Negative temperature coefficient (NTC) materials are usually based on ceramic semiconductors and electrons are involved in their transport mechanism. A new type of NTC material, adequate for alternating current (AC) applications, is represented by zeolites. Indeed, zeolites are single-charge carrier ionic conductors with a temperature-dependent electrical conductivity. In particular, electrical transport in zeolites is due to the monovalent charge-balancing cations, like K⁺, capable of hopping between negatively charged sites in the aluminosilicate framework. Owing to the highly non-linear electrical behavior of the traditional electronic NTC materials, the possibility to have alternative types of materials, showing linearity in the electrical behavior, is very desirable. Among different zeolites, the natural clinoptilolite has been selected for investigating the NTC behavior since it is characterized by high zeolite content, convenient Si/Al atomic ratio, good mechanical strength, due to its compact microstructure, and low toxicity. Clinoptilolite has shown a rapid and quite reversible impedance change under heating, characterized by a linear dependence on temperature. X-ray diffraction (XRD) has been used to identify the natural zeolite, to establish all types of crystalline phases present in the mineral, and to investigate the thermal stability of these phases up to 150°C. X-ray photoelectron spectroscopy (XPS) analysis has been used for the chemical characterization of the natural clinoptilolite sample, providing important information on the cationic content and framework composition. In addition, since electrical transport takes place in the zeolite free-volume, a Brunauer–Emmett–Teller (BET) analysis of the mineral has been also performed.

Electroencephalography (EEG) signals provide valuable insights into various activities of the human brain, including the detection of mental stress, which is a complex physiological and psychological response. However, the challenge lies in identifying mental stress accurately while mitigating the limitations associated with a large number of EEG channels. This includes issues such as computational complexity, the risk of overfitting, and the increased setup time for electrode placement, which can be cumbersome for real-life applications. Therefore, it is crucial to develop EEG channel selection algorithms that enable the creation of a wearable device capable of assessing mental stress in real-life scenarios. This study introduces a novel channel selection method aimed at identifying highly accurate channels for detecting mental stress. Our approach, known as the Correlation Coefficient of Hjorth Parameters (CCHP), assesses the correlation between activity, mobility, and complexity in the time domain to nominate the most relevant channels. By selecting channels that exhibit high correlation with the stress task while being uncorrelated with each other, CCHP significantly reduces the number of EEG channels required, without compromising accuracy or performance. To evaluate the effectiveness of CCHP, we conducted experiments using the DEAP public dataset. Comparing our results with other recent algorithms that utilize the full set of EEG channels, CCHP achieved a superior classification accuracy of 81.56% using only eight EEG channels. Furthermore, CCHP outperformed existing channel selection methods by an impressive 8%. These findings strongly indicate that the CCHP algorithm shows great promise in the design of a wearable application for mental stress detection, utilizing a minimal number of EEG channels.

A field experiment was conducted for determination of crop coefficient (KC) and water stress coefficient (Ks) for wheat crop under different salinity levels, during 2015-16. Complete randomized block design of five treatments were considered, i.e., 0.51 dS/m (fresh water) as a control treatment and other four saline water treatments (4, 6, 8 and 10 dS/m), for S1, S2, S3 and S4 with three replications. The results revealed that the water consumed by plants during the different crop growth stages follows the order of FW>S1>S2>S3>S4 salinity levels. According to the obtained results, the calculated values of crop coefficients significantly differed from those suggested by FAO No.56 for the crops. The Ks values clearly differ from one stage to another because the salt stress causes both osmotic stress, due to a decrease in the soil water potential, and ionic stress which the average values of water stress coefficient (Ks) follows this order; FW(1.0)=S1(1.0)>S2(1.0)>S3(0.93)>S4(0.82). Overall, it was found the differences are attributed primarily to specific cultivar, the changes in local climatic conditions and seasonal differences in crop growth patterns. Thus, further studies are essential to determine the crop coefficient values under different variables, to make the best management practice (BMP) in agriculture.

Clustering coefficient measures are key complex network analysis tools. We examine local and global clustering coefficient measures with respect to the lexicographic graph product. As a preliminary condition, we analyze the $K_3$ subgraph structure focused on vertex inclusion with respect to the product graph. From this structure, we determine both the clustering coefficient for the product graph vertices and the average clustering coefficient for the product graph.

This algorithm is designed to perform Discrete Fourier Transforms (DFT) to convert temporal data into spectral data. This algorithm obtains the Fourier Transforms by studying the Coefficient of Determination of a series of artificial sinusoidal functions with the temporal data, and normalizing the variance data into a high-resolution spectral representation of the time-domain data with a finite sampling rate. What is especially beneficial about this DFT algorithm is that it can produce spectral data at any user-defined resolution.

The influence of small-scale processes at the ocean-atmosphere boundary layer such as spray and foam on the surface waves prediction is studied. Estimates of the effect of including the exact number of specific fragmentation "parachute" type in the spray on the resulting drag coefficient is shown. For the estimates, the numerical simulations within WAVEWATCH III wave model are performed. The parameterizations of wind input were tested within WAVEWATCH III wave model: default ST4 and ST6 parameterizations and the ST1 and ST6 parameterizations used together with the implemented drag coefficient parameterization. The proposed parameterization takes into account the presence of foam and spay. The obtained results are compared with the NDBC buoys data. The importance of small-scale processes for waves at hurricane winds prediction and the prospects for their inclusion in modern numerical wave models is shown.

This paper presents the PEnsemble 4 model, a sophisticated machine learning framework that integrates IoT-based environmental data to accurately forecast maize yield. With the projected significant growth in global maize demand over the next decade, the inherent risks posed by the crop’s dependence on weather conditions necessitate improved prediction capabilities. The PEnsemble 4 model, developed with high accuracy, incorporates comprehensive datasets encompassing soil attributes, nutrient composition, weather conditions, and UAV-captured vegetation imagery. By employing a combination of Huber and M estimates, the PEnsemble 4 model effectively analyzes temporal patterns in vegetation indices, specifically CIre and NDRE, which serve as reliable indicators of canopy density and plant height. In addition, this research significantly contributes to precision agriculture by offering an efficient and sustainable alternative to conventional farming practices through precise yield predictions. Notably, the PEnsemble 4 model enables earlier estimation, advancing the timeline for yield prediction from the conventional day 100 in the R6 stage to day 79 in the R2 stage. This improvement enhances decision-making processes in farming operations. The remarkable accuracy rate of 91% underscores the importance of adopting a multifaceted data approach that harnesses IoT-derived environmental insights. Additionally, the PEnsemble 4 model extends its benefits beyond yield prediction, facilitating the detection of water and crop stress, as well as disease monitoring in broader agricultural contexts. Ultimately, the PEnsemble 4 model establishes a new standard in maize yield prediction, revolutionizing crop management and protection through the synergistic utilization of IoT and machine learning technologies.

Research on spatio-temporal geostatistical modelling remains a critical challenge in numerous scientific and engineering disciplines. This work introduces a novel extension of the dual kriging the spatio-temporal dual kriging (ST-DK) whose drift functions with fixed and adaptive coefficients are established. The approach appears to be effective in modelling complex spatio-temporal dynamics, particularly when relevant auxiliary variables exert substantial influence on the target variable. To illustrate its performance, we compare the ST-DK model with the classical spatio-temporal regression kriging (ST-RK) method for estimating temperature and air pressure data across Thailand in 2018. Our findings demonstrate that both ST-DK and ST-RK models, when utilizing adaptive coefficients, outperform their constant coefficient counterparts. Furthermore, the ST-DK method consistently exhibits superior performance compared to the ST-RK model.

In the last few years, researchers have paid increasing attention to singing voice evaluations.In their studies, they observed changes in the vibrations of the vocal folds during the transi-tion of registers. Additionally, they also found that these changes are less visible and audiblein the case of skilled singers. In order to confirm this theory we defined a new parameter,the Passaggio Peak Coefficient (PPC), obtained from an EGG signal to analyse pitch andopen quotient jump characteristics during the transition of vocal registers among 21 femaleand male choir members with different singing skills. The Kruskal-Wallis test proved thatit is possible to distinguish vocal skills, based on the ability to smoothen transitions amongfemale singers at a 5% significance level.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

This document makes a comprehensive analysis of the inequality of the water market in Chile, measured by the Gini coefficient method. The situation of water rights in Chile is of particular interest because it is a completely privatized system, where rights are traded in the market and therefore water is presented as a commodity. This privatization of water in Chile occurred as part of the process of neoliberalization since the 1981 Water Code. The results of this study indicate that both the concentration and the inequality in the distribution of water rights is very high. It proposes a profound revision of applying a mercantile logic to a scarce basic resource for life such as water and exploring the importance of its role as a national good for public use.

Let $\mathcal{\mathcal{S}}_{\cos}^{\ast}$ denote the class of normalized analytic functions $f$ in the open unit disk $\mathbb{D}$ satisfying the subordination $\dfrac{zf^{\prime}(z)}{f(z)}\prec\cos z$. In the second section of this article we find the sharp upper bounds for the initial coefficients $a_{3}$, $a_{4}$ and $a_{5}$ and the sharp upper bound for module of the Hankel determinant $|H_{2,3}(f)|$ for the functions from the class $\mathcal{S}_{\cos}^{\ast}$. The first result of the next section deals with the sharp upper bounds of the logarithmic coefficients $\gamma_{3}$ and $\gamma_{4}$ and we found in addition the sharp upper bound for $\left|H_{2,2}\left(F_{f}/2\right)\right|$. For obtaining these results we used the very useful and appropriate Lemma 2.4 of N.E. Cho et al. [Filomat 34(6) (2020), 2061--2072], and the technique for finding the maximum value of a three variable function on a closed cuboid. All the maximum found values were checked by using MAPLE\texttrademark{} computare software, and we also found the extremal functions in each cases. All of our present results are the best ones and give sharp versions of those recently published in [Hacet. J. Math. Stat. 52, 596--618, 2023].

This study uses a mass-spring-damping system to simulate the repeated strain of liquefaction cyclic triaxial tests. The two results are compared in this paper to understand the feasibility of the mass-spring-damping system developed in this paper and the feasibility of future research on this related topic and development potential. The main factors affecting this mode's repeated strain are the spring coefficient k and the external force Q0. The spring coefficient has an inverse relationship but does not increase in multiples. The external force has a direct proportional relationship but does not increase the result- a non-multiple increase. When the pore water pressure of the liquefied cyclic triaxial test specimen rises, it will cause the specimen to liquefy, decreasing effective stress, shear modulus G, and damping ratio D, causing an increase in strain. The shear modulus and damping ratio are related to the spring coefficients k and c. Both are variables that change with time. This article takes an original thin-tube specimen at point A in the Yunlin area in Taiwan as a testing example. Through Mathematica software, it can be obtained that the mass m=1kg, the spring coefficient k=244e-0.1t kgf/cm, and the damping coefficient c=0.739e-0.257t kgf-s/cm and external force Q0=10.1sin2πt kg; Finally, this study selected the original thin-tube specimens from four locations in the Yunlin area, and simulated the repeated strain amount of the cyclic triaxial test specimens through a spring-damping system. The results show that the spring-damping system is feasible for simulated cyclic triaxial tests because the model is simple and the parameters are easy to understand and obtain, which also shows the extensibility of this model. Preliminary results of the research show that this model can further simulate the repeated strain obtained by cyclic triaxial tests without considering the increased trend in pore water pressure and the decrease in effective stress during cyclic loading.

