists in high concentrations in the bile, and is positive in Kupffer cells.

Pharmacovigilance databases are showing evidence of injury in the context of the COVID-19 modified mRNA shots. According to recent publications, adverse event reports linked to the mRNA COVID-19 products largely point to the spike protein as an aetiological agent of adverse events, but we propose that the platform itself may be culpable. To assess the safety of current and future mRNA vaccines, further analysis on the risks due to the platform itself, and not specifically the expressed antigen. If harm can be exclusively and conclusively attributed to the spike protein, then it is possible that future mRNA vaccines expressing other antigens will be safe. If harms are attributable to the platform itself, then regardless of the toxicity, or lack thereof, of the chosen payload therein, the platform may be inherently unsafe, pending modification. In this work, we examine previous studies of RNA-based delivery by a lipid nanoparticle and break down the possible etiological elements of harm.

Riparian restoration is an important objective for landscape managers seeking to redress the widespread degradation of riparian areas and the ecosystem services they provide. This study investigated the long-term outcomes of ‘one-off’ restoration activities undertaken in the Upper Murrumbidgee Catchment, NSW, Australia. The objective of the restoration was to protect and enhance riparian vegetation and control erosion, and consequently reduce sediment and nutrient delivery into the Murrumbidgee River. To evaluate the outcomes 10 years after restoration, rapid riparian vegetation and geomorphological assessments were undertaken at 29 sites spanning the four different restoration methods used (at least five replicates per treatment), as well as at nine comparable untreated sites. We also trialed the use of aerial imagery to compare width of riparian canopy vegetation and projective foliage cover prior to restoration with that observed after 10 years. Aerial imagery demonstrated the width of riparian canopy vegetation and projective foliage cover increased in all restored sites, especially those with native plantings. The rapid assessment process indicated that 10 years after riparian restoration, the riparian vegetation was in a better condition at treated sites compared to untreated sites. Width of riparian canopy vegetation, native mid-storey cover, native canopy cover and seedling recruitment were significantly greater in treated sites compared to untreated sites. Geomorphological condition of treated sites was significantly better than untreated sites, demonstrating the importance of livestock exclusion to improve bank and channel condition. Our findings illustrate the value of ‘one-off’ restoration activities in achieving long-term benefits for riparian health. We have demonstrated that rapid assessments of the vegetation and geomorphological condition can be undertaken post-hoc to determine the long-term outcomes, especially when supported with analysis of historical aerial imagery.

When disposing of waste metal resources in landfills, environmental issues such as soil contamination may arise. Recycling these resources not only recovers valuable metals but also mitigates environmental pollution. Platinum (Pt), a valuable metal used in fuel cells for its high water production activity, will see increased future demand as a fossil fuel alternative. This study analyzes the environmental and resource reduction effects of recycled Pt, considering the growing emphasis on its recycling for stable supply and demand of Pt. The environmental impact and resource consumption of recycled Pt with primary Pt (from natural mines) were compared and analyzed using the Life Cycle Assessment (LCA) technique. Results revealed that resource consumption for primary Pt was 8.25E+01 kg Sb-eq./kg, significantly more than the 5.45E+00 kg Sb-eq./kg for recycled Pt. This represents an environmental reduction effect of approximately 93%. In the case of greenhouse gas emissions, primary Pt emitted 1.35E+04 kg CO2-eq./kg, while recycled Pt emitted 6.94E+02 kg CO2-eq./kg, resulting in an environmental reduction effect of approximately 95%. In conclusion, recycling Pt, compared to primary extraction, offers substantial environmental and resource reduction benefits. This study underscores the significance of recycling and highlights the potential environmental improvements achievable through sustainable practices.

Most of the municipalities in the Gulf region are facing performance related issues in their municipal solid waste management (MSWM) systems. They lack to possess a deliberate inter-municipality benchmarking processes. Instead of identifying the performance gaps for their key components (e.g., personnel productivity, operational reliability, etc.) and adopt proactive measures, the municipalities primarily rely on an efficient emergency response. A novel hierarchical modeling framework, based on deductive reasoning, is developed for performance assessment of MSWM systems. Fuzzy rule based modeling using Simulink-MATLAB was used for performance inferencing at different levels, i.e., component, sub-components, etc. The model is capable of handling the inherent uncertainties due to limited data and imprecise knowledge base. The model’s outcomes can exclusively assist the managers working at different levels of organizational hierarchy for effective decision-making. Performance of the key component, assists the senior management to assess the overall compliance level of performance objectives. Subsequently, operation management can hone in the sub-components to acquire useful information for intra-municipality performance management. While, individual indicators are useful for inter-municipality benchmarking. The model has been implemented on two municipalities operating in Qassim Region, Saudi Arabia. The results demonstrate the model’s pragmatism for continuous performance improvement of MSWM systems in the country and elsewhere.

Exploring new approaches to innovating higher vocational education is a worldwide pursuit driven by the increasing demand for graduates equipped with competencies. This study investigated how Outcomes-Based Education (OBE) influences the attainment of graduate competence (AGC) in China’s higher vocational education, using the theory of Constructive Alignment (CA) as its foundation. The OBE framework incorporates intended learning outcomes (ILOs), project-based learning (PjBL), assessment strategies (ASs), and AGC. The study tested the model by assessing the impact of ILOs, PjBL, and ASs on AGC, respectively and sequentially. Surveys were administered to 320 CBEC learners in April 2024, resulting in 301 usable responses. Data were analyzed using structural equation modeling (SEM) with SPSS 23.0 and AMOS 24.0. Results indicated that PjBL and ASs were directly and positively related to graduate competency attainment, while ILOs were indirectly associated with graduate competence through the mediating roles of PjBL and ASs. The most substantial mediating effect between ILOs and graduate competence was ASs, followed by PjBL, and then, the chain mediating effect of PjBL and ASs. These findings enhance the theoretical understanding of OBE and provide detailed procedures for tracking and enhancing sustainability in higher vocational education. Beneficiaries include educators, policymakers, and accreditation bodies.

In 2020, the early Covid-19 lockdown and social distancing induced the abrupt migration of traditionally presential learning activities to online domains. This “new normal” environment affected management not only of training courses, but also educational events whose main added value consisted in providing students with an interactive experience onsite, as it is the case of inter-institutional summer schools. The following research corresponds to a case study in which our organization, a French university, had to reformulate, in less than three months, one of its traditional summer schools while trying to keep the original goals. We aimed at identifying the impact of four managerial decisions by analyzing, through qualitative and quantitative surveys, students’ perception of gained or lost value regarding four topics: a) online teaching, b) pre-recorded busines cases providers, c) online social events, and d) technical solutions. With an emphasis in both didactics (i.e., knowledge) and pedagogics (i.e., learning experience), the analysis of perceived value allowed as to learn about students’ assessment position, which revealed two main issues at stake: belonging, in relation to students’ identity and academic background, and performing, related to students’ expectations.

While the container crane is an important part of daily port operations, it has received little attention compared with other infrastructures, such as buildings and bridges. Crane collapse due to earthquake affects the operation of the port, and indirectly impacts the economy. This study proposes fragility analyses for various damage levels of the container crane that allow the port owner and partners to better understand the seismic vulnerability presented by container cranes. A large quantity of nonlinear time history analyses was applied for a three-dimensional (3D) finite element model to quantify the vulnerability of the container crane in considering the uplift and derailment behavior. The uncertainty of demand and capacity of the crane structures were also considered through random variables, i.e. elastic modulus of members, ground motion profile, and intensity. The results analyzed in the case of a Korean container crane showed that the probability of exceeding the first uplift with or without derailment is shown before the crane reaches the structure’s limit states. This means that under low seismic excitation, the crane might be derailed without any structural damage. But when the crane reaches the minor damage state, it is always coupled with a certain probability of uplift with or without derailment. This study also proposes the fragility curves developed for different structural periods to enable port stakeholders to assess the risk of their container crane.

The number of fishers working on commercial fishing vessels worldwide is approximately 159,800 according to the Food and Agriculture Organization of the United Nations. The International Labour Organization estimates that the mean annual number of deaths during fishing is approximately 24,000. Most guidelines for the prevention of marine accidents have been developed with a focus on vessels involved in international navigation. As these guidelines may have parts that are unsuitable for application in small-scale boats operating in coastal areas, appropriate modifications are required. This study analyzed quantitative data on 1,790 marine accidents that occurred in trap fishery, a globally common type of fishery, and data obtained through a survey of 101 fishers in South Korea. A guideline to reduce the rate of fatal accidents was developed using the Bayesian network, a method used for the analysis of accidents, as suggested in the formal safety assessment protocol. The results of data analysis and the developed guidelines are expected to be beneficial to all fishers involved in trap fishery across many countries worldwide.

