Unmanned aerial vehicles (UAVs) have increasingly become integral to multi-access edge computing (MEC) due to their flexibility and cost-effectiveness, especially in the B5G and 6G eras. This paper aims to enhance the Quality of Experience (QoE) in large-scale UAV-MEC networks by minimizing the shrinkage ratio through optimal decision-making in computation mode selection for each user device (UD), UAV flight trajectory, bandwidth allocation, and computing resource allocation at edge servers. However, the interdependencies among UAV trajectory, binary task offloading mode, and computing/network resource allocation across numerous IoT nodes pose significant challenges. To address these challenges, we formulate the shrinkage ratio minimization problem as a mixed-integer nonlinear programming (MINLP) problem and propose a two-tier optimization strategy. To reduce the scale of the optimization problem, we first design a low-complexity UAV partition coverage algorithm based on the Welzl method and determine the UAV flight trajectory by solving a Traveling Salesman Problem (TSP). Subsequently, we develop a coordinate descent (CD) based method and an alternating direction method of multipliers (ADMM) based method for network bandwidth and computing resource allocation in the MEC system. The CD-based method is simple to implement and has a low computational complexity, while the ADMM-based method can further enhance the optimization result through joint optimization. Extensive simulations demonstrate that our proposed algorithms perform well in large-scale edge networks and outperform other representative benchmark methods.

Spectral photon counting cone-beam CT imaging is challenged by individual pixel response behaviour, which leads to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform post-processing ring artefact correction of sinogram data or scan reconstructions, without taking the pixel response explicitly into account. Here we present a novel post-processing method (DAC-shifting), which explicitly measures the current pixel response using flat field images, and subsequently corrects the projection data. The DAC-shifting method was evaluated with a repeat series of spectral photon counting imaging (Medipix3) of a phantom with different density inserts, and in iodine K-edge imaging. The method was also compared against PMMA based STC. The DAC-shifting method was shown to be effective in correcting individual pixel response, and was robust against detector instability. On the contrary, STC correction showed varying results, which was almost as good as DAC-shifting when data was acquired just after STC calibration, but worse with larger time differences. In K-edge imaging, DAC-shifting provides a sharper attenuation peak, and more uniform CT values, which is expected to benefit iodine concentration quantification.

A Digital Twin (DT) refers to a virtual representation or digital replica of a physical object, system, process, or entity. This concept involves creating a detailed, real-time digital counterpart that mimics the behavior, characteristics, and attributes of its physical counterpart. DTs have the potential to improve efficiency, reduce costs, and enhance decision-making by providing a detailed, real-time understanding of the physical systems they represent. While this technology is finding application in numerous fields, such as energy, healthcare, transportation, it appears to be a key component of the digital transformation of industries. In this paper, we present the research results achieved by IoTwins, a European research project aimed at investigating opportunities and issues of adopting DTs in the fields of industrial manufacturing and facility management. Particularly, we discuss a DT model and a reference architecture for use by the research community to implement a platform for the development and deployment of industrial DTs in the cloud continuum. Guided by the devised architectures’ principles, we implemented an open platform and a development methodology to help companies build DT-based industrial applications and deploy them in the so-called Edge/Cloud continuum. To prove the research value and the usability of the implemented platform, we discuss a simple yet practical development use case.

The performance and lifespan of cutting tools are significantly influenced by their surface quality. The present report highlights recent advances in enhancing the surface characteristics of tungsten carbide and high-speed steel cutting tools using a novel micro-machining technique for polishing and edge-honing. Notably, the main aim is to reduce the surface roughness while maintaining the hardness of the materials at an optimal level. By conducting a thorough analysis, of surfaces obtained with different techniques. It was that micro-machining method effectively decreased the surface roughness of the cutting tools, most effectively of the techniques investigated. Significantly, the surface roughness is reduced from an initial measurement of 400 nm to an impressive value of 60 nm. No significant change in hardness was observed, which guarantees the maintenance of the mechanical properties of the cutting tools. This analysis enhances the comprehension of surface enhancement methodologies for cutting tools through the presentation of these findings. The observed decrease in surface roughness, along with the consistent hardness, exhibits potential for improving tool performance. These enhancements possess the capacity to optimise manufacturing processes, increase tool reliability, and minimise waste generation.