To understand the relationship between water permeability and the pore structure of cementitious materials, literature that studied both water permeability and the pore structure are reviewed, and their correlation is studied. Although the majority of this data is for cement paste, mortar, concrete, and cemented soil are also included. Based on this study, it is established the determination coefficient between water permeability and the total pore volume is very low; however, those between water permeability and the critical, threshold, and median pore diameters, respectively, are moderate. On the other hand, the threshold pore diameter, derived based on the percolation theory, exhibits a very high determination coefficient. The calculated water permeability, using the Katz and Thompson equation, agrees with the reported water permeability quantitatively to a certain level, but is overestimated.

The assessment outcomes of regional susceptibility to geological disasters can directly indicate the extent and intensity of risks within the study area, thus, providing targeted guidance for disaster management efforts. This study selects eight evaluation indicators, namely elevation, gradient, terrain relief, lithology of strata, normalized difference vegetation index, distance from the fault, distance from road, and distance from the river. The study focuses on Huize County in Yunnan Province as the research area, utilizing the certainty factor (CF) and random forest (RF) models for evaluating the susceptibility to geological disasters. The non-geological disaster points in the study area are determined using the deterministic coefficient prior model, and the deterministic coefficient values for each evaluation factor serve as the classification data for the random forest model. The optimal parameters for the random forest are selected through iterative calculations of bag error in PyCharm, while the weight of the evaluation factor is determined based on the ran-dom forest model with the optimal parameters. The results of geological disaster susceptibility zoning in Huize County are obtained by overlaying the weighted deterministic coefficients of each evaluation factor. The accuracy of the evaluation results is verified using zoning statistics and ROC curves with a test sample of 30% of the points. The results demonstrate the high accuracy of the model in evaluating the susceptibility to geological disasters in Huize County. Compared to the single deterministic coefficient model, this approach offers advantages in terms of reliability and accuracy. The evaluation results can serve as a scientific reference for related work in Huize County.

The importance of irrigation in boosting agricultural production and productivity is widely understood. Proper planning and effective and efficient management and operation of irrigation system require crop and site-specific data. Since the last few years, Ethiopia has embarked on expansion of irrigated wheat. However, crop-specific data useful for irrigation planning and management for wheat crop is limited. The objective of this research was to determine water requirements and crop coefficients for wheat crops based on field measurements. The research was carried out at the Debre Zeit Agricultural Research Center in central Ethiopia during the dry season (Bega) of 2021/22. The crop considered for the experiment was durum wheat of the Utuba variety. Two non-weighing lysimeter units were employed to measure the water balance components. The soil moisture was monitored using gravimetric method on daily basis conducted both before and after each irrigation event at various depth intervals. The crop required a total of 115 days to fully mature. The length of the growth of initial, development, mid, and late stages were about 20, 30, 42, and 23 days, respectively. Microsoft Excel was used for the data analysis and the CropWAT8.0 model to estimate the reference evapotranspiration. Crop evapotranspiration (ETc) was determined using the water balance equation, and crop coefficients were computed from ETc and reference evapotranspiration (ETo). The results indicate that the total seasonal water requirement of the crop was 392.75mm. The growth stage-based water requirement was 40.35 mm, 82.44 mm, 238.66 mm, and 31.3 mm during the initial, development, mid, and late growing stages, respectively. For the initial, development, mid, and late stages of wheat growth, the crop coefficient was calculated to be 0.51, 0.83, 1.29, and 0.52, respectively. It was found that a fourth-degree polynomial equation fits well and explains the relationship between day of growth stage and kc of the crop. Although a one-season measurement, the results generated here could be useful for crop-specific data in scarce areas.

The deterioration of soil-cement in corrosive environment leads to the reduction of strength and the increase of permeability. Effective methods of determining deteriorated layer permeability coefficient of soil-cement are currently lacking. A laboratory test method for permeability coefficient of deteriorated layer was proposed using the modified permeability coefficient testing apparatus. According to the proposed method, the permeability coefficient of deteriorated layer can be obtained after testing the permeability coefficient of the soil-cement specimen in curing room and the equivalent permeability coefficient and deterioration depth of the soil-cement specimen in corrosion environment. Taking the marine dredger fill of Jiaozhou Bay for example, the deteriorated layer permeability coefficients of soil-cements with different cement contents were tested. It turned out that the permeability of deteriorated layer increases with the increase of age. At the beginning of curing age, larger cement content leads to smaller permeability coefficient of the deteriorated layer of soil-cement. As the curing age increases, the deteriorated layer permeability coefficient of the soil-cement with larger cement content becomes larger. The evolution of the permeability coefficient of deteriorated layer with age can be formulated as the Logistic function. This study provides a support for anti-permeability designs of soil-cement structures in corrosive environment.

This study aimed to evaluate potential posttreatment changes in ADC values within the tissue surrounding the enhancing lesion, particularly in areas not exhibiting MRI characteristics of in-volvement. Additionally, the objective was to investigate the correlation between ADC values, treatment response, and survival outcomes in individuals diagnosed with gliomas. This retrospective study included a total of 49 patients that underwent either stereotactic biopsy or maximal surgical resection. Histologically confirmed as Grade III or IV gliomas, all cases adhered to the 2016 and 2021 WHO classifications, with subsequent radio-chemotherapy administered post-surgery. Patients were divided into two groups: short and long survival group. Baseline and follow-up MRI scans were obtained on a 1.5T MRI scanner. Two ROI circles were positioned near the enhancing area, one ROI in the NAWM ipsilateral to the neoplasm and another symmetrically in the contralateral hemisphere on ADC maps. At follow-up there was a significant difference in both ipsilateral and contralateral NAWM be-tween the two groups, -0.0857 (p=0.004) and -0.0607 (p=0.037), respectively. There was a weak negative correlation between survival and ADC values in ipsilateral and contralateral NAWM at the baseline with the correlation coefficient -0.328 (p=0.02) and -0.302 (p=0.04), respectively. The correlation was stronger at the follow-up. The findings indicate that ADC values in normal appearing white matter (NAWM) may function as a prognostic biomarker in patients with diffuse gliomas.

There are many problems based on solving non-autonomous differential equations of the form x¨(t)+ω2(t)x(t)=0, where x(t) represents the coordinate of a material point and ω is the angular frequency. The inverse problem involves finding the bounded coefficient ω. Continuity of the function ω(t) is not required. The trajectory x(t) is unknown, but the initial and final values of the phase variables are given. The variation principle of minimum time for the entire dynamic process allows for the determination of the optimal solution {x(t),ω(t)}. Thus, the inverse problem is an optimal control problem. No simplifying assumptions were made.

Satellite measurements are one of the main sources of data on the state of the marine environment. To obtain information about the sea brightness coefficient , it is needed to correctly carry out atmospheric correction. In the presence of dust aerosol over the Black Sea, physically incorrect values of the spectral brightness coefficient often occur, and specifically negative values in the IR region of the spectrum. The main objective of the study is to evaluate the influence of dust aerosol on the spectral dependence of sea brightness, based on analytical calculations from the transfer theory using the principle of plane-parallel layers and results of validation of AERONET-OC field and remote sensing data. The work analyzes spectral dependence of the first error eigenvector of the standard atmospheric correction in the presence of dust aerosol. As result it is given that with an absorbing aerosol, the atmospheric correction error is described by the spectral course of molecular scattering, i.e. close to

Hydrogen is a promising energy carrier, exploitable to extract energy from fossil fuels, biomasses as well as intermittent renewable energy sources and its generation from fossil fuels with CO₂ separation at the source is one of the most promising pathway for fossil fuels utilization. This work is focused on a particular configuration, called Reformer and Membrane Module (RMM), which alternates stages of Steam Reforming (SR) reaction with H2 separation stages to overcome the thermodynamic limits of the conventional SR. The configuration has numerous advantages with respect to the more studied and tested membrane reactors and has been tested on a pilot scale during a pilot-scale research project. Although the numerous modelling works appeared in the literature, the design features of the material exchanger (in the so-called RMM architecture) of different geometrical configurations have not been developed and the mass transfer correlations, capable of providing design tools useful for such membrane modules, are not available. The purpose of this work is therefore to apply a physical-mathematical model of the mass transfer, in three different geometries, considering both concentration polarization and membrane permeation, in order to: i) simulate the cited experimental results, ii) estimate the scaling-up correlations for the “material exchange modules”; iii) identify the mass transfer limiting regime in relation to the gas mass flow rate.

We present an exact expression for the upscaled dynamic dispersion coefficient (D) for one-dimensional transport by Hagen-Poiseuille flow which is the basis for modeling transport in porous media idealized as capillary tubes. The theoretical model is validated by comparing the breakthrough curves (BTCs) from a 1D advection-dispersion model with dynamic D to that from direct numerical solutions utilizing a 2D advection-diffusion model. Both Taylor dispersion theory and our new theory are good predictors of D at lower Peclet Number (Pe) regime, but gradually fail to capture most parts of BTCs as Pe increases. However, our model generally predicts the mixing and spreading of solutes better than Taylor’s theory since it covers all transport regimes from molecular diffusion, through anomalous transport, and to Taylor dispersion. The model accurately predicts D based on the early part of BTCs even at relatively high Pe regime (~62) where the Taylor’s theory fails. Furthermore, the model allows for calculation of the time scale that separates Fickian from non-Fickian transport. Therefore, our model can readily be used to calculate dispersion through short tubes of arbitrary radii such as the pore throats in a pore network model.

Fresnel incoherent correlation holography (FINCH) is a well-established incoherent imaging technique. In FINCH, three self-interference holograms are recorded with calculated phase differences between the two interfering, differently modulated object waves and projected into a complex hologram. The object is reconstructed without the twin image and bias terms by a numerical Fresnel back propagation of the complex hologram. A modified approach to implement FINCH by a single camera shot by pre-calibrating the system involving recording of the point spread function library and reconstruction by a non-linear cross-correlation has been introduced recently. The expression of the imaging characteristics from the modulation functions in original FINCH and the modified approach by pre-calibration in spatial and polarization multiplexing schemes are reviewed. The study reveals that a reconstructing function completely independent of the function of the phase mask is required for the faithful expression of the characteristics of the modulating function in the image reconstruction. In polarization multiplexing method by cross-correlation, a partial expression was observed, while in spatial multiplexing method by cross-correlation, the imaging characteristics converged towards a uniform behavior.

Longitudinal dispersion coefficient (LDC) plays an essential role in modeling the transport of pollution and sediment in the natural rivers. As a result of transportation processes, the concentration of pollution changes along the river. Different studies have been conducted to provide simple equations for estimating LDC. In this study, Support Vector Regression (SVR), Gaussian Process Regression (GPR), M5P and Random Forest (RF) examined to predict the LDC in the natural streams. The hydraulic and geometric features of different rivers gathered for developing the mentioned models for LDC estimation and various statistical criteria were utilized to scrutinize of the models. Furthermore, the Taylor chart was used to evaluate the models and achieved results showed that among machine learning models, M5P displayed the superior performance with CC of 0.823, SI of 0.812, NS of 0.577 and WI of 0.879. As well, S-D model with CC of 0.795 SI of 0.827, NS of 0.558 and WI of 0.890 had more precise results than other empirical models. The results indicates that the developed M5P model with simple formulations was superior to other machine learning models and empirical models and therefore, it can be used as a proper tool for estimating LDC in natural rivers.