As universities increasingly compete to improve students’ experience through investment in their campuses, well-designed Campus Open Spaces (COSs) become a major feature as well as a marketing tool. Well-designed and managed COSs are increasingly attractive to students and increase the number of public visits to university campuses (footfall). Current literature does not provide planners with evidence of what makes a COS add value to the student experiences. As such, this paper aims to find the nexus between the value/cost of COS and the attractiveness to - and enhanced experience of - students. This aim is approached via a three-phase integrative framework and results in a validated assessment model with a ‘COS Exp score’ that quantifies the most used/vital, best used/engaging, and most valued/beneficial COS. The data was gathered from in-depth analysis of 21 universities in the UK & USA. The conclusion offers valuable insights into improving experience-based outdoor space developments.

Background: Telemedicine (interconsultation between primary and hospital care teams) has been operating in the counties of Central Catalonia Bages, Moianès and Berguedà since 2011 in the specialties of teledermatology, teleulcers, teleeyelids and teleaudiometries. For the period until the end of 2019, a total of 52,198 visits have been recorded. Objective: To analyse the differential costs between telemedicine and usual care in a semi-urban environment. Methodology: A cost-minimization evaluation, including direct and indirect costs from a societal perspective, distinguishing healthcare and user’s costs, within a three-month period. Results: Telemedicine saved € 780,397 over the period analysed. A differential cost favourable to telemedicine of about € 15/visit has been observed, the patient being the largest beneficiary of this saving (by 85%) in terms of shorter waiting times and travel costs. From the healthcare system perspective, moving the time spent in a hospital care consultation to primary care is efficient in terms of the total time devoted per patient. In social terms and in this context, telemedicine is more efficient than usual care. Conclusion: Users’ saving of time in terms of consultation and travel is the main driver of interconsultation between primary and hospital care savings in a semi-urban context. The telemedicine service is also economically favourable for the healthcare system, enabling it to provide a more agile service, which also benefits the healthcare professionals.

The prognostic abilities of artificial intelligence and neuroscience in forensics and the criminal justice system stand as a reformatory paradigm for understanding any criminal conduct. While the use of artificial intelligence has been labeled transformational data analytical capabilities, neural predictive approaches also enable an intricate understanding of culpability and criminal propensities. The literature on the complex nature of neuroprediction and artificial intelligence, its ethical deliberations and its usability in curving recidivism are analyzed. This theoretical review elucidates the complex interplay, nuptial relationships and convergence of these relationships in the quest for justice. The consequences of not protecting individual rights in the criminal justice system are surveyed using grounded theory. The degree of acceptability and dependability of AI-generated evidence in legal proceedings are also reviewed. All these topics are yet to be contemplated under one roof to offer an argumentative view. The author expects to prompt readers and new commers to embrace more sociolegal and technological research before incorporating such research in the Indian Judiciary. The review focuses on the question of whether to blame such technology inclusion wholly or rather to prioritize the acquisition of bias-free pretrained datasets and processing models.

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit consists of (i) a sensor and hardware layer that can be configured in a modular manner per research needs, (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study for photo-plethysmography (PPG) sensor with 15 participants, PhysioKit shows strong agreement with research-grade PPG sensors. Furthermore, we report usability survey results from 10 micro-project teams (44 individual members in total) who use PhysioKit for 4-6 weeks, providing insights into its use cases and research benefits. We conclude by discussing extensibility and potential impact of the toolkit on the research community.

With growing global concern of food and water insecurity, an efficient method to monitor irrigation projects is essential, especially in the developing world, where irrigation performance is often suboptimal. In Nepal, the irrigated area has not been objectively recorded, although their assessment has substantial implications on national policy, project’s annual budgets, and donor fund-ing. Here we present the application of Landsat images to measure irrigated areas in Nepal for the past 17 years to contribute to the assessment of the irrigation performance. Landsat 5 TM (2006-2011) and Landsat 8 OLI (2013-2022) images were used to develop a machine-learning model which classifies irrigated and non-irrigated areas in study areas. The random forest classification achieved overall accuracy of 82.2% and kappa statistics of 0.72. For the class of irrigation areas, the producer’s accuracy and the consumer’s accuracy were 79% and 96%, respectively. Our regionally trained machine-learning model outperforms the existing global cropland map, highlighting the need of such models for local irrigation project evaluations. We assess irrigation project performance and its drivers by combining long-term changes in satellite-derived irrigated area with local data related to irrigation performance, such as annual budget, irrigation service fee, crop yield, precipitation, and main canal discharge.

Cold brew coffee has emerged as a new trend during the last decade. However, “cold brew” is an extraction style of ground roasted coffee with water at less than body temperature (typically 8°C or room temperature) rather than a beverage per se. Cold brew extraction poses several challenges including the need of specific optimization depending on the multivariate influences of coffee variety and processing, roast degree, grinding, dosage, water composition, turbulence, brew system (drip, immersion etc.), time and temperature. While cold brew is typically characterized by a floral sweetness, over-extraction may lead to abundant acidity and bitterness. To avoid this, an extraction degree of 70% was suggested using rather shorter times (i.e. 2 h at 15°C with 80 g/L coffee with optimized medium roast profiles). Due to the lack of sterilizing temperatures during preparation, cold brew is special in the coffee sector because hygiene and food safety aspects pose specific challenges for food industry. To avoid microbiological contamination and spoilage, cold brew should be as freshly prepared as possible and shelf-life should be minimized.

Safety of source water streams is an urgent environmental issue, while protections in monsoon controlled subtropical regions face difficulties because of the lack of small scaled observation and analysis in small source water catchments. Basing on continuous weekly water quality data (2014-2017) in Pingqiao River Catchment, the annual average values of TN, NO₃, NH₄ and TP are 3.36, 1.64, 0.28 and 0.02 (mg/L) respectively. During dry, normal and wet seasons, the variability of parameters is over 35%, which indicates an obvious seasonality. Multiple methods are combined in order to assess the water quality and find the driving factors during dry, normal and wet seasons. This study suggests precipitation and fertilization are the mainly seasonal factors, which can make water quality better in wet season than dry season due to the dilution effect. The mechanism between seasonality and compound of nutrients can also be traced by log(TN:TP), and log(NO₃:NH₄). Among six main land use types (forest, tea plantation, cropland (paddy), urban, bare soil and water), the former three ones are influential mostly during dry and wet season. Tea plantation has the largest nutrients discharge amount per area, which is similar to cropland in dry season. By contrary, forest has the double power in reducing nitrogen release in wet and normal seasons. When transformed into paddies, croplands can lower the phosphorus concentration. Conclusions of this study can be used in southeastern China and similar regions on source water protection and agricultural plans.

Disposable absorbent hygiene products have evolved for superior performance, enhancing the convenience of daily lives. Yet the use of disposable hygiene pads has brought safety concerns on chemical exposure, and significant efforts have been made to assess the potential risks associated with use of hygiene pads. This article intends to overview the safety assessment framework of diapers and feminine pads, which includes hazard identification, hazard characterization, exposure assessment, risk characterization, and postmarket risk management. Risk assessment of various constituents are reviewed for quantification methods and conservative estimation of exposure parameters. By reviewing the up-to-date considerations in risk assessment, we aim to provide insightful discussion on safety evaluation of current versions of disposable absorbent products. More clinical testing and postmarket surveillance are needed for continuous monitoring of potential health impacts of advanced products and constituents.

Although commercially-available low-cost air quality sensors have low accuracy, the sensor system are being used to collect the data for the regulation of PM2.5 emission caused by industrial activities or to estimate the personal exposure for PM2.5. In this work, to solve the accuracy problem of low-cost PM sensor, we developed a new PM2.5 calibration model by combining the deep neural network (DNN) optimized in calibration problem and a LSTM optimized in time-dependent characteristics. First, two datasets were generated to test the accuracy performance and generalization performance of the PM2.5 calibration machine learning (ML) model. The PM2.5 concentrations, temperature and humidity by low-cost sensor and gravimetric-based PM2.5 measuring instrument were sampled for a sufficiently long time. The proposed model was compared with benchmark (multiple linear regression model) and low-cost sensor results. For root mean square error (RMSE) for PM2.5 concentrations, the proposed model reduced 41-60% of error compared to the raw data of low-cost sensor, and reduced 30-51% of error compared to the benchmark model. R2 of ML model, MLR and raw data were 93, 80 and 59 %. Also, the developed model still showed consistent calibration performance when calibrated with new sensors in different locations. Low-cost sensors combined with ML model not only can improve the calibration performance of benchmark, but also can be applied to the sensor monitoring systems for various epidemiologic investigations and regulatory decisions.

