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.

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.

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.

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.

Change Detection (CD) of aerial images refers to identifying and analyzing changes between two or more aerial images of the same location taken at different times. The CD is a highly challenging task due to the need to distinguish relevant changes, such as urban expansion, deforestation, or post-disaster damage assessment, from irrelevant ones, such as light conditions, shadows, and seasonal variations. Many CD papers have recently been published, where most of the papers that proposed a new model contained a comparison between their proposed and state-of-the-art (SOTA) models. While many recent studies propose new deep learning (DL) models for improving CD performance, their comparative analyses are often restricted, lacking comprehensive insights into the proposed models' real-world generalizability, robustness, and performance trade-offs across diverse change characteristics. This paper presents a novel generic framework to systematically benchmark and assess DL-based CD models through three parallel pipelines: 1) cross-testing models on diverse benchmark datasets to evaluate generalization, 2) robustness analysis against different image corruptions, and 3) multi-faceted contour-level analytics evaluating detection sensitivity to change size/complexity. The framework is applied to comparatively evaluate five state-of-the-art DL-based CD models - Changeformer, BIT, Tiny, SNUNet, and CSA-CDGAN. Extensive experiments unveil each model's strengths, limitations and biases, highlighting their relative proficiencies in generalizing across data distributions, resilience to noise corruption, and discriminative capabilities for changes of varying characteristics. The proposed benchmarking framework demonstrates significant potential for guiding the selection of suitable CD models tailored to specific application requirements by comprehensively evaluating their generalizability, robustness, and detection capabilities across diverse real-world scenarios. This systematic evaluation approach can drive future research into developing more robust and versatile CD solutions aligned with practical needs.

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.

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.

The meaning of a good social outcome in land use transport policy/planning has been relatively underdeveloped, compared to economic and environmental sustainability goals, but this is now changing. Cities are increasingly prioritizing reducing social exclusion, with the allied intent of providing all residents with equitable access to the benefits of their city. However, in jurisdictions that use cost-benefit analysis to guide government decision-making, this poses a challenge: monetization of the benefits of reducing social exclusion is poorly developed. An evaluation gap thus confronts benefit-cost based assessment of initiatives intended to reduce social exclusion, compared to initiatives directed towards societal economic and environmental goals. This is a particular problem for public transport services that primarily enable people at risk of mobility-related social exclusion to access more opportunities in their society (social transit). The benefits of reducing social exclusion associated with these services have not been monetized, so social transit initiatives are poorly placed to argue their merits against competing initiatives where benefit monetization is more advanced (e.g., mass public transport and roads). The paper summarizes Australian research that has developed monetized measures for the value of increased trip making, bridging/bonding social capital, sense of community and several conceptions of wellbeing, and of reducing neighbourhood disadvantage, as these contribute to reducing social exclusion. New Singaporean research on the value of trip making to support reduced exclusion is also presented, affirming the Australian trip values. Trip values are then used in case study examples to show they can make a material difference to the societal worth of initiatives intended to reduce exclusion. Using these trip values, and other pathway values linked to reducing social exclusion, closes or at least substantially reduces the evaluation gap confronting social goal achievement in land use transport policy and planning, strengthening the case for reducing exclusion. These values will assist jurisdictions that are seeking to provide their residents with more equitable access to the benefits of their city.

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.

Although the beneficial health effects of prebiotics have been demonstrated in numerous research papers, its incorporation into daily food remains unfamiliar to consumers. This work evaluates the resistant maltodextrin (RMD) addition in the sensory attributes of pasteurized orange juice, together with the physico-chemical properties and the aromatic profile. RMD addition moderately improved almost all sensory attributes evaluated by panellists. It also proportionally increased °Brix together with density and decreased acidity. Colour changes were registered with higher RMD concentrations. Orange pulp presence affected the volume particle size distribution analysis while RMD addition did not exercised any effect. The aroma volatile compounds were also analysed. Pulp-added samples marked higher alcohol and aldehydes quantity, whereas pulp-free samples registered higher terpenes and terpenoids values. Ketones and acids were also quantified. RMD had a moderate impact on volatile compounds quantifications, playing the orange pulp presence a much more decisive role. A correlation analysis was also performed to relate instrumental and sensorial determinations for all samples. This work proves that the addition of RMD to orange juice is technologically feasible while also achieving a good response at the sensory level.

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

In recent years, underwater exploration for deep-sea resource utilization and development has a considerable interest. In an underwater environment, the obtained images and videos undergo several types of quality degradation resulting from light absorption and scattering, low contrast, color deviation, blurred details, and nonuniform illumination. Therefore, the restoration and enhancement of degraded images and videos are critical. Numerous techniques of image processing, pattern recognition and computer vision have been proposed for image restoration and enhancement, but many challenges remain. This survey presents a comparison of the most prominent approaches in underwater image processing and analysis. It also discusses an overview of the underwater environment with a broad classification into enhancement and restoration techniques and introduces the main underwater image degradation reasons in addition to the underwater image model. The existing underwater image analysis techniques, methods, datasets, and evaluation metrics are presented in detail. Furthermore, the existing limitations are analyzed, which are classified into image-related and environment-related categories. In addition, the performance is validated on images from the UIEB dataset for qualitative, quantitative, and computational time assessment. Areas in which underwater images have recently been applied are briefly discussed. Finally, recommendations for future research are provided and the conclusion is presented.