We have investigated the interfacial dislocations in InxGa1–xN/GaN (0 ≤ x ≤ 0.20) heterostructures using diffraction contrast analysis in a transmission electron microscopy. The analysis indicate that the structural properties of the interface dislocations depend on the indium composition. For lower indium composition up to x = 0.09, we observed that the screw-type dislocations and dislocation half loops occurred at the interface even though the former do not contributes toward elastic relaxation of the misfit strain in the InGaN layer. With the increase of indium composition (0.13 ≤ x ≤ 0.17), in addition to the network of screw-type dislocations, edge-type misfit dislocations were found generated with their density gradually increasing. For higher indium composition (0.18 ≤ x ≤ 0.20), all the interfacial dislocations are transformed into a network of straight misfit dislocations along the <10-10> directions leading to partially relaxation of the InGaN epilayer. The presence of dislocation half loops may be explained by slip on the basal plane, the formation of misfit dislocations are attributed to punch-out mechanism.

The non-contact patient monitoring paradigm moves patient care into their homes and enables long-term patient studies. The challenge, however, is to make the system non-intrusive, privacy-preserving, and low-cost. To this end, we describe an open-source edge computing and ambient data capture system, developed using low-cost and readily available hardware. We describe five applications of our ambient data capture system. Namely: (a) Estimating occupancy and human activity phenotyping; (b) Medical equipment alarm classification; (c) Geolocation of humans in a built environment; (d) Ambient light logging; and (e) Ambient temperature and humidity logging. We obtained an accuracy of 94% for estimating occupancy from video. We stress-tested the alarm note classification in the absence and presence of speech and obtained micro averaged F1 scores of 0.98 and 0.93, respectively. The geolocation tracking provided a room-level accuracy of 98.7%. The root mean square error in the temperature sensor validation task was 0.3°C and for the humidity sensor, it was 1% Relative Humidity. The low-cost edge computing system presented here demonstrated the ability to capture and analyze a wide range of activities in a privacy-preserving manner in clinical and home environments and is able to provide key insights into the healthcare practices and patient behaviors.

The US pacific northwest recorded its highest temperature in late June 2021. The three-day stretch of scorching heat had a devastating effect on not only the residents of the state, but also on the crops thus impacting the food supply-chain. It is forecasted that streaks of 100-degree temperatures will become common. Farmers will have to adapt to the changing landscape to preserve their crop yield and profitability. A research collaborative consisting of researchers and academicians in Eastern Washington led by a pioneering startup has setup a 16.9-acre Honeycrisp Apple Smart Orchard in Grandview, WA as a laboratory to study the environmental and plant growth factors in real-time using modern computational tools and techniques like IoT (Internet of Things), Edge and Cloud Computing, and Drone and LiDAR (Light Detection and Ranging) imaging. The computational analysis is used to develop guidelines for precision agriculture for orchard blocks to address plant growth issues scientifically and in a timely fashion. The analysis also helps in creating risk-mitigation strategies for severe weather events while helping prepare farmers to maximize crop yield and profitability per acre. I was fortunate to gain access to the terabytes of farm data related to the weather, soil, water, tree, and canopy health, to analyze and formulate recommendations for the farmers that can be adopted nationwide for different crops and weather conditions. This paper discusses the different streams of farm data that were analyzed (ex. soil moisture, soil water potential, and sap flow) and the development of the framework to use data to convert insights into actionable steps. For example, the use of sensors can inform a farmer that their level of soil water potential is below threshold in a specific patch of the orchard, prompting them to turn on irrigation for the patch instead of the whole orchard. I estimate that using an IoT-sensor-based decision framework discussed in this paper, growers can save up to 55% of their water costs for the season. Using these insights, farmers can better manage their irrigation resources and labor, thus maximizing their crop yield and profits.

The consequences of manipulations in structure and amino acid composition of native cyclolinopeptide A (CLA) from linen seeds and its linear precursor on their biological activities and mechanisms of action are reviewed. The modifications included truncation of the peptide chain, replacement of amino acid residues with proteinogenic or non-proteinogenic ones, modifications of peptide bond, and others. The studies revealed changes in the immunosuppressive potency of these analogs investigated in a number of in vitro and in vivo experimental models, predominantly in rodents, as well as differences in their postulated mechanism of action. The modified peptides were compared with cyclosporine A and parent CLA. Some of the synthesized and investigated peptides show potential therapeutic usefulness.