Bonfire night is a worldwide phenomenon given to numerous annual celebrations characterised by bonfires and fireworks. Since Thailand has no national ambient air quality standards for metal particulates, it is important to investigate the impacts of particulate injections on elevations of air pollutants and ecological health impacts resulting from firework displays. In this investigation, Pb and Ba were considered potential firework tracers because their concentrations were significantly higher during the episode and lower than/comparable with minimum detection limits during other periods, indicating that their elevated concentrations were principally due to pyrotechnic displays. Pb/Ca, Pb/Al, Pb/Mg, and Pb/Cu can be used to pin-point emissions from firework displays. Air mass backward trajectories (72 h) from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated that areas east and north-east of the study site were the main sources for the air transportation. Although the combined risk associated with levels of Pb, Cr, Co, Ni, Zn, As, Cd, V, and Mn was far below the standards mentioned in international guidelines, the lifetime cancer risks associated with As and Cr levels exceeded US-EPA guidelines, and may expose inhabitants of surrounding areas of Bangkok to elevated cancer risk.

Background: Malnutrition in oesophageal and pharyngeal cancer patients constitutes a common and serious concern, which significantly reduces patients’ prognosis. Cancers of the oesophagus and the pharynx can considerably impair feeding in patients, resulting in severe undernutrition. This is a scoping review which aims to critically summarize and scrutinize the current clinical evidence on the use and prognostic role of diverse nutritional assessment tools on the prognosis of patients with oesophageal and pharyngeal cancers. Methods: PubMed, Scopus, Web of Science and Google Scholar databases were comprehensively explored utilizing relative keywords to detect clinical studies that investigate whether nutritional status may affect disease prognosis. Results: Several assessment tools have evaluated and highlighted the prognostic role of nutritional status on patients’ survival and disease complications in both oesophageal and pharyngeal cancers. Regarding oesophageal cancer, CONUT, PNI, PG-SGA and NRS-2002 are more commonly used, while albumin is also frequently evaluated. Regarding pharyngeal cancers, fewer studies are currently available. PNI has been evaluated and its significance as a factor for shorter overall survival, distant metastasis-free survival, progression-free survival, and locoregional recurrence-free has been highlighted. Comprehensive Nutritional Index has also been evaluated with positive results, as well as NRS 2002, GPS, and body weight status. However, there is currently a lack of studies with adequate female patients. There is also a significant lack of well-designed prospective studies with well-organized methodology. Conclusion: Nutritional status may significantly affect disease progression and patients’ survival, highlighting the importance of a good nutritional status in patients with oesophageal and pharyngeal cancers. Further large-scaled and well-designed prospective clinical studies are strongly recommended to verify the potential beneficial effects of nutritional status in patients with oesophageal and pharyngeal cancers.

Evidence shows that weightloss improves insulin sensitivity but few studies have examined the effect of macronutrient composition independently of weight loss on direct measures of insulin sensitivity. We randomised 89 overweight or obese women to either a standard diet (StdD) that was intended to be low in fat and relatively high in carbohydrate (n=42) or to a relatively high protein (up to 30% of energy), relatively high fibre (>30g/day) diet (HPHFib) (n=47) for 10 weeks. Advice regarding strict adherence to energy intake goals was not given. Insulin sensitivity and secretion was assessed by a novel method - the Dynamic Insulin Sensitivity and Secretion Test (DISST). Although there were significant improvements in body composition and most cardiometabolic risk factors on HPHFib, insulin sensitivity was reduced by 19.3% (95% CI: 31.8, 4.5%; p=0.013) in comparison with StdD. We conclude that the reduction in insulin sensitivity after a diet relatively high in both protein and fibre, despite cardiometabolic improvements, suggests insulin sensitivity may reflect metabolic adaptations to dietary composition for maintenance of glucose homeostasis, rather than impaired metabolism.

Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z₅₀) and impedance ratio of high and low frequency (Z₂₅₀/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z₅₀)) + (−55.24 × (Z₂₅₀/Z₅)) + (−10,940 × (1/Z₅₀)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z₅₀)) + (−36.61 × (Z₂₅₀/Z₅)) + (−9332 × (1/Z₅₀)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

By using a two-stage physiologically based extraction test (PBET) and (W-PBET), the authors of this paper have estimated the bioaccessibility of metals (Pb and Fe) and their compounds in the GI tract of waterfowl and mammals. It has been shown that the metals (Pb and Fe) have low bioaccessibility; combined with the short time of shot exposition at the GI tract, this eliminates the risk of toxic effects in the case of shot ingestion by waterfowl. It has also been discovered that there is a significant difference in the bioaccessibility of metals and their compounds. A model was proposed and tested to predict the toxic effects of lead on biological objects depending on the threshold mass of consumption. This model takes into account data on the bioavailability of lead and regulatory values indicating dangerous concentrations of lead.

We aimed to investigate the ability of children aged 5–14 years old (preschoolers, primary schoolers, and preteens) to assess and anticipate time intervals. 287 Russian children aged 5–14 years old and 26 adults of control group participated in our study. The neuropsychological assessment, Wechsler Intelligence Scale for Children and a battery of time-related tests were applied. All groups of children overestimated the event’s duration, although the accuracy of the second estimations increased among the participants aged 6–8 years after a prompt was offered. A zone of proximal development for time anticipation task was detected for children aged 9-11 years, when the prompt could significantly improve the accuracy of time perception. The participants overestimated the duration of both upcoming and past events, with the degree of overestimation being found to be negatively correlated with age. Further, a higher degree of accuracy in terms of time estimation was found to be correlated with higher scores on the attention and memory tests, and accuracy of time anticipation was associated with scores of praxis test.

Building carbon footprint analysis is a key instrument for assessing the impact of different constructions on climate change. Several standards and methodologies are available to calculate the footprint of buildings, including standards and norms, life cycle assessment (LCA), and dedicated software tools. The use of BIM software for these calculations is both scientifically justified and very practical. This scientific publication focusses on the application of a BIM-based research methodology for the analysis of the carbon footprint of a single-family house. The research process included the following steps: (i) design of a single-family house with timber frame construction using Archicad BIM software, (ii) simulation of the building energy performance using the EcoDesigner Star plug-in, (iii) life cycle assessment (LCA) using the plug-in for Archicad, (iv) preparation of a second model with traditional masonry construction for comparison, and (v) comparative analysis of the single-family house models with timber frame and masonry construction. Analysis of the results highlights significant differences in CO2e emissions between masonry and timber buildings and the varying impact of individual elements on the total CO2e emissions of the buildings studied. These findings are relevant for future work on sustainable building design and construction, which aims to minimise negative environmental impacts. The goal of minimising the cumulative carbon footprint of buildings is critical to achieving the Sustainable Development Goals and combating climate change.

Since the 20th century, Japan has experienced a period of very rapid urbanization. Cities have experienced substantial densification and expansion, resulting in gradually elevated flood risk. Urban flooding has also occurred in most large cities in Japan, particularly in Tokyo. In response to this growing problem, much effort and resources have been spent on research and development aimed at understanding, simulating, and managing urban flood risk in Japan. The objective of this review is to summarize, discuss and share key outputs from some of the main research directions in this field, significant parts of which have been uniquely developed in Japan and only published in Japanese. After a general introduction to urban runoff modelling, in the next section, key historical works in Japan are summarized, followed by a description of the situation in Japan with respect to observations of precipitation and water level. Then, the storage function model approach is reviewed, including an extension to urban basins, as well as recent experiments with AI-based emulation in Japanese basins. Subsequently, we review the prospects of detailed hydrodynamic modelling involving high-resolution, vector-based Geographical Information System (GIS) data for the optimal description of the urban environment with applications in Tokyo. We conclude the paper with some future prospects related to urban flood risk modelling and assessment in Japan.

In recent years, the discharge of various emerging pollutants, chemicals and dyes in water and wastewater has represented one of the prominent human problems. Since water pollution is directly related to human health, highly resistant and emerging compounds in aquatic environments will pose many potential risks to the health of all living. Therefore, water pollution is a very acute problem that has constantly increased in recent years with the expansion of various industries. Consequently, choosing efficient and innovative wastewater treatment methods to remove contaminants is crucial. Among advanced oxidation processes, electrochemical oxidation (EO) is the most common and effective method for removing persistent pollutants from municipal and industrial wastewater. However, there are still many gaps despite the great progress in using EO to treat real wastewater. This is due to the lack of comprehensive information on the operating parameters which affect the process and its operating costs. In this paper, among various scientific articles, the impact of operational parameters on the EO performances, a comparison between different electrochemical reactor configurations, and a report on general mechanisms of electrochemical oxidation of organic pollutants have been reported. Moreover, an evaluation of cost analysis and energy consumption requirements have also been discussed. Finally, the combination process between EO and another important advanced oxidation technology, PEC, called photoelectrocatalysis (PEC), has shortly been discussed and reviewed. This article showed that there is a direct relationship between important operating parameters with the amount of costs and the final removal efficiency of emerging pollutants. Optimal operating conditions can be achieved by paying special attention to reactor design, which can lead to higher efficiency and more efficient treatment. The rapid development of EO for removing emerging pollutants from impacted water and its combination with other green methods can result in more efficient approaches to face the pressing water pollution challenge.

