There is a growing trend among consumers to seek out natural foods and products with natural ingredients. This shift in consumer preferences had a direct impact on both food and pharmaceutical industries, leading to a focus of scientific research and commercial efforts to meet these new demands. The aim of this work is to review recent available scientific data on foods of interest, such as artichoke, gooseberry, and polygonoideae plants, as well as olive oil and red raspberries. Interestingly, the urgency of solutions to the climate change emergency has brought new attention to by-products of grapevine bunch stem and cane, which have been found to contain bioactive compounds with potential health benefits. There is a pressing need for a faster process of translating scientific knowledge from the laboratory to real-world applications, especially in the face of the increasing societal burden associated to non-communicable diseases (NCDs), environmental crises, the post-pandemic world, and ongoing violent conflicts around the world.

China is a traditional agricultural country, and the integration of rural industries has become an essential policy direction for the current strategy of agricultural modernization in China. In recent years, the agricultural industrial chains across various regions of China have consistently expanded and extended. The multifunctionality of agriculture is continuously unearthed, and the principal entities managing agriculture have become increasingly diversified and have grown significantly. New industries and forms in agriculture emerge incessantly. Accurately and profoundly understanding the inherent features of the integration of industries in rural China, establishing a scientific and rational measurement index system in line with the current status and development goals of rural China, and employing appropriate measurement methods to assess its development level and process, is instrumental in comprehending the level of integrated development in various regions. This aids in identifying challenges in the developmental process and proposing targeted developmental strategies. Hence, this paper, rooted in the integration of rural industries, cross-industry, industry extension, industry agglomeration, and industry penetration, sets up an measurement index system. Using provincial panel data from 2011 to 2020, the paper measures the level of integrated development in rural industries across China and its 31 provinces. Based on the measurement results, further techniques such as kernel density estimation and Gini coefficient decomposition have been used to analyze the spatial distribution characteristics and dynamic trends of the integrated development of rural industries in China. Research indicates that during the sample period, the overall level of integrated development in rural industries in various provinces in China has shown an upward trend. Development among the eastern, central, and western regions is highly uneven, but this disparity has been gradually narrowing in recent years. Furthermore, the levels of integrated development in different provinces exhibit significant spatial agglomeration effects. The development level of neighboring regions significantly impacts the province's development status. In the process of integrated development of rural industries in China, there's a trend where "it's easier to downgrade than to upgrade," with very few regions achieving leapfrog development.

The existence of the hole on a plate affects the calculation of eddy current problems. Consequently, the accuracy for the prediction of the material properties decreases if the effect of the hole is not taken into account. In this paper, a novel analytical method based on the modified integration range is proposed which can address the presence of the hole. Due to the presence of the hole, the conventional Dodd-Deeds analytical solution cannot be used to calculate the inductance change. Therefore, a revised upper integration limit is introduced to replace the original limit -- ∞ when using the co-axially air-core electromagnetic sensor. With the presence of the hole, the magnitude of the received signal reduces, and the peak frequency feature changes. The analytical method is validated by measured and numerical simulation results. It is found that the upper limit is related to the radius of the open hole. With the new technique, the thickness of sample plates with holes can be estimated based on the peak frequency feature.

Rice, as a staple crop feeding billions, faces constant threats from various diseases jeopardizing global food security. Precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. Integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with better understanding of their functional roles in disease resistance. Improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can give a transformative impact on rice breeding for enhancing disease resistance.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

In this study, an alternative method to conventional production methods involving thin section copper permanent mould casting (rapid solidification), hot rolling and heat treatment processes to manufacture AISI DC 53 cold work tool steel, has been investigated. In this new method, solidification of the AISI DC 53 was done in the thin section copper mould instead of traditional ingot casting. After solidification, thin slabs obtained was homogenized to 1150 ^oC and hold at this temperature for one hour and then hot rolling was be applied. During hot rolling process, about % 30 reduction in thickness of slab was obtained. After hot rolling, heat treatment (austenitizing, quenching and tempering) have been applied to thin slab. The samples have been taken as cast, as rolled and as heat treated (austenitized and tempered) and the microstructural analysis, hardness tests, retained austenite quantity measurement by XRD method have been performed. The heat treatment and tests have been performed for a commercially available AISI DC 53 which is manufactured by thick section ingot casting and rolling. Hardness values of the AISI DC 53 steels produced by traditional route is in the range of 52-54 HRC after austenitization at 1025 ^oC for one hour and quenched in compressed air and tempered twice at 525 ^oC for 120 mins. On contrary the permanent mould cast AISI DC 53 after homogenization at 1150 ^oC and immediately hot rolling then air cooling and austenitized at 1025 ^oC for one hour then quenched by compressed air and tempered twice at 525 ^oC for 120 mins have hardness valeus in the range of 55-57 HRC. Experiments have revealed that the properties of new rapid solidified steel in permanent copper mould are better than the commercially available steel and have a more refined microstructure than commercially produces alternative. Therefore, the new proposed method can be used as an alternative manufacturing method for cold-work tool steels.

This article is about a framework for determining the degree of realism of any given 1 passenger ride motion discomfort measurement formula. After providing some context and reviewing 2 evidence of deficiency in currently popular ride motion discomfort measurement formulas, the article 3 outlines the research program that needs to be carried out in order to establish such a framework. 4 The research begins with gathering recordings of uncomfortable ride motion episodes encountered in 5 a chosen type of passenger transport service. It then has test subjects compare the episodes via a ride 6 motion simulator and adjust their amplitudes pair wise until they cause equal discomfort. It explains 7 how to take the pair wise amplitude adjustments and determine amplitude adjustments that bring all 8 of the motion episode recordings to a common level of discomfort so that they form a normalized set. 9 Then, the lower the scatter of the scores assigned by any given discomfort measurement formula to 10 the members of that set, the more realistic that formula will be for the chosen service.

The building envelope has the most significant contribution in the reduction of the building energy consumption. Application of new, alternative and improved materials and systems has an important impact on the buildings performances. This paper is focused on the thermal transmittance, as an indicator of the thermal conductance of the construction element. It includes comparisons of the U-values, calculated by software, with those measured in situ on three representative façade walls. The walls have been constructed with the new wall system Fragmat NZ-1, a new product in Macedonian buildings. This research provides basic information on the thermal transmittance of the system. The results of the analysis show that the in situ measuring is a useful tool in validation of the precision of analytically calculated values, since it was difficult to obtain precise results from the analytical calculations only, especially when the layers are with non-uniform thickness.

The paper presents an error model of a measurement chain containing link performing discrete wavelet transform algorithm which is most often the last stage of measurement signal processing. The goal is to determine the uncertainty budget of the input quantities of the wavelet transform algorithm. The error model takes into account parts of analog, analog-to-digital and digital processing, describing the properties of subsequent fragments of the chain using their transmittance and processing functions. The proposed model enables the description of both deterministic and non-deterministic properties of signal errors. The proposed model was validated using an example measurement chain created for this purpose.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

This paper presents a new approach of eddy current methods for determining the size of the co-axial hole in the metallic circular disk. In recent decades, for the air-cored sensor probe, the impedance change due to the presence of an infinite metal plate can be calculated by the Dodd-Deeds model. However, in practical measurements, the sample cannot match with the condition required - ‘infinite’, thus the Dodd-Deeds model could not be applied to the disk with finite size and certainly not a co-axial hole in the center. In this paper, a dual-constraint analytical method is proposed. That is, the upper and lower limits of the integration are substituted with specific values instead of the original 0 and . Besides, it is found that, once the outer radius of the disk is fixed (i.e. the lower limit of integration is fixed), the upper limit reduces linearly as the size of the coaxial hole increases. Both the FEM simulation and experiments have been carried out to validate this method. The radius of the hole can be estimated based on the dual-constraint integration feature.

This study delves into the critical domain of public procurement, specifically focusing on Sustainable Public Procurement (SPP) and Environmental, Social, and Governance (ESG) considerations within the context of South Korea. The aim of this research is to empirically scrutinize the factors influencing the impact index of SPP, with a particular emphasis on services related to labor standards. The investigation spans three years, from January 1, 2019, to July 31, 2021, encompassing state agency orders and post-implementation legal changes. Leveraging the comprehensive Korea On-line E-Procurement Sys-tem(KONEPS) platform, we meticulously collected data, ultimately culminating in 21,573 services meeting our criteria, from which 250 cases underwent an in-depth analysis. The study sheds light on the influence of social responsibility evaluation cri-teria on overall procurement scores, while also uncovering the moderating effects of various factors. The outcomes of this study offer valuable insights into the impact index of social responsibility evaluation criteria within South Korea's public procurement landscape. Factors including procurement year, classification, service period, and estimated price were identified as significant influencers. Moreover, the number and location of evalu-ation criteria items, inclusion of sincerity elements, and the evaluating agency were deemed pivotal determinants of the influence index. These findings hold profound implications for policymakers, procurement practitioners, and researchers and provide a roadmap for optimizing the utilization of social responsibility evaluation criteria to advance responsible and sustainable procurement practices. Future research avenues include conducting further study of additional moderat-ing variables, expanding datasets to encompass a broader spectrum of procurement contexts, and evaluating the long-term repercussions of social responsibility evaluation on procurement outcomes. These endeavors promise to further refine and advance public procurement practices in South Korea and beyond.

The scope of this study was twofold: first, to introduce a new method in examining measurement invariance, especially with large-scale studies where a large number of group comparisons are involved: the alignment approach, where only configural invariance is necessary to achieve measurement invariance. Second, to evaluate the psychometric robustness of this approach using real-life data. Particularly, we applied this approach to examine whether the factor structure of a cognitive ability test (PGAT) exhibits measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The sample consisted of 9,849 graduate students from 26 universities around the Kingdom. The results indicated a robust configural model suggesting that the P-GAT subscales were invariant across the 26 universities. Finally, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all other group means were conducted for both cognitive domains (Verbal and Quantitative). In both domains, King Saud University had the highest mean score among all universities. Moreover, its mean factor score was significantly higher than any other university besides Dammam University. On the other hand, several universities allocated at the northern and Southern borders of the country exhibited the lowest factor mean scores.

Sensory integration is an essential function of human life, and its decline causes difficulties in the quality of life, especially in older adults. In this study, we proposed an arm-reaching task based on a virtual reality head-mounted display (VR-HMD) system to assess sensory integration in daily life, and examined whether reaching task performance was associated with age and resting-state functional connectivity (rsFC) between the brain regions of interest involved in sensory integration. We hypothesized that performance during a reaching task with multiple cognitive loadings would be affected by aging. The gap angle between the reaching hand and target positions was compared between older and middle-aged adults as a measure of sensory integration function. In addition, rsFC, which was significantly correlated with the gap angles of individual participants in the older adult group, was identified using resting-state functional magnetic resonance imaging data. The mean gap angle was significantly larger in the older adults than in the middle-aged group and was also significantly correlated with connections between the left primary motor area and the left inferior temporal gyrus, temporo-occipital part. Because the connectivity between the areas is known to be related to visuomotor integration, the results suggest the involvement of visuomotor integration in the decline of sensory integration function in old age and the validity of the gap angle during the proposed VR-HMD task as an index for the decline in function.

Diesel is consistently a very popular fuel for internal combustion engines. Its consumption in the European Union has been rising over recent years, as has the number of engines increasingly sensitive to fuel contamination. One of the most important parameters affecting diesel quality is water content. Although its exceedances of the standard’s permissible amount are not common, they carry the risk of serious damage to expensive, modern fuel injection systems. Current methods of measuring water content require both specialised personnel and equipment, as well as transporting the sample to a suitable laboratory. The research presented in this paper was aimed at verifying whether it would be possible to test the moisture content of diesel using impedance spectroscopy. Once refined, such measurement method could be used in situ. Analysing the properties of diesel is challenging, mainly because many types of the fuel are sold, the chemical composition of which is always a well-guarded manufacturer’s secret. The experimental results obtained on many types of commercially available diesel show that it is possible to use impedance spectroscopy to estimate the water content of different types of diesel fuel. The measurement accuracy achieved makes it possible to detect approaching or exceeding the permissible water content.

The conformity assessment of products or a measured value with the given standards is carried out based on the global risk of producers and consumers calculation. A product may conform to specifications but be falsely rejected as non-conforming. This is about the producer's risk. If a product doesn't meet the requirements but is falsely accepted as conforming, that poses a risk to the consumer. The conventional approach to risk assessment, which yields only a single numerical value for the global risk of producers and consumers, is naturally extended, and utilized for assessing risk in measurement models with linear regression. The outcomes of the two-dimensional extension, along a moderate scale, are the parabolas with an opening upwards. Risk surfaces were obtained through three-dimensional extension over the area limited by the moderate scale and guard band axes. Four models with different ranges of tolerance intervals were used to test this innovative method of risk assessment in linear regression. The corresponding standard measurement uncertainties are determined by applying a simplified measurement model with the use of comprehensive data on the measurement performance and by determining measurement uncertainty derived from consideration of the functional relationship obtained by linear regression analysis. Models that utilize information from linear regression analysis to determine measurement uncertainty are biased towards risks at the edges of the moderate scale. Testing the model's performances with metrics related to the confusion matrix, such as the F1 score, further substantiated this assertion. The diagnostic odds ratio has been proven to be extremely effective in identifying the curve along the guard band axis, along which the global risks of producers and consumers are at their lowest.

In the world's first pig-to-human cardiac xenotransplant, the elevated levels of porcine cytomeg-alovirus (PCMV) are considered key factors contributing to patient mortality. This has renewed attention to PCMV, a virus widely prevalent in pigs. Currently, there are no effective drugs or vaccines targeting PCMV, and its high detection difficulty poses challenges for prevention and control research. In this study, antiviral small hairpin RNA (shRNA) was selected and inserted into the Rosa26 and miR-17-92 loci of pigs via a CRISPR/Cas9-mediated knock-in strategy. Further in vitro viral challenge experiments demonstrated that these genetically edited pig cells could effec-tively limit PCMV replication. Through this process, we constructed a PCMV-infected cell model, validated partial viral interference sites, enhanced gene knock-in efficiency, performed gene editing at two different gene loci, and ultimately demonstrated that RNA interference (RNAi) technology combined with CRISPR/Cas9 has the potential to generate pig cells with enhanced antiviral infec-tion capabilities. This opens up possibilities for the future production of pig populations with anti-viral functionalities.

Technology has transformed aeroponics, providing numerous advantages over traditional soil-based agriculture. However, there remains a need for comprehensive information on the types of technology employed in aeroponics and their impact on the growing process. This paper presents a literature review of 47 studies published between 2012 and 2023 in peer-reviewed journals and conference proceedings. As a result, it identifies the status and tendencies in the usage of technology in aeroponics as well as the main opportunities and challenges. Furthermore, this paper introduces the Technology Adoption and Integration in Sustainable Agriculture (TAISA) model. TAISA is a model that identifies the degree of technology integration in any sustainable agriculture system to determine how technology affects production and quality. Overall, the systematic review suggests that technology can play a vital role in improving the efficiency and sustainability of aeroponic farming. However, careful consideration must be given to the costs and technical requirements associated with using these technologies. Moreover, the TAISA model reveals that technology has primarily been employed in creating new processes that are not possible to implement without the help of technology. Therefore, we conclude that technology use has taken root in aeroponics and can be promoted to improve sustainable agriculture.

In this paper we investigate into the possible resurrection for the aether and it’s compatibility with the theory of relativity. We revisit the Michelson-Morley experiment and expose some of the major inadequacies. In this regard, we have presented the true/corrected form of the Michelson-Morley experiment. We have tried to revise the interpretational aspect of the mathematical formalism regarding the metric of Minkowskian space-time in addendum with it’s relationship to the two theories of time. We herein have also tried to restrain some of the quantum mechanical issues arising from the mainstream understanding of the mathematical formalism of the Minkowskian manifold. Essentially, we have argued in favour of aether to be incorporated into our mathematical formalism as well the physical understanding of the universe.

Human longevity is an important but difficult goal due to the extreme complication of human body. If people could repeatedly transfer their consciousness from old bodies to new ones, their lifespan might be prolonged extremely. However, there are several difficulties which prevent the achievement of such a technique. In this paper, we propose an approach that can transfer human consciousness indirectly, and avoid or significantly relieve those difficulties. The strategy of our approach is to integrate the consciousnesses of two bodies (old and new) into a unique consciousness. By doing so, the consciousness is extended to the new body. After that, the consciousness shrinks and remains in the new body when the old body dies. This may also apply to integrating more than two bodies of human, or animal, or even across different species. After investigating thousands of literatures, we find quite strong evidence (related discoveries and technologies) that can support the proposed approach and its advantages. Beside prolonging human lifespan, the approach could also have other meaningful applications.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

This paper studies the duration patterns of unemployment spells for immigrants and the determinants of unemployment’s completion into one of a number of studied labour market states in Finland. We estimate a duration model for unemployment with competing risks of its terminating into employment, labour market training or economic inactivity. Taking into account the wide period of observation and opportunities to analyse processes of labour market integration during various periods of economic development in Finland, in combination with the individualistic character of the labour careers of immigrants, this research is beneficial owing to the many various findings concerning labour market integration of immigrants. The approach undertaken in this research has a dualistic “descriptive-dynamic” character under which integration is understood as a never-ending process, which is conditioned by a time period of long-term existence and a context of solitary action. We find that transitions out of unemployment spells have a cyclical character; after every new “cycle” in unemployment, the probability of terminating unemployment decreases further. We also find that ascriptive factors make sense in the process of job-placement of immigrants from unemployment. Therefore, the gender, education and age of immigrants, as well as the effect of the period in which first unemployment occurred, potentially predict transitions out of unemployment and further labour market integration of immigrants.

The purpose of this article is to address two questions that will aid researchers in understanding FinTech’s inception, development, and potential impact on the stability of the financial system. First, it explains why financial technology is a current phenomenon. While many of the underlying technology for FinTech breakthroughs have been around for some time, it is only recently that financial institutions and entrepreneurs have begun to apply them to financial goods and services. Supply and demand factors in "conventional" financial innovation have been studied, and they have been found to converge, leading to a high rate of innovation. And second, this article explains why FinTech is being covered in greater depth than other types of innovation. This study introduces the concept of "depth" of innovation as a means of answering this question. The more fundamental the innovation, the more it will affect the financial sector. In this paper, we demonstrate that many recent developments in the field of financial technology (FinTech) are truly revolutionary advances, with far-reaching implications for the financial services industry. In addition to the benefits of more adaptability, higher transformational potential might bring increased risk to economic security.

The technology for determining the point’s coordinates on the earth’s surface using the global navigation satellite system (GNSS) is becoming the norm along with ground-based methods. In this case, determining coordinates does not cause any particular difficulties. However, to identify normal heights using this technology with a given accuracy, special research is required. The fact is that satellite determinations of geodetic heights (h) over an ellipsoid surface differ from ground-based measurements of normal height (HN) over a quasi-geoid surface by a certain value called quasi-geoid height or height anomaly (ζ). In relation to determining heights of a certain territory, the concept of geoid height (N) is usually operated when dealing with a geoid model. In this work, geodetic and normal heights are determined for 5 control points in three different regions in Lebanon, where measurements are carried out using GNSS technology and geometric levelling. The obtained quasi-geoid heights are compared with geoid heights derived from the global Earth model EGM2008. The results obtained showed that, in the absence of gravimetric data, the combination of global Earth model data, geometric levelling for selected areas and satellite determinations allows the creation of a high accurate altitude network for mountainous areas.

This paper applied case study research to design architectures for green-field supply chain integration. The integration design is based on a case study of a supply chain integration of 5 companies, operating in different, but supply chain complimenting industry sectors. The case study research is applied to design and validate the architectures in a real world scenario. The supply chain integration architectures enable the conversion of individual into integrated strategies. The architectures are categorised and the process develops into a conceptual system for identifying the correlations between individual participants’ strategic areas of interest and the integrated supply chain areas of interest. The novelty of this paper is a conceptual system for green-field supply chain integration architectures, which can be applied in real world by supply chain practitioners.

A temperature-modulated pyroelectricity measurement system for a small single crystal is developed and applied to standard sample measurements performed on a thin single crystal of lithium niobate. The modulation measurement is based on the AC technique, in which the temperature of the sample is periodically oscillated, and the synchronized pyroelectric signal is extracted using a lock-in amplifier. Temperature modulation is applied by irradiating periodic light on the sample placed in the heat exchange gas. To apply this technique to the transparent reference sample, a commercially available black resin is coated on the sample’s surface to absorb the light energy and transmits it to the specimen. The experimental results are analyzed using a two-layer heat transfer model to verify the effect of the light-absorbing layer as well as the non-contact temperature modulation system.

The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study's goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lesser greenhouse gas emission as compared to the electricity produced by traditional fossil fuel. Gleichen, is a small town in southern Alberta and is near to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess electricity generated or buying electricity when there is less or no availability of solar and wind. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh which is competitive with the price of electricity generated by natural gas and coal which is 0.127 CAD/kWh.

This paper proposed three-dimensional numerical simulation method by coupling of electrostatic and fluid fields to evaluating the performance of electrical sensor in the concentration measurement of gas/solid two-phase flow. Compared with the static numerical simulation, this real-time dynamic 3-D simulation method can research on a designed capacitance sensor combining the dynamic characteristics of the two-phase flows for concentration measurement. Several fluid-electrostatic models of transmission pipes with different sensor structures are built. Under different test positions and different particle concentrations, the flow characteristics and the corresponding electric signals can be obtained, and the correlation coefficient between the concentration values and the capacitance values are used for performance evaluation of the sensors. The effects of flow regimes on concentration measurement are also been investigated in this paper. To validate the results of simulation, an experimental platform with horizontal straight pipe for phase volume concentration measurement of solid/air two-phase flow is built, and the experimental results agree well with simulation conclusions. The simulation and test results show that the coupling models can give constructive reference opinions for the sensor design and collection of installation position in different transmission pipelines, which are very important for the practical process of pneumatic conveying system.

The up-to-date challenge towards clean road transport are non-exhaust emissions. Important advances regarding measurement systems, including well defined characterisation techniques, as well as regulation, will happen in the next few years. In this work we present detailed results of particle emissions from a test bed for wheel suspension and brakes, consisting of aerosol (size distribution, particle number (PN) and mass (PM)) and electron microscopy measurements (EM) under different load conditions. Standard tyres and brakes from series production were tested with a high-load driving cycle while particle measurements were conducted by gravimetric measurements and with a TSI SMPS, a TSI APS and a GRIMM OPS. Furthermore, samples were analyzed by electron microscopy. A bimodal particle size distribution (PSD) was obtained with the SMPS, with peaks at 20nm and around 400nm. EM analysis of >1400 single particles from the electrostatic sampler matches the PSD results. EM analysis also showed ultrafine particles, mainly from O, Fe, Si, Ba, Mg and S and also fractal particles with high C fractions. Our results suggest, in agreement with previously published literature, that particulate emissions are related to brake disc temperature and occur in significant amounts above a threshold temperature.

As of not long ago, understanding the administrative conduct of cells has been sought after through autonomous investigation of the transcriptome or the proteome. In view of the focal creed, it was commonly accepted that there exist an immediate correspondence between mRNA records and produced protein articulations. In any case, late examinations have demonstrated that the relationship among's mRNA and Protein articulations can be low because of different factors, for example, unique half lives and post record apparatus. In this manner, a joint investigation of the transcriptomic and proteomic information can give valuable experiences that may not be translated from singular examination of mRNA or protein articulations. This article audits the current significant methodologies for joint investigation of transcriptomic and proteomic information. We order the various methodologies into eight primary classes dependent on the underlying calculation and last investigation objective. We further present analogies with different spaces and talk about the current exploration issues around there.

Single-phase-to-ground fault in non-effectively grounded systems poses serious public safety concern. Along with increasing deployment of low-voltage (LV) sensors, new opportunities and ways are created for solving this traditional problem in distribution systems. A new approach, identifying primary single-phase-to-ground line fault and locating it through measurement data from smart sensors deployed in the secondary side of distribution transformers, is proposed in this paper. When a fault occurs in primary distribution feeder, the transient aerial mode voltage (AMV) of each LV smart sensor is calculated. The fault line can be identified by an abrupt change value of AMV at LV side. Next, by finding the position of the maximum value of this AMV from LV sensors on the fault line, the fault location can be pinpointed to two neighboring distribution transformers. The proposed method has been proven to be efficient and reliable by simulation studies.

Self-report measurement is frequently used in human sports to assess training adaptations [1, 2]. This is a technique novel to the equestrian sport. The aim of this study was to describe how elite event riders of Germany evaluate their own fitness as well as that of their horses for the entire duration of an eventing season. Additionally, correlations with possible influencing external factors such as type of training or duration of grazing were also investigated. Short online questionnaires were used to allow eight riders to describe the training of their horses. Five criteria (general performance, ability to concentrate, general state of mind, general muscular condition and emotional wellbeing) were used to assess both, their horse's, as well as their own wellbeing. A 1-10 rating scale was used to score each criterion resulting in an average of 38 points out of 50 (maximum wellbeing) for horse (Std. dev. 0.55) and rider (Std. dev. 0.65) respectively. A total of 120 questionnaires were analysed. A correlation could be demonstrated (Spearman's correlation coefficient = 0.5) between rider and horse score, whereby it only became a linear correlation above 30 points. In addition, the horse score correlates positively with its success at competitions. While the horses were rated similarly throughout the season, the riders’ perceived welfare was higher in the middle of the season compared with the beginning and end of the season. Regularly turned-out horses resulted in higher horse scores (Linear mixed model, p=0,04, n=120). It can be concluded that the self-report measurement of fatigue and wellbeing can be a useful tool for trainers and riders to better determine the horse’s fatigue and recovery. It should be noted that external factors influence both, rider and horse assessment.

The group delay response of chirped fiber Bragg gratings (CFBG) written in polarization-maintaining fiber can be measured using the beat spectrum of the reflections from the two polarization axis, with a resolution and reproducibility better than 50 fs. The method is theoretically described, and we analyze the effect of group delay ripples (GDR) on the performance of a stretcher-compressor pair used in chirped pulse amplification systems. Ripples with a spectral period of the order of the pulse bandwidth are the most deleterious. Those are readily captured with our method, despite the limit on resolution due to the fiber polarization beat length. As a rule of thumb, the GDR should not exceed half the pulse duration. The reconstructed phase of the CFBG is also used to predict the pulse compression performance for a given device. Measurement of GDR as low as 161 fs is experimentally demonstrated.

Tipping bucket rain gauges (TBRs) have been, and apparently will continue to be one of the most widely used pieces of equipment for rainfall monitoring, being frequently used for the calibration, validation and downscaling of radar and remote sensing data, due to their major advantages–low cost, simplicity, and low energy consumption. Thus, many works have focused and continue to focus on their main disadvantage–measurement biases (mainly in wind and mechanical underestimations). However, despite arduous scientific effort, calibration methodologies are not frequently implemented by monitoring networks operators or data users, propagating bias in databases and in the different applications of such data, causing uncertainty in the modeling, management, and forecasting in hydrological research, mainly due to a lack of knowledge. Within this context, this work presents a review of the scientific advances in TBR measurement uncertainties, calibration, and error reduction strategies from a hydrological point of view, by describing different rainfall monitoring techniques in Section 2, summarizing TBR measurement uncertainties in Section 3, focusing on calibration, and error reduction strategies in Section 4, a discussion and perspectives in Section 5, and conclusions in Section 6, providing an overview of the of the state of the art and future perspectives of the technology.

Recent studies have demonstrated a relationship between poor vitamin D status and respiratory infections and diarrhea among young children. Acute lower respiratory infections (ALRI) and diarrhea are among the two most important causes of death in under-5 children. In this analysis, we examine the extent to which vitamin-D deficiency (<10 ng/ml) predicts these outcomes using data from a randomized controlled trial (RCT) of daily folic acid and/ or vitamin B12 supplementation for six months in 6 to 30 months old children conducted in Delhi, India. Of the 960 subjects who had vitamin-D concentrations measured, 331(34.5%) were vitamin-D deficient. We found, after controlling for relevant potential confounders (age, sex, breastfeeding status, wasting, stunting, underweight, anemia status at base line and season), the risk of ALRI was significantly higher among vitamin-D deficient (OR 1.26; 95% CI: 1.03 to 1.55) compared to vitamin-D-replete children in the six months follow-up period. Vitamin-D status was not significantly associated with episodes of diarrhea and clinical pneumonia. The extent of causal relationship of vitamin-D status and ALRI needs to be explored in further studies.

Film cooling technology is of great significance to enhance the performance of aero-engines and extend service life. With the increasing requirements for film cooling efficiency, researchers and engineers have carried out a lot of work on the precision and digital measurement of cooling holes. Based on the above, this paper outlines the importance and principles of film cooling technology, reviews the evolution of cooling holes. Also, this paper details the traditional measurement methods of the cooling hole used in current engineering scenarios with their limitations and categorizes digital measurement methods into five main types, including probing measurement technology, optical measurement technology, infrared imaging technology, computer tomography(CT) scanning technology, and composite measurement technology. The five types of methods and integrated automated measurement platforms are also analyzed. Finally, through a generalize and analysis of cooling hole measurement methods, this paper points out technical challenges and future trends, providing a reference and guidance for forward researches.

Microwave radiation diagnosis technology can detect thermal changes in skin tissue earlier than anatomical changes, but its detection accuracy is limited by non-target radiation interference in the measurement environment, additional measurement errors of system units, and energy scattering and transmission between skin tissues. This paper aims to address the scientific challenges of analyzing the forward and inversion modelling detection mechanism of layered accurate temperature measurement of human skin tissue based on multi-band. The study focuses on the construction of a pencil beam antenna optimization system, the optimization strategy of high-sensitivity correlated radiometer architecture, and the high-precision multi-band forward and inversion modelling detection algorithm. The key technologies include: (1) A new method of integrated modeling and multi-index optimization of antenna with high directivity and small aperture is proposed, and a priori knowledge-guided neural network of pencil beam distribution is constructed to realize the inversion model of antenna structural parameters; (2) The influence mechanism of high sensitivity correlated radiometer architecture error is analyzed, and a periodic phase shift error correction algorithm based on uniform polar circle is designed; (3) Combining deep learning theory and hyperparameter optimization framework, an iterative model is established, and the objective function modified by the penalty factor is defined to realize a new detection method combining forward and inversion. This paper presents a theoretical foundation for the industrialization of microwave radiation diagnostic technology.

The issue of measurement reliability is certainly undervalued in the local agricultural marketplace organization. Besides, there was nothing identified concerning the extent of cereal commodity trade measurement cost. Hence, this paper aimed to estimate the magnitude of cereals trade quantity measurement cost caused by instrument error and unreliability; mainly by targeting the local marketplace in Ethiopia. The survey was conducted in six different districts’ marketplaces (n = 602) of Oromia region by employing administered structured questionnaires and site mass measurement calibration. The gathered data were analyzed using independent samples t-test, one sample t-test, and analysis of variance. According to the findings, the actual value measurement means of the quantity of most local units of the farmers were greater than small traders. The independent t-test result indicated that the average values of the quantity of the majority of units of measurement between farmers and small traders were varied significantly. Estimated measuring instruments’ error and unreliability associated average measurement cost of one-day market transaction over total cereals marketed amount were higher comparatively for a sack, bowl, and glass units. This study demonstrates that homogeneity in measurement, policy, and institutions that aid cereals trade would have an indispensable role to reduce measurement costs and ensure equitable exchange.

External hoof characteristics, balance, and conformation have been extensively studied in horses; however, mules remain understudied in these aspects. This study evaluated the size, shape, and symmetry of untrimmed and unshod forelimb hooves, compared the symmetry between forelimb hooves and stratified external forelimb hoof measurements based on the body condition score of mules raised in the foothill plains of northern Thailand. The forelimb hooves of 38 mules were photographed and 33 parameters, including angular and linear measurements, were analyzed. Despite the absence of shoeing and trimming, these mules exhibited optimal left-right forelimb hoof symmetry, with no significant (p < 0.05) differences in: outer wall length and inner wall length (OWL - IWL); sole length and sole width (SLS - SW); dorsal hoof wall length and heel length (DHWL - HL); and frog length and frog width (FL - FW). However, significant (p < 0.05) differences were observed within each body condition score group for forelimb hoof measurements for DHWL, IWL, heel separation (HS), heel bulb distance (HBD), SW, FW, and FL. These findings provide valuable insights into mule welfare and management, contributing to understanding of the interplay between overall health and hoof conformation in the study area.

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows to estimate direct, diffuse and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterisation techniques and allows the generation of high quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data and its resolution if two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient.

For the electromagnetic eddy current testing, various methods have been proposed for reducing the lift-off error on the measurement of samples. In this paper, instead of eliminating the measurement error caused by the lift-off effect, an algorithm has been proposed to directly measure the lift-off distance between the sensor and non-magnetic conductive plates. The algorithm is based on a sample-independent inductance (SII) feature. That is, under high working frequencies, the inductance is found sensitive to the lift-off distance and independent of the test piece under an optimal single high working frequency (43.87 kHz). Furthermore, the predicted lift-off distance is used for the thickness prediction of the non-magnetic conductive samples using an iterative method. Considering the eddy current skin depth, the thickness prediction is operated under a single lower frequency (0.20 kHz). As the inductance has different sensitivities to the lift-off and thickness, the prediction error of the sample thickness is different from that of the lift-off distance. From the experiments on three different nonmagnetic samples – aluminium, copper, and brass, the maximum prediction error of the lift-off distance and sample thickness is 1.1 mm and 5.42 % respectively at the lift-off of 12.0 mm.

One of the most popular techniques for determining electrical properties of material is the free-space measurement technique. With the potential for new applications requiring efficient, accurate and broadband material measurement systems using higher millimeter-wave and terahertz frequencies, the free-space measurement method has received renewed interest. This is mainly due to its simplicity, favorable properties as a non-destructive method, and it allows transmission and reflection measurements without any physical contact with the sample. This paper reviews and discusses state- of-the-art free space material measurement systems, starting with the different measurement techniques available for material characterization, their important concepts, post-processing in determining their properties, and progress towards expanding their use at higher frequencies. Also, this paper reviews dielectric material characterization using the free space method focusing on their application extension towards the higher frequencies. Besides, the algorithms for conversion methods and usage of lens in free space material measurement system was discussed in this paper. Finally, a future perspective on the outlook of this free space method is presented prior to the conclusion.

Surgeries that take place in medicine and dentistry or during any form of childbirth results in a significant amount of blood loss. The prevalent measurement methods that surgeons and anesthesiologists utilize as the “gold - standard” has several drawbacks. There are numerous other methods to measure blood loss, which, however, due to their impracticality and limitations, are not ideal either. This paper focuses on minimally invasive neurosurgery in particular, by taking into account a surgical technique known as Endoscopic Endonasal Transphenoidal surgery (EETS), which is used to treat pituitary tumors and adenomas. Along with the review of the existing literature pertaining to blood loss management, this paper proposes a modified electrode probe method along with the concept of usage, computer interface, and the system of integration. The probe is intended to measure the hematocrit count from the collected blood under all circumstances, such that the medical practitioner is assisted to improve the blood loss management technique for better patient recovery.

Within the past decade, the aerospace engineering industry has evolved outside the constraints of using single, large, custom satellites. Due to increased reliability and robustness of commercial off the shelf (COTS) printed circuit board (PCB) components, missions instead have transitioned towards deploying swarms of smaller satellites. This approach significantly decreases the mission cost by reducing custom engineering and deployment expenses. Nanosatellites are able to be quickly developed with a more modular design at lowered risk. The Alpha mission at Cornell Space Systems Studio is fabricated in this manner. However, for the purpose of this mission, only one satellite was initially developed. This manuscript will discuss a systems engineering approach to the development of this satellite. As a disclaimer, this manuscript is written from a systems perspective. Therefore it will follow many subsystems from a wide range of functionalities. The research in this manuscript was kept broad with the hope to contribute to the mission as a system, through a range of development phases including validation and verification of existing methods. The two systems that will be primarily focused on are the Attitude Control System (ACS) of the carrier nanosatellite (cubesat), and the RF communications on the ex-creted picosatellites (chipsat). Milestones achieved in chipsat RF include chipsat to chipsat communication, chipsat to SDR ground station communication, packet creation, error correction, appending a preamble, and filtering the signal. Achievements on the ACS side included controller traceability/verification and validation, software rigidity tests, hardware endurance testing, Kane damper and IMU tuning. These developments matured the technological readiness level (TRL) of our systems in preparation for satellite deployment.

Lately Silicon Carbide (SiC) and Galium Nitride (GaN) based high frequency power conversion has gained immense popularity which stems from relatively low switching energy, robustness to high temperature operation, wide-band gap and superior thermal limits. While this aspect inherently results in a high-density power stage design, the design of adjoining passive components, particularly magnetics, needs careful attention. This is especially true if the compatibility of core and winding options and their performance is limited with the use of higher switching frequency. In this regard, this paper presents a brief review of existent research conducted in materials, optimization and integration of magnetics for single and three phase applications, ranging from filters, resonant inductors to isolation transformers. Design knobs pertaining to medium voltage (MV) applications, low-voltage (LV) applications, e-mobility sector such as more electric aircrafts (MEAs) and electric vehicles (EVs) are discussed. Guidelines for magnetics design are summarized for each application with a projected roadmap on future trend for magnetics.

This study aims to assess using a smartphone app (DecibelX), as a noise measuring alternative to the more costly traditional use of measuring noise levels with a Sound Level Meter (SLM). The study compares the accuracy of the app to readings taken with a SLM and dosimeter, and also evaluates the app’s performance for pure tone and narrow band noise. And a usability study identifies strengths and weaknesses related to usability of the app.

Cancer being a multi-factorial disease, a multi-target approach is needed to treat it with minimal side-effects. Therefore, combined use of a proven herbal formula with chemo-therapy could be the better therapeutic. It may maintain homeostasis by synergistically targeting multiple signaling pathways involved in tumorigenesis, thus circumventing recurrence, resistance, and immunosuppression. Here we aim to determine the effectiveness and safety of an FDA-approved herbal formula, SR033 in combination with 5-fluorouracil (5FU) and paclitaxel (PTX). We report chemo-sensitization and chemo-synergy in HeLa and MCF-7 cell lines, immunomodulation of COX-2, PD-L1, VEGF and TGFβ and overall survival in-vitro and in-vivo via oral and topical delivery of SR033. In-vitro, SR033/5FU significantly reverses 5FU and PTX-resistance, lower COX-2, and PD-L1, resulting in TGFβ/ VEGF axis modulation. Furthermore, the study suggests that due to anti-oxidative potential of SR033, oral administration exerts chemo-preventive activity and restores cellular compartment in solid tumor and ascites-bearing mice models. Furthermore, the topical application, SR033L with low-dose 5FU increases survival rate, reduces tumor growth, and completely restores local and peripheral neutrophil-lymphocyte ratio in solid tumor mice model. The study indicates that SR033 could be a strong candidate in combination with low-dose 5FU and PTX for a holistic approach to cancer management.

The paper delves into an extensive exploration of the integration of the circular economy paradigm within the realm of additive manufacturing (AM). The objective is to comprehensively investigate existing methodologies for structuring the symbiotic relationship between circular economy and additive manufacturing, while meticulously analyzing the current research gap concerning the implementation of circular economy principles in additive manufacturing practices. A thorough review focusing on the sustainability of additive manufacturing within the circular economy framework was conducted. This review aims to recognize and delineate pertinent aspects related to post-use material valuation in AM, recyclability of materials, and the environmental footprint associated with these processes. Emphasis was placed on the significance of examining circular economy facets concerning additive manufacturing processes to establish a holistic understanding. The overarching goal of this review is to augment knowledge regarding the potential advantages and benefits derived from the seamless integration of circular economy principles within AM. By elucidating the activities essential to attain compliance with the Sustainable Development Goals, this study endeavors to illuminate the pathway toward promoting sustainable development through the harmonious marriage of additive manufacturing and the circular economy.

Antimony (Sb) Substitution less than 10 % is examined on a single crystal of a layered superconductor NdO_0.7F_0.3BiS₂. Superconducting transition temperature of the substituted samples decreases with increasing Sb concentration. A lattice constant along the c axis showed a large decrease compared with that along the a axis. Since in-plane chemical pressure monotonically decreases with increasing Sb concentration, the suppression of the superconductivity is well described in terms of the decrease in in-plane chemical pressure.

Environmental pollution by noise is one of the most serious health threats nowadays. The impact of noise on the human body depends not only on the sound level but also on its spectral distribution. Reliable measurements of the environmental noise spectrum are often hampered by the very high price of top quality measuring devices. This paper explores the possibility of using much cheaper audio recorders for frequency analysis. Comparative research were performed in laboratory and field conditions, which showed that, with some limitations, these devices can be useful for the needs of environmental noise frequency analysis. This fact gives an opportunity for reduce the cost of noise analysis experimental work.

This paper introduces a novel approach to addressing the challenge of accurately timing short distance runs, a critical aspect in the assessment of athletic performance. Electronic photoelectric barriers, although recognized for their dependability and accuracy, have remained largely inaccessible to non-professional athletes and smaller sport clubs due to their high costs. A comprehensive review of existing timing systems reveals that claimed accuracies beyond 30 milliseconds lack experimental validation across most available systems.To bridge this gap, a mobile, camera-based timing system is proposed, capitalizing on consumer-grade electronics and smartphones to provide an affordable and easily accessible alternative. By leveraging readily available hardware components, the construction of the proposed system is detailed, ensuring its cost-effectiveness and simplicity. Experiments involving track and field athletes demonstrate the proficiency of the proposed system in accurately timing short distance sprints. Comparative assessments against a professional photoelectric cells timing system reveal a remarkable accuracy of 62 milliseconds, firmly establishing the reliability and effectiveness of the proposed system. This finding places the camera-based approach on par with existing commercial systems, thereby offering non-professional athletes and smaller sport clubs an affordable means to achieve accurate timing.In an effort to foster further research and development, open access to the device's schematics and software is provided. This accessibility encourages collaboration and innovation in the pursuit of enhanced performance assessment tools for athletes.

Background: Exposure to environmental tobacco smoke (ETS) presents substantial health risks for pregnant women and newborn infants. Measurements of ETS include invasive and expensive biochemical tests as well as less invasive and lower-cost self-reported exposure and avoidance measures. Better understanding of self-report measures will help to select ETS assessments for evaluation. Methods: This analysis was conducted within the context of a tailored video intervention to reduce tobacco smoking and ETS exposure during pregnancy and after delivery, in the control group sample of 147 nonsmoking women. Measurements of salivary cotinine concentration, self-reported ETS exposure and avoidance behaviors were captured at 32 weeks gestation and 6 months postpartum. Results: Salivary cotinine concentration was significantly related to ETS avoidance among pregnant nonsmokers at 32 weeks gestation, but not ETS exposure. At 6 months postpartum, both the reported ETS exposure of the infant and maternal avoidance behaviors to reduce her infant’s exposure were associated with the infant’s salivary cotinine concentration. At 32 weeks gestation and 6 months postpartum, avoidance behaviors decreased as exposure increased. Discussion: This study suggests that for nonsmoking women during pregnancy, report of tobacco smoke avoidance is more valid than report of exposure. After delivery, self-reported ETS exposure or avoidance are associated with each other and biochemical measurement of salivary cotinine. These results provide researchers and clinicians with evidence to support inclusion of avoidance behaviors in the selection of ETS measure.

Objectives: Few studies in literature evaluate the "mean measure" of root divergence. Most of them are linear measurements, they hardly describe the dental furcation conformation. It is left to the subjectivity of the operator deciding whether a furcation is convergent or divergent. The goal of this study is to create a visual evaluation method to overcome these problems giving a conformation of the entire interradicular space. Material and methods: A user-friendly software (Paint®, Windows10®) was used to measure endo-oral radiographs of upper and lower molars. Three kinds of measurements were taken. Three operators used the software to measure 20 radiographs, then the technique was repeated on 250 radiographic images to identify an average measurement. The ratio of these three measurements allowed to develop a new visual evaluation method of the interradicular space. Results: Intra and inter-operator reproducibility was statistically assessed on a sample of 20 anonymous endo-oral radiographs measured by 3 blind operators. Then, a sample of 250 anonymous endo-oral radiographs were measured by a blind operator and were statistically evaluated to identify an average value to define a main conformation of the interradicular space. Measurements made by the 3 operators on the 20 radiographic images showed that the technique is reproducible, and a mean value of the interradicular space was obtained. Conclusions: A new anatomical evaluation of the interradicular space in its entirety, which could help the clinicians in the therapy of furcated molars, can be obtained.

The integration of artificial intelligence (AI) technologies into business practices presents both opportunities and challenges for Sabah, Malaysia. This dynamic abstract explores the latest research problem at the intersection of AI and business in Sabah, focusing on optimizing resource allocation in agriculture and enhancing tourism experiences through AI-driven solutions.In Sabah's agricultural sector, AI holds immense potential to revolutionize traditional farming practices. With limited arable land and unpredictable weather patterns, farmers face significant challenges in maximizing crop yields while minimizing resource inputs. Through the application of machine learning, remote sensing, and IoT devices, researchers aim to develop precision farming techniques that can analyze soil health, monitor crop growth, and predict pest outbreaks with unprecedented accuracy. By optimizing resource allocation and enhancing decision-making processes, these AI-driven solutions have the potential to revolutionize Sabah's agriculture industry, promoting sustainability and resilience in the face of environmental uncertainties.Moreover, the tourism industry in Sabah stands to benefit from AI integration, particularly in enhancing visitor experiences and destination management. With its diverse natural landscapes and rich cultural heritage, Sabah attracts tourists from around the globe. AI-powered recommendation systems, tailored to individual preferences and behavior, have the potential to provide personalized travel itineraries, optimize resource allocation, and boost visitor satisfaction. Additionally, natural language processing (NLP) algorithms can analyze online reviews and social media sentiments, providing valuable insights for destination marketing and management strategies. By harnessing the power of AI, Sabah can elevate its tourism offerings, attract more visitors, and enhance its reputation as a premier travel destination.However, alongside these opportunities, challenges abound in the integration of AI into Sabah's business landscape. Concerns regarding data privacy, cybersecurity, and ethical implications must be carefully addressed to ensure the responsible and sustainable deployment of AI technologies. Furthermore, the digital divide and limited access to technology in rural areas pose barriers to widespread adoption, necessitating comprehensive strategies for capacity building and infrastructure development.In conclusion, the advancement of AI integration in Sabah's business landscape holds immense promise for driving innovation, economic growth, and sustainability. By addressing the research problems outlined in this abstract, researchers, policymakers, and industry stakeholders can collaboratively navigate the opportunities and challenges of AI integration, paving the way for a prosperous and inclusive future for Sabah, Malaysia.

This study investigates the impact of financial integration on international dynamics from the perspective of volatility shocks. To achieve this, I employ an IRBC model with time-varying volatilities, recursive preferences, and a global bank. The model demonstrates that volatility shocks trigger precautionary saving incentives, but the specific effects vary based on the type of shock. In the presence of productivity volatilities, countries with a higher level of financial integration exhibit greater divergence in their business cycles, while financial integration tends to result in more synchronized business cycles in the face of financial volatilities. Disregarding volatility shocks would underestimate the impact of financial integration on the comovement of business cycles across countries. Furthermore, welfare analysis also indicates that financial markets play a crucial role in enhancing social welfare, regardless of the type of volatility.

In the modern world, stress has become a pervasive concern that affects individuals' physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management, by measuring heart rate, heart rate variability (HRV), and various matrices related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and Biofeedback using smartwatches and finger monitor/sensor pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. we apply various algorithms and methodologies employed for HRV analysis and stress detection is discussed, including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers use smartwatch technology to address stress and promote holistic well-being, we discuss the data's advantages and limitations, future developments, and the significance of user-centered design and personalized interventions. Keywords: smartwatch; stress; wearable device; heart rate variability; comparative analysis

Rural tourism plays an increasing role in maintaining sustainable rural development. In-11 tegrating culture into rural tourism is multifaceted. Local communities have often been regarded as 12 homogeneous, and different voices within them are selectively presented or re-interpreted by pow-13 ers. A better understanding of how and why cultures are integrated into rural tourism is urgently 14 needed. This paper aims to investigate (1) the aims and motives of tourism managers to integrate 15 cultural concepts into rural tourism; (2) who has participated in the cultural integration process; and 16 (3) how cultures have been integrated into rural tourism. Based on a scoping literature review, we 17 found that cultures could add more attractions, such as historical heritage, artwork, cultural land-18 scape, customs, food, and language, to the natural landscape and bring more tourists to rural areas. 19 However, integrating cultures into rural tourism is not always successful. Conflicts of interest 20 among different stakeholders are also often found. Some of the worst cases of cultural integration 21 have even destroyed the original natural landscape and local cultures. While cultural integration is 22 complicated, injustice and perverse effects do not have to be a consequence of integrating cultures 23 into rural tourism. Multi-way communication among tourism providers, managers, and consumers 24 can mitigate disruptive outcomes and unlock positive social outcomes.

Molecular methods have revolutionised virtually every area of biology, and metazoan phylogenetics is no exception: molecular phylogenies, molecular clocks, comparative phylogenomics, and developmental genetics have collectively transformed our understanding of the evolutionary history of animals. Moreover, the diversity of methods and models within molecular phylogenetics has resulted in significant disagreement among molecular phylogenies as well as between these and traditional phylogenies. Here, I argue that tackling this multifaceted problem lies in integrating evidence to infer the best evolutionary scenario. I begin with an overview of recent developments in early metazoan phylogenetics, followed by a discussion of key conceptual issues in phylogenetics revolving around phylogenetic evidence and theory. I then argue that integration of different kinds of evidence is necessary for arriving at the best evolutionary scenario rather than the best-fitting cladogram. Finally, I discuss the prospects of this view in stimulating interdisciplinary cross-talk in early metazoan research and beyond.

The need to consider sustainability has substantially increased the complexity of implementing construction and infrastructure projects and new management practices have emerged during the past decade to tackle the global sustainability challenges, where the engagement and coordination of broader competences from stakeholders throughout the supply chain is required. This new project management paradigm has been accompanied by greater attention to the concept of collaborative business arrangements, often called partnering, that has emerged in construction and infrastructure projects to improve project deliveries. However, there are uncertainties about the optimal strategy to foster, integrate and maintain the required collaboration, particularly in sustainable management practices in infrastructure maintenance projects. This paper addresses these uncertainties, based on a single case study of an infrastructure maintenance contract involving an extensive collaborative business arrangement. The findings reveal that different collaborative practices affect diverse aspects of sustainable project management. Further, the extensive collaborative business arrangement has promoted sustainable deliveries based upon organizational learning and continuous improvements. Thus, this study offers an encouraging example of how extensive collaboration can be fostered and play a key role in sustainable project management practices.

The growing interest in the use of energy storage systems to improve the performance of tramways has prompted the development of control techniques and optimal storage devices, displacement, and sizing to obtain the maximum profit and reduce the total installation cost. Recently, the rapid diffusion of renewable energy generation from photovoltaic panels has also created a large interest in coupling renewable energy and storage units. This study analyzed the integration of a photovoltaic power plant, supercapacitor energy storage system, and railway power system. Random optimization was used to verify the feasibility of this integration in a real tramway electric system operating in the city of Naples, and the benefits and total cost of this integration were evaluated.

We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the i-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.

The primary objective of this study is to examine the extent of financial integration between Latin American and US financial markets, particularly in light of recent efforts to foster integration through trade agreements. Spanning from January 1, 1990, to December 31, 2019, the sample focuses on major market indices and key sectors. Financial integration is quantified using a DCC multivariate GARCH model, incorporating a smooth transition model, structural breaks, and regression-based approaches. Results indicate increased comovement with the US for main market indices in Argentina, Chile, Colombia, Mexico, and Peru, while Brazil shows a decrease. Similar trends are observed in sectoral analyses. The study also reveals heightened correlation post-trade agreements. Structural break analysis highlights significant shifts in dynamic correlations for countries with US free trade agreements. These findings support the argument of increased financial integration, bearing significance for portfolio diversification and international policy formulation.

Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigated the relationship between the symbiotic units, environments, models, and effects of the integration of medical and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects for on this integration. Results: The path coefficient of symbiotic unit on the symbiosis model was 0.46 (p&lt;.001), the path coefficient of symbiotic environment on symbiosis model was 0.52 (p&lt;.001). The path coefficient of the symbiotic unit and environment was 0.91 (p&lt;.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that Health policy-makers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical and disease prevention in public hospitals.

1) Background: In service business areas, design enhances the customer experience through the elements which anticipate specific emotional responses of customers. Many service companies are keen to develop and examine design elements from the customer perspective. Furthermore, recently, having considered the significance of customers’ emotional responses by design elements, categorising design elements into manageable dimensions can facilitate the evaluation of design elements. However, design elements and dimensions of design value are not defined in the current service marketing literature, and companies need a measurement tool and managerial guideline to their innovative value creation and compelling service delivery. For these reasons, this research aims to categorise the design value dimensions and propose the managerial implication for the innovative use of design; 2) Methods: This study used the mixed methodology; two stages of interviews and SEM (Structural Equation Modelling); 3) Results: Interview analyses facilitate the identification of design elements in the service delivery process. SEM results underpin the relevance of the categorised design elements and their impact on customer loyalty by comparing different groups (country and time elapsed from experience); and 4) Conclusions: Findings are the fundamentals of developing measuring tool for design and trigger future studies for conceptualising intangible assets.

In the dynamic landscape of Sabah's socio-economic development, the integration of AI technologies holds both promise and challenge. While AI has the potential to drive economic growth, enhance productivity, and elevate quality of life, it also brings forth concerns regarding job displacement, skill gaps, and unequal distribution of benefits. The latest research problem in the realm of AI and employment in Sabah revolves around ensuring inclusive and sustainable development amidst this technological disruption. This encompasses two key dimensions: skill development and education, and labor market dynamics. Addressing the research questions necessitates a multifaceted approach. Firstly, in the realm of skill development and education, there is a critical need to assess the adequacy of existing programs in equipping the workforce with AI-driven skills. Strategies such as promoting STEM education, fostering digital literacy, and facilitating lifelong learning initiatives, particularly among marginalized communities, are essential. Additionally, fostering collaboration between stakeholders and implementing curriculum reforms are pivotal steps in enhancing the alignment between educational curricula and the demands of an AI-driven economy.

In this paper, we dive into the exciting world of wireless communication, focusing on how millimeter-wave technology and Multiple-Input Multiple-Output phased array antennas are shaping the future of 5G and the upcoming 6G technologies. We cover the latest advancements in millimeter-wave and beam-forming technologies, emphasizing their role in enhancing network security and efficiency in automotive vehicles through dual radar communication. Our discussion spans the benefits, applications, challenges, and solutions of these technologies individually from millimeter-wave to beam-forming technology and joint radar communications, alongside a look at their theoretical and practical implementations. We emphasize the integration of beam-forming technology in joint radar communications for future automotive vehicles and its impact on automotive systems, smart cities, and the Internet of Things (IoT). Looking ahead, we discuss the potential of these technologies to transform future tech landscapes, while also addressing the security implications of merging communication and radar capabilities. This paper aims to provide a clear view of the advancements and prospects of millimeter-wave, beam-forming, and dual radar communication technologies.

Sensory processing is a crucial function of the nervous system that significantly affects a large portion of the population, particularly older individuals who may be dealing with different forms of dementia. The global population of people aged 65 or older has reached a substantial count of around 703 million, representing approximately 9% of the total global population. Within this demographic, an estimated 5-8% of those aged 60, highlighting the growing need to address sensory modulation challenges for healthy aging. Sensory diet, derived from sensory integration theory, provide a tailored approach to modulating sensory experiences and triggering neuroplastic changes in the brain. Recent neuroimaging studies have revealed intricate structural and functional alterations in the brain associated with the implementation of sensory diets. Furthermore, the integration of the Metaverse, augmented reality, and virtual reality has opened up personalized experiences, fostering cognitive stimulation and emotional well-being for individuals during aging. This article offers a comprehensive exploration of the effectiveness of sensory diets in enhancing attentional control, self-regulation, and alleviating sensory-related distress among the healthy aging and dementia population. By employing precise quantitative evaluations such as sensory processing scales and advanced neuroimaging methodologies, it presents solid evidence of the tangible impact of these interventions. Emphasizing the importance of interdisciplinary cooperation and leveraging technological advancements, the article underscores the crucial need for customized sensory diets to optimize sensory processing and improve the overall well-being of older individuals contending with sensory modulation challenges and dementia.

Building Information Modelling (BIM) methodology have been optimizing the construction activity in all sectors: multidisciplinary designs development; construction planning and monitoring; building management and maintenance. A BIM environment aggregates several disciplines and different skillsets and in order to control and improve the quality of a BIM project, a BIM manager is required. The BIM manager has the responsibility to coordinate all tasks involved in a building design and associated activities usually workout over the project documents. The professional can access to various discipline models, located in a shared board, and request for amendments if inconsistencies are detected. The present study issue is illustrated with three building cases were distinct specific projects, disciplines and tasks were elaborated: collaboration between disciplines (architecture, structures and construction); structural analyses and reinforcement details; quantity take-off of materials and cost estimation; construction scheduling and simulation. Although there are limitations in the implementation of BIM methodology in all sectors and stages, within the construction industry, BIM have been bringing an important improvement in the quality of a building design, reflected in the quality of the final product. BIM methodology is a current demand in the construction industry supported on advanced technology and in an adequate management of projects, were the BIM manager has an important role.

Construction productivity entails a wide range of work combinations. When human resources are scarce, it is critical to replace manpower with machinery, and calculating machinery productivity is crucial. Traditional labor productivity methods, however, cannot address dredging complex multi-attribute decision-making (MADM) problems. Aiming to address the limitations of the traditional labor productivity method, this paper extends the data envelopment analysis (DEA) and proposes a new dredging productivity evaluation method. The proposed method can solve the problem of evaluating various combinations of factors (single-input, multiple-input, sin-gle-output, and multiple-output) and the problem suggesting that the efficiency of the DEA method'scalculation results is equal to 1. The effectiveness of the proposed method was verified using reservoir dredging examples. The simulation results show that the proposed method has broad applicability, can accurately evaluate the related dredging performance issues, and provide directions for construction managers to improve labor productivity.

Isometric exercises for physiotherapeutic rehabilitation are often prescribed, with little quantification of the load being prescribed. This article aimed to provide a framework and practical examples of how the physiotherapist may take a more quantitative evidence-based approach to isometric assessment, monitoring, and exercise prescription of knee osteoarthritis, by integrating a strain gauge into their practice. Strength measures to monitor were discussed. A series of fourteen studies were reviewed, with the intent of identifying isometric exercises that had been utilized in the rehabilitation of knee osteoarthritis. Of the fourteen studies, the three most identified isometric exercises were seated knee extension, knee flexion, and the supine straight leg raise. The integration of strain gauge technology with these exercises provided the focus of the remainder of the article.

A time integration scheme based on semi-Lagrangian advection and Laplace transform adjustment has been implemented in a baroclinic primitive equation model. The semi-Lagrangian scheme makes it possible to use large time steps. However, errors arising from the semi-implicit scheme increase with the time step size. In contrast, the errors using the Laplace transform adjustment remain relatively small for typical time steps used with semi-Lagrangian advection. Numerical experiments confirm the superior performance of the Laplace transform scheme relative to the semi-implicit reference model. The algorithmic complexity of the scheme is comparable to the reference model, making it computationally competitive, and indicating its potential for integrating weather and climate prediction models.

Urban flood risk mapping is an important tool for the mitigation of flooding in view of human activities and climate change. Many developing countries, however, lack sufficiently detailed data to produce reliable risk maps with existing methods. Thus, improved methods are needed that can improve urban flood risk management in regions with scarce hydrological data. Given this, we estimated the flood risk map for Rasht City (Iran), applying a composition of decision-making and machine learning methods. Flood hazard maps were produced applying six state-of-the-art machine learning methods such as classification and regression trees (CART), random forest (RF), boosted regression trees (BRT), multivariate adaptive regression splines (MARS), multivariate discriminant analysis (MDA), and support vector machine (SVM). Flood conditioning parameters applied in modeling were elevation, slope angle, aspect, rainfall, distance to river (DTR), distance to streets (DTS), soil hydrological group (SHG), curve number (CN), distance to urban drainage (DTUD), urban drainage density (UDD), and land use. In total, 93 flood location points were collected from the regional water company of Gilan province combined with field surveys. We used the Analytic Hierarchy Process (AHP) decision-making tool for creating an urban flood vulnerability map, which is according to population density (PD), dwelling quality (DQ), household income (HI), distance to cultural heritage (DTCH), distance to medical centers and hospitals (DTMCH), and land use. Then, the urban flood risk map was derived according to flood vulnerability and flood hazard maps. Evaluation of models was performed using receiver-operator characteristic curve (ROC), accuracy, probability of detection (POD), false alarm ratio (FAR), and precision. The findings showed that the CART method is most accurate method (AUC = 0.947, accuracy = 0.892, POD = 0.867, FAR = 0.071, and precision = 0.929). The results also demonstrated that DTR, UDD, and DTUD played important roles in flood hazard modeling; whereas, the population density was the most significant parameter in vulnerability mapping. These findings indicated that machine learning methods can improve urban flood risk management significantly in regions with limited hydrological data.

This paper introduces a method for tunnel point cloud and BIM model integration and cross-section monitoring, providing information to analyse tunnel cross-sections and surrounding rock deformation, and support for tunnel maintenance and reconstruction. Three types of data are processed for the integration: laser scanning point cloud, BIM tunnel model and terrain model from oblique photogrammetry. An adaptive BIM modelling scheme is proposed for tunnels with alien structures. Precise spatial registration of the data sets is conducted by applying singular value decomposition (SVD) algorithm to calculate transformation parameters from the point cloud model to the BIM model. Since the tunnel central line has high-order derivability, a cross-section calculation method based on tangent vector is proposed to obtain the cross-sectional profile of tunnels at any mileage. The proposed method has been verified by applying it to a tunnel reconstruction project. The experiment results show that the tunnel point cloud and the BIM model were highly coincident after the integration. The developed program can effectively get the cross-section of the tunnel at any mileage, and correctly express the spatial relationship between the BIM tunnel, the point cloud of tunnel and the external mountainous terrain.

In this paper we explore extending the concept of common cross-study Common Data Element concepts beyond simple demographics to cover disease-specific concepts relevant to imaging. We test interactively linking the resulting database to the associated images in a federated manner. We examine the use of existing standards, not only for terminology, but for interchange of serialized data in forms familiar to imaging and clinical trials specialists and their dedicated systems. Our intent is to perform preliminary work to inform both the upcoming Imaging Data Commons specifically, as well as more general integration projects beyond imaging.

Microgrids (MGs) have evolved as critical components of modern energy distribution networks, providing increased dependability, efficiency, and sustainability. Effective control strategies are essential for optimising MG operation and maintaining stability in the face of changing environmental and load conditions. Traditional rule-based control systems are extensively used due to their interpretability and simplicity. However, these strategies frequently lack the flexibility for complex and changing system dynamics. This paper provides a novel method called hybrid intelligent control for adaptive MG that integrates basic rule-based-control and deep learning techniques, including gated recurrent units (GRU), basic recurrent neural network (RNN) and long short-term memory (LSTM). The main target of this hybrid approach is to improve MG management performance by combining the strengths of basic rule-based systems and deep learning techniques. These deep learning techniques readily enhance and adapt control decisions based on historical data and domain-specific rules, leading to increasing system efficiency, stability, and resilience in adaptive MG. Our results show that the proposed method optimises MG operation, especially under demanding conditions such as variable renewable energy supply and unanticipated load fluctuations. This study investigates special RNN architectures and hyper-parameter optimization techniques with the aim of predicting power consumption and generation within the adaptive MG system. Our promising results show the highest-performing models indicating high accuracy and efficiency in power prediction. The finest-performing model accomplishes an R2 value close to 1, representing a strong correlation between predicted and actual power values.

This paper comprehensively reviews sensors and sensing devices developed or/and proposed so far utilizing two smart materials: electrorheological fluids (ERFs) and magnetorheological materials (MRMs) whose rheological characteristics such as stiffness and damping can be controlled by external stimuli, an electrical voltage for ERFs and a magnetic field for MRMs, respectively. In this review article, the MRMs are classified into magnetorheological fluid (MRF), magnetorheological elastomer (MRE) and magnetorheological plastomer (MRP). To easily understand the history of sensing research using the two smart materials, the order of this review article is organized in a chronological manner of ERF sensors, MRF sensors, MRE sensors and MRP sensors. Among many sensors fabricated from each smart material, one or two sensors or sensing devices are adopted to discuss on the sensing configuration, working principle and specifications such as accuracy and sensitivity. Some sensors adopted in this article include force sensor, tactile device, strain sensor, wearable bending sensor, magnetometer, display device and flux measurement sensor. After briefly describing what have been reviewed in a conclusion, several challenging future works, which should be done for practical applications as sensors or sensing devices, are remarked in terms of new technologies such as artificial intelligence neural network in which several parameters affecting the sensor signals can be precisely tuned or controlled. It is sure that this review article is very helpful to make creative sensors using not only the proposed smart materials but also several different types of smart materials including shape memory alloys and active polymers.

In this research the possibility of using pH change to measure proton conductivity of proton exchange membranes (PEM) or else known as polymer electrolyte membranes are tested with using an experimental setup prepared by using pH meters. PEMs are an important part of the fuel cells and proton conductivity of the PEMs are one of the most important properties of the PEMs. Also, proton conductivity is the one of the biggest limiting factors of fuel cells thus it is important to measure the proton conductivity of the PEMs while trying new polymers or new types of membranes. But as current measurement methods do not have a standard and can be separated into mainly two different measurement methods which are Electron Impedance Spectroscopy (EIS) and Ion Exchange Capacity (IEC). EIS gives clearer results, but it needs an impedance analyzer machine, platinum electrodes and setup so this cannot be possible for every researcher due to its economical aspect. For IEC it is basically a titration method to see acid groups in the polymer or polymer matrix which are directly responsible for proton conductivity so this can show an indirect measurement of proton conductivity. But as for this one drawback are firstly this one is an indirect measurement and secondly needs overnight bath in solution can take long times. So, the possibility of using pH can be easier and both from time and economical aspect if it can be proven the give a direct relationship between pH change and proton conductivity.

Background and Objectives: The Temperament Evaluation of Memphis, Pisa, Paris and San Diego Autoquestionnaire (TEMPS-A) is designed to assess affective temperaments. The short version of TEMPS-A (TEMPS-A-SV) was translated into diverse languages for its broad application in research and clinical settings. However, no study was conducted to validate the Korean version of TEMPS-A-SV among patients with mood disorders. The purpose of this study is to examine the reliability and validity of the TEMPS-A-SV in mood disorder patients of the Korean population. Materials and Methods: In this cross-sectional retrospective study, a total of 715 patients (267 patients with major depressive disorder, 94 patients with bipolar disorder I, and 354 patients with bipolar disorder II) completed the Korean TEMPS-A-SV. Cronbach's alpha and McDonald’s omega was used to assess reliability. Exploratory factor analysis (EFA) was also performed. Spearman's correlation coefficient was used to examine associations between five temperaments. The difference in five temperament scores between gender or diagnosis groups were analyzed, and the correlation between five temperament scores and age were tested. Results: The Korean TEMPS-A-SV displayed good internal consistency (α = 0.65–0.88, ω = 0.66–0.9) and significant correlations between the subscales except one (correlation between hyperthymic and anxious). Using EFA, a two-factor structure was produced: Factor I (cyclothymic, depressive, irritable, and anxious) and Factor II (hyperthymic). The cyclothymic temperament score differed by gender and the anxious temperament score was significantly correlated with age. All the temperaments, except for irritable temperament, showed significant differences between diagnosis groups. Conclusions: Overall, our findings indicate that TEMPS-A-SV is a valid and reliable measure of estimating affective temperaments among Koreans. Our results confirm validity of TEMPS-A-SV among Korean patients with mood disorders. However, more study is required on affective temperaments and associated characteristics in people with mood disorders.

Lift-offs of the sensor could significantly affect the measurement signal and reconstruction of material properties when using the electromagnetic (inductive) eddy current sensor. Previously, various methods (including novel sensor designs, and features like zero-crossing frequency, lift-off point of intercept) have been used for eliminating the measurement error caused by the lift-off distance effect of the sensor. However, these approaches can only be applied for a small range of lift-off variations. In this paper, a linear relationship has been found between the sensor lift-off and ratio of dual-frequency eddy current signals, particularly under the high working dual frequencies. Based on this linear relationship, the lift-off variation can be reconstructed firstly with a small error of 2.5 % when its actual value is up to 10 mm (10.1 % for 20 mm). The reconstructed lift-off is used to further get the property of the material under a low single frequency. Experiments on different ferrous metals have been carried out for the testing of the reconstruction scheme. Since the inductance is more sensitive to the material property (and less sensitive to the lift-off) under low frequencies, the reconstruction error of the material property is much smaller than that of the lift-off, with 1.4 % under 12 mm (and 4.5 % under 20 mm).

The accurate assessment of wound size is a critical step in advanced wound care management. This study aims to introduce and validate a Light Detection and Ranging (LiDAR) technique for measuring wound size. Twenty-eight wounds treated from December 2022 to April 2023 at the Chunganam National University Hospital were analyzed. All wounds were measured using three techniques; conventional ruler methods, the LiDAR technique, and ImageJ analysis. Correlation analysis, linear regression, and Bland-Altman plot analysis were conducted to validate the accuracy of the newly introduced method. The measurement results (Mean ± Standard deviation) obtained using the Ruler method, LiDAR technique, and ImageJ analysis were 112.99 ± 110.07 cm², 73.59 ± 72.97 cm², and 74.29 ± 72.15 cm², respectively. The Pearson correlation coefficient was higher in the LiDAR application (0.995) than the conventional ruler methods (Mean difference; -5.0000 cm2), as was the degree of agreement (Mean difference; 38.6933 cm2). Wound size measurement using LiDAR is a simple and reliable method that allows practitioners to conveniently assess wounds with a flattened and irregular shape. However, non-flattened wounds cannot be assessed owing to the technical limitations of LiDAR.

Mathematical models of cognition measure individual differences in cognitive processes, such as processing speed, working memory capacity, and executive functions, that may underlie general intelligence. As such, cognitive models allow identifying associations between specific cognitive processes and tracking the effect of experimental interventions aimed at the enhancement of intelligence on mediating process parameters. Moreover, cognitive models provide an explicit theoretical formalization of theories regarding specific cognitive process that may help overcoming ambiguities in the interpretation of fuzzy verbal theories. In this paper, we give an overview of the advantages of cognitive modeling in intelligence research and present models in the domains of processing speed, working memory, and selective attention that may be of particular interest for intelligence research. Moreover, we provide guidelines for the application of cognitive models in intelligence research, including data collection, the evaluation of model fit, and statistical analyses.

Tuberculosis (TB) associated stigma is well-documented phenomenon that may contribute to sub-optimal TB care in Pakistan. The objective of study was to assess TB related knowledge and perceived stigma among community members. This was cross-sectional survey using convenience sample of 183 individuals recruited between October and December 2017. A validated stigma measurement tool developed by Van Rie et al. was adapted. Data was analyzed using SPSS version 20.0. 183 individuals (73% males; n = 134) participated in survey. Eighty-seven percent were aware that TB is curable disease (n = 159) and 91% thought that it could be transmitted by coughing (n = 167). However, respondents also thought that TB was spread through contaminated food (73%; n = 134), sharing meals (55%; n = 100), sharing utensils (53%; n = 96) and by having sexual intercourse with a TB patient (51%; n = 93). Fifty-seven percent (n = 104) associated TB with high levels of stigma. Persons who had less than six years of education (crude OR = 1.2; 95% CI: 0.89, 1.72) and lacked knowledge that TB is curable (crude OR = 3.42; 95% CI: 1.20, 9.70) were more likely to associate TB with stigma. In addition, females (crude OR = 1.33; 95% CI: 0.87, 2.04) and those who were unemployed (crude OR = 1.06; 95% CI: 0.65, 1.74) were also more likely to associate TB with stigma. We found an association between lack of knowledge about TB and perceived stigma. This highlights need for improved education and awareness about TB.

The use of artificial intelligence (AI) is becoming more prevalent across industries as diverse as healthcare, finance, and transportation. Artificial intelligence is based on the analysis of large data sets and requires a continuous supply of high-quality data. However, using data for AI is not without its challenges. This paper comprehensively reviews and critically examine the challenges of using data for AI, including data quality, data volume, privacy and security, bias and fairness, interpretability and explainability, ethical concern, and technical expertise and skills. This paper examines e these challenges in details and offers advices on how companies can address them. By understanding and addressing these challenges, organizations can harness the power of AI to make smarter decisions and gain a competitive advantage in the digital age.

Co-integration and Causality was built to conduct studies on causality relation between carbon intensity and coal consumption leading to providing important basis for the transition to a low carbon economy. The EG two-step method was performed to study the relation between carbon intensity and coal consumption of China during 1990-2015 and the co-integration and Granger test was constructed to build up the co-integration and error correction models for analysis of the interaction between carbon intensity and coal consumption. The results showed that in long term there is a stable co-integration relation and a positive correlation between carbon intensity and coal consumption; whereas fluctuations exist in short term and there is a one-way Granger causality of carbon intensity with respect to coal consumption.

The direct measurements of the magnetic flux density in steel blocks within Compact Muon Solenoid (CMS) magnet yoke are performed with 22 flux loops installed in selected regions of the yoke. The 10,000-ton CMS magnet flux return yoke encloses a 4 T superconducting solenoid with a 6-m-diameter by 12.5-m-length free bore and consists of five dodecagonal three-layered barrel wheels and four end-cap disks at each end. The yoke steel blocks, mostly up to 620 mm thick, serve as the absorber plates of the muon detection system. A TOSCA 3-D model of the CMS magnet has been developed to describe the magnetic field everywhere outside of the tracking volume which was measured with a field-mapping machine. In the present study, for the first time, the reliable reconstruction of the magnetic flux density in the steel blocks of the yoke is performed using the CMS magnet standard discharges from the operational magnet current of 18.164 kA. To provide this reconstruction, the voltages induced in the flux loops (with amplitudes of 20–250 mV) have been measured with six 16-bit DAQ modules and integrated offline over time. The results of the flux loop measurements during three magnet ramp downs are presented and discussed.

Prolonged sedentary behaviour (SB) has shown to be detrimental to health. Nevertheless, population levels of SB are high and interventions to decrease SB are needed. This study aimed to explore the effect of an individualized consultation intervention aimed at reducing SB and increasing breaks in SB among college employees. A pre-experimental study design was used. Participants (n=36) were recruited at a college in Massachusetts, USA. SB was measured over 7 consecutive days using an activPAL3 accelerometer. Following baseline measures, all participants received an individualized SB consultation which focused on limiting bouts of SB >30 minutes, participants also received weekly follow-up e-mails. Post-intervention measures were taken after 16 weeks. Primary outcome variables were sedentary minutes/day and SB bouts >30 minutes. Differences between baseline and follow-up were analyzed using paired t-tests. The intervention did not change daily sedentary time (-0.48%; p>0.05). The number of sedentary bouts >30 minutes decreased significantly by 0.52 bouts/day (p=0.015). In this study a consultation based SB intervention was successful in reducing number of bouts >30 minutes of SB. However, daily sedentary time did not reduce significantly. These results indicate that consultation-based interventions may be effective if focused on a specific component of SB.

About a decade ago, active optical crop canopy sensors are being used to manage in-season variable nitrogen (N) fertilization in cornfields to match the plant demand that occurs mid season, increasing the efficiency compared to broadcast N applications. There were also initiatives of using ultrasonic sensors to measure plant height on-the-go for N application and crop water demand estimation, but no studies have integrated the optical, ultrasonic and canopy temperature for crop water stress assessment. The objective of this chapter is to evaluate the crop water status using infrared thermometry integrated with optical and ultrasonic sensors. Specifics objectives are: (i) evaluate the corn canopy temperature under different previous crop, N rates and irrigation levels; (ii) test a procedure for water stress assessment in commercial cornfields using the integration of sensors, (iii) correlate plant based sensor measurements (N status, plant height and canopy temperature) with grain yield, soil attributes and detailed topographical features, and (iv) study the spatial dependence of canopy temperature. This study was conducted in one small plot study area and on three producer’s fields in 2010. The small plot experiment consisted of two irrigation levels (70 and 100% of evapotranspiration – ET), two previous crop schemes (corn after corn – CC and corn after soybeans – CS), and four N rates (0, 75, 150, 225 kg N ha^-1). Canopy temperature, optical reflectance and plant height was measured from R2 until R6 in the small plots. At the producer’s fields, three long strips across center pivots were used to have a non-limited N and water crop and then continuous georeferenced sensors measurements were taken during side-dress (V11 growth stage) in about 10 hectares in each field. In the small plot study the crop canopy temperature was influenced by the irrigation levels and N rates. The procedure proposed could be used to identify zones in the producer’s field where water stress can be a yield limiting factor other than N derived. Inside the zones considered that water stress played a major whole, there were low correlations between plant height, plant N status and canopy temperature, indicating that the canopy temperature had more influence from water stress than vegetation cover. Concave and lower elevation areas had higher yields compared to convex and high elevation, showing that the detailed elevation mapping can be beneficial to delineate stables zones that possibly could be used in variable irrigation systems. The spatial dependence of canopy temperature was over 65 meters across producers’ sites, showing that the commercial high clearance applicator’s swath width was adequate to obtain accurate maps. The integration of plant N status, plant height and canopy temperature was beneficial to detect water stressed zones in the field. Opportunities can be foresee also for on-the-go N fertilization using integration of these sensors because is likely that water stress can be confounded with different N supply during the growing season and in different zones in the field.

The reuse and integration of data give big opportunities, supported by the F.A.I.R. data principles. Seamless data integration from heterogenous sources has been interest of the geospatial community for long time. However, 3D city models, BIM and information supporting smart cities present higher semantic and geometrical complexity, which pose new challenges, never tackled in a comprehensive methodology. Building on previous theories and studies, this paper proposes an overarching workflow and framework for multisource (geo)spatial data integration. It starts from the definition of use case-based requirements for the integrated data, guides the analysis of integrability of the involved datasets, suggesting actions to harmonise them, until data merging and validation. It is finally tested and exemplified on a case study. This approach allows the development of consistent, well-documented and inclusive data integration workflows, for the sake of use cases automation in various geospatial domains and the production of Interoperable and Reusable data.

The present paper reports an alternative solution of the measurement problem in quantum theory. The measurement problem can be characterized as that the U-procedure verses the R-procedure. The R-procedure is tested by the Yes/No measurement originally proposed by von Neuman and discussed in details by Penrose. We propose a novel stochastic sampling method to tackle the measurement paradox. Each testing sample produces a pair of Yes-number c and No-number d, which in turn generates a sample phase with respect to the exponential form of (c+id). All the sample phases forms a group G_R. Taking G_R as the sampling potential, combined with the dynamic phase group G_U，we establish a unified model of U-procedure and R-procedure for the evolution of wavefunction. Based on the Born rule, the probability of a sample is given by the squared magnitude of （c+id）. Some metaproperties of the new U-R model, such as natural transformation, consistency, and completeness, are presented. The present work provides a new picture of quantum mechanics and alike. The measurement problem widely exists in dynamic analysis, higher cognition, and large data modeling. Thus, the work reported here has a wide range of applications. Keywords: The measurement problem; U-R procedures; the Yes/No type measurement; stochastic sampling; sample phase; Born probability.

Multi-junction solar cells comprised of stacked III-V semiconductor junctions represent the highest-efficiency photovoltaic technology, with recent demonstrations exceeding 47% efficiency . Optimizing the design and thickness of each junction is critical for maximizing performance . This work utilizes Silvaco TCAD tools to systematically optimize a 5-junction cell based on AlInP, AlGaInP, AlGaInAs, GaInP, GaAs, InGaAs, and Ge similar to recent record cells . The junction thicknesses are varied using a predictive profiler to sample the parameter space . For each combination, the spectral absorption and I-V characteristics are simulated to determine the efficiency . Statistical analysis identifies the optimal thickness set that maximizes performance to 26% under 1 sun illumination .

This paper is concerned with developing an efficient numerical algorithm for fast implementation of the sparse grid method for computing the $d$-dimensional integral of a given function. The new algorithm, called the MDI-SG ({\em multilevel dimension iteration sparse grid}) method, implements the sparse grid method based on a dimension iteration/reduction procedure, it does not need to store the integration points, nor does it compute the function values independently at each integration point, instead, it reuses the computation for function evaluations as much as possible by performing the function evaluations at all integration points in a cluster and iteratively along coordinate directions. It is shown numerically that the computational complexity (in terms of CPU time) of the proposed MDI-SG method is of polynomial order $O(Nd^3 )$ or better, compared to the exponential order $O(N(\log N)^{d-1})$ for the standard sparse grid method, where $N$ denotes the maximum number of integration points in each coordinate direction. As a result, the proposed MDI-SG method effectively circumvents the curse of dimensionality suffered by the standard sparse grid method for high-dimensional numerical integration.

This paper developed a new theory for supply chain architecture, and engineering design that enables integration of the business and supply chain strategies. The architecture starts with individual supply chain participants and derives insights into the complex and abstract concept of green-field integration design. The paper presented a conceptual system for depicting the interactions between business and supply chain strategy engineering. The system examines the decisions made when engineering the business strategy, with regards to the supply chain design. The system derived with a new understanding of how strategies are integrated, and what are the implications for engineering successful strategies. The study revealed that supply chain design is not considered in great detail before architecting the business strategies. Thus, companies consequentially experience supply chain problems that are likely to be detrimental to the growth potentials. The paper also derived with the findings that proactive and pre-emptive involvement of supply chain participants in the strategy engineering process, would lead to a more robust strategic design.

The aim of the present study was to provide initial validity evidence of a Greek translation of the 24-item Brunel Mood Scale, referred to as the BRUMS-Greek, a measure of anger, confusion, depression, fatigue, tension, and vigour. Data were collected from 1,417 Greek adult exercise participants and 369 physically inactive adults, totaling 1,786 adults (male = 578, female = 1,208) aged 18–64 years (M = 34.73 ± 11.81 years). Given the large univariate and multivariate non-normality, confirmatory factor analyses treating responses as ordered categorical variables was conducted, which supported the hypothesised six correlated-factor measurement model. Internal consistency reliability of BRUMS-Greek subscales was supported via Cronbach alpha coefficients. Construct validity of scales was supported (a) via correlations in the hypothesised direction with trait positive and negative affect, (b) with more positive and less negative moods reported immediately after participation in a single exercise class compared to pre-exercise mood, and (c) with exercise participants reporting more positive and less negative mood states compared to physically inactive adults. Women reported higher tension and lower vigour scores than men. Tension scores were higher and confusion scores lower among younger participants (≤ 35 years) than older participants (≥ 36 years). Participants with obesity reported higher negative mood scores than those who were underweight or normal weight. In sum, the BRUMS-Greek demonstrated acceptable psychometric characteristics, and is proposed to be a suitable measure for use with exercise participants, physically inactive adults, and other Greek populations to explore research questions related to mood.

Quantitative dynamic strain measurements of the ground would be useful for engineering scale problems such as monitoring for natural hazards, soil-structure interaction studies and non-invasive site investigation using full waveform inversion (FWI). Distributed Acoustic Sensing (DAS), a promising technology for these purposes, needs to be better understood in terms of its directional sensitivity, spatial position, and amplitude for application to engineering-scale problems. This study investigates whether the physical measurements made using DAS are consistent with the theoretical reception patterns and experimental measurements of ground strain made by geophones. Results show that DAS and geophone measurements are consistent in both phase and amplitude for broadband (10s of Hz), high amplitude (10s of microstrain) and complex wavefields originating from different positions around the array when: (1) the DAS channels and geophone locations are properly aligned, (2) the DAS cable provides good deformation coupling to the internal optical fiber, (3) the cable is coupled to the ground through direct burial and compaction, and (4) laser phase noise is mitigated in the DAS measurements. The theoretical relationship between DAS-measured and point-wise strain for vertical and horizontal active sources is introduced using 3D elastic finite-difference simulations. The implications of using DAS strain measurements are discussed including directionality and magnitude differences between the actual and DAS-measured strain fields. A method for spatially aligning the DAS channels with the geophone locations at tolerances less than the spatial resolution of the DAS system is proposed.

A method of accuracy error compensation for the time interval is examined, allowing to eliminate the dependence of accuracy error on the duration of measured intervals and minimising the influence of destabilising factors - ambient temperature changes and the initial deviation of the meter clock generator frequency from the nominal value. The compensation method is based on a calibration procedure that measures precise time intervals under conditions of changing ambient temperature. Then the dependence of the accuracy error on temperature for a particular meter is recorded. Based on these data, a correction table is compiled containing correction factors and temperature values at which these factors were determined. Under real measurement conditions, the correction factor corresponding to the current temperature is determined from the table for measured results correction. The table with correction factor values could be stored in the memory of the meter or processing computer. Experimental verification of the method showed that applying a correction for a meter with a standard XO class clock generator (certificated instability of ±50 ppm) can obtain an equivalent clock generator instability of ±0.15 ppm. The application of the method is efficient in cases where the use of high-end clocking to ensure the required measurement accuracy is not economically feasible.

Models of quantum measurements are presented, including observers subject to the laws of quantum mechanics. Observers perform multiple measurements in an attempt to disprove the collapse hypothesis. It is shown that under reasonable assumptions the effort cannot succeed. Under a unitary evolution the end state is a correlation between the result of the first measurement and the result(s) of the others, consistent with the observer's collapse hypothesis. The observer may conclude that the laws of nature include a non-unitary collapse mechanism, even if one does not actually exist. Discard of information is the crucial factor which distinguishes entanglement from measurement.

A variant of the von Neumann-Wigner Interpretation is proposed. It does not make use of the familiar language of wave functionsand observers. Instead it pictures the state of the physical world as a vector in a Fock space and, therefore not, literally, a functionof any spacetime coordinates. And, rather than segregating consciousness into individual points of view (each carrying with it asense of its proper time), this model proposes only unitary states of consciousness, Q(t), where t represents a fiducial time withrespect to which both the state of the physical world and the state of consciousness evolve. States in our world's Fock space areclassified as either 'admissible' (meaning they correspond to definite states of consciousness) or 'inadmissible' (meaning they donot). The evolution of the state vector of the world is such as to always keep it restricted to 'admissible' states. Consciousness istreated very much like what Chalmers calls an "M-Property." But we try to show that problems with the quantum Zeno effect do not arise from this model.

Copper indium gallium diselenide, Cu(In,Ga)Se2, thin-film of about 1.2 μm has been deposited on Mo coated soda lime glass by thermal co-evaporation of Cu, In, Ga, and Se sources. The thin film CIGS was characterized by energy dispersive spectroscopy (EDS) and identified the elemental composition of Cu, In, Ga and Se in the film. A CIGS device was completed by the successive deposition of multiple layers; SLG/Mo/CIGS/CdS/ZnO/ITO which yielded the efficiency of 11%. External spectroscopic ellipsometry (ex-situ SE) was performed on the completed device and the device analysis was performed. Starting with the parameterized complex dielectric functions of the individual component layers, SE analysis was performed using a step-wise procedure that ranks the fitting parameters according to their ability to reduce the mean square error (MSE) of the fit. The resulting layer thicknesses and dielectric functions were used to simulate the external quantum efficiency (EQE) of the device assuming complete active layer collection. Electronic losses were identified by comparison of simulated EQE with the measured EQE. The ultimate goal of this work is the optimization of narrow band-gap CIGS-related solar cells for the bottom layer in tandem devices.

Abstract Introduction: With the containment of the COVID-19 pandemic in Côte d'Ivoire, efforts were made to seamlessly integrate COVID-19 vaccination into the national immunization program. A collaborative initiative involving UNICEF, WHO, GAVI, and partner organizations resulted in the creation of the COVID-19 Vaccine Integration Mapping Tool. This paper presents a case study documenting the field testing of the Integration Mapping Tool and assessing the integration of COVID-19 vaccination within primary healthcare and routine immunization in Côte d'Ivoire. The study aims to describe the pilot process, gather feedback on tool usefulness and challenges, and establish integration priorities through roadmap development. Methods: Under the guidance of the Ministry of Health and Universal Coverage Cabinet, a workshop was conducted with participants from major health programs to field test the tool. Data analysis was performed using Excel, and the results were presented through tables, heat maps, and line graphs. Results: The first-of-its-kind field test of the Integration Mapping Tool in Cote d'Ivoire showcased its potential to bring key partners together to discuss the current state of integration, to improve transparency about resource allocation resource allocation, and enhance data management for the successful incorporation of COVID-19 vaccination into existing immunization systems. The integration of COVID-19 vaccines in Côte d'Ivoire showed a moderate level of progress, with improvement needed in resource allocation, payment systems, targeting of highest risk groups and vaccine administration. Support should be increased for target population identification, distribution points, quality of care mechanisms, and health personnel training. Health information systems and access to essential medicines were relatively satisfactory. Integration into existing programs, intersectoral collaboration, national health strategy, communication strategy, community participation, and data utilization require improvement. The post-workshop satisfaction survey gave the tool a score of .7 out of 10. Early lessons from Côte d'Ivoire provide guidance for enhancing integration, focusing on data-driven decision-making, collaboration, stakeholder engagement, and effective leadership. Conclusion: The successful field test of the Integration Mapping Tool (IMT) in Côte d'Ivoire marks a groundbreaking milestone, exemplifying the transformative potential of innovative tools in immunization practices. The IMT's application sets a precedent for seamless COVID-19 vaccination integration worldwide, emphasizing data-driven decision-making, collaboration, timing, and leadership. The pilot exercise's success in Côte d'Ivoire was attributed to political commitment, well-facilitated workshops, assessments, and the fact that the team in CI had previously already developed some initial integration plan.