Climate change and environmental degradation are major threats to sustainable agricultural development in Southern Africa. Thus, the concept of sustainable intensification (SI) i.e. getting more output from less input using certain practices such as agroforestry, organic fertilizer, sustainable water management etc. has become an important topic among researchers and policy makers in the region in the last three decades. A comprehensive review of literatures on the adoption of SI in the region identify nine relevant drivers of adoption of SI among (smallholder) farmers. These drivers include (i) age, (ii) size of arable land, (iii) education, (iv) extension services, (v) gender, (vi) household size, (vii) income, (viii) membership in farming organization and (ix) access to credit. We present the results of a meta-analysis of 21 papers on the impact of these determinants on SI adoption among (smallholder) farmers in Southern African Development Community (SADC) using random-effects estimation techniques for the true effect size. While our result suggests that variables such as extension services, education, age, and household size may influence the adoption of SI in SADC, factors such as access to credit is also of great importance. Decision-makers should therefore concentrate efforts on these factors in promoting SI across the SADC. This includes increasing the efficiency of public extension service as well as involvement of private sector in extension service. Furthermore, both public and private agriculture financing models should consider sustainability indicators in their assessment process.

The COVID-19 pandemic has highlighted the need for a robust medical infrastructure and crisis management strategy as part of smart-city applications, with technology playing a crucial role. The Internet of Things (IoT) has emerged as a promising solution, leveraging sensor arrays, wireless communication networks, and artificial intelligence (AI)-driven decision-making. Advancements in Edge Computing (EC), Deep Learning (DL), and Deep Transfer Learning (DTL) have made IoT more effective in healthcare and pandemic-resilient infrastructure. When combined with medically oriented IoT setups, DL-architectures are suitable for integrating into pandemic-compliant medical infrastructure. The development of intelligent pandemic-compliant infrastructure requires combining IoT, edge and cloud computing, image processing, and AI tools to monitor adherence to social distancing norms, mask-wearing protocols, and contact tracing. The proliferation of 5G wireless communication has enabled ultra-wide broadband wireless communication, with high reliability and low latency, thereby enabling seamless medical support as part of smart-city applications. Such set-ups are designed to be ever-ready to deal with virus-triggered pandemic-like medical emergencies. This study presents the design of a pandemic-compliant mechanism leveraging IoT optimized for healthcare applications, edge- and cloud-computing frameworks, and a suite of DL-tools. The framework uses a composite attention-driven framework incorporating various DL-pre-trained models (DPTM) for protocol adherence and contact tracing. When connected to public networks, it can detect specific cyber-attacks. The results confirm the effectiveness of the proposed methodologies.

Wearable assistant devices play an important role in daily life for people with disabilities. Those who are hearing impaired may face dangers while walking or driving on the road. The major danger is their inability to hear warning sounds from cars or ambulances. Thus, the goal of this study is to develop a wearable assistant device for the hearing impaired to recognize emergency vehicle sirens on the road using edge computing. An EfficientNet-based fuzzy rank-based ensemble model was proposed to classify seven audio sounds, including human vocalizations and emergency vehicle sirens. This model was embedded in an Arduino Nano 33 BLE Sense development board. The audio files were respectively obtained from the CREMA-D dataset and Large Scale Audio dataset of emergency vehicle sirens on the road, with a total number of 8756 files. The seven audio sounds included neutral vocalization, anger vocalization, fear vocalization, happy vocalization, car horn sound, siren sound, and ambulance siren sound. The audio signal was converted into a spectrogram by the short-time Fourier transform as the feature. When one of the car horns, sirens, or ambulance sirens was detected, the wearable assistant device presented alarms through vibration and messages on the OLED panel. The performances of the EfficientNet-based fuzzy rank-based ensemble model in offline computing achieved an accuracy of 97.1%, precision of 97.79%, sensitivity of 96.8%, and specificity of 97.04%. In edge computing, the results were an accuracy of 95.2%, precision of 93.2%, sensitivity of 95.3%, and specificity of 95.1%. Thus, the proposed wearable assistant device has the potential benefit of helping the hearing impaired avoid traffic accidents.

As an emerging network paradigm, Space-Air-Ground integrated networks (SAGIN) has attracted the attentions from academia and industry. That is because SAGIN can implement seamless global coverage and connections among electronic devices in space, air, and ground spaces. Additionally, the shortages of computing and storage resources in mobile devices greatly affect the quality of experiences for intelligent applications. Hence, we devise to integrate SAGIN as an abundant resource pool into mobile edge computing environments (MEC). To facilitate efficient processing, we need to solve the optimal task offloading decisions. Different from the existing MEC task offloading solutions, we have to face some new challenges, such as the fluctuation of processing capability for an edge computing node, the uncertainty of the transmission latency caused by the heterogeneous network protocols, the uncertain amount of uploaded tasks during a period, and so on. In this paper, we firstly describe a task offloading decision problem in new challenge environments. But, we cannot use the standard robust optimization and stochastic optimization methods to obtain the optimal result under the uncertain network environments. In this paper, we propose the condition value at risk-aware distributionally robust optimization algorithm, named as CVAR-DRO, to solve the task offloading decision problem. The proposed CVAR-DRO method combines the distributionally robust optimization and the condition value at risk model for solving the optimal result. And then, We have evaluated our approach in simulation SAGIN environments with the confidence interval, the number of mobile task-offloading and the various parameters. We compare our proposed CVAR-DRO algorithm with the state-of-the-art algorithms, such as the standard robust optimization algorithm, the stochastic optimization algorithm, the DRO algorithm, and the brute algorithm. The experimental results show that CVAR-DRO can get a sub-optimal mobile task-offloading decision. Overall, CVAR-DRO is more robust than others to the new challenges mentioned above in SAGIN.