Background: Previous in vitro and in vivo studies have demonstrated that storage of cooked rice at 4 °C for 24 h and reheating to 65 °C significantly reduced starch digestibility and postprandial glycaemic responses. Moreover, the effect was greater for parboiled rice compared to other rice varieties commonly consumed in New Zealand. This study aimed to evaluate consumer preferences of related sensory attributes and consumer acceptability of several rice varieties freshly cooked or reheated. Method: Sixty-four consumers volunteered and recorded on Visual Analoge Scales their preference and acceptability of freshly prepared or cold-stored and reheated medium grain white, medium grain brown and parboiled rice. Results: All six rice samples were accepted by participants (average 54%). Reheated parboiled rice and reheated medium grain brown rice were both accepted by participants as a preferred staple meal compared to other rice samples. Among all rice samples, the sweetness and the flavour of freshly cooked warm medium-grain white rice were less preferred (scored 42.1% and 45.0% respectively) compared with other samples (P = 0.05). Participants who prepared and consumed brown rice at home regularly (more than 10 times per month), preferred the reheated brown rice (73.8% (67.4, 80.2)) and reheated parboiled rice (74.3% (67.9, 80.7)) (P < 0.001). Conclusions: It is suggested that reheated parboiled rice, with the lowest starch digestibility and glycaemic impact (both in vitro glucose release and in vivo glucose response) could be accepted as a healthier alternative for the daily staple meal.

Background: With the trend of intelligent display, the interface design of in-vehicle HUD is an expanding research field; Methods: To solve the subjectivity and uncertainty in the optimization of HUD interface design schemes, this paper proposed a hybrid scheme evaluation and optimization method based on entropy weight and VIKOR. The entropy weight method was used to reduce the subjectivity the decision-maker's weighting and obtain the objective weight of each indicator; The VIKOR method was used to obtain the best ranking of alternative schemes, and then the optimal interface design scheme was selected; Results: The evaluation of in-vehicle HUD interface design schemes were taken as an example for verification and calculation. The results showed that this method considers the subjectivity and uncertainty of the decision-making process in the optimization of design scheme, which can effectively improve the objectivity and accuracy of the evaluation results, and provide a reference for designers to optimize interface design schemes.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

BACKGROUND: Patients with diabetic foot ulcers (DFU) and chronic limb-threatening ischemia (CLTI are at higher risk for major amputations and mortality. The aim of this study was to assess the safety and cost-efficacy of intramuscular injection of autologous monocyte-rich PRP platelet-rich plasma Tropocells® PRP (Estar Medical, Holon, Israel) in diabetic patients with chronic limb-threatening ischemia (CLTI) in which revascularization was not feasible. METHODS: a retrospective study was carried out on a series of patients with type 2 diabetes, grade Texas 3C or D DFU, and CLTI. All patients had undergone at least a previous revascularization and were allocated to a surgery waiting list for major amputation. According to the data provided by the manufacturer (https://www.zuccatobiotech.it/index.php/prodotti/tropocells), the monocyte-rich PRP kit obtained a platelet-rich plasma with a high concentration of peripheral blood mononuclear cells (with a proportionately lower amount of lymphocytes), a low concentration of neutrophils and an almost complete depletion of red blood cells. All patients underwent a procedure of local infiltration of autologous mononuclear cells through multiple perilesional and intramuscular injections of 10 mL PBMNC suspensions (0.2–0.3 mL in boluses) performed below the knee along the relevant vascular axis (anterior tibial artery and posterior tibial artery) at intervals of 1–2 cm and to a mean depth of 1.5–2 cm, using a 21 G needle. The procedures were performed according to the instructions of the manufacturer and were repeated at least two times (maximum 3 times) at intervals of 30 days. The principal endpoint was a composite of TcPO2 values at the first toe ≥30 mmHg and/or TcPO2 increase of at least 50% from baseline and/or ulcer healing. Secondary endpoints were individual components of the primary endpoint, quality of life, any adverse events, and direct costs. All the endpoints were evaluated at 26 weeks. RESULTS: Out of 21 enrolled patients, 13 (61.9%) reached the primary endpoint, whereas three patients underwent a major amputation, and two patients died. The median TpCO2 was significantly increased, and pain was significantly reduced. The overall mean and median cost per patient were 9,255±7,328€ and 4,001 [2,991;7,565]€, respectively. CONCLUSIONS: the use of PBMNCs implants in patients with DFU and no-option CLTI seems to be efficacious in reducing the risk of major amputation and improve ulcer healing.

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

A scientific investigation into visual preferences of rural recreation path landscapes is crucial for enhancing visual qualities and visitors' experience. Taking Baofeng, a representative traditional village in Yunlong, as an example, this study analyzed the visual preference of three typical linear recreational paths with different landscape attributes. We used eye-tracking technology to collect eye movement data and conducted a subjective semantic differential evaluation. Our findings manifest a general inclination amongst individuals to favor closer views and paths with clear trajectories and rich elevation changes while walking, despite preference differences on different types of paths. Regarding group diversity, more inclusive design should be made to meet the sensory needs of different groups. Moreover, despite the limited level of correlation between subjective and objective evaluation methods, combining these two approaches remains indispensable. This synthesis advances prior quantitative landscape evaluation with a specific focus on rural path landscapes and upholds the integrity of results by combining objectivity with subjectivity. It also provides relevant design suggestions for further rural renewal and path planning of Baofeng village.

The presented research faces the problem of early detection of sepsis for patients in the Intensive Care Unit. The PhysioNet/Computing in Cardiology Challenge 2019 facilitated the development of automated, open-source algorithms for the early detection of sepsis from clinical data. A labeled clinical records dataset for training and verification of the algorithms was provided by the challenge organizers. However, a relatively small number of records with sepsis, supported by Sepsis-3 clinical criteria, led to highly unbalanced dataset (only 2% records with sepsis label). A high number of unbalanced data records is a great challenge for machine learning model training and is not suitable for training classical classifiers. To address these issues, a number of various models were investigated. A solution including feature selection and data balancing techniques was proposed in this paper. In addition, several performance metrics were investigated. Results show, that for successful prediction, a particular model having few or more predictors based on the length of stay in the Intensive Care Unit should be applied.

