Paper discussed the problem of proper process of gas-freeing and ventilation of vessel cargo tank after washing process in aim to the entrance into the tank and its inspection. Correct assessment of atmosphere composition into the cargo tank is a basic condition of safe entrance and work of a crew. It should be done following actions: assessment of flammability hazard, the presence of other toxic gases for human and oxygen concentration. In the aim ship-owner should prepare adequate procedures: before entrance, during work and on emergency situations. On a vessel the assessment performs responsibility (entitled) officer whose decisions are crucial for the safety of prosecuting operations. The one of primary problem is proper (adequate) assessment of oxygen concentration in the air into the tank (enclosed spaces) after the measurement which should be properly interpreted. It concerns basically such situations when the oxygen concentration into the tank after measure leads the value over 22% or below 20.6% of volume (mole) contribution (v/v).

The Blended Wing Body (BWB) configuration is considered to have the potential of providing significant advantages when compared to conventional aircraft designs. At the same time, numerous studies have reported that technical challenges exist in many areas of its design, including stability and control. This study aims to create a novel BWB design to test its flying and handling qualities using an engineering flight simulator and as such, to identify potential design solutions which will enhance its controllability and manoeuvrability characteristics. This aircraft is aimed toward the commercial sector with a range of 3,000 nautical miles, carrying a payload of 20,000kg. In the engineering flight simulator a flight test was undertaken; first, to determine the BWB design’s static stability through a standard commercial mission profile, and then to determine its dynamic stability characteristics through standard dynamic modes. Its flying qualities suggested its stability with a static margin of 8.652% of the Mean Aerodynamic Chord (MAC) and consistent response from the pilot input. In addition, the aircraft achieved a maximum lift-to-drag ratio of 28.1; a maximum range of 4,581 nautical miles; zero-lift drag of 0.005; and meeting all the requirements of the dynamic modes.

The present paper aims to increase knowlodge of the methods of resistance estimating of concrete in situ by means of non-destructive tests used to integrate the quantitative results from cylindrical specimens (core). The results of experimental investigations carried out on concrete conglomerate samples of a school building are shown. The experimental campaign then will be presented like a case study, conducted on a series of concrete beams and pillars of an existing building. The distructive tests on cores were conducted at the Civil Structures Laboratory of the Engineering Department of the University of Campania "Luigi Vanvitelli". The expression obtained through the calibration procedure of the values of non-destructive tests with those provided by the core drills allowed to estimate the average values of the compressive strength of the concrete. It is highlighted how this result was achieved with a very limited core number provided that they are extracted in selected points and that there was a proportionality link with the resistances obtained from non distructive tests.

It is important for enterprises to decide their environmental policies after carefully examining their future paths based on the relationship between the environment and the economy. This study focused on Japanese minimum administrative divisions (municipalities) and attempted to quantify the annual environmental efficiency of production activities within each division according to the theory of life-cycle impact assessment (LCIA). This study leverages the assessment theory LIME2, which is an endpoint-type LCIA method developed in 2010 that integrates environmental loads for certain impact categories, such as global warming and land use into a simple indicator by monetary unit. First, annual environmental impact assessments were conducted for all Japanese municipalities based on statistical information that was reliable, verifiable, and comparable. Next, the environmental efficiency of productivity for each division was conceptualized by dividing the gross domestic product by the environmental damage amounts as calculated above. Assessment results for each municipality were placed on a map of Japan in order to visualize the regionality of each indicator. The findings revealed in this study will aid public administrators in their decision-making process with respect to environmental policies.

Green ICT has received significant attention in organizations to reduce global warming since last decade. Several maturity models have been proposed for tracking green ICT practices in organizations. Current literature shows that SMEs around the world try to follow some common strategies such as virtualization, consolidation of devices, energy efficiency and disposal of ICT equipment for greening ICT. The increasing interest for green ICT practices in organizations is not only due to the desire to attain environment-friendly atmosphere but mainly because of sustaining business goals such as cost reduction, competitive advantages and stakeholders’ pressure. Nevertheless, due to the lack of green ICT knowledge, organizations, specially SMEs, tend to ignore those practices. Therefore, this research proposes a framework that provides combination of existing green and sustainable ICT maturity models by mapping them with the strategies the businesses are already following. Out of this framework, a web application has been developed that provides questionnaire for SMEs to identify their present situation of green ICT practices and guidelines for improvement. The results have been analyzed by testing the application in some SMEs of Finland and Bangladesh. Finally, a survey has been conducted to attain SMEs’ perception about the possibility of sustainable development of businesses through this application.

Traffic source emissions inventories for the rapidly growing West African urban cities are necessary for better local characterization of vehicle emissions released into these cities atmosphere. This study based on local field campaign in a representative site of anthropogenic activities over West African cities such as Yopougon (Abidjan, Côte d'Ivoire) during 2016, provided useful information on vehicle type and age, traveling time, fuel type and amount for fuel consumption estimation. Also, high traffic flow of personal car were recorded on highway, boulevard and backstreet whereas high flows of intra-communal sedan taxi are recorded on main and secondary roads. In addition, the highest daily fuel consumption value of 56 L.day^-1 was recorded in heavy vehicle while the lowest value of 15 L.day^-1 is recorded for personal car using gasoline. This study will be useful for the improvement of uncertainties related to the different databases used to estimate inventories emissions either national or international reports. This work provides useful information for future studies on urban air quality, climate and health impacts assessment in African cities. It may also be useful for policy makers to support implementation of emission reduction policy in West African cities.

Excessive vibration of temporary grandstand owing to crowd has lateral rhythmic motions can cause human in panic, which attracted increasing attention in recent years. This paper focuses on experiments that a temporary grandstand occupied 20 participants is oscillated by a shaking table with a series of random waves and induced by crowd with rhythmic swaying motions at lateral direction, respectively. And then a series of vibration perception questionnaires about crowd reaction are obtained. Evaluation of annoying level derives in concept of degree of membership and annoying rate method is proposed, then the human health risk of vibration serviceability of temporary grandstand is assessed with acceleration vibration dose value(VDV). From these results it is clear that standing crowd is more tolerant to vibration than seated crowd. The measured vibrations generated by crowd activities on temporary grandstand can cause panic in crowd. New relationship between the annoyance rate and structural acceleration VDV at logarithmic coordinate is proposed. The findings of this study can be utilized to manage the vibration of temporary grandstand and assess the human health risk.

Objective: To evaluate the direct costs of treating patients with neuromyelitis optica spectrum disorders (NMOSD) in outpatient care, from a hospital and Unified Health System (SUS) perspective. Methods: Observational study with data collection by microfunding, carried out with patients diagnosed with neuromyelitis optics, treated at a university hospital, in the city of Rio de Janeiro. Mann-Whitney tests were performed to measure cost differences between patient groups by disease severity and analysis perspective. Results: Nine individuals with a median age of 48 years (IQR 30 - 59 years) were included. The median total costs for patients with greater severity from the perspective of the SUS and the hospital were R$ 21,638.22 (IIQ: R$ 15,614.63; R$ 25,985.32) and R$ 32,094.11 (IIQ: R$ 25,610 .60; R$ 38,617.25) respectively. For patients with moderate severity the median was R$ 7,339.85 (IIQ: R$ 6,235.45; R$ 11,912.05) from the SUS perspective and R$ 11,505.80 (IIQ: R$ 7,339.85; R$ 22,424.76) from the perspective of the hospital, where the use of medications had a major impact. Conclusion: The main cost drivers were medicines, especially those used off-label, and procedures.

The current research investigated the environmental risk of the polycyclic musk compounds, Galaxolide® (HHCB) and Tonalide® (AHTN), in the marine environments. These substances are lipophilic, bioaccumulated and potentially biomagnified in aquatic organisms. To understand the toxicity of HHCB and AHTN, we performed acute toxicity tests by exposing marine microalgae (Phaeodactylum tricornutum, Tretraselmis chuii and Isochrysis galbana), crustaceans (Artemia franciscana), echinoderms (Paracentrotus lividus), bivalves (Mytilus galloprovincialis), fish (Sparus aurata) and a candidate freshwater microalga (Raphidocelis subcapitata) to environmentally relevant concentrations (0.005 - 5 µg/L) following standardized protocols. The effects of both substances on microalgae growth were incipient and only I. galbana was sensitive to HHCB and AHTN, with IC10 values of 5.22 µg/L and 0.328 µg/L, respectively. Significant (p < 0.01) concentration dependent responses were measured in P. lividus and M. galloprovincialis larvae developments as well as S. aurata mortality tested with HHCB. The effect of HHCB on P. lividus larvae development was the most sensitive endpoint recorded, producing an EC50 value of 4.07 µg/L. Our results show that HHCB represents a high risk to P. lividus larvae development for early life stages in marine environments.

Understanding the distribution in drought and floods plays an important role in disaster risk management. The present study aims to explore the trends in the standardized precipitation index and extreme precipitation days in China, as well as to estimate the economic losses they cause. We found that in the Northeast China, northern of North China and northeast of Northwest China were severely affected by drought disasters (average damaged areas were 6.44 million hectares) and the most severe drought trend was located in West China. However, in the north of East China and Central China, the northeastern of the Southwest China was severely affected by flood disasters (average damaged areas were 3.97 million hectares) and the extreme precipitation trend is increasing in the northeastern of the Southwest China. In the Yangtze River basin, there were increasing trends in terms of drought and extreme precipitation, especially in the northeastern of the Southwest China, where accompanied by severe disaster losses. By combining the trends in drought and extreme precipitation days with the distribution of damaged areas, we found that the increasing trend in droughts shifted gradually from north to south, especially in the Southwest China, and the increasing trend in extreme precipitation gradually shifted from south to north.

Accurate assessment of bone age (BA) is crucial for pediatric clinical practice. This study validated the Radiological Reference Atlas for Bone Age in the Canary Islands Population with a total of 203 anteroposterior left hand and wrist radiographs from healthy children (91 females, 112 males) across preschool, school-age, and adolescent stages. Intra-observer agreement, assessed by intraclass correlation coefficients (BAA1: ICC = 1.000, BAA2: ICC = 0.995, BAA3: ICC = 0.943), showed differing levels of precision among assessors. Inter-observer agreement was high (Pearson’s r = 0.905 - 0.951), suggesting consistent evaluations across different expertise levels. Accuracy analysis revealed significant BA underestimation compared to chronological age (CA) in preschool (MD = -17.036 months, p < 0.001) and school-age (MD = -8.165 months, p < 0.001) groups, but closer agreement in teenagers (MD = -0.33 months, p = 0.550). Furthermore, a relevant underestimation in the teenage stage for girls compared to boys was also noted. These findings underscore the atlas's precision; however, its accuracy for BA assessment in younger children and adolescent girls needs to be approached with caution.

Rhizosphere microorganisms can utilize nutrient resources in the rhizosphere efficiently, while rhizosphere growth-promoting bacteria play a crucial role in regulating soil fertility and promoting plant health. In this study, we employed a combination of isolation, purification, identification of dominant microorganisms, and high-throughput sequencing technology to analyze the main microbial groups and diversity in the rhizosphere soil of Helichrysum arenarium（L.）Moench. in Altay, Xinjiang，China. By isolating bacterial strains from the rhizosphere soil using a dilution coating method, we successfully obtained 43 strains. Subsequently, selective medium was utilized to screen for growth-promoting characteristics among these isolated strains from the rhizosphere soil of H. arenarium（L.）Moench.. The results obtained through high-throughput amplification sequencing revealed that the rhizosphere soil harbored diverse bacterial communities belonging to 35 phyla, 93 orders, 215 families, 324 genera and 231 species associated with H. arenarium（L.）Moench., as well as fungal communities consisting of 14 phyla ,47 orders ,96 families ,204 genera and 571 species. Among these bacterial communities identified, eight phyla exhibited relative abundances exceeding 1%, with Actinobacteriota being most predominant at an abundance rate of 41.30%. Additionally,five bacterial genera were found to have relative abundances exceeding 1% ,with Arenimicrobium_luteum being most abundant at 6.11% . Furthermore,four fungal phyla displayed relative abundances surpassing1 % ,with Ascomycota accounting for 67.21% of total fungal community composition.Finally,four fungal genera demonstrated relative abundances higher than 1% ,with Knufia representing 3.80% of total fungal community composition.The analysis on culturable bacteria's promotion activity within the rhizospheric soil indicated that two strains,S16and S29, exhibited the highest solubility index for inorganic phosphorus. However, it lacked the ability to dissolve organophosphorus and potassium. On the other hand, strains S7 and S10, which were screened, demonstrated nitrogen-fixing capabilities. Nine strains with excellent iron-bearing capacity were identified, with strain S16 exhibiting the highest D/d value and strongest iron-bearing capacity among them. Our findings revealed that 43 rhizosphere soil bacteria belonged to three genera. The ten growth-promoting bacteria were identified as Kocuria rosea, Priestia megaterium, Bacillus mobilis, B. bataviensis, B. mycoides (two strains), B. paramobilis, and Alcaligenes faecalis. This study provides a particular research basis for the influence of H. arenarium（L.）Moench. rhizosphere microorganisms on soil nutrient release and depicts a solution for improving the yield and quality cultivation of H. arenarium（L.）Moench. by isolating, screening, and identifying rhizosphere soil growth-promoting bacteria, including screening strains with growth-promoting functions and analyzing the population structure of rhizosphere and habitat soil in combination with high-throughput sequencing technology.