The standard edge crush test (ECT) allows to determine the crushing strength of the corrugated cardboard. Unfortunately, this test cannot be used to estimate the compressive stiffness, which is an equally important parameter. It is because, any attempt to determine this parameter using current lab equipment quickly ends in a fiasco. The biggest obstacle is obtaining a reliable measurement of displacements and strains in the corrugated cardboard sample. In this paper, we present a method that not only allows to reliably identify the stiffness in the loaded direction of orthotropy in the corrugated board sample, but also the full orthotropic material stiffness matrix. The proposed method uses two samples: (a) traditional, cut crosswise to the wave direction of the corrugated core, and (b) cut at an angle of 45 degrees. Additionally, in both cases, an optical system with digital image correlation (DIC) is used to measure the displacements and strains on the outer surface of samples. The use of a non-contact measuring system allows to avoid using the measurement of displacements from the crosshead, which is burdened with a large error. Apart from the new experimental configuration, the article also proposes a simple algorithm to quickly characterize all sought stiffness parameters. The obtained results are finally compared with the results obtained in the homogenization procedure of the cross-section of the corrugated board. The results were consistent in both cases.

This paper presents an Edge-based color image segmentation derived from the method of Particle Motion in a Vector Image Fields (PMVIF) that could previously be applied only to monochrome images. Instead of using an edge vector field derived from a gradient vector field and a normal compressive vector field derived from a Laplacian-gradient vector field, two novel orthogonal vector fields, directly computed from a color image, one parallel and another orthogonal to the edges, were used in the model to force a particle to move along the object edges. The normal compressive vector field is derived from the center-to-centroid vectors of local color distance images. Next, the edge vector field is derived by taking the normal compressive vector field, multiplied by differences of auxiliary image pixels to obtain a vector field analogous to a Hamiltonian gradient vector field. Using the PASCAL Visual Object Classes Challenge 2012 (VOC2012) and the Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500), the benchmark score of the proposed method is provided in comparison with those of the traditional PMVIF, Watershed, SLIC, K-means, Mean shift, and JSEG. The proposed method yields better RI, GCE, NVI, BDE, Dice coefficients, faster computation time, and noise resistance.

In this work, the problem is considered for eliminating a non-uniform rectilinear smearing of an image by mathematical and computer-based way, for example, a picture of several cars taken with a fixed camera and moving with different speeds. The problem is described by a set of 1-dimensional Fredholm integral equations (IEs) of the first kind of convolution type with a 1-dimensional point spread function (PSF) at uniform smearing and by a set of new 1-dimensional IEs of a general type (not convolution type) with a 2-dimensional PSF at non-uniform smearing. The problem is also described by one 2-dimensional IE of convolution type with a 2-dimensional PSF at uniform smearing and by a new 2-dimensional IE of a general type with a 4-dimensional PSF at non-uniform smearing. The problem for solving Fredholm IE of the first kind is ill-posed (unstable). Therefore, IEs of convolution type are solved by the Fourier transform (FT) method and Tikhonov's regularization (TR), and IEs of general type are solved by the quadrature/cubature and TR methods. Moreover, the magnitude of the image smear Δ is determined by the original “spectral method”, which increases the accuracy of image restoration. It is shown that the use of a set of 1-dimensional IEs is preferable to one 2-dimensional IE in the case of non-uniform smearing. In the inverse problem (image restoration), the Gibbs effect (the effect of false waves) in the image may occur. It can be edge or inner. The edge effect is well suppressed by the proposed technique “diffusing the edges". In the case of an inner effect, it is eliminated with difficulty, but the image smearing itself plays the role of diffusing and suppresses the inner Gibbs effect to a large extent. It is shown (in the presence of impulse noise in an image) that the well-known Tukey median filter can distort the image itself, and the Gonzalez adaptive filter also distorts the image (but to a lesser extent). We propose a modified adaptive filter. A software package was developed in MatLab and illustrative calculations are performed.