We introduce a total energy and environmental evaluation method in the manufacturing industry. The method gives us a series of descriptive indexes to assess the overall environmental effect level on materials, energy, wastes and products in the life cycle process. Meanwhile, the method uses partial indexes, environmental effect factors, and correction offsets into the quantitative model to analyze the learning process and rebound effect on the energy and environment at each procedure. In this work, we choose S-shaped learning curves to describe how to decrease energy consumption and improve the technical learning by doing for recent 30 years. Also, we draw the different rebound effect curves of the total energy-environmental evaluation with technical learning method, which use the annual industrial production growth rate to show that it's significant to estimate its effect on technology changes. The ideas about the interaction of energy and production environment from material flows to energy consumption, direct us to build an example to estimate quantitatively the results with different condition factors, and realize the process improvement and develop new products.

Modern war is sudden and rapid, and once the battle starts, the demand for equipment maintenance and guarantee will show an outburst situation, which puts equipment maintenance and guarantee capability to a severe test. To accurately grasp the civil-military integration of aviation maintenance and guarantee capabilities, it is necessary to evaluate their capabilities. To this end, the evaluation indicator system is established by using the three-dimensional indicator system construction model of "maintenance task → task demand → capability demand", and the evaluation method based on intuitionistic fuzzy entropy and normal grey cloud model is proposed, using intuitionistic fuzzy entropy theory to determine the expert weights and indicator weights, and the grey cloud model theory to determine the capability evaluation level. Finally, the application process of the evaluation model is demonstrated through specific examples, and the evaluation results are analyzed to verify the effectiveness of the evaluation model.

Modern war is sudden and rapid, and once the battle starts, the demand for equipment maintenance and guarantee will show an outburst situation, which puts equipment maintenance and guarantee capability to a severe test. To accurately grasp the civil-military integration of aviation maintenance and guarantee capabilities, it is necessary to evaluate their capabilities. To this end, the evaluation indicator system is established by using the three-dimensional indicator system construction model of "maintenance task → task demand → capability demand", and the evaluation method based on intuitionistic fuzzy entropy and normal grey cloud model is proposed, using intuitionistic fuzzy entropy theory to determine the expert weights and indicator weights, and the grey cloud model theory to determine the capability evaluation level. Finally, the application process of the evaluation model is demonstrated through specific examples, and the evaluation results are analyzed to verify the effectiveness of the evaluation model.

This study analyzes how Perceived Credibility of a 360-degree feedback and Evaluation of Outcome impact on ratees’ attitudes towards behavioral change. The study adopts a qualitative-quantitative mixed method approach. Reasoned Action Theory was selected as the theoretical framework, and ten 360-degree assessment ratees were interviewed on their perceived credibility, evaluation of outcome and attitude toward behavioral change in the 360-degree assessment practices. The qualitative inputs were analyzed under the methodology of grounded theory. Additional 159 respondents participated in the quantitative research phase of the research to validate the findings in the qualitative research phase. It was validated that Perceived Credibility, Evaluation of Outcome has impact on Attitude Toward Behavioral Change in 360-degree assessment.

The Impact of Event Scale-Revised (IES-R) is the most popular measure of post-traumatic stress disorder (PTSD), which has been recently validated in Arabic. This instrumental study aimed to determine optimal cutoff scores of the IES-R and its subscales in Arab samples of psychiatric patients (N = 168, 70.8% females) and healthy adults (N = 992, 62.7% females) from Saudi Arabia during the COVID-19 pandemic as an ongoing collective traumatic event. Based on a cutoff score of 14 of the Depression Anxiety Stress Scale 8-items (DASS-8), receiver operator curve (ROC) analysis revealed two optimal points of 39.5 and 30.5 for the IES-R in the samples (area under the curve (AUC) = 0.86 &amp; 0.91, p values = 0.001, 95% CI: 0.80-0.92 &amp; 0.87 to 0.94, sensitivity = 0.85 &amp; 0.87, specificity = 0.73 &amp; 0.83, Youden index = 0.58 &amp; 0.70, respectively). Different cutoffs were detected for the six subscales of the IES-R, with numbing and avoidance expressing the lowest predictivity for distress. Meanwhile, hyperarousal followed by the irritability expressed stronger predictive capacity for distress than all subscales in both samples. In path analysis, pandemic-related irritability resulted from direct and indirect effects of key PTSD symptoms (intrusion, hyperarousal, and numbing). Irritability contributed to traumatic symptoms of sleep disturbance in both samples while the opposite was not true. The findings suggest usefulness of the IES-R at a score of 30.5 for detecting adults prone to trauma related distress, with higher scores needed for screening in psychiatric patients. Various PTSD symptoms may induce dysphoric mood, which represents a considerable burden that may induce circadian misalignment and more noxious psychiatric problems/ co-morbidities (sleep disturbance) in both healthy and diseased groups.