Use of a multi-sensor approach can provide citizens a holistic insight in the air quality in their immediate surroundings and assessment of personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from 7 European cities, discusses data fusion and harmonization on a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants, and offers possible solutions and improvements. Harmonizing the data streams identified issues with the used devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate the process of generating visualizations and reports and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization on a diverse set of multi-sensor data streams considerably improved the quality and quantity of data that a research participant receives. Though automatization accelerated the production of the reports considerably, manual structured double checks are strongly recommended.

Membrane gas absorption technology has been considered as a promising approach to mitigate CO2 emissions from power plants. The aim of this study is to evaluate the environmental impacts of CO2 absorption and desorption processes by hollow fiber membrane contactors using life cycle assessment methodology. On the basis of ReCipe 2016 Midpoint and ReCipe 2016 Endpoint methods, the research results show that, membrane gas absorption system exhibits the lowest environmental impacts across the majority assessed categories in comparison with chemical absorption and membrane gas separation systems. The CO2 capture process via membrane gas absorption has the most significant impact on METP category, with heat consumption as the primary contributing factor accounting for 55%, followed by electricity consumption accounting for 43.1%. According to the sensitivity analysis, heating by natural gas shows a better performance than other heat supply sources in improving overall environmental impacts. In addition, the increasing utilization of renewable energy in electricity supply reduces the global warming potential, fossil resource consumption and ozone formation.

Cheese whey, a significant byproduct of the dairy industry, poses a substantial environmental challenge due to its organic pollutant load and large size demands for effective and affordable valorization methods. The abundance of lactose and other organic compounds in whey contributes to its elevated Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD), further straining natural ecosystems. This study aimed to investigate the nutritional potential of whey and its conversion into value-added products: bioethanol and probiotic drinks. To achieve this, Bacillus megaterium and Bacillus subtilis strains, isolated from soil samples in Nepal, were co-cultured with Lactobacillus and Saccharomyces cerevisiae in the whey broth for fermentation. Ethanol distillation was carried out using a Rota-evaporator to maintain the viability of the fermenting organisms within the broth. Moreover, the probiotic criteria of the fermenting strains were extensively examined. Experimental observations revealed a remarkable concentration of 9.2 g/L of ethanol, resulting in an ethanol yield of 0.23 g/L. Extrapolating this rate, it is theoretically possible to produce an annual global bioethanol output of 5 million tons using whey as a sustainable and abundant resource. Furthermore, the study explores novel advancements in the distillation process, demonstrating the successful extraction of ethanol at room temperature. Additionally, the fermentation organisms employed in this research exhibit robust viability, surviving various in-vitro stress-tolerant tests, including exposure to bile salt, pH fluctuations, and gastric juice. These resilient strains also demonstrated long-term stability in fermented whey broth, making them promising candidates for the development of probiotic beverages. This dual approach not only enables the sustainable management of organic waste but also presents an opportunity to create value-added products with positive implications for both the environment and human health.

Kenya’s construction industry is experiencing exponential growth in tandem with construction trends globally. With the growth experienced in the industry, there has been significant growth in the economy and a 50% contribution to the world’s landfill waste and pollution to the adjacent environment. Globally, the construction industry is among the largest consumers of natural resources and significant contributors to pollution. This has given rise to high pressure to adopt environmentally sensitive approaches in the construction industry to present a competitive advantage. It is, therefore, crucial to address the need for sustainability measures for Landscape Architecture projects to increase knowledge and awareness, create incentives geared towards supporting sustainable practices, and leverage legal instruments and policies. Green construction practices and strategies have positively impacted the environment and the Kenyan construction industry’s social and economic performance. However, there are several barriers to the adoption and improvement of monitoring and evaluation of sustainable practices, thus slowing down the industry in taking charge of sustainability.

Cocoa is a natural resource that plays a very important role globally, being one of the most produced and traded commodities. Being a labor-intensive product and considering that its cultivation involves about 50 million people globally, it seems significant to explore its social sustainability. In light of this, this research aimed to map social risks within the cocoa supply chain from a life cycle perspective. Therefore, according to a Reference Scale Approach, or Type I, the Social Life Cycle Assessment was used, considering the two most influential Countries in its production, i.e. Côte d'Ivoire and Ghana. The results showed that there could be a very high risk that more than half of the cocoa globally is produced through child labour and with wages too low to guarantee workers a decent living, returning incomes of $30-38/month. Forced labour is much less frequent than child labour, while cocoa from Ghana may induce a high risk of improper work, considering the 30.2 hours per week worked by farmers. This is mainly due to the low association power of 10-16%, which reveals a high risk that workers may not organize themselves into trade unions. Finally, at 23-25%, there is also a very high risk of discrimination due to the high presence of migrant labour. The S-LCA results, therefore, showed that the cocoa industry is still characterized by socially unsustainable sourcing.

A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in seafood was performed, with the objective of appraising the effectiveness of the control strategies placed along the food chain. Whereas all the 13 QRA models retrieved were of short scope, covering at most from end of processing to consumption; the majority (85%) focused on smoked or gravad fish. Since the modelled pathways commenced with the packaged product, none of the QRA models addressed cross-contamination events. Many models agreed on the fact that keeping the product’s temperature at 4.0-4.5 ºC leads to greater reductions in the final risk of listeriosis than reducing the shelf life by one week; and that the effectiveness of both measures can be surpassed by reducing the initial occurrence of L. monocytogenes in the product (at the end of processing). It is therefore necessary that future QRA models for RTE seafood contains a processing module that can provide insight into intervention strategies that can retard L. monocytogenes growth, such as the use of bacteriocins, ad-hoc starter cultures and/or organic acids, and other strategies seeking to reduce cross-contamination at the facilities, such as stringent controls for sanitation procedures. Since risk estimates were shown to be moderately driven by growth kinetic parameters, namely, the exponential growth rate, the minimum temperature for growth, and the maximum population density, further work is needed to reduce uncertainties about them.

Purpose: To identify factors linked with nutritional risk via the Malnutrition Universal Screening Tool scale assessment among critically ill patients from a hospital in Cali (Colombia). Materials and methods: A retrospective, analytical observational study was conducted with patients admitted to an intensive care unit (ICU). Sociodemographic, clinical, hematological, and biochemical parameters were analyzed, as well as their association with nutritional risk and patient mortality. Binary logistic regression was applied to outline nutritional risk. Results: Overall, 28.4% prevalence of elevated nutritional risk was observed. An association was found between nutritional risk and hemoglobin and hematocrit values, primary diseases accounting for ICU admission, gastrointestinal symptoms, and nutritional support route (p < 0.05). Mortality was 11.6% and it was correlated with nutritional risk, hemoglobin, and blood urea nitrogen. Conclusions: Gastrointestinal symptoms and the type of nutritional support received during hospitalization may increase nutritional risk, whereas polycythemia was a protective factor. We found an associative model to determine nutritional risk with high specificity and an adequate diagnostic validity index.

In this paper, aiming at the safety evaluation of ultimate bearing safety capacity of ultra-high-performance-concrete (UHPC) composite pile bridge foundation, the symmetrical reliability method with forward and inverse analysis considering the randomness of parameters is proposed to evaluate the safety performance of composite pile foundation. The proposed method, consid-ering the randomness of parameters, was used to calculate the safety factor of ultimate bearing capacity of composite pile foundation to meet the prescribed target reliability requirements. An example was used to verify the correctness of the proposed method. The proposed method was applied to an actual engineering example and the sensitivity of the parameters were analyzed, the calculation results show that: ignoring the randomness of the parameters will overestimate the safety of the composite pile foundation; the target reliability index has a great influence on the safety of composite pile foundation; the influence of statistical parameters of random variables on the safety of UHPC composite pile foundation cannot be neglected; the initial iteration value of the safety factor has no effect on the final calculation result. The proposed method has high ac-curacy and applicability, and provides an effective way for the safety factor estimation of ultimate carrying capacity of UHPC composite pile foundation.

Machine Learning techniques can be used to identify whether deficits in cognitive functions contribute to antisocial and aggressive behavior. This paper initially presents the results of tests conducted on delinquent and non-delinquent youths to assess their cognitive functions. The dataset extracted from these assessments, consisting of 37 predictor variables and one target. was used to train three algorithms that aim to predict whether the data corresponds to that of a young offender or a non-offending youth. Prior to this, statistical tests were conducted on the data to identify characteristics that exhibited significant differences in order to select the most relevant features and optimize the prediction results. Additionally, other feature selection methods, such as Boruta, RFE, and Filter, were applied, and their effects on the accuracy of each of the three machine learning models used (SVM, RF, and KNN) were compared. 80% of the data were utilized for training, while the remaining 20% were used for validation. The best result was achieved by the K-NN model trained with 19 features selected by the Boruta method, followed by the SVM model trained with 24 features selected by the filter method.

The wastewater circular economy (WW-CE) promises a solution to improve water and sanitation management worldwide. However, the transition from conventional to circular wastewater treatment plants (WWTPs) requires facilitation to aid in decision makers understanding of integral sustainability impacts of alternative WW-CE configurations. This research implemented Life Cycle Sustainability Assessment (LCSA), combining Life Cycle Assessment, Social Life Cycle Assessment and Life Cycle Costing with a Multi-criteria Decision Making (MCDM) model to quantify environmental, socio-cultural, and economic impacts of conventional WWTPs with the WW-CE. Two real WWTPs in Chile have embraced the WW-CEs and adopting the title of Biofactories. These were considered as case studies, compared under three scenarios to demonstrate the sustainability trade-offs of the transition from no sanitation to conventional WWTPs and Biofactory WW-CE configurations. Results demonstrated that the transition to WW-CEs improved integral sustainability according to the LCSA model implemented in both WWPTs. This study highlights the urgent need to adopt sustainable decision-making models to not only improve sanitation coverage, but also improve sustainability performance of the sanitation industry across the globe.

In the absence of a holistic view of Landscape Sustainability, credible data and consistent information are needed to help decision making and support adaptive management. However, consolidated tools (system of standards and controls) of assessment exist, but show a complexity of the references on one hand, and are mostly qualitative and environmental indicators based on the other hand. This review article deals with the theme of both environmental and landscape indicators in general, the principles and the fundamental definitions. The main models used, the prerequisites and various fields of application are also taken into consideration. Last but not least, various environmental and landscape indicators are presented and compared.

Embryo quality evaluation during in vitro development is vital for the success of assisted reproductive technologies (ART). However, the subjective morphological assessment by embryologists may result in inconsistencies that affect the selection of the best embryo for transfer. To provide a more comprehensive evaluation of embryo quality, we performed the integration of embryo metabolomics with standardized morphokinetic classification. The culture medium of 55 embryos (from 21 couples undergoing ICSI) was collected at two timepoints (day 3 and 5). Samples were split into Good (n=29), Lagging (n=19) and Bad (n=10) according to embryo morphokinetic evaluation. Embryo metabolic performance was assessed by 1H-NMR, monitoring the variation of specific metabolites (pyruvate, lactate, alanine, glutamine, acetate, formate). Adjusted metabolite differentials were observed during the first three days of culture and found to be discriminative of embryo quality at the end of day 5. Pyruvate, alanine, glutamine, and acetate were major contributors to this discrimination. Good and Lagging embryos were found to export and accumulate pyruvate and glutamine in the 3 first days of culture, while Bad embryos consumed them. This suggests that Bad embryos have a less active metabolism than Good and Lagging embryos and these two metabolites as putative biomarkers for embryo quality. This study provides a more comprehensive evaluation of embryo quality and can lead to improvements in ART by enabling the selection of the best embryos. By combining morphological assessment and metabolomics, the selection of high-quality embryos with the potential to result in successful pregnancies may become more accurate and consistent.

As required by the EU legislation and the national risk management duties, the pesticide residues were determined by four specialized laboratories in 9,924 samples taken from 119 crops of economic importance and imported foodstuffs during 2017-2021 in Hungary. The screening method applied covered 622 pesticide residues as defined for enforcement purposes. The limit of detection ranged between 0.002-0.008 mg/kg. The 1.0% violation rate was lower than in the European Union for all commodities. No residue was detectable in 45.9% of the samples. For detailed analyses of the results, eight commodities (apple, cherry, grape, nectarine/peach, sweet peppers, and strawberry) were selected as they were analyzed over 195 samples and contained most frequently residues. Besides testing their conformity with national MRLs, applying 0.3MRL action limits for pre-export control, we found that 73% of the sampled lots would be compliant with ≥90% probability based on second independent sampling. Multiple residues (2-23) in one sample were detected in 36-50% of the tested lots. Noting the provisions of integrated pest management and the major pests and diseases of selected crops, normally 3-4, exceptionally 7-9 active ingredients of different mode of actions should be sufficient for their effective and economic protection.

Pose estimation has various applications in analyzing human movement and behavior, including providing feedback to users about their movements so they could adjust and improve their movement skills. To investigate the current research status and possible gaps, we searched Scopus and Web of Science for articles that (1) human `body' pose estimation is used and (2) user movement is assessed and communicated. We used either a bottom-up or top-down approach to analyze 20 articles for methods used to estimate human pose, assess movement, provide feedback to users, as well as methods to evaluate them. Our review found that pose estimation systems typically used CNNs while movement assessment methods varied from mathematical formulas or models, rule-based approaches, to machine learning. Feedback was primarily presented visually in verbal forms and nonverbal forms. The experiments to evaluate each part ranged from the use of public datasets to human participants. We found that while there was an improvement, the majority of pose estimation challenges remain. The effectiveness and factors for choosing movement assessment methods for a new context are still unclear. In the end, we suggest that studies about feedback prioritization and erroneous feedback are needed.

Abstract: The need to rapidly reduce GHG has accelerated the adoption of circular models of production. However, this has proved to be a challenging task for SMEs, who lack the financial, organizational and informational capabilities to implement circular business models. In this context, calculating the carbon footprint (CF) of their products could provide the basis for assessing the different circular economy (CE) practices. The aim of this study is to present a CF calculation tool that can be used to calculate the CF of SMEs. The design of the tool was based on the Life Cycle Assessment (LCA) methodology, taking into account the various barriers that SMEs face in adopting CE practices. The tool was tested in a small cheese factory in northern Greece. The pro-duction process was mapped, a GHG inventory was created and the total emissions related to the production of a specific product was estimated. The final aim is to test this tool at a large scale.

To evaluate the impact of a new Substance Use Disorder (SUD) education program on medical students' representations, we selected the Substance Abuse Attitude Survey (SAAS) questionnaire, which we adapted to our curriculum and cultural context. To validate this adapted version, we conducted an exploratory factor analysis following the administration of our 29-items bSAAS questionnaire to 657 medical students in Belgium (response rate: 71,1%). 23 items correlated to 3 factors namely "Stereotypes and moralism", "Treatment optimism" and "Specialised treatment" were retained (70% of total variance explained, Cronbach's alpha= 0.80) and constituted the new questionnaire called beSAAS. The factor "Specialised treatment", stood out from previous studies which could be explained by our target population and the impact of the formal, informal, and hidden curriculum in medical education. This study highlighted certain factors influencing stereotypical representations such as age, gender, origin, and personal or professional experience with substance use. Our study allowed us to retain the beSAAS as a good questionnaire to evaluate SUD stigma and highlighted interesting findings to improve SUD training in medicine. Further studies are needed to complete its validity and reliability.

Background: Some studies have shown that an increase in visceral fat is associated with postoperative clinical and oncologic outcomes. However, no studies have used bioelectrical impedance analysis (BIA) to determine the effects of visceral fat on the oncologic outcomes of colorectal cancer (CRC). This study aimed to investigate the relationship between visceral fat area (VFA) and clinical, and oncologic outcomes in CRC. Methods: This study included 203 patients who underwent anthropometric measurements by BIA before surgical treatment for CRC between January 2016 and June 2020. Results: According to the cutoff level of VFA by receiver operating characteristic curve analysis, 85 (40.5%) patients had a low VFA, and 119 (59.5%) had a high VFA. Multivariate analysis found that preoperative CRP (hazard ratio [HR], 3.882; 95% confidence interval [CI], 1.001–15.051; p=0.050) and nodal stage (HR, 7.996; 95% CI, 1.414–45.209; p=0.019) were independent prognostic factors for overall survival, while sex (HR, 0.110; 95% CI, 0.013–0.905; p=0.040), lymphovascular invasion (HR, 3.560; 95% CI, 1.098–11.544; p=0.034), and VFA (HR, 4.263; 95% CI, 1.280–14.196; p=0.040) were independent prognostic factors for disease-free survival (DFS). Conclusion: High VFA preoperatively measured by BIA was associated with inflammations and was an independent prognostic factor for DFS.

The needs for environmental reporting to include positive outcomes considering differences between creation of less harm, benefits and net benefits are explored. To become mainstream, nature-positive development needs positive messaging, measures and metrics to guide, plan and assess urban outcomes. With the accelerating climate crisis and negative messages getting the upper-hand, it’s important to avoid paralysis by bad news. Whilst striving for a nature-positive world, more effort should be on moving beyond zero to qualify and quantify benefits, gains, and regenerative outcomes instead of oscillating around damage and loss sticking points. Life Cycle Benefit Assessment (LCBA) is a method to measure gains in accelerating restoration and climate security. It enables a good news focus as its reach is to quantify and show positive gains beyond the negative and zero loss outcomes. The paper aims to clarify concepts, challenges and quantitative methods then review real-world third-party-certified case studies. Climate security, human wellness and resource viability gains inside safe operating space within planetary boundaries are quantified as positive benefits. Contrary to conventional Life Cycle Impact Assessment (LCIA) LCBA assigns damage and loss as negative debts and benefit as positive gains. It concludes that LCBA offers business and design a new environment assessment tool, with research needed on economic and other outcomes.

Combination treatment, i.e., the use of two or more drugs for the same condition, is frequent in medicine if monotherapy yields an insufficient therapeutic response. We here review and challenge clinical study designs and formats of reporting outcomes for the evaluation of the benefit/risk ratio of combination treatment over monotherapy. We demonstrate that benefits of combination treatment at the group level over-estimate the probability of benefit at the single patient level based on outcome simulations under almost any imaginable setting. Based on these findings we propose that studies testing combination treatment should always report on percentages of responders to monotherapy and combination treatment. We provide equations that allow calculation of the percentage of patients truly benefitting from combination (responders to both monotherapies) and that of patients exposed to risk of harm from adverse effects without a reasonable expectation of individual benefit. These considerations are explained based on real clinical data, mostly from the field of functional urology (male lower urinary tract symptoms).

Clinical trials for Alzheimer’s disease (AD) face multiple challenges, such as the high screen failure rate and even allocation of heterogeneous participants. Artificial intelligence (AI), which has become a potent tool of modern science with the expansion in the volume, variety, and velocity of biological data, offers promising potential to address these issues in AD clinical trials. In this review, we introduce the current status of AD clinical trials and topic of machine learning. Then, a comprehensive review is focused on the potential applications of AI in the steps of AD clinical trials, including the prediction of AD biomarkers and differential diagnosis of AD in the prescreen during eligibility assessment and the likelihood stratification of patients who will progress to AD dementia and fast cognitive decline group from the slow decline group in randomization. Finally, this review provides challenges, developments and the future outlook on the integration of AI into AD clinical trials.

One of the main drivers behind the urbanization process is attributed to economic fundamentals of urban growth, which boost migration from rural to urban context. This migration can be studied geographically, with increasing rates of population as the main component in developing countries, over Asia and Africa, specifically. Research has been focusing in creating models and adaptative schemes to manage and plan cities to promote sustainable development for housing large quantities of population and preserve a long-term living environment. The approach from a smart city perspective, adjusted to the rapid urbanization condition can be helpful to deal urban issues by convergence and interaction between urban agents and information technology. At academia, few works have addressed the role of Smart Cities to face the challenge of rapid urbanization. The aim of this study is to research and analyze if strategies with smart city vision can lessen environmental impacts at cases with rapid urbanization, and how can we leverage technology to promote environmental sustainability at rapid urbanization phenomena occurring at developing countries using RIAM environmental assessment method in the case of Beijing, China'.

Optic nerve sheath diameter (ONSD) can help predict the neurologic outcome of patients with post-cardiac arrest (CA) return of spontaneous circulation (ROSC). We aimed to investigate the effect of ONSD changes before and after CA on neurologic outcomes in patients with ROSC after CA using brain computed tomography (CT). The study included patients hospitalized after CA, who had undergone pre- and post-CA brain CT from January 2001 to September 2020. The patients were divided into good and poor neurologic outcome (GNO and PNO, respectively) groups based on the neurologic outcome at hospital discharge. We performed between-group comparisons of the amount and rate of ONSD changes on brain CT and calculated the area under the curve (AUC) to determine their predictive value for neurologic outcomes. Among the 96 enrolled patients, 25 had GNO. Compared to the GNO group, the PNO group showed significantly higher amount (0.30 vs. 0.63 mm; p=0.030) and rate of change (5.26 vs. 12.29 %; p=0.041). The AUC for predicting PNO was 0.64 (95% CI=0.53–0.73; p=0.04) and patients with a rate of ONSD change &gt;27.2% had PNO with 100% specificity and positive predictive value. Hence, ONSD changes may predict neurologic outcomes in patients with post-CA ROSC.

Research professors develop scientific products that impact and benefit society, but their competencies in doing so are rarely evaluated. Therefore, employing a mixed two-stage sequential design, this study developed a self-assessment model of research professors’ competencies with four domains, seven competencies, and 30 competency elements. Next, we conducted descriptive statistical analysis of those elements. In the first year, 320 respondents rated themselves on four levels: initial, basic, autonomous, and consolidated. In the assessment model’s second year, we compared 30 respondents’ results with those of their initial self-assessment. The main developmental challenge was Originality and Innovation, which remained at the initial level. Both Training of Researchers and Transformation of Society were at the basic level, and Digital Competency was at the autonomous level. Both Teaching Competence and Ethics and Citizenship attained the consolidated level. This information helps establish priorities for accelerating researchers’ training and the quality of their research.

Introduction In 2016 the European Union setup its first structured food provision program to combat food insecurity. We aimed to measure the program’s capacity in assisting its beneficiaries to achieve a healthy diet and measure their satisfaction. Methods A computational study was carried out to calculate daily food provision per person under the program for January 2016-December 2017. A cross sectional survey in 3942 beneficiaries took place in December 2017-June 2018 collecting anthropometric, sociodemographic and program satisfaction data. Descriptive statistics were performed and reported as relatively frequencies, mean ± standard deviation. Results Dairy, fresh meat, legumes, sugar, olive oil and tomato concentrate were the most commonly procured items. The program’s contribution to vegetable, dairy and cereal intake was the lowest (3.4%, 6.1%, 6.0% respectively) as opposed to free sugars (12.2%) and oils (24.5%). The program’s algorithm favors greatly (almost 3-fold) single person applications compared to 4+ persons applications. The monetary value was estimated at 21.23±23.4 euros/food provision, however 64.4% of beneficiaries reported a high positive impact on the household budget. 50.7% and 41.6% reported high positive impact on feelings of anxiety and security, respectively. ~70% of the beneficiaries were highly satisfied with the foods provided, with lower scores for quality and shelf-life (50.7% and 58.8% high respectively). Conclusions The program is met by high beneficiary satisfaction and is perceived as a substantial assistance. Increases in the amounts and variety of foods delivered, with a focus on fruit, vegetables and fish should be considered, to further improve the program’s dietary impact.

The traditional standards employed for pain assessment have many limitations. One such limitation is reliability because of inter-observer variability. Therefore, there have been many approaches to automate the task of pain recognition. Recently, deep-learning methods have appeared to solve many challenges, such as feature selection and cases with a small number of data sets. This study provides a systematic review of pain-recognition systems that are based on deep-learning models for the last two years only. Furthermore, it presents the major deep-learning methods that were used in review papers. Finally, it provides a discussion of the challenges and open issues.

As organizations are vulnerable to cyber attacks, their protection becomes a significant issue. Capability Maturity Models can enable organizations to benchmark current maturity levels against best practices. Although many maturity models have been already proposed in the literature, a need for models that integrate several regulations exists. This article presents a light web-based model that can be used as a cybersecurity assessment tool for Higher Education Institutes (HEIs) of the UK. The novel Holistic Cybersecurity Maturity Assessment Framework incorporates all security and privacy regulations and best practices that HEIs must be compliant to and can be used as a self-assessment or a cybersecurity audit tool.

Endemic freshwater fish from semiarid environments are among the most threated species in the world due to the water overexploitation and habitat fragmentation problems. Stepped or pool-type fishways are used worldwide to reestablish longitudinal connectivity and mitigate fish migration problems. Many of them are being installed or planned in rivers of semiarid environments, however, very few studies about fish passage performance through pool-type fishways has been carried out to date on these regions. The present work focuses on the passage performance of two potamodromous cyprinids endemic of these regions, with different ecological and swimming behavior: southern Iberian barbel (Luciobarbus sclateri) and Iberian straight-mouth nase (Pseudochondrostoma polylepis), in two of the most common types of stepped fishways: vertical slot and submerged notch with bottom orifice fishways. Experiments were carried out during the spawning season in the Segura River (South-Eastern Spain), using a PIT tag and antennas system. Ascent success was greater than 80%, with a median transit time lower than 17 minutes per meter of height in all trials and for both species and fishway types. Results show that both types of fishways, if correctly designed and built, provide interesting alternatives for the restoration of fish migration pathways on these regions.

Improving the efficiency of the supply process in prefabricated components is challenging and requires accounting for a variety of risks involved in the management of the suppliers. The purpose of this study is to present a method to account for the systematic trade-offs between several supplier alternatives. A novel framework is presented for the whole assessment of supplier alternatives by taking advantage of the information extracted from customized building information modeling (BIM) and a database required for assessment of impacts. A data library related to assessment criteria for supply alternatives is built to facilitate the storage and sharing of information. Analytic hierarchy process (AHP) is used to select the optimal supplier that is able to provide the most satisfaction for the determined criteria. The proposed framework was also illustrated by the implementation in a mega project. The study implication is that BIM-enabled supplier selection can indeed lead to more benefits and higher values for all stakeholders.

An exploratory Life Cycle Assessment was carried out to provide insight into the environmental impacts of using the green seaweed Ulva spp. as a feedstock for production of bioplastic. The study focused on the production of lactic acid as a precursor of polylactic acid. The studied production process consists of (1) the cultivation of Ulva spp. in Integrated Multitrophic Aquaculture, (2) the processing of the biomass for solubilisation of sugars, (3) the fermentation of the sugars to lactic acid and (4) isolation of lactic acid from the fermentation broth. The study identifies environmental hotspots and compares the experimental seaweed production chain with conventional feedstock. The main hotspot identified is electricity consumption during seaweed cultivation. This impact of electricity consumption can be lowered by reducing energy use and sourcing renewable energy, and by improving the material efficiency in the product chain. To improve understanding of the environmental impacts of the production process, future studies can broaden the system boundaries and broaden the scope of sustainability issues included in the environmental assessment.

The social criteria of sustainable development have remained underexplored. Moreover, a large number of green building assessment tool and social sustainability documentations have been developed which, has had a direct impact on social criteria issues, but there seems to be a substantial gap in the study of social criteria in green building assessment tools. In examining the problem facing social sustainability, taking into consideration social sustainability in sustainable development reviews and green building assessment tool towards social aspects. This paper through analysis identified a centripetal conceptual framework composed of seven key components equity, education, participation & control, social cohesion, health & safety, accessibility & satisfaction, and cultural values. The interpretation of the social sustainability in green building assessment tool would impact building practitioners towards implementing social criteria in GBAT. The aim was to identify social categories as well as consider a starting point for the development of an effective social criteria assessment tool for green building.

Material efficiency is a key element of new thinking to address the challenges of reducing impacts on the environment and of resource scarcity, whilst at the same time meeting service and functionality demands on materials. Directly related to material efficiency is the concept of the Circular Economy, which is based on the principle of optimising the utility embodied in materials and products through the life cycle. Whilst steel, as a result of high recycling rates, is one of the most ‘circular’ of all manufactured materials, significant opportunities for greater material efficiency exist, which are yet to be widely implemented. In the field of Life Cycle Management, Life Cycle Assessment (LCA) is commonly used to assess the environmental benefits of recovering and recycling materials through the manufacturing supply chain and at end-of-life. As well as containing information to calculate environmental impacts, LCA models also provide the flows of materials through the product life cycle and can also be used to quantify material efficiency and the circularity of a product system. Using an example taken from renewable energy generation, this paper explores the correlation between product circularity and the environmental case for strategies designed to improve material efficiency. An LCA-based methodology for accounting for the recovery and re-use of materials from the supply chain, and at end-of-life, is used as the basis for calculating the carbon footprint benefits of five material efficiency scenarios. Resulting carbon footprints were then compared with a number of proposed material circularity indicators. Two conclusions from this exercise were that i) LCA methodologies based around end-of-life approaches are well placed for quantifying the environmental benefits of material efficiency and circular economy strategies and ii) when applying indicators relating to the circularity of materials these should also be supported by LCA studies.

The Inventory Déjà Vu Experiences Assessment (IDEA) is the only screening instrument proposed to evaluate Déjà vu (DV) experience. Here we intended to validate the Italian version of IDEA (I-IDEA) and at the same time to investigate the incidence and subjective qualities of DV phenomenon in Italian healthy adult individuals on basis of an Italian multicentre observational study. In this study we report normative data on the I-IDEA, collected on a sample of 542 Italian healthy subjects aging between 18 to 70 years (average age 40, range 18-70) with a formal educational from 1-19 years. From September 2013 to March 2016 were recruited 542 healthy volunteers from ten outpatient neurological clinics in ItalyAll participants (i.e family members of neurological patients enrolled, medicine’s student, physicians) had no neurological or psychiatric illness and they gave informed consent to participate in the study. All subjects enrolled had self-administered the questionnaire and they are able to complete I-IDEA test without any support. In total 396 (73%) of the 542 healthy controls had DV phenomenon. The frequency of DV was inversely related to age as well as to derealisation, jamais vu, precognitive dreams, depersonalization, paranormal activity, remembering dreams, travel frequency and daydreams (all P<0.012). The Italian version of IDEA maintains good properties in Italian version, thus confirming that this instrument is reliable for detecting and characterising the DV phenomenon.

Coastal inundation is an increasing problem. Sea-level rise will greatly increase the frequency and depth of inundation, forcing vulnerable communities to adapt. Communities will need to decide when and how to adapt. The process of decision-making along adaptive pathways is now being used internationally to plan for adaptation over time by anticipating decision points in the future however it unfolds. This process requires risk and uncertainty considerations to be transparent in the scenarios used in such planning. We outline a framework for uncertainty identification and management within coastal hazard assessments which recognizes different types of decision and identifies the types of uncertainty that must be accounted for, such as statistical, scenario and deep uncertainty types. We show how coastal-inundation hazard can be mapped and presented in a way that clearly separates sources of uncertainty, so that they are transparent within a dynamic adaptive pathways planning process. Traditional coastal inundation maps show inundated area only. We present maps of inundation depth and frequency which clearly show the degree of exposure, where that exposure occurs, and how much sea-level rise can be tolerated. The new uncertainty framework and mapping techniques can better identify decision points and their expected time range, which provides more useful input to the adaptation process than traditional coastal inundation assessments.

Our socio-demographic status is determined by socio-demographic position and success. In the theoretical frame works, little was known about the theory, quantification and evolutionary mechanism of socio-demographic status of individual(s). This paper proposed theoretical assumptions for the evolution of socio-demographically unique population. Seven (7) factors (the driving forces) and eight (8) conditions responsible for the evolution of socio-demographically unique population were identified and explained. The evolutionary transitions were organized into six (6) socio-demographic ranks. The paper also identifies the basic features that clarify our understanding about the conception of socio-demographic status of an individual(s) as common, universal and desirable positions, achievements, and advantages every individual strives and competes to attain, achieve and maintain which are determined by biological and social environments, driven and regulated by a continuum of competitions. The paper presents a new dimension for the quantitative assessment of an individuals’ socio-demographic status and the established hierarchical transitions.

The article describes the methodology of the experimental analysis of operational and cost-effective assessment using geographic information system (GIS) technologies, as opposed to the assessment of the tourism potential of the nature of the Fergana Valley in Uzbekistan using long term and costly classical approaches. Based on the ArcGIS (10.8) grid index approach of 20 natural geographical indicators of the valley, such as geographical location, relief, climate, hydrographic and biological, the level of tourism comfort was determined and the location of 6 tourist-recreation zones were defined. The level of accuracy of the tourist-recreational zones all situated utilizing GIS technologies was confirmed by field-expedition approaches.

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of human visual system (HVS) can be combined. In this paper, inspired by the ventral pathway and dorsal pathway of HVS, a dual-pathway convolutional neural network is proposed for BIQA task. The proposed method consists of two pathways: “what” pathway, which mimics the ventral pathway of HVS to extract the content features of distorted images, and the “where” pathway, which mimics the dorsal pathway of HVS to extract the global shape features of distorted images. Then, the features from the two pathways are fused and mapped to an image quality score. Additionally, the gradient images weighted by the contrast sensitivity are used as the input to the “where” pathway, allowing it to extract global shape features that are more sensitive to human perception. Moreover, a dual-pathway multi-scale feature fusion module is designed to fuse the multi-scale features of the two pathways, enabling the model to capture both global features and local details, thus improving the overall performance of the model. The experiments conducted on six databases show that the proposed method achieves the state-of-the-art performance.

The city administration of China planned numerous metro projects and more metros can hardly avoid undercrossing a bridge. While metro shield construction when undercrossing a bridge (MSCUB) is frequently located in complicated natural and social context, which made the construction process more susceptible to safety accidents. Therefore, it is crucial to look into safety risk of MSCUB. The paper identified the safety risk factors during SSCUR by using literature review and experts’ evaluation, proposed a novel safety risk assessment model by integrating CFA and FER, and then selected a project case to test the validity of the suggested model. Research results show that (a) a safety risk factors list of MSCUB was identified, including 4 first-level safety risks and 37 second-level safety risk factors; (b) the proposed safety risk assessment model can be used to measure the risk values of the overall worksite safety risk, the first-level safety risks and the safety risk factors of MSCUB; (c) environment-type safety risk and personnel-type safety risk have higher risk values when shield construction undercrossing a bridge; (d) when compared to worker-type safety risk, manager-type safety risk is the higher risk value. The research can enrich the theoretic knowledge of MSCUB safety risk assessment and provide references to safety managers for conducting scientific and effective safety management on the construction site when subway undercrossing a river.

This study establishes life cycle assessment model to quantitively evaluate and predict material resource consumption, fossil energy consumption and environmental emissions of plug-in hybrid electric vehicles (PHEVs) by employing the GaBi software. the envi-ronmental impact of different vehicle working conditions, power battery degradation scenarios and mileage scenarios on the operation and use stage of PHEV, BEV and HEV is distinguished. The findings indicate that under urban, highway, and aggressive driving conditions, PHEVs' life cycle material resource and fossil fuel consumption exceed that of BEVs but are less than HEVs. Battery degradation leads to increased material resource consumption, energy use, and environmental emissions for both PHEVs and BEVs, en-vironmental emission of BEVs are more sensitive than those of PHEVs to the impact of power battery degradation. Among different-mileage scenarios, PHEVs demonstrate the least sensitivity to increased mileage regarding life cycle material resource consumption, with the smallest increase. Future projections for 2025 and 2035 suggest life cycle GWP of HEV, PHEV and BEV in 2035 is 1.21×104, 1.12×104 and 1.01×104 kg CO2-eq respectively, which is decreased by 48.7%, 30.9% and 36.1% compared with those in 2025. The out-comes of this study are intended to bolster data support for the manufacturing and de-velopment of PHEV, BEV and HEV under different scenarios and offer insights into the growth and technological progression of the automotive sector.

In response to a threefold increase in osteoporotic vertebral fractures (OVF) at our institution over the past decade and the subsequent development of new fractures within a year in a third of cases, we evaluated the effectiveness of STIR MRI scans in conjunction with CT scans for initial OVF diagnosis. This study, conducted over five months, involved full spine sagittal STIR MRI scans alongside CT scans for patients over 50 with minor injury-related vertebral fractures. The independent assessments by radiologists and neurosurgeons of 64 patients revealed that while CT scans identified 161 fresh fractures, of which only 68 were previously reported, MRI detected 266 fractures, 1.65 times more than CT. CT scans showed single fractures in 27% of patients and multiple fractures in 73%, whereas MRI identified single fractures in 9% and multiple fractures in 91% of patients. Additionally, MRI demonstrated a 1.5-fold increase in adjacent fracture detection. The use of MRI influenced treatment plans in 67% of cases. Given these findings, we advocate for including a STIR MRI of the entire spine alongside CT scans in OVF cases, as it significantly enhances fracture detection and can alter treatment strategies.

MRI is the gold standard for treatment response assessment in glioblastoma. However, there is no consensus regarding the optimal interval for MRI follow-up during standard treatment. Moreover, reliable assessment of treatment response is hindered by the occurrence of pseudoprogression. It is unknown if a radiological follow-up strategy with 2-3 months intervals actually benefits patients and how it influences clinical decision making about continuation or discontinuation of treatment. This study assessed the consequences of scheduled follow-up scans (post-chemoradiotherapy [post-CCRT], after 3 cycles of adjuvant chemotherapy [TMZ3/6], after completion of treatment [TMZ6/6]) and unscheduled scans on treatment decisions during standard concomitant and adjuvant treatment in glioblastoma patients. Additionally, we evaluated how often follow-up scans resulted in diagnostic uncertainty (tumor progression versus pseudoprogression), and whether perfusion MRI improved clinical decision making. Scheduled follow-up scans during standard treatment in glioblastoma patients rarely resulted in early termination of treatment (2.3% post-CCRT, 3.2% TMZ3/6, and 7.8% TMZ6/6), but introduced diagnostic uncertainty in 27.7% of cases. Unscheduled scans resulted in more major treatment consequences (30%; p&lt;0.001). Perfusion MRI caused less diagnostic uncertainty (p=0.021) but did not influence treatment consequences (p=0.871). This study does not support the current pragmatic follow-up strategy and suggests a more tailored follow-up approach.

This study aimed to investigate the effects of forearm postures and elbow joint angles on muscle torque and mechanomyography (MMG) signals. The torque about the elbow and MMG of the biceps brachii (BB) muscle were measured in 36 healthy subjects using an in-house elbow flexion testbed and Neuromuscular electrical stimulation (NMES) of the BB muscle. The BB muscle received stimulation intensity while the forearm was positioned in the neutral, pronation or supination. The elbow was flexed at angles 10°, 30°, 60° and 90°. (0° = full elbow extension). The study analyzed the impact of forearm posture(s) and elbow joint angle(s) on the root mean square value of torque (TQ_RMS). Subsequently, MMG parameters such as the root mean square value (MMG_RMS), the mean power frequency (MMG_MPF), and the median frequency (MMG_MDF), were analyzed in the longitudinal, lateral, and transverse axes of the BB muscle fibers. Forearm posture and elbow flexion angle were found to significantly influence TQ_RMS (P < 0.05). Similarly, MMG_RMS, MMG_MPF and MMG_MDF exhibited a significant difference for all postures and angles (P < 0.05). However, the combined main effect of forearm postures and elbow joint angles was insignificant in the longitudinal axis (P > 0.05). The study also found that MMG_RMS and TQ_RMS increased with the joint angle to 60° and decreased to the other angle(s). However, during this investigation,MMG_MPF and MMG_MDF exhibited a consistent decrease in response to joint angles. This finding suggests that the muscle contraction evoked by NMES may be influenced by the interplay between actin and myosin filaments, which are responsible for muscle contraction and are in turn influenced by muscle length. As restoring the function of limbs is a common goal in rehabilitation services, it becomes imperative to develop methods that may enable the real-time tracking of exact muscle dimensional changes and activation levels.

DNA barcoding has emerged as a transformative tool in the realm of biodiversity assessment, facilitating rapid and precise species identification. This review article delves into the evolving landscape of DNA barcoding, with a particular focus on the emergence of mini-barcodes and alternative genes as innovative approaches. Traditional DNA barcoding, anchored in the COI gene, has significantly advanced our understanding of species diversity; however, inherent challenges persist, especially when dealing with degraded samples or taxonomic groups where COI falls short. The introduction of mini-barcodes, characterized by their reduced sequence length, has revolutionized DNA barcoding by expanding its applicability. We explore the utility of mini-barcodes in various scenarios, ranging from DNA extraction from ancient or fragmented specimens to in-field identification using portable sequencing technologies. Case studies and practical insights into their effectiveness are presented, emphasizing their role in overcoming traditional limitations. Alternative genes, a complementary facet of DNA barcoding, offer a novel avenue for enhancing taxonomic resolution and accuracy. This review showcases instances where researchers have harnessed alternative genes to overcome COI's constraints, particularly in diverse taxonomic groups, such as fungi, plants, and microorganisms. The selection of these genes is discussed, along with their potential to uncover hidden biodiversity and improve species delimitation. Examining the broader implications of mini-barcodes and alternative genes, we unveil their pivotal roles in advancing conservation efforts, forensic science, and citizen science initiatives. The adaptable nature of these approaches empowers a diverse range of stakeholders, from scientists conducting critical research to concerned citizens contributing to our collective understanding of the natural world. Looking ahead, we envision an exciting future for DNA barcoding, as these innovations continue to evolve. Integration with cutting-edge sequencing technologies, data analysis methods, and the harnessing of big data hold immense potential. Nonetheless, challenges related to standardization, scalability, and data sharing persist.