The moiré effect is typically observed in regular periodic structures and sometimes in random (aperiodic) structures. However, only regular structures were used in measurements. In this study, we propose structures whose images are not regular but not completely random, and resemble a series of lines, such as a grid of dotted lines or a matrix of dots. A relatively simple image processing technique can make the moiré effect in such structures very similar to regular structures. We demonstrated using five different structures (including text) in measurements, with similar results.

Background: Studying patients carrying identical by descent (IBD) pathogenic gene variants allows to control for the disease-causing genetic background and to more accurately document the impact of modifiers. Familial hypercholesterolemia (FH) is characterized by elevated LDL-c levels, premature atherosclerosis and is often caused by defects in the LDLR gene. There is a high prevalence of FH in French Canada carry IBD FH-causing due to a founder effect from France in the 17th Century. Several FH patients currently living in French Canada (founder population) and in France (colonizing population) carry IBD FH-causing variants. The expression of FH is affected by environmental and genetic modifiers and patients with IBD variants may present different characteristics. Methods: In this study, we compared FH clinical expression patients carrying IBD LDLR pathogenic variants living in France or Canada. Four IBD variants, namely c.259T>G p.(Trp87Gly); c.2000G>A p.(Cys667Tyr); c.682G>A p.(Glu228Lys); and c.1048C>T p.(Arg350*) were selected. Untreated plasma lipid profiles, APOE genotype, cardiovascular risk factors and occurrence of symptomatic ASCVD were compared in 105 adult carriers (30 from France and 75 from French Canada). Results: All parameters were similar between the two populations, except for untreated total cholesterol (10.14 ± 1.89 mmol/L vs 8.65 ± 1.84 mmol/L, p=0.0006) and LDL-c concentrations (7.94 ± 1.86 mmol/L vs 6.93 ± 1.78 mmol/L, p=0.016) that were significantly higher in FH patients living in France, a trend that was observed in all studied LDLR variants. Conclusion: This study illustrates that FH patients sharing IBD pathogenic LDLR variants that have evolved in different geographic, cultural and socio-economic environments for hundreds of years, differ in term of cholesterol levels highlighting the importance of better understanding the interplay between genetic and environmental modulators of FH expression.

The primary aim of this study was to investigate the variations in cognitive load as self-efficacy gradually increases and examine the potential within-mediating effect of state anxiety between self-efficacy and cognitive load. The experiment manipulated the self-efficacy of 49 adult participants through the false feedback paradigm, employing a within-subject experimental design and using facial expression recognition as the experimental task. The data were analyzed using Hierarchical Linear Modeling. The results revealed that self-efficacy negatively predicted state anxiety and cognitive load, while state anxiety positively predicted cognitive load. Moreover, state anxiety played a complete mediating role at multiple levels in this process.

Background: In 2023, ChatGPT-4 has been impactful across several sectors including healthcare, where it aids in medical information analysis and education. Electronic Patient-Reported Outcomes (ePROs) play a crucial role in monitoring cancer patients’ post-treatment symptoms, enabling early in-terventions. However, managing the voluminous ePRO data presents significant challenges. This study assesses the feasibility of utilizing ChatGPT-4 for analyzing side effect data from ePROs. Methods: Thirty cancer patients were consecutively collected via a web-based ePRO platform, reporting side effects over 4 weeks. ChatGPT-4, simulating oncologists, dietitians, and nurses, analyzed this data and offered improvement suggestions, which were then reviewed by professionals in those fields. Results: Two oncologists, two dieticians and two nurses evaluated the AI’s performance across roles with 540 reviews. ChatGPT-4 excelled in data accuracy and completeness, and was noted for its empathy and support, enhancing communication and reducing caregiver stress. It was particularly effective as a dietician. Discussion: ChatGPT-4 shows promise in processing ePRO data with high accuracy, suggesting that AI can enhance clinical decision-making. Nevertheless, its limitations in emotional engagement highlight the need for AI to supplement, not replace, human care. Emphasizing the role of dietitians underscores the importance of nutritional advice in cancer care. Future studies will further explore the feasible application of AI and ePRO in cancer care clinical processes.