We examine the impact of temperature (T) on the Seebeck coefficient S, i.e., the T dependence of S for the single-component molecular conductor Pd(dddt)_2] (dddt = 5,6-dihydro-1,4-dithiin-2,3-dithiolate) with a half-filled band, where the coefficient is obtained from a ratio of the thermal conductivity to the electrical conductivity. The conductor exhibits Dirac electrons with a nodal line, which shows the energy variation around the chemical potential and the density of states (DOS) with a minimum. Using a three-dimensional tight-binding (TB) model in the presence of both impurity and electron--phonon (e--p) scatterings, we study the Seebeck coefficient S_y for the molecular stacking and the most conducting direction. The impact of T on S_y exhibits a sign change, where S_y > 0 with a maximum at high temperatures and S_y < 0 with a minimum at low temperatures. The T dependence of S_y suggests that the contribution from the conduction (valence) band is dominant at low (high) temperatures.The result is examined using a spectral conductivity \sigma_y(\epsilon,T) as a function of the energy $\epsilon$ close to the chemical potential \mu. Further, the Seebeck coefficients for perpendicular directions (x and z) are examined, to show both S_x and S_z being positive and no sign change in contrast to S_y.

Water pollution is the main cause of global ecological degradation and seriously affects people's water supply. In order to respond to the water environmental protection policy and provide management departments with a basis for refining water quality, this paper used the environmental Gini coefficient (EGC) method based on four indicators such as water environmental capacity, population, land area, and gross domestic production (GDP) to represent social factors, economic factors, and environmental factors, respectively. After the optimization, for COD, the EGC based on the land area was 0.30, EGC based on population was 0.21, EGC based on environment capacity was 0.02, and the EGC based on GDP was 0.45, and the sum of EGC was 0.962. From this result, we observed that the change in the Gini coefficient of each indicator was not very big. Hence, the most significant change in the Gini coefficient was that of GDP, with a higher rate than other criteria. Then, the COD, AND, and TP discharge allocation model was constructed to obtain the total allocated discharge permit in Lushui Basin. The results found that the total discharge permit allocation of COD, AN, and TP to the Lushui basin were 51483.304 tons/year, 843.119 tons/year, and 340.926 tons/year, respectively. Based on the GIS spatial analysis technology, the distribution of unfair factors that cause pollution inequity was investigated. Finally, the reduction measures were proposed to implement environmental supervision and strengthen water environment management strictly.

The article contains the results of experimental studies for a multi-opening orifice with substitute constriction factor of β = 0.5 (m = 0.25), mounted in a DN50 hydraulic measuring flume. Flow measurements were taken for a progressing turbulent flow within Reynolds numbers (Re = 4700...19500). Based on experimental data, flow characteristics as well as discharge coefficient C characteristics were determined. Relative expanded uncertainty of determining a discharge coefficient C was estimated within the changes of volume flow qv from 0.35 dm3/s to 0.68 dm3/s. The value does not exceed 1.25% within the changes of Reynolds numbers 9800 ≤ Re ≤ 19500.

Understanding the spatially varying effects of demographic factors on the spatio-temporal variation of intestinal parasites infections is important for public health intervention and monitoring. This paper presents a hierarchical Bayesian spatially varying coefficient model to evaluate the effects demographic factors on intestinal parasites morbidities in Ghana. The modeling relied on morbidity data collected by the District Health Information Management Systems. We developed Poisson and Poisson-gamma spatially varying coefficient Models. We used the demographic factors, unsafe drinking water, unsafe toilet and unsafe liquid waste disposal as model covariates. The models were fitted using the Integrated Nested Laplace Approximations (INLA). The overall risk of intestinal parasites infection was estimated to be 10.9 per 100 people with a wide spatial variation in the district-specific posterior risk estimates. Substantial spatial variation of increasing multiplicative effects of unsafe drinking water, unsafe toilet and unsafe liquid waste disposal occurs on the variation of intestinal parasites risk. The structured residual spatial variation widely dominates the unstructured component, suggesting that the unaccounted-for risk factors are spatially continuous in nature. The study concludes that both the spatial distribution of the posterior risk and the associated exceedance probability maps are essential for monitoring and control of intestinal parasites.

We consider the inverse function $z=g(w)$ of a (normalized) starlike function $w=f(z)$ of order $\alpha$ on the unit disk of the complex plane with $0<\alpha<1.$ Krzy{\. z}, Libera and Z\l otkiewicz obtained sharp estimates of the second and the third coefficients of $g(w)$ in their 1979 paper. Prokhorov and Szynal gave sharp estimates of the fourth coefficient of $g(w)$ as a consequence of the solution to an extremal problem in 1981. We give a straightforward proof of the estimate of the fourth coefficient of $g(w)$ together with explicit forms of the extremal functions.

The diffusion coefficients of ions are measured in a microchip filled with a cationic charged 3D hydrogel in order to study the effect of cationic charged 3D hydrogel on the diffusivity of ions. In this study, poly-diallyl-dimethyl-ammoniumchloride (poly-DADMAC) is used to produce a 3D hydrogel. Four different fluorophores are used in the 3D hydrogel rhodamine 6G, rhodamine-BSA, fluorescein isothio-cyanate (FITC) and FITC-BSA. The rhodamine 6G and rhodamine-BSA are positively charged (cations), while fluorescein isothio-cyanate (FITC) and FITC-BSA are negatively charged (anions). Two widely used techniques which are short time diffusivity measurement technique and long time diffusivity measurement techniques are used to measure the diffusion coefficients. For the short time measurement, Fluorescence recovery after photo-bleaching (FRAP) is used by a 3D confocal microscope. For the long time measurement, fluorescence images are taken for 11 days to observe a pure diffusivity without any convective movement. As a result, the diffusivity of the cations was found to be lower than that of the anions in the cationic charged hydrogel.

Immersion in salt-lake solution was adopted to periodically test the concrete chloride-ion diffusion coefficient. The regression analysis was also completed. Also investigated was the time-dependent law of concrete chloride-ion diffusion coefficient with time. The influence of chloride-ion concentration in solution, water-to-cement ratio, and corrosion time on the largeness and accumulation rate of the concrete chloride-ion diffusion coefficient was also analyzed. Test results show that the concrete chloride-ion diffusion coefficient gradually decreased with increasing time and increased with increasing chloride-ion concentration in a salt lake . Taking into account the influence of factors such as water–binder ratio, chloride-ion concentration, and time-varying characteristics, a multi-factor calculation model for the concrete chloride-ion diffusion coefficient was established. Combining the prediction results and the measured data reported in this paper, the effectiveness and applicability of the established concrete chloride-ion diffusion coefficient calculation model were compared and verified, and the durability design and service life of a concrete structure under cool chlorine were compared. The results of analysis provide important boundary conditions.

The runoff coefficient (C) represents the relationship between the surface runoff volume and the precipitated volume. It is used in engineering projects for flood estimation methods. Although C values are tabulated and consecrated in hydrological engineering, as if they were constant, they may not correspond to the reality, because in the same catchment, they can vary according to the intensity, temporal and spatial distribution of precipitation events, humidity conditions, and ground cover. This study had the objective of analyzing extreme events of precipitation and the corresponding flows to obtain experimental runoff coefficients (C) and compare them with the tabulated values. The study was conducted in four experimental catchments in the State of São Paulo, Brazil, with different land uses and soils. The runoff coefficients (C) were obtained from the analysis of hydrograms and using a digital filter, which allowed the separation of the direct runoff, of the total flow. When analyzing flow and precipitation data in different seasons of the year, selecting events of the floods of catchments and separating the flows, we observed a variation of the flow coefficient values, different from those obtained from tables.

The diffusion coefficient--a measure of dissipation, and the entropy--a measure of fluctuation are found to be intimately correlated in many physical systems. Unlike the fluctuation dissipation theorem in linear response theory, the correlation is often strongly non-linear. To understand this complex dependence, we consider the classical Brownian diffusion in this work. Under certain rational assumption, i.e. in the bi-component fluid mixture, the mass of the Brownian particle $M$ is far greater than that of the bath molecule $m$, we can adopt the weakly couple limit. Only considering the first-order approximation of the mass ratio $m/M$, we obtain a linear motion equation in the reference frame of the observer as a Brownian particle. Based on this equivalent equation, we get the Hamiltonian at equilibrium. Finally, using canonical ensemble method, we define a new entropy that is similar to the Kolmogorov-Sinai entropy. Further, we present an analytic expression of the relationship between the diffusion coefficient $D$ and the entropy $S$ in the thermal equilibrium, that is to say, $D =\frac{\hbar}{eM} \exp{[S/(k_Bd)]}$, where $d$ is the dimension of the space, $k_B$ the Boltzmann constant, $\hbar $ the reduced Planck constant and $e$ the Euler number. This kind of scaling relation has been well-known and well-tested since the similar one for single component is firstly derived by Rosenfeld with the expansion of volume ratio.

To avoid loss of information and incorrect ranking, this paper proposes a method for ranking generalized fuzzy numbers, which guarantees both horizontal and vertical values are important parameters affecting the final ranking score. In this method, the normalized height coefficient is introduced to evaluate the influence of the height of fuzzy numbers on the final ranking score. The higher the normalized height coefficient of a fuzzy number is, the higher its ranking. The left area and the right area are presented to calculate the impact of vertical value on the final ranking score. The left area is considered the benefit area. The right area is considered the cost area. The fuzzy number is preferred if the benefit area is larger and the cost area is smaller. The proposed method can be employed to rank both normal and non-normal fuzzy numbers without normalization or height minimization. Numerical examples and comparison with other methods highlight the feasibility and robustness of the proposed method, which can overcome the shortcomings of some existing methods and can support decision-makers to select the best alternative.

This study will present a comprehensive review of the two-phase flow boiling heat transfer coefficient of hydrocarbons such propane (R-290), butane (R-600) and iso-butane (R-600a) and ethanol at various experimental conditions. Studying the multiphase flow heat transfer coefficient has a crucial importance for many heat transfer equipment to achieve higher efficiency for more compact design and cost reduction. One reason behind choosing hydrocarbons as refrigerants in this study is because hydrocarbons have zero ozone depletion potential (ODP=0) and insignificant direct global warming potential (GWP = 3). Moreover, thermodynamic and thermophysical characteristics of hydrocarbons qualify them to be a strong candidate for more heat transfer applications. Initially, by constructing a database for the working fluids from various experimental work available in the literature. The current data that this study has collected for the flow boiling of spans wide ranges of parameters, such as: mass flux, heat flux, operating pressure, and saturation temperature, etc. Furthermore, by comparing the experimental multiphase heat transfer coefficient database with the anticipated values of each correlation, the prediction performance of 26 correlations found in the literature was assessed. This study leads to the selection of the best prediction method based on the minimum deviation of predicted results from the experimental database provided by calculated mean absolute error (MAE) from the assessed correlations. The findings of this study can also be useful in the development of more accurate correlation methods for these fluids and improve the prediction of their flow boiling characteristics.

The thermal insulation properties of building walls are critical to the overall energy efficiency and comfort of a building. One important factor that can affect these properties is the type of bricks used in construction. Bricks can vary in their geometry and thermal coefficient, which can impact their ability to transfer heat through the wall. The geometry of a brick can affect its thermal properties by altering the amount of air trapped within it and the surface area available for heat transfer. Hollow bricks or those with complex geometries may have lower thermal conductivity than regular solid bricks due to the air pockets trapped within them. Conversely, larger surface areas on the exterior of the brick can increase heat transfer. The thermal coefficient of clay, a common material used in brick production, is another important factor. Clay has a relatively low thermal conductivity, meaning it is a poor conductor of heat. However, the quality of the clay, as well as the firing temperature and duration used in brick production, can impact its thermal coefficient. Higher firing temperatures and longer firing times can result in a more compact and dense clay brick, which can improve its thermal properties. In summary, the thermal insulation properties of building walls can be significantly affected by the type of bricks used in their construction. It is important to consider the geometry and thermal coefficient of the bricks when designing a building to achieve the desired level of thermal insulation. By selecting bricks with appropriate properties, designers can help to improve the energy efficiency and comfort of the building while reducing its environmental impact.

The emergence of electric vehicles has brought new issues such as the problem of rolling element bearings (REBs) operating at high speeds. Losses due to these components in mechanical transmissions are a key issue and must therefore be taken into account right from the design stage of these systems. Among these losses, the one induced by the motion of rolling elements , known as drag loss, becomes predominant in high-speed REBs. Although an experimental approach is still possible, it is difficult to isolate this loss in order to study it properly. A numerical approach based on CFD is therefore a possible way forward, even if other issues arise. The aim of this article is to study the ability of such an approach to correctly estimate the drag coefficient associated with the motion of rolling elements. The influence of the numerical domain extension, the mesh refinement, the simplification of the ring shape and the presence of the cage, on the values of the drag coefficient is presented. While it seems possible to compromise on the calculation domain and mesh size, it appears that the other parameters must be taken into account as much as possible to obtain realistic results.

The main goal of our work is the revealing of problematic issues related to estimates of the absorption coefficient of colored organic matter in the northern seas from data of the Ocean and Land Color Instrument (OLCI) on the Sentinel-3 satellites. In particular, a comparison of the OLCI standard error estimates ADG443_NN_err., relating to the measurement and retrieval of the geophysical products, with the uncertainties in the real situation of the northern seas, where the natural conditions are extremely unfavorable (first of all, frequent cloudiness, low Sun heights). We conducted a comprehensive multi-sensor study of the uncertainties using various approaches, first at all, directly comparing the data from satellite (OLCI Sentinel-3 and four other ocean color sensors) and field measurements in five sea expeditions 2016-2019, by using the different processing algorithms. Our analysis has shown that the real uncertainties of the final product are significantly higher than the calculated errors of the ADG443_NN_err., which is 100% and ~10%. The main reason for that is the unsatisfactory atmospheric correction. We present the results of the analysis of the different effecting factors (satellite sensors, processing algorithms, use of the other parameters), and formulate the tasks of future work.

The health of the landing gear retraction and extension hydraulic system may be assessed using fuzzy comprehensive evaluation (FCE), however the traditional FCE method depends solely on human assessment by specialists, which is excessively subjective. To address the issue of excessive human subjective variables in the assessment, an improved FCE model based on enhanced risk coefficient is provided, which includes four consideration indexes: failure probability, failure severity, failure detection difficulty, and failure repair difficulty. To reduce subjective human judgment errors entirely due to expert experience, the improved FCE takes into account the likelihood of failure using a statistical method, the severity of failure using a fault simulation analysis based on the LMS Imagine.Lab AMESim simulation platform, and the difficulty of fault detection and repair using the aircraft manufacturer's professional maintenance information. As part of the evaluation model, the range of health assessment values and accompanying treatment methods are included, making it easier to implement on a daily basis in aircraft maintenance. As a final step, the simulation is evaluated and the simulated faults are calculated.

The economics and safety of reactors can be affected by the diffusion of fission products into graphite. Xenon (Xe) fission products diffusing into the graphite is the most critical neutron absorber and poison that can slow down or stop the chain reaction. The transport parameters for inhibiting the xenon diffusion in graphite are therefore the utmost scientific problem. Self-sintered nanopore-isotropic (~ 40nm) graphite (SSNG) derived from green pitch coke can decrease Xe diffusion into the graphite. In this study, a method for measurement of diffusion coefficients of fission products diffusion in graphite by Rutherford backscattering spectrometry (RBS) was reported. The SSNG substrates were implanted with Xe at a dose of 4.8×1015 ions/cm2 and energy of 7 MeV. The RT-implanted samples were annealed in a vacuum at 650°C for 9 h. The implanted and annealed samples were characterized by RBS. The diffusion coefficient D(Xe,650°C) is 6.49×10-20 m2/s. The results indicate the excellent ability to inhibit Xe diffusion of the SSNG and present significance in designing and evaluating the safety of nuclear reactors.

The use of several light-related variables, such as the Secchi disc depth, the euphotic depth, and in particular, the diffuse attenuation coefficient (Kd), is deeply rooted in phytoplankton research, but these are not the most appropriate indicators of the amount of light available for photosynthesis. We argue that the variable of interest for phytoplankton is the mean light intensity in the mixed layer (Im), which represents the mean light to which phytoplankton cells are exposed throughout their life cycle, while being continuously mixed in the mixed layer. We use empirical data collected in different coastal ecosystems in southern Portugal to demonstrate why Im should be the preferred metric instead of the deeply rooted Kd. We show that, although the relationship between Im and Kd is inversely proportional, it is not always strong or even significant. Different Im values can be associated to the same Kd, but distinct Im have different physiological effects of phytoplankton. Therefore, Kd does not capture the amount of light available for photosynthesis, given that, unlike Im, Kd calculation does not consider the depth of the mixed layer. Therefore, we urge phytoplankton researchers to consider the measurement and calculation of Im when evaluating light-related processes in phytoplankton ecology.

An interesting anomaly of the diffusion process with an apparently negative diffusion coefficient defined through the mean-square displacement in a one-dimensional quantum molecular chain model is shown. Nevertheless, the system satisfies the H-theorem, so that the second law of thermodynamics is satisfied. The reason why the “diffusion constant” becomes negative is due to the effect of the phase mixing process, which is a characteristic result of the one-dimensionality of the system. We illustrate the situation where this negative “diffusion constant” appears.

Hyperspectral imaging, a rapidly evolving technique, furnishes exhaustive information on Earth's surface reflectance over an extensive spectrum of wavelengths. We have developed a more precise method for analyzing spectral data by meticulously selecting plant leaf pixels and employing a relative reference approach. This enhanced technique correlates camera pixel values with light intensity, bypassing the need for complex equations and thereby providing clearer insights into vegetation vitality. The findings of this study not only enhance the precision of hyperspectral imaging but also bolster our capability for ecological monitoring and understanding environmental health. A novel algorithm based on the red-edge slope was established to classify images, exploiting the spectral reflectance data gleaned from the hyperspectral Liquid Crystal Tunable Filter (LCTF) camera. Compared with conventional SVM and K-means algorithms, our novel algorithm demonstrated commendable performance, achieving an overall accuracy of 90% with a Kappa Coefficient of 0.86. This comparison highlights the novel algorithm's relative strength and potential for large-scale satellite and drone imagery analysis applications. The advancements facilitated by this research are instrumental in ecological assessments, conservation efforts, and resource management strategies, signaling a leap forward in the era of environmental monitoring and analysis.

The vacuum preloading method effectively strengthens the soft soil foundations with vertical drainage, which will produce a smear effect when laying sand drains. Meanwhile, the seepage of pore water and soil deformation during consolidation exhibits nonlinear characteristics. Therefore, based on Gibson's 1D large strain consolidation theory, this paper developed a more generalized large strain radical consolidation model of sand-drained soft foundations under free strain assumption. In this system, the double logarithmic compression permeability relationships for soft soils with large strain properties, the variation of the radical permeability coefficient in the smear zone, and the effect of the non-Darcy flow were all included. Then, the partial differential control equations were numerically solved by the finite difference method and validated with existing radical consolidation test results and derived analytical solutions. Finally, the influences of relevant model parameters on consolidation are discussed. The analysis shows that the greater the maximum dimensionless vacuum negative pressure P0, the faster the consolidation rate of sand-drained foundations. Meanwhile, the decrease in the negative pressure transfer coefficient k1 will result in a decreasing final settlement amount. Moreover, the consolidation rate of sand-drained foundations is slower considering the non-Darcy flow, but the final settlement is unaffected.

In China, the majority of mountainous regions are characterized by complex topography and a delicate, sensitive geological environment. Coupled with a generally underdeveloped infrastruc-ture and numerous unreasonable human engineering activities, these regions are often highly susceptible to geological disasters. Geological hazards can cause significant damage to human lives and property, impeding the development of mountainous areas. Consequently, researching the assessment of geological hazard vulnerability is crucial for disaster prevention, emergency management, and economic development in these regions. This study focuses on Xuanwei City and selects eight factors for evaluation, including elevation, gradient, slope aspect, normalized vegetation index, stratigraphic lithology, distance from faults, distance from rivers, and distance from roads. These factors are chosen based on a comprehensive analysis of the spatial and tem-poral distribution of geological hazards and disaster incubation conditions. Two paired models, the deterministic coefficient model + logistic regression model (CF+LR) and the information quan-tity model + logistic regression model (I+LR), were employed to quantitatively assess the study ar-ea. The accuracy of these models was evaluated using ROC curves and AUC values. The results indicate that: (1) The AUC values for the CF+LR and I+LR coupled models are 0.799 and 0.772, respectively, demonstrating that both models can objectively and reliably assess the vulnerability to geological hazards in the study area; (2) Based on the CF+LR model calculations, the geological hazard susceptibility of Xuanwei City can be categorized into four zones: extremely high suscepti-bility (6.09%), high susceptibility (31.08%), medium susceptibility (32.26%), and low susceptibility (30.57%); (3) The CF+LR model more accurately represents the evaluation results and offers a strong reference value.

The hydrodynamic results obtained from the permeability of porous materials not only affect the assessment of the stream of the gas flow through those materials but they also refer to the loss of pressure energy in that flow. The direct measure of that loss is flow resistances.The results of experimental research upon the assessment of the flow resistances of porous materials with respect to gas flow. The research conducted applied to natural materials with an anisotropic gap-porous structure. The tests were carried out on a gas permeability measuring system, adapted to different shapes of porous material samples. The process issue of the total pressure drop on a porous deposit was considered in the Reynolds number category. The coefficient of flow resistance for anisotropic materials was defined and the value of this coefficient was compared to the gas stream and the total pressure drop on the porous bed was experimentally evaluated.

Mate crime is a specific subset of hate crime in which the perpetrator is known to the victim. To date, there is very little research into the perception and experience of mate crime in autism. The aim of the current study was to examine perceptions of friendship and mate crime in autistic adults, using semi-structured interviews. Five adults were interviewed about their experiences of social interactions, friendships and mate crime. Participants described distancing themselves from the ‘disability’ label whilst growing up to avoid condescension and being perceived as vulnerable, whilst learning to camouflage their social difficulties. Feelings of anxiety were associated with socialising, and participants valued relationships that did not place too many overwhelming demands on their time or energy. Finally, all participants had prior experiences of bullying. They understood the concept of mate crime but were unsure as to whether they would be able to identify it in their own lives if it occurred. However they could identify potential support networks in close friends and family. Results highlight the importance of further research into positive and negative aspects of social relationships in autistic adults, and the need to provide support to those who are socially vulnerable.

This article draws on empirical research seeking to develop more nuanced understandings of child prostitution, previously theorised on the basis of children’s rights, feminist, and structure/agency debates, largely ignoring children’s own understandings of their involvement in prostitution. Conducted in Malawi, one of the economically poorest countries in the world, the study goes to the heart of questions of inequality and child protection. With careful attention to ethical considerations, a participatory approach was used to enable 19 girls and young women, whose involvement in prostitution began in childhood, to convey their own experiences and understandings of involvement. Data were collected using a range of methods, chosen by participants to match their abilities and interests. Data analysis and interpretation were aided by reference to the capability approach focussing on questions of human rights and social justice for women and girls. Generating rare insights into participants’ worlds, the research demonstrates how the persistence of deeply embedded cultural values in contexts of extreme poverty serves to sustain gender inequalities, constraining choices for girls and denying them opportunities to lead valued lives. The article ends by considering the theoretical and methodological implications of the study, policy and practice recommendations and opportunities for further research.

Industrial green technology innovation has become an important content in achieving high-quality economic growth and comprehensively practicing the new development concept in the new era. This paper measures the efficiency of industrial green technology innovation and regional differences based on Chinese provincial panel data from 2005 to 2018, using a combination of the super-efficient SBM model for considering undesirable outputs and the Dagum Gini coefficient method, and discusses and analyses the factors influencing of the industrial green technology innovation efficiency by constructing a spatial econometric model. The results show that: firstly, the industrial green technology innovation efficiency in China shows a relatively stable development trend, going through three stages: " stationary period", " recession period " and "growth period ". However, the efficiency gap between different regions is obvious, specifically in the eastern > central > western regions of China, and the industrial green technology efficiency innovation in the central and western regions is lower than the national average. Secondly, regional differences in the efficiency of industrial green technology innovation in China are evident but tend to narrow overall, with the main reason for the overall difference being regional differences. In terms of intra-regional variation, variation within the eastern region is relatively stable, variation within the central region is relatively low and shows an inverted 'U' shaped trend, and variation within the western region is high and shows a fluctuating downward trend. Thirdly, the firm size, government support, openness to the outside world, environmental regulations and education levels contribute to the efficiency of industrial green technology innovation. In addition, the industrial structure hinders the efficiency of industrial green technology innovation, and each influencing factor has different degrees of spatial spillover effects.

In this research, a novel method to investigation the transient heat transfer coefficient in a channel is suggested experimentally, in which the water flow, itself, is considered both just liquid phase and liquid-vapor phase. The experiments were designed to predict the temporal and spatial resolution of Nusselt number. The inverse technique method is non-intrusive, in which time history of temperature is measured, using some thermocouples within the wall to provide input data for the inverse algorithm. The conjugate gradient method is used mostly as an inverse method. The temporal and spatial changes of heat flux, Nusselt number, vapor quality, convection number, and boiling number have all been estimated, showing that the estimated local Nusselt numbers of flow for without and with phase change are close to those predicted from the correlations of Churchill and Ozoe (1973) and Kandlikar (1990), respectively. This study suggests that the extended inverse technique can be successfully utilized to calculate the local time-dependent heat transfer coefficient of boiling flow.

The present article is dealing with the state of question about building-energy monitoring systems used for data collection to estimate the Heat Lost Coefficient (HLC) with existing methods and so determinate buildings’ Envelope Energy Performance (EEP). In addition, the data requirements of HLC estimation methods are related with commonly used methods for fault detection, calibration and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests since 1978, a qualitative and quantitative analysis of Monitoring and Controlling System (MCS) specifications has been carried out. Although most actual Buildings Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply the HLC estimation methods.

Abstract Several studies have been conducted to strengthen weak road layers, regardless of whether they are un-der construction or are undergoing maintenance. Using substrates filled with different materials has proven effective for increasing the strength of these layers. In this study, I evaluated the coefficient of lateral soil pressure under various conditions when using reinforced and unreinforced piles filled with in-expensive material and the extent of their contribution to strengthening road layers. The results con-firmed that there was a difference in the coefficient of lateral soil pressure when the sand-filled piles were reinforced. The sand-filled piles were divided into several parts by arming. The maximum coeffi-cient of lateral soil pressure was 0.38 in the case of sand (1 mm) with reinforcement, whereas it was 0.29 in the same case without reinforcement as shown in Figure 1. The maximum coefficient of lateral soil pressure was 0.27 in the case of granite grain (2 mm) with reinforcement, whereas it was 0.17 in the same case without reinforcement. Moreover, the maximum lateral pressure coefficient was 0.26 in the case of granite grain (3 mm) with reinforcement, and it was 0.30 in the same case without reinforce-ment.

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

Numerous experimental and theoretical studies undertaken to determine the effective-stress coefficient for seismic velocities in rocks stem from the importance of this geomechanical parameter both for monitoring changes in rock saturation and pore pressure distribution in connection with reservoir production, and for overpressure prediction in reservoirs and formations from seismic data. The present work pursues a task to determine, in the framework of a low-frequency laboratory study, the dependence of the elastic moduli of n-decane saturated sandstone on the relationship between pore and confining pressures. The study was conducted on a sandstone sample with high quartz and notable clay content in the quasi-static regime, when the 100 ml tank filled with n-decane was directly connected to the pore space of the sample. The measurements were carried out at a seismic frequency of 2 Hz and strains, controlled by semiconductor strain gauges, not exceeding 10-6. The study was performed using a forced-oscillation laboratory apparatus utilizing stress-strain relationship. The dynamic elastic moduli have been measured in two sets of experiments: at constant pore pressures of 0, 1 and 5 MPa and differential pressure (defined as a difference between confining and pore pressures) varied from 3 to 19 MPa; and at а constant confining pressure of 20 MPa and pore pressure varied from 1 to 17 MP. It was shown that the elastic moduli obtained in the measurements are in good agreement with the Gassmann moduli calculated for the range of differential pressures used in our experiments, which corresponds to the effective-stress coefficient equal to unity.

Inequality of health service for different specialty categories not only occurs in different areas inequality of health service for different specialty categories in the world, but also happens in the online service platform. In the online health community (OHC), health service was often of inequality for different specialty categories, including both online views and medical consultation for offline registered service. Moreover, how the factor city-level impacts the inequality of health service in OHC is still unknown. We designed a causal inference study with data on distributions of serviced patients and online views in over 100 distinct specialty categories on one largest OHC in China. To derive the causal effect of the city-levels (two levels inducing 1 and 0) on the Gini coefficient, we matched the focus cases in cities of rich healthcare resources with the potential control cities. For the Gini coefficient of serviced patients in over 100 specialty categories, the average treatment effect of level-1 cities is 0.470, which is 0.029 higher than that of the matched group. Similarly, for the Gini coefficient of online views, the average treatment effect of Level-1 cities is 0.573, which is 0.016 higher than that of the matched group. For each of the specialty categories, we also estimated the average treatment effect the specialty category’s Gini coefficient ( ) with the balanced covariates. The results support the argument that the total Gini coefficient of all the doctors in OHC shows that the inequality of health service is still very serious. This study contributes to the development of the theoretically grounded understanding of the causal effect of city-level on the inequality of health service in an online to offline healthcare service setting.

Quantum correlations, especially time correlations, are crucial in ghost imaging in order to significantly reduce the background noise on the one hand while increasing the imaging resolution. Moreover, the time correlations serve as a critical reference, distinguishing between signal and noise, which in turn enable clear visualization of biological samples. Quantum imaging also addresses the challenge involved in imaging delicate biological structures with minimal photon exposure and sample damage. Here we explore the recent progress in quantum correlation-based imaging, notably its impact on secure imaging and remote sensing protocols as well as on biological imaging. We also exploit the quantum characteristics of heralded single-photon sources (HSPS) combined with decoy-state methods for secure imaging. This method uses Quantum Key Distribution (QKD) principles to reduce measurement uncertainties and protect data integrity. It is highly effective in low-photon-number regimes for producing high-quality, noise-reduced images. The versatility of decoy-state methods with WCSs (WCS) is also discussed, highlighting their suitability for scenarios requiring higher photon numbers. We emphasize the dual advantages of these techniques: improving image quality through noise reduction and enhancing data security with quantum encryption, suggesting significant potential for quantum imaging in various applications, from delicate biological imaging to secure quantum communication.

This study presents head losses (hL) and loss coefficients (K) obtained experimentally for schedule 40 PVC pipe elbows, with 90o and 45o in small commercial diameters of ½ to 1½ inches that are commonly used in small networks. The investigation was conducted on a system constructed with short pipes and fittings necessary to measure, direct, and control flow, as well as to evaluate pressure head losses at elbows. Simple water flow was used with rates of 0.342 to 0.980 lps (Q), which generated moderate Reynolds numbers (Re) of 13337 to 80221. It was found that hL showed dependence on the velocity head in all elbows, as well as that hL are greater as the diameter increases for same velocity head. The K values in the elbows tended to be constant when Q &gt; 0.75 lps, but for Q &lt; 0.75 lps the K coefficient increased inversely proportional to Q, becoming larger as the diameter increased. Likewise, the K coefficient tended to increase as Re decreased, while K tended to be constant as Re increased. The results of the experimental coefficient were compared against K values reported in the literature, where significant similarities and discrepancies were found.

The article presents the results of tests of minor head losses through PVC and PP elbows for a flow of water and mixtures of water and sand with grain sizes of up to 0.5 mm and concentrations of 5.6 g∙L-1, 10.84 g∙L-1, and 15.73 g∙L-1. The tests were carried out at variable flow velocities for three elbow diameters of 63, 75, and 90 mm. The flow rate, pressure difference in the tested cross-sections, and temperature of the fluids were measured and automatically recorded. The results of the measurements were used to develop mathematical models for determining the minor head loss coefficient as a function of elbow diameter, sand concentration in the liquid, and Reynolds number. The mathematical model was developed by cross validation. It was shown that when the concentration of sand in the liquid was increased by 1.0 g∙L-1, the coefficient of minor head loss through the elbows increased, in the Reynolds number range of 4.6∙104 − 2.1∙105, by 0.3−0.01% for PP63, 0.6−0.03 % for PP75, 1.1−0.06 % for PP90, 0.8−0.01 % for PVC63, 0.8−0.02 % for PVC75, and 0.9−0.04 % for PVC90. An increase in Re from 5∙104 to 2∙106 for elbows with diameters of 63, 75 and 90 mm caused a 7.3 %, 6.8 %, and 6.0 % decrease in the minor head loss coefficient, respectively.

A two-year experiment was conducted with a local maize hybrid under full irrigation (F), deficit irrigation (D) and rainfed conditions (R) to estimate maize evapotranspiration in Bosnia and Herzegovina. Three approaches (Allen & Pereira (A&P), SIMDualKc (SD), and Vegetation Index (VI)) were used to estimate the actual crop coefficient (Kc act), actual basal crop coefficient (Kcb act), and actual crop evapotranspiration (ETc act) were applied with the dual crop coefficient method and remote sensing (RS) data. While Kcb act from all approaches matched FAO56 tabulated values, SD showed differences, in comparison to A&P, of up to 0.24 in D and R conditions, especially in initial and mid-season stages. VI demonstrated very good performance in all treatments. In F, the obtained Kc act for all approaches during the initial and end stages were higher than the tabulated values, ranging from 0.71-0.87 for Kc ini act and from 0.80-1.06 for Kc end act, while the mid-season period showed very good agreement with the literature. Maize crop evapotranspiration range is 769-813 mm, 480-752 mm, and 332-618 mm for F, D and R, respectively. The results confirmed the suitability of both approaches (SD and VI) to estimate maize crop evapotranspiration under F, with the VI approach demonstrating an advantage in calculating Kcb act, Kc act, and ETc act values under water stress conditions. The 67.6% increase in grain yields with irrigation emphasizes the need to transition from rainfed to irrigation-dependent agriculture, even for drought-resistant crops like maize.

This study addressed a Fluid-Structure Interaction of an open Water test for vp1304 propeller to predict pressure and stress distributions with a low cost and high precision method. The most striking aspect of such a method(one-way coupling) is to use one hydrodynamic solution for the number of different structural sets involved in other materials or different layup methods and combinations of layers. An open-access software(OpenFOAM) with an open-source code solver is used to simulate the fluid domain. Abaqus is used To evaluate and predict the deformation and strength of the blade with the Finite Element Method(FEM). The coupling approach is based on dry condition, which means the added mass effects due to propeller blades vibration is neglected. The pressures imposed on the blades are extracted from the fluid solver for each time step. Then, These pressures role as a load condition for the structure solver. This approach was verified in the last paper(wedge impact); a key factor for the present solution is the rotational rate interrelated between two solution domains, which is explained in this paper. Finally, the blades' stress and strain are calculated and compared in each advance coefficient.

Aerobic vaginitis (AV) is a distinct clinical entity characterized by inflammation and abnormal vaginal microflora. Often mistaken for bacterial vaginosis, AV remains relatively unknown and underdiagnosed. AV's understanding is evolving, with some experts suggesting it may primarily be an immunological disorder, the prevalence of which ranges from 7-13% in non-pregnant women and 4.1-8.3% during pregnancy. Pregnancy can affect susceptibility to vaginal infections, leading to adverse outcomes for the woman and the newborn. This review summarizes the correlation between AV and adverse pregnancy outcomes, particularly preterm birth, the leading cause of morbidity and mortality among neonates. Improved understanding of AV's impact on pregnancy outcomes can lead to early recognition, proper management, and effective interventions. While some studies support an association between AV and preterm labor, the existing knowledge of this relationship remains limited. The evidence suggests that AV may contribute to adverse pregnancy outcomes, mainly preterm birth, but further research is needed to establish a definitive link. Further studies are needed to investigate the underlying mechanisms and clarify AV's role in premature labor. A comprehensive understanding of AV's impact on pregnancy outcomes is crucial for early recognition, appropriate management, and effective interventions.

The increasing complexity of the design and operation evaluation process of multi-energy grids (MEGs) requires tools for the coupled simulation of power, gas and district heating grids. Most tools analyzed in this paper either do not allow coupling of infrastructures, simplify the grid model or are not publicly available. We introduce the open source piping grid simulation tool pandapipes that – in interaction with pandapower - fulfills three crucial criteria: clear data structure, adaptable MEG model setup and performance. In an introduction to pandapipes we illustrate how it fulfills these criteria through its internal structure and demonstrate how it performs in comparison to STANET®. Then we show two case studies that have been performed with pandapipes already. The first case study demonstrates a peak shaving strategy as interaction of a local electricity and district heating grid in a small settlement. The second case study analyzes the potential of a power-to-gas device to serve as flexibility in a power grid under consideration of gas grid constraints. They both show the importance of a clear database, a simple simulation setup and good performance to set up different large and complex studies on grid infrastructure design and operation.

The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.

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

Few-shot object detection (FSOD) aims to address the challenge of requiring a substantial amount of annotations for training in conventional object detection, which is very labor-intensive. However, existing few-shot methods achieve high precision with the sacrifice of time-consuming for exhaustive fine-tuning, or take poor performance in novel-class adaptation. We presume the major reason is that the valuable correlation feature among different categories is insufficiently exploited, hindering the generalization of knowledge from base to novel categories for object detection. In this paper, we propose Few-Shot object detection via Correlation-RPN and Transformer Encoder-Decoder (CRTED), a novel training network to learn object-relevant features of inter-class correlation and intra-class compactness while suppressing object-agnostic features in the background with limited annotated samples. And we also introduce a 4-way tuple-contrast training strategy to positively activate the training progress of our object detector. Experiments over two few-shot benchmarks (Pascal VOC, MS-COCO) demonstrate that, our proposed CRTED without further fine-tuning can achieve comparable performance with current state-of-the-art fine-tuned works. The codes and pre-trained models will be released.

Background: Gender stereotypes and biases can influence perceptions of competence and suitability for certain medical specialties. Empathy is an important component of an optimal doctor-patient relationship. The scope of our study is to verify the correlation between “empathetic" behavioral style with attention and sensibility to the gender differences of patients of the medical students. Methods: An online survey was conducted using the Jefferson Scale for Empathy (JSE), to measure empathy in the context of health professions education and patient care; and the Nijmegen Gender Awareness in Medicine Scale (N-GAMS), which measures attitudes and assumptions about gender. A total of 234 students (52.1% M; mean age: 22.68±2.48) from Medicine and Surgery at the University of Salerno (Italy) participated, of whom n° 175 were third-year students and n° 59 were fifth-year students. Results: The JSE score shows that male students have higher scores (77.29±12.38) than females (75.91±10.39). Conversely, female students have higher perspective-taking (JSE Factor 1: Male= 51.26±11.84; Female= 52.72±11.88). In addition, third-year students are much more empathetic than their fifth-year colleagues (JSE Score: 3°ys= 77.35±11.46; 5°ys= 74.49±11.33). With reference to the GS, we found that male students have greater sensitivity than their female colleagues (GS: Male= 2.67±0.68; Female= 2.37±0.48); conversely, they have higher scores of gender stereotype towards patients (GRIP: Male= 2±0.88; Female= 1.59±0.61) and doctors (GRID: Male= 1.88±0.89; Female= 1.64±0.63). Also, the third-year students compared to their fifth-year colleagues are characterized by greater gender sensitivity (GS: 3°ys= 2.57±0.62; 5°ys= 2.42±0.57), less bias with respect to patients (GRIP: 3°ys= 1.77±0.79; 5°ys= 1.90±0.78) but, on the other hand, show more stereotypes and prejudices towards doctors (GRID: 3°ys= 1.77±0.81; 5°ys= 1.75±0.74). Conclusions: Humanistic attitudes, including empathy, should be instilled, and evaluated among trainees as an essential part of their postgraduate medical education.

This study aimed to determine whether camelina oil is safe for use in canine diets, using canola oil and flax oil as controls as they are similar and generally regarded as safe (GRAS) for canine diets. Thirty privately-owned adult dogs of various breeds (17 females; 13 males), with an average age of 7.2 ± 3.1 years (mean ± SD) and body weight (BW) of 27.4 ± 14.0 were used. After a 4-week wash-in period using sunflower oil and kibble, dogs were blocked by breed, age, and size, and randomly allocated to one of three treatment oils (camelina (CAM), flax (FLX), or canola (OLA)) at a level of 8.2 g oil/100g total dietary intake. Body condition score (BCS), BW, food intake (FI), and hematological and select biochemical parameters were measured at various timepoints over a 16-week feeding period. All data were analyzed with ANOVA using PROC GLIMMIX of SAS. No biologically significant differences were seen between treatment groups for BW, BCS, FI, hematological and biochemical results. Statistically significant differences noted among some serum biochemical results were considered small and due to normal biological variation. These results support a conclusion that camelina oil is safe for use in canine nutrition.

Dynamic time history analysis is a powerful and effective method to study the seismic response of tunnels, the dynamic time history to analyze the seismic response of the tunnel in the typical subway in this paper. The analysis results show that the overall levelling of the tunnel will not affect the tunnel too much, and the seismic response of the tunnel is mainly related to the relative displacement of the ground around the tunnel. The analysis results show that the internal force of the tunnel and the tunnel inclination have a good linear relationship, and the tunnel inclination can be used to measure the magnitude of the seismic response of the tunnel.

The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.

Mycobacterium ulcerans is the causative agent of the Buruli ulcer, also known, in Australia, as Daintree ulcer or Bairnsdale ulcer. This destructive skin disease is characterized by extensive and painless necrosis of the skin and soft tissue with the formation of large ulcers, commonly on the leg or arm. To date, 33 countries with tropical, subtropical and temperate climates in Africa, the Americas, Asia and the Western Pacific have reported cases of Buruli Ulcer. The disease is rarely fatal, although it may lead to permanent disability and/ or disfigurement if not treated appropriately or in time. It is the third most common mycobacterial infection in the world after tuberculosis and leprosy. The precise mode of transmission of M. ulcerans is yet to be elucidated. Nevertheless, it is possible that the mode of transmission varies with different geographical areas and epidemiological settings. The knowledge about the possible route of transmission and potential animal reservoir of M. ulcerans is poorly understood and still remains patchy. We conducted a systematic review with selected key words on PubMed and INFORMIT databases to aggregate available published data on animal reservoirs of M. ulcerans. After certain inclusion and exclusion criteria, a total of 17 studies were included in the review. A variety of animals, e.g rodents, shrews, possums (ringtail and brush tail), horses, dogs, alpacas, koalas and Indian flap-shelled turtles have been recorded as being infected with M. ulcerans around the world. The majority of studies included in this review identified animal reservoirs, either aquatic or terrestrial, as predisposing for the emergence and reemergence of M. ulcerans infection. Taken together, the selected studies in this systematic review and discussed so far, it is clear that exotic wildlife, aquatic animals and native mammals play a significant role as reservoirs for M. ulcerans.

This study tries to focusing on applying information communication technology for economic importance of Mid Oil Company (MDOC), which is among contemporary oil companies in Iraq. Since ICT forms a significant aspect of achieving organizational economic objectives, most of public and private bodies seek to utilize ICT tool and techniques to improve work efficiencies. The emerging growth in ICT has made it process and service automation possible in managing organizational activities. To determine this effect of ICT on organizations, this study formulated statistical research model at MDOC through using fifteen questionnaires, which were distributed on three axes. The outcome of the questionnaire analysis revealed that there is inadequate comprehensive infrastructure to suitably support ICT within the selected organization management. In addition, it revealed that there are no ideal standards to maintain and sustain internet networks. Based on these revelations, the study presents recommendation for the adoption of ICT with the aim of minimizing cost, enhancing communication and managing infrastructure. Also recommends the need to support IT department within an organization, with essential equipment, in terms of man and machine, for better efficiency to employ the key of ICT Impact in Iraqi governmental oil companies.

Within the Active Living and Well-Being Project (RRP3), funded by the Republic of Slovenia and the European Regional Development Fund Investing in Your Future programme, we aim to develop different approaches and prototypes to provide ICT solutions for the family in order to connect its members, communicate, promote quality family time, active life, a health-friendly lifestyle and well-being, and integrate various sensor and user-based data sources into a smart city ecosystem platform. A mixed methodology, combined qualitative and quantitative approaches, was selected to conduct a study. An online survey with a structured questionnaire as well as semi-structured interviews were performed. Through the analysis of the results we tried to establish a family-centred design approach that would be inclusive as much as possible, creating benefits for all generations in order to develop interactive prototypes that would allow us to further test and verify different use-case scenarios.

Bridges enable communications and transportation of goods nationally and internationally, underpinning economic and social activities, thus they are pylons of our prosperity and mobility. Bridges worldwide are constantly subjected to physical wear, ageing, deterioration, hazards, environmental influences, and increased loading. Loss of performance and functionality of bridge structures would have a crucial impact on overall infrastructural resilience and would cause significant negative economic and social consequences. Monitoring their behaviour for different loading conditions relies on accurate estimations of the stress-strain state of various critical components and remaining capacities. These activities are of high importance for better planning lifespan prolongation, that is the extension of their service life and prevention of unforeseen collapses, in line with sustainability principles of well-informed maintenance. In many cases, access to the structure is limited or even impossible, which causes the need for the deployment of remote and contactless methods. One such innovative technique, which has recently attracted attention in scientific and practical applications is the digital image correlation (DIC). DIC is a contactless approach applicable for long-term measurements, which enables obtaining the full field of strains and deformations. Although the DIC approach has been widely used in world engineering practice for monitoring bridges and has proved to be a reliable and accurate method, there is a lack of systematic integral review on previous practical applications, revealing limitations and perspectives. This is the main motivation and novelty of this study, which will describe selected case studies, in which DIC was used on real full-scale bridge structures and propose improvements for the method.

The intestinal microbial community of aquatic animals is closely related to the environment and thus affects the health of aquatic animals. Here we investigated annual variation of intestinal bacteria community structures of Ruditapes philippinarum cultured using two different methods, bottom sown and raft hanging. Bacterial diversity of seawater and sediment in different seasons was examined as well. Correlation between R. philippinarum intestinal bacteria community structures and environmental factors was analyzed. The results showed that in the two aquculture areas where R. philippinarum was differentially cultured, bacteria community structure of seawater and sediment both altered with seasons. However, neither seasonal changes nor difference in culture methods could significantly affect the intestinal bacteria community structures of R. philippinarum. Additionally, in terms of the alpha diversity of intestinal bacteria communities, there was no significant difference in R. philippinarum cultured using the two methods. For benthic cultured clams, alpha diversity of the intestinal bacterial communities was often higher than that of the environmental bacterial communities. For raft hanging cultured calms, Alpha diversity of the intestinal bacterial communities was normally comparable with that of the environmental counterparts. Beta diversity analysis showed that the intestinal bacterial community structure of R. philippinarum was mainly determined by both deterministic and stochastic processes. Correlation analysis showed that the intestinal bacterial community structures of R. philippinarum were determined by a variety of environmental factors. For clams collected from the benthic culture area, the intestinal bacterial structure was more correlated with the physicochemical properties of sediment in comparing with those of seawater. For clams collected from the raft-culture area, the intestinal bacterial structure was mainly determined by the phsicochemical characteristics of seawater. This study helps us to better understand the bacterial community structure in complex aquaculture ecosystems, providing a reference for healthy shellfish aquaculture and ecosystem protection in aquaculture area.

The application of a commonly used computer algorithm based on the group-additivity method for the calculation of the liquid viscosity coefficient at 292.15K and the activity coefficient at infinite dilution in water at 298.15K of organic molecules is presented. The method is based on the complete breakdown of the molecules into their constituting atoms, further subdividing them by their immediate neighbourhood. A fast Gauss-Seidel fitting method using experimental data from literature is applied for the calculation of the atom groups’ contributions. Plausibility tests have been carried out on each of the calculations using a 10-fold cross-validation procedure which confirms the excellent predictive quality of the method. The goodness of fit (Q²) and the standard deviation (σ) of the cross-validation calculations for the viscosity coefficient, expressed as log(η), was 0.9728 and 0.11, respectively, for 413 test molecules, and for the activity coefficient log(γ)^∞ the corresponding values were 0.9736 and 0.31, respectively, for 621 test compounds. The present approach has proven its versatility in that it enabled at once the evaluation of the liquid viscosity of normal organic compounds as well as of ionic liquids.

The COVID-19 pandemic crisis has brought about unprecedented economic and social consequences worldwide. The implementation of isolation measures, including national and international travel restrictions, significantly affected contact-intensive sectors such as tourism. During this lockdown period, Information and Communication Technology (ICT) was crucial in maintaining connectivity and enabling remote activities. Governments across the world implemented discretionary measures to mitigate the crisis's adverse effects on economic activity. This paper aims to analyze whether the level of ICT adoption and the importance of tourism influence the fiscal policy efforts pursued by governments. Based on the results of a linear regression analysis for 154 countries, the findings suggest that in countries with higher international tourism receipts, the governments had to promote higher fiscal stimulus. At the same time, ICT development diminished the efforts of the fiscal policy response to the crisis since it facilitated economic resilience. The findings of this study can contribute to understanding how governments responded to the pandemic crisis and the factors that influenced their fiscal policy decisions.

Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications, especially in crop monitoring and disaster warning. Evaluating the dependability of those products before they can be used on a large scale is crucial. In this study, we assessed the level 2 (L2) SM product from the Chinese Fengyun-3C (FY-3C) radiometer against in situ measurements collected from the Chinese Automatic Soil Moisture Observation Stations (CASMOS) during a one-year period from January 1 to December 31, 2016 in Henan, which is an agricultural province in China. Four statistical parameters were used to evaluate the products’ reliability: mean difference, root-mean-square error (RMSE), unbiased RMSE (ubRMSE), and the correlation coefficient. These statistical indicators revealed that the FY-3C L2 SM product generally did not agree with the in situ SM data from CASMOS. The time-series analysis further indicated that the correlations and estimated error were highly related to the growing periods of the crops in our study area. FY-3C L2 SM data tended to overestimate soil moisture during May, August, and September, when the crops reach their maximum vegetation density, and tended to underestimate the soil moisture content during the rest of the year. The averaged correlation coefficient between FY-3C SM and the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index was 0.55, which demonstrates that the vegetation water content of the crops considerably influences the SM product. To improve the accuracy of the FY-3C SM product, an improved algorithm that can filter out the influences of the crops should be applied in the future.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

There are many uncertainties and risks in residential electricity consumption during the economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—are important to the sustainable development of electric power industry. Using panel data from 30 provinces for the 1995-2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions.” Robust tests of different segment specifications and regression methods are performed to ensure the conservatism of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. And government should emphasize electricity conservation in industrial sector rather than in residential sector.

The domain of Information and Communication Technology (ICT) education has garnered significant consideration in recent times. However, several challenges are inherent to this area of study, including monetary expense, temporal factors, pedagogical environment, teacher training programs, incentive, syllabus design, and health-related concerns. This paper presents an analysis of the difficulties encountered in the realm of ICT education in Japan, taking into account ten different perspectives.

We suppose that a Cooper pair (CP) will experience a damping force exerted by the condensed matter. A Langevin equation of a CP in two dimensional condensed matter is established. Following a method similar to Nelson's stochastic mechanics, generalized Schr\"{o}dinger equation of a CP in condensed matter is derived. If the CPs move with a constant velocity, then the corresponding direct current (DC) electrical conductivity can be calculated. Therefore, a Drude like formula of resistivity of CPs is derived. We suppose that the damping coefficient of CPs in two dimensional cuprate superconductors is a linear function of temperature. Then the resistivity and scattering rate of CPs turn out to be also linear-in-temperature. The origin of linear-in-temperature resistivity and Planckian dissipation in cuprate superconductors may be the linear temperature dependence of the damping coefficient of CPs.

The layered oxyselenide BiCuSeO has garnered significant interest because of its ability to exhibit low thermal conductivity and a high Seebeck coefficient. This study involved the preparation of Bi1−xNaxCuSeO1−xFx(x=0, 0.05, 0.10, 0.15, and 0.20) ceramics through the processes of high energy ball milling and cold isostatic pressing. A systematic study was conducted to investigate the impact of co−doping Na/F on the thermoelectric performance of BiCuSeO ceramics. Replacing Bi3+ with Na+ results in the introduction of a considerable amount of holes, leading to a notable enhancement in the electrical conductivity and power factor. The conductivity was significantly increased from 9.10 S cm−1 in the pure BiCuSeO to 94.5 S cm−1 in Bi0.85Na0.15CuSeO0.85F0.15 at 323 K. At 823 K, the power factor of the Bi0.85Na0.15CuSeO0.85F0.15 sample achieved 44.8×10−5 W/ m K2. Moreover, the Bi1−xNaxCuSeO1−xFx ceramics exhibit a minimum thermal conductivity of 0.43 W m−1 K−1. As a result, the Bi0.85Na0.15CuSeO0.85F0.15 sample achieves a maximum ZT value of 0.78, which is 7.09 times greater than that of the pure BiCuSeO sample (0.11) .

Background Community infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased rapidly since the emergence of the Omicron strain. During the eighth and ninth pandemic waves—when movement restrictions in the community were eased—the all-case registration system was changed, and the actual status of infection became uncertain. Methods We conducted regular rapid antigen tests (R-RAT) once or twice a week to examine the actual state of coronavirus disease (COVID-19) diagnosis among healthcare employees. Results Overall, 320 (1.42/day) and 299 (1.76/day) employees were infected in the eighth and ninth pandemic waves. During both periods, 59/263 doctors (22.4%), 335/806 nurses (41.6%), 92/194 administrative employees (47.4%), and 129/218 clinical laboratory technicians (59.2%) were infected. In the eighth wave, 56 of 195 employees were infected through close contact; in the ninth wave, 26 of 62 employees were infected. No significant difference was observed in the number of vaccinations between infected and non-infected employees. The positivity rate of R-RAT was 0.41% and 0.45% in the eighth and ninth waves. R-RAT detected infection in 212 and 229 employees during the eighth and ninth waves, respectively; the ratio of R-RAT-detected positive employees to those who reported infection was significantly higher during the ninth wave (odds ratio: 1.67, 95% confidence interval: 1.17–2.37, p

In this paper, we compile the fractional power series method and the Laplace transform to design a new algorithm for solving the fractional Volterra integro-differential equation. For that, we assume the Laplace power series (LPS) solution in terms of power q=1m,m∈Z+, where the fractional derivative of order α=qγ for which γ∈Z+. This assumption will help us to write the integral, the kernel, and the nonhomogeneous terms as a LPS with the same power. The recurrence relations for finding the series coefficients can be constructed using this form. To demonstrate the algorithm's accuracy, the residual error is defined and calculated for several values of the fractional derivative. Two strongly nonlinear examples are discussed to provide the efficiency of the algorithm. The algorithm gains powerful results for this kind of problem. Under Caputo meaning the obtained results are illustrated numerically, and graphically. Geometrically, the behavior of the solution declares that the changing of the fractional derivative parameter values' in their domain alters the style of the attained solution in a symmetrical meaning and fully coinciding to the ordinary derivative value'. From these simulations, the results report that the recommended novel algorithm is a straightforward, accurate, and superb tool to generate analytic-approximate solutions for Integral, and integro-differental equations of fractional order.

The evolution towards Industry 4.0 is driving the need for innovative solutions in the area of network management, considering the complex, dynamic and heterogeneous nature of ICT supply chains. To this end, Intent-Based networking (IBN) which is already proven to evolve how network management is driven today, can be implemented as a solution to facilitate the management of large ICT supply chains. In this paper, we first present a comparison of the main architectural components of typical IBN systems and, then, we study the key engineering requirements when integrating IBN with ICT supply chain network systems while considering AI methods. We also propose a general architecture design that enables intent translation of ICT supply chain specifications into lower level policies, to finally show an example of how the access control is performed in a modelled ICT supply chain system.

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

For a nonzero normed linear space X‎, ‎we will define some different classes of fuzzy norms on X generated by linear and bounded linear functionals‎. ‎Also separate continuity of the elements of each class are investigated‎. ‎The aim of this research is to introduce a source of examples and counterexamples in the field of fuzzy normed spaces‎.

Observed ENSO statistics exhibits a non-gaussian behavior, which is indicative of the presence of nonlinear processes. In this paper we use the Recharge Oscillator model (ROM), a largely used Low-Order Model (LOM) of ENSO, as well as methodologies borrowed from the field of statistical mechanics to identify which aspects of the system may give rise to nonlinearities that are consistent with the observed ENSO statistics. In particular, we are interested in understanding whether the nonlinearities reside in the system dynamics or in the fast atmospheric forcing. Our results indicate that one important dynamical nonlinearity often introduced in the ROM cannot justify a non-gaussian system behavior, while the nonlinearity in the atmospheric forcing can instead produce a statistics similar to the observed. The implications of the non-Gaussian character of ENSO statistics for the frequency of extreme El Nino events is then examined.

This paper presents the results of a recent study that was conducted with a number of German municipalities/cities. Based on the obtained and briefly presented recommendations emerging from the study, the authors propose the concept of an Urban Data Space (UDS), which facilitates an eco-system for data exchange and added value creation thereby utilizing the various types of data within a smart city/municipality. Looking at an Urban Data Space from within a German context and considering the current situation and developments in German municipalities, this paper proposes a reasonable classification of urban data that allows to relate the various data types to legal aspects and to conduct solid considerations regarding technical implementation designs and decisions. Furthermore, the Urban Data Space is described/analyzed in detail, and relevant stakeholders are identified, as well as corresponding technical artifacts are introduced. The authors propose to setup Urban Data Spaces based on emerging standards from the area of ICT reference architectures for Smart Cities, such as DIN SPEC 91357 “Open Urban Platform” and EIP SCC. Thereby, the paper walks the reader through the construction of an UDS based on the above mentioned architectures and outlines all the goals, recommendations and potentials, which an Urban Data Space can reveal to a municipality/city.

This paper attempts to alter a prevailing assumption that buildings use energy to an understanding that in fact, people use energy. Therefore, to successfully accelerate the transition to a low-carbon society and economy more emphasis should be on motivating people and increasing their awareness by making them energy conscious building users and therefore active players in the energy transition process. In this context, this paper provides insights from the Horizon 2020 MOBISTYLE project. It demonstrates research and development approaches, highlights the main project objectives, and presents findings of an ethnographic (qualitative) study of users’ habits, practices, and needs. The aim of the project is to motivate behavioural change by raising consumer awareness through the provision of attractive personalized information on user’s energy use, indoor environment and health, all enabled by an integrated information and communication technology (ICT) service. In this context, the anthropological people-centred approach is integrated into the MOBISTYLE approach putting users at the centre of the ICT tools development process. The main quantitative objective of the project is a reduction of energy use for at least 16 % prompted by the provision of combined information and feedback systems on energy, indoor environmental quality (IEQ) and health. The most relevant motivational factors and key performance indicators (KPIs) for encouraging a more energy conscious and healthy lifestyle were defined by means of a people-centred approach, adopting anthropological inquiries in different settings. Information about users’ lifestyles and their needs was collected in focus groups with potential users in five case studies, located in different European Union (EU) countries. Behaviour change is achieved through awareness campaigns, which encourage users to be pro-active about their energy consumption and to simultaneously improve health and well-being.

Linear-width is a well-regarded width parameter in graph theory. The constructs of linear loose tangle and linear tangle present obstacles to attaining linear-width. In this succinct paper, our primary focus will be the exploration of maximal linear loose tangles.

This paper reports on in-depth qualitative interviews conducted with 69 disabled people in England and Scotland, and with 28 key informants from infrastructure organisations in the voluntary and statutory sectors, about the impact of COVID-19, and measures taken to control it. Participants were recruited through voluntary organisations. As with everyone, the Pandemic has had a huge impact: we discuss the dislocations it has caused in everyday life; the failures of social care; the use of new technologies; and participants’ view on leadership and communication. We conclude with suggestions for urgent short term and medium term responses, so that the United Kingdom and other countries can respond better to this and other pandemics, and build a more inclusive world.

Special machinery engineering is of great importance to the manufacturing industry and makes a comparatively large contribution to many economies. Digital transformation is already well advanced in many producing industries, and modern ICT technologies such as agents, service orientation, digital twins and artificial intelligence are being used with increasing success. In addition to improving specific product characteristics such as reliability or flexibility, the adoption of modern ICT technologies to ensure sustainability is being intensively discussed. So far, however, there has been little uptake of these technologies in the special machinery industry; sustainability receives little attention. This article examines in detail the reasons for and impediments to the adoption of modern ICT technologies based on a study among special machinery manufacturers. Observations of existing challenges were gathered during daily work, described in detail, and used to derive conclusions about causal barriers. From this, detailed requirements are derived to promote the adoption of modern ICT technologies in the special machinery engineering sector and, ultimately, to bring sustainability more into focus.

We investigate the human sustainability of ICT and management changes using a French linked employer-employee survey on organizational changes and computerization (COI). We approach the human sustainability of changes through the evolutions of work intensity, skill utilization and the subjective relationship to work. We compare in the private sector and the State civil service the impacts of ICT and management changes on the evolution of these three dimensions of work experience. We find that when ICT and management changes are intense, they are positively associated in the public sector with work intensification and new knowledge. In the private sector ICT and management changes increase the use of skills, but at a rate decreasing with their intensity and without favoring the accumulation of new knowledge. However, their impacts on the subjective relationship to work are much stronger, with public sector employees expressing discouragement as well as the feeling of an increased effort-reward imbalance when private sector employees become more committed. We tested that the self-selection of employees, the specific sources and paths of changes and the implementation of performance pay did not explain this divergence. We identify two partial explanations: one is related with employee turnover in the private sector, the other one with the role of trade unions. These results suggest that the human sustainability of ICT and management changes depends on their intensity and on how their implementation takes into account the institutional context of the organization.

The 2030 global agenda of the United Nations emphasizes peace, human rights, gender equality, partnership, and women's empowerment. It balances the social, economic, and environmental dimensions of sustainable development. The SDG framework was designed to be integrated and indivisible, making the interconnections of 17 Goals and 169 Sustainable Development Goals Targets (SDTs) more complex that need extensive and intensive investigative research. Recent studies have increased on the interrelationships of SDGs, but none of these have focused on integrating Climate Change (CC), Sustainable Forest Management (SFM), and Information and Communication Technology (ICT), also known as CSI Nexus. This study aims to investigate and identify the 169 SDTs linked to CC, SFM, and ICT and assesses the significance of the relationships between these variables. The alignment of SDTs to CSI Nexus was identified through clustering and mapping techniques. The result argued that 56 SDTs are directly connected within CC+SFM+ICT, 16 within CC+SFM, one within SFM+ICT, and 51 within ICT+CC. Our result suggests that CC is significantly associated with SFM; however, ICT has no significant association with CC and SFM. It further asserts that the ICT and SFM have minimal influence on the SDG 2030 framework. The proposed CSI Nexus and SDTs Integration Framework was a science-informed guide for priority-setting, policy coherence, and decision-making supporting the 2030 Sustainable Development Goals. This study does not include interactions, network analysis and visualization, simulations, and modeling between SDG targets.

The specific demands inherent to supply chains built upon large IoT systems, make a must the design of a coordinated framework for cyber resilience provisioning intended to guaranteeing trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure and heterogeneous ICT infrastructures. As such, the proposed solution is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability and mitigation strategies as well as security metrics and evidence-based security assurance. In this paper we present FISHY, as a preliminary designed architecture, designed to orchestrate both existing and beyond state-of-the-art security appliances in composed ICT scenarios and also leveraging capabilities of programmable network and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption as well as three real-world use cases where to strongly support the envisioned benefits of a FISHY adoption.

The utility of ICTs for providing market information to rural smallholder farmers is growing rapidly, and access to reliable information and sources is considered crucial for beneficial market interaction. This study explored critical factors contributing to usage of electronic sources for market information search among rural smallholder livestock farmers. Using data collected from 129 respondents through a non-random sampling technique; descriptive and regression analysis was applied to identify key factors responsible for their awareness and use of ICT-based market information sources. Level of education was found to be a driver of awareness of ICT-based sources, and use of these sources was influenced by farmer-specific characteristics such as household size, education, income, membership of cooperatives and herd-size. The key ICT tools used was radio and mobile phones, widely available in the study area. Identified constraints to use of these ICTs include cost and patchy network signals in some areas. Policy interventions to reduce cost of mobile phone services and expansion of base stations; including practical recommendations for improved programming in radio and television offerings, are considered indispensable for greater uptake of e-information sources among smallholder livestock farmers.

As known all physical properties of solids are described well by the system of quantum linear harmonic oscillators. It is shown in the present paper that the system consisting of classical linear harmonic oscillators having temperature dependent masses or (and) frequencies has the same partition function as the system consisting of quantum linear harmonic oscillators having temperature independent masses and frequencies while the means of the square displacements of the positions of the oscillators from their mean positions for the system consisting of classical linear harmonic oscillators having: the temperature dependent masses; temperature dependent frequencies; and temperature dependent masses and frequencies differ from each other and from that of the system consisting of quantum linear harmonic oscillators, and hence, the system consisting of classical linear harmonic oscillators describes well the thermodynamic properties of the system consisting of quantum linear harmonic oscillators and solids.

The objective of this paper is to investigate the debonding behavior of the interface between continuously and discontinuously fiber reinforced thermoplastics using the climbing drum peel test. The study emphasizes the importance of considering different climatic boundary conditions due to the properties of thermoplastics. Specimens with varying moisture contents are prepared and tested. It is observed that an increase in moisture content initially results in a higher fracture surface energy being required to separate the two materials, but a further increase results in a decrease of the required energy. The study presents an explanatory model of increasing plasticization of the polymer due to increased polymer chain mobility, which results in more deformation energy being required to propagate the crack. The experiment is also modeled numerically for the first time with cohesive surfaces, which successfully reproduces the force-displacement curve in the experiment.

The study explored the contribution of ICT-based information sources to market participation among smallholder livestock farmers. Use of ICTs is considered paramount for providing smallholder farmers with required market information, in order to reduce market asymmetries. A Double Hurdle regression was utilized to analyze data collected from 150 smallholder livestock farmers in the study area. The results show that while use of ICT-based market information sources significantly influenced market participation, the effect of using ICT-based information sources on intensity of market participation was not significant. Other variables shown to influence both market participation and the intensity of market participation were age, additional income and membership of farmer cooperatives. This suggests the need to also consider other associated factors in the application of interventions which utilize ICT-based information sources in achieving planned market interventions.