In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

Tea (Camellia L.) falls into the family Theaceae, is a valuable commercial crop, and tea products made from its buds and young leaves are favored by consumers all over the world. The more common Thea plant is Camellia sinensis (C. sinensis), but its most important relative, Camellia taliensis (C. taliensis), is also utilized by locals in the area of cultivation to manufacture tea. In this investigation, C. taliensis (DL) and C. sinensis (QJZ) were characterized in terms of their agronomic traits, physicochemical indices, metabolomics, and transcriptomics. The leaf area of DL is larger than that of QJZ; the color of DL’s buds and leaves is yellowish-green, while that of QJZ’s is green. DL’s buds and leaves are more densely velvety than those of QJZ. The HPLC results indicated that the physicochemical contents varied considerably between the two samples, with DL having greater concentrations of EGCG and GABA than QJZ, while QJZ had remarkably higher concentrations of C, CA, and EGC than DL. A total of 2269 metabolites and 362,190,414 genes were positively identified, with the number of DAMs and DEGs being 1001 and 34,026, respectively. The flavonoids, phenolic acids, and alkaloid metabolites were dramatically different between the two tea group plants. Bioinformatics profiling revealed that the DAMs and DEGs of the two tea group plants interacted with each other and were involved in metabolic pathways including “biosynthesis of secondary metabolites”, “biosynthesis of amino acids”, “biosynthesis of cofactors”, “phenylpropanoid biosynthesis”, and “flavonoid biosynthesis”. Overall, these results provide statistical support for germplasm conservation and production for both C. taliensis and C. sinensis.

This publication aims to create 4K UHD video sequences with a specific focus on smart cities and transport. The created database will be accessible to all experts in the field and can be further used for research purposes. All reference video sequences will be transcoded into different quality settings. The resolution, compression standard, and bitrate will be changed. The work will aim to find out the best combination of video parameters from the measured values. Thanks to the overall evaluation, we will ensure for each single video sequence the quality with the best experience for the providers that will offer the service. The database will also be available with its objective and subjective ratings, with dynamicity information characterized by spatial and temporal information. After, It will be possible to compare the results of the subjective evaluation of a selected sample of our respondents with the work of other researchers who can evaluate with a different sample of evaluators.

As an important carrier of urban residents' public life, urban public open space plays an indispensable role in improving the quality of life of urban residents. Accessibility is an important indicator to characterize the publicity and service level of a public open space. This study optimized the GIS-based, Gaussian two-part mobile search method to quantitatively calculate and evaluate the accessibility of public open space within a 5-minute walking distance for residents in Nanshan District, Shenzhen. On this basis, social survey methods, including the questionnaire survey method via a field survey and the interview method, were used to conduct field research on residents' accessibility satisfaction. Comparing the results of the survey on residents' accessibility satisfaction to the GIS quantitative evaluation results of accessibility, the results of the field research show that current residents of Nanshan are more satisfied with the accessibility of public open space. In view of the similarities and differences between the two sets of results, the influencing factors of public open space accessibility were analyzed, corresponding countermeasures were proposed for the construction of public open spaces in the future.

This study mostly analyzes the pragmatic viewpoints of speech acts and language functions through Halliday’s (1975) language functions and Searle’s (1976) speech acts were adapted to analyze the functional aspects of the conversations and it was also intended to explore the teachers’ perception toward teaching and learning English as a Foreign Language (EFL) learners’ textbooks and the teacher’s components of communicative knowledge regarding the functions of language in daily activity. The participants of this paper consisted of thirteen Sunrise 10, 11, 12 grades of Kurdish teachers at high school English in Iraqi Kurdistan. Through semi-structured interview, it was found that the conversations in the mentioned textbooks are insufficient from the pragmatic point of view. Some recommendation for the textbook designers, teachers, material developer were raised to make up the shortcomings of the textbooks. The findings reveal that the conversation texts in Sunrise textbooks are not meeting the systematic standard of pragmatic competence the English language learners and the book designer must be recommended to be aware of those shortcomings of the textbook series if they are required to develop their speaking skills in both student and activity series. The implications of this paper can be helpful in comparing the results of this study with other similar studies to check if there is a universal pattern in performing the speech acts and language functions and the interest to Kimberley Education for Life learners in increasing their knowledge of pragmatics in general and the role of language functions and speech acts investigated in this study.

Abstract: Seismic performance and loss assessments can have widely varying degrees of uncertainty. An essential issue is whether a particular assessed seismic loss or performance result has sufficient reliability to serve as the basis for risk management decisions and actions, including whether or not a code prescribed performance level is met, or if an assessed loss level is acceptable. A method is developed measuring the reliability of performance and loss assessments for individual buildings and for portfolios. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the evaluation, and the technical validity of the assessment procedure or model. The approach characterizes the uncertainty of each component of the assessment procedure for each building in qualitative terms. The resulting reliability measure is likely to be most useful for the cases where an entity is determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low risk of seismic damage loss over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

On-stream inspections are the most appropriate method for routine inspections during plant operation without going through production downtime. Ultrasonic inspection, one of the on-stream inspection methods, faces challenges when performed at high temperatures exceeding the recommended 52°C. This study aims to determine the ultrasonic velocity and attenuation with the known material grade, thickness, and temperatures by comparing theory calculation versus experiment with temperatures ranging between 30°C to 250°C on low carbon steel covering most petrochemical equipment material and working conditions. The theoretical analysis was to obtain Young's modulus, Poisson's ratio, and longitudinal velocity at different temperatures. The experiments validated the predicted results of ultrasonic change due to temperature increase and showed a maximum error of 3%. The experimental data of velocity and decibel change from the temperature range provide a reference for the future when dealing with unknown materials information on site that require a quick corrosion status determination.

Comprehensive geriatric assessment, defined as an interdisciplinary assessment and development of an overall plan of treatment and follow-up, has become a fundamental part of clinical geriatric care. Since the 1970s, the Veterans Administration has encouraged the development of geriatric evaluation and management programs. Evolution of geriatric evaluation and management has occurred over time and many VA medical centers have transferred inpatient geriatric evaluation programs to long-term care Community Living Centers (CLC) and outpatient settings. Availability of resources and trained personnel across the continuum of care as well as administrative facilitation of collaboration between care components are critical to the efficient utilization of geriatric services. Facilities may need to prioritize their resources and utilize the most effective and relevant elements of geriatric evaluation and management according to patient population needs, available space, resources, and institutional priorities.

Soil temperature reflects the impact of local factors，such as vegetation，soil and the atmosphere of a region. Therefore, it is important to understand the regional variation of soil temperature. However, lack of observations with adequate spatial and/or temporal coverage, it would be difficult to use the observation data to study the regional variation. Based on the observation data from Nanchang and Ganzhou stations and ERA-Interim/Land reanalysis data, this study analyzed the temporal-spatial distribution characteristics of soil temperature over Poyang Lake Basin. The results showed close correlations between observation data and reanalysis data at different depths. Reanalysis data could mainly reproduce the temporal-spatial distributions of soil temperature over the Poyang Lake Basin, but generally underestimate their magnitudes. Temporally, there is an obvious warming trend in the basin. Seasonally, the temperature raised fastest in spring and slowest in summer, except for the ST4, which rising fastest in spring and slowest in winter. In terms of depths, the temperature of ST1 rises fastest. For the other layers, the warming trend is almost similar. An abrupt change of annual soil temperature at all depths occurred in 1997, and annual soil temperatures at all depths were abnormally low in 1984. Spatially, annual soil temperature decreased with latitude, except for the summer ST1. Because of the high temperature and precipitation in summer, the ST1 are higher around the lake and the river. The climatic trend of soil temperature presents the general increase trend from south to north, opposite to the distribution of soil temperature. The findings provide a basis for understanding and assessing the variation of the soil temperature over the Poyang Lake Basin.

Background: While the clinical factors of the post-COVID-19 condition (PCC) are becoming clearer, the economic implications remain uncertain, posing a challenge to healthcare professionals in terms of understanding and managing this emerging phenomenon. This article aims to investigate the demographic and clinical characteristics of PCC patients and quantify the economic impact of their healthcare resource utilisation. Methods: A retrospective and case-control observational study was conducted, comparing the case group of PCC population before and after diagnosis with a control group. Demographic and clinical variables were analysed with the objective of describing the population. Economic analysis was performed to evaluate the resource costs in procedures and primary, secondary (both outpatient and inpatient) and emergency care. Findings: PCC patients (N=341) exhibited older age and elevated cardiovascular risk factors compared to controls (N=49,078). There were differences in the socio-economic distribution between male and female patients in the PCC patients. Hypertension and diabetes mellitus type 2 were the most common chronic diseases observed among the case patients. Economic analysis revealed that PCC patients were approximately four times as costly as control patients, with increased utilisation of healthcare resources. However, post-diagnosis PCC patients showed a reduction in costs, primarily driven by decreased primary care visits and hospitalisations. Conclusion: Coordinated care management for PCC patients is associated with reduced costs and improved healthcare resource utilisation. Further research is warranted to investigate long-term health outcomes and establish causal relationships between COVID-19 sequelae and healthcare resource utilisation.

Risk management strategies protect the company as a whole as well as employees from unforeseen financial impacts. As in the case of personal finance, preparing for certain scenarios helps to face any difficulties that the company may encounter and allows it to get out of this impasse.For any project to be successful, the way the project executing agency will deal with potential risks must be determined so that it can identify, mitigate or avoid problems when it needs to do so. Successful project managers realize that risk management is important, because the achievement of project objectives depends on planning, preparation, results and evaluation that contribute to the achievement of strategic goals, especially the sustainable development of societies.Risk management strategies work to protect the company as a whole as well as employees from unexpected financial effects, and as is the case in personal finance, preparing for certain scenarios helps to face any difficulties that the company may face and allows it to get out of this impasse.To ensure the success of your project, determine how you will handle potential risks so that you can identify, mitigate or avoid problems when you need to do so. Successful project managers understand that risk management is important, because the achievement of project objectives depends on planning, preparation, results, and evaluation that contribute to the achievement of strategic objectives.

Formaldehyde, sulfuric acid and salicylic acid were combined to create 3,3’-methylenebis[2-hydroxybenzoic acid] (MHB) ligand, which was subsequently permitted to bind with zinc ions. The ligand and its zinc (II) complex (Zn-MHB) have been described by a combination of elemental analyses, spectral (UV-Vis, IR, MS, NMR), XRD, TEM as well as TGA measurement. The ligand has been suggested to coordinate to the zinc center in tetradentate manner forming binuclear tetrahedral complex. An X-ray analysis indicated a considerable difference between MHB (crystalline) and Zn-MHB (amorphous). UV-Vis spectra were used to determine the optical properties such as bandgap, refractive index, optical conductivity and penetration depth. Possibility of employing the samples for optoelectronic applications was indicated from the band gap values which underlie the range of semiconductors. TEM revealed spherical shapes and mutation of ligand particles into nano-scale by complexation. The antimicrobial potential of the MHB towards gram-positive and negative bacterial growths has been investigated. The results suggested that it would be possible to employ MHB to stop bacterial development, particularly salmonella typhimurium. Cytotoxicity of the MHB was assessed against two types of mammalian cells: VERO (the kidney of an African green monkey) and HFB4 (human skin melanocytes). Lower sensitivity was observed in VERO cells.

In this paper, we propose a novel approach named EmbedHDP to enhance the evaluation models used to assess sentence suggestions within nursing care record applications. The key focus is determining whether these suggestions garner assessments that align with caregivers as human evaluators. It is crucial due to the direct relevance of the information provided to the health or condition of the elderly. The motivation behind this proposal stems from challenges observed in previous models, such as BERTScore, which encountered difficulties in effectively evaluating the nurse care record domain, consistently providing quality assessments of generated sentence suggestions above 60%. Additionally, while widely used, cosine similarity exhibits limitations concerning word order, leading to potential misjudgments of semantical differences within similar word sets. Similarly, relying on lexical overlap, ROUGE tends to overlook semantic accuracy. Furthermore, despite its utility, BLEU neglects semantic coherence in its evaluations. EmbedHDP excels in evaluating nurse care records by effectively handling a variety of sentence structures and medical terminology and providing differentiated and contextually relevant assessments. We used a dataset comprising 320 pairs of sentences with correspondingly equivalent lengths. The results revealed that EmbedHDP outperformed other evaluation models, achieving a coefficient score of 61%, followed by cosine similarity with a score of 59%, and BERTScore with 58%. This shows the effectiveness of our proposed approach in improving the evaluation of sentence suggestions in nursing care record applications.