The objective of this research was to create a Spanish-adapted version of the 30-item Multidimensional Ethics Scale (MES-30), analyze its structural validity, and create a short, valid, and culturally-adapted version. A total of 594 employees from organizations operating in different industries, primarily located in Ecuador, participated in this study. The comparison of different models using Confirmatory Factor Analysis (CFA) showed that the bifactor model proved better fit in all scenarios. The high common variance explained by the general factor (&gt; 80%) and the high values of ωh (&gt; .90) led to the conclusion that the explanatory model of the adapted MES-30 is essentially one-dimensional. In order to obtain a more valid and reliable measurement of the substantive common factor, a short version (Spanish MES-15) has been proposed, which contains items from all philosophical approaches and three non-redundant scenarios. The one-dimensional model for the Spanish MES-15 showed excellent goodness of fit in all scenarios. Regarding the metric equivalence between the original instrument (adapted MES-30) and the short one, the correlation between both measurements was greater than .90, the correlation of the short version with the social desirability scale was lower, and both instruments similarly predicted the intention of executing the actions described in the scenarios, the probability of executing the actions attributed to peers and supervisors, and the general ethical evaluation of those actions.

BACKGROUND: diabetic foot ulcers (DFU) represent the main cause of major amputations and hospitalizations in diabetic patients. Aim of this study was to assess safety and cost-efficacy of intramuscular injection of peripheral blood mononuclear cells (PBMNCs), in diabetic patients with no-option chronic limb-threatening ischemia (CLTI) and small artery disease (SAD). METHODS: a retrospective study was carried out on a series of types 2 diabetic patients with DFU grade Texas 3 and no-option CLTI and SAD. All patients had undergone at least a previous revascularization and were allocated in a surgery waiting-list for major amputation. The principal endpoint evaluated at 90 days was a composite of TcPO2 values at the first toe ≥30 mmHg and/or TcPO2 increase of at least 50% from baseline and/or ulcer healing. Secondary endpoint were individual components of the primary endpoint, any serious and non-serious adverse events, direct costs at one year. RESULTS: the composite endpoint was achieved in 9 patients (60.0 %); one patient (6.7%) healed within 90 days and 26.7% and 46.7% showed TcPO2 ≥30 mmHg and a TcPO2 increase of at least 50% at 90 days, respectively. At 1-year, three (20.0%) patients underwent a major amputation (all diagnosed SAD grade III). One patient died after seven months, and seven patients (46.7%) healed. The overall median and mean cost per patient were 8,238±7,798€ and 4,426[3,798;8,262]€, respectively. CONCLUSIONS: the use of PBMNCs implants in no-option CLTI diabetic patients with SAD seems to be of help in reducing the risk of major amputation.

The Australian Bureau of Meteorology offers a national operational 7-day ensemble streamflow forecast service covering regions of high environmental, economic and social significance. This semi-automated service generates streamflow forecasts every morning and is seamlessly integrated into the Bureau's Hydrologic Forecasting System (HyFS). Ensemble rainfall forecasts, European Centre for Medium-Range Weather Forecasts (ECMWF) and Poor Man's Ensemble (PME), available in the Numerical Weather Prediction (NWP) suite, are used to generate these streamflow forecasts. The NWP rainfall undergoes pre-processing using the Catchment Hydrologic Pre-Processer (CHyPP) before being fed into the GR4H rainfall-runoff model, which is embedded in the Short-term Water Information Forecasting Tools (SWIFT) hydrological modelling package. The simulated streamflow is then post-processed using the Error Representation and Reduction In Stages (ERRIS). We evaluated the performance of the operational rainfall and streamflow forecasts for 96 catchments using four years of operational data between January 2020 and December 2023. Performance evaluation metrics included CRPS, relative CRPS, CRPSS, and PIT-Alpha for ensemble forecasts and NSE, PCC, MAE, KGE, PBias and RMSE and three categorical metrics CSI, FAR and POD for deterministic forecasts. The skill scores CRPS, relative CRPS, CRPSS and PIT-Alpha, gradually decreased for both rainfall and streamflow as the forecast horizon increased from Day 1 to Day 7. A similar pattern emerged for NSE, KGE, PCC, MAE and RMSE as well as the categorical metrics. Forecast performance also progressively decreased with the higher streamflow regime. Most catchments showed positive performance skills, meaning the ensemble forecast outperformed climatology. Both streamflow and rainfall forecast skills varied spatially across the country – and were generally better in the high runoff generating catchments, and poorer in the drier catchments situated in the western part of the Great Dividing Range, South Australia and mid-west of Western Australia. We did not find any association between model forecast skill and the catchment area. Our findings demonstrate that the 7-day ensemble streamflow forecasting service is robust and draws great confidence from agencies that use these forecasts to support decisions around water resources management.

Public-private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs towards attainment of sustainable, climate resilience and zero carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries like Ghana where private investment inflow has plummeted due to COVID-19 recession and poor project performance. Thus, this study aims at assessing the key financial risk management strategies in ensuring sustainable PPP infrastructure projects in Ghana. The study utilised primary data from PPP practitioners in Ghana solicited through survey questionnaires. Factor analysis, mean scores and fuzzy synthetic analysis are the data analysis techniques for this study. The results revealed sustainable and green funding models, effective cost reduction initiatives, competent team with committed leadership, and emerging technologies and regulations constitute the key strategies to manage financial risks of sustainable PPP infrastructure projects. Although, future studies must expand the scope of data gathering, the findings of the study enrichen the theoretical understanding of financial risks in sustainable investments in PPP infrastructures. Relevant remedies that will aid the development of practical financial risk management guidelines are provided in this study for PPP practitioners.

Nondestructive determination of the neutron irradiation induced embrittlement of nuclear reactor pressure vessel steel is a very important and recent problem. In the frame of the so called NOMAD project, funded by the Euratom research and training program, novel nondestructive electromagnetic testing methods were applied for inspection of irradiated reactor pressure vessel steel. In this review the most important results of this project are summarized. Different methods were used and compared with each other. Measurement results were compared with the destructively determined ductile to brittle transition temperature (DBTT) values. Three magnetic methods: 3MA (micromagnetic, multiparameter, microstructure and stress analysis), MAT (magnetic adaptive testing) and Barkhausen noise technique (MBN) were found as the most promising techniques. The results of these methods were in good confidence with each other. Good correlation was found between the magnetic parameters and the DBTT values. The basic idea of the NOMAD project is to use a multi-method/multi-parameter approach and to focus on their synergies that allows to recognise the side effects therefore supressing them at the same time. Different types of Machine Learning (ML) algorithms were tested in competition and their performances were evaluated. The important outcome of the ML technique is that not only one, but several different ML techniques could reach required precision and reliability, i.e. to keep the DBTT prediction error lower than +/-25°C threshold, which was previously not possible for any of the NDE methods as single entities. A calibration/training procedure was carried out on the merged outcome of testing methods with excellent results to predict transition temperature, yield strength and mechanical hardness for all investigated materials. Our results, achieved within NOMAD project can be useful for the future potential introduction of this (and in general, any) nondestructive evolution method.

Portugal, in line with the European Union, is aiming for carbon neutrality by 2050 (Net 1 Zero), which implies a transition to sustainable energy sources. Climate change is all too evident, extreme weather periods are occurring in a cyclical manner, with greater brevity to such an extent that the grid operator must deal with production scenarios where it can no longer rely on hydroelectric production given the recurring drought situation. This situation increases dependence on thermal production using natural gas and imports. This has significant economic implications. Portugal has exploited its onshore wind potential, reaching an installed capacity of 5.671 MW by 2022. However, the expansion of onshore wind energy is limited to reinforcing existing infrastructure. To overcome these challenges, it is necessary to expand the exploitation of offshore wind potential that is already underway. This article proposes the location of offshore wind production platforms along the Portuguese coast. This allows for an analysis of offshore production and its optimization according to the minimum cost per MWh in the face of extreme scenarios, i.e., in periods of extreme drought where hydroelectric production capacity is practically non-existent. The model is fed by using market price indications and the amount of energy needed for the following day. Using forecast data, the model adapts offshore wind production for the following day according to the minimization of the average market price. The results of the simulations allow us to conclude that despite the high cost of offshore technology (in deep waters), in extreme climate scenarios, it enables cost reduction and a clear decrease in imports.

Nowadays, the demand of agricultural production increase, Moreover, the rapid increase of the population in Egypt led to an increase in the demand for food, prompting the government to reclaim more desert lands. Such a study contributes to providing information that contributes to the promising optimization of land resources. This study carried out in an area south Egypt covering 386,171.04 hectares (ha). Remote sensed data were manipulated for defining the land cover/use features. Setting up DEM configures the network of natural drainage flows via the descending slopes. It was a guide for allocating micro dams as water harvesting sites as well as minimizing the runoff hazards and managing the priority of land use suitability versus flood hazards. Land cover/use units were defined as terrestrial irrigated areas of sequentially herbacous crops and permanent trees covering 1387.83 ha in levees; 1608.82 ha in point bar; 718.89 ha in bow bar and 23938.29 ha in alluvial plain. Terrestrial natural vegetation is dominated by xerophytes herbaceous in wadis (123533.56 ha). Terrestrial non-vegetated areas includes bare areas of rock land (98102.59 ha) and 67201.57 in bajada. Artificial non linear surfaces include buildings (5403.59 ha) and linear features include roads and railways (875.78 ha). Aquatic areas include artificial irrigation and drainage canals (1062.15 ha) and natural water body of River Nile course (2785.92 ha). Current land suitability for specific Land Utilization Types (LUTs) was assessed by matching soil attributes with the growth requirement of each LUT. Current land suitability can be improved by decreasing of salinity and framing practices. Accordingly, the land units can be potentially more profitable for increasing the ability of extra crops to be more productive. Old cultivated areas are the most profitable land cover/use units highly suitable (S1) for all LUTs comparing with other land cover categories.

The construction safety risks (such as landslides or slumps) of the high-fill subgrade are characterized by uncertainty and variability. In order to ensure the construction safety of the high-fill subgrade of the expressway, a comprehensive risk assessment model of high-fill subgrade construction according to the combination weighting method based on game theory was established. Firstly, settlement rate, lateral differential settlement, horizontal displacement at the foot of the slope, deep horizontal displacement, and excess pore pressure were selected as evaluation indicators, and an evaluation index system of high-fill subgrade was constructed. Secondly, the subjective and objective weights were obtained via the analytic hierarchy process and entropy method. Furthermore, the optimized weights were obtained by introducing game theory, and the construction risk of the high-fill subgrade was evaluated and analyzed using the fuzzy comprehensive evaluation method. Finally, based on the high-fill section of the Zhijiang-Tongren Expressway in Hunan Province (China), the evaluation model was validated through field measurement data. The results show that the safety scores obtained using the three methods of analytic hierarchy process, entropy method, and combination weighting method based on game theory are similar. The combination weighting evaluation model can correct the evaluation result error caused by a single weight and avoid information delay caused by the manual processing and analysis of monitoring data. The high-fill subgrade safety evaluation grade based on the combination weighting method and game theory is consistent with the engineering situation, and its fault tolerance range is within 20%. The evaluation model proposed in this study can scientifically and effectively evaluate the safety risks of high-fill subgrade construction, significantly improving the safety and reliability during the construction process.