Although researchers have proposed various indentation size effect (ISE) models, these models often involve different form and number of parameters that can make our wonder which is the best in existed ISE models. Three types of ISE test data, namely, normal ISE, reverse ISE and transition of normal to reverse ISE, are used to evaluate the sixteen ISE models. The comparatively study indicates that H-J, N-G-Fs, N-G-H, N-G-A and N-G-Qs models can accurately predict the normal ISE. The reason for this is that the friction stress that is not related to dislocation activities or the indentation size effect of plastic zone has been introduced into these models. Therefore, these two factors should be considered in future ISE models. The sixteen ISE models are originally proposed to describe the normal ISE of different materials. However, to our surprise, some of these models are able to capture the reverse ISE and the transition of normal to reverse ISE of different materials. The determination coefficients (DC) of the sixteen ISE models are also determined for different materials. For reverse ISE, the highest DC value for NiCSi, TC4 and PED Ni are given by the EXP, N-G-Fs and N-G-A models, respectively. For the transition of normal to reverse ISE, the N-G-YC, N-G-Fs, and N-G-H models produce the maximum DC for ZrO2, Cu and Y2O3-ZrO2, respectively. Moreover, the mean DC of the N-G-Fs model is the maximum among the sixteen ISE models, followed by the N-G-H model, but they cannot accurately predict the reverse ISE. Therefore, the N-G-Fs and N-G-H models should be further modified to accurately predict the reverse ISE.

This investigation aimed to knowledge of the presence of Brucella spp .in the samples from Babylon province and the relationship with environmental factors. The seasonal collection of animal soil samples for various villages in the middle, south, and north of Babylon province, Hilla City, Iraq, with physicochemical parameters (air and soil temperature, pH, EC, TDS, salinity, TOC), as well as heavy metals (Fe, Cu, Cd, and Pb). The results showed the presence of Brucella species in some of soil samples and its percentage varies according to the four seasons, where the highest percentage of Brucella spp. was in summer season and the lowest in winter season and these percentages were related to seasonal environmental indicators. After sending the positive bacterial samples isolated from the soil for sequencing analysis, it was found that the bacterial samples isolated from the soil have new strains recorded in Genbank as following: five strains for Brucella intermedia and one strain for Brucella rhizosphaerae, Also, phylogenetic analysis was for the drawing of phylogenetic tree and the determination of phylogenetic relationship for Knowledge the degree of convergence between species and their source. Through our research, we concluded that proportion of Brucella spp. presence in summer was high and also environmental factors which included (Air and Soil temperature, pH, EC, TDS and Salinity) were high, except TOC was lower in summer season whereas heavy metals for Cu, Fe, Cd were lower in summer except Pb was high. This indicated that differences of seasons affect to Brucella ratio in soil. The findings of sequencing for the bacterial samples from soil demonstrated that B. intermedia was found in both the spring and fall seasons while B.rhizosphaerae found in the spring season , These types of Brucella had genetic variations. Also concluded that during phylogenetic analysis of the 16S rRNA sequences indicated that B.intermedia was nearest to Pakistan and other strain of B.intermedia was nearest to Russia while B.rhizosphaerae was nearest to Ukraine and Pakistan.

Road pavement monitoring represents the baseline to the pavement maintenance process. To quickly fix a damaged road, relevant authorities need a high-efficiency methodology that allows them to obtain data describing the current conditions of a network of roads. In urban areas, large-scale monitoring campaigns may be more expensive and not fast enough to describe how pavement degradation has evolved over time. Furthermore, at low speeds, many technologies are inadequate for monitoring the streets. In such a context, employing black box equipped vehicles to perform a routine inspection could be an excellent starting point. However, the vibration-based methodologies used to detect road anomalies are strongly affected by the speed of these vehicles. In this study, a statistical method was to analyze the effects of speed on road pavement conditions at different severity levels through the data recorded by taxi vehicles. Likewise introduced was a process that overcomes the speed effect when considering road surface conditions. The methodology proposed has succeeded in predicting the right damage severity level based on only two recorded parameters: speed and pavement deterioration index.

MicroRNAs are small ribonucleotides which act as key gene regulators. Their altered expression is often associated with onset and progression of several human diseases, including cancer. Given their potential use as biomarkers, there is a need to find detection methods of microRNAs suitable for use in clinical setting. Field Effect Transistor based biosensors (bioFETs) appear to be valid tools to detect microRNAs, since they may reliably quantitate the specific binding between the immobilized probe and free target in solution through an easily detectable electrical signal. We have investigated the detection of human microRNA 155 (miR-155) using an innovative cap-turing probe constituted by a synthetic peptide nucleic acid (PNA), which has the advantage to form a duplex even at ionic strengths approaching the physiological conditions. With the aim to develop an optimized BioFET setup, the interaction kinetics between miR-155 and the chosen PNA was preliminary investigated by Surface Plasmon Resonance (SPR). By exploiting both these results and our custom-made bioFET system, we were able to attain a low-cost, real-time, label-free, highly specific detection of miR-155 in the nano-molar range.