Wild Chinese prickly ash with elevated antioxidants is a valuable genetic resource for Zanthoxylum bungeanum Maxim improvement. There are rich wild germplasm resources in the Qinling Mountains. In a study with wild germplasm resources from different altitudes and six cultivated varieties, the phenolic and flavonoid compounds were analyzed by high performance liquid chromatography (HPLC). The chromatograms of them were basically the same, although their chemical composition content was greatly different. The thirty samples were divided into three categories through the hierarchical clustering analysis. And catechin, hyperoside and quercitrin were considered to be key compound for the quality evaluation, by contrast, the wild samples with an altitude of 2300±50 m (Ⅳ group) had the highest content of key compounds, and showed stronger antioxidant activity and antibacterial ability, indicating that these wild samples could be used as an excellent breeding resource. This is the first time to evaluate the quality of wild Chinese prickly ash in different altitude areas of Qinling Mountains. These excellent wild germplasm resources provided substantial potential accessions for use directly in Chinese prickly ash breeding programs.

Interpretation of increased gain in the bovine animals is difficult to be validated due to inherent genetic variation to meet their requirement for energy and protein, and those may relate to the bull species, e.g., Thai swamp buffalo. Therein, the study aimed at investigating and predicting protein requirement systems, with providing abundant energy intake 2.20 Mcal/kg DM for maintenance and growth of Thai swamp buffaloes using the comparative prolonged feeding trial for 90 days. Sixteen bull Thai swamp buffaloes at the initial (Age: 18-24 months; BW: 233 ± 25.0 kg) were as-signed into four treatment groups, four buffaloes each, fed 5.42, 6.96, 8.94, and 10.71% DM crude protein (CP). CP intake, BW, and physiological fluid were determined. The net CP requirements for maintenance and growth of Thai swamp buffaloes were 5.41 g CP/kg W0.75 and 0.46 g CP/g average daily gain (ADG), respectively. Our results indicated that CP requirement increases, when BW increases. An increased dietary CP resulted in an increased number at blood urine nitrogen (N), N absorption, total volatile fatty acid, urinary purine derivative, and the microbial N. Notably, the net CP requirement for growth of Thai swamp buffalo was higher than it reported in NRC, but the maintenance was lower.

Existing studies often lack a systematic solution for Unmanned Aerial Vehicles (UAV) inspection system, which hinders their widespread application in crack detection. To enhance its practicality, this study proposes a formal and systematic framework for UAV inspection systems, specifically designed for automatic crack detection and pavement distress evaluation. The framework integrates UAV data acquisition, deep learning based crack identification, and road damage assessment in a comprehensive and orderly manner. Firstly, the flight control strategy is presented, and road crack data is collected using the DJI Mini 2 UAV imagery, establishing a high-quality UAV crack image datasets with ground truth information. Secondly, a validation and comparison study is conducted to enhance the automatic crack detection capability and provide an appropriate deployment scheme for UAV inspection systems. This study develops automatic crack detection models based on mainstream deep learning algorithms(namely, Faster-RCNN, YOLOv5s, YOLOv7-tiny, and YOLOv8s) in urban road scenarios. The results demonstrate that the Faster-RCNN algorithm achieves the highest accuracy and is suitable for online data collection of UAV and offline inspection at work stations. Meanwhile, the YOLO models, while slightly lower in accuracy, are the fastest algorithm and are suitable for lightweight deployment of UAV with online collection and real-time inspection. Quantitative measurement methods for road cracks are presented to assess road damage, which will enhance the application of UAV inspection systems and provide factual evidence for maintenance decisions made by road authorities.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

Huge amounts of wastes are generated during shrimp processing, representing approximately 65% of the initial shrimp weight, which can become an environmental problem when accumulated. Residues such as shrimp shells can be processed to obtain value-added products such as chitin, chitosan, astaxanthin, and a nitrogenous extract under the biorefinery concept. In this work, the economic evaluation and the techno-economic sensibility analysis for a mass integrated biorefinery based on shrimp were developed to determine the economic feasibility of the project and to identify the critical techno-economic variables that affect the profitability of the process. The results showed that a biorefinery for the annual processing of 4,113.09 tons of fresh shrimp in Colombia is profitable, with a return on investment percentage (%ROI) equal to 65.88% and a net present value (NPV) of 10.40 MM USD. The process supports decreases of up to 28% in capacity of production and increases of 12% and 11% in the cost of raw materials and variable operating costs without incurring losses, respectively. However, the decrease over 500 USD/t in the shrimp meat selling price is not supported, thus it is mainly recommended to increase the selling price of this product.

Sustainability is pivotal in the urban transformation strategy in order to reach more resource-efficient, resilient and smarter cities. The goal of being a sustainable city should drive the decisions for city interventions. Nonetheless, impacts need to be quantified, lacking of standard and/or common methodologies that could be replicable across multiple cities. There exist many initiatives aiming at defining indicators and assessment procedures, but without convergence in the definition of terms and application methodologies, making complex its real implementation. Within mySMARTLife project (GA#731297), a KPI-driven evaluation framework is defined with the aim of covering the multiple pillars of a city (i.e. energy, mobility, citizens, economy) in a holistic way. This methodology also defines the concepts and terms to guide urban planners and/or experts at time of implementing the framework in a specific city. The evaluation framework has been deployed in the three cities of Nantes, Hamburg and Helsinki and some lessons learnt have been extracted, such as the necessity of providing a definition of measurement boundary to avoid interpretations. Thanks to a co-creation strategy, the main difficulties and issues from the cities have been taken into consideration for increasing the replicability.

Childsmile is Scotland’s national child oral health improvement programme designed to reduce inequalities in oral health and ensuring universal access to NHS dental services by working closely with children and their families. Research has shown that parents with more dental concerns are less likely to bring their children for regular preventive dental check-ups. Therefore, a communication toolkit named ‘Chatterbox’ was created to help families access dental care services. This study aimed to evaluate the acceptability of Chatterbox from the perspective of parents with young children and from staff who work with them. Thirty parents of young children, volunteers, and staff affiliated with three third-sector family support organisations in Dundee participated in in-depth interviews, focus groups, and observations to assess the objectives of Chatterbox. Framework analysis was conducted to capture the themes, patterns, and findings triangulated using observations and field notes. Chatterbox was found to promote effective communication, identify barriers to dental attendance, provide a platform for reflection, convey the complexities of daily life, and boost parents' confidence to seek assistance. Chatterbox has the potential to help parents in accessing preventive dental care for their young children, when used with trained support workers.

Protected areas serve as an effective mechanism usually supported by a statute to conserve and protect wildlife-rich areas worldwide. Such extensive external management needs elaborate planning, regular monitoring, and periodic assessment of results. Thus, management effective evaluation (MEE) has emerged as one of the major tools for quantifying the performance of any protected area, globally since 2006. India has successfully conducted a complete round of management effectiveness evaluation of all its terrestrial protected areas (except conservation reserves and community reserves), with 25 such areas already undergoing a repeat assessment. Simultaneously, India biennially carries out a country-wide status of forest cover in all its states and union territories. This study has correlated the trend in change of forest cover for the states that contain those 25 repeat evaluated protected areas with their change in MEE scores over the same period. Our study found a positive correlation between the change in forest cover and the change in management effectiveness score from 2005-06 to 2018-19. Owing to increased protection regimes in the PAs including the degraded areas if they make part of such areas, the habitat often shows recovery. Effective habitat conservation is thus intertwined with the monitoring and preserving the wildlife populations in the protected areas, thereby, reduction in forest cover equally impacts the management scores. However, in states where the loss in forest cover has been reported, more protected areas need to be assessed to plan complementary strategies for both habitat and species conservation.

Interactions of different factors in differently tilled faba bean agrosystem is still insufficiently studied and evaluated. For these reasons we studied the results of long-term field experiment, which was carried out in the Research Station of Vytautas Magnus University, Agriculture Academy (Lithuania). The aim of this study is comprehensively evaluating the effect of the deep and shallow ploughing, deep cultivation-chiseling, shallow cultivation-disking, and no-tillage systems for faba bean cultivation on the much-interacted factors, relations between them and strength of impact by the integrated evaluation method using complex evaluation index (CEI). Calculations showed that the influence of the no-tillage system was the greatest on the faba bean agrosystem than other system used. Shallow cultivation was more efficient than deep and shallow ploughing and deep cultivation systems. In the deep ploughing system, there were calculated more minimal, i.e. close to 1 as the CEI value, which showed DP ineffectiveness.

European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills skills gap and/or enables acquisition of new ones related to the planning and implementation of such solutions can empower local/ regional authorities to identify them, adopt them and eventually deliver them properly. The aim of this paper is to present the Key Performance Indicator (KPI) framework that has been used for the assessment of the effectiveness of the Learning and Exchange Programme applied in an EU-funded project. It presents the methodological steps for the adoption of the KPIs, as well as the tools used for the selection of the KPI data and the KPI monitoring at project level. It also presents the results from the application of the framework for assessing the knowledge performance towards the deployment of sustainable mobility solutions. It finally reflects on recommendations for applying the KPI framework to other cases and thematic contents.

Viruses are abundant and diverse entities that have important roles in public health, ecology, and agriculture. Identification and surveillance of viruses rely on understanding their genome organization, sequences, and replication strategy. Despite technological advancements in sequencing methods, our current understanding of virus diversity remains incomplete, highlighting the need to explore undiscovered viruses. Virus databases play a crucial role in providing access to sequences, annotations and other metadata, and analysis tools for studying viruses. However, there has not been a comprehensive review of virus databases in the last five years. This study aimed to fill this gap by identifying 24 active virus databases and included an extensive evaluation of their content, functionality and compliance with the FAIR principles. In this study, we thoroughly assessed the search capabilities of five database catalogs, which serve as comprehensive repositories housing a diverse array of databases and offering essential metadata. Moreover, we conducted a comprehensive review of different types of errors, encompassing taxonomy, names, missing information, sequences, sequence orientation, and chimeric sequences, with the intention of empowering users to effectively tackle these challenges. We expect this review to aid users in selecting suitable virus databases and other resources, and to help databases in error management and improve their adherence to the FAIR principles. The databases listed here represent current knowledge of viruses and will help aid users find databases of interest based on content, functionality, and scope. Use of virus databases is integral to gain new insights into the biology, evolution, and transmission of viruses, and develop new strategies to manage virus outbreaks and preserve global health.

The paper addresses the problem of a statistically significant numerical evaluation of the biomechanics of respiration using the motion of the ribcage through the identification of the kinematics of the sixth rib. We report the results of an experimental campaign conducted using a RESPIRholter device prototype for efficient, comfortable, and numerical monitoring on two groups of volunteers, namely with healthy people and with chest operated patients. The results are reported in terms of statistical processing of the data extracted from the monitoring which are represented in plots of acquired motion characteristics with movement graphs in terms of angles and accelerations. This experimental campaign can be considered a first result for the construction of a database useful for a reference of diagnostics as reported by the discussed example case study.

Despite their enormous potential the use of Indoor Localization Systems (ILS) remains seldom. One reason is the lack of market transparency and stakeholders’ trust in the systems’ performance as a consequence of insufficient use of Test and Evaluation (T&E) methodologies. The heterogeneous nature of ILS, their influences, and their applications pose various challenges for the design of a methodology that provides meaningful results. Methodologies for building-wide testing exist, but their use is mostly limited to associated indoor localization competitions. In this work, the T&E 4iLoc Framework is proposed - a methodology for T&E of indoor localization systems in semi-controlled environments based on a system-level and black-box approach. In contrast to building-wide testing, T&E in semi-controlled environments, such as test halls is characterized by lower costs, higher reproducibility, and better comparability of the results. The limitation of low transferability to real world applications is addressed by an application-driven design approach. The empirical validation of the T&E 4iLoc Framework, based on the examination of a contour-based Light Detection and Ranging ILS, an Ultra Wideband ILS, and a camera-based ILS for the application of Automated Guided Vehicles in warehouse operation, demonstrates the benefits of T&E with the T&E 4iLoc Framework.

North American Whites tend to evaluate members of their own race more positively than members of other races. One exception may be White Liberals, who appear politically motivated to evaluate members of (disadvantaged) racial outgroups more positively than members of their own racial group. We confirmed this claim presently, where 75 White Liberals, 95 White Conservatives, 49 Black Liberals and 71 Black Conservatives evaluated biracial faces using explicit and implicit evaluation tests. We instrumentally ‘frustrated’ half our participants to note whether incidental anger influenced ideologically-motivated racial attitudes. Evaluations towards racial outgroups were largely unaffected by negative mood induction -White Liberals were pro-Black relative to White Conservatives, and Black Conservatives were pro-White relative to Black Liberals, independent of mood. Negative mood induction selectively influenced own-race evaluations. Black Liberals and White Conservatives became respectively more pro-Black and pro-White when frustrated.Conversely, Black Conservatives and White Liberals became respectively less pro-Black and pro-White. Frustration significantly amplified negative own-race attitudes across explicit and implicit evaluation measures for White Liberals. We speculate on some social consequences that may follow from frustration-amplified ‘anti-White’ bias across White Liberals.

The aim of this paper is the evaluation of the success of graduating with distinction in higher education (SGDHE) using the fuzzy DEMATEL method. The observation has been done using cause and effect criteria. 11 cause and 14 effect clusters have been used in this study. The study result of this work shows that all the effects are connected to the given causes and a cause-effect graph has been generated for each connection. This proposed approach is demonstrated with the empirical case of Dire Dawa University students in Dire Dawa Ethiopia.

This paper proposed a new evaluation model based on analytic hierarchy process to quantitatively evaluate the capability of multi-satellite cooperative remote sensing observation. The analytic hierarchical process model is a combination of qualitative and quantitative analysis of systematic decision analysis method. According to the objective of the remote sensing cooperative observation mission, we decompose the complex problem into several levels and a number of factors, compare and calculate various factors in pairs, and obtain the combination weights of different schemes. The model can be used to evaluate the observation capability of resource satellites. Taking the optical remote sensing satellites such as China’s resource satellite series and GF-4 as examples, this paper verifies and evaluates the model for three typical tasks: point target observation, regional target observation and moving target continuous observation. The results show that the model can provide quantitative reference and model support for comprehensive evaluation of the collaborative observation capability of remote sensing satellites.

This paper presents an analysis of precipitation extremes over the East African region. The study employs six extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) to evaluate possible climate change. Observed datasets and CMIP6 simulations and projections are employed to assess the changes during the two main rainfall seasons of March to May (MAM) and October to December (OND). The study evaluated the capability of CMIP6 simulations in reproducing the observed extreme events during the period 1995 – 2014. Our results show that the multi-model ensemble (herein referred to as MME) of CMIP6 models can depict the observed spatial distribution of precipitation extremes for both seasons, albeit with some noticeable exceptions in some indices. Overall, MME's assessment yields considerable confidence in CMIP6 to be employed for the projection of extreme events over the study area. Analysis of extreme estimations shows an increase (decrease) in CDD (CWD) during 2081 – 2100 relative to the baseline period in both seasons. Moreover, SDII, R95p, R20mm, and PRCPTOT demonstrate significant OND estimates compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while reduction is observed over the Tanzania region. The increase in projected extremes during two main rainfall seasons poses a significant threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. More studies are encouraged to examine the underlying physical features modulating the occurrence of extremes incidences projected for relevant policies.

In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated COVID-19 disease has become a global pandemic causing significant mortality and morbidity. In the absence of vaccines and effective therapeutics, reliable serological testing can be a key element of public health policy to control further spread of the disease and gradually ease quarantine measures. However, prior to launch of large-scale seroprevalence studies to assess herd immunity, it is critical to understand the limits and potential of current SARS-CoV-2 serological tests on the market. In this study, we provide an overview of serological testing and conduct a systematic review of independent evaluations of SARS-CoV-2 serological tests performance. Our findings show significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid diagnostic tests with high performance level in detecting SRAS-CoV-2 specific antibodies. The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests.

The contribution deals with the joining of various types of materials by technology of thermal drilling. In various branches of industries, also in the automotive industry must be joining operations, service, repairing, substitution or protection workpieces, components with various types of materials. Equally, the important role as joint, is also used material, and a product preparation by assembly and disassembly operations. By utilization of new friction hybrid joining technologies we can shortage the production time, provide automation in operations, increase the quality of joints, spare of economical expenses and also we can protect the environment. In this paper authors have investigated the effect of friction drilling on the tested material, aluminium alloy AlMgSi, which was used for material testing. The created joints were evaluated visually and by microscopy methods. The errors of tested joining were documented and described, too. This contribution was made with cooperation of Technical University of Kosice and with U. S. Steel Kosice, s.r.o.

Injuries of repetitive efforts constitute one of the prime causes of absenteeism in the workplace, have bear a considerable cost for the public health system and can cast doubt on the sustainability of a company. The objective of this paper is to build, in the researchers, the needed knowledge to choose a set of relevant scientific articles about repetitive strain injuries in the poultry meat industry, aiming identify characteristics in those scientific publications that have the potential to contribute on the topic of this paper. The research is characterized as exploratory-descriptive, draws on primary and secondary data sources. The study involves the application of a method for selection and analysis of the selected articles. To this end, the method utilized was the Knowledge Development Process – Constructivist (Proknow-C) as theoretical intervention instrument. Within the process development, it was obtained a portfolio of 16 articles aligned to the research and scientifically recognized with the main periodicals, papers, authors and keywords. The ProKnow-C process allowed identify opportunities in the literature about injuries in the poultry meat industry and showed opportunities for research future. This paper, under the constructivist perspective, presents a structured process to build, in the researcher, the necessary knowledge to identification, selection and analysis of relevant scientific articles relating to research context and, for these articles, find prominences and opportunities for a research theme without similar publications.

Student-centered teaching practices such as active learning continue to gain momentum in college science education. Many instructors committed to these innovative practices transform their classroom beyond the standard lecture. Nevertheless, widespread implementation of these practices is limited because the learning benefits for students are often attained through increased instructional complexity to which many instructors cannot commit. When co-instructors are teaching the course, the level of commitment to building a student-centered classroom may be even more profound. For these reasons, new tools are needed to help instructors and co-instructors plan, organize, evaluate, and communicate their classroom innovations. Pathway modeling is a tool with potential to fill this gap. Unlike curriculum mapping -- which identifies academic content gaps, redundancies, and misalignments by examining a series of courses within a plan of study – course pathway modeling creates a visual map of a single course and reveals how teaching practices influence short-, mid-, and long-term student learning outcomes. This essay demonstrates how course pathway modeling can help co-instructors better represent the complexity of student-centered teaching practices. We include guides for creating course pathway models and discuss how this approach offers the potential to improve curricular design, course evaluation, student assessment, and communication between co-instructors.

SMARCA4-deficient non-small cell lung cancer (NSCLC) is a more recently recognized subset of NSCLC. We describe the 18F-fluorodeoxyglucose (FDG) PET/CT findings in a rare case of SMARCA4-deficient NSCLC and response to therapy. A 45-year-old male patient with a history of heavy smoking (10 years) underwent an 18F-fluorodeoxyglucose (FDG) PET/CT dynamic (chest) + static (whole-body) scan for diagnosis and pre-treatment staging. 18F-FDG PET/CT showed an FDG-avid mass in the upper lobe of the left lung (SUVmax of 22.4) and FDG-avid lymph nodes (LN) in the left pulmonary hilar region (SUVmax of 5.7). In addition, there are multiple metastases throughout the body, including distant LNs, adrenal glands, bone, and brain. Pathological findings confirmed SMARCA-4 deficient NSCLC. After 4 cycles of chemotherapy and immune checkpoint inhibitors（ICI）, the patient underwent again an 18F-FDG PET/CT scan (including dynamic scan) for efficacy evaluation. We report cases that deepen the understanding of the 18F-FDG PET/CT presentation of SMARCA4-deficient NSCLC as well as dynamic imaging features and parametric characteristics.

Oil has become the object of global exploits and fierce competition among the major world powers as it is a key strategic non-renewable resource. Transnational petroleum investment is therefore an important mechanism available to countries and international corporations to control oil resources even though there are numerous inherent uncertainties and risks. A new risk assessment index system is proposed in this paper based on use of the Delphi expert scoring system and fuzzy comprehensive evaluation that aims to minimize the potential risks inherent to multinational petroleum investment. This approach encapsulates political, legal, socioeconomic, and infrastructural factors to develop a technical method that can be used for transnational petroleum investment risk assessment. An evaluation of oil investment risk within a case study area is also presented; results provide reference data that can be applied by national and international oil companies to mitigate risks of transnational oil investment.

Popular geo-computer vision works make use of aerial imager with sizes ranging from 64 × 64 to 1024 × 1024 pixels without any overlap, although the learning process of deep learning models can be affected by the reduced semantic context or the lack of information near image boundaries. In this work, the impact of three image sizes (256 × 256, 512 × 512, and 1024 × 1024 pixels) and two image overlap levels (no overlap and 12.5% overlap) on the performance of road classification models was statistically evaluated. For this, two convolutional neural networks used in various tasks of geospatial object extraction were trained (using the same hyperparameters) on a large dataset (containing aerial image data covering 8650 km² of the Spanish territory that was labelled with binary road information) under twelve different scenarios, each scenario featuring a different combination of tile size and overlap. To assess their generalisation capacity, the performance of all resulting models was evaluated on a data from novel areas covering approximately 825 km². The performance metrics obtained were analysed using appropriate descriptive and inferential statistical techniques to evaluate the impact of the performance at distinct levels of the fixed factors (tile size, tile overlap, neural network architecture). Statistical tests were applied to study the main and interaction effects of the fixed factors on the performance. A significance level of 0.05 was applied to all the null hypothesis tests. The results were highly significant for the main effects (p-values lower than 0.001), while the two-way and three-way interaction effects among them had different levels of significance. The results indicate that the training of road classification models on images with a higher tile size (more semantic context) and tile overlap (additional border context and continuity) significantly impacts their performance. The best model was trained on a dataset featuring tiles with a size of 1024 × 1024 pixels and a 12.5% overlap and achieved a loss value of 0.0984, an F1 score of 0.8728, and an ROC-AUC score of 0.9766, together with an error rate of 3.5% on the test set.

A novel investigation into the structure-function relationship was undertaken to enhance understanding of the mechanism of action of the vasoactive peptide angiotensin II (AngII) using unconventional substitutions such as AIB (α-aminobutyric acid), CHA (cyclohexylalanine acid), IAP (isonipecotic acid), TOAC (2,2,6,6-tetramethylpiperidine-1-oxyl-4-amine-4-carboxylic acid) at position 3, and DMT (2,6-dimethyl-Tyrosine) at position 4. Biological potency assays were conducted on guinea pig ileum, and structural features were analyzed using circular dichroism (CD) and molecular dynamics (MD). CHA3-AngII and AIB3-AngII analogs retained some agonistic activity, whereas IAP3-AngII and TOAC3-AngII derivatives were inactive. CD results indicated low conformational flexibility for AIB3-AngII and CHA3-AngII, and greater conformational restrictions for IAP3-AngII and TOAC3-AngII, consistent with computational modeling analyses. DMT4-AngII exhibited significant agonistic activity compared to the inactive Phe4AngII. Molecular modeling suggested a potential interaction between the hydroxyl group of Tyr4 and the amide bond between positions 7 and 8. AngII showed greater conformational restriction compared to DMT4-AngII and Phe4-AngII, underscoring the importance of tyrosine at position 4.

This study assessed the impact of mineral fertilization on tuber yield and food quality of yam genotypes, specifically Dioscorea alata and Dioscorea rotundata. Four genotypes, each from D. alata and D. rotundata, were used in field experiments conducted in Ibadan, Nigeria, in the 2017 and 2018 cropping seasons. Experiments were conducted under low soil NPK fertility conditions with and without fertiliser treatments. A recommended NPK rate for the area (90, 50, and 75 Kg N, P, K ha-1) was applied to plots with fertiliser treatment. Tuber yield, functional and pasting properties of yam flour, and sensory attributes of pounded yams were collected. The results showed differential responses of the genotypes to tuber yield and food quality with fertiliser application. Fertiliser application has generally increased fresh tuber yield, but it has affected some genotypes' flour quality and textural attributes of the pounded yams. As regards genotypes Danacha and TDa0200012, fertiliser application has increased tuber yield without causing a decrease in tuber quality hence, suggesting Danacha and TDa0200012 as suitable genotypes for maximizing fertiliser productivity. However, in another genotype Ojuiyawo, fertiliser application effectively increased tuber yield but deteriorated tuber quality. Our results suggested that it is crucial to determine the impact of fertilisation on tuber yield and quality for each genotype and select the appropriate genotype to improve productivity through mineral fertilisation. The results of this study can be widely applied to enhance yam productivity in sub-Saharan Africa and useful for sustainable agriculture in yam-growing areas.

Teledermatology, the dermatological consultation and diagnosis via digital communication technologies, has become increasingly important in modern healthcare. The integration of teledermatology into clinical practice has gained significant interest, especially during the COVID-19 pandemic. Numerous studies have shown the effectiveness and reliability of teledermatology, with high levels of patient satisfaction and diagnostic accuracy. Pathpoint® eDerma is a cloud-based dermatology platform that aims to streamline the documentation and management of dermatological conditions. It offers several clinical benefits, including faster diagnosis, reduced unnecessary procedures, improved access to care, and cost savings. The platform follows a comprehensive risk management plan and complies with safety regulations. It undergoes regular recertification and reviews to ensure its safety and effectiveness. The clinical evaluation of eDerma confirms its ability to deliver significant clinical benefits while effectively mitigating risks. The benefit-risk ratio of eDerma is highly acceptable, supporting its use in clinical settings to enhance dermatological care.

In order to realize the sustainable utilization of water resources and the sustainable development of economy, the evaluation index system of water use efficiency system and economic development system was constructed. Entropy weight method and comprehensive evaluation method were adopted to determine the index weights and conduct comprehensive evaluation for the two systems. The coupling coordination model was used to calculate the coupling degree, coordination degree and coupling coordination degree of the two systems. The annual coupling stage and coupling coordination intensity of the two systems were analyzed and determined. The results showed that the comprehensive evaluation values of both water use efficiency system and economic development system in Jinan City increased greatly from 2008 to 2017, and showed a changing trend of ups and downs. The two systems were in the antagonistic stage, and were gradually approaching the running-in stage, indicating that they were in the state of common development. The coupling coordination degree of the two systems gradually increased in waves, progressed from the moderately to the highly coordinated coupling. In the future, if the water control path appropriate to Jinan City can be explored actively, the water-saving kinetic energy of economic development can be increased constantly, and the linkage effect between economic development and water resources utilization can be given full play to, the two systems will be in the orbit with the benign interaction and healthy harmonious development.

Background: Upper respiratory tract infections (URTIs) are a major public health concern due to their high incidence and potential for complications. Pharmacists often serve as the first point of contact for patients with URTIs. This study aims to develop and evaluate the RESP-8 tool to assist pharmacists in determining the need for medical evaluation. Methods: This prospective interventional cohort study was conducted over six months (October 2023 to March 2024) in community pharmacies. Participants included adults aged 18 years and older presenting with URTI symptoms. Pharmacists used the RESP-8 tool, which comprises eight criteria to assess the need for medical referral. Data on medical history, symptom duration, and progression were recorded. The primary outcome was the feasibility of implementing the RESP-8 tool. Secondary outcomes included the accuracy of the tool, the percentage of patients recommended for medical evaluation, and compliance with these recommendations. Results: A total of 64 participants were included, with an average age of 55.7 years. Pharmacists recommended medical evaluation for 75% (48/64) of patients using the RESP-8 tool. Among these, 70.83% (34/48) complied with the recommendation. The tool demonstrated high accuracy in identifying patients needing further medical evaluation, with only two noted errors. All compliant patients received appropriate treatment without complications. The tool was easy to implement, taking less than 5 minutes per patient. Discussion: The RESP-8 tool effectively guided pharmacists in recommending medical evaluations for URTI patients. The high compliance rate indicates patient trust in pharmacists' guidance. While the study's small sample size limits generalizability, the results are promising. Future studies with larger populations are necessary to validate these findings and further refine the tool. Conclusion: The RESP-8 tool shows potential in enhancing pharmacists' ability to make informed decisions about medical referrals for URTIs, ultimately improving patient outcomes and optimizing healthcare resource management.

South Africa (SA) is grappling with a severe food insecurity crisis exacerbated by socioeconomic challenges. This resulted in the Department of Basic Education (DBE) advocating for the establishment of vegetable gardens at schools. However, information on the suitability of the soils in SA for sustainably growing Beetroot is unavailable. This study aimed to assess the suitability of soils for sustainable Beetroot production at various schools in the Kgakotlou circuit. Four Secondary Schools were selected: Mothimako, Madipoane, Klaas Mothapo and Phomolong. A detailed soil survey was carried out to study soils in vegetable gardens. Soil samples were collected for laboratory analysis of physicochemical properties. The soil suitability was evaluated using the physicochemical properties of the soils and optimal soil requirements for Beetroot production. We found various soils in the schools, including Cambisols (Hutton and Nkonkoni), Leptosol (Glenrosa), Plinthosol (Westleigh), and Acrisols (Tshiombo and Tubatse). Portions of the gardens on Hutton and Westleigh soil were moderately suitable (S2), limited by electrical conductivity (EC). Meanwhile, portions of Tshiombo, Tubatse, and Nkonkoni were marginally suitable (S3), limited by pH and EC. Portions on Glenrosa soil at Klaas Mothapo and Phomolong were not suitable (NS) and were limited by shallow depth, soil pH and EC. The results reveal the importance of considering soil suitability before establishing vegetable gardens in school settings. Indexing soil suitability using the physicochemical properties of soil resources for sustainable beetroot production is proposed for schools in the Kgakatlou circuit and other parts of SA.

Introduction Urolithiasis, a prevalent urological condition (8-13% globally) exhibits regional variations, influenced by water quality, climate, health factors and diet. Sri Lanka with its tropical climate and dietary patterns is part of the "Stone Belt" of Asia. This study in Northern Sri Lanka examines urinary stone compositions and assesses the prevalence of metabolic disorders among urolithiasis patients. Methods This prospective cross-sectional study, conducted at tertiary urology centre from July 2022 to June 2023, focused on surgically treated urolithiasis patients. Institutional ethical clearance was obtained. Patient details and investigational findings were collected through questionnaires and data extraction forms. Stone analysis utilized Fourier transform infrared spectroscopy and detailed metabolic evaluation of 24 hour urine collection sample is carried out. Results This study followed 153 surgically treated urolithiasis patients, primarily male (64.3%), mean age 48.64. Ureteric colic (48.4%) was common, with kidney stones (45.8%) prevalent; 57.52% had recurrent stones. Diabetes mellitus (DM=23.5%) was the top comorbidity. Calcium oxalate monohydrate (COM) stones (78.4%) were most frequent, followed by uric acid (12.4%). COM predominated in 40-59 age group. No significant gender-stone type association. 86.9% had metabolic abnormalities, notably hypocitraturia (60.1%). 23% had both hypocitraturia and hypomagnesuria. Some metabolic disorders showed gender differences, with a marginal age-metabolic disorders association (p < 0.061). Urine oxalate levels were normal with higher variability in males. Conclusion Middle-aged males with urolithiasis commonly presented with ureteric colic and predominantly had calcium oxalate monohydrate stones. Recurrent stones were common, often accompanied by metabolic abnormalities such as hypocitraturia and hypomagnesuria, with diabetes mellitus as the primary comorbidity.

Evaluating genetic diversity in walnut (Juglans regia L.) populations is a rapid approach used by walnut breeding programs to distinguish superior genotypes. The present study identified the Hamedan province walnut population as one of the richest, most genetically diverse regions in Iran during 2019-2020. After initial screening, 47 genotypes were selected for further evaluation of pomological and phenological traits based on International Plant Genetic Resources Institute (IPGRI) descriptors. Nut and kernel weights among the selected genotypes ranged between 7.15-21.05 g and 3.0-10.8 g, respectively. Principal component analysis (PCA) categorized genotypes into three distinct groups while cluster analysis (CA) further categorized genotypes into one of four groups. Spearman correlation analysis showed a positive correlation (P <0.01) between nut weight (NWT), nut size, and kernel weight (KW) while a negative correlation (P <0.01) between shell thickness (STH) and packing tissue thickness (PTT) with kernel percentage (KP) was observed. Lastly, 10 of 47 genotypes (TAL8, TAL9, TAL10, TAL14, TAL19, TAL22, TB2, TB4, TB6, and RDGH5) were considered superior. Superior genotypes were late-leafing (25-40 days after the standard) and displayed a lateral bearing (LB) habit with heavy nuts (12.52–16.82 g) and kernels (6.53–8.15 g), thin-shells (1.06–1.25 mm), and lightly-colored kernels. Cuttings of superior genotypes were then grafted in the orchard. Detecting superior and late-leafing genotypes in this investigation suggests cultivars resistant to late-spring frost may soon be isolated.

Part 1 of this 2-paper series identified a wide and deep network of context, generative mechanisms and outcomes responsible for psychosocial development in a performance basketball club. In this – part 2 – study, the stakeholder’s programme theories were tested during a full-season ethnography of the same club. The findings confirm the highly individualised nature of each young person’s journey. Methodologically, immersion in the day-to-day environment generated a fine-grain analysis of the processes involved, including: i) sustained attentional focus; ii) structured and unstructured skill building activities; iii) deliberate and incidental support; and iv) feelings indicating personal growth. Personal development in and through sport is thus shown to be conditional, multi-faceted, time-sensitive and idiosyncratic. The findings of this two-part study are considered to propose a model of psychosocial development in and through sport. This heuristic tool is presented to support sport psychologists, coaches, club administrators and parents to deliberately create and optimise developmental environments.

Sensing Technology (ST) plays a key role in Structural Health Monitoring (SHM) systems. ST focuses on developing sensors, sensory systems or smart materials that monitor a wide variety of materials properties aiming to create smart structures and smart materials, using Embedded Sensors (ESs), and allowing continuous and permanent measurements of the structural integrity. The integration of ESs is limited to the processing technology to embed the sensor due to its high-temperature sensitivity and the possibility of damage during its insertion into the structure. In addition, the technological process selection is dependent on the base material composition, either metallic or composite parts. The selection of smart sensors or the technology underlying them is fundamental to the monitoring mode. This paper presents a critical review of the fundaments and applications of sensing technologies for SHM employing ESs, focusing on the actual developments and innovation of these, as well as analysing the challenges that these technologies present, to build a path that allows a connected world through distributed measurement systems.

This paper reports on the conception and implementation of a participatory approach within an agricultural research project aimed at fostering the transition towards organic in the Italian rice district. We investigate the relationships among scientists and stakeholders, exploring researchers’ attitudes, barriers, and potential in relation to participatory research. We use participant observation, in-depth interviews, and systematic cataloguing of communication documents, from the beginning to two years into project implementation, for a total period of three years. The results of the analysis show that, despite a high level of authoritative commitment to participation, scientists reveal a scarcity of knowledge and skills, and poor attitudes that come from a negative perception of participatory research. They engage in various forms of collaboration with stakeholders, as long as decision-making remains essentially in their hands. With the deep analysis of a case study, the paper contributes to the ongoing discussion on the quality of participatory agricultural research, in particular presenting evidence on the key role of researchers and their attitudes. The paper also contributes to the development of a culture of learning by doing, through honest monitoring and evaluation, and the capacity to learn from failure.

Given the high levels of overall volume of alcohol use, detrimental drinking patterns, and high levels of alcohol-attributable mortality and burden of disease, Lithuania implemented a series of alcohol control policies within a relatively short period of time (2008 to 2019). Based on their expected impact on alcohol consumption and alcohol-attributable harm, as well as their target population, the respective policies were classified using a set of objective criteria and expert opin-ion. The classification criteria included: positive vs. negative outcomes, mainly immediate versus delayed outcomes, and general population versus specific group outcomes. The judgement of the alcohol policy experts converged on the objective criteria, and, as a result, two tiers of inter-vention were identified: Tier 1 – general population interventions with an anticipated immediate impact; Tier 2 – other interventions aimed at the general population. In addition, interventions for specific populations were identified. This adaptable methodological approach to alcohol control policy classification is intended to provide guidance and support the evaluation of alcohol policies elsewhere, lay the foundation for the critical assessment of the respective policies to im-prove health and increase life expectancy, and to reduce crime and violence.

Machine Learning is increasingly and ubiquitously being used in the medical domain. Evaluation metrics like accuracy, precision, and recall may indicate the performance of the models but not necessarily the reliability of their outcomes. This paper assesses the effectiveness of a number of machine learning algorithms applied to an important dataset in the medical domain, specifically, mental health, by employing explainability methodologies. Using multiple machine learning algorithms and model explainability techniques, the project provides insights into the model workings to help determine the reliability of the machine learning algorithm predictions. The results are not intuitive. It was found that the models were focusing significantly on less relevant features and at times, unsound ranking of the features to make the predictions. The paper therefore argues that it is important for research in applied machine learning to provide insights into explainability of the models in addition to other performance metrics like accuracy. This is particularly important for applications in critical domains such as healthcare. A future direction is to investigate methods to quantify the effectiveness of the machine learning models in terms of the insights from their explainability.

Ethics values for public officers are important for enhancing cultural ethical levels and keeping society free from low-level barbarian ethical values. Barbarian ethics values are reflected in animal behavior, as in some countries security agencies, and a culture based on strength is dominant, especially in political and military parties. This study gave insight into the change in security agency duties from fighting criminal activities to managing criminal activities. Keeping high-level ethical values is essential for enhancing the behavior of public officers and stakeholders in any official institution at a standard level. This study provides stakeholders with a clear vision of the different defects in public institutions and how to improve and avoid negative ethical issues. By identifying all aspects of public officers and deviations from ideal ethical values for public officers,the negative ethical values in security agency officers have been noticed for a long time due to feelings of injustice or unfairness in native citizens of any country, generating mafia-based institutions instead of police departments or security agencies in any country.

This study aims to explore the utilization of deep learning models, specifically the innovative Multi-Modal Contextual Fusion Convolutional Neural Network (MSHA), for the detection and diagnosis of Adrenocortical Carcinoma (ACC) using computed tomography (CT) images. The objective is to develop an accurate and reliable model that can assist in the effective detection and classification of ACC. The study utilizes a dataset comprising contrast-enhanced CT images from 53 confirmed ACC patients. The MSHA model is employed, which incorporates a combination of mixed-scale dense convolution, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information techniques. Evaluation metrics are used to assess the performance of the MSHA model, and a comparison is made with other established models, including ResNet50, VGG16, VGG19, and InceptionV3. The evaluation of the MSHA model demonstrates high performance, with an accuracy of 96.65% and precision, sensitivity, specificity, and F1 score of 96.0%. These results highlight the MSHA model's capability in accurately detecting and classifying ACC. Furthermore, compared to other models, the MSHA model outperforms ResNet50, VGG16, VGG19, and InceptionV3, indicating its superior performance in ACC detection and diagnosis. The findings of this study suggest that the MSHA model holds significant potential in assisting healthcare professionals with the detection and diagnosis of ACC. With its advanced features and contextual fusion techniques, the MSHA model achieves high accuracy and performance. The results highlight the clinical significance of this novel model and its potential to improve patient management and outcomes in the detection and diagnosis of ACC using CT images.

To supply stable and high-quality power according to the advancement of industrial growth, electric power companies have performed maintenance of power facilities using various meth-ods. In the case of domestic power distribution facilities, there are limitations in performing di-agnostic management on all facilities owing to the large number of facilities; therefore, old fa-cilities are managed by the health index assessment method. The health index assessment com-prises only facility operation data and external environmental data and is managed only for four types of distribution facilities, including overhead/underground transformers and switchgear. In the case of extra high–voltage overhead wires, there is no standard for old replacement, despite the large number of wires, such as transformers and switchgear, and the large ripple effect of power failure in the event of a power outage. Therefore, in this paper, a health index assessment methodology for extra-high voltage overhead cables was developed. In this paper, we devel-oped an economic health index assessment methodology that additionally considers risk cost, which is different from the existing health index assessment method that uses only operational data and external environmental data to determine facility performance evaluation and aging replacement criteria. Using the health index assessment methodology developed in this paper, it is possible to expect a reduction in facility operating costs and investment costs from the per-spective of electric power companies through the replacement of old extra-high voltage over-head cables. In addition, from the perspective of consumers, it is expected to increase power re-liability and reduce the ripple effect of failure by preferentially replacing equipment with a high probability of failure.

The osteoarthritis (OA), the main cause of disability, is a chronic condition that most frequently affects older adults. As the population ages, the cost of treatment is placing pressure on the healthcare budget. As a result, it is imperative to evaluate the medicines' cost-effectiveness and the influence they have on health resource allocation. Hence, our study aims to summarize the cost and outcome of utilizing glucosamine in OA treatment. Authentic databases like Medline, Cochrane, and Scopus were adopted for the identification process up until July 2023. Our primary inclusion criteria centered on the economic evaluation of Glucosamine in OA treatments with provided the incremental cost-effectiveness ratio (ICER) at least. The Quality of Health Economic Studies (QHES) instrument was applied to grade the quality of the studies. A total of 7 qualified studies were selected and discussed the cost-effectiveness of glucosamine with or without other formulations. All of them demonstrated that glucosamine was cost-effective. There was an in-creasement of QALY when incorporating Glucosamine into conventional care. Moreover, Crystalline Glucosamine Sulfate (pCGS) was more cost-effective than the Other Formulations of Glucosamine (OFG). In overall, utilizing pCGS was more beneficial than OFG in terms both of cost and quality of life.

The research question in this article concerns how a competitive environment affects the learner (officer cadet's) personal leadership development and their relationship to their team and with future civilian foundations. More specifically, what are the possible learning effects of the “hidden” curriculum? This article investigates how a more than 250 years of leadership education provides new army officers with new skills and how such an environment may affect the cadets' leadership training. The paper builds on ethnographic data gathered during the three-year education program in most of the relevant practical locations and contexts. Findings regarding trust in their learning environment, cadets have reported scores of (Mean 2.83) on a 1 (low trust) to 5 (high trust) Likert scale, underpinning interviewdata regarding the lack trust in the academy and in their fellow cadets. Cadets also point out that competition has hindered their learning (Mean 2.50). These findings are interpreted in relation to possible negative effects stemming from internal competition and the evaluation system as a whole. The overall output of this system is a zero–sum game, and thus effects evaluative practices and learning processes. This study is of relevance to higher education officers responsible for designing learning environments.

Pulsed thermography is a vital technique in the nondestructive evaluation field. However, its data analysis can be complex and requires skilled experts. Advances in deep learning have yielded exceptional results, including image segmentation. Therefore, many efforts have been made to apply deep learning methods to data processing for nondestructive evaluation. Despite this, there is currently no public Pulsed thermographic dataset available for evaluating various spatial-temporal deep methods of segmenting pulsed thermographic data. This article aims to provide such a dataset and assess the performance of commonly used deep learning-based instance segmentation models on it. Additionally, the impact of the number of frames and data transformations on model performance is examined. The findings suggest that suitable preprocessing methods can effectively reduce the data size without compromising the deep models’ performance.

Infectious bursal disease (IBD) is one of the most endemic diseases of commercial poultry in Ethiopia. Vaccination has been practiced as the major means of IBD prevention and control. A study was conducted to determine and compare the immunogenicity of two commercially available IBD vaccines in broiler chicken with maternally derived antibody (MDA). Day-old chickens of 270 were randomly assigned to three groups, group 1 vaccinated with brand 1 vaccine at 7^th and 19^th days and group 2 with brand 2 vaccine at 15^th and 22^nd days while group 3 were kept as control. Six chickens were also randomly selected and bled on day 1 for differential leukocyte count (DLC) and determination of MDA. Representative chickens from each group were bled at 24^th and 42^nd days of age for antibody titration using the indirect ELISA test. DLC scores were determined in the 1^st and 24^th days. The result revealed highly significant differences (P = 0.001) between group 1 and group 2 in DLC at 24^th days of age. Antibody titers against IBD were differed significantly (P = 0.02) at 24^th and 42^nd days of age in broilers vaccinated with brand 1 and brand 2 vaccines. It is concluded that although both brands of vaccine induce an adequate immunological response at the end of the experiment, brand 1 vaccine has shown significantly high antibody titers against the IBDV and DLC than brand 2.

Efficient quality evaluation provides support for the timely and good maintenance of the lane line marking. This paper searches and optimizes the back propagation(BP) network model which referred to the analytic hierarchy process(AHP) model structure, as well as the number of nodes in the middle layer network. Based on this, a comprehensive evaluation method of multi-dimensional lane line quality such as shape, color and contrast is established. The experimental results show that the parameters of the model are more simplified, and the scoring and classification results of lane lines are more accurate.

The fast and flexible characteristics of badminton determine the necessity of its lunge, and fast lunge will have an important impact on the results of the game in actual combat. In lunge evaluation, the contact time to the ground is a key indicator. This article selects two middle-aged male badminton amateurs with similar body shape and age， but different skill levels as the research objects to carry out comparative experiments. The microseismic equipment is used to record the floor vibration which is caused by the running of badminton amateurs in sports. The microseismic signals of lunge are processed and analyzed by MATLAB software. And we evaluate the pro and cons of various time to touch the ground from amateurs with different skill levels. The research found that 1. Microseismic technology can detect the contact time to the ground. 2. High-level badminton amateurs have obvious advantages in the footwork contact time. Microseismic technology has a certain feasibility as a tool for evaluating the footwork contact time of badminton.

Opening gated-communities (GCs) has been widely discussed for urban inclusion and revitalization. With the policies of opening GCs being promoted in China, quantitative and comprehensive evaluation of the potential benefits is heavily needed. Taking Shanghai as an example, this study quantifies and analyzes the accessibility benefits and risks of opening GCs with factors including GC types, opening levels, travel modes, and travel destinations considered. We found that (1) opening GCs can bring 50m+ accessibility gains to 17% and 52% of the residents in Moderately Opening (MO) and Completely Opening (CO) scenarios, respectively. (2) Cycling benefits more than walking in all cases and scenarios. (3) For different GCs, conventional GCs have fewer benefits in MO but more in CO than the newly-established one. For different facilities, trips to bus stations demonstrate the largest accessibility gains. (4) The accessibility benefit of a residential building is highly determined by its closeness to the gates and relative location in the block. (5) Only 1% and 5-7% of external trips may penetrate the opened communities in MO and CO scenarios, respectively, which are far less than both expectation and the benefits. These findings precipitate at least two policy implications in China.

We report on an exploratory study conducted at a graduate school in Sweden with a humanoid robot, Baxter. First, we describe a list of potentially useful capabilities for a robot teaching assistant derived from brainstorming and interviews with faculty members, teachers, and students. These selected capabilities consist of reading, greeting, alerting, remote operation, clarification, and motion. Second, we present feedback on how the robot's capabilities, demonstrated in part with the Wizard of Oz approach, were perceived, and iteratively adapted over the course of several lectures, using the \EP tool. Third, we discuss observations and findings regarding the capabilities and the development process. Our findings suggest that using a social robot as a teaching assistant is promising using the chosen capabilities. We find that personalizing the capabilities and the role of embodiment are important topics to be considered in future work.

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (licensed) bands. Therefore, in this paper, we present a SDR based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe two use cases for the proposed framework.

Full-scale wind turbine technology has been widely developing in the recent years and condition monitoring techniques assist at the scope of making 100\% technical availability a realistic perspective. In this context, several retrofitting techniques are being used for further improving the efficiency of wind kinetic energy conversion. This kind of interventions is costly and, furthermore, the estimation of the energy enhancement is commonly provided under the hypothesis of ideal conditions, as for example absence of wakes between nearby turbines. A precise quantification of the energy gained by retrofitting is therefore precious in real conditions, that can be very different from ideal ones. In this work, three kinds of retrofitting are studied through the operational data of test case wind farms: improved start-up through pitch angle adjustment near the cut-in, aerodynamic blade retrofitting by means of vortex generators and passive flow control devices, extension of the power curve by raising cut-out and high wind speed cut-in. SCADA data are employed and reliable methods are formulated for estimating the energy improvement from each of the above retrofitting. Further, an insight is provided about wind turbine functioning under very stressing regimes, as for example high wind speeds.

This contribution illustrates the training evaluation system developed within the Master’s Program in Family and Community Mediation at Università Cattolica del Sacro Cuore in Milan. This is an interim evaluation, which focuses on the training process and which considers fundamental the collaboration with the subjects of the training. The peculiarity of this work concerns the possibility of inserting research within the training process, following a logic of mutual enrichment both in terms of content and learning. The contribution illustrates in detail the outcome and the process evaluation system, defining the perspective, the objectives, and the methodology of implementation. In particular, the outcome evaluation focuses on the distal and proximal outcomes of the training, while the process analysis focuses on the dynamics within the group of participants. Although further evaluations involving different training groups and other training processes are needed, this training evaluation system allows to shed light on both the topic and the context in which training is delivered. The integration between different points of view and several levels of analysis allows the researchers to deepen the individual path of each participant as well as to have feedbacks on the progress of the training group as a whole.

This research addresses the respiratory distress syndrome (RDS) in preterm newborns, caused by insufficient surfactant synthesis, which can lead to serious complications, including pneumothorax, pulmonary hypertension, and pulmonary hemorrhage, increasing the risk of a fatal outcome. By analyzing chest radiographs and blood gases, we specifically focus on the significant contributions of these parameters to the diagnosis and analysis of the recovery of patients with RDS. The study involved 32 preterm newborns, and the analysis of gas parameters before and after the administration of surfactants and inhalation corticosteroid therapy revealed statistically significant changes in values of parameters such as FiO2, pH, pCO2, HCO3 and BE (Sig.&lt;0.05), ehile the pO2 parameter showed a potential change (Sig.=0.061). Parallel to this, the research emphasizes the development of a lung segmentation algorithm implemented in the MATLAB programming environment. The key steps of the algorithm include preprocessing, segmentation, and visualization for a more detailed understanding of the recovery dynamics after RDS. These algorithms have achieved promising results, with a global accuracy of 0.93±0.06, precision 0.81±0.16 and an F-score of 0.82±0.14. These results highlight the potential application of algorithms in the analysis and monitoring of recovery in newborns with RDS, also underscoring the need for further development of software solutions in medicine, particularly in neonatology, to enhance the diagnosis and treatment of preterm newborns with respiratory distress syndrome.

This study evaluated the impact of the level of supplementation of Moringa oleifera leaves on the nutritional (proximate, mineral and vitamin content) as well as on the antioxidant capacities of smoothies made from a blend of pineapple, banana and apple. The beverage (smoothies) were supplemented with Moringa oleifera leaves at 1.5, 3.0 and 4.5% levels and evaluated for proximate, antioxidant (ferric reducing antioxidant power, FRAP and 2,2-Diphenyl-1-picryhydrazy, DPPH), mineral, vitamin, physicochemical and quality acceptability. The results showed that the moisture content of the beverage ranged between 49.24 – 78.62%, total ash: 1.01 – 9.71, crude fiber: 5.14 – 9.39%, crude fat: 0.72 – 1.86%, crude protein: 5.47 – 19.37% and carbohydrate: 3.65 – 16.99%. Calcium (12.03 -15.53) and potassium (17.22 -25.38) were the predominant mineral elements when compared to magnesium (1.51 – 3.05) mg/L. The vitamin contents ranged between 2.5 – 10.8 and 0.15 – 0.93 mg/L for vitamin C and E, respectively. Total phenolic contents ranged between 4.68 – 6.18 mg/ml while the total flavonoid contents ranged between 0.01 – 0.14 mg/ml. The radical scavenging abilities (DPPH) of the samples ranged between 16.05 – 88.77% while the ferric reducing antioxidant power (FRAP) ranged between 0.38 – 7.36 mg/ml. The brix values showed high sugar contents (15 – 18%) while the pH results showed that the sample was almost neutral at a range between 6.3 and 6.5. The overall quality (sensory) acceptability of the different quality parameters evaluated indicated that the control sample was more preferred. While supplementation with Moringa oleifera leaves significantly affected the sensory parameters, its addition nevertheless offers a potential avenue to obtain additional nutrients besides its improved antioxidative properties.

Abstract Issue Addressed: Men’s Sheds (‘Sheds’) have been identified as inherently health promoting and as potential settings to engage ‘hard-to-reach’ men in more structured health promotion initiatives. However, little is known about the sociodemographic or health and wellbeing characteristics of Shed members (‘Shedders’) on which such initiatives might be based. This study captures a baseline cross sectional analysis of Shedders (n=384) who participated in ‘Sheds for Life’, a health promotion initiative tailored to Sheds. Methods: Objective health measure, (body composition, blood pressure, blood lipids) captured via health screening as well as sociodemographic and health and wellbeing measures (physical activity, subjective wellbeing, mental health, social capital, cooking and diet) via questionnaires were assessed. Results: Participants were mostly over 65 years, retired with limited educational attainment. The majority were in the ‘at-risk’ categories for objective health measures, with most being referred to their GP following health screening. Older Shedders were also more likely to meet physical activity guidelines. Mental wellbeing was positively correlated with life satisfaction and increased social capital and these were also positively correlated with physical activity. Conclusions: Findings highlight the potential of Sheds in reaching a ‘hard-to-reach’ and ‘at-risk’ cohort of men. Despite a high prevalence of ‘at-risk’ objective health measures, participants report their health in positive terms. Future health promotion initiatives should capitalise on the inherent health promoting properties of Sheds. So what? Findings raise important implications for prioritising and designing health promotion initiatives in Shed settings.

Sport has the potential to support psychosocial development in young people. However, extant studies have tended to evaluate purpose-built interventions, leaving regular organised sport relatively overlooked. Moreover, previous work has tended to concentrated on a narrow range of outcomes. To address these gaps, we conducted a season-long ethnography of a youth performance sport club based on a novel Realist Evaluation approach [1]. We construed the club as a social intervention within a complex system of agents and structures. In this - Part 1 - account we detail the perceptions of former and current club parents, players and coaches, using them to build a set of programme theories. The resulting network of outcomes (i.e. self, emotional, social, moral and cognitive) and generative mechanisms (i.e., the attention factory, the greenhouse for growth, the personal boost, and the real-life simulator) spanning across multiple contextual layers provides a nuanced understanding of stakeholders’ views and experiences. This textured perspective of the multi-faceted process of development provides new insights for administrators, coaches and parents to maximise the developmental properties of youth sport, and signposts new avenues for research in this area.

According to the characteristics of the sustainable development of subway traffic, the establishment process of an evaluation index system is determined, and the evaluation method and basis are defined. The evaluation index system is established from the aspects of subway traffic sustainability, economic sustainability and urban coordination sustainability. The comprehensive evaluation method of the analytic hierarchy process (AHP) model is used to calculate the weights of comprehensive evaluation indexes at each level. Finally, the sustainable development model of Shijiazhuang subway traffic is evaluated. The results show that the proposed evaluation system and model reflect the degree of sustainable development of subway traffic and can be used for reference in the evaluation of regional subway traffic sustainable development.

As the necessity for safety and aesthetic of nightscape have arisen, the importance of nightscapes (i.e., nighttime landscape) planning has garnered the attention of mainstream consciousness. Therefore, this study is to suggest the guideline for nightscape planning using electroencephalography (EEG) technology and survey for recognizing the characteristics of a nightscape. Furthermore, we verified the EEG method as a tool for landscape evaluation. This study analyzed the change of relative alpha power and relative beta power and self-reporting of participants in order to investigate the correlation between EEG and fear according to twelve nightscape settings. Our findings indicated the corresponding measures of fear vary accordance with whether there was people or not, and the environmental settings (Built Nightscape Images; BNI vs Natural Nightscape Images; NNI). Based on our physiological EEG experiment, we provided a new analytic view of the nightscape. The approach we utilized enables a deeper understanding of emotional perception and fear among human subjects by identifying the physical environment which impacts how they experience nightscapes.

In the Italian context, the diffusion of online fake news about food is becoming increasingly fast-paced and widespread, making it more difficult for the public to recognize reliable information. Moreover, this phenomenon is deteriorating the relation with public institutions and industries. The purpose of this article is to provide a more advanced understanding of the individual psychological factors and the social influence contribute to the belief in food-related online fake news and the aspects that can increase or mitigate this risk. Data were collected with a self-report questionnaire between February and March 2019. We obtained 1004 valid questionnaires filled out by a representative sample of Italian population, extracted by stratified sampling. We used structural equation modelling (SEM) and the multi-group analyses to test our hypothesis. The results show that self-evaluation negatively affects the social-influence, which in turn positively affects the belief in online fake news. Moreover, this latter relationship is moderated by the readiness to change. Our results suggest that individual psychological characteristics and social influence are important to explain the belief in online fake news in the food sector; however, a pivotal role is played by the motivation of change lifestyle. This should be considered to engage people in clear and effective communication.

The article presents the results of research on a new method of spatial analysis of walls and buildings moisture. Due to the fact that destructive methods are not suitable for historical buildings of great architectural significance, a non-destructive method based on electrical tomography has been adopted. A hybrid tomograph with special sensors was developed for the measurements. This device enables the acquisition of data, which are then reconstructed by appropriately developed methods enabling spatial analysis of wet buildings. Special electrodes that ensure good contact with the surface of porous building materials such as bricks and cement were introduced. During the research, a group of algorithms enabling supervised machine learning was analyzed. They have been used in the process of converting input electrical values into conductance depicted by the output image pixels. The conductance values of individual pixels of the output vector made it possible to obtain images of the interior of building walls, both flat intersections (2D) and spatial (3D) images. The presented group of algorithms has a high application value. The main advantages of the new methods are: high accuracy of imaging, low costs, high processing speed, ease of application to walls of various thickness and irregular surface. By comparing the results of tomographic reconstructions, the most efficient algorithms were identified.

Preoperative assessment is crucial in surgical care, traditionally relying on physical examinations and paper-based questionnaires. The emergence of digital tools like Pathpoint® ePOA represents a significant advancement, aiming to enhance the efficiency, accuracy, and standardisation of preoperative evaluations. Pathpoint® ePOA is a cloud-based platform designed to integrate seamlessly with Electronic Health Records (EHRs), providing a comprehensive, data-driven approach to preoperative assessments. It supports improved risk stratification, optimised resource allocation, and enhanced patient engagement through features such as customisable templates and real-time data integration.Current research highlights that digital preoperative tools like ePOA offer notable advantages, including increased clinical capacity, better complexity stratification, and improved patient follow-up. Despite these benefits, gaps remain in comparative studies, detailed clinical outcomes, and patient engagement strategies, indicating areas for further exploration. Pathpoint® ePOA adheres to rigorous safety standards and risk management protocols, ensuring reliability and data security while contributing to improved surgical outcomes. The benefit-risk ratio for ePOA is favourable, underscoring its potential to advance preoperative care by optimising clinical workflows and enhancing patient safety.

Aim: Utilizing the subjective experience of nurse executives who have supervised nurses during a major disaster in a hospital setting, this study aims to describe the subjective experience of nurse executives (NE) who have supervised nurses’ response to major disaster. This paper will focus on strategies to support nursing response to disaster, specifically to strengthen resiliency and the ability to maintain function despite the shock of disaster, including those caused by climate changes. Methods: Semi-structured interviews were conducted with 11 hospital-based nurse executives who supervised nurses during some of the worst natural and human-made disasters in different regions of the United States. A phenomenological approach was used to analyze and describe emerging themes from qualitative data. Results: Three Nurse Executives demonstrated theme saturation for mitigation steps to augment traditional disaster readiness activities: 1.) Assessment of Human Infrastructure: Daily Skills Needed During Disaster Response, 2.) Identification and Study of Failure Points & Metrics, 3.) Strengthening Human Infrastructure: Rectifying Deficiencies), and 4.) Monitoring Metrics & Making Corrections During Conventional Periods. Conclusion: Mitigation steps may improve outcomes in hospital function during conventional times; therefore, may improve resiliency and the ability to maintain functions during major disasters, including climate change.

Globally, the demand for plant-based alternative food is increasing rapidly as these products are getting quite popular in vegan and vegetarians. However, it is still in the early stage and faces various technological challenges, but the imitation of sensory profile is the most challenging part as the products are meant to be an alternative of meat. The development of similar product to meat requires an accurate selection of ingredients and processing. An understanding about the sensory profile can help to construct the product and technologies that are consumer centric and sustainable. In this review, we focus on the comparative differences in the sensory profile of animal meat and plant-based meat alternative specially in the color, texture and flavor, along with the method used to resemble them. The paper also explains about the sensory evaluation and how it affects the consumer preference and acceptability. Additionally, a direction to further research for developing better plant-based alternative products has also been suggested.

The objective of this study is to design and synthesize substituted η6-chromium tricarbonyl metal complexes carrying o-carborane units as potential boron neutron capture therapy (BNCT) agents. In this study, 1,2-Diphenyl-o-carborane units were used as starting materials to generate biologically active species. We investigated how the structural changes of 1,2-diphenyl-o-carborane substituted with chromium(0) tricarbonyl affect the biological properties; [(CO)3Cr]Ph2C2 (2) and [(CO)3Cr]2Ph2C2 (3) species were produced in moderate yields. The molecular structures of compounds 1–3 were identified and established by infrared (IR), 1H, 11B, and 13C nuclear magnetic resonance (NMR), and X-ray crystallography analyses. Crystal structures of o-carboranyl chromium complexes 1 [a = 10.859(1) Å, b = 24.953(3) Å, c = 13.938(2) Å, β = 111.854(2)º], 2 [a = 10.621(3) Å, b = 17.056(5) Å, c = 12.174(4) Å, β = 106.622(5)º], and 3 [a = 17.540(2) Å, b = 18.060(2) Å, c = 19.484(4) Å, α = 105.746(2)º, β = 110.226(2)º, γ = 91.256(2)º] were obtained. In vitro study using B16 and CT26 cancer cells containing the triphenyl-o-carboranyl chromium (0) complexes Ph3C2BCr2 and Ph3C2BCr3, which we have previously reported, the compounds 2 and 3 accumulated at higher levels than compounds Ph3C2BCr2 and Ph3C2BCr3. However, the phenylated o-carboranyl chromium(0) complexes have been found to be more cytotoxic than p-boronophenylalanine (BPA).

Wind turbine upgrades have been spreading in the recent years in the wind energy industry, with the aim of optimizing the efficiency of wind kinetic energy conversion. This kind of interventions has material and labor costs and it is therefore fundamental to estimate realistically the production improvement. Further, the retrofitting of wind turbines sited in harsh environments might exacerbate the stressing conditions to which wind turbines are subjected and consequently might affect the residue lifetime. This work deals with a case of retrofitting: the testing ground is a multi-megawatt wind turbine from a wind farm sited in a very complex terrain. The blades have been optimized by installing vortex generators and passive flow control devices. The complexity of this test case, dictated by the environment and by the features of the data set at disposal, inspires the formulation of a general method for estimating production upgrades, based on multivariate linear modeling of the power output of the upgraded wind turbine. The method is a distinctive part of the outcome of this work because it is generalizable to the study of whatever wind turbine upgrade and it is adaptable to the features of the data sets at disposal. In particular, applying this model to the test case of interest, it arises that the upgrade increases the annual energy production of the wind turbine of an amount of the order of the 2%. This quantity is of the same order of magnitude, albeit non-negligibly lower, than the estimate based on the assumption of ideal wind conditions. Therefore, it arises that complex wind conditions might affect the efficiency of wind turbine upgrades and it is therefore important to estimate their impact using data from wind turbines operating in the real environment of interest.

Background: Patients undergoing brain tumor resection experience changes to their neurocognitive abilities, many of which can be difficult to predict. We hypothesized that changes in brain connectivity could predict changes in neurocognitive functioning, demonstrating the potential for brain connectivity aware surgical planning to provide enhanced outcomes for patients. Methods: Patients underwent functional and diffusion MR scanning and neuropsychological testing before tumor resection and two weeks post-resection. Using this functional and diffusion imaging, we measured changes in the topology of the functional and structural graph networks, respectively. From the neuropsychological testing scores, we derived a composite score that describes a patient’s overall level of neurocognitive functioning. We then used a multiple linear regression model to test if structural and functional connectivity measures could predict changes in composite scores. Results: Twenty-one subjects completed imaging and neuropsychological evaluation both before and after surgery. The multiple linear regression model showed that changes in functional local efficiency were inversely correlated with changes in composite score (p

In this paper, we derive the distribution of eigenvalues for a 2×2 random confusion matrix stemming from a machine learning (ML) evaluation problem. Additionally, we present the distributions of both the matrix’s trace and the difference between the two traces of random confusion matrices. We also illustrate the application of these derived distributions in calculating the superiority probability of four baseline ML models.

Underground storage of natural gas has the characteristics of clean and low-carbon, and has the ability to provide sustainable and stable supply. It is a very high-quality green energy that can increase the storage efficiency of gas storage through fracturing, achieving the sustainable development goal of "Carbon Peaking and Carbon Neutrality". The accurate evaluation of the fracability of a reservoir is an important prerequisite for reservoir fracturing design and post fracturing productivity evaluation. At present, research on fracability is mainly based on qualitative characterization or quantitative evaluation based on rock mechanics and fracturing construction parameters, which cannot fully reflect the rock composition and structure of each stage. Firstly, based on logging data, this paper analyzes the evolution laws of strain energy such as elastic properties, pre-peak dissipation energy, and post-peak fracture energy during the transition of rock materials from plastic deformation to brittle fracture in an energy perspective, and determines the key energy that affects the brittle characteristics of rocks. Secondly, a brittleness index evaluation approach has been established that can comprehensively reflect the mechanical properties of rocks during pre-peak deformation and post-peak damage stages. In addition, this article focuses on the impact of reservoir stratigraphic environment by combining the influence of geo-stresses with the rock brittleness index, and proposes a new method for evaluating reservoir fracability. Finally, this paper conducts a study on the fracability evaluation of three wells in a gas storage facility in eastern China. The results indicate that low modulus and fracability coefficient are beneficial for fracturing, thereby improving the gas production and peak shaving ability of gas storage.

Based on survey data from 297 beef cattle farmers in five provinces, Hunan, Ningxia, Inner Mongolia, Shandong and Gansu, the impact of the package of support policies on farmers' beef cattle production was assessed by means of propensity score matching (PSM). The results showed that the package of support policies, the education level of the household head, participation in beef cattle professional cooperatives and taking out loans for beef cattle farming had significant positive impacts on farmers’ inventories of beef cattle and breeding cows. The current package of beef cattle support policies implemented by the national and local governments has significantly promoted the production of beef cattle by farmers, and the effects of the policy implementation have been positive. The implementation of the relevant support policies led to increases in farmers’ inventories of approximately 17 head of beef cattle and approximately 9 head of breeding cows. The contribution rates of the policy implementation to the beef cattle and breeding cow inventories reached 52.96% and 67.30%, respectively.

Pregnant women with diabetes often present impaired fetal growth, which is less common if maternal diabetes is well-controlled. However, developing strategies to estimate fetal body composition beyond fetal growth that could better predict metabolic complications later in life is essential. This study aimed to evaluate subcutaneous fat tissue (femur and humerus) in fetuses with normal growth among pregnant women with well-controlled diabetes using a reproducible 3D-ultrasound tool and offline TUI (Tomographic Ultrasound Imaging) analysis. Additionally, three artificial intelligence classifier models were trained and validated to assess the clinical utility of the fetal subcutaneous fat measurement. A significantly larger subcutaneous fat area was found in three-femur and two-humerus selected segments of fetuses from women with diabetes compared to the healthy pregnant control group. The full classifier model that includes subcutaneous fat measure, gestational age, fetal weight, fetal abdominal circumference, maternal body mass index, and fetal weight percentile as variables, showed the best performance, with a detection rate of 70%, considering a false positive rate of 10%, and a positive predictive value of 82%. These findings provide valuable insights into the impact of maternal diabetes on fetal subcutaneous fat tissue as a variable independent of fetal growth.

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

Osteoarthritis (OA) is the degeneration of cartilage in joints that results in bones rubbing against each other, it causes uncomfortable symptoms such as pain, swelling, stiffness, and can lead to disability. It usually occurs in the elderly and causes a large medical burden. The aim of this study is to evaluate cost-effectiveness between the standard treatment for osteoarthritis and the standard treatment with added crystalline glucosamine sulfate at various stages. The Markov analysis modelling was applied to evaluate the effect of both adding glucosamine compared to standard treatment from a societal perspective during whole patients’ lifetimes. Data input was collected by review in previous studies. The outcome was measured in quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) from a societal perspective was ap-plied with 3%-discounted for all cost and outcome. One-way analysis via Tornado diagram was performed to investigate the change of factors in model. In general, the adding glucosamine into the standard treatment proved to be more cost-effectiveness compared to the standard treatment. Particularly, early stage adding glucosamine in the treatment was cost-effectiveness then post-stage adding glucosamine. The addition of supplementing crystalline glucosamine sulfate to whole regimen at any stage was cost-effectiveness at willingness-to-pay (WTP) threshold

The aim of the work was to carry out an ergonomic assessment of the workload when working with a chainsaw during motor-manual tree processing. Wearable technology was used, namely Garmin, Biostrap and Whoop devices, which are generally available. The dependence of the heart rate (HR) on physical workload was examined to calculate Heart Rate Index. The case study was done with one worker, three variations of chainsaw devices cutting the poplar wood. It was proved that the use of a heavier work tool, MS 500i /90 cm 9,3 kg, significantly contributes both to the creation of a non-physiological working position and to an increase in the energy required to perform work, which was represented by an increase in heart rate. With a lighter work tool and a shorter cutting blade, both a decrease in heart rate and a reduction in the working time were performed in a non-physiological position. The results can be used in common practice for workers´ self-assessment to increase safety and health protection at work or work productivity not only in motor-manual processing in forestry related professions.

Purpose: This study evaluates the performance of the Early Intervention Physiotherapist Framework (EIPF) for injured workers. This study provides a proper follow-up period (3 years) to examine the impacts of the EIPF program on injury outcomes such as return to work (RTW) and time to RTW. This study also identifies the factors influencing the outcomes. Methods: The study was conducted on data collected from compensation claims of people who were injured at work in Victoria, Australia. Injured workers who commenced their compensation claims after the first of January 2010 and had their initial physiotherapy consultation after the first of August 2014 are included. To conduct the comparison, we divided the injured workers into two groups: physiotherapy services provided by EIPF-trained physiotherapists (EP) and regular physiotherapists (RP) over the three-year intervention period. We used three different statistical analysis methods to evaluate the performance of the EIPF program. We used descriptive statistics to compare two groups based on physiotherapy services and injury outcomes. We also completed survival analysis using Kaplan-Meier curves in terms of time to RTW. We developed univariate and multivariate regression models to investigate whether the difference in outcomes achieved after adjusting for significantly associated variables. Results: The results showed that physiotherapists in the EP group on average dealt with more claims (over twice as many) than those in the RP group. Time to RTW for the injured workers treated by the EP group was significantly lower than for those who were treated by the RP group, indicated by descriptive, survival and regression analyses. Earlier intervention by physiotherapists led to earlier RTW. Conclusion: This evaluation showed that the EIPF program achieved successful injury outcomes three years after implementation. Motivating physiotherapists to intervene earlier in the recovery process of injured workers by initial consultation helps to improve injury outcomes.

The overlap of visual items in data visualization techniques is a known problem aggravated by data volume and available visual space issues. Several methods have been applied to mitigate occlusion in data visualizations, such as Random Jitter, Transparency, Layout Reconfiguration, Focus+Context Techniques, etc. This paper aims to present a comparative study to read visual variables values with partial overlap. The study focuses on categorical data representations varying the percentage limits of partial overlap and the number of distinct values for each visual variable: Hue, Lightness, Saturation, Shape, Text, Orientation, and Texture. A computational application generates random scenarios for a unique visual pattern target to perform location tasks. Each scenario presented the visual items in a grid layout with 160 elements (10 x16), each visual variable had from 3 to 5 distinct values encoded, and the partial overlap percentage applied, represented by a gray square in the center o each grid element, were 0% (control), 50%, 60%, and 70%. Similar to the preliminary tests, the tests conducted in this study involved 48 participants organized into four groups, with 126 tasks per participant, and the application captured the response and time for each task performed. The result analysis indicates that the Hue, Lightness, and Shape visual variables are robust to high percentages of occlusion and gradual increase in encoded visual values. The Text visual variable show promising results for accuracy, and resolution time was a bit higher than the last visual variables mentioned. In contrast, the Texture visual variable presented lower accuracy to high levels of occlusion and more different visual encoding values. At last, the Orientation and Saturation visual variables got the highest error and worst perfomance rates during the tests.

By using various skill scores and spatial characteristics of spatial verification methods and tradi-tional techniques of the model evaluation tool (MET, V10.0.0), the gridded precipitation obser-vation CMPAV (V2.0) and three datasets that derived from local (LOC), Shanghai (SHA), and Grapes (GRA) model respectively are conducted to assess the 3 lead day rainfall forecast with 0.5-day intervals during summer of 2020 over central east China. Results have shown that LOC generally outperforms the other two for most skill scores but usually with relatively larger un-certainties than SHA, and it has the least displacement errors for moderate rainfall among the three datasets. However, the rainfall of GRA has been heavily underestimated and accompanied with large displacement error. Both LOC and SHA have shown almost equitable abilities in forecasting convection and rainstorms of the large area but with a slightly over-forecast of local convection, while LOC likely over-forecasts the local rainstorms. In addition, SHA slightly favors over-forecast on a broad scale range and a broad threshold range, and LOC slightly misses the rainfall exceeding 100 mm. Generally, for a broadly comparative evaluation on rainfall, the popular dichotomous methods should be recommended under considering reasonable classifi-cation of thresholds if the accuracy is highly demanded. And most spatial methods should be suggested to conduct with proper pre-handling of non-rainfall event cases. Especially, the veri-fications including spatial characteristic difference information could be recommended in a computationally sufficient environment.

With the rise of piano teaching in recent years, many people have joined the team of piano learners. However, the expensive cost of manual instruction and the unique one-on-one teaching model have made piano learning an extravagant event. Most existing approaches based on the audio modality aim to evaluate piano players' skills. Unfortunately, these methods ignored the information contained in the video, which led to a one-sided and simplistic evaluation of the piano player's skills. More recently, multimodal-based methods are proposed to assess the skill level of piano players using both video and audio information. However, existing multimodal approaches use shallow networks to extract video and audio features, which are deficient in extracting complex spatio-temporal and time-frequency features from piano performance. Furthermore, the fingering and the pitch-rhythm information of the piano performance is contained in the spatio-temporal and time-frequency features, respectively. In the paper, we propose a ResNet-based audio-visual fusion model that combines video and audio features to assess the skill level of piano players. Firstly, ResNet18-3D is used as the backbone network for our visual branches, which can extract feature information from the video data. Then, we consider ResNet18-2D as the backbone network of the aural branch and extract the feature information from the audio data. The extracted video features are fused with the audio features to generate multimodal features for the final piano skill evaluation. The experimental results on the PISA dataset show that our proposed audio-visual fusion model, with a validation accuracy of 70.80%, outperforms the state-of-the-art methods in both performance and efficiency. Then, we also explore the impact of different layers of ResNet on model performance, and the experimental results show that the audio-visual fusion model dealing with the piano skill assessment problem can make full use of both feature information when the number of video features is close to the number of audio features.

Smart local energy systems (SLES) have been promoted in policy as a solution to decarbonisation challenges which also bring wider benefits, such as community prosperity and energy affordability. But the combination of conditions required to enable their successful emergence and operation are still to be elaborated. This paper reports on the development of a Theory of Change (ToC) for the “societal project” of emergence of SLES with benefits. ToC is a process of making explicit the causal links by which activities lead to outcomes, surfacing assumptions, and recognising possible unintended consequences. We describe the ToC development process, involving consultation and collaboration across a research consortium. It consists of layers (e.g. users, skills, data and digital), and shows conditions considered necessary to deliver SLES, and for these to deliver wider benefits. It also provides interactive links to evidence emerging from the consortium, as well as policy/governance conditions and metrics. We reflect on potential uses of the ToC – internally to the consortium and externally – along with challenges we encountered in pursuing this approach. Policy implications relate to the importance of enabling conditions across multiple sectors, the absence of any of which could inhibit delivery of either SLES or their ensuing benefits.

The operation status of manufacturing equipment is directly related to the reliability of the operation of manufacturing equipment and the continuity of operation of the production system. Based on the analysis of the operation status of manufacturing equipment and its characteristics, it is proposed that the concept of assessing the operation status of manufacturing equipment can be realized by applying real-time acquisition of accurate inspection data of important parts of weak motion units and comparing them with their motion status evaluation criteria. Through the study of the application characteristics of fractional-order calculus theory, a differential data fusion model based on the fractional-order differential operator is established. The advantages of Internet of Things (IoT）technology and fractional order differential fusion algorithm are integrated to obtain real-time high-precision data of the operating parameters of manufacturing equipment, and the research objective of operating condition assessment of manufacturing equipment is realized. The feasibility and effectiveness of the method are verified by the application of the method in machining center operation status assessment.

Fusarium Head Blight (FHB) is a destructive disease affecting the grain yield and quality of wheat, barley, rye and triticale. Developing varieties with genetic resistance is integral to successfully managing FHB. However, significant knowledge gap exists in the genetic diversity present in triticale for FHB resistance. This information is critical for breeding new varieties of triticale as its production continues to increase. In the present study, a set of 298 winter triticale accessions from a worldwide collection were screened for their type-2 FHB resistance in an artificially inoculated misted nursery with high levels of inoculum density. Most of the triticale accessions were susceptible to FHB, and only 8% of accessions showed resistance in the field nursery screening. The resistant accessions identified in the nursery screening were selected and further screened for three years in greenhouse conditions. Seven accessions were found to show robust FHB resistance over the three years of greenhouse testing. Thirteen accessions showed significantly lower levels of Deoxynivalenol accumulation when compared to the susceptible triticale control. The accessions identified in the study will be useful in triticale and wheat breeding programs for enhancing FHB resistance and reducing DON accumulation.

Systems thinking is a valuable skill that may be required for an individual to be promoted in the business arena to managerial or leading positions. Thus, assessing systems thinking skills is an essential transaction for decision-makers in the organization as a preceding step to the promotion decision. One of the well-known and validated tools for this task is a questionnaire. However, because some of the questions invade the employee / candidate’s privacy, the answer may be biased. In this paper, we consider this potential bias, a phenomenon that is becoming more and more significant as privacy concerns and awareness continuously increase in the modern digital world. We propose a formal methodology to optimize the questionnaire based on the privacy sensitivity of each question, thereby providing a more reliable assessment. We conducted an empirical study (n=142), and showed that a systems skills questionnaire can be enhanced. This research has a significant contribution to improving the systems skills assessment process in particular, and also lays the foundations for improving the evaluation of other skills / traits.

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

This study aimed to evaluate the capacity of Saccharomyces cerevisiae for Cadmium absorption in Milk. Nowadays one of the most serious problems is heavy metals pollution. Applying microorgaisms as a novel biotechnology is so useful especially in foodstuffs. Among the biosorbents for heavy metals’ removal, Saccharomyces cerevisiae has got an increasing attention due to its popularity in food industry. In this regard, the effects of some important factors such as the initial metal concentration, biomass concentration and contact time on the biosorption capacity of Saccharomyces cerevisiae were studied. The biosorption was analyzed by the inductively coupled plasma mass spectrometer (ICP-MS). The maximum Cd bioremoval (70%) was at 80 μg/L of this metal concentration in milk samples containing 30×10⁸ CFU Saccharomyces cerevisiae at the end of storage time (the 4^th day). There were no significant differences in sensory and physicochemical properties of milk samples during storage (p < 0.05). The isotherm studies followed by two popular models; Langmuir and Freundlich and the results showed a better fit to the Langmuir isotherm. All together, the results of this project demonstrated that the approach of using this valuable yeast, could be applied for food and drinks’ detoxification and producing healthier foods.

In order to evaluate the economy of superhighway, on the basis of the analysis of the cost of the ordinary expressway and high speed railway, the cost of superhighway is estimated. On this basis, the standard of the toll of superhighway at all levels is determined by reference to the standard of the construction cost and the toll collection standard of the ordinary expressway. According to the toll collection standard of superhighway and the fuel consumption cost of superhighway at all levels, the cost of single car and the single person cost of superhighway are calculated. Based on the analysis of highway passenger transport, railway passenger transport and civil aviation ticket price, the single person cost per kilometer of the above travel modes is calculated and compared with the single person travel cost per kilometer of superhighway. The results show that the single person cost of superhighway is between 0.29 and 0.47 yuan /km, which is 0.28 yuan /km higher than the highway bus, 0.18 yuan /km higher than the ordinary expressway self driving and 0.23 yuan /km higher than the express train, but 0.78 yuan/km lower than that of the first class seat of high-speed train, and is 0.92 yuan/km far lower than that of civil aviation flight economy class and 2.42 yuan/km lower than the business class. Therefore, the superhighway trip has certain advantages in economy.

The introduction of innovative digital tools for supporting manufacturing processes has far-reaching effects on an organizational and an individual level due to the development of Industry 4.0. The FACTS4WORKERS project funded by H2020, i.e. Worker-Centric Workplaces in Smart Factories, aims to develop user-centered assistance systems in order to demonstrate their impact and applicability at the shop floor. To do so it is important to understand how to develop such tools and how to assess if advantages can be derived from the created ICT system. This study introduces the technology of a workplace solution that is linked to a specific industrial challenge. Subsequently, a 2-stepped approach to evaluate the presented system is discussed. Heuristics, which are an output of project “Heuristics for Industry 4.0”, are used to test if the developed solution covers critical aspects of socio-technical system design. Insights into the design, development and holistic evaluation of digital tools at the shop floor should be shown.

Plants are such important keys of biological part of our environment, supply the human life and creatures. Understanding how the plant’s functions react with our surroundings, helps us better to make plant growth and development of food products. It means the plant phenotyping gives us bio information which needs some tools to reach the plant knowledge. Imaging tools is one of the phenotyping solutions which consists of imaging hardware such as the camera and image analysis software analyses the plant images changings such as plant growth rates. In this paper, we proposed a preprocessing algorithm to eliminate the noise and separate foreground from the background which results the plant image to help the plant image segmentation. The preprocessing is one of important levels has effect on better image segmentation and finally better plant’s image labeling and analysis. Our proposed algorithm is focused on removing noise such as converting the color space, applying the filters and local adaptive binarization step such as Niblack. Finally, we evaluate our algorithm with other algorithms by testing a variety of binarization methods.

Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable whole-body imitation and task-oriented teleoperation via imitation are challenging issues. In this paper, a novel comprehensive and unrestricted real-time whole-body imitation system for humanoid robots is designed and developed. To map human motions to a robot, an analytical method called geometrical analysis based on link vectors and virtual joints (GA-LVVJ) is proposed. In addition, a real-time locomotion method is employed to realize a natural mode of operation. To achieve safe mode switching, a filter strategy is proposed. Then, two quantitative vector-set-based methods of similarity evaluation focusing on the whole body and local links, called the Whole-Body-Focused (WBF) method and the Local-Link-Focused (LLF) method, respectively, are proposed and compared. Two experiments conducted to verify the effectiveness of the proposed methods and system are reported. Specifically, the first experiment validates the good stability and similarity features of our system, and the second experiment verifies the effectiveness with which complicated tasks can be executed. At last, an imitation learning mechanism in which the joint angles of demonstrators are mapped by GA-LVVJ is presented and developed to extend the proposed system.

Irrigation and fertilization are indispensable links in the jujube planting industry in southern Xinjiang, China. However, the water and fertilizer integration effects on jujube growth and fruit quality remain unclear. A two-year water and fertilizer optimization coupling test was conducted to determine the optimal water- and nutrient-supply scheme. The three-factor randomized block experiment included water (W), nitrogen (N), and phosphorus (P). According to the principal component analysis of each index, each treatment’s comprehensive score was obtained. Using yield and economic regression models, the theoretical value and yield value of the optimal economic benefit are inferred. When W, N, and P were applied together, the fruit quality and yield of each treatment significantly differed, and the vitamin C, soluble sugar, and sugar–acid ratio increased significantly with an increase in nitrogen fertilizer. However, the titratable acid decreased. An increase in irrigation and nitrogen application significantly increased fruit yield. The comprehensive score was the highest in the N3P3W2 treatment, which improved fruit quality, and the lowest in the N4P3W2 treatment. When the amounts of N, P, and W were 275.56 kg·hm-2, 413.66 kg·hm-2, and 7278.19 m3·hm-2, respectively, the theoretical economic benefit was the best. The N4P3W2 treatment is the optimal treatment.