The minimum dominating tree (MDT) problem consists of finding a minimum weight sub-graph from an undirected graph, such that each vertex not in this sub-graph is adjacent to at least one of the vertices in it, and the sub-graph is connected without any ring structures. This paper presents a Dual Neighborhoods Search (DNS) algorithm for solving the MDT problem, which integrates several distinguishing features, such as two neighborhoods collaboratively working for optimizing the objective function, a fast neighborhood evaluation method to boost the searching effectiveness, and several diversification techniques to help the searching process jump out of the local optimum trap thus obtaining better solutions. DNS improves the previous best-known results for 4 public benchmark instances while providing competitive results for the remaining ones. Several ingredients of DNS are investigated to demonstrate the importance of the proposed ideas and techniques.

In view of the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm all nodes participate in the consensus, the three-stage process has problems such as large communication overhead, random selection of master nodes and lack of reward and punishment mechanism. A Speculative Practical Byzantine Fault Tolerance (SP-PBFT) is proposed. Firstly, the consensus protocol was optimized, and a timeout mechanism was proposed to divide the consensus process into optimistic mode and pessimistic mode, which reduced the communication overhead under the premise of resisting Byzantine node attacks .Secondly, a node evaluation mechanism was proposed to calculate the node reputation value according to the node's historical behavior and give the corresponding reward or punishment, which reduced the possibility of malicious nodes participating in the consensus process. Finally, the Fibonacci grouping mechanism was used to reduce the number of nodes participating in the consensus process, fundamentally improving the consensus efficiency, avoiding the problem of centralization of the consensus process caused by the cumulative reputation value of nodes, and improving the enthusiasm of consensus nodes. Simulation experiments using Docker containers to simulate multiple nodes show that the SP-PBFT consensus algorithm proposed in this paper has better performance than PBFT consensus algorithm and other improved algorithms in terms of consensus delay, throughput, fault tolerance and communication complexity.

Wash’Em is a process that supports humanitarians in assessing and designing rapid but context-specific hygiene programmes in crises or outbreaks. The process consists of training implementers, using tools to learn from populations, and entering findings into a software which generates contextualised activities. A process evaluation of Wash’Em use was conducted in a drought-affected area in Midland province, Zimbabwe. Data was collected during the programme design and following implementation, using a mix of qualitative methods. Findings were classified against the intended stages of Wash’Em, and the evaluation domains were defined by the UKRI Medical Research Council. The Wash’Em process was not fully implemented as intended. An abridged training was utilised, some of the tools for learning from populations were omitted, many of the recommended activities were not implemented, the delivery modalities were different from intended, the budget available was minimal, and the number of people exposed to activities were fewer than hoped. Despite these ‘on the ground’ challenges and adaptations, the Wash’Em process was considered feasible by implementers and was seen to be less top-down than most programme design approaches. The populations exposed to the intervention found the activities engaging, understood the content, and reportedly took action to improve handwashing behaviour.

The digital era offers many opportunities to the wind energy industry and research community. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenges in successfully implementing digitalisation is the lack of data sharing and collaboration between organisations in the sector. In order to overcome this challenge, a new collaboration method called WeDoWind was developed in recent work. The main innovation of this method is the way it creates tangible incentives to motivate and empower different types of people from all over the world to actually share data and knowledge in practice. In this present paper, the challenges related to comparing and evaluating different SCADA data based wind turbine fault detection models are investigated by carrying out a new case study, the "WinJi Gearbox Fault Detection Challenge", based on the WeDoWind Method. Six new solutions were submitted to the challenge, and a comparison and evaluation of the results show that, in general, some of the approaches (Particle Swarm Optimisation algorithm for constructing health indicators, performance monitoring using Deep Neural Networks, Combined Ward Hierarchical Clustering and Novelty Detection with Local Outlier Factor and Time-to-failure prediction using Random Forest Regression) appear to have a high potential to reach the goals of the Challenge. However, there are a number of concrete things that would have to have been done by the Challenge providers and the Challenge moderators in order to ensure success. This includes enabling access to more details of the different failure types, access to multiple data sets from more wind turbines experiencing gearbox failure, provision of a model or rule relating fault detection times or a remaining useful lifetime to the estimated costs for repairs, replacements and inspections, provision of a clear strategy for training and test periods in advance, as well as provision of a pre-defined template or requirements for the results. These learning outcomes are used directly to define a set of best practice data sharing guidelines for wind turbine fault detection model evaluation. They can be used by the sector in order to improve model evaluation and data sharing in the future.

The estimation of ecological service system value of water resources in Tarim river basin is of great significance for resource allocation management and ecological protection. However, there is still no unified and complete evaluation method for ecological service system value of inland river in China. Based on the perspective of the whole value chain, the study classifies its ecological service functions, and divides 11 sub-categories into 4 categories (supply, regulation, culture and support) as evaluation indicators to carry out quantitative evaluation. The results showed that the total value of ecological service system in Tarim river basin in 2018 was 4156.5247×108 Yuan, and the value of regulating function, cultural function, supporting function and supply function were successively from high to low, which were as follows: 2565.6825×108 Yuan, 1009.5471×108 Yuan, 884.0770×108 Yuan, 20.3350×108 Yuan, among which the value of regulation function is dominant.