The sulfated polysaccharide (SP) was extracted from Gracilaria edulis and tested for its ability to protect against carbon tetrachloride (CCl4)-induced liver injury in Wistar rats. The chemical composition of the sulfated polysaccharide, documented 12.90% of yield, 83.07% of carbohydrate, 0% of protein, 15.02% of ash, and 2.09% of moisture, and the carbon, hydrogen, nitrogen, and sulfur content were 25.90%, 4.28%, 2.65%, and 3.61%. SP has a molecular weight of 41kDa. The monosaccharide and structural properties of SP were investigated using GC-MS, FT-IR, and 1H-NMR spectral analysis. In rats, CCl4 produced hepatotoxicity, as evidenced by an increase in serum ALT, AST, and ALP levels and a decrease in ALB levels. The SP treated showed decreases in ALT, AST and ALP levels, as well as an increase in ALB levels. SOD, catalase, GPx, and GSH levels were suggestively lower in CCL4-induced rats compared to normal control rats. SOD, catalase, GPx and GSH levels in the SP-treated rats, on the other hand, improved to normal levels. The rat liver tissue treated with SP recovered well from hepatic injury. SP can be considered an alternative in the treatment of liver injury or as preventive medicine.

Short-form video has taken over social media and attracted attention from advertisers. As brands shift their advertising spending to short-form video social platforms, doubts remain about the advertising efficacy on these platforms, especially given the skyrocketing advertising costs in recent years. In a large-scale randomized experiment on ByteDance in collaboration with an automobile brand, we show a significant effect of the advertising campaign on ByteDance, compared with effects reported in other studies. Exposed users are eight times more likely to convert from outside than from within ByteDance, which raises the importance of information sharing between the platform and brands. When considering conversions outside ByteDance, the average cost per conversion, which brands commonly use to evaluate the cost of campaigns, shrinks by 5 or 25 times, depending on the methods used to calculate it. Information sharing can also affect a brand’s targeting strategy. While commonly used demographic variables by the automobile brand are effective for target marketing with only platform data, they are not when considering conversions outside ByteDance. Instead, a behavioral variable proposed herein (prior brand home page visits) effectively moderates the advertising effect but has no effect when including only platform data in the analysis.

Physicians exposed to a risky environment experience burnout, which negatively impacts patient care, stress decreases compassion, harms patient-doctor communication and may jeopardize patient safety. Patients are directly exposed to their physicians' overload and can sense their exhaustion, making them a sensitive seismograph of burnout. This study aimed to compare patients' standpoints towards physicians' burnout before and during the COVID-19 pandemic, characterizing patients' perceptions according to the 4 components of burnout. Two cross-sectional surveys (February-March 2018 and 2021) were conducted. 314 responders, 133 in 2018 and 181 in 2021. Physician burnout, accountability, empathy towards doctors ("mirror reflection") and the expected patient-doctor partnership were measured. Patients' perception of physicians' burnout was significantly associated with urban community, education and religiosity. Perceived accountability was associated with female gender and education. Empathy was associated with employment and gender. Patients described physicians' burnout as significantly higher prior to the COVID-19 pandemic. Physicians' accountability, empathy for doctors, and perceived partnership were more intense in 2021, implying that the emergency emphasized the physician's role and the patient-doctor relationship. Global disasters may have an unexpected positive effect on how patients understand the role and duty of physicians and the health system.

The inclusion of scientific journals in prestigious indexers is often associated with higher citation rates; journals included in such indexers are significantly more acknowledged than those that are not included in them. This phenomenon refers to the Matthew effect on journal citations, according to which, journals in exclusive rankings tend to be increasingly cited. This paper shows the opposite: that the inclusion of journals in local indexers ruled by inclusive logic reduces the Matthew effect on journal citations, since it enables them to be equally exposed. Thus, we based our arguments on the comparison of 68 Brazilian journals before and after they were indexed in the Scientific Periodicals Electronic Library (Spell), which ranks journals in the Brazilian management field based on local citations. Citation impact indicators and iGini (a new individual inequality analysis measure) were used to show that the inclusion of journals in Spell has increased their impact factor and decreased their citation inequality rates. In addition, the results indicated that the effect between ranking and inequality has declined after journals were included in Spell; this outcome indicates that the database has reduced the Matthew effect on journal citations.

High-quality optical Fano resonances, which exist in a spherical dielectric microparticle in the spatial configurations of the "whispering-gallery modes" (WGMs) and recently are referred to as the “super-resonances”, possess extremal sensitivity not only to the micro-cavity size and shape but also to the optical properties of the particulate material. The increase in the power of light radiation coupling into a super-resonance can lead to the manifestation of strong optical nonlinearity of the resonator material due to the cubic nonlinearity (optical Kerr effect) and generation of free electron plasma in certain regions of the spherical microcavity. In fact, an optically linear medium of the resonance cavity transforms into a Drude-Kerr-type medium with a strong dependence on input laser intensity. With the help of the finite-elements numerical simulations, we theoretically analyze the transformations of the resonant contour for a number of high-quality WGMs excited in a lanthanum-glass microsphere exposed to an optical radiation of different intensity. We show that in a certain input intensity range, the competition of Kerr and plasma optical nonlinearities can stop and even reverse the Stokes shift of the super-resonance observed in a pure Kerr medium. Additionally, optical ionization and plasma generation within the mode volume significantly reduce the strength of the magnetic super-resonance and lead to its spoiling and frequency splitting.

Cancer is amenable to low-cost treatments, given that it has a significant metabolic component, which can be effected through diet and lifestyle change at minimal cost. The Warburg hypothesis states that cancer cells have altered cell metabolism towards anaerobic glycolysis. Given this metabolic reprogramming in cancer cells, it is possible to target cancers metabolically by depriving them of glucose. In addition to dietary and lifestyle modifications which work on tumors metabolically, there are a panoply of nutritional supplements and repurposed drugs associated with cancer prevention, and better treatment outcomes. These interventions and their evidentiary basis are covered in the latter half of this review to guide future cancer treatment.

Carbon nanotubes have sparked a substantial amount of scientific and technological research due to their exceptional mechanical, physical and electrical characteristics compared to conventional materials. As a result, detailed studies on their mechanical properties have been conducted, and static and dynamic behavior of single-walled and multi-walled carbon nanotubes have been proposed using Euler-Bernoulli and Timoshenko beam models. The main objective of this paper is to study the free vibration of a Timoshenko-Ehrenfest single-walled carbon nanotube based on the nonlocal theory and taking surface effects into account. To model these effects on frequency response of nanotubes, we use Eringen’s nonlocal elastic theory and surface elastic theory proposed by Gurtin and Murdoch to modify the governing equation. A modified version of Timoshenko nonlocal elasticity theory - known as the nonlocal truncated Timoshenko beam theory - is put forth to investigate the free vibration behavior of single-walled carbon nanotubes (SWCNT). Using the Hamilton’s principle, the governing equations and the corresponding boundary conditions are derived. Finally, to check the accuracy and validity of the proposed method, some numerical examples are carried out. The impacts of the nonlocal coefficient, surface effects and nanotube length on the free vibration of single-walled carbon nanotube (SWCNT) are evaluated and the results are compared with those found in the literature. The findings indicate that the length of the nanotube, the nonlocal parameter and the surface effect all play important roles and should not be disregarded in the vibrational analysis of nanotubes. Finally, the results show how effective and successful the current formulation is at explaining the behavior of nanobeams.

Seaweeds, notably cochayuyo (Durvillaea incurvata), are recognized for their rich macro- and micronutrient content, along with their inhibitory effects on the α-glucosidase enzyme. The present study aims to evaluate the effectiveness of this inhibition in actual starchy food products under in vitro gastrointestinal conditions. The study utilized freeze-dried cochayuyo, extracted using hot pressurized liquid extraction with 50% ethanol at 120 C and 1500 psi. The inhibition mechanism of α-glucosidase was determined, and the polyphenol composition of the extract was analyzed using Ultra-High-Performance Liquid Chromatography. The study further evaluated the extract’s impact on starch digestibility, total phenolic content, and antioxidant capacity in noodles as representative starchy food under gastrointestinal conditions. The results indicate that the α-glucosidase inhibition mechanism is mixed. Phenolic compounds, primarily tetraphloroethol, could contribute to this anti-enzymatic activity. The extract was observed to decrease starch digestibility, indicated by a lower rate constant (0.0158 vs. 0.0261 min-1) and digested starch at an infinite time (77.4 vs. 80.5 g/100 g). A significant increase (~1200 vs. ~390 µmol TROLOX/100 g) in antioxidant activity was also noted during digestion when the extract was used. Thus, the study suggests that the cochayuyo extract can reduce starch digestion and enhance antioxidant capacity under gastrointestinal conditions.

Enzalutamide is a drug used to treat PC. Docetaxel is a drug for chemotherapy for different cancers including prostate cancer (PC). The effectiveness of these drugs in treating castration-resistant prostate cancer (CRPC) is not consistent and thus, CRPC is still an incurable disease. Recent evidence showed that the bio-inhibitor of FABP5, dmrFABP5, suppressed the tumorigenicity and metastasis of the CRPC cells. In this work, we studied the possible synergic effect of dmrFABP5 combined with either Enzalutamide or Docetaxel on suppressing tumorigenicity of the PC cells. A highly significant synergic effