There is an international concern for reducing energy consumption and protecting the environment in the construction industry. The energy efficiency of a building depends on the thermal resistance of concrete, and utilizing concrete products with elevated thermal resistance can enhance this aspect. This study analyzes the impact of perlite, as an addition, on the physico-mechanical properties of concrete, with the aim of identifying perlite concrete products that will respond to the improvement of the heat transfer resistance of the building envelope. The study examines the effect of replacing different amounts of concrete aggregates with perlite in percentages of 10%, 20%, 30%, and 100%. The results show that substituting sand with perlite improves the thermal performance of concrete, but its mechanical properties are negatively affected. The research carried out highlighted that perlite can be successfully introduced in the production of concrete blocks used for external non-bearing wall panels, the outstanding feature being the reduction of energy consumption in buildings. Overall, the paper identifies an efficient and environmentally friendly way of using perlite in the construction industry, enhancing the energy efficiency of buildings while minimizing the environmental footprint caused by the construction industry.

The Covid-19 health crisis and its related confinement measures and policies has had a significant impact on the telework adoptions rates, where many businesses were affected abruptly without being prepared, resulting in numerous ad-hoc applications especially while assessing employee’s performance and productivity while working remotely. The difficulties that have emerged with the pandemic have revealed the fragility of the traditional performance appraisal process and the unintentional existence of proximity bias. The Lebanese liquidity crisis is an ongoing financial crisis affecting Lebanon that became fully apparent toward late-2019 when large demonstrations erupted amid acute political instability and economic challenges. In light of the compounded simultaneous occurrence of recurring episodes of COVID-19 outbreaks and the ongoing country’s financial liquidity crisis, the standing of the Lebanese banking sector – who played key roles in the Lebanese economy and were long considered as financially sound and stable – has drastically changed. Faced with such a situation, Lebanese commercial banks started contracting both their branch network and human capital base, and thus they been forced to rethink their human capital strategies by implementing new practices allowing them to adapt to this context of crisis. It is in this perspective that the present research work is inscribed, where we explore the main managerial practices and processes implemented within top Lebanese banks to assess their employee’s performance during the compounded simultaneous crises. A thematic qualitative analysis method of an exploratory nature was adopted, and semi-structured interviews were conducted with senior managers from top Lebanese commercial banks. Results were processed using a deductive approach for themes identifications. Accordingly, it was concluded that in such times of acute crisis, Lebanese banks have altered the purpose of their Performance Appraisal Review (PAR) process and have implicitly or explicitly adopted a Forced Ranking method to primarily focus on retaining just the top performers, while placing those at the bottom on probation with the risk of termination.

The rapid spread of African swine fever virus (ASFV), causing severe and often lethal disease in domestic pigs and Eurasian wild boar, continues to be a threat for pig populations and dependent industries. Despite scientific achievements that deepen our understanding of ASFV pathogenesis, alternative transmission routes for ASFV remain to be elucidated. We previously demonstrated the efficient transmission of ASFV from infected boars to naïve recipient gilts via artificial insemination, thereby highlighting the importance of surveillance in boar semen prior to shipment. Since accurate and reliable detection of even low amounts of ASFV in boar semen is key for disease prevention and control, we established a suitable diagnostic pipeline to efficiently detect ASFV genome in boar semen. Here, we assessed sensitivity, specificity and overall performance of various routine nucleic acid extraction kits as well as qPCR protocols in detecting ASFV genome in blood and semen of boars. Feasibility of respective kits and methods for future use in boar studs was also considered. Variability in sensitivity mostly concerned samples with low to very low amounts of ASFV genome. Ultimately, we defined a well-suited pipeline to precisely detect ASFV genome in boar semen, as early as 2 days post ASFV infection.

The effect of individual and combined supplementation of FA and GPM on physiological variables, productive performance, and carcass characteristics of finishing pigs under heat stress conditions were investigated. Forty Yorkshire x Duroc pigs (80.23 kg) were individually housed and randomly distributed into 4 groups under a 2 x 2 factorial arrangement (n=10): Control (basal diet, BD); FA, BD + 25 mg FA; GPM, BD with 2.5% GPM; and MIX, BD with 25 mg FA and 2.5% GPM. Additives were supplemented for 31 days. The inclusion of FA or GPM did not modify rectal temperature and respiratory rate. An interaction effect (P <0.05) was observed on FI, while average daily gain (ADG) and feed conversion (FC) were not affected by treatments (P >0.05). The inclusion of FA improved hot and cold carcass weight and carcass yields, while the addition of GPM decreased the marbling (P <0.05), and GPM tended to increase loin area (P <0.10). GPM increased liver weight (p <0.05). The addition of GPM and FA can improve some carcass characteristics under heat stress conditions. It is necessary to continue investigating different levels of inclusion of GPM and FA, to demonstrate their potential growth promoting effect in finishing pigs.

Ni-rich layered cathodes are regarded as a potential candidate for high energy-density lithium-ion batteries, but their high sensitivity to air during storage and poor thermal stability are a vital challenge for large-scale applications. In this paper, an effective solid-solution strategy was proposed to improve the surface and structural stability of Ni-rich layered cathodes by introducing Li2MnO3. The structural analysis results indicate that the formation of Li2CO3 inert layers on Ni-rich layered cathodes during storage in air is responsible for the increased electrode interfacial impedance, thereby resulting in the severe deterioration of electrochemical performance. The introduction of Li2MnO3 can reduce the surface reactivity of Ni-rich cathode materials, playing a certain suppression effect on the formation of surface Li2CO3 layer and the deterioration of electrochemical performances. Additionally, the thermal analysis results show that the heat release of Ni-rich cathodes strongly depends on the charge of states, and Li2MnO3 can suppress oxygen release and significantly improves the thermal stability of Ni-rich layered cathodes. This work provide a method to improve the storage performance and thermal stability of Ni-rich cathode materials.

As the lifespan of porous asphalt pavement extends, it invariably experiences performance degradation and an increase in tire/pavement noise compared with the original surface when it is newly built. To understand the medium-term performance of porous asphalt pavement during service and reveal the influence of different pavement performance indicators on tire/pavement noise generation, a seven-year continuous observation and data analysis study was conducted. Porous asphalt with different designed material parameters was taken into account, including thin-layer porous asphalt overlay with a maximum nominal aggregate size of 10mm (PUC-10), porous asphalt with a maximum nominal aggregate size of 13mm (PAC-13), and a two-layer porous asphalt incorporating both PUC-10 and PAC-13 (PUC-10+PAC-13). Using automated pavement technology testing equipment, key performance indexes, including damage rate (DR), rut depth (RD), international roughness index (IRI), and sideway force coefficient (SFC), were measured and calculated. The on-board sound intensity (OBSI) method was used to test noise levels in three types of porous asphalt pavement structures and on a dense graded easy compact asphalt concrete (ECA) for comparison. The progressions of the medium-term performances were analyzed according to the measured results. The correlations between tire/pavement noise levels and testing speed, testing lane, pavement structure, and road condition indicators were investigated by regression. The research results revealed that the DR and SFC of the three types of porous asphalt pavement displayed more significant attenuation in the service period, while the IRI and RD showed small changes. Among them, the SFC demonstrated significant attenuation over the first 4 years, decreasing between 13.8% and 17.0%. From the 3-7 years of operation, the transverse crack disease in porous asphalt pavement progressed rapidly. The three porous asphalt pavement structures tested exhibited commendable noise reduction capabilities. Compared to ECA, the OBSI noise levels of these structures were lower by 2.09 dB, 1.53 dB, and 2.88 dB, respectively. Compared to other pavement condition indicators, RD had a more significant impact on the OBSI value of the PUC-10 porous asphalt pavement. For the PUC-10+PAC-13 porous asphalt pavement, there was a significant linear relationship between the OBSI value and SFC, mainly due to polishing of the coarse aggregate surface. It leads to a decrease of the micro-texture, which lies in increasing tire/pavement noise at high-frequency ranges and decreasing SFC. This study will have guiding significance for the research of the attenuated law and durability improvement of porous asphalt tire/pavement noise.

The aim of this study was to develop and assess the reliability and validity of an innovative field test that measures lower limb explosive power in basketball players (i.e., alactic anaerobic capacity) for the dominant and non-dominant leg. The test examines the performance of vertical, horizontal, and combined movements while holding the ball – similar to penetration of the basket or layup. Such capabilities are required throughout basketball practice and games, combined with upper and lower body coordination. The study included 22 male basketball players, ages 16-18, members of an elite youth league team in Israel. To assess validity, the participants performed the test for each leg, followed by nine standardized tests that were developed for a range of ball games, including basketball. To assess reliability, the participants performed a retest of the unique test 72-hours later. Our findings indicate the validity and reliability of the proposed anaerobic alactic field test for basketball players, for the dominant and non-dominant leg. Moreover, strong correlations were seen between the novel test and the standardized tests, with a high correlation for horizontal explosive power (0.5<r<0.7), a very high correlation for vertical explosive power (0.7<r<0.9), and a nearly perfect correlation for the two combined (r>0.9). In conclusion, this unique field test for basketball players could assist coaches in developing and applying optimal training programs and game plans, for players individually, and for the team as a whole. As the test measures each leg separately, it could also offer an assessment tool following players’ injuries.

The study examines the relationship between corporate social responsibility (CSR) and the corporate life cycle (CLC) of the Chinese pharmaceutical listed companies for the duration of 2010 to 2018. The firm cash flow pattern is used as a proxy for the CLC. The study results indicate that the relationship between CSR and CLC is positive and linear in all the phases of the CLC including, the introduction, growth and maturity stage. Although the relationship is smaller and more significant at the maturity phase. The research further shows that investors incorporating social responsibilities values play a key role in the firm cash flow performance (CFP) across all the firm stages. Whilst, employees espousing social responsibility tenets can only improve CFP in the decline or shakeout stages. Likewise, embedding CSR into the customers group only improves CFP at the maturity stage. Applying the lag effects lead to the same study results. The finding for the bi-directional causality indicates that although CSR can positively influence CFP, CFP is ultimately more associated with the firm unobservable characteristics rather than performance attributed to CSR. On the whole, our study results point to positive causality between CSR and CFP across all the firm life stages and the CSR has a mediating effect on each life cycle.

While considering the sensitivity over the parameter optimization, it is essential to determine which parameters have the most significant implications on model performance. This study focuses on the baseflow recession constant as one of the independent basin parameters to forecast low flows, perform hydrograph analysis, and calibrate rainfall-runoff models for significant improvement. Prior studies examined that the optimization of data adjustment parameters can improve the hydrological model performance and determine the minimum acceptable data length for data scarce regions using the Xinanjaing model. However, it is essential to pay special attention to the sensitivity of the recession constant, which can also impact the model performance during the data scarcity. Therefore, this study extends the research to comprehend the recession constant sensitivity over data adjustment parameters in the shorter datasets leading to more reliable parameter estimation. In terms of that, this study explores how recession constant affects hydrological parameter estimation on annual scale while keeping data adjustment parameters constant in continuous hydrological modeling, employing the Xinanjiang (XAJ) model as a case study. This study considered two approaches of recession constant (cg); (i) assessing the relationship between cg and the data adjustment parameter (Cep), for the 28-year datasets, (ii) investigating the significant impacts of the sensitivity of cg over Cep in shorter datasets which can affect the estimation of the acceptable minimum data length in the data scarce basins. The study underscores the importance of the recession constant sensitivity for reliable continuous hydrological model predictions, especially in data-scared areas. The study’s outcomes enhance the understanding of the importance of parameter sensitivity and its relationship in conceptual hydrological modeling during the data limitations.

Bioinformatics is a rapidly developing field enabling scientific experiments through computer models and simulations. Considering the vast databases of biological data available, it is ex-tremely important to develop efficient methods and algorithms for their processing. Sequence comparison is the best method for studying the evolutionary interaction between genes. It is based on alignment – the process of arranging two or more sequences to achieve the maximum level of identity and degree of similarity. The paper presents a new version of the algorithm for pairwise DNA sequences alignment, based on a new method called CAT, where a dependency with a previous match and the closes neighbor are taken in consideration to increase uniqueness of the CAT profile and to reduce possible collisions, i.e. two or more sequence having same CAT profiles. This makes proposed algorithm suitable for finding exact match of a concrete DNA se-quence in a big set of DNA data faster. The generation of CAT profiles is made once before data has been uploaded to the database, allowing the profiles to be used as metadata for the sequenc-es. It consists of an algorithm to calculate a CAT profile against the selected reference sequences and an algorithm to compare two sequences based on the calculated CAT profiles. Improve-ments in generation of the CAT profiles, are detailed described in the paper. Block scheme, pseudo code tables and figures were updated according to the proposed new version and ex-perimental results. Experiments have been carried out with the new version of the method and different datasets to align DNA sequences based on the CAT method. New experimental results in terms of collisions, speed, and efficiency of the proposed solutions are presented. Experiments related to the performance comparison with Needleman-Wunsch were re-executed with the new version of the algorithm to confirm that we have the same performance. An analysis of the per-formance of the proposed CAT based algorithm against Knuth–Morris–Pratt algorithm, which has a complexity of O(n) and is one of the most widely used for searching biological data, was performed. The impact of prior matching dependencies on uniqueness for generated CAT pro-files is investigated. The analysis of the experimental results obtained by sequence alignment shows a small deviation of the proposed algorithm based on the CAT method, which can be ig-nored if this deviation is acceptable at the expense of performance. The time efficiency of the CAT algorithm remains constant, regardless of the length of the sequences. Therefore, the ad-vantage of the proposed method is its fast processing in the alignment of large sequences, for which the execution of the exact algorithms takes a long time. The example code realization of the CAT Method, under the protection of the GNU General Public License v3.0, can be accessed on GitHub at: https://github.com/HristoS/CATSequenceAnalysis.

COVID-19 had a significant impact on construction projects due to labor shortages and COVID-19 restrictions, yet little is known about the impact it had on construction safety. To address this gap, an Australian construction project was selected to study the impact of COVID-19 on safety performance, safety climate and safety leadership. The study collected data from safety climate surveys, leading and lagging safety indicators and used linear regression to compare safety performance pre and post the onset of COVID-19. Our results showed after the onset of COVID-19 there was a significant reduction (Pr&gt;F at 0.05%) in incident rate, an improvement in supervisor safety leadership and safety climate, and satisfaction with organisational communication. The study identified the increase level of safety awareness due to COVID-19 did not result in an increase in the level of engagement in safety leadership. Interestingly, participation in the safety leadership activities did not improve until a change of Project Manager occurred. The study determined leaders who establish a positive safety climate within a project could negate the safety performance impact of COVID-19. The study confirms the importance of site safety leadership in maintaining engagement in risk management and the value of focused safety communication.

Manufacturing firms need to streamline their initiatives in line with 17 sustainable development goals (SDGs) 2030 as a means for improving performance. This research adapts SDG’s goals 8 decent job and economic growth’ as a measure of performance, in examine the effect of corporate sustainability strategies on performance of manufacturing firms. Census sampling technique was used in cross sectional survey of 900 multi-industry managers from one hundred and fifty (150) manufacturing firms in Kano, Nigeria. A five Likert scale, well-structured questionnaire was used in collecting data, analysed by Structural Equation Modelling SEM PLS Package. The study shows positive and significant effect of eco-efficiency, and positive and insignificant effect of both legitimation and risk mitigation strategies on performance respectively. The study concluded that the positive and significant effects of eco efficiency initiatives could be due to benefits derived from total quality management system, energy monitoring, and process safety management reflected in sustainability oriented visionary leadership of the managers. The positive and insignificant effects of legitimation initiatives could be as a result of huge spending on sustainability reporting, and corruption. The positive and insignificant effect of risk mitigation could be due to pro-activeness of the firms’ managers in tackling risk through sustainability oriented visionary leadership. The study recommended firms should adopt conservative eco-efficiency initiatives for improving performance and stop adopting extroverted legitimation and introverted risk mitigation strategies as both have no significant effect on performance. Future researchers should use longitudinal research design using financial metrics adopting the same independent variables in other economic sectors.

The nuclear reactor measurement system is a crucial component of the nuclear measurement system in a nuclear power plant. Its primary function is to measure the power distribution within the reactor core using detectors, calibrate, and provide data on core fuel consumption. Therefore, the study of the detectors' reliability is crucial for ensuring the safe operation of the nuclear power system. The article describes the operational mechanism of the gas ionization chamber detector utilized in the intermediate-range detector of the off-board nuclear measurement system. It also analyzes the movement of particles between the plates during the ionization process of the nuclear reaction taking place in the detector. The functional relationship between the current in the recombination region and the ionization region involved in the actual working condition, and the change with the increase of voltage between the plates, is deduced. A mathematical model is established for the number of pulses generated between the plates and the magnitude of the voltage between the plates. Subsequently, the change in the offset of the voltage corresponding to the inflection point of the ping curve and the change rule of the slope of the ping curve are investigated. Combined with the analysis of experimental data, the results show that the initial particle energy of Ar+, the primary sensitive particle on the detector surface, follows a normal distribution and is influenced by the energy loss associated with the initial velocity and the voltage between the plates. The trends of the inflection points and slopes of the ping curves can be utilized to evaluate the performance and operational status of the detector. Combined with the results of the experimental data analysis, the fit is good, and the inflection point currents in the normal state decrease by about 1.5% annually. The intelligent diagnostic system, based on the method studied in this paper, has been successfully implemented in the RPN digital retrofit and upgrade project at Qinshan No. 2 Plant.

The possibility of using Si-based anodes in lithium-ion batteries is actively investigated due to the increased lithium capacity of silicon. The paper reports the preparation of submicron silicon fibers on glassy carbon in the KI–KF–KCl–K2SiF6 melt at 720°C. For this purpose, the parameters of silicon electrodeposition in the form of fibers were determined by cyclic voltammetry, and ex-perimental samples of ordered silicon fibers with an average diameter from 0.1 to 0.3 μm were obtained under galvanostatic electrolysis conditions. Using the obtained silicon fibers, anode half-cells of lithium-ion battery was fabricated, and its electrochemical performance under mul-tiple lithiation and delithiation was studied. By means of voltametric studies, it is observed that charging and discharging of the anode based on the obtained silicon fibers occurs at potentials from 0.2 to 0.05 V and from 0.2 to 0.5 V, respectively. A change in discharge capacity from 520 to 200 mAh g-1 during the first 50 charge/discharge cycles at a charge current of 0.1C and a Coulomb ef-ficiency of 98-100% was shown. The possibility of charging silicon-based anode samples at charging currents up to 2C was also noted; the discharge capacity ranged from 25 to 250 mAh g-1.

Small hydro-power systems seem to be the best solution for energy generation through the use of pump as turbine (PAT) due to its low cost and lesser environmental hazards associated with it. Recently, PAT applications are gaining global attention in energy generation but its operation is not fully understood. The performance and flow behavior is affected by several operational conditions. This study seeks to investigate the effects of rotational speed on flow behavior and performance of a PAT. Rotational speed is an important physical parameter that affects the operation of a PAT. A selected centrifugal pump model of four blades and splitters was used for the study. Numerical simulations were carried out using k-ε turbulence model to solve the three-dimensional (3D) equations in both pump and PAT modes. The outcomes were then validated using experimental results in the pump mode to obtain overview flow physiognomies. The results predicted that the efficiency increases as the rotational speed increases in the pump mode whereas in turbine mode, higher rotational speed cannot convert hydraulic energy into mechanical energy. Thus, a rotational speed of 1500 rpm performed the highest efficiency of 69.8% at QBEP among the other rotational speeds selected. Moreover, the head performance in the turbine mode increases as the flow rate increases. This research provides useful information which will help improve PAT performance as well as selecting PAT for small hydro-power site.

The present study investigated the effect of different ambient temperature and relative humidity (RH) but equal temperature-humidity index (THI) on laying performance, egg quality, heterophil to lymphocyte ratio (H/L ratio), corticosterone (CORT) concentration in blood, yolk and albumen, and plasma biochemical parameters in laying hens. One hundred and twenty commercial hens (Hy-Line Brown) aged 60 weeks were allocated into 2 environmental chambers. Laying hens were subjected to either one of two thermal treatments, i.e., 26ºC and 70% RH (LH75) and 30ºC and 30% RH (HL75) for 28 days. Both thermal treatments had equal THI being 75. Neither LH75 nor HL75 affected (P > 0.05) laying performance including egg production, egg weight, egg mass, feed intake, and feed conversion ratio. Plasma biochemical parameters such as total cholesterol, high-density lipoprotein cholesterol, triglyceride, calcium, magnesium, and phosphorus was not altered (P > 0.05) by thermal treatments. As to the stress indicators, both environment regimes failed (P > 0.05) to affect blood H/L ratio and CORT levels in plasma, yolk and albumen although albumen CORT levels were elevated (P < 0.05) in LH75 vs. HL75 at days 3, 7, and 28. In conclusion, our study suggests that laying hens performed and responded equally when they were exposed to equal THI environment conditioned from either 26ºC and 70% RH or 30ºC and 30% RH. The results of this study will be served as a scientific basis for management decisions and handling under thermally challenging conditions.

This qualitative study explores the challenges and successes in supplier development from the perspectives of procurement managers across diverse industries. Through in-depth interviews, key themes emerged, highlighting the critical role of communication, trust, performance measurement, capacity building, risk management, innovation, regulatory compliance, and technology integration in supplier relationship management. Procurement managers emphasized the importance of clear, continuous communication and trust-building activities to align objectives and foster collaborative partnerships. Performance measurement was crucial for evaluating and improving supplier performance, supported by capacity-building initiatives to enhance supplier capabilities. Risk management strategies focused on identifying and mitigating risks, while compliance efforts aimed to ensure adherence to industry standards. Innovation and technological integration were pivotal for driving efficiency and competitiveness, enabling faster time-to-market and improved product quality. Cultural sensitivity and relationship strengthening emerged as essential for navigating diverse cultural contexts and enhancing partnership effectiveness. Overall, the findings underscored positive outcomes including enhanced quality, cost efficiencies, and increased resilience within supply chains. This research contributes valuable insights into effective supplier management practices, emphasizing the strategic importance of supplier development initiatives for sustainable growth and competitive advantage in today's dynamic business environment.

The proton exchange membrane fuel cell (PEMFC) is a critical and essential component of zero-emission electro-hydrogen generators. An accurate prediction of its performance is important for optimal operation management and preventive maintenance of these generators. However, the prediction is not simple because the PEMFCs have complex electrochemical reactions with multiple nonlinear relations between operating variables as inputs and voltage as output. In this paper, we propose an efficient prediction approach based on XGBRegressor and Tree-structured Parzen Estimator. In addition, to better select relevant features, Kernel Principal Component Analysis and Mutual Information are jointly used. The proposed approach allows consideration of the dynamic operating conditions of the PEMFC. To test and validate the robustness of the proposed approach, a real data-set of ten PEMFCs was considered. Furthermore, a comparison study with traditional machine learning models, such as artificial neural networks and support vector machine regression, was investigated. The obtained results confirm that our model outperforms the considered traditionel machine learning models.

In this paper we show how to efficiently implement parallel discrete simulations on Multi-Core and GPU architectures through a real example of application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with48cores and also an NVIDIA Tesla6V100 GPU, both running on Amazon Web Server (AWS) Cloud, and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results are compared and analysed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current Multi-Core CPUs with large core numbers can bring a performance very near to that of GPUs, even similar in some cases.

This article conceptualises the link between firms’ value chains and distribution networks and the requirements for double materiality assessments in contemporary reporting regulations worldwide. The new European Sustainability Reporting Standards (ESRS) and the standards for sustainability reporting issued by the International Sustainability Standards Board (ISSB), called IFRS S1 and IFRS S2, require companies to report their own direct (scope 1) and indirect (scope 2) greenhouse gas (GHG) emissions as well as GHG emissions in their value chains and distribution networks (both scope 3). However, GHG emissions comprise just one dimension of information that is relevant to understand when assessing, managing and reporting the footprints and impacts of a firm and are, therefore, only a fraction of the key performance indicators (KPIs) related to ESG that should be disclosed. Through a case study, this article demonstrates the connection between the due diligence analysis of firms’ value chains and distribution networks, the analysis of the competitive parameters of the business model, the identified impacts, risks and opportunities, and the double materiality perspective. The double materiality perspective prioritises actions based on probability and significance, creating a natural space to identify KPIs. The article concludes by applying the REGS model and illustrating how it can assist firms in identifying relevant KPIs based on double-materiality assessments.

In reservoir engineering, one of the main sources of information for the characterization of reservoir and well parameters is well testing. Among the unconventional well testing methodologies, Harmonic Well Testing (HPT) is appealing from an economic standpoint because it could provide well performance and reservoir behavior monitoring without having to interrupt field production. Recorded pressure analysis is performed in the frequency domain by adopting a derivative approach similar to conventional well testing. To this end, pressure and rate data must be decomposed into harmonic components. Test interpretability can be significantly improved if pressure data are detrended prior to interpretation, filtering out non periodic events such as discontinuous production from neighboring wells and flow regime variations which did not respect the designed test periodicity. Therefore, detrending offers the possibility of overcoming the limitation of HPT applicability due to the difficulty of imposing a regularly pulsing rate for the whole test duration (typically lasting several days). This makes HPT attractive for well performance monitoring, especially in gas storage fields. In this paper, the application of different detrending methodologies to synthetic HPT pressure data generated in different reservoir and operational scenarios is presented and discussed. Moreover, a real case application is also presented.

This study investigates the nonlinearities in three-phase inverters for SiC-based systems and compares their performance to IGBT-based systems. An analytical model of inverter voltage distortion is developed, which accounts not only for dead time (td), switching delay time, switching frequency (fs), and voltage drops of power devices, but also for output parasitic capacitance (Cout). Experimental tests validate the model, which provides a more accurate estimate of the inverter’s output phase voltage distortion. The power device characteristics are obtained from datasheets, while Cout is determined through experimentation. Three-phase inverters with varying switching frequencies, fundamental frequencies, and dead-time values are used in simulations and experiments to determine the influence of nonlinearity on phase voltage deviation and current distortion. The results show that, due to SiC devices’ faster switching time, the phase voltage deviation and phase current distortion are lower in SiC-based inverters than in IGBT-based ones for high-frequency applications, as the dead time can be reduced.

This paper introduces an advanced method that integrates contingent valuation and machine learning (CVML) to estimate residents’ demand for reducing or mitigating environmental pollutions and climate change. To be precise, CVML is an innovative hybrid machine-learning model, and it can leverage a limited amount of survey data for prediction and data enrichment purposes. The model comprises of two interconnected modules: Module I, an unsupervised learning algorithm, and Module II, a supervised learning algorithm. Module I is responsible for grouping the data into groups based on common characteristics, thereby grouping the corresponding dependent variable, whereas Module II is in charge of demonstrating the ability to predict and the capacity to appropriately assign new samples to their respective category based on input attributes. Take a survey on the topic of air pollution in Hanoi in 2019 as an example, we found that CVML can predict households’ willingness– to– pay for polluted air mitigation at a high degree of accuracy (i.e., 98%). We found that CVML can help users reduce costs or save resources because it makes use of secondary data that is available on many open data sources. These findings suggest that CVML is a sound and practical method that could be widely applied in a wide range of fields, particularly environmental economics and sustainability science. In practice, CVML could be used to support decision-makers in improving the financial resources to maintain and/or further support many environmental programs in years to come.

This study mainly experimentally investigates and explores the effects of local low-frequency vibrations on the starting-up and heat transfer characteristics of the pulsating heat pipe. A micro motors with the vibration frequency of 200 Hz were imposed on the external surface of evaporation, condensation and adiabatic section of the pulsating heat pipe, respectively, and the starting-up temperature and the average temperatures along the evaporation section as well as the thermal performances of the vibrating heat pipe were experimentally scrutinized under the local vibrations of different positions. The following important conclusions can be achieved by the experimental study: 1) The effect of vibrations at the evaporation section and at the adiabatic section on the starting-up time of pulsating heat pipe is more significant than that at the condensation section. 2) The vibrations at different positions can reduce the starting-up temperature of the pulsating heat pipe. The effect of the vibrations at the evaporation section is the best as the heating power is lower, and the effect of the vibration at the adiabatic section is the best as the heating power is higher. 3) The vibrations at the evaporation section and at the adiabatic section can reduce the thermal resistance of the pulsating heat pipe. However, the vibrations at the condensation section have little effect on the thermal resistance of the pulsating heat pipe. 4) The vibrations at the evaporation section and at the adiabatic section can effectively reduce the temperature of evaporation section of the pulsating heat pipe, but the vibrations at the condensation section have no effect on the temperature of evaporation section of the pulsating heat pipe.

The purpose of this study is to explore the effects of dual-task training, including cognitive tasks, on cognitive and bodily functioning and β-amyloid levels in Alzheimer's dementia patients. The subjects were 34 inpatients diagnosed with Alzheimer's dementia at a nursing hospital located in Gyeongsansi, South Korea. The patients were randomly divided into a dual-task group (n = 16) and a single-task group (n = 18). The dual-task group performed cognitive tasks at the same time as exercising tasks, while the single-task group performed only exercise tasks. Each group was trained for 30 minutes three times a week for eight weeks. The Mini-Mental State Examination was used to measure the patients’ cognitive function. Static and dynamic balance were measured to evaluate bodily functioning. Static balance was measured using Biorescue, while dynamic balance was measured using the Berg Balance Scale. Blood analysis was performed to measure levels of β-amyloid, which is known to cause Alzheimer's dementia. Both groups exhibited statistically significant improvements in gait function after the training (p < .05). The dual-task group exhibited statistically significant differences in cognitive function, static and dynamic balance function, and β-amyloid levels after training (p < .05). A significant difference was observed between the two groups (p < .05). Dual-task activities were found to be effective in improving cognitive and bodily functioning and reducing β-amyloid levels in Alzheimer's dementia patients. Therefore, dual-task training is thought to be an effective method of treating and preventing Alzheimer's dementia.

Recently, environmental degradation has become an international issue due to the extensive economic activities around the globe. This aspect demands the policymakers' and new researchers’ emphasis. Hence, the present article examines the impact of corporate social responsibilities (CSR) to community and environment on the environmental performance (ENP) of the manufacturing industry in China. The article also investigates the mediating role of green innovation and environmental strategy among CSR to community, CSR to environment and ENP of manufacturing industry in China. The article gets the primary data from the selected employees of the manufacturing industry using questionnaires. The article also tests the data's validity and reliability, and association among variables using smart-PLS. The outcomes indicated that CSR to environment has a positive association with ENP. The outcomes also revealed that green innovation and environmental strategy significantly mediate among CSR to community, CSR to environment and ENP. The article guides the policymakers in making policies related to improve ENP using CSR to environment and green innovation.

The effect of defatted Hermetia illucens meal (HIM) dietary inclusion on growth performance, stress indicators and gut histological traits of Sparus aurata was studied. For 131 days, 312 fish were fed with one basal diet, containing fish meal as animal protein source, and three diets containing 25%, 35% and 50% HIM as a partial replacement for fishmeal. On all fish (26 fish per tank, 3 replicate tanks per diet, 78 fish per diet) the growth performance were calculated. At the end of the trial, on a subsample of 72 specimens (6 fish per tank, 3 replicate tanks per diet, 18 fish per diet), stress parameters were determined on blood samples and gut histological tract investigated. Insect meal inclusion did not affect (p > 0.05) growth performance, blood parameters, length and width of villi and goblet cell count of the posterior gut tract while, those of the anterior gut tract while increased (p < 0.05). The histological examination of the intestinal sections showed in fish fed the HIM25 and HIM50 diets, more frequent and evident morphological changes; instead, there were no substantial differences between HIM0 and HIM35 groups. In conclusion, the HIM35 was the most tolerated formulation by fish.

2S-hesperidin is a flavanone (flavonoid) found in high concentrations in citrus fruits. It has an antioxidant and anti-inflammatory effect, improving performance in animals. This study investigated the effects of chronic intake of an orange extract (2S-hesperidin) or placebo on aerobic-anaerobic and metabolic performance markers in amateur cyclists. A double-blind, randomized, placebo-controlled trial was carried out between late September and December 2018. Forty amateur cyclists were randomized into two groups: one taking 500mg/day 2S-hesperidin and other taking 500 mg/day placebo (microcellulose) for 8 weeks. All participants completed the study. Performance and metabolic aerobic-anaerobic markers were measured using incremental and rectangular tests by indirect calorimetry. The anaerobic power was determined using Wingate tests. After 8 weeks supplementation, there was a significant increase in the incremental test in estimated functional threshold power (FTP) (3.23%; p≤0.05) and maximum power (2.68%; p≤0.05) with 2S-Hesperdin compared to placebo. In the rectangular test, there was a significant decrease in VO₂ (-8.26%; p≤0.01) and VO₂R (-8.88%; p≤0.01) at VT2 in placebo; however, there were no significant differences between groups. In the Wingate test, there was a significant increase (p≤0.05) in peak and relative power in both groups, but without significant differences between groups. Supplementation with an orange extract (2S-hesperdin) 500mg/day improves estimated FTP and maximum power performance in amateur cyclists.

This paper seeks to optimize the mechanical and durability properties of ultra-high performance concrete (UHPC). To meet this objective, concrete specimens were manufactured by using 1,100 kg/m3 of binder, water/binder ratio 0.20, silica sand and last generation of superplasticizer. Silica fume, metakaolin and two types of nano silica were used for improving the performances of the concrete. Additional mixtures included 13mm long OL steel fibers. Compressive strength, electrical resistivity, mercury intrusion porosimetry tests and differential and thermogravimetric thermal analysis were carried out. The binary combination of nano silica and metakaolin, and the ternary combination of nano silica with metakaolin and silica fume, led to the best performances of the UHPC, both mechanical and durable performances.

This study aims to determine the optimal configuration (position and operation duration) for wall mounted mechanical mixers based on the comparison of three-dimensional computational fluid dynamics (CFD) modelling results and physical data collected from the treatment plant. A three-dimensional model of anoxic zone 1, 2 and 3 of Northern Wastewater Treatment Plant (WWTP) located at Cairns Regional Council, Cairns, Queensland, Australia was developed and validated. The model was used to simulate the flow pattern of the WWTP and the simulation results are in good agreement with the physical data varying between 0% to 15% in key locations. The anoxic zones were subject to velocities less than the desired 0.3 metres per second however results for suspended solids concentration indicate that good mixing is being achieved. Results for suspended solids concentrations suggest that the anoxic zones are towards the upper limits recommended by literature for specific power dissipation. The duration for operation of mechanical mixers was investigated and identified that the duration could be reduced from 900 seconds down to 150 seconds. Alternative mixer positioning was also investigated and identified positioning which would increase the average flow velocity with decreased duration (150 seconds). The study identified that Council may achieve savings of $24,000 per year through optimisation of the mechanical mixers.

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

A car-roof photovoltaic has an enormous potential to change our society. With this technology, 70% of the personal car can run by the solar energy collected by the solar panel on its car-roof. Unfortunately, it is not a simple extension of the conventional photovoltaic technology. This paper list what we need to do for realizing the future that majority of the personal cars run by renewable solar energy, after clarification of the difference from the conventional photovoltaic technology. In addition to the technological development, the standardization of this innovative technology will be important, and the list was made highlighting the standardization.

As a new kind of highly compact and efficient micro-channel heat exchanger, printed circuit heat exchanger (PCHE) is a promising candidate satisfying the heat exchange requirements of liquefied natural gas (LNG) vaporization at low and high pressure. The effects of airfoil fin arrangement on heat transfer an flow resistance were numerically investigated using supercritical liquefied natural gas (LNG) as a working fluid. The thermal properties of supercritical LNG were tested by utilizing a REFPROF software database. Numerical simulation was performed using FLUENT. The inlet temperature of supercritical LNG was 121 K,and its pressure was 10.5MPa. The reference mass flow rate of LNG was set 1.22 g/s for the vertical pitch L_v = 1.67 mm and the staggered pitch L_s = 0 mm, with the Reynolds number of about 3750. The SST k-ω model with enhanced wall treatment was selected by comparing with the experimental data. The airfoil fin PCHE had better thermal-hydraulic performance than that of the straight channel PCHE. Moreover, the airfoil fins with staggered arrangement displayed better thermal performance than that of the fins with parallel arrangement. The thermal-hydraulic performance of airfoil fin PCHE was improved with increasing L_s and L_v. Moreover, L_v affected on the Nusselt number and pressure drop of airfoil fin PCHE more obviously. In conclusion, a sparser staggered arrangement of fins showed a better thermal-hydraulic performance in airfoil fin PCHE.

To enhance the uplift capacity and facilitate the installation of multi-row perfobond connectors at shallow burial depths, this study puts forward a novel notched T-perfobond connector. The design incorporates an integrated flange at the bottom of the connector and a notch at the edge of the hole. Through pull-out model tests on four notched T-perfobond connectors, this research investigates their failure mechanisms and pull-out capacities. Utilizing the explicit dynamics method in Abaqus, a finite element model of the pull-out resistance test for the notched T-perfobond connector is established and verified against experimental data. Furthermore, a detailed parametric analysis involving 54 models is conducted, examining crucial parameters such as rib dimensions, hole geometry, flange size, notch width, bar diameter, and material properties. Based on the combined experimental and numerical results, the paper assesses the suitability of current formulas for calculating the pull-out capacity of perfobond connectors and proposes a refined calculation method specifically for notched T-perfobond connectors. All the findings in this paper can serve as a reference in the design and construction of composite structures.

Yellow nanorod Mg-MOF-74 was obtained by solvothermal synthesis method. XRD、N2 adsorption-desorption isotherms、SEM and TGA results suggest that the particle size of Mg-MOF-74 reaches 400 nm after the introduction of sodium acetate in the precursor of Mg-MOF-74. Besides, the morphology of Mg-MOF-74 was changed from cauliflower to rod particles. At the same time, the BET specific surface area and pore volume of Mg-MOF-74 were also increased a lot. Then the CO2 dynamic adsorption capacity of Mg-MOF-74 was measured by self-made fix bed under 30 ℃、0.1 bar CO2 partial pressure. The results show that the CO2 adsorption capacity of Mg-MOF-74-N2 reaches 3.67 mmol/g and its CO2 adsorption capacity remains unchanged after 10 times CO2 adsorption-desorption cycles.

Previous research has either neglected to consider misbehaviour or misconduct in the virtual workplace during the current COVID-19 pandemic or highlighted some challenges encountered with remote working or work from home but in isolation, e.g., misbehaviours or ethical concerns associated with improper use of technology when accessing clients’ confidential information, without understanding their aetiology and context in a holistic manner. This has impacted the ability of existing research in providing recommendations organisations can practically implement to improve the sustainability and productivity of the virtual workplace, especially as they seek to navigate the current pandemic and prepare for the global business environment in the next decade. Instead, this study, for the first time, proposes a novel holistic methodology to identify the aetiologies of ethical and performance challenges with focus to the Information Technology consulting sector, as well as developing a set of recommendations companies can adopt to manage such behavioural and productivity challenges. Thus, this study illustrates the key issues associated with remote working implemented to respond to the current COVID-19 pandemic, which mine not only the individual performance in an organisation but also its overall productivity, as well as suggests the main performance and reward management strategies that can be leveraged to mitigate them. Tailored strategies are described and discussed as referred to this industry to help in navigating a more unstable yet competitive market to manage the virtual employees’ misbehaviours in the workplace and drive growth for individuals and organisations alike.

The study evaluated the impact of supplementing ZH in combination with D3 on growth performance, energy efficiency, carcass traits, and meat quality of feedlot lambs. Thirty-two Dorper x Katahdin cross lambs (37.3±5.72 kg) were utilized in a 29 d experiment in a complete randomized block design with a 2x2 factorial structure consisting of two levels of ZH for 26 d (0 and 0.20 mg /kg PV-1) and two levels of D3 for 7 d (0 and 1.5x106 IU/d-1). ZH improved (P≤0.05) average daily gain (ADG) and feed efficiency by 9.9% and 17.8%, respectively, as well as hot carcass weight (HCW) and dressing carcass by 4.3% and 2.6%, respectively. (p≤0.03). However, ZH increased (p<0.01) muscle pH and Warner-Bratzler shear force (WBSF) (2.5 and 23.0%, respectively). D3 supplementation negatively affected (P≤0.02) dry matter intake (DMI) (last 7 d) and ADG by 15.7% and 18.1%. On the other hand, D3 improved the pH of the longissimus muscle (LM) by 1.7% (p=0.03) without affecting WBSF. When D3 was supplemented in combination with ZH, it was observed that meat quality was improved by reducing muscle pH compared to lambs treated only with ZH. However, D3 did not improve meat tenderness produced by ZH supplementation.

From the various perspectives of Machine Learning (ML) and the multiple models used in this discipline, there is an approach aimed at training models for the Early Detection (ED) of anoma-lies. The early detection of anomalies is crucial in multiple areas of knowledge since identifying and classifying them allows for early decision-making and provides a better response to mitigate the negative effects caused by late detection in any system. This article presents a literature review to examine which machine learning models (MLM) operate with a focus on ED in a multidisci-plinary manner and specifically how these models work in the field of fraud detection. A variety of models were found, including Logistic Regression (LR), Support Vector Machines (SVM), De-cision Trees (DT), Random Forests (RF), Naive Bayesian Classifier (NB), K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Extreme Gradient Boosting (XGB), among others. It was identified that MLMs operate as isolated models, categorized in this article as Single Base Models (SBM) and Stacking Ensemble Models (SEM). It was identified that MLMs for ED in multiple areas under SBM and SEM implementation achieved accuracies greater than 80% and 90%, respectively. n fraud detection, accuracies greater than 90% were reported by the authors. The article concludes that MLMs for ED in multiple applications, including fraud, offer a viable way to identify and classify anomalies robustly, with a high degree of accuracy and precision. MLMs for ED in fraud are useful as they can quickly process large amounts of data to detect and classify suspicious transactions or activities, helping to prevent financial losses.

The study addresses improving disaster management performance using artificial intelligence to achieve sustainable development and support the global economy and proposes implementable strategies to achieve resilience and growth. Through a literature review, it examines the impact of natural disasters on international trade and focuses on the challenges faced by developing economies in developing countries. The study emphasizes the interconnectedness of global trade networks and the need for proactive risk management. Existing qualitative literature from previous studies was compiled and analyzed for the study. The results indicate potential disruptions in commercial activities and economic growth in Middle Eastern countries due to natural or human-caused disasters such as wars and terrorism. Here we find the importance of measures to build resilience and diversify trading partners and markets. Recommendations include investing in resilient infrastructure, promoting digital trade, strengthening institutional capacities, and enhancing regional and international cooperation. By providing insights to policy makers, businesses and stakeholders, this study contributes to understanding the resilience of developing economies to natural disasters and provides practical guidance for them to overcome the challenges posed by such disasters and achieve sustainable growth.

Background. The measurement of physical performance constitutes an indicator of physical functional capacity and allows the design of physical exercise programs adapted to the individual abilities and needs of older adults with and without frailty. Aim. To present a synthesis of knowledge on the effect of exercise programs on physical performance in older adults with and without frailty in the community. Method. A systematic review was carried out in accordance with the PRISMA-2020 criteria. The search for articles was made until May 4, 2023 in PubMed, Scopus, Web of Science, Cochrane Library, SciELO and LILACS. The outcome variable was physical performance, measured through the SPPB (Short Physical Performance Battery). The mean difference (MD) was estimated to evaluate the effect. Results. We found 2,483 studies, of which 12 met the eligibility criteria for the systematic review and 9 for the meta-analysis. The effect of exercise on SPPB score was significantly higher in the exercise group compared to control in non-frail older adults with MD=0.51 [95% CI, 0.05 to 0.96, p&lt;0.05]. Likewise, in older adults with frailty, the effect of exercise on the global SPPB score was significantly higher in the exercise group compared to the control with an MD=0.66 [95% CI, 0.09 to 1.24, p&lt;0.05 ]. Conclusion. Our findings suggest that exercise programs are effective in increasing and/or maintaining physical performance in older adults with and without frailty, whose effect is more evident in older adults with frailty, probably due to the greater margin of recovery of intrinsic capacity.

Background: There has been a lack of tools to identify listening difficulties in school settings for both hearing and hearing-impaired Italian students. Thus, the present study aimed to realize cross-cultural adaptation and validation of the Listening Inventory for Education-Revised for Italian students (LIFE-R-ITA). Methods: Following the validation of two forward-backward translations by a multidisciplinary committee, the content validation for the LIFE-R-ITA was performed by pre-testing six implanted children (8-18 years old). After minor cross-cultural adaptations, normative data were collected from a sample of 223 hearing students enrolled in different school settings and educational degrees. Results: For the LIFE-R-ITA, hearing students showed an average score of 72.26% (SD=11.93), reflecting some listening difficulties. The subscales (LIFE total, LIFE class, and LIFE social) indicated good internal consistency. All items were shown to be relevant. Most challenging situations happened when listening in large rooms, especially when other students made noise. LIFE social scores were significantly worse than those of LIFE class (p &lt; 0.001). Conclusions: The LIFE-R-ITA may support teachers and clinicians in assessing students’ self-perception of listening at school. Such understanding may help students overcome their listening difficulties, by planning and selecting the most effective strategies among classroom interventions.

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

As a potential motivation, psychological empowerment stimulates employees' work behaviors, and it determines the degree of effort and duration of employees' work. Only when employees are psychologically empowered, will they have an impact on their behavior when they believe that they are trusted. This paper chose to set the independent variable as the employee's perceived trust and the dependent variable as the company's work performance, and explored the mediating role of psychological empowerment in the two. The psychological empowerment of employees had a positive impact on work performance. Employees with high psychological empowerment tended to be proactive in their work, and had more input in the work, which in turn encouraged employees to have higher work performance. The four dimensions of psychological empowerment can positively affect employee task performance, and the ability and influence of psychological empowerment had a positive impact on relationship performance. Psychological empowerment as a whole perception played a part of the mediating role between the perception of superior dependency and task performance, and it played a part of the mediating role between perception of superior dependency and relationship performance. As a whole perception, psychological empowerment played a part of mediating role between perceived information disclosure and task performance, and part of mediating role between perceived information disclosure and relationship performance. In the study of perceived trust and work performance, this article focused on the mediating role of psychological empowerment, and further understood the internal mechanism of perceived trust.

(1) Background: The diphtheria toxoid antigen is a major component in pediatric and booster combination vaccines and is known to raise a protective humoral immune response upon vaccination. Although antibodies are considered critical for diphtheria protection, little is known about the antigenic determinants that maintain humoral immunity. (2) Methods: One hundred twelve 15-mer peptides covering the entire sequence of DTx protein were prepared by Spot-synthesis. Membrane-bound peptides immunoreactivity with sera from mice immunized with triple DTP vaccine allowed mapping of continuous B-cell epitopes, topological studies, MAPs synthesis, and ELISA development. (3) Results: Twenty epitopes were identified, being 2 in the signal peptide, 5 in the CD, 7 in the HBFT domain, and 5 in the RBD. Two 17-mer (CB/Tx-2/12 and CB/DTx-4-13) derived bi-epitope peptides linked by a Gly-Gly spacer were chemically synthesized. The peptides were used as antigens to coat ELISA plates and assayed with human (huVS) and mice vaccined sera (miVS) for in vitro diagnosis of diphtheria. The assay proved to be highly sensitive (99.96%) and specific (100%) either for huVS and miVS and when compared with a commercial ELISA test, demonstrate high performance. (4) Conclusions: Our work displayed the complete picture of the linear B cell IgG response epitope of the DTx responsible for the protective effect and demonstrated the specificity and eligibility to enter phase IIB studies of some epitopes to develop new and fast diagnostic assays.

Opportunistic routing is the latest technique that uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of routing protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. These applications provide dynamic communication in disaster recovery environments. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward

For the task planning problem of the command and control architecture, the existing algorithms have problems such as low efficiency and poor re-planning quality under abnormal conditions. Based on the requirements of the current accusation architecture, this paper constructs a distributed command and control architecture model based on multi-agents, which makes use of the superiority of multi-agents in dealing with complex tasks. The concept of MultiAgents-HTN is proposed under the framework. The original hierarchical task network planning algorithm is optimized, the multi-agent collaboration framework is redefined, and the coordination mechanism of local conflict is designed. Taking the classical resource scheduling problem as the experimental background, the comparison between the proposed algorithm and the classical HTN algorithm is carried out. The experimental results show that the proposed algorithm has higher quality and higher efficiency than the existing algorithm, and the space anomaly is heavy during processing. The planning is more efficient, and the time is more complicated and superior in dealing with the same problem, with good convergence and adaptability. The conclusion proves that the distributed command and control architecture proposed in this paper has high practicability in related fields and can solve the problem of distributed command and control architecture in multi-agent environment.

Throughout this paper the impact of anxiety on adolescent athlete’s is highlighted through analyzing neurological and psychological aspects involved in sports performance. The neuroanatomy and neuropsychology of the human brain plays a major role in developing athlete’s that has only begun to be analyzed within recent years. Especially in young athletes, there are numerous factors that affect performance on the field that originate from the environment and training the adolescent athlete is involved in. Sports performance is viewed as a major physical factor such as training and lifting weights, however the psychological aspect of sports performance often goes unnoticed. Athletes can begin to develop mental fatigue and anxiety which inevitably can decrease their ability to perform. The athlete’s internal suffering begins to go unnoticed, as the only tangible factor is watching their performance decrease. This causes the athlete to push themselves further in training resulting in greater mental fatigue. This paper emphasizes the numerous factors neurologically that play a role in athletic performance which should be focused on in adolescent athletes as they navigate the challenges and competition that are apparent within athletics. It is critical to understand the processes and hormonal changes the body undergoes with training and playing a sport, this information can change the way adolescent sports are approached and advanced.

The Industrial Internet of things (IIoT) enabled smart system has entered into a golden era of rapid technology growth. IIoT is a concept to make every system interrelated such that they are able to collect and transfer data over a wireless network without human intervention. In this paper, we discuss the development of an IoT enabled system to monitor the vibration signature of equipment as part of prognosis and availability management system (P&AM) that serves to prevent unplanned operation downtime and catastrophic failure of a whole system. In order to simply the complexity of processing video content and performing inference, the Intel OpenVINO platform was selected because of it’s simplicity, portability across Intel AI processors, performance and comprehensiveness of it’s analytical and diagnostics capabilities that can be tested in Intel’s DevCloud. The IIoT system consists of a High Performance Computing (HPC) platform based on Intel’s Xeon processors and Movidius AI accelerator, Intel’s OpenVINO toolkit for AI, a Regul high performance programmable controller capturing vibration data through sensors and a low-latency network connection. Notifications of anomalies are sent to a smartphone. This paper reveals an approach for the features extraction and selection, known as feature engineering, of the equipment component we want to protect. Feature engineering is the first step for the P&AM of these components and extends to the whole system. The broader aim of this paper is to help technical leaders at the exploring or experimenting stages of their AI framework to learn the concepts of implementing algorithms using datasets that have real value to their companies. Datasets generated and referred to in this paper were generated by simulation under various material failure scenarios.

This study aims to test empirical research on the effect of financial resource ability, research and development (R &amp; D) on innovation orientation and competitive position. This study also examines the critical mediating role of innovation orientation and competitive position to achieving new products performance (NPP). This study used a quantitative research approach by comparing data from service industry and manufacture industry in Indonesia included in Indonesian-State-Ownership companies. The analysis unit in this study used middle managers and top managers who responsible for managing divisions within the Indonesian-State-Ownership companies. The number of respondents studied in this study was 287 sample. The purposive sampling technique was used in taking the research sample. This study indicated that financial resources abilities, research and development (R &amp; D) abilities positive effect on innovation orientation and competitive position. This study also testing the importance role of innovation orientation and a competitive position to enhancing new products performance (NPP).

This research investigates the microstructure and mechanical behaviour of a polylactic acid (PLA)-iron (PLI) composite designed to enable magnetic actuation. Tensile specimens of PLI are produced through Fused Filament Fabrication, incorporating diverse printing angles ranging from 0° to 90°, thereby facilitating the creation of a variety of layups. The microstructure of these 3D-printed composites is analysed using X-ray micro-tomography. Furthermore, the tensile mechanical properties of all composites are evaluated, and the findings are deliberated in relation to the conditions of the printing angle. Additionally, the fractography of broken specimens is examined using Scanning Electron Microscopy. The findings indicate that the printing angle plays a significant role in influencing the tensile properties of the 3D-printed PLI composites, particularly in adjusting mechanical anisotropy. Moreover, an optimal layup of 45°/45° is attained, resulting in an enhanced ranking of the tensile performance. These findings related to 3D-printed PLI composites present a cost-efficient option for manufacturing bio-sourced light-adaptive composites through 3D printing, enabling the generation of intricate magnetic actuation performance.

The purpose of the article is to measure, using the VAIC and MVAIC models, the impact of intellectual capital and its elements on the financial performance of Omani industrial companies listed on the Muscat Stock Exchange (MSE) from 2017 to 2021. Regression analysis using the Gretl software was applied to the study of panel data on the activities of 34 industrial companies in Oman, obtained from the official MSE website and from published financial statements. The analysis of literature sources was carried out using bibliometric analysis, the results of which were visualized using the VOSviewer software. To analyze the relationships between financial performance and its determinants (intellectual capital variables and control variables), four types of PERF models were developed, based on which sixteen models were directly examined. Four dependent variables (Earnings before interest, Taxes, Depreciation and Amortization, Return on Assets, Return on Equity, Assets Turnover Ratio) and eight independent variables (Value Added Intellectual Coefficient, Modified Value Added Intellectual Coefficient, Capital Employed Efficiency, Human Capital Efficiency, Structural Capital Efficiency, Relational Capital Efficiency, Size, and Leverage) were used to form these models. The Empirical Results section has discussed descriptive statistics and correlations, selection of estimate panel data parameter based on the F-statistics, Breusch-Pagan test, and Hausman test, assumption test results (Normality, Autocorrelation, Heteroscedasticity), and panel regression models. Analysis of the impact of VAIC, MVAIC and its elements on the financial performance of Omani industrial companies has yielded mixed results. VAIC and MVAIC in general have a significant positive effect only on ATO. For individual elements of VAIC and MVAIC, the following most significant associations with financial performance measures were found: CEE negatively affects ROE; SCE has a positive effect on l_EBITDA and ATO; RCE negatively affects ATO; l_SIZE has a positive effect on l_EBITDA and ROA; and LEV has a positive effect on ROA.

In this study, three new demountable joints consisting of reinforced concrete columns and steel beams were proposed and their seismic performance was investigated using cyclic loading tests. The test results demonstrated that the three demountable RCS joints had good seismic performance. Using the finite element software ABAQUS, the influence of parameters such as beam flange thickness, bolt strength, and connector steel strength on the seismic performance of each joint was analyzed, and the influence of different parameters on the seismic behavior of the joint was determined. The results also showed that the three demountable RCS joints were sensitive to changes in the thickness of the steel beam flange, while the connector steel strength and bolt type had little impact on the joint's capacity. Additionally, shear capacity calculation formulas for the joint core area provided by different codes and researchers were compared with test and finite element results. The results showed that the calculation results of the ASCE guidance method, the Nishiyama method, and the CECS 347-2013 method were higher than the test values, while the calculation results of the Para method were lower because it did not consider the contribution of the cylindrical steel plate to the shear capacity of the joint core area.

In this study, the focus is on the drop test simulation of an MR (Magnetorheological) damper-based main landing gear (MRMLG), aiming to explore multi-degree-of-freedom (DOF) dynamic models during aircraft landing. Three different 6-DOF dynamic models are proposed in this work and their drop performances are compared with results achieved one of commercial softwares. The proposed models include a nonlinear aircraft model (NLAM), a linearized approximated aircraft model (LAAM) linearizing from the nonlinear equations of motion in NLAM, and a fully approximated aircraft model (FAAM) which linearizes the MRMLG's strut force model. In order to evaluate drop performance of the aircraft landing gear system with MR dampers, a 7-DOF aircraft model incorporating the nonlinear MRMLG is formulated using RecurDyn. The principal comparative param-eters are the coefficient of determination (R2) for system response of each model with Re-curDyn model and root mean square error (RMSE) which is the ensembles of CG dis-placement data for each model. In addition, the ensemble of time series data is created for diverse drop scenarios, providing valuable insights into the performance of the proposed drop test models of the aircraft landing gear system featuring MR dampers.

Background: Chronic exposure to severe hypoxia causes an increase in hematocrit (Hct) and hemoglobin concentration ([Hb]), which can lead to Excessive Erythrocytosis (EE), which could impact physical performance. This work aims to determine the differences in the six-minute walking test (6MWT) outputs between EE and healthy subjects residing at more than 5000 meters. Methods: A prospective, cross-sectional study was performed on 71 men (36 healthy and 25 suffering EE) living in La Rinconada, Peru (5100 m). Basal levels of [Hb] and Hct were obtained. All the subjects per-formed the 6MWT, and distance reached, vital signs, dyspnea, and fatigue (Borg scale) at the end of the test were recorded. Results: The average [Hb] and Hct levels in the control group were 18.7 ± 1.2 g/dL and 60.4 ± 7.1%, respectively, contrasting with EE subjects who showed 23.4 ± 1.6 g/dL and 73.6 ± 5.9% (p < 0.001). However, no statistically significant differences were observed in BMI or other anthropometric parameters. At the end of the 6MWT, the distance traveled, and vital constants were similar between both groups, except for arterial oxygen saturation which was consistently lower in subjects with EE along the test. Conclusion: EE does not significantly affect 6MWT performance at high altitudes nor the hemodynamic control during moderate aerobic exercise of subjects who live permanently in a severe hypoxic environment.

The insufficient of fish meal has been become a prominent problem with the development of the aquaculture industry. Therefore, it is great significance that replacement fish meal using other protein sources for the sustainable development of aquaculture industry. In this study, fermented cottonseed meal (FCM) and fermented rapeseed meal (FRM) were used to replace fish meal in Chinese mitten crab. The ratio of FCM and FRM were set according to 1:2, 1:1, and 2:1, and were supplemented into 25% fish meal (FM-25) and 15% fish meal (FM-15) diets, respectively, to formulated 6 kinds of experimental diets. The feeding duration was 8 weeks. The results showed that the weight gain (WG) and specific growth rate (SGR) of crabs fed the diets containing 25% fish meal were significantly higher than crabs fed 15% fish meal diets. At 25% fish meal level, the WG and SGR of crabs fed the diet with 1FCM:1FRM were significantly higher than those fed the 1FCM:2FRM and 2FCM:1FRM diets. At 25% fish meal level, the crude lipid (CL) content of crabs fed the diet with 1FCM:2FRM were significantly higher than those fed the 2FCM:1FRM and 1FCM:1FRM. At 25% fish meal level, the activities of glutathione peroxidase (GPX) and peroxidase (POD) of crabs fed the diet with 1FCM:2FRM were significantly higher than those fed the 2FCM:1FRM and 1FCM:1FRM. At 25% fish meal level, the relative expression of peroxiredoxin (PRX) of crabs fed the diet with 1FCM:1FRM were significantly higher than those fed the 2FCM:1FRM and 1FCM:2FRM. In summary, diets supplemented with a mixture of fermented cotton meal and fermented rapeseed meal (1:1) can significantly improve the growth and antioxidant capacity of Chinese mitten crab.

Autonomous systems and intelligent machines are involved in almost all areas of human activity and they are now more and more present in our everyday life. The reason for this extensive use certainly resides in all the benefits these machines offer to the users. In experimental settings, numerous studies have demonstrated the positive effects that the introduction of autonomous systems have on human decision-making and performance. However, studies have shown in addition that the introduction of these systems can have important negative effects as well. Considering that autonomous systems are now introduced in sensitive domains like the military or medicine, we need more than ever a comprehensive understanding of the effects they cause on human performance and decision-making, and particularly in tasks and contexts with a social or moral dimension. The aim of this narrative review is threefold. First, we will provide an overview of the main effects on a human agent’s decision-making and performance produced by the introduction of autonomous systems. Second, we will review the conditions identified as underlying factors of these effects, and see how current models of human – autonomous systems interaction integrate those conditions. Third, we will conclude this review by highlighting new directions for future investigations.

The UHPC grouted bellow is an innovative technology for connecting assembled buildings, where the anchorage performance of the rebar and UHPC filled in bellows plays a critical role in determining the overall connection effectiveness. To ascertain a dependable anchorage length and establish a bond-slip relationship between the rebar and UHPC within the bellow, we conducted tests on 8 groups of 16 specimens of metal corrugated pipes filled with UHPC and rebar under tension. The tests considered varying parameters such as the aperture ratio D/d and anchorage length L. By analyzing the failure modes, load versus deflection curves, and steel strain data, we gained valuable insights into the influence of the aperture ratio and anchorage length on the anchorage performance. Furthermore, we calculated the experimental curve of the bond-slip relationship between the rebar and the UHPC interface grouted in the bellows and derived a bond-slip model through fitting. These findings serve as a crucial foundation for the force analysis of assembled structures connected using UHPC grouted bellows.

This overview study set out to compare and synthesise the findings of review studies conducted on predicting student academic performance (SAP) in higher education using educational data mining (EDM) methods, EDM algorithms and EDM tools from 2013 to June 2020. It conducted multiple searches for suitable and relevant peer-reviewed articles on two online search engines, on nine online databases, and on two online academic social networks. It, then, selected 26 eligible articles from 2,050 articles. Some of the findings of this overview study are worth mentioning. First, only 2 studies explicitly stated their precise sample sizes with maths and science as the two most mentioned subject areas. Second, 16 review studies had purposes related to either EDM techniques, EDM methods, EDM models, or EDM algorithms employed to predict SAP and student success in the higher education sector. Third, there are six commonly used typologies of input variables reported by 26 review studies, of which student demographics was the most commonly utilised variable for predicting SAP. Fourth and last, seven common EDM algorithms employed for predicting SAP were identified, of which Decision Tree emerged both as the most used algorithm and as the algorithm with the highest prediction accuracy rate for predicting SAP.

Opportunistic routing uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward.

CAD-CAE software companies have introduced numerous tools aimed at facilitating topology optimization through Finite Element Simulation, thereby enhancing accessibility for designers via user-friendly interfaces. However, the imposition of intricate constraint conditions or additional restrictions during calculations may introduce instability into the resultant outcomes. In this paper, an algorithm for updating the design variables called Adaptive Variable Design is proposed to keep the final design space volume of the optimized part always under the target value while giving the main algorithm multiple chances to update the optimization parameters and search for a valid design. This algorithm aims to producing results that are more conducive to manufacturability and potentially more straightforward in interpretation. A comparison between several commercial software and the proposed algorithm, implemented in MATLAB, is carried out to prove the robustness of the latter. By simulating identical parts under similar conditions, we seek to generate comparable results and underscore the advantages stemming from the adoption and comprehension of the proposed topology optimization methodology. Our findings reveal that the integrated enhancements within MATLAB pertaining to the topology optimization process yield favourable outcomes with respect to discretization, and the manufacturability of resultant geometries. Furthermore, we assert that the methodology evaluated within MATLAB holds promise for potential integration into commercial packages, thereby enhancing the efficiency of topology optimization processes.

Organisational performance is a major concern for any company wishing to remain competitive in today's market. This is why many companies have begun to integrate digital technologies into their management systems. The aim of this article is to determine the contribution of digitisation to organisational performance management, through observations and analysis of a single case study of a company that has adopted a digital transformation project. It emerged that digital transformation makes a significant contribution to organisational performance management. However, this transformation requires significant support and adaptation of skills and organisational structures.

This research addresses the formidable challenge of achieving precise trajectory tracking for autonomous vehicle formations in uncertain environments. It introduces an adaptive control system tailored for autonomous vehicles, with a primary focus on ensuring prescribed performance in trajectory tracking within a leader-follower formation paradigm. The system incorporates a guidance law that allows the leader vehicle to dynamically adjust desired yaw angles and speeds for follower vehicles based on the established reference trajectory, enhancing tracking accuracy and responsiveness to environmental changes. To address practical external disturbances, the study utilizes Radial Basis Function Neural Networks (RBFNN) in conjunction with second-order filters for error approximation. This approach is further strengthened by a carefully formulated adaptive law. The innovative integration of a barrier Lyapunov function with the backstepping method significantly enhances the system’s adaptability and robustness, ensuring trajectory tracking performance meets predetermined standards. Simulation results illustrate the control system’s adept handling of various external disturbances, consistently maintaining trajectory tracking errors within predefined limits. This underscores the system’s potential to markedly enhance the operational reliability and efficiency of autonomous vehicle formations in unpredictable environmental conditions.

Numerous elements, such as the composition and characteristics of carbon nanomaterials, the composition and characteristics of the matrix material, moisture levels, temperature, and loading circumstances, influence the piezoresistive behaviour of self-sensing cementitious composites. While some past research has explored the impact of some of these factors on the performance of self-sensing cementitious composites, additional investigations need to be conducted to delve into how loading conditions affect the sensitivity of self-sensing cement-stabilized composites. Therefore, this study explores the influences of various loading conditions (i.e., location of loading regarding the location of recording electrodes, and loading level) on the electromechanical performance of self-sensing cement-stabilized sand. To this end, firstly, the evaluation of the percolation threshold based on 10% cement-stabilized sand specimens containing various multiwall carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) was performed. Then, 10% cement-stabilized sand containing 4% MWCNTs/GNPs was tested under various cyclic compressive stresses. The results suggested that the distance between the loading area and the electrode location used for recording the electrical resistance significantly impacts the sensitivity of cement-stabilized sand. Optimal sensitivity was achieved when the electrodes were positioned directly beneath the loading area. Moreover, the study yielded that the stress sensitivity of self-sensing cement-stabilized sand increases proportionally with the stress level. Examination through scanning electron microscopy (SEM) demonstrated that the loading condition influences the bridging characteristics of carbon nanomaterials in cement-stabilized sand, leading to diverse electromechanical behaviors based on the loading condition. This study underscores the importance of considering specific parameters when designing the application of self-sensing cement-stabilized sand for practical field use.

Background: Restorative materials might significantly affect load transmission at peri-implant bone. The aim of the present study is to evaluate the shock absorption capacity of two different polymeric materials to be used as frameworks for implant-supported prostheses. Methods: A masticatory robot was used to compare the shock absorption capacity of polyether-ketoneketone (PEKK) Pekkton®ivory (Cendres+Mètaux) and glass fiber-reinforced composite (GFRC) TRINIATM (Bicon). Five identical sample crowns for each of the materials was tested un-der the same conditions described in previously published papers (Menini et al. 2013). Forces transmitted at the simulated periimplant bone were recorded and statistically analysed. Results: The statistical analysis of forces transmitted at the simulated dental implant revealed significant differences between all the materials tested and significant differences with the mate-rials tested in a previously published paper (Menini et al. 2013: zirconia, glass ceramic, composite resin, acrylic resin). Only differences between PEKK and veneered PEKK and between PEKK and one of the previously tested composite resins were not statistically significant. PEKK samples demonstrated significantly greater shock absorption capacity compared to GFRC. Conclusions: PEKK revealed optimal shock absorption capacity. Further studies are needed to evaluate its efficacy in case of long span prostheses with reduced prosthetic volume.

The envelope (façade) of a building is the first barrier between the exterior and the interior of the building and withstands the highest variation of temperature and solar radiation. Trombe walls are used to take advantage of that and contribute to the heating of interior air, helping the heating system. In this study, a new Trombe wall design is presented with the aim to contribute significantly to the ventilation of residential buildings. For this an exterior wall equipped with a proposed Trombe system was studied in a numerical simulation analysis. The proposed systems consist of two parts, the air cavities on the exterior of the wall, covered with silica glass, and another layer used for heat transfer, on the interior, comprised of a MPCLBs wall of 115mm. Two cities in Romania were considered to represent the coldest and hottest climate in Romania. Brașov representing the cold climate and Constanța representing the hot climate. In the investigation, both the presence and absence of solar radiation were taken into account. In total 4 cases were established. For all four cases monthly research was made using monthly means temperature, direct and diffuse solar radiation. The results are promising and illustrate that the system works the best during the transitional seasons of spring and autumn. The lower the outdoor temperature the higher the temperature can be increased. Overall, solar radiation accounted for an average of 2 °C increase. The temperature increase varied between 3.4 °C to 15.99 °C for Brașov and between 6.42 °C to 12.07 °C in Constanța.

The goal of this study was to characterize the initial growth trajectory of Epicrates assisi, 1 Epicrates cenchria, and Epicrates crassus snakes raised in captivity. An exponential model with 2 parameters for birth weight (A) and growth rate (k) was fitted for each animal. There was a significant 3 difference A and k among the three species, the means (standard error) for A and k parameters were 4 31 (0.3) g and 0.0027 (0.00006) for E. assisi, 27.6 (0.6) g and 0.0046 (0.00013) for E. cenchria and 25.9 5 (1.4) g and 0.0033 (0.00027) for E. crassus. We showed a significative variability between species for 6 initial growth trajectory. In addition, we also demonstrated the existence of variability within species, 7 which can be used to change the growth trajectory of snakes, being a tool for selection and genetic 8 improvement.9

This study aimed to investigate the current status of the Sustainable Workplace Equality Policy (SWEP) in an emerging country—Kuwait—and how it impacts firms’ financial and market performance. The study included companies listed in the Kuwait Boursa (Boursa Kuwait is the operator of the Kuwait Stock Exchange) in the period between 2012 and 2020. A disclosure index was prepared for SWEP based on guidelines provided by a combination of various sources and standards such as the Global Reporting Initiatives (GRI) standard, S&P global corporate sustainability assessment, Dow Jones sustainability index, United Nations global compact, and KPMG sustainability reporting standards. Time series regression analysis was used to examine the study hypotheses. The analysis revealed a strong positive relationship between the SWEP disclosure and firm measures of financial performance. The results indicate that SWEP is value-relevant and affects firms’ market value, suggesting that investors should consider firms’ disclosure of the SWEP when making investment decisions. The results of the current study are of interest to several stakeholders, especially investors and policymakers. Specifically, the study is relevant to the Kuwaiti Government, which has defined a clear path for sustainable growth with the Vision 2035/New Kuwait that is aimed at transforming the country into a financial and commercial hub for the region by 2035.

The objectives of this article are to examine whether the application of digitalization in enterprise budgeting affects the fulfilment of budgeting functions and their qualitative characteristics, and to investigate whether the realization of budgeting functions brings benefits. The research was conducted from the perspective of contingency theory, both internal and external conditions. The study used an online survey targeting company budgeting staff. Structural Equation Modelling was utilized to validate the structural model (PLS-SEM technique). The conclusions confirm that the application of digitalization, which particularly pertains to ERP, Business Intelligence systems and accounting systems with budgeting solutions, positively impacts the fulfilment of budgeting functions and most of their qualitative characteristics, while Blockchain makes a minor contribution. Our research suggests that contingency variables, particularly internal ones such as company size, the quality of the organizational structure, and support for competitive strategy, continue to affect budgeting implementation even with the participation of digitalization in budgeting. Budgeting functions and their qualitative aspects are notably correlated with the advantages derived from budgeting, including financial performance, sustainable development and budget task execution.

The main aim of this study is to examine the effects of Total Quality Management (TQM) practices (leadership of management, decision making, continuous improvement, customer focus, employee involvement, process management and relations with suppliers) on the financial and operational performance of hospitals in service industry. The data of the study were collected by the questionnaire prepared in the light of published studies and the suggestions of medical and administrative staff. Medical and administrative staff were chosen as target participants that reflect perspectives of hospitals. 1069 questionnaires were answered in 6 private and 26 public hospitals in the Marmara region in Turkey. The results claim that “customer focus” affects both operational performance as well as the financial performance of hospitals more than other TQM practices. While “process management” and “customer focus” explain the variance of financial performance significantly. “Process management” does not explain variance of operational performance.

At present, countries around the world adopt digital strategy, so that enterprises apply digital technology, digital supply chain, blockchain, and a series of digital measures to enhance their competitiveness. By analyzing the relationship between digital transformation of manufacturing export enterprises, and their business performance and export performance, this paper focused on the current situation and existing problems of digital transformation of manufacturing export enterprises in China. Based on the Resource Based View theory and Trade theory, the impact of digital transformation of enterprises performance, proposing hypotheses, and building regression models were explored. With the samples of 1007 listed companies in Shanghai and Shenzhen Stock markets from 2012 to 2019, the regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis were conducted. The results shew that: (1) Listed manufacturing export enterprises carried out digital transformation, which had a significantly positive effect on enterprise performance; (2) It was found that digital transformation could improve enterprise performance by reducing costs, improving R&amp;D intensity and improving human resources etc. (3) According to the fractal analysis, non-state-owned enterprises had more positive effects on enterprise performance, and digital transformation of manufacturing export enterprises in developed areas had a more significant impact on enterprise performance. Finally, according to the empirical results, relevant suggestions for digital transformation were provided.

Market uncertainty has a significant impact on market performance. Previous studies put much efforts in investigations on market uncertainty related to information asymmetry and risk. However, they have neglected the uncertainty inherent in market transactions, which is also an important aspect of market performance, besides quantity of transactions and market efficiency. In this paper, we put forward the concept of transaction entropy to measure the market uncertainty and see how it changes with price. The definition of transaction entropy is the ratio of total information entropy of all traders to quantity of transactions, reflecting the level of uncertainty in making transactions. And the transaction entropy is the lowest at equilibrium, it will be decreasing in a shortage market, and increasing in a surplus market. Additionally, we make a comparison of total entropy of the centralized market with that of the decentralized market, revealing that the price filtering mechanism could effectively reduce market uncertainty. Overall, the introduction of transaction entropy enriches our understanding of market uncertainty and facilitates a more comprehensive assessment of market performance.

Indonesia has emerged as one of the leading producers and exporters of palm oil, as supported by data from the Central Bureau of Statistics in 2021, which indicate that Indonesian palm oil exports reached an impressive value of US$ 18.44 billion, or IDR 258 trillion, in 2020, marking an 18.43 percent growth compared to the previous year. Furthermore, the domestic market for palm oil and palm kernel oil remains substantial, despite improvements in export quantities. Various industries, including cooking oil refineries, specialty fats, shortening, margarine, bath soaps, and oleochemicals, present potential markets for palm oil (CPO) and palm kernel oil (PKO). The palm oil industry encompasses four related sub-sectors, namely growers, millers, refiners, and oleochemicals, forming an integrated value chain from upstream to downstream. The current focus on environmental, economic, and social sustainability is driving companies to adopt internal green activities and expand their efforts into sustainability supply chain management (SSCM). Implementing SSCM practices is often seen as economically beneficial, as research has demonstrated their positive impact on firm performance from a resource perspective. Within the palm oil industry, a wide range of green management applications are being utilized. This study aims to examine and highlight the existing sustainable management practices across the entire palm oil supply chain, with a particular emphasis on producing high-quality palm oil. To achieve this objective, the paper utilizes a systematic review methodology, The number of papers analyzed were 62 articles published which involves an extensive review of relevant literature to identify research trends, gaps, and issues. The study seeks to contribute to the body of knowledge by expanding the theory of organizational readiness in preparing globally competitive palm oil products. The research findings hold practical significance for practitioners and academics, providing a comprehensive roadmap for implementing green management applications at the organizational level in the palm oil industry's upstream-to-downstream chain.

Knowledge of body composition is essential for athletes for their sport performance. It has yet to be determined whether differences in body composition are present between international and non-international players playing in the same elite professional club competition. Similarly, it is not yet clear whether differences in body composition according to ethnic origin exist in the elite professional game, where relative homogeneity is to be expected among soccer players. There is no single anthropometric profile that guarantees sporting success, as the somatotype of football players differs according to their individual characteristics. The aim of this study was to assess the description and comparison of the body composition profile of latin american professional football players playing in european leagues. The sample was composed of 238 subjects football players from European professional football leagues. Differences were found in all variables measured. The present study shows that in Latin American professional football players playing in Europe, there are significant differences in different body composition variables such as weight, height, WC, skinfold and fat values. This means that the treatment of these data and the possible classifications of sporting performance carried out in football clubs should be different to other European or African-American football players.

The present study aimed to develop a mathematical model to estimate the performance of an indoor rowing event of 6000m through an 500 m all out test in junior athletes. We selected141 subjects from the Brazilian rowing confederation database (15.9 ± 1.0 years), subsequently randomised the sample to the development (~70%) and cross-validation (~30%) groups of the mathematical model. Performance data for 500m and 6000m were collected (there was a 48h washout between one test and anoth-er).Subsequently, the mathematical model: Time(min) 6000m = { [( Time(s) 500-m * 6) * 2] / 60} + 1.3, was developed by arithmetic modeling using machine learning and Regression analysis, being tested by intraclass correlation coefficient (ICC), Concordance correlation coefficient (CCC), Validity (Cb ), preci-sion (ρ) and bland-Altman plotting. The prediction of the result of 6000m through the mathematical model utilizando apenas o desempenho de 500m “all-out” test showed a significant reliability in de-velopment group (r2 = 0.730, ICC = 0.753; CCC = 0.895, Cb = 0.879, ρ: 0.957, pure error: 0.2 secounds (1.0% estimative error)); and in cross-validation group (r2 = 0.710, ICC = 0.747; CCC = 0.888, Cb = 0.875, ρ: 0.903, pure error: 0.3 secounds (1.4% estimative error)). When comparing the estimated re-sults of the 6000m performance by the mathematical model with the real performance of 6000m per-formed in indoor rowing, no statistical differences were observed. In addition, the mathematical model did not present a significant proportion bias in relation to the 6000 m performance in both groups. The mathematical model for predicting 6000m performance through a 500m fast test was significant for national level junior rowing athletes.

Digital transformation of companies is often referred to as a future track and a strategic path towards ensuring the survival and sustainability of companies. In this paper, we aim to outline this transformation process in Tunisian companies and identify its driving factors and finally explain its key success factors. To this end, we examine a sample of 70 companies operating in all economic sectors. The results indicate that such a digital strategy has a significant and a positive effect on the success of digital transformation of companies. Leadership has an effect at a low level of digital maturity. On the other hand, corporate culture does not have a significant effect on digital transformation. These results contribute to explaining this emerging phenomenon by focusing on the driving factors as well as the factors that contribute to its success.

UHPC is a cement-based composite that is used in new construction and/or renovation of existing structures to increase their service life. It is a unique composite material that may be used as an alternative to concrete in harsh conditions. Following decades of research and development, a wide range of commercial UHPC compositions are now accessible across the world to fulfill the growing number of applications and demand for high-quality construction materials. Although UHPC has significant advantages over conventional concrete, its use is limited because of rigid design restrictions and excessive pricing. As a consequence, a detailed analysis of UHPC's durability qualities is necessary to provide critical information for material testing requirements and methods, as well as to widen its practical applications. The goal of this study is to learn more about UHPC and to encourage more research and use of UHPC.

Understanding how species that follow different life-history strategies respond to stressful temperature can be essential to efficient treatments against agricultural pests. Here we focus on how the development and reproduction of C. medinalis is influenced by exposure to different rearing temperatures in the immature stage. We found that low (18 or 22 °C) or high (30 and 34 °C) rearing temperatures negatively affected the immature development and flight performance compared to the normal temperature 26 °C, with higher larval and pupal mortality, lower pupation and eclosion rates and shorter flight duration and distance. Low rearing temperatures significantly slowed down the immature process, but accelerated adult reproduction. However, high rearing temperatures had the opposite impacts. Interestingly, the flight of adults with un-mature rearing low temperatures (18 and 22 °C) significantly decreased their lifetime fecundity and mating frequency, but increased pre-oviposition period of females compared to the control; On contrast, high rearing temperatures (30 and 34 °C) significantly accelerated onset of oviposition and enhanced synchrony of spawning. These results indicate high rearing temperatures in the immature stage are more likely to trigger the onset of migration, but low rearing temperatures induces adults to have a greater resident propensity with stronger reproductive ability.

The exposure to extreme temperatures in workplaces involves physical hazards for workers. A poorly acclimated worker may have lower performance and vigilance and may therefore be more exposed to accidents and injuries. Due to the incompatibility of the existing standards implemented in some workplaces and the lack of thermoregulation in many protective equipment, thermal stress remains one of the most frequent physical hazards in many work sectors. However, many of these problems can be overcome with the use of smart textile technologies that enable intelligent thermoregulation in personal protective equipment. Smart textiles can detect, react and adapt to many external stimuli. Interconnected sensors and actuators that interact and react to existing risks can provide the wearer with increased safety, protection and comfort. Thus, the skills of smart protective equipment can contribute to the reduction of errors and the number and severity of accidents in the workplace, and thus promote improved performance, efficiency and productivity.This review provides an overview and opinions of authors on the current state of knowledge on these types of technologies by reviewing and discussing the state of the art of commercially available systems and the advances made in previous research works.

The aim of this article was to examine if there are position-specific differences in the morphological characteristics of sub-elite female football players and to establish normative standards for this level of female football players. The morphological features of 101 sub-elite female football players (age: 21.8±2.7 years) were assessed. Twenty anthropometric sites were used in the measurements of body composition and somatotype. The average value of body fat percentage was 20.8±5.7%. The somatotype of the overall group was 4.0–2.4–2.1. Positional significant (p ≤ 0.05) differences were found between goalkeepers and outfield players in morphological characteristics. Goalkeepers were taller, heavier, possessed the highest body fat percentage and showed higher values for all skinfolds, breadth, girth and length measurements. However, there were very few practically worthwhile differences between the outfield positions. Positional groups did not differ (p ≤ 0.05) in somatotype characteristics either. The study suggests that at sub-elite level there are mainly differences between goalkeepers and outfield players, but outfield players are homogeneous when comparing morphological characteristics. These results may serve as normative values for future comparisons regarding the morphological characteristics of female football players.

Background: The treatment plan of prosthetic restorations supported by dental implants require comprehensive scientific knowledge to deliver prostheses with good prognosis, even before the implant insertion. This review aims to analyze the main prosthetic determinants of the prognosis of implant-supported prostheses. Methods: A systematic review of the literature was conducted with a PICO question: "For partially or complete edentulous subjects treated with implant-supported prostheses, which prosthetic factors could affect clinical outcomes?". A literature search was performed electronically in PubMed (MEDLINE), Scopus and Cochrane Library with the following equation [PROGNOS* OR RISK] FACTOR IMPLANT DENTAL, and by hand search in relevant journals and throughout the selected papers. Results: This revision was carried out based on 50 papers focused on several prosthodontics-related risk factors that were grouped as follows: implant-connection, loading protocol, transmucosal abutments, prosthetic fit, provisionalization, type of retention, impression technique, fabrication technique, and occlusion. More than a half of the studies were systematic reviews (30%), meta-analysis (16%) or prospective evaluations of prosthesis with various kinds of events (18%). But also narrative reviews of literature (14%) and in vitro/animal studies (16%) were found. Conclusions: The current literature provides insufficient evidence for most of the investigated topics. However, based on the accumulated data, it seems reasonable to defend that the best treatment approach is the use of morse taper implants with transmucosal abutments, recorded by means of rigidly splinted copings through the pick-up technique, and screwed by milled prosthesis occlusally adjusted to minimize functional overloading.

The complexity of the design in high-rise residential projects is a challenge for the construction industry in completing projects that fit the needs of users. Performance-Based Building Design (PBBD) appears as a design concept that can describe these needs into performance requirements. In this case designing a building can be considered as an iterative process of exploration, where desired functional properties can be created, the shapes are suggested, and evaluation processes is used, so as to bring together the shapes and functions of the building. This concept is a container for designers to produce high-performance buildings. This study aimed to identify the performance-based building design factors applied by architect designers and engineers in high-rise residential building in Surabaya. As part of this study, primary data was collected based on surveys conducted through observation and questionnaire distributed to designers who had or were involved in the high-rise residential design process in Surabaya. A total of sixty-eight respondents were included in this study. Descriptive analysis through a mean and standard deviation scatter plot was used to rank the application of PBBD. Meanwhile, factor analysis was used in the analysis of PBBD application factors. From the results of the analysis, four factors were obtained for the application of PBBD in high-rise residential buildings in Surabaya, namely; the interests of occupants, the sustainability of building operations, the design collaboration process, and the risk of loss. Future research is the influence relationships and measure the success model of PBBD at a higher level into BIM (Building Information Modeling) interoperability.

The heat values of waste mineral oils are equal to the heat value of the fuel oil. However, heat value alone is not sufficient for the use of waste mineral oils. as fuel. However, the critical physical properties of fuels such as density and viscosity need to be adapted to the system in order to be used. In this study, the engine oils used in the first 10,000 km of the vehicles were used as waste mineral oil. An organic-based Mn additive was synthesized to improve the properties of the waste mineral oil. It was observed that mixing the Mn additive with the waste mineral oil at different doses (4, 8, 12 and 16 ppm) improves the viscosity of the waste oil and the flash point. The resulting fuel was evaluated for emission using different loads in a 5 kW capacity generator to compare the fuel with standard diesel fuel and to determine the effect of Mn addition. In the experimental study, it was observed that the emission characteristics of the fuel obtained from waste mineral oil were worse than diesel fuel, but some improvement with Mn addition. As a result, we found that the use of waste mineral oils in engines in fuel standards was not appropriate, but may be improved with additives.

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

The study aims to analyze the performance criteria of the GR4J model to reproduce high water flows in the Ouémé watershed at Bonou's outlet which has been vulnerable to climate change in recent decades. The methodology focused on the use of daily climatological and hydrometric data extracted from files of National Directorate of Meteorology, and General Directorate of Water; they were supplemented by those of SIEREM/HSM dataset over the period 1961-2015. The rainfall was regionalized using Thiessen method. The performance of the GR4J model was assessed with NSE, RMSE and KGE criteria. The results indicate that the study area is marked by rainfall variabilities and detection of two breakpoints (1968 and 1987) which divide the series into three sub-periods; these discontinuities have repercussions on the streamflow. It's found that GR4J model overestimates the streamflow during the low water period and underestimates them in high water. However, the efficiency and performance criteria NSE, RMSE and KGE calculated on high water flow rates are better in calibration than in validation. The KGE values are range between 83-85% in calibration and 56-68% during validation, which gives to GR4J model the efficiency and performance to reproduce high flow rates in the study area

This paper presents a brief account and rationale for implementation of competency-based learning in any form of management and leadership development programmes in South Africa. The fact that competency-based learning (CBL), also known as outcomes-based learning has been scrapped from the schooling system in South Africa is unfortunate as this method enhances critical thinking skills and practical problem-solving skills. This paper presents CBL as a model of meta-cognitive approach to learning that integrates both theory and practice into experiential learning through six dimensions, namely, active learning, constructive learning, cumulative learning, goal-oriented learning, learner-centred and curriculum design strategies. In the advent of the fast-paced global economy, managers and leaders need to seek those business schools that value real-time practical approach to curriculum for relevance and to maximize shareholder value through human resource development. This brief presentation ends by recommending an approach through CBL that fosters three critical pillars of leadership development, namely: intellectual, behavioural and emotional agenda.

This study examines if enterprises’ digital transformation enhances their sustainable development capabilities and reduces carbon emissions, thus enhancing carbon neutrality performance and implementing the "dual-carbon" strategy. It specifically explores the impact of Chinese firms’ digital transformation on carbon neutrality performance in 30 provinces and municipalities in China from 2011 to 2021. Based on the Difference-in-Difference method and spatial econometric modeling, this study finds a U-shaped relationship between enterprise digital transformation and carbon performance, with spatial spillover effects. It also finds that converting environmental charges into taxes can significantly improve carbon performance. In terms of the mechanism of action, digital transformation affects carbon performance by influencing energy use efficiency and adjusting the level of industrial structure advancement and rationalization. In terms of heterogeneity, this U-shaped relationship exists only in the eastern and central regions, and the significance is more substantial in the east; in addition, the impact of enterprise digital transformation on carbon performance is more evident in regions with higher R&D intensity and higher economic development levels. These findings imply that the government should further encourage and guide enterprise digital transformation, monitor the effects of environmental protection policies and select and implement carbon emission reduction strategies according to local conditions to improve carbon performance.

The problem of health status prediction of insulated-gate bipolar transistors (IGBTs) gains a lot of attention in the field of health management of power electronic equipment. The performance degradation of IGBT gate oxide layer is one of the important failure modes. In view of failure mechanism analysis and easy implementation of monitoring circuit, this paper selects the gate leakage current of IGBT as the precursor parameter of gate oxide degradation, and uses time domain characteristic analysis, gray correlation degree, Mahalanobis distance, Kalman filter and other methods to carry out feature selection and fusion, and finally obtains a health indicator characterizing the degradation of IGBT gate oxide. Based on the Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) network, this paper constructs an IGBT gate oxide degradation prediction model, and performs experimental analysis on the dataset released by NASA-Ames Laboratory, and the average absolute error of performance degradation prediction is as low as 0.0216. Compared with Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Support Vector Regression (SVR) and CNN-LSTM models, CNN-LSTM network has the highest prediction accuracy. These results show the feasibility of gate leakage current as a precursor parameter of IGBT gate oxide layer failure, as well as the accuracy and reliability of the CNN-LSTM prediction model.

The year 2022 was characterized by several major events that impacted the business world in Indonesia and even globally after the COVID-19 pandemic devastated all business sectors in Indonesia and the world. The current business environment is experiencing accelerating turbulence characterized by increasing intensity of business competition, rapid changes in the market, and industrial connections climate. The industrial connection climate of an institution can be measured by the pattern of relationships that occur between workers and management. Industrial connections are fundamental to the sustainability of an organization and are understood as an important factor in influencing institutional performance. This research aims to look at the impact of the existence of industrial connections instruments, turbulence in the business environment on the industrial connections climate. Besides, how the industrial connections climate relates to firm performance. The research design is an inferential quantitative, using sampling and snowball sampling methods with total sample are 406. The data collected were analyzed using Structural Equation Model using LISREL version 8.70. This research used a survey to build an SEM model that tested the effect of organizational turbulence and industrial connections instruments on organizational climate directly, and tested mediation on organizational performance. All related indicators have outer loading more than 0.5 and T-value more than 1.96. Therefore, the conclusion is that all measurements are valid. Composite Reliability (CR) and VE for all indicators are >0.7 and >0.5 respectively. This research shows that industrial assosiation climate has a positive effect on business turbulence and industrial connections instruments. However, industrial connections instruments show a greater impact on the assosiation climate. This is because industrial connections instruments are the media used in the implementation of industrial connections in organizations. This research also confirms that industrial assosiation climate is positively related to organizational performance. The result of the indirect influence (IE) of 0.20 with t value is 8.47 means that the climate of Industrial connections is able to mediate the influence of Industrial connections Facilities on Organizational Performance.

While providing safe water for the rural poor is considered a basic human right, there are numerous issues associated with existing technologies with shortcomings. Performance issues have continued to fail to meet the needs of impoverished families due to issues including high cost, difficulties with performance, and continuing needs for maintenance. These issues have severely interfered the safe water accessibility. Key aspects of the Guelph Water Filter (GWF) system can avoid/minimize many of these issues. The GWF as described herein enables delivery of low cost, long-term performance at 3Log removal of E.coli and can deliver 1 to 3 L of treated water per hour. The GWF is simple to operate, has an ability to provide sufficient water for a family, maintains longevity of performance, is easy to maintain and has protection against breakage during the cleaning process, is repairable at village level, and operates using a sizable reservoir of water to supply raw water, meaning the technology does not need to be refilled frequently. Hence, the capability of the novel GWF technology is shown to bypass many of the troublesome features of alternative low-tech water treatment technologies. The potential for the GWF to function for 2 days continuously avoids the need for young girls to fetch raw water frequently during a day, thereby enabling them to attend school. Hence, the GWF enhances the potential to result in ‘safe water and full schools’, providing the opportunity for girls to receive education and capture socio-economic benefits for the community.

This article presents an experimental study focused on the impact of supplementing pure gasoline (E0) with bioethanol, gradually increasing the biofuel concentration up to 70% (E10, E50, and E70). The research was conducted in two phases: In the first phase (Part I), the engine's operation involved varying engine speeds (n = 2000 rpm, n = 2500 rpm) and adjusting throttle openings (15%, 20%, 25%) to analyze changes in brake torque, thermal efficiency, and ecological indicators. The second phase (Part II) aimed to complement and clarify the study data. Here, the engine was maintained at a constant speed (n = 2000 rpm) and brake torque (MB = 80 Nm) while altering ignition timing. The findings revealed that increasing the bioethanol concentration up to 70% led to modest enhancements in engine brake torque and thermal efficiency. However, the most significant impact was observed in the reduction of greenhouse gas emissions and incomplete combustion byproducts. The study also established that achieving higher thermal efficiency requires compensating for the extended ignition delay phase resulting from bioethanol addition by advancing ignition timing. Nevertheless, this approach is constrained by the escalating emissions of carbon dioxide and hydrocarbons. These findings provide valuable insights into optimizing the balance between bioethanol supplementation, engine performance, and environmental sustainability in spark ignition engines.

Using the World Bank Global Findex Database for 91 countries in 2014, 2017, and 2021, we examine whether fintech levels influence bank performance and whether fintech’s interaction with GDP per capita causes differential effects on bank performance globally. Since fintech levels were already very high for rich countries when the World Bank started providing fintech development statistics in 2014, we estimate AbFintech by regressing fintech levels on GDP per capita by year. AbFintech is the difference between the fintech level and its fitted values. Then, using multiple regression analyses, we investigate the impact of AbFintech on bank performance worldwide, focusing on the differential effects of AbFintech and GDP levels on bank performance. We find AbFintech significantly increases bank performance, primarily in less developed countries. Specifically, AbFintech increases banks’ ROA in the least developed countries and net interest margin in the 75th percentile countries. Also, AbFintech decreases the cost-to-income ratio in the 75th percentile countries, while it increases the ratio in the most developed countries. AbFintech does not affect the ratio of noninterest income to total income, regardless of the level of economic development.

Education is the bedrock of any nation. It is essential for individual and societal growth and development. This triggers the demand for quality education which simultaneously increases with a growing demand for quality assurance. This study investigated the role of quality assurance in achieving the expected outcome of education in Bosnia and Herzegovina’s higher education system. Comparative development is looked at by examining other National Qualification Frameworks. The study was based on textual reviews and descriptive analysis on student enrollment and programs of studies. Unlike the global trend, it can be seen that student enrollment is on the decline in Bosnia and Herzegovina. It was found that quality assurance is an indispensable tool for strengthening the higher education system and for achieving the desired change and outcomes, that education offers. It was also found that study programs and curricula are pivotal for teaching and learning processes, and that a unified qualification framework is essential for achieving set objectives of education at all levels. The study recommended, among other things, that sound quality assurance systems as well as appropriate structure for monitoring and accreditation be put in place and be judiciously followed in order to achieve the desired outcomes in conjunction with the set objectives of higher education. Moreover, vital thoroughly analyzed pressures (i.e., democratic, economic, and systemic) barriers show signs of epistemological, political, and institutional barriers in the country.

While lidar-based forest inventory methods have been widely demonstrated, prediction of tree diameters with lidar is not well understood. The performance metrics typically used in studies for prediction of diameters can be difficult to interpret and may not support comparative inferences between sampling designs or study areas. We evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions using two indices which are easier to interpret and compare. The indices are based on the coefficient of determination (R²), and root mean square deviation (RMSD). These indices facilitate comparisons with alternative (non-lidar) inventory strategies, and with other project areas. We evaluate k nearest neighbors (k-NN) dbh density (relative frequency by dbh class) prediction strategies with lidar for 190 training plots distribute across the 800 km² Savannah River Site in South Carolina, USA. We evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. Amongst the examined strategies we found Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.

Three-dimensional (3D) facies and petrophysical models were generated from previously published data of carbonate strata in the Dam Formation (eastern Saudi Arabia) to quantitatively investigate, describe, understand, model, and predict the permeability anisotropy of tidal flat carbonate within a sequence stratigraphic framework. The resulting 3D models were used to conduct fluid flow simulations to demonstrate how permeability anisotropy influences the production of hydrocarbons and ultimately affects decisions concerning future drilling in the exploration and development of carbonate reservoirs that have tidal flat strata. The constructed 3D facies model consists of four lithofacies associations, two of which were grain-dominated associations and two of which were mud-dominated associations. These lithofacies associations varied spatially in four reservoir zones (zones 1 to 4), which represent two fourth-order sequences in the uppermost part of the Dam Formation. Zones 1 and 3 consist of transgressive parasequences, and zones 2 and 4 consist of the regressive parasequences of these sequences. The 3D porosity and permeability models have a coherent match with the distribution of the lithofacies and the stratigraphic framework of the Dam Formation. The results suggested that the permeability anisotropy in zones 1 and 3 is controlled by the occurrence of the grain-dominated lithofacies associated with tidal flat channels. This lithofacies association overlies the sequence boundaries of sequences 1 and 3, forms reservoir bodies with relatively high permeability values, and is elongated perpendicular to the shoreline of the depositional environments. In contrast, permeability anisotropy in zones 2 and 4 is thought to be controlled by the occurrence of the grain-dominated lithofacies associated with the oolitic shoal. This lithofacies association overlies the maximum flooding surface of sequences 2 and 4, forms reservoir bodies with relatively high permeability values, and is elongated parallel to the shoreline of the depositional environments. Fluid flow simulation results suggested that the trend in hydrocarbon production from the constructed 3D models depends on permeability anisotropy in each reservoir zone. Thus, recognizing trends in permeability anisotropy, which might be predicted using sequences stratigraphy, could help to identify potential areas for future drilling.

Marine sediment sample was collected and the total aerobic population was counted and probiotic Bacillus cereus was isolated. Then it was mixed with formulated feed by spraying, while control diet was purchased from a local aquarium. 30 days of feeding experiment was conducted. Carassius auratus fishes were randomly divided into two experimental groups in rectangular tanks. The first group served as a control in which fishes were fed with commercial feed. The second group of fish were fed with probiotic incorporated feed. After 40 days, their survival and growth performance were detected. Bacillus cereus incorporated feed significantly yielded higher survival rate of the fish compared to control. Food conversion ratio (FCR) was significantly lower than the control group. The main aim of this work is to investigate the effect of a marine probiotic bacteria, Bacillus cereus on the survival and growth performance of gold fish Carassius auratus.

In recent years, ESG (environmental, social, governance) has emerged as a critical investment concept. Its goal is to create value for both shareholders and society, encouraging companies to optimize social value. However, the exploration and research into "the proportion of firms ex-porting and the pathways through which the environmental, social, and governance activities of carbon-intensive firms influence firms' financial performance" remains largely unexplored. This study establishes a research framework within this context, utilizing listed Chinese manufactur-ing companies as the research subjects. Employing a fixed-time, fixed-industry, two-way fixed-effects model methodology, it delves into the relationship between ESG ratings, the pro-portion of firms' exports, and firms' financial performance through panel regression modeling. This study emphasizes the moderating role of carbon-intensive firms in the relationship. Find-ings indicate that both enterprise export proportions and carbon-intensive firms significantly affect the correlation between corporate ESG activities and financial performance. This has im-plications for investors, company management, policymakers, and regulators. Based on these findings, we propose policy recommendations at corporate and governmental levels to enhance ESG significance, strengthen corporate governance, and promote continuous ESG advancement. The study provides micro-level evidence of the interaction among ESG ratings, export ratios, carbon-intensive enterprises, and corporate performance, empowering investors to make in-formed decisions.

Reducing waiting times is crucial for ports to be efficient and competitive. Important causes of waiting times are cascading interactions between realistic hydrodynamics, accessibility policies, vessel-priority rules, and detailed berth availability. The main challenges are determining the cause of waiting and finding rational solutions to reduce waiting time. In this study, we focus on the role of the design depth of a channel on the waiting times. We quantify the performance of channel depth for a representative fleet rather than the common approach of a single normative design vessel. It relies on a mesoscale agent-based discrete-event model that can take processed Automatic Identification System and hydrodynamic data as its main input. The presented method’s validity is assessed by hindcasting one year of observed anchorage area laytimes for a liquid bulk terminal in the Port of Rotterdam. The hindcast demonstrates that the method predicts the causes of 73.4% of the non-excessive laytimes of vessels, thereby correctly modelling 60.7% of the vessels-of-call. Following a recent deepening of the access channel, cascading waiting times due to tidal restrictions were found to be limited. Nonetheless, the importance of our approach is demonstrated by testing alternative maintained bed level designs, revealing the method’s potential to support rational decision-making in coastal zones.

At present European buildings typically consume two to five times more energy than predicted at the design stage. An important cause of this performance gap is the discrepancies between the design specification and the As-Built condition. Such discrepancies are mainly due to the gaps in knowhow between design, production and construction professionals. Design is more and more contained into a virtual environment and loses touch with the physical production and construction sites. As the construction sector enters the Industry 4.0 era, Building Information Modelling (BIM) based Mixed Reality can intertwine virtual and real worlds to bridge the knowhow gaps.

An increasing number of studies have shown that safety culture factors have a substantial influence on safety performance in a variety of industrial sectors. These factors' impact on safety performance is unclear, especially at the public service and statutory authorities. On the other hand, the understanding of indicators for safety performance in every working sector in Malaysia is on the continuing progress. Hence, this study's contribution is to explore the influence of safety culture factors (i.e., management commitment and supervision in safety, safety system) and safety competence on safety performance in government paramedic training institutes. IPMA (importance-performance map analysis) is a technique used in Smart PLS to determine the significance and performance of each of these factors. The study was conducted via an online survey and involved 258 safety and health committee members in Ministry of Health paramedic training institute. As a matter of relevance, the IPMA's empirical data study revealed that management commitment and supervision in safety were the predominant factors in determining safety performance. Meanwhile, for performance, the findings showed that worker involvement, safety system, and safety competence perform well in determining the safety performance.

This study was conducted to propose the Green Economic Development Plan for Manufacturing S.M.E.s based on financial performance and operations thru Green Initiatives. The descriptive survey method used to gather data to determine the green initiative's implementation of small and medium (S.M.E.s) manufacturing enterprises. Green initiatives use as a basis for crafting a green economic development plan. Document analysis was also employed to obtain data from any available printed materials and records provided by the respondents. Such methods of gathering information used to validate data gathered from local and foreign-related literature. The observation also employed to survey the assets owned and validate any green initiatives practiced, including their implementation. The study's findings show that among the green initiatives implemented by SMMEs, which resulted in the reduction of total costs and expenses, were the proper disposal and segregation of waste materials, water management by recycling wastewater and using water-efficient equipment, natural resources, and raw materials management. SMMEs should encourage active participation and support of suppliers and customers in achieving G.E.D.'s objectives by developing incentive schemes.Furthermore, SMMEs should continue to benchmark with G.E.D. Practitioners are operating locally and abroad to adopt best greening strategies and regularly network with concerned government agencies for continuous updating on G.E.D. Initiatives that may benefit the firm. Further research may be conducted on green initiatives implemented by small and medium enterprises in other industry sectors.