Introduction: In the medical area, teaching is essential since it must offer the appropriate instruments to demonstrate that graduates have acquired the necessary skills. Objective: Evaluate the quality of research in residents of medical specialties after a standardized digital training program with rubrics. Methods: An observational, prospective research study in resident physicians of seven medical specialties first-year of an introductory program to methodology. It is integrated with the result variable through the quality of the final product and the quality variable will be measured with an ad hoc questionnaire validated by the Delphi method with a consistency level of 3-3. The data will be integrated into a base of the SPSS system and determined with the Chi-square test considering a minimum significance of 0.05. Results: 85 first-year medical residents (n=85) enrolled in the Research Seminar. The mean age was 31.34 years (± 3.96). About gender Male 38±31.13 Female 31.51±3.83. The global final grade was 80.61 (± 9.59) and the global sat-isfaction of the course was referred to as good by 62.2%. We observed a positive relationship between the scope of evaluation and the level of satisfaction. Conclusion: The research seminar implementation in a b-learning mode in response to the educational needs in medical residents for the field of health education showed a relationship between higher qualification, higher satisfaction, as well as determining that the comprehensive evaluation through the use of rubrics standardized allowed to delimit the deficiencies and strengths for timely feedback influencing the process of acquiring skills and the quality of the final product.

Reaching the land-related UN-Sustainable Development Goals (SDGs) and similar goals articulated by the EU-Green Deal (GD) by 2030 presents a major challenge and requires a pragmatic approach to be focused on joint learning by land users (mostly farmers), researchers and other stakeholders in “Living Labs” and system experiments at experimental farms of research organizations. Defining specific indicators and thresholds for ecosystem services in line with land-related SDGs, are crucial to establish: “Lighthouses” that can act as inspiring examples if they meet the various thresholds. This exploratory paper discusses indicators and thresholds for an arable farm operating on marine, calcareous light clay soils in the Netherlands. Studies of a system experiment are used to discuss and test operational methodology to be widely applied when characterizing many “Living Labs” in future as planned by the European Union. The important role of soils, contributing to ecosystem services, is discussed in terms of soil health. Recommendations are made for innovative methodology to be associated with all land-related SDGs. Satisfying thresholds of ecosystem services, that will vary by soil type, region and farm-type, can be the basis for farm subsidies such as the Common Agricultural Policy (CAP). Research on Living Labs and in system experiments has to be judged by different criteria than those associated with traditional linear research. Important contributions by soils to achieve ecosystem services are framed in terms of soil health and are the most effective way to promote soil science in a by now widely desired inter- and transdisciplinary context.

With the continuous development of urbanization and industrialization in the world, concrete is widely used in various engineering constructions as an engineering material. However, the consequent problem of durability of concrete structures is also becoming increasingly prominent. As an important additional measures, protective coating can effectively improve the durability of concrete performance. Moreover, the uniformity of the concrete surface coating will directly affect its protective effect. Therefore, we propose a nondestructive inspection and evaluation method of coating uniformity based on infrared imaging and cluster analysis for concrete surface coating uniformity detection and evaluation. Based on the obtained infrared images, a series of processing and analysis of the images were carried out using MATLAB software to obtain the characteristics of the infrared images of concrete surface. Finally, by extracting the temperature distribution data of the pixel points on the concrete surface, an evaluation method of concrete surface coating uniformity based on a combination of cluster analysis and hierarchical analysis was established. The evaluation results show that the determination results obtained by this method are consistent with the actual situation. This study has a positive contribution to the testing of concrete surface coating uniformity and its evaluation.

Background: The purpose of this study was to evaluate and compare the performance of health, safety and environmental management of civil, traffic and urban services contractors in the 18th district of Tehran municipality in 2015-2016. Methods: This is an applied, longitudinal, descriptive-comparative study. The statistical population of this study was construction contractors, urban services and traffic in the municipality of district 18 of Tehran in the years 2015-2016. from 52 contractors, 18 construction contractors, 21 utilities contractors and 13 traffic contractors, respectively, were selected using census method. the research instrument consisted of periodic direct observation and completion of the HSE standard checklist by researchers. Data were analyzed using Kruskal-Wallis nonparametric test by SPSS software.Results: The HSE performance of all contractors (civil, utilities and traffic) was acceptable and the results of Kruskal-Wallis test showed that the HSE performance of contractors at the second visit of 2015 and the first visit of 2016 was significantly different in favor of civil contractors )p <0.01), but there was no significant difference between the first and third visits of 2015 and the second and third visits of 2016 (p> 0.05). visits in six periods indicate HSE Civil Contractors status increased from 100% unfavorable to 88.88% acceptable level and 11.11% good level, and in the case of civil service contractors who initially had 95.23% in an unfavorable situation and 4.76% in a favorable situation achieved 100% acceptable performance, and finally, the traffic contractors, who were 100% unfavorable, were upgraded to 100% acceptable. Conclusion: According to the findings of the study, it seems that the supervision of municipality inspectors on HSE performance of contractors can be effective in improving and strengthening the commitment to HSE requirements, therefore, it is suggested that periodical visits be made to the municipal contractors.

This study presents a prediction model based on Logistic Growth Curve to evaluate the effectiveness of Movement Control Order (MCO) on COVID-19 pandemic spread. The evaluation assesses and predicts the growth models. The estimated model is a forecast-based model that depended on partial data from the COVID-19 cases in Malaysia. The model is then studied together with the effectiveness of the three phases of MCO implemented in Malaysia. Evidence from this study suggests that results of the LGC prediction model match with the progress and effectiveness of the MCO to flatten the curve, thus helped to control the spike in number of active COVID-19 cases and spread of COVID-19 infection growth.

The role of the submission was to find out what changes people think they need to make in their home because of getting older. At advanced age, the likelihood of different limitations such as vision impairment, hearing impairment or physical inability is increased. Currently, tenants are often forced to leave their long-term living space, as these spaces cannot serve “new” individual needs. This transition from the privacy of their home to the new environment often appears to be a painful change. They will not have a well-known environment because their homes cannot be adapted to their new needs. The aim is a comprehensive approach to the design of such an exterior and interior space which could serve people at all stages of their life, including the terms of mobility. This means that even if there is an unexpected situation and changes in movement abilities and physiological limitations of man, not only by natural aging, but according to accidents or disabilities we can adapt the living space to the given conditions. The survey results are presented in Germany and Slovakia. In the survey, respondents expressed their opinion on what they considered important in creating an adaptive environment considering various life changes. Results are processed graphically with explanation. The results could be of an interest to architects and designers of the environment. Based on the results of the questionnaire survey, studies of possible modifications of flats and houses were developed. The contribution brought these results to three age groups of respondents; people aged 35, 50 and over 50.

Land consolidation engineering inevitably interferes with terrestrial ecosystems, leading to natural capital loss. Therefore, conducting an ecological sensitivity evaluation of a project area before consolidation engineering is very important for reducing unnecessary human interference. Conservation of terrestrial ecosystems and the biodiversity therein to the greatest possible extent is urgently needed. This research analyzes the interference by human activities caused by land consolidation engineering in terrestrial ecosystems. GIS technology, ecological values, landscape pattern indexes, and an ecological risk evaluation were used to construct an ecological sensitivity evaluation index. The coefficient of variation method and a comprehensive sensitivity rating evaluation were used to calculate the weights and results. The project area was divided into sensitivity zones according to the results, and the results and suggestions are as follows: In the highly eco-sensitive zone, where bare rocks, gravel, and grass-covered areas compose the main landscape type, vegetation should be restored, and forests should be planted. In the medium eco-sensitivity zone, where irrigated paddy fields and arid land compose the main landscape type, land parcels should be merged, and agricultural infrastructure should be constructed or improved. In the low eco-sensitivity zone, where forests compose the main landscape type, roads should be closed, natural habitat should be restored, and buffer zones should be created. This study provides suggestions for future land management decisions.

While previous research has shown the use of attachable air-caps on windows to efficiently reduce a building’s energy consumption, the air-caps considered had to be attached to the entire window’s surface, thus limiting the occupants’ view and creating the inconvenience of needing to detach and attach the air-caps. In this study, a window-mounted air-cap roller module using Velcro tape that may be easily attached, detached, and rolled up or down was developed and performance tested in a full-scale test bed. It was found that as the area of the air-caps attached on a window increased, the required indoor lighting energy increased. However, the window insulation improved, thus reducing the cooling and heating energy needed. Attaching the air-caps to the entire window surface effectively reduced the building’s energy consumption, but views through the window may be disturbed. Thus, the developed window-mounted air-caps enable an occupant to reduce the building energy consumption and maintain their view according to their need. The findings of this study may contribute to a reduction in building energy consumption without sacrificing a pleasant indoor environment. Further studies may be needed to verify their efficacy under varying indoor and outdoor conditions.

Project portfolio configuration (PPC) is an important approach to maintain the sustainable development of enterprises and achieve organizations’ strategy. However, the synergetic efficacy of PPC which determines the degree of the project's strategic objectives achieved is a fuzzy problem and hard to be measured. To solve this problem, this paper takes the data envelopment analysis (DEA) as the tool to measure the efficacy of PPC under deterministic conditions. First, a portfolio evaluation index system which takes financial indicators and non-financial indicators into consideration is developed based on the review of the literature; Second, an evaluation model based on DEA is built to reduce the number of decision making-unit with the perspective of synergetic theory; Then, a computational experiment is studied to verify the feasibility of this proposed model. The results of this computational experiment show that this model can effectively narrow scope of decision-making, improve the decision-making level and provide a reference to decide the DEA effective project portfolio decision-making unit. To our knowledge, this study is the first time to apply the notion of synergetic efficacy and DEA to the PPC domain. It is hoped that this paper may shed lights on any further study about PPC and enterprise competitiveness of sustainable development.

Currently, most middleware application developers have two choices when designing or implementing API services: They can either stick with REST or explore the emerging GraphQL technology. Although REST is widely considered the standard method for API development, GraphQL is believed to overcome the main drawbacks of REST, especially data fetching issues. Yet, doubts remain as there are no experimental studies with convincing results to evaluate the performance of the two services. In this paper, we propose a research methodology to evaluate the performance of REST and GraphQL API services, which includes two main contributions. The first contribution is that the performance evaluation of the two services is conducted in the real operation of a massive and intensively accessible management information system. The second contribution is the fair and independent performance evaluation results obtained for both API services. The performance evaluation was studied using basic measures of QoS, including response time, throughput, CPU load, and memory usage. The results show that REST is still faster in response time and throughput, while GraphQL is very efficient in resource utilization, i.e., CPU load and memory utilization. Therefore, GraphQL is the right choice when data requirements change frequently and resource utilization is the most important consideration. REST is used when some data is frequently accessed called by multiple requests.

With global warming, arable land in boreal regions is tending to expand into high latitude regions in the northern hemisphere. This entails certain risks; such that inappropriate management could result in previously stable carbon sinks becoming sources. Agroecological models are an important tool for assessing the sustainability of long-term management, yet applications of such models in boreal zones are scarce. We collated eddy-covariance, soil climate and biomass data to evaluate the simulation of GHG emissions from grassland in eastern Finland using the process-based model DNDC. We simulated gross primary production (GPP), net ecosystem exchange (NEE) and ecosystem respiration (Reco) with fair performance. Soil climate, soil temperature and soil moisture at 5 cm were excellent, and soil moisture at 20 cm was good. However, the model overestimated NEE and Reco following crop termination and tillage events. These results indicate that DNDC can satisfactorily simulate GHG fluxes in a boreal grassland setting, but further work is needed, particularly in simulated second biomass cuts, the (>20 cm) soil layers and model response to management transitions between crop types, cultivation, and land use change.