The accurate wellbore pressure control not only prevents from lost circulation/blowout and fracturing formation by managing density of drilling fluid, but also improves productivity by mitigating reservoir damage. The geothermal pressure calculated by constant parameters for geothermal well would bring big error easily, as the changes of physical, rheological and thermal properties of drilling fluids with temperature were neglected. This paper researches the wellbore pressure coupling by calculating the temperature distribution with existed model, fitting the rule of density of drilling fluid with temperature and establishing mathematical models to stimulate the wellbore pressures, which is expressed as the variation of Equivalent Circulating Density (ECD) under different conditions. With this method, temperature and ECDs in the wellbore of the first medium-deep geothermal well ZK212 Yangyi Geothermal Field in Tibet were determined, and the sensitivity analysis was simulated by assumed parameters, i.e. circulating time, flow rate, geothermal gradient, diameters of wellbore, rheological models and regimes, the results indicated the geothermal gradient and flow rate were the most influence parameters on the temperature and ECD distribution, and additives added in drilling fluid should be careful which would change the properties of drilling fluid and induce the temperature redistribution. To make sure the safe drilling, velocity of pipes tripping into the hole, depth and diameter of wellbore are considered to control the surge pressure.

This study investigates the moderating role of information asymmetry in shaping the effect of environmental sustainability reporting on the firm value of listed manufacturing companies in Nigeria. Utilizing an ex-post facto research design, the study draws on a stratified sample of 29 manufacturing firms from a population of 43 listed on the Nigerian Exchange as of December 31, 2022. Spanning from 2007 to 2022, the study collects secondary data from annual reports, Nigerian All Share Index reports, meristem securities and register platform Admin platform and sustainability reports. Employing descriptive and inferential statistics, along with multiple regression techniques, the analysis considers Firm value as the dependent variable, Environmental sustainability reporting as independent variables, Information asymmetry (IA) as the moderating variable and Equity ratio, Return on asset and Leverage as control variables. Results indicate that information asymmetry shows a negative and significant effect on the relationship between environmental sustainability reporting and firm value. The study concluded that information asymmetry impacts firm value despite environmental disclosure efforts. The study recommends that Nigerian manufacturing companies should engage in comprehensive disclosure practices to enhance transparency and address information asymmetry through adequate stakeholder engagement. The study’s findings emphasized the need for Nigerian policy makers to enhance regulations on environmental sustainability reporting. By implementing stricter disclosure laws and standards, policy can reduce information asymmetry and foster a more transparent business environment. This could attract foreign investment and demonstrate Nigeria’s commitment to sustainable practices. Furthermore, the study also highlights the importance of transparency in maintaining stakeholder trust. Improved disclosure practices can increase public trust in the manufacturing sector, promoting corporate responsibility. This heightened transparency benefits investors and the broader community, ensuring companies are accountable for their environmental impacts, ultimately leading to better environmental stewardship and community welfare.

Many pilot-based initiatives have been developed to promote awareness and use of climate information services among vulnerable smallholder farmers in Africa through million-dollar investments. However, despite their experimental nature, these pilot projects have been successful in raising participating farmers’ awareness and use of climate information services and they can inform transferrable good practices. Through a systematic literature review approach, this review sought to understand ways in which these past pilot projects have contributed to climate risk management in the context of smallholder farming and the factors that led to their success. Results showed that climate information services main contribution to climate risk management has been through facilitating farm level decision making. Factors that led to success of the pilots include: use of downscaled information; building institutional partnerships to add value to climate information; involving farmers through the co-designing and co-developing process; face-to-face way of communication; embedding pre-seasonal workshops in the activities of local institutions for sustainability; using diversity of communication channels to enhance reach among others. These factors can be borrowed as good practices to inform future efforts focused on increasing adoption of climate information services among a wider population beyond pilot project reach.

In Bangladesh, climate change is a major concern because of its geophysical location and climate dependent agriculture. As sessile organisms, crops plants have to face difficulties often in this environmentally vulnerable country. Therefore, this study examines the seasonal trend of two climatic parameters viz. temperature (maximum and minimum) and rainfall over a period of 1983 to 2013. Besides, this study provides insight into the relationship between climatic parameters and crop yield of two major crops viz. rice and wheat during 1997-2013. To assess the relationship of climatic parameters with time and yield using Pearson correlation analysis, time series data used at an aggregate level. SPSS software utilized for this analysis. The cropping seasons such as rice growing seasons Aus (summer rice), Aman (autumn rice) and Boro (winter rice) exhibited a significant increase in maximum and minimum temperature. Rainfall found to have a decreasing trend for all the seasons. This study also revealed that the climatic parameters had significant effects on rice yield, but these results varied among three rice crops. Maximum temperature had positive effects on all rice yields, especially on Aus and Aman. Minimum temperature had a negative effect on Aman rice yield but a positive effect on Aus rice yield. Wheat yield negatively associated with temperature. Rainfall exhibited negative relation with both rice and wheat yield.

In this paper, we demonstrate that fixed-weight layers, generated from random distribution or logistic functions, can effectively extract significant features from input data, resulting in high accuracy on a variety of tasks, including Fisher’s iris, Wisconsin Breast Cancer, and MNIST datasets. We have observed that logistic functions yield high accuracy with less dispersion in results. We have also assessed the precision of our approach under conditions of minimizing spikes number generated in the network, it is a practically useful for reducing energy consumption in spiking neural networks. Our findings reveal that the proposed method demonstrates a highest accuracy on Fisher’s iris and MNIST datasets with logistic regression. Furthermore, they surpass the accuracy of the conventional (non-spiking) approach using logistic regression in the case of Wisconsin Breast Cancer. We have also investigated the impact of non-stochastic spike generation on accuracy.

The work presented in this paper makes multiple scientific contributions with a specific focus on the analysis of misinformation about COVID-19 on YouTube. First, the results of topic modeling performed on the video descriptions of YouTube videos containing misinformation about COVID-19 revealed four distinct themes or focus areas - Promotion and Outreach Efforts, Treatment for COVID-19, Conspiracy Theories regarding COVID-19, and COVID-19 and Politics. Second, the results of topic-specific sentiment analysis revealed the sentiment associated with each of these themes. For the videos belonging to the theme of Promotion and Outreach Efforts, 45.8% were neutral, 39.8% were positive, and 14.4% were negative, for the videos belonging to the theme of Treatment for COVID-19, 38.113% were positive, 31.343% were neutral, and 30.544% were negative, for the videos belonging to the theme of Conspiracy Theories regarding COVID-19, 46.9% were positive, 31.0% were neutral, and 22.1% were negative, and for the videos belonging to the theme of COVID-19 and Politics, 35.70% were positive, 32.86% were negative, and 31.44% were negative. Third, topic-specific language analysis was performed to detect the various languages in which the video descriptions per topic were published on YouTube. This analysis revealed multiple novel insights. For instance, for all the themes, English and Spanish were the most widely used and second-most widely used languages, respectively. Fourth, the patterns of sharing these videos on other social media channels such as Facebook and Twitter were also investigated. The results revealed that videos containing video descriptions in English were shared the highest number of times on Facebook and Twitter. Finally, correlation analysis was performed by taking into account multiple characteristics of these videos. The results revealed that the correlation between the length of the video title and the number of Tweets as well as the correlation between the length of the video title and the number of Facebook posts was statistically significant.

We present a general theory of estimation of analysis error covariances based on cross-validation as well as a geometric interpretation of the method. In particular we use the variance of passive observation–minus-analysis residuals and show that the true analysis error variance can be estimated, without relying on the optimality assumption. This approach is used to obtain near optimal analyses that are then used to evaluate the air quality analysis error using several different methods at active and passive observation sites. We compare the estimates according to the method of Hollingsworth-Lönnberg, Desroziers et al., a new diagnostic we developed, and the perceived analysis error computed from the analysis scheme, to conclude that, as long as the analysis is near optimal, all estimates agree within a certain error margin.

State Forest Management Organizations (SFMOs) play a crucial role in the European forest sector, managing almost half the forests in the region. SFMOs are often managed for timber production only whereas, being publicly owned, they should play an important role in providing a vast range of public goods (e.g. soil protection, biodiversity conservation). Their management goals depend on the history and current conditions of the forest sector at a national level, as well as different challenges and the potential for development. Although there is a lack of knowledge about the current performance of SFMOs, there have been recent changes to their management goals and practices in response to the new demands expressed by society (e.g. transparency, social inclusion). The main purpose of this study is to analyse the current situation of SFMOs by clustering them according to indicators that reflect three pillars of the common understanding of sustainable forest management (SFM) concept. With the help of Principal Component Analysis (PCA), we grouped countries according to common characteristics of the forest sector at the national level. Results show three main clusters of SFMOs in Europe. The first cluster has rather small but commercially-oriented forestry unit together with other business activities and a strong focus on public services. The second sees itself as the protector of public interest, rather than commercially-oriented organisations. The third is mainly profit-seeking. The existence of diverse SFMO clusters shows the possibility of different approaches for SFM with a focus on different goals (e.g. profit gaining, public service delivery).

Biodiversity plays an important role in maintaining the ecological balance of the earth. The study of traditional knowledge related to biological resources is a hot issue in the field of international biodiversity conservation. Xishuangbanna is a key area of biodiversity and a cultural hotspot of international significance. According to the Technical Regulation for Classification, Investigation, and Inventory of Traditional Knowledge Relating to Biological Diversity issued by the Ministry of Ecology and Environment, we investigated and catalogued the traditional knowledge related to biodiversity of the Jino people who have lived in Xishuangbanna for generations, and collected 490 entries of traditional knowledge related to biodiversity of the Jino people. Drawing on the traditional knowledge diversity index calculation method proposed by Wang Guoping, the overall traditional knowledge α-diversity index of the Jino people is 0.63, indicating that the richness of the traditional knowledge of the Jinuo people is relatively high. The traditional culture related to biodiversity, the traditional knowledge related to agricultural genetic resources, and the traditional technology related to the sustainable utilization of biological resources are relatively rich and diverse. The diversity index is 0.86, 0.82 and 0.79 respectively. In addition, Xishuangbanna has invested a lot of energy in biodiversity protection, including the establishment of nature reserves, botanical gardens, zoos, ecological tea gardens and other species reserves, the promulgation of laws and policies related to biodiversity protection, and has achieved remarkable results in in-situ protection and ex-situ protection. On the basis of analyzing the progress and achievements of biodiversity conservation in Xishuangbanna, this study points out that Xishuangbanna faces challenges such as the loss of traditional knowledge, insufficient conservation efforts, and great changes in land use, and puts forward corresponding suggestions.

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common one has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

The European Green Deal poses a two-pronged challenge for the automotive industry: migrating to solutions based in light structures, requiring light weight concepts and light materials, while at the same time avoiding dependence towards the importation of these advanced materials. Aluminium alloys are lightweight and cost-effective materials that can successfully cover the requirements of many structural applications, however their production requires from bauxite and other Critical Raw Materials (CRM), such as Si and Mg. Aluminium alloys are fully recyclable, but scrap is usually contaminated and its use is related to an increment of impurities, tramp element and undesired inclusions. Traditionally, the use of secondary alloys has been restricted to low performance applications. The present work analyses the effect that the use of scrap has in the quantity of inclusions present in the alloy and in other properties relevant for the material processing. The study was carried out for common alloys belonging to 3 of the most common aluminium processes used in the car manufacturing industry: High Pressure Die Casting (HPDC) (EN AC-43500), extrusion (6063) and sheet metal forming (5754 and 6181). Reference alloy were mixed with different level of scrap (0, 20, 40, 60, 80 and 100%) trying to keep the chemical composition as unaffected as possible. The inclusions level of the alloy was characterized with the Prefil Foot-printer® test. In addition, the obtained materials, after being cast in an open mould, were subjected to metallographic characterization. Relevant properties to assess the formability quality of the alloys for the corresponding transforming process, were obtained: flowability test for HPDC alloy and high temperature compression for extrusion alloys. The results obtained suggest that the number of inclusions present in the melt highly increase with the amount of scrap used to produce the alloy. These inclusions are also related with an important lost of flowability, but do not have a noticeable impact on microstructure.

Pigeon paramyxovirus serotype 1 (PPMV-1), primarily originating from racing pigeons, has become a global panzootic, spreading to poultry and wild birds, thus posing a threat to the poultry industry. Egypt uses both inactivated pigeon paramyxovirus (PPMV-1) and conventional Newcastle disease virus (NDV) vaccines to protect pigeons. However, the impact of prevalent strains and the effectiveness of available vaccines in pigeons in Egypt are unclear. This study investigates the virulence of PPMV-1 isolated from vaccinated pigeons in Sharkia, Egypt (Pigeon/ Egypt/Sharkia-19/2015/KX580988). Ten-day-old specific-pathogen-free embryonated chicken eggs infected with this strain exhibited a mean death time (MDT) of 86.4±5.88 hours. The intracerebral pathogenicity index (ICPI) in day-old chicks was 0.8, while pigeons experienced an ICPI of 0.96 and an intravenous pathogenicity index (IVPI) of 2.11. These findings classify the strain as virulent and velogenic. Experimental infection with this PPMV-1 strain at 106 EID50/0.1 ml resulted in a 62.5% mortality rate in pigeons, displaying nervous and enteric distress. The virus caused extensive lesions in visceral organs, with strong immunohistochemistry signals in all examined organs, indicating the systemic spread of the virus concurrent to its neurotropic and viscerotropic tropism. Furthermore, vaccination using inactivated PPMV-1 and live NDV LaSota vaccine regimen protected 100% of pigeons against mortality, while a single NDV LaSota vaccine provided 62.5% protection. The PPMV alone or combined with NDV LaSota induced protective levels of hemagglutination inhibition antibody titers and reduced virus shedding from buccal and cloacal cavities. These findings suggest that using both inactivated PPMV-1 (G-VI) and live attenuated NDV (LaSota) vaccines is an effective prophylactic regimen for preventing and controlling PPMV-1 and NDV in pigeons, thereby reducing the risk of interspecies transmission.

Live-streaming commerce (LSC) is a new shopping method that combines the characteristics of social commerce and e-commerce. Since the global coronavirus disease 2019 (COVID-19) outbreak, the number of branded platforms is growing rapidly, and their competition is fiercer than ever. Understanding consumer needs and improving service quality become the key issue for survival. This study aims to develop and empirically validate a multi-dimensional hierarchical model for measuring service quality on LSC platforms. A hierarchical reflective construct was proposed to capture dimensions based on literature on e-retail and social commerce service quality. The pro-posed model was rigorously tested using two waves of survey data through the partial least squares method. Results showed that the service quality of LSC is a third-order, reflective con-struct and includes five primary dimensions (the streamer’s interaction quality, physical envi-ronment, website quality, outcome quality and ordering process) and twelve sub-dimensions (trustworthiness, expertise, responsiveness, telepresence, consumption scenarios, information quality, system operation quality, fulfillment and refund/compensation, privacy/security, contact and ease of use). Findings also supported the hypothesis that service quality has a significant impact on customers’ satisfaction and their behavioral intentions. Furthermore, we tested an al-ternative model, and the results showed that the relationship between dimensions and overall assessment is reflective rather than formative. We offered directions for further research on LSC service quality and discussed managerial implications stemming from the empirical findings.

Hail causes damage to property, including roofs, automobiles, and crops, with an average annual loss of $850 million. In residential structures, tile roofing systems are common in the southern U.S. due to their resistance to hail impact and long service life. Additionally, the commercial buildings and some portions of the residential structures have low-sloped or flat roof systems. Commercial low-slope roof systems are equally prone to hail-strike damages as steep residential roof systems. The objectives of this paper are to present a literature review, inspection protocol, and case studies on a comparative assessment of hail threshold for built-up roof (BUR) and tile roof (TR) systems. The published papers determining the hail impact assessment of different roofing systems from 1969 through 2023 were studied and analyzed. This study develops a comparative hail damage assessment table between BUR and TR systems, and the hail threshold for various built-up roof composition systems. In addition, the different failure modes and their causes, the characteristics of hail impacts, and the variables influencing the impact resistance of these roofing systems were examined using field studies. To better understand the effects, it is recommended that an intelligent model be developed to predict the hail resistance threshold of various configurations of BUR and TR systems with critical variables.

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

A cross-flow ultrafiltration harvesting system of a pre-concentrated microalgae culture was tested in an innovative anaerobic-based WRRF. The microalgae culture was cultivated in a membrane photobioreactor fed with the effluent from an anaerobic membrane bioreactor treating sewage. These harvested microalgae biomass was then anaerobically co-digested with primary and secondary sludge from the water line. Depending on the needs of this anaerobic co-digestion, the filtration harvesting process was evaluated intermittently over a period of 212 days for different operating conditions, mainly the total amount of microalgae biomass harvested and the desired final total solids concentration (up to 15.9 g·L1 with an average of 9.7 g·L1). Concentration ratios of 15-27 were obtained with average transmembrane fluxes ranged from 5 to 28 L·m2·h1. Regarding membrane cleaning, both backflushing and chemical cleaning resulted in transmembrane flux recoveries that were, on average, 21% higher than those achieved with backflushing alone. The carbon footprint assessment shows promising results as the GHG emissions associated with the cross-flow ultrafiltration harvesting process could be less than the emissions savings associated with the energy recovered from the biogas production from the anaerobic valorisation of the harvested microalgae.

Higher salt (sodium) intake has been associated with a higher blood pressure (BP). The association degree may be influenced by factors such as age, origin and dietary components. This study aimed to evaluate the 24-hours urinary sodium (Na) and potassium (K) excretion in normotensive and hypertensive Dominicans adults and estimate their salt intake. 163 volunteers (18-45, 46-80 years) participated in a cross-sectional study. 24-hours Na and K urinary excretion were measured using an ion selective electrode technique. Na and K urinary excretion (99.4±46.5 and 35.0±17.5 mmol/24h) did not correlated with BP, except in the normotensive group in which K correlated with SBP (0.249, p=0.019). Na and K excretion were similar for normo- and hypertensive subjects. Na-to-K molar ratio (3.1±1.3) was higher in younger subjects (p=0.040). Na-to-K ratio was associated with DBP in the total group (r=0.153, p=0.052), in the hypertensive group (r=0.395, p<0.001) and in the older group with SBP (0.350, p=0.002) and DBP (0.373, p<0.001). In the older group, Na-to-K ratio and DBP correlated after controlling for subjects with hypertension controlled by treatment (r=0.236, p=0.041). The Na-to-K ratio correlated, when salt intake was over 5g/d (52.2%), with SBP (rho=0.219, p=0.044) and DBP (rho=0.259, p=0.017). Determinants of BP were age-dependent and in younger subjects were: sex (SBP, beta: 14.02±2.87, p<0.001) and body mass index (BMI) (beta:-12.07±3.72, p=0.001, beta:9.44±2.87, p=0.001, for SBP and DBP, respectively) and, in the olders, the Na-to-K ratio, for SBP (beta:6.7±2.4, p=0.005) and DBP (beta:3.8±1.1, p<0.001). The mean Na and salt intakes (2.3 and 5.8 g/d) were slightly higher and K intake lower (1.4 g/d) than WHO recommendations.

Circadian rhythms misalignment is associated with hypertension. The aim of the study was to evaluate the concentration of selected clock proteins- cryptochrome 1 (CRY1) and circadian locomotor output cycles kaput (CLOCK) and to determine their relationships with biochemical and anthropometric parameters and lifestyle elements (diet, physical activity, quality of sleep) in hypertensive patients. In 25 female with hypertension (HT) and 49 non-hypertensive women (NHT), the CRY1 and CLOCK concentrations, total antioxidant status (TAS), lipid profile and glycemia were conducted. Blood pressure and anthropometric measurements, nutritional, exercise and sleep analyses were performed. In HT the CRY1 level was 40.2% lower than in the NHT. No differences were noted in CLOCK concentration between groups. The study showed no relationship between CRY1 or CLOCK concentrations and glucose or lipids profile, amount of physical activity and sleep quality, although CRY1 was associated with some anthropometric parameters. There was a negative correlation between the CLOCK concentration and the amount of saturated fatty acids consumed (24h) in HT. That indicates the possible influence of the diet on the CLOCK level. In a detailed prognosis of the risk of hypertension, it is worth considering the measurement of the level of CRY1 in populations with abnormal anthropometric indices.

While Twitter has been touted to provide up-to-date information about hazard events, the reliability of tweets is still a concern. Our previous publication extracted relevant tweets containing information about the 2013 Colorado flood event and its impacts. Using the relevant tweets, this research further examined the reliability (accuracy and trueness) of the tweets by examining the text and image content and comparing them to other publicly available data sources. Both manual identification of text information and automated (Google Cloud Vision API) extraction of images were implemented to balance accurate information verification and efficient processing time. The results showed that both the text and images contained useful information about damaged/flooded roads/street networks. This information will help emergency response coordination efforts and informed allocation of resources when enough tweets contain geocoordinates or locations/venue names. This research will help identify reliable crowdsourced risk information to enable near-real time emergency response through better use of crowdsourced risk communication platforms.

In this paper an integrated methodology for the coupling between 1D- and 3D-CFD simulation codes is presented, which has been developed to support the design and calibration of new diesel engines. The aim of the proposed methodology is to couple 1D engine models, which may be available in the early-stage engine development phases, with 3D predictive combustion simulations, in order to obtain reliable estimates of engine performance and emissions for newly designed automotive diesel engines. The coupling procedure features simulations performed in 1D-CFD by means of GT-SUITE and in 3D-CFD by means of Converge, executed within a specifically designed calculation methodology. An assessment of the coupling procedure has been performed by comparing its results with experimental data acquired on an automotive Diesel engine, considering different working points including both part load and full load conditions. Different multiple injection schedules have been evaluated for part-load operation, including pre and post injections. The proposed methodology, featuring detailed 3D chemistry modeling, was proven to be capable to properly assess pollutant formation, specifically to estimate NOx concentrations. Soot formation trend was also well-matched for most of the explored working points. The proposed procedure can therefore be considered as a suitable methodology to support the design and calibration of new Diesel engines, thanks to its ability to provide reliable engine performance and emissions estimations from the early-stage of a new engine development.

Environmental interventions and ecological adaptations harbor millions of valued substances and metabolites in plants which can be employed and commercialized for human benefits. Present study encompasses the untapped potential of pine needles of Indo-Himalayan region for the production of different metabolites and their pharmacological significance in terms of antioxidant and antimicrobial activity. Total phenolic and flavonoid content from the needles of ten pine species was quantified using three different solvent systems. Results revealed that out of 10 different selected Pinus species, Pinus taeda showed highest concentration of total phenolics, soluble-F phenolics and flavonoids content (approx.147.02 mg/g, 141.08 mg/g and 21.91mg/g respectively) as compared to other species. On the other hand P. greggii showed highest Bound-W phenolic content (approx.3.62mg/g). Among all the selected plant species, the needles of P.echinata exhibited the highest and P.thunbergii had the lowest ratio of total flavonoids to total phenolics. Most of these compounds were found to have effective antioxidant activities as well as antimicrobial activity, as estimated by oxygen radical absorbance capacity (ORAC) and disk diffusion test respectively.

The application of OpenAI's advanced artificial intelligence language model, ChatGPT, in education has garnered widespread attention from the academic community. The openness and intelligence features of ChatGPT demonstrate great potential and value in supporting students' learning, daily life, and communication. This study, grounded in the theoretical frameworks of Innovation Diffusion Theory (IDT) and the Technology Acceptance Model (TAM), conducted a systematic empirical analysis through a questionnaire survey of 677 university students who had used or were currently using ChatGPT. The results indicate that the six perceived attributes of innovation significantly influence university students' behavioral intention to use ChatGPT, while attitudes towards ChatGPT, perceived usefulness, and perceived ease of use indirectly influence students' behavioral intention to continue using ChatGPT. Based on the findings of this study, we propose an extended Technology Acceptance Model (TAM) that incorporates key elements of Innovation Diffusion Theory (IDT) to optimize the application of advanced technologies, such as ChatGPT, in education, thereby improving students' learning efficiency and behavioral performance. These findings not only provide important insights into the complex relationships between college students’ perceptions of ChatdGPT technology and predictors of behavioral intentions, but can also help relevant education departments, higher education institutions, and university teachers to effectively plan and evaluate the use of ChatGPT as a learning tool.

Microbes are the most prevalent and widely-distributed life form on planet Earth. They are also cognitive organisms with memory and superior problem-solving skills that use quantum phase transitions during their remarkably-effective gathering and dissemination of information. This narrative review explores the biological ramifications of human holobionts physically embodying the human microbiome and connecting to the Internet of Microbes (IOM) beyond our body. Within the review, we consider: 1) the ways in which our microbial co-partners exerted control over our ancestors and continue to influence our current human generation, 2) how they mold virtually every key aspect of our life and even remain with our body in death and 3) how inward-looking contemplative tools such as meditation and embodied cognition provide an ideal opportunity to connect to the microbial information super highway and tap the full range of human holobiont capacities.

Geriatric decisional capacity assessment is a complex medico-legal activity that evaluates normal subjects involved in specific civil matter like wealth transfer, access to treatment or voluntary hospitalization. Our objective was to evaluate how geriatric extrajudicial capacity exams impacted a general psychiatric unit over a decade. We also assessed the value of a surrogate biomarker (neutrophils to lymphocyte ratio) as a screening factor in the capacity assessment process. 72 cases were assessed in one psychiatric unit over a decade (2009-2018). As population was fast ageing, the total number of capacity exams per year doubled in time. None of the subjects had an active diagnostic of severe cognitive impairment or active psychiatric disease. The percentage of subjects receiving an “absence of capacity” conclusion remained constant over time (approx. 20% of all cases). 81% of the subjects within this subgroup had a clinical diagnostic of mild cognitive impairment compared to 46% in the “presence of capacity” subgroup (p&lt;0.001). The surrogate biomarker neutrophils to lymphocyte ratio was significantly higher in the “absence of capacity” subgroup, mainly related to a cognitive impairment diagnostic. The ratio has to be validated by larger studies before to be included in the capacity assessment process as an early screening tool.

Financial capacity instruments are psychometric tools designed to evaluate individual decisional capacity based on financial decisions. As tests are complex and need special conditions for administration and evaluation, it is difficult to use them in daily geriatric clinics. Our scoping review objective was to evaluate existing financial capacity instruments from the perspective of simplicity and portability. We evaluated one English speaking knowledge database (Medline) using a dedicated MeSH terminology. The review yielded one independent instrument, The Semi-Structured Clinical Interview for Financial Capacity, that can be easy adapted for every-day clinical use. It is simple to understand and perform and do not need trained personnel for administration. It can be finalized in 15 minutes. Initially validated on 261 subjects (with different forms of cognitive impairment), it showed good accuracy and precision mainly in subjects with cognitive impairment. The test is less apt to detect early or fluctuating cognitive impairment. Simplicity, the main advantage of the test, allows gamification fact that increases portability. Familiar images (coins, money) that are used for performing simple tasks does not need complex translation and adaptation. In form of a game, the test is suitable for serial administration, increasing the chance for early capacity reduction detection. Results reflect a physician judgement related to the subjects’ capacity to understand and execute simple financial instructions and not financial proficiency scores. The main limitation of our review is that we investigated only one, English speaking, knowledge database. The scoping strategy generated a financial capacity instrument that can be used in geriatric clinics for early diagnostic of decisional capacity reduction. Further studies are needed to evaluate the reliability and validity of the test in conditions of serial administration and in populations having various financial experience.

Concussion, also known as mild traumatic brain injury (mTBI), commonly causes transient neurocognitive symptoms, but in some cases, it causes cognitive impairment, including working memory (WM) deficit, which can be long-lasting and impede a patient’s return to work. The predictors of long-term cognitive outcomes following mTBI remain unclear because abnormality is often absent in structural imaging findings. The purpose of the study was to determine whether machine learning-based models using functional magnetic resonance imaging (fMRI) biomarkers and demographic or neuropsychological measures at baseline could effectively predict 1-year cognitive outcomes of concussion. We conducted a prospective, observational study of patients with mTBI who were compared with demographically-matched healthy controls enrolled between September 2015 to August 2020. Baseline assessments were collected within the first week of injury, and follow-ups were conducted at 6 weeks, 3 months, 6 months, and 1 year. Potential demographic, neuropsychological, and fMRI features were selected according to the significance of correlation with the estimated changes in WM ability. The support vector machine classifier was trained using these potential features and estimated changes in WM between the predefined time periods. Patients demonstrated significant cognitive recovery at the third month, followed by worsened performance after 6 months, which persisted until 1 year after concussion. Approximately half of the patients experienced prolonged cognitive impairment at 1-year follow up. Satisfactory predictions were achieved for patients whose WM function did not recover at 3 months (accuracy=87.5%), 6 months (accuracy=83.3%), 1 year (accuracy=83.3%), and performed worse at 1-year follow-up compared to baseline assessment (accuracy=83.3%). This study demonstrated the feasibility of personalized prediction for long-term postconcussive WM outcomes based on baseline fMRI and demographic features, opening a new avenue for early rehabilitation intervention in selected individuals with possible poor long-term cognitive outcomes.

Mild Cognitive Impairment (MCI) is a clinical syndrome characterized by a moderate decline in one or more cognitive functions with a preserved autonomy in daily life activities [1]. MCI exhibits cognitive, behavioral, psychological symptoms [2]. The executive functions (EFs) are a set of key functions for everyday life and physical and mental health; and allow adapting the behavior to external changes [3-5]. Higher-level executive functions develop from basic EFs (inhibition, working memory, attentional control, and cognitive flexibility). They are planning, reasoning, problem- solving, and fluid intelligence (Gf) [3]. This systematic review investigates the relationship between higher-level executive functions and healthy and pathological aging, assuming the role of executive functions deficits as a predictor of cognitive decline. The systematic review was conducted according to the PRISMA Statement [6-7]. A total of 73 studies were identified. The results indicate that 65.8% of the studies confirm significant EFs alterations in MCI (100% problem solving, 71.4% fluid intelligence, 56.8% planning, 50% reasoning). These results seem to highlight a strong prevalence of higher-level executive functions deficits in MCI elderly than in healthy elderly.

Background: Animal-assisted therapy has positive effects on cognitive function, depression, performance ability, and social functioning in elderly patients. The aim of this study was to evaluate the effects of rearing pet insects on the cognitive function of healthy elderly participants, with fMRI (functional magnetic resonance imaging) being used for this purpose. Methods: Community-dwelling elderly women (≥60 years) with normal cognitive function were enrolled during April 2015. They were randomized at a 1:1 ratio into two groups: insect-rearing and control (n=16) groups, with the insect-rearing group being further classified into two groups for analysis according to the subjects’ scores in the Wisconsin Card Sorting Test, WCST) at the first fMRI: insect-rearing group I with a relatively high score (n=13), and insect-rearing group II with a relatively low score (n=6). All subjects were educated on a healthy lifestyle for better cognitive function at every visit, and the insect-rearing groups received and reared crickets as pet insects. The fMRI was performed at baseline and after 8 weeks using the WCST as a stimulus. The WCST consisted of two variations, a high level baseline (HLB) and semi-WCST version. Results: There were no significant differences in the baseline characteristics among the three groups. There was a significant difference accuracy of the HLB–semi-WCST (p<0.05) in insect-rearing group II after 8 weeks from the baseline test. In the fMRI analysis involving the WCST reaction test, increased activation was observed in the right dorsal lateral prefrontal cortex and parietal cortex in insect-rearing group II when the semi-WCST, rather than the HLB, was performed. There were no significant differences in the other groups. Conclusion: The rearing of pet insects as an animal-assisted therapy is cost-effective, easy, and occupies little space. In this study, it showed positive effects on executive functions and performance improvement in elderly women. Further larger studies on the effects of pet insects on cognitive function are warranted.

Characterization of fungal spider pathogens lags far behind their insect counterparts. In addition, little to nothing is known concerning ecological reservoir and/or fungal entomopathogen community surrounding infection sites. Five infected spider cadavers were identified in the neo-tropical climate of north central Florida, US, from three of which viable cultures could be obtained. Multilocus molecular phylogenetic and morphological characteristics identified one isolate as a new species of Gibellula, named, G. floridensis, and the other two as isolates of Parengyodontium album. To examine the insect fungal community sampling of different habitats/trophic levels including soil, leaf litter, leaf, and twig from the surrounding area of the infection sites were collected and analyzed by ITS amplicon sequencing. These data revealed broad but differential distribution of entomopathogenic fungi between habitats and some variation between sites, with members of genera Metarhizium and Metacordyceps from Clavicipitaceae, Purpureocillium and Polycephalomyces from Ophiocordyceps, and Akanthomyces and Simplicillium from Cordycipitaceae, predominating. However, no sequences corresponding to Gibellula or Parengyodontium, even at the genera levels could be detected. Potential explanations for these findings are discussed. These data highlight novel discovery of fungal spider pathogens and open the broader question regarding the environmental distribution and ecological niches of such host specific pathogens.

The refractive index of seawater is one of the essential parameters in ocean observation, so it is necessary to achieve high-precision seawater refractive index measurements. A seawater refractive index measurement system based on position-sensitive detectors is an effective means to achieve high-precision measurement of seawater refractive index. However, in the actual seawater refractive index measurement process, the impact of the measurement error caused by the jitter signal obtained from the measurement on the measurement results cannot be ignored. In this paper, we theoretically analyse the causes of the long jitter signals during seawater refractive index measurement and quantify the influencing factors. Through the analysis, it can be seen that the angle between the two windows in the refractive index measurement area of seawater causes a great error on the measurement results, so the angle between the two windows should be controlled within 2.06° in order to effectively reduce the measurement error. At the same time, the factors affecting the measurement accuracy of the position-sensitive detector are analysed, and the factors leading to the reduction of the measurement accuracy of the position-sensitive detector are mainly the background light, the size of the photosensitive surface, and the change of the temperature of the working environment. For the above factors, we add a narrow-band filter with a bandwidth of 0.9nm in front of the photosensitive surface of the position-sensitive detector during the construction of the measurement system, so as to filter out stray light other than the signal light source. On the premise of ensuring the measuring range of the refractive index of seawater, a position-sensitive detector with a photosensitive surface size of 4 mm×4 mm was selected. In order to reduce the temperature variation of the working environment of the position-sensitive detector, the measurement system was partitioned. In order to validate the testing error range of the optimised test system, standard seawater samples under the same conditions were measured. It can be seen that the jitter signal of the measurement system has been reduced from 0.0022mm before the optimisation to 0.0011mm after the optimisation, and the deviation of the refractive index has been reduced by 1.09×10−8RIU. The experimental results show that the refractive index of seawater has been effectively reduced by adjusting the optical path and the structure of the seawater refractive index measurement system.

Aquatic environments are generally heterogeneous in space and time, and the marine organisms have their ways response to those environmental heterogeneities. Cutlassfish (Trichiurus spp.) once is one of the “Chinese Four Major Marine Fish Species” along the coast of northwest Pacific Ocean. There are some comments on the cutlassfish (T. spp.) name identification. In this study, three cutlassfish species, namely, the largehead hairtail (T. japonicas) in East China Sea (ECS), Chinese short-tailed hairtail (T. brevis), and South China Sea (SCS) cutlassfish (T. nanhaiensis), have been identified in the northwest Pacific Ocean. This work integrated 115 studies in cutlassfish population dynamics from 24 sites across 8 countries in the world. The biomass distribution of T. japonicas in the ECS and T. nanhaiensis in SCS, was found to be highly correlated with water temperature and salinity. Spatiotemporal heterogeneity of cutlassfish is found to correlate with both genetic and environmental characteristics in the northwest Pacific Ocean (e.g., density dependency, primary productivity and climate ocean oscillation). Closely related species coexisting in the same shelf region (e.g., T. japonicus and T. nanhaiensis in ESC) often differ in diet and microhabitat. The difference of skull phenology between T. nanhaiens and T. brevis is found to correlate with species separation and environmental heterogeneity. With the implications for the design of ecological research programs on cutlassfish, our study found that the effect of temporal changes outweighs (to some extent) the effect of spatial changes on cutlassfish in those shelf regions.

The emergence of the Internet of Things (loT) has led to remarkable advancements in various sectors such as urbanization, manufacturing, and healthcare, intending to enhance the quality of life and contribute to the world economy. However, by the conclusion of 2024, ti is projected that the global network of the Internet of Things (IoT) will encompass over 207billion interconnected devices. The immense data collected and exchanged are often stored in centralized servers, leading to vulnerabilities such as data breaches. Blockchain technology, originally developed for cryptocurrency transactions, provides a possible solution for these challenges with its decentralized, immutable, and encrypted features. This survey provides a comprehensive discussion regarding the fusion of Blockchain technology and the loT, covering architectural alignment, application, security, and limitations. The contributions of this survey include an overview of Blockchain technology and its secure applications, the integration of Blockchain into IoT , an examination of suitable methods for Blockchain integration,and a taxonomy or security and limitations of loT and blockchain integration.

This investigation aimed to explore the impact of acute and regular physical exercise on Brain-Derived Neurotrophic Factor (BDNF) levels in individuals with obesity. Using the Population, Intervention, Comparator, Outcome, and Study design (PICOS) approach, the inclusion criteria were defined as follows: i) population - individuals with overweight or obesity of any age or gender; ii) intervention - acute or chronic interventions involving aerobic or anaerobic methodologies; iii) comparator - for acute effect studies, pre- and post-evaluations served as comparators, while interventions included at least one experimental group or the inclusion of a control group; iv) outcome - BDNF variability concerning the applied methodology; v) study design - restricted to experimental studies exclusively. Conducted in August 2022, the searches were carried out on PubMed, Academic Search Complete, and Web of Science. The risk of bias was assessed using the Risk of Bias in Non-randomized Studies (RoBANS) tool. Out of 98 potentially relevant articles, 16 met the eligibility criteria, encompassing 23 trials. Substantial heterogeneity was observed for both acute (I2 = 80.4%) and long-term effects (I2 = 88.7%). Additionally, RoBANS analysis indicated a low risk of bias for the included studies. The study's findings revealed a significant increase in the concentration of circulating BDNF in individuals with obesity compared to the control group following acute exercise. However, such an effect was not evident in the context of long-term physical exercise, with a small effect size (ES = 0.49) recorded in the latter scenario. The observed significant increase in BDNF levels post-acute exercise suggests a potential acute response mechanism contributing to the intricate interplay between exercise and neurotrophic factors in this population. Nevertheless, the absence of a similar effect in the context of long-term physical exercise implies a potential adaptation or ceiling effect. These findings underscore the importance of considering both the duration and nature of exercise interventions when exploring the neurobiological responses associated with obesity and exercise. The study provides valuable insights for future research and clinical implications in understanding the nuanced relationship between exercise, neurotrophic factors, and obesity.

While traditional AC mechanical circuit breakers have been competent for protecting AC circuits, high penetration of DC power distribution technologies like DC microgrids (MGs) obligate better disruption performance features such as quick and reliable switch-ing speeds. However, a DC circuit breaker (DCCB) novel design is challenging due to the need to quickly break high currents within milliseconds, caused by the high fault current rise in DC grids compared to AC grids. In DC grids, the circuit breaker must provide zero current crossing and be designed for absorbing surges since the arc is not naturally extinguished by the system. Additionally, the DC breaker must mitigate the magnetic energy stored in the system inductance and withstand residual over-voltages after current interruption. These challenges require a fundamentally different topology for DCCBs, which are typically made using solid-state semiconductor technology, metal oxide varistors (MOV), and ultra-fast switches. This study aims to provide a comprehensive review on development, design, and performance description of DCCBs in parallel with a specific concentration on analysis of internal topology, energy absorption path and sub-circuits in Solid-State (SS)-based DCCBs. The research explores various novel designs that introduce different structures for energy dissipation solution. The classification of these designs is based on the fundamental principles of surge mitigation and a detailed analysis of the techniques employed in DCCBs. In addition, our framework offers an advantageous reference point for the future evolution of SS-circuit breakers in numerous developing power delivery systems.

Abstract: Since ancient times aging has also been regarded as a disease, and humankind has always strived to extend the natural lifespan. Analyzing the genes involved in aging and disease allows for finding important indicators and biological markers for pathologies and possible therapeutic targets. An example of the use of omics technologies is the research regarding aging and the rare and fatal premature aging syndrome progeria (Hutchinson-Gilford progeria syndrome, HGPS). In our study, we focused on the in silico analysis of differentially expressed genes (DEGs) in progeria and aging, using a publicly available RNA Seq dataset (GEO dataset GSE113957) and a variety of bioinformatics tools. We identified several genes that appear to be involved both in natural aging and progeria (KRT8, KRT18, ACKR4, CCL2, UCP2, ADAMTS15, ACTN4P1, WNT16, IGFBP2). Further analyzing these genes and the pathways involved confirmed their possible roles in aging, suggesting the need for further in vitro and in vivo research. The graphical abstract illustrates the analysis workflow we used and will introduce in the following as an example to demonstrate the power of omics and bioinformatics.

Sentiment analysis to characterize properties of Bitcoin prices and their forecasting is here developed thanks to the capability of the Fuzzy transform to capture stylized facts and mutual connections between time series having different nature. Six years of daily Bitcoin Prices and Google Trends are analyzed in order to establish new perspectives in the management of their dynamics.

The aquatic vegetation of the Neva Bay is characterized by high biodiversity and play an important role. In recent years, hydrotechnical works associated with transport and industrial construction have been carried out in the Gulf of Finland. As a result of industrialisation and active anthropogenic impact these areas are a place of hyperaccumulation of nutrients and pollutants. This paper presents results of the ecotoxicological state assessment of subaquatic soils and investigation of the development of macrophyte thicket ecosystems of the Neva Bay.

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.

Assessing carbon stocks in tropical forests is crucial for understanding their role in mitigating climate change. (1) Background: However, existing assessments have underestimated certain factors that can substantially influence carbon dynamics. (2) Methods: This study focuses on one such factor - buttress roots from a tropical forest. (3) Results: Our findings reveal that a significant proportion of trees (69.57%) had 3 to 5 buttress roots per tree. The total biomass of the buttress roots and the aboveground portion of the trees with buttress roots were calculated to be 8.5 tonnes/ha and 10.7 tonnes/ha respectively. The buttress root biomass accounted for 16.18% of the total tree biomass. It was observed that the presence of buttress roots during both the rainy and dry seasons increased the soil organic carbon content by an average of 20.8% in the upslope areas with buttress roots. During the rainy season, the presence of buttress roots did not affect the heavy fraction organic carbon in the soil layers in a statistically significant way. Regardless of the season, the soil respiration rate in the areas without buttress roots was higher than that in the areas with buttress roots. The presence of buttress roots had a positive effect on soil nutrient concentration in all seasons, creating a healthier environment for trees. Tree species with buttress roots had on average 20% higher organic carbon content during both the wet and dry seasons. (4) Conclusions: These findings highlight the importance of considering buttress roots in carbon stock assessments and forest management strategies. By integrating buttress roots into carbon accounting models, we can obtain more accurate estimates of carbon stock potential and develop more effective conservation and restoration strategies for tropical forests.

The review emphasizes the importance of the petroleum refining industry in Iraq, highlighting the environmental obstacles it presents. The industry's significant role in the country's economy necessitates a crucial evaluation and improvement of the environmental impact of oil refining in Iraq. The study scrutinizes the progression of crude oil refining techniques, from basic distillation to advanced technologies like vacuum distillation, thermal cracking, and catalytic cracking, all of which are associated with environmental damage. The refining processes produce hazardous gases such as carbon dioxide, carbon monoxide, sulfur oxides, and nitrogen oxides. Refineries also consume substantial amounts of water and discharge effluent, causing environmental issues. It highlights that significant solid waste is produced throughout the refining process, contributing to the environmental difficulties caused by the petroleum industry in Iraq. The paper proposes several approaches to enhancing the environmental performance of Iraq's petroleum refining processes through a comprehensive environmental impact assessment, focusing on identifying problematic areas, measuring environmental damage, and proposing solutions. It provides insights into the types of waste generated in Iraqi refineries, such as polluted hydrocarbon liquids, and highlights the environmental impact of leaks and spills from oil and byproducts, affecting groundwater and soil quality. The paper suggests reusing consumable auxiliary agents and mineral elements in other industrial fields to minimize waste generation, as well as employing advanced technologies like artificial intelligence and machine learning for efficient refining processes and reduced effluents. By offering suggestions to policymakers, industry stakeholders, and environmental regulators in Iraq, the study aims to inform sustainable practices and environmental management strategies within the petroleum refining sector, contributing to improved environmental outcomes and sustainable development in the industry.

Camouflage evaluation typically involves human visual search and detection experiments that are time-consuming and expensive. Hence, there is a need for models that compute camouflage effectiveness from digital imagery. Convolutional neural networks are a powerful tool for automatic object detection and recognition. We investigated whether such a network (YOLO) can also provide a measure of camouflage effectiveness that is related to human perception. To this end, human performance measures of camouflage effectiveness such as detection time and target conspicuity were obtained in observer experiments and compared with the performance of the (standard, i.e. pre-trained) YOLO-V4-tiny algorithm. YOLO provides the probability that a detected object is correctly classified, and this is adopted as our measure of camouflage effectiveness. We compared the YOLO-predicted classification probability for a person in camouflage clothing moving through rural and urban scenes to human detection performance. Overall, camouflage effectiveness predicted by YOLO correlates with human observer performance. At close distances, YOLO’s classification performance appears sensitive to high-contrast shape-breaking elements of a camouflage pattern. This suggests that YOLO may be adapted to assess camouflage effectiveness for a wide range of applications, such as evaluating or optimizing one’s signature and predicting optimal hiding locations in a given environment. Further research is required to fully establish YOLO’s limitations and applicability for this purpose.

Agriculture is the main economic activity of Mozambique and there is lack of information about the quality of agricultural soils. In this paper, five soils from the Manica and Sussudenga districts (Manica province) were sampled in the years 2021/2022 and 2022/2023 (before and after the rainy seasons), were subjected to an agronomical and environmental chemical analysis to assess its quality, either from the fertility and environmental contamination point of view. Standard analytical methodologies from external certified laboratories and local X-ray fluorescence measurements were used. All the studied soils are acidic (pH ranging from 4.5 and 5.4), have no salinity problems (conductivity ranging from 4.2 to 11.8 mS/m), have low amount of soil organic matter (0.90% to 1.81%), and soils from the Sussudenga district have a very low cation exchange capacity (CEC) (average of 3.33 cmolc/kg), while those from Manica district ranges from very low to average CEC (3.59 to 13.11 cmolc/kg). Also, Sussudenga soils have a phosphorous deficiency (values ranging from &lt;20 to 38.5 mg/kg) and there are deficiencies and/or excesses of some macro and micronutrients in all soil samples. Manica soils are contaminated, apparently from geogenic origin, with Cr (280 to 1400 mg/kg), Co (80 mg/kg), Ni (78 to 680 mg/kg) and V (86 mg/kg). Agricultural soils monitoring must be fostered in Mozambique in order to improve food quality and quantity to assure economic and environmental sustainability.

Background and objectives: Effective management for chronic diseases, hereditary and rare diseases and Thalassaemia in particular constitutes an important indicator for the quality of healthcare systems. We aimed at assessing healthcare services in different countries by using publicly available health indicators and by surveying Thalassaemia patients and their caregivers. Materials and Methods: We reviewed official worldwide databases from the WHO, World Bank, and scientific resources and also used a structured patient tailored self-completed questionnaire to survey Thalassaemia patients and their caregivers in 2023. Results: A total of 2,082 participants were surveyed (mean age 27 years, males 42%). About 1 in 4 respondents had less than high school education, while 24% had a bachelor degree. About a third of respondents were married and had either full- or part-time employment. The vast majority (~80%) had initiated transfusion therapy between 1 – 4 years of age. Only 42% reported no delays in receiving blood transfusion, while 47% reported occasional delays and 8% serious delays. About half of patients reported being very satisfied (11%) or satisfied (38%) with the quality of provided services, while 1 in 3 patients reported being unsatisfied or very unsatisfied, and their access to treatment was difficult or very difficult due to traveling expenses and high cost of treatment. Conclusion: Important improvements in the care of Thalassaemia patients have been documented during the past decades. Nevertheless, our recent survey reveals many unmet needs where additional focus is required through national healthcare systems in order to address them effectively and achieve satisfactory patient outcomes.

In the northern Patagonian region of Argentina, there exist some of the largest bentonite deposits. Four bentonite samples (B1, B2, B3, and B4) from two deposits were thoroughly characterized and evaluated as potential adsorbents of anthocyanins extracted from red cabbage. Anthocyanins (ACy) are natural colourants obtained from fruits and plants and have shown excellent antioxidant properties that have promising applications in health. The adsorption of ACy onto bentonites enhances their stability relative to that observed in aqueous solutions. Material characterization showed that three of the samples are sodium bentonites (Na-bentonites: B2, B3, and B4), while the fourth exhibits a large quantity of magnesium and calcium in its interlayer, classifying it as a Mg-Ca-Na-bentonite (B1). Na-bentonites demonstrated higher ACy adsorption capacities, occurring through cation exchange while Mg-Ca-Na-bentonite adsorption occurs by another kind of interaction and a cooperative adsorption mechanism, resulting in the lowest ACy adsorption. The highest adsorption capacity was for B3, characterized by the highest smectite content, cation exchange capacity, and proportion of monovalent cations in its interlayer. Under the conditions studied, sodium smectites proved to be capable of retaining red cabbage ACy, there by introducing a novel avenue for potential applications of regional materials with potential implications for health-related uses.

The concrete sector is known for its significant contribution to the CO2 emissions. There are two main contributing factors for this situation: the large amount of concrete consumed per year on the planet and the high CO2 released from Portland cement manufacture, the key binding agent in concrete. To face the consequent sustainability issues, diverse strategies have been explored on the carbon capture and storage potential of cementitious materials. This paper addresses the potential of storing CO2 in concrete during the curing stage, applied to the precast Portuguese industry. To this purpose, it was assumed that CO2 will become a waste that will require an outlet in the future, considering that carbon capture will become mandatory in many industries. This work concluded that the net benefit in terms of carbon retention is positive for the process of storing carbon in concrete during the curing stage. More specifically, it was demonstrated that the additional emissions from the introduction of this new operation are only 10% of the stored amount, returning a storage potential of 76 000 tonnes of CO2 yearly. Moreover, the overall net reduction in the concrete life cycle averages 9.4% and 8.8% for precast elements and only non-structural elements, respectively. When a low cement dosage strategy is coupled with carbonation curing technology, the overall carbon net reduction is estimated to be 45%.

For years, effort has been devoted to establishing an effective bull breeding soundness evaluation procedure; usual research on the subject is based on BBSE (Bull Breeding Soundness Examination) methodologies, which have significant limitations in terms of their evaluation procedure, such as high cost, time-consuming and administratively difficult. This research focuses on the creation of a prediction model to supplement and/or improve the BBSE approach, through the study of two algorithms, Clustering and Artificial Neural Network (ANN), to find the optimum Machine Learning (ML) approach for our application, with an emphasis on data categorization accuracy. The tool is designed to assist veterinary medicine and farmers in identifying key factors and increasing certainty in their decision-making during the selection of bulls for breeding purposes, providing data from a limited number of factors generated from a deep pairing study of bulls. Zebu Bulls, European Bulls, and Crossbred Bulls were the general groupings. The data utilized in the model's creation (N =359) considers five variables that influence improvement decisions. This approach enhances decision-making by 12%. ANN obtained an accuracy of 90%; Precision was 97% for satisfying, 92% for unsatisfying, and 85% for Bad.

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

Growing population, industrialization, and power requirements are adversely affecting the environment by increased greenhouse gases, resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led the nations to promote clean and self-renewable sources of energy to address the environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting offshore wind power resources assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above means sea level (AMSL) and temperature and pressure data near surface is used. The data is obtained from ERA5 (fifth generation reanalysis for the global climate weather) at chosen six (L1-L6) offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL while temperature and pressure are available near water surface level. At L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL; respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at L1 and L3 sites and generally lower values of wind variability indices are indicative of favourable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy, for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at L5 and L1 sites corresponding to wind turbines WT1 and WT4. Based on the analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifiers indices introduced, will help decision-makers in deciding the potential windy sites with more confidence.

Urban parks play a pivotal role in fostering the development of sustainable and smart cities, encompassing multifaceted dimensions of environmental, social, and economic significance. To effectively manage these urban parks, it is imperative to undertake an in-depth investigation of their environmental, social, and economic conditions, as well as their level of sustainability. However, there is currently a lack of readily applicable methodologies that comprehensively measure these benefits and provide a sustainability rating for urban parks. In this study, we propose a valuable tool that employs effective and affordable measures for the daily management of these green spaces. Our methodology is rooted in the three pillars of sustainability: environmental, social, and economic. Within these pillars, we have defined 19 indicators and 50 criteria, enabling a comprehensive assessment of park sustainability. This methodology is developed through the characterization and systematic documentation of the park’s day-to-day operations. To validate our methodology, we present a case study of Cárcamos Park, situated in the state of Guanajuato in Mexico, utilizing accurate operational data collected from January to December 2020. Through this real-life scenario, we demonstrate the high applicability and effectiveness of our methodology. The sustainability assessment of Cárcamos Park reveals a sustainability level of 57%, placing it within the medium sustainability range. Importantly, our methodology can also be incorporated during the design phase of new urban green spaces, offering flexibility and ease of application tailored to the unique characteristics of each park. Park managers can use our procedure and apply it to any park, evaluate their sustainability status and detect areas of opportunity. Our approach provides a comprehensive and practical tool for measuring and improving the sustainability of urban parks. Its simplicity and applicability make it accessible to anyone interested in creating a greener and more sustainable urban environment.

Biomass-derived carbon dots (CDs) are gaining much interest in recent times as it is a sustainable option with abundant availability, low cost, and tunable luminescence. Herein, we report a simple green synthesis method to produce highly fluorescent CDs from Eucalyptus globulus leaves using the one-pot hydrothermal approach. The fabricated CDs exhibit strong blue fluorescence with an excitation and emission maxima of 340 nm and 442 nm respectively. The highest quantum yield (QY) obtained was 60.7%. Due to its promising optical properties and biocompatibility, CDs can be a potential candidate for biosensing applications. Moreover, we employed a life cycle assessment (LCA) cradle-to-gate approach to study the environmental impacts of the synthesis strategy used for the fabrication of CDs. The results point out that citric acid is a main hotspot in CDs synthesis, regarding environmental impacts in most categories. This justifies the introduction of biomass, which reduces the amount of citric acid, thus leading to a more sustainable synthesis strategy for fabricating CDs.

A micro energy harvesting device proposed in the literature, is numerically studied. It consists of two bluff bodies in a micro-channel and a flexible diaphragm at its upper wall. Vortex shedding behind bodies induces pressure fluctuation causing vibration of the diaphragm that converts me-chanical energy to electrical by means of a piezoelectric membrane. Research on enhancing vortex shedding is justified due to the low power output of the device. Amplitude and frequency of un-steady pressure fluctuation on the diaphragm center are numerically predicted. Vortex shedding severity is mainly assessed in terms of pressure amplitude. The CFD model set-up is described in detail and appropriate metrics to assess energy harvesting potential are defined. Several cases are simulated to study the effect of inlet Reynolds number and channel blockage ratio on the prospec-tive performance of the device. Furthermore, the critical blockage ratio leading to vortex shedding suppression is sought. Higher inlet velocity for a constant blockage ratio is found to enhance vor-tex shedding and pressure drop. Great blockage ratio values, but lower than the critical one, seem to provide great pressure amplitudes in the expense of moderate pressure drop. There is evidence that the field is fruitful for research and relevant directions are provided.

In this paper, particular attention is paid to an advanced variant of the plug-in hybrid engine, known as PHEV, which combines two functionalities: the vehicle's internal combustion engine (ICEV) and the electric engine (BEV). The paper also presents the assumptions of the DEVS model, which allows for the estimation of vehicle’s energy consumption. The study described herein also presents the influence of factors such as ambient temperature and constant speed on the PHEV’s energy consumption. It has been shown that the vehicle’s range estimated based on its electronic control module (ECU) is about 20% shorter per annum on average for its year-round operation in every-day driving conditions. When analyzing the energy consumption based on the vehicle’s unit energy consumption model, attention was paid to values that are strongly correlated with the traffic volume and weather conditions affecting the moving vehicle. In addition, the authors emphasized that the estimated total energy consumption of an electric (BEV) or hybrid (PHEV) vehicle, relative to the normative values arising from the type approval test cycle, deviate from the actual values arising from real driving conditions and often vary substantially. In extreme cases, the actual range of a hybrid vehicle is 75% shorter.

Efficient management of basal cell carcinoma (BCC) requires reliable assessments of both tumors and post-treatment scars. We aimed to estimate image similarity metrics that account for BCC's perceptual color and texture deviation from perilesional skin. 176 clinical photographs of BCC were assessed by six physicians using a visual deviation scale. Internal consistency and inter-rater agreement were estimated using Cronbach's α, weighted Gwet's AC2, and quadratic Cohen's Kappa. The mean visual scores were used to validate a range of similarity metrics employing different color spaces, distances, and image embeddings from pre-trained VGG16 neural network. The calculated similarities were transformed into discrete values using ordinal logistic regression models. The Bray-Curtis distance in the YIQ color model and rectified embeddings from the 'fc6' layer minimized the mean squared error and demonstrated strong performance in representing perceptual similarities. Box plot analysis and Wilcoxon rank-sum test were used to visualize and compare the levels of agreement, conducted on a random validation round between the two groups: ‘Human-System’ and ‘Human-Human’. The proposed metrics were comparable in terms of internal consistency and agreement with human raters. The findings suggest that the proposed metrics offer a robust, and cost-effective approach to monitoring BCC treatment outcomes in clinical settings.

The influence of numerous factors determines and changes the daily behavior of consumers. This paper aims to estimate and rank the weight of cultural, social, personal, and psychological factors that change the buying habits of individuals. The research was conducted on a sample of 559 re-spondents. Data from the survey were used to create a hierarchical model structure. The Analytic Hierarchy Process (AHP) as a decision-making method was used in the analysis to estimate and rank the factors that influence consumer habits. An analysis of results showed that the personal and psychological factors have the principal influence on consumer habits. Personal budget, as the dominant criterion in a group of set criteria, contributed to the fact that the personal factors have the dominant influence on consumer habits. The work showed that the choice of the method used is relevant to the results and that the analysis of the impact on consumer habits can be expanded by including several factors.

Stray current is a relevant phenomenon in particular for DC electrified transportation systems, affecting the track and infrastructure within the right of way and other structures and installations nearby. It worsens with time and the level of protection depend on timely maintenance, besides correct design choices. The assessment of track insulation is the starting point for both stray current monitoring systems and at commissioning or upon major changes. Standardized methods (ref. EN 50122-2, or IEC 62128-2) are almost unchanged in the last 20 years, but suffer from accuracy issues and variability due to parameters and conditions not under operator’s control. A critical discussion and analysis of the sources of variability and practical constraints is proposed, followed by the evaluation of uncertainty, with the objective not only to assess the accuracy of provided results, but to foster research on innovative, more flexible and accurate, methods.

There has been an increase in the inefficiencies of urban infrastructure services in Indian cities as a result of rapid and unplanned urbanization (UNDP, 2017). Indian cities have grown multidimensional as a result of massive industrializa-tion and technological spread backed by globalization impacting the early 2000. It has transformed the city fabric and the associated challenges. Therefore, an Urban Climate Vulnerability Assessment (UCVA) is needed to identify, target and recognize climate vulnerable urban cities, sectors, or populations. The UCVA framework consists of seven broad thematic indicators — physical, hazard, social, demographic, financial provisioning, infrastructure and admin-istration vulnerabilities, and their sub indicators to represent the climate vul-nerability of Indian cities. This assessment is for seven Indian cities namely Delhi, Mumbai, Chennai, Bengaluru, Srinagar, Shillong, and Ahmedabad which were selected based on their geographical location, population, ecosystem types and hazards/ hazard trends to understand and assess the respective vul-nerabilities. The Assessment is done through a comprehensive approach using a robust and predictive qualitative framework. It helps in determining respec-tive risks and in improving community resilience to the climate hazards by in-tegrated planning and improved preparedness. UCVA can support as a deci-sion support mechanism for devising suitable mitigation and adaptation strategies for building urban climate resilience.

The vocal folds are found in the larynx and their vibrations produce the voice. Little is known about morphology and the size of cattle larynx. The aim of the study was to quantify the shape asymmetry of the vocal folds in calves obtained post-mortem using a geometric morphometric approach. A sample of 14 larynges from calves (in an age range 335 to 625 days) belonging to “Bruna dels Pirineus” breed and its F1 crosses was obtained in an abattoir during the first semester of 2021. Landmark sets were superimposed on images of fixed transverse sections of larynges. Using geometric morphometric techniques, we analysed the presence of asymmetries. Results demonstrate differences between right and left vocal fold sides as directional asymmetry, at least in fixed structures. Our findings provide a foundation for quantifying the possible contribution of vocal organ asymmetry among cattle. This study can be considered the first to detect vocal fold asymmetries in cattle. Studies with a larger sample size are needed to validate the information in large populations. One limitation is that the present study does not have samples from adult animals, so it would be interesting to know if the results are similar among them.

This paper presents a methodology for indirectly estimating the scale of seabird bycatch using existing data, eliminating the need for regular monitoring. The study focuses on five species of ducks that winter in the Polish waters of the Baltic Sea and are highly susceptible to bycatch: Long-tailed Duck, Velvet Scoter, Common Scoter, Greater Scaup, and Tufted Duck. The evaluation units used are divided into the Bornholm and Gotland Groups within the Polish Exclusive Economic Zone (PEEZ). The analysis acknowledges the lack of data for certain areas known to have high concentrations of diving birds and fishing activity. The population sizes of waterbirds were assessed using ship-based surveys and a distance sampling approach. Fishing effort data from the winter seasons between 2015/2016 and 2019/2020 were analyzed. Bycatch rates were estimated based on surveys conducted in previous seasons, and threshold values for bycatch were established using the concept of "small numbers" defined in EU directives. The results show that within the Gotland subdivision of the PEEZ, the estimated average abundance of all diving waterbirds was 207,114 individuals, with an average bycatch of 7,921 birds (3.8% of the total). The Velvet Scoter was the most abundant species, followed by the Long-tailed Duck. Benthivorous ducks constituted the majority of the bird population in the area. In the Bornholm subdivision, the estimated average abundance of diving waterbirds was 600,845 individuals, with an average bycatch of 5,056 birds (0.8% of the total). The Long-tailed Duck was the most numerous species, followed by the Velvet Scoter. Benthivorous ducks also dominated in this area. The findings highlight the need for effective management and conservation measures to address the high mortality of seabirds due to bycatch. The methodology presented in this study offers a valuable approach for estimating bycatch scale and can support efforts to minimize the impact on seabird populations in the Baltic Sea.

Abstract: Image aesthetic assessment (IAA) with neural attention has made significant progress due to its effectiveness in object recognition. Current studies have shown that the features learned by convolutional neural networks (CNN) at different learning stages indicate meaningful information. The shallow feature contains the low-level information of images and the deep feature perceives the image semantics and themes. Inspired by this, we propose a visual enhancement network with feature fusion (FF-VEN). It consists of two sub-modules, the visual enhancement module (VE module) and the shallow and deep feature fusion module (SDFF module). The former uses an adaptive filter in the spatial domain to simulate human eyes according to the region of interest (ROI) extracted by neural feedback. The latter not only takes out the shallow feature and the deep feature by transverse connection, but also uses a feature fusion unit (FFU) to fuse the pooled features together with the aim of information contribution maximization. Experiments on standard AVA dataset and Photo.net dataset show the effectiveness of FF-VEN.

Activated Corrosion Products (ACPs) formation and deposition pose a critical safety issue for nuclear fusion reactors. The working fluid transports the ACPs towards regions accessible to worker personnel. Predicting ACPs formation deposition and transport is fundamental for source term identification, reduction of radiation exposure assessment, maintenance plan definition, design optimization, and waste management. The code OSCAR-Fusion has been developed by the CEA (France) to evaluate the ACPs generation and transport in closed water-cooled loops for fusion application. This work aims at assessing the impact of water chemistry on the transport, precipitation, and deposition of corrosion products for the EU-DEMO divertor Plasma Facing Unit Primary Heat Transfer System. Sensitivity analyses and uncertainty quantification are needed due to the multi-physics phenomena involved in ACPs formation and transport. The OSCAR-Fusion/RAVEN code coupling developed by the Sapienza University of Rome and ENEA has been used. This work presents the perturbation results of different parameters chosen for a closed water-cooled loop considering a continuous scenario of 1888 days. The aim of this work is to assess the variation of build-up of ACPs, perturbing the alkalizing agent concentration into the coolant and the corrosion and release rates of different materials.

Motivation: DeGAUSS is a software application for geocoding and geomarker assessment that circumvents barriers related to cost and reproducibility presented by conventional approaches. Most importantly, DeGAUSS safeguards protected health information (PHI), such as a mailing address. Implementation: DeGAUSS is implemented as a family of software containers with R code, geospatial software libraries, and geographic data. The containers are available in online repositories and accessed by users through the command line. It is free and open-source software under continuous development. General Features: DeGAUSS operates locally, ensuring that PHI is not passed over the internet, and reproducibly, which allows for easier operation in multi-site studies. In addition to geocoding, software containers are available for many geomarkers commonly utilized in epidemiological studies, including data related to the census, meteorology, land cover, greenspace, roadways, access to care, and air pollution. Availability: This software is freely available via “GitHub Container Registry” at https://degauss.org/.

Worldwide, diarrhoea in children under-five years of age is the second leading cause of death. Despite having high morbidity and mortality, diarrhoeal diseases can be averted by simple and cost-effective interventions. The Integrated Management of Childhood Illness (IMCI) has proposed the use of Oral Rehydration Salt (ORS) and zinc together with adequate food and fluid intake for the management of acute non-dysenteric watery diarrhoea in children. In the past, few studies examined the determinants of adherence to diarrhoea case management. Therefore, this study measured the determinants of therapeutic and dietary adherence to diarrhoea case management using the third and fourth wave of Pakistan Demographics & Health Surveys (PDHS) datasets. Data from 4,068 children between 0 to 59.9 months with positive history of diarrhoea were included, while data on children with dysentery, severe dehydration, and co-morbid condition was excluded. This study reported therapeutic adherence in less than 10% of children in Pakistan, while dietary adherence was reported in 39.2% of children (37.7% in 2012-2013 ~ 40.7% in 2017-2018). A significant improvement in therapeutic (0.8% in 2012-2013 ~ 8.1% in 2017-2018) and dietary adherence (37.7% in 2012-2013 ~ 40.7% in 2017-2018) was reported in the 2017-2018 survey, compared to the 2012-2013 survey. In general, children over the age of one year (compared to children <1 year) and of the richer/richest socioeconomic class (compared to poorest/poorer socioeconomic class) have showed higher therapeutic and dietary adherence. Therapeutic and dietary adherence among diarrhoeal children can be improved by increasing the awareness and accessibility of ORS, zinc, and essential foods.

The article presents the results of a morpho-physiological assessment of rice samples by the strength of growth, as well as an assessment of the degree of development of the conducting system of the flag leaves of rice plants. The resistance of varieties to flooding is very relevant in the fight against weeds due to the deep layer of water that weeds cannot overcome. Currently, there are no zoned varieties in Russia that would meet these requirements. Therefore, the problem of creating such rice varieties is urgent, as it will reduce production costs, reduce grain losses during harvesting, improve the quality of the products obtained, and also reduce the pesticide load on the ecosystem. As a result of research, a number of studied samples revealed the potential to quickly lengthen the first leaves, overcome a large layer of water and accumulate vegetative mass. As a result of the evaluation of the conducting system of the flag leaf of rice plants, it was found that in plants with the flood resistance gene Sub1A, which stops growth under water, the conductive beams were smaller in comparison with other fast-growing samples with the AG, Sk genes. Consequently, fast-growing samples have bigger sizes of the conducting system as a resistance mechanism.

Sea surface salinity (SSS) is one of the Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS). Acquiring high-quality SSS datasets with high spatial-temporal resolution is cruicial for research on the hydrological cycle and earth climate. This study assessed the quality of SSS data provided by four high-resolution ocean reanalysis products, including the Hybrid Coordinate Ocean Model (HYCOM) 1/12° global reanalysis, the The Copernicus Global 1/12° Oceanic and Sea Ice GLORYS12 Reanal-ysis, the Simple Ocean Data Assimilation (SODA) reanalysis, the ECMWF Oceanic Reanalysis System 5 (ORAS5) product and the Estimating the Circulation and Climate of the Ocean Phase II (ECCO2) reanalysis. Regional comparison in the Mediterranean Sea shows that reanalysis largely depicts the accurate spatial SSS structure away from river mouths and coastal areas but slightly underestimates the mean SSS values. Better SSS reanalysis performance is found in the Levantine Sea while larger SSS uncertainties are found in the Adriatic Sea and the Aegean Sea. The global comparison with CMEMS level-4 (L4) SSS show generally con-sistent large-scale structures. The mean ΔSSS between monthly gridded reanalysis data and in situ analyzed data is -0.1 PSU in the open seas between 40°S and 40°N with the mean Root Mean Square Deviation (RMSD) generally smaller than 0.3 PSU and the majority of correlation coefficients higher than 0.5. Comparison with collocated buoy salinity shows that reanalysis products well captures the SSS variations at the locations of tropical moored buoy arrays at weekly scale. Among all the four products, the data quality of HYCOM re-analysis SSS is highest in marginal sea, GLORYS12 has the best performance in the global ocean especially in tropical regions. Comparatively, ECCO2 has the overall worst performance to reproduce SSS states and variations by showing the largest discrepancies with CMEMS L4 SSS.

Swimming pools are examples of water-intensive facilities, where solutions for reducing economic and environmental costs are increasingly frequently searched. One of the solutions is the recovery of water from wastewater, including from washings obtained through the process of rinsing filter bed. The study objective was the qualitative and quantitative assessment of post-coagulation sludges, the main pollutant found in the washings. During the analyses, assessment of the sedimentation capabilities of the sludges was performed (gravitationally), particle size distribution was assessed (particle size distribution analyzer) and assessment of phytotoxicity with the use of plant indicators in short-term tests was performed (Lemna minor, Lepidium sativum, Sinapis alba, Raphanus sativus). The samples were collected from two independent circulations, which differed in terms of capacity and type of coagulant used. The tested post-coagulation sludges were characterized by high content of total suspended solids: in samples from Circulation 1 from 251 to 128 mg/l, in Circulation 2 from 489 to 228 mg/l. However, the sedimentation processes enabled significant separation of sludges. The hydrolyzed coagulant contributed to the improvement of sedimentation capabilities of sludges. Despite the fact that in many samples low sludge concentrations favored stimulation of plant growth, the post-coagulation sludges can constitute a hazard to plant growth, particularly in the long-term perspective.

The WHO European Region defined the role of a new central professional for primary care, the Family and Community Nurse (FCN). The introduction of FCN in the framework of health policies highlight a key role of nurses in addressing the families’ and communities’ needs. A scoping review was conducted in order to identify and describe the available tools which has been adopted for the assessment of the community health needs by FNC. A comprehensive literature review on Embase, Cochrane Library, PubMed, CINAHL, Scopus and PsycInfo databases was conducted including all studies up to May 2021. A total of 1563 studies were identified and 36 of them were included. The literature review had made possible to identify studies employing twelve different community assessment's tools or modalities. Referring the WHO framework proposed in 2001 some common themes have been identified with an uneven distribution, as profiling the population, deciding on priorities for action and public healthcare programmes, implementing the planned activities, evaluation of health outcomes, multidisciplinary activity, flexibility and involving the community. To the best of our knowledge, this work is the first attempt to provide an overview of community assessment tools, keeping the guidance provided by the WHO as a reference.

Growing interest surrounds the assessment of perivascular spaces (PVS) on magnetic resonance imaging (MRI) and their validation as a clinical biomarker of adverse brain health. Nonetheless, the limits of validity of current state-of-the-art segmentation methods are still unclear. Here, we propose an open-source three-dimensional computational framework comprising 3D digital reference objects and evaluate the performance of three PVS filtering methods under various spatiotemporal imaging considerations (including sampling, motion artefacts, and Rician noise). Specifically, we study the performance of the Frangi, Jerman and RORPO filters in enhancing PVS-like structures to facilitate segmentation. Our findings were three-fold. First, as long as voxels are isotropic, RORPO outperforms the other two filters, regardless of imaging quality. Unlike the Frangi and Jerman filters, RORPO’s performance does not deteriorate as PVS volume increases. Second, the performance of all “vesselness” filters is heavily influenced by imaging quality, with sampling and motion artefacts being the most damaging for these types of analyses. Third, none of the filters can distinguish PVS from other hyperintense structures (e.g. white matter hyperintensities, stroke lesions, or lacunes) effectively, the area under precision-recall curve dropped substantially (Frangi: from 94.21 [IQR 91.60, 96.16] to 43.76 [IQR 25.19, 63.38]; Jerman: from 94.51 [IQR 91.90, 95.37] to 58.00 [IQR 35.68, 64.87]; RORPO: from 98.72 [IQR 95.37, 98.96] to 71.87 [IQR 57.21, 76.63] without and with other hyperintense structures, respectively). The use of our computational model enables comparing segmentation methods and identifying their advantages and disadvantages, thereby providing means for testing and optimising pipelines for ongoing and future studies.

Consumer rhythm-monitoring devices, such as the Apple Watch, are becoming more readily available. Irregular pulses can be detected using an optical sensor built into the wearable device. The Apple Watch (Apple Inc., Cupertino, CA, USA) is a class II medical device with pulse rate and electrocardiography (ECG) monitoring capabilities. Here we report a case in which an arrhythmia that was conventionally perceived but undiagnosed was identified as atrial fibrillation by self-acquisition of ECG data using an Apple Watch.

Digitalization is widely recognized as a transformative power for sustainable development. Careful alignment of progress made by digitalization with the globally acknowledged Sustainable Development Goals (SDGs) is crucial for inclusive and holistic sustainable development in the digital era. However, limited reference has been made in SDGs about harnessing the opportunities offered by digitalization capabilities. Moreover, research on inhibiting or enabling effects of digitalization considering its multi-faceted interlinkages with the SDGs and their targets is fragmented. There are only limited instances in the literature examining and categorizing the impact of digitalization on sustainable development. To overcome this gap, this paper introduces a new Digitainability Assessment Framework (DAF) for context-aware practical assessment of the impact of the digitalization intervention on the SDGs. The DAF facilitates in-depth assessment of the many diverse technical, social, ethical, and environmental aspects of a digital intervention by systematically examining its impact on the SDG indicators. Our approach draws on and adapts concepts of the Theory of Change (ToC). The DAF should support developers, users as well policymakers by providing a 360-degree perspective on the impact of digital services or products, as well as providing hints for its possible improvement. We demonstrate the application of the DAF with the three test case studies illustrating how it supports in providing a holistic view of the relation between digitalization and SDGs.

Yemen is a water-scarce country with inadequate fresh water and considerable groundwater depletion, as well as a lack of adequate surface water. The study region is considered an arid region, and there is insufficient water to meet the needs of the region's yearly population growth rate of 4 %. This study aims to assess the water resources in the Sana'a region and to identify the current water situation and forecast for the future. Rainfall changes spatial and temporal in very few quantities and an annual average of 267 mm. Water harvesting facilities are entirely filled by 75% of the total water facilities in the rainy seasons. The groundwater level in Sana’a Basin decreases about 6-8 meters annually due to the increase in the number of wells, the abundance of abstraction, and the lack of recharge. The amount of abstraction exceeds 400% of the recharge in the Sana'a basin. The water per capita is 70 - 85 m³ annually. It is an abstraction from the aquifers by private wells. The crop cultivated area decreased from 184217 hectares in 2007 to 122583 hectares in 2018 due to lack of water. The sewage treatment plant treats 18.25 Mm³ annually, with less than 70 % efficiency. The water deficit is about 500 to 723 Mm³ annually; it is an abstraction from the aquifers by private wells. The current water situation in the Sana'a region is catastrophic, and the planning and management must ensure a water balance in the future.

The current study was planned to simulate runoff due to the snowmelt in the Lidder River catchment of Himalayan region under climate change scenarios. A basic degree-day model, Snowmelt-Runoff Model (SRM) was utilized to assess the hydrological consequences of change in climate. The SRM model performance during the calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found as 11.7, -10.1, -11.8, 1.96, and 8.6 during 2009-2014, respectively, while the R2 is 0.96, 0.92, 0.95, 0.90, and 0.94, respectively. The Dv and R2 values indicating that the simulated snowmelt runoff has a close agreement with the observed value. The simulated findings were also assessed under the different scenarios of climate change: a) increases in precipitation by +20 %, b) temperature rise of +2 °C, and c) temperature rise of +2 °C with a 20 % increase in snow cover. In scenario "b", the simulated results showed that runoff increased by 53 % in summer (April–September). In contrast, the projected increased discharge for scenarios "a" and "c" was 37 % and 67 %, respectively. In high elevation data-scarce mountain environments, the SRM is efficient in forecasting future water supplies due to the snowmelt runoff.

We assessed how close human perceptions of landscape modification matched a multivariate index based on remotely sensed data of the same locations. Using a Human Footprint (HF) map of the continental U.S. (scaled 0-100), we created three series of aerial images, each with ten images distributed evenly across the 10 deciles of HF score. Using a web-based survey, 290 members of the global public ranked the images in one series based on their perception of the degree of human modification. Respondents also reported age, sex, and country. The degree of correspondence between rankings by respondents and by HF score was high, an average of 1.29 units of difference out of a maximum possible of 5.0. Differences among respondents were not explained by age, sex, or general geographic location. These results suggest that human perception of relative landscape modification conforms closely with the relative ranking made by a multivariate, analytical index.

Animal welfare is not only an ethically important consideration in good animal husbandry, but can also have a significant effect on an animal’s productivity. The aim of this paper is to show that a reduction in animal welfare, in the form of increased stress, can be identified in pigs from frontal images of the animals. We train a Convolutional Neural Network (CNN) using a leave-one-out design and show that it is able to discriminate between stressed and unstressed pigs with an accuracy of >90% in unseen animals. Grad-CAM is used to identify the animal regions used, and these support those used in manual assessments such as the Pig Grimace Scale. This innovative work paves the way for further work examining both positive and negative welfare states with a view to the development of an automated system that can be used in precision livestock farming to improve animal welfare.

The oil and gas sector has recognised structural integrity assessment of ageing platform for prospective life extension as a rising concern, particularly in encountering the randomness of the harsh ocean environments. This condition leads to uncertainty in wave-in-deck load estimates and a high load level being imposed on offshore structures. This emphasises the necessity of enhanced reliability, as failure might result in inaccessibility because of the uncertainties related to long-distance services, such as accuracy of predictions of loads and responses. Even though the established guidelines present a fundamental assessment, additionally, comprehensive rules are required. This paper performed a reliability analysis incorporating practical approaches that can more accurately represent time-dependent structural deterioration. The following two procedures have been adopted by a majority of significant oil and gas operators to monitor the safety and integrity of these structures: a) Ultimate Strength Assessment (USA) method and b) Reliability Design Assessment (ReDA) method. A comparison of these two reliability approaches was performed on selected ageing jacket structures in the region of the Malaysian sea. The comparative findings, namely, reserve strength ratio (RSR) at various years of the return period (RP) and ratio value for risk of failure regarding the probability of failure (POF), provided a check and balance in strengthening confidence in the results. The findings showed that the structural components might safely survive either using the USA and ReDA method in such conditions, as the reliability indexes were determined to be satisfactory compared to allowable values from ISO 19902 design specifications. Therefore, these evaluations were determined to control the risk level of the structure during the remaining of its lifetime and undertake cost-effective inspections or mitigation strategies when necessary.

Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability assessment and index sensitivity. Aiming at the problem of over-fitting and parameter optimization in neural network learning, the paper proposes an improved machine learning algorithm—the Ensemble Learning Based on Policy Optimization Neural Networks (ELPONN) algorithm with the policy optimization and ensemble learning. This algorithm presents optimized neural network learning algorithm through different strategies evolution, and builds an ensemble learning model of multi-intelligent algorithms to assessment the capability and analyze the sensitivity of the indexes. Through the assessment of capabilities, the algorithm effectively avoids parameter optimization from entering the minimum point in performance to improve the accuracy of equipment capability assessment, which is significantly better than previous neural network assessment methods. The experimental results show that the mean relative error is 4.10%, which is better than BP, GABP, and early stopping. The ELPONN algorithm has better accuracy and stability performance, and meets the requirements of capability assessment.

Pre-monsoon dust aerosols over Indian regions are closely linked to the monsoon dynamics and Indian summer monsoon rainfall. Past observational studies have shown a decline in dust loading over the Indian landmass potentially caused by changing rainfall patterns over the desert regions. Such changes are expected to have far reaching impact on regional energy balance and monsoon rainfall. Using a regional climate-chemistry model, RegCM4.5 with an updated land module, we have simulated the long-term (2001-2015) changes in dust over the arid and semi-arid dust source regions of the North-Western part of the sub-continent. It is found that the area-averaged dust aerosol optical depth (AOD) over the arid and semi-arid desert regions has declined by 17% since the start of this millennium. The rainfall over these regions exhibits a positive trend of 0.1 mm day^-1year^-1 and a net increase of > 50%. The wet deposition is found to be dominant and ~5 fold larger in magnitude over dry deposition and exhibits total changes of ~ 79 % and 48% in the trends in atmospheric dust. As a response, significant change in the surface (11%), top of the atmosphere radiative forcing (7%), and widespread atmospheric cooling are observed in short wave domain of radiation spectrum, over the Northern part of the Indian landmass. Such quantification and long term change studies are necessary for understanding the regional climate change and the water cycle.

It was once thought that high QoS (Quality of Service) performance solves recurrent problems of low-quality multimedia services. Since then, solutions have been proposed to ensure a high level of QoE (Quality of Experience). In this document, the authors attempt to outline their understanding of an accurate meaning of quality of multimedia services. Starting from QoS and passing through generalised QoE, the authors focus on aspects of subjective and objective quality modelling and optimisation of visual performance for TRV (Target Recognition Video) applications (such as video surveillance), outlining the path of ITU-T standardisation in this area. The authors revised the ITU-T Recommendation P.912 to reflect improved subjective test techniques developed since this Recommendation was approved. The authors also attempt to predict at least some existing errors of reasoning, which are likely to become evident for the industry in the next decade.

Product Design is getting nowadays new challenges on developing new products, since the industry is in a rush to introduce products into the marketplace, where customers demand products faster, cheaper, and free of failures. In the meantime, global companies are always trying to improve their Product Design process to get advantages over their competitors using proven tools like FEMA and mixing methodologies like Fuzzy theories with FMEA. Even today using all this tools and combination of methodologies there is a gap to address and it is required a robust risk analysis solving current issues in the electronic industry. This document aims to reveal a novel integrated method, where Failure Mode and Effect Analysis, Pythagorean Fuzzy Sets and Dimensional Analysis are cohesive into a model that minimize the uncertainty of the ranking and prioritization over the Failure Mode and Effect Analysis execution, helping to identify risks within an accurate grade over possible failures in the Product Design process. A real practical example is used to show the proposed method, where it is identified a robust methodology integration and solid and results using a sensitivity analysis.

In many developed countries, mental health disorders have become problematic, and the economic loss due to treatment costs and interference with work is immeasurable. Therefore, we developed a method to assess individuals’ mental health using emotional components contained in their voice. We propose two indices of mental health: vitality, a short-term index, and mental activity, a long-term index capturing the trends in vitality. To evaluate our method, we used the voices of healthy individuals (n = 14) and patients with major depression (n = 30). The patients were also assessed by specialists using the Hamilton Rating Scale for Depression (HAM-D). A significant negative correlation existed between the vitality extracted from the voices and HAM-D scores (r = -0.33, p &lt; .05). We could discriminate the voice data of healthy individuals and patients having depression with a high accuracy using the vitality (p = .0085, area under the curve = 0.76). Further, we developed a method to estimate stress through emotion instead of analyzing stress directly from voice data. By daily monitoring of vitality using smartphones, we can encourage hospital visits for people before they become depressed or during the early stages of depression, to prevent adverse consequences of depression.

Soft drinks exist in various forms and brands and are marketed by different brewery industries across the country. Nigeria been an underdeveloped country were aforesaid health problems are common, people tends to consume them lots believing it gives more energy. This study was therefore set to assess the sugar content from different soft drinks sold in Nigeria. Ten (10) soft drinks registered and licensed in Nigeria by their respective companies were purchased from a supermarket in Ihumudumu environment of Ekpoma, Nigeria. The sugar contents were assessed using standard methods. Result showed significant differences (p<0.05) in ranges of 0.36g/100ml (Limca) to 3.88g/100ml (Teem Bitter Lemon). Conclusively, the sugar contents were all below recommended value and it can be consumed by those who need low sugar in the body.

Demand responsive transport (DRT) is operated according to flexible routes, dispatch intervals, and dynamic demand, is attracting a lot of attention. The biggest characteristic of DRT service is that the vehicle routes and schedules are operated optimally based on real-time travel requests of using passengers without fixed operating schedules. Today, the smart-city era has arrived, particularly because of progress in the wireless communications technology and technology related to location information service and real-time passenger demands and requests, and services that change the vehicles’ operating schedules in real-time according to dynamic demand have attracted more attention. In this study, we analyze the effects of the DRT system to solve the first mile/last mile problem based on a proposed DRT routing algorithm considering real-time travel behavior. The algorithm is modified from the dynamic vehicle routing problem (DVRP), in which a DRT-based routing algorithm tends to minimize users’ cost and providers’ operation cost. So far, the DVRP has only been able to serve a single request per vehicle at a time. However, this needs to be extended for the purpose of DRT, wherein several passengers board a vehicle at the same time. The routing algorithm can serve multiple requests at a time and schedule picks ups, drop offs, and rides according to the requests and as calculated by the dispatch algorithm. The basic principle of routing is as follows. The DRT vehicle moves on an attractive path and picks up a passenger if boarding is requested, but it does not simply hang around as a DVRP would. In this step, if another DRT vehicle is present near another passenger, the vehicle that would minimize that passenger’s total travel time picks up the passenger. The optimal routing algorithm developed in this study is applied to the activity-based model; that is, a microscopic traffic demand estimation method is implemented through an activity-based model by using an open-source, activity-based model package called Multi-Agent Transport Simulation (MATSim). MATSim is used for the simulation, because it combines a multi-modal traffic flow simulation with a scoring model for agents, and it provides co-evolutionary algorithms that can alter agents’ daily routines. This process is applied to a type of mode choice and route choice repeatedly over several iterations until some form of user equilibrium has been reached. This study analyzed the feasibility of implementing the DRT service by analyzing the benefits for the users and cost of the operator from the effects of increasing public transportation use and providing personalized mobility service based on DRT implementation by the introduction of DRT will be analyzed according to the scale of DRT supply. Through the simulation, the DRT is expected to provide convenient, fast, and cost-effective mobility services to customers; provide an optimal vehicle scale to providers; and, ultimately, achieve a safe and efficient transportation system.

Functional mobility assessments (i.e., Timed Up and Go) are commonly used clinical tools for mobility and fall risk screening in the aging population. In this work, we proposed a new Mixed Reality (MR)-based assessment that utilized a Microsoft HoloLens^TM headset to automatically lead and track the performance of functional mobility tests, and subsequently evaluated its validity in comparison with reference inertial sensors. Twenty-two healthy adults (10 older, 12 young) participated in this study. An automated functional mobility assessment app was developed based on the HoloLens platform. Mobility performance was recorded with the headset built-in sensor and validated with reference inertial sensor (Opal, APDM) taped on the headset and lower back. Results indicate vertical kinematic measures by HoloLens was in good agreement with the reference sensor (Normalized RMSE ~ 10%). Additionally, the HoloLens-based test completion time was in perfect agreement with clinical standard stopwatch measure. Overall, our preliminary investigation indicates that it is possible to use an MR headset to automatically guide users to complete common mobility tests with good measurement accuracy, thus it has great potential to provide objective and efficient sensor-based mobility assessment.

In recent years, using multispectral cameras on UAVs has provided an opportunity to capture separate bands that offer the extraction of spectral features used for early detection of diseased plants. One of the main steps in disease detection is radiometric calibration that converts digital numbers to reflectance values commonly using white reference panels. This paper focused on the necessity of radiometric calibration to distinguish disease trees in orchards based on aerial multi-spectral images. For this purpose, two study sites with various climate conditions and tree species as well as different disease types were selected where multispectral images were taken using a multirotor UAV. The impact of radiometric correction on plant disease detection was assessed in two ways: 1) comparison of separability between the healthy and diseased classes using T-test and entropy distances; 2) radiometric calibration effect on the accuracy of classification. The experimental result showed the insignificant effect of radiometric calibration on separability criteria. Furthermore, based on T-test and entropy distances criteria, NIR and R spectral features made highest distances between healthy and Greening infected citrus trees, respectively, at the first study site while NDRE and BNDVI spectral features made highest distances between healthy and peach leaf curl infected trees, respectively, at the other study site. In the second strategy, the experimental result showed that radiometric calibration had no effect on the accuracy of classification. As a result, the overall accuracy and kappa values for both un-calibrated and calibrated orthomosaic classifications of the citrus orchard were 96.6% and 0.94%, respectively, using five spectral bands as well as DVI, NDRE, NDVI and GNDVI vegetation indices using a random forest classifier. The experimental results were also similar at the other study site. Therefore, the overall accuracy and kappa values for both the un-calibrated and calibrated orthomosaic classifications were 96.1%, 0.92, respectively, using five spectral bands as well as NDRE, BNDVI, GNDVI, DVI, and NDVI vegetation indices.

Background: Selectively targeting dopamine receptors has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases evolving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a molecular basis has not been fully elucidated. Methods: Homology modeling and molecular dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D1-like and D2-like receptors). Fifteen structurally diverse ligands were docked to these models. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for DR sub-type specificity. Results: We showed that the number of conformations for a receptor:ligand complex was associated to unspecific interactions > 2.5 Å and hydrophobic contacts, while the decoys binding energy was influenced by specific electrostatic interactions. Known residues such as 3.32Asp, the serine microdomain and the aromatic microdomain were found interacting in a variety of modes (HB, SB, π-stacking). Purposed TM2-TM3-TM7 microdomain was found to form a hydrophobic network involving Orthosteric Binding Pocket (OBP) and Secondary Binding Pocket (SBP). T-stacking interactions revealed as especially relevant for some large ligands such as apomorphine, risperidone or aripiprazole. Conclusions: This in silico approach was successful in showing known receptor-ligand interactions as well as in determining unique combinations of interactions, key for the design of more specific ligands.

The competitiveness of domestic products at the regional or global market is one of the cornerstones of a country’s internationalcompetitiveness. In this regard, the assessment and analysis of the competitiveness of a country’s international trade becomes an important issue. Thus, development and diversification of the export potential of the country is viewed as one of the most important directions of the international trade policy of the given country. Therefore, another important task is the specialization of the country in the most efficient and competitive segments of the economy. The above-mentioned circumstances embody the fact, that the role of quantitative assessment of potential competitive advantages is important, as it allows determining to what extent certain factors influence on the formation of export capacity in the country. The main objective of the study is to determine the role of export competitiveness in the process of competitive advantages formation of a country. This study mainly focuses on quantitative analysis based on the calculation of Balassa index, determining the extent to which a country has a comparative advantage in producing and exporting certain goods. The study presents the example of the Republic of Armenia, the study covers the period between 2002- 2016. Based on the index calculation, it can be determined whether the country has "revealed" comparative advantage or not. The practical significance of the study lies in the fact that its main findings and conclusions arising from it can be used in assessing the export competitiveness of not only Armenia, but also for other countries or groups of countries.The outcomes and implication of the research can be used to improve the competitiveness of goods and services in the global market.

Climate change such as sea level rise, change in temperature, precipitation, and storminess are expected to impact significantly coastal lagoons. The nature and magnitude of these impacts are uncertain. The objective of the research is to determine the climate change impacts on mixing and circulation at Songkhla lagoon, Thailand. Songkhla lagoon is the largest lagoonal water resource in Thailand and Southeast Asia. The lagoon is a combined freshwater and estuarine complex of high productivity which represents an extraordinary combination of environmental resources believed to be unique in the region. This work is part of a Climate Change impact assessment framework. It is the validation phase (step 5) of the framework applying a case study. Delft 3D was used to simulate CC scenarios in the climate downscaling models, part of the previous framework steps. These results were compared to the current conditions to determine the main changes in mixing and circulation in the coastal lagoon. Three indicators were applied to quantify the impacts: flushing time, salinity intrusion and stratification. The results suggest an increase in water velocities at the inlet in future scenarios and a decrease of flushing time. Salinity and stratification showed more complex changes in futures scenarios.

This paper presents a methodology for determining the sensitivity of the main air flow directions in ventilation subnetworks to changes of aerodynamic resistance and of air density in mine workings. Formulae for determination of the sensitivity of the main subnetwork air flows by establishing the degree of dependency of the air volume stream in a given working on the variations in resistance or air density of other workings of the network have been developed. They have been implemented in the VentGraph mine ventilation network simulator. This software, widely used in Polish collieries provides an extended possibility to predict the process of ventilation, air distribution and, in the case of underground fire, also the spread of combustion gasses. The new method facilitates assessment by mine ventilation services of the stability of ventilation systems in exploitation areas and determine of the sensitivity of the main subnetwork air flow directions to changes of aerodynamic resistance and air density. Recently in some Polish collieries new longwalls are developed in seams located deeper then the bottom of the intake shaft. Such solution is called “exploitation below the level of access” or “sublevel”. The new approach may be applied to such developments to assess the potential of changes of direction and air flow rates. In addition, interpretation of the developed sensitivity indicator is presented. While analyzing air distributions for sublevel exploitation, application of current numerical models for calculations of the distribution results in tangible benefits, such as the evaluation of the safety or risk levels for such exploitation. Application of the VentGraph computer program, and particularly the module POŻAR (fire) with the newly developed options, enables an additional approach to the sensitivity indicator in evaluating air flow safety levels for the risks present during exploitation below the level of the intake shaft. The analyses performed and examples presented enabled useful conclusions in mining practice to be drawn.

The research analysed the publications metric of literature regarding the impact of socially responsible investing (SRI) and environmental, social, and governance (ESG) on portfolio and financial performance. The study aimed to determine the latest trends, key themes, authors, and influential journals. Data from the SCOPUS database was used in this study. A total of 1377 research articles from academic journals related to this topic and published from 2013 to 2022, they data was cleaned to remove duplicate, and documents that do not meet the criteria of this study. For this bibliometric analysis, a total of 260 articles were chosen in order to summarise the collective knowledge and emerging patterns in ESG, SRI, ethical, and impact investing, a bibliometric analysis was employed. The thematic map classified the ESG, SRI, and performance relationship themes into four categories of themes: niche themes, motor themes (corporate financial performance, corporate social performance, ESG, ESG factors, sustainability, performance, integrated reporting, gender diversity, and board size), emerging or declining themes (social responsibility, environmental performance, socially responsible investment, ethical investment, and SRI), and basic or transversal themes (financial performance, corporate social performance, ESG performance, environmental, social, and governance). Social responsible investing, engagement, and ESG, implies a position between niche themes and highly developed topic/emerging or decreasing theme, and covid, ROA, while, tobin’s Q, implies a position between highly developed topic/emerging or decreasing theme and basic theme. The findings contribute to the enhanced understanding of ESG, SRI, ethical, and impact investing, which are crucial for an efficient capital market in promoting sustainability and sustainable development. The study offers vital practical implications and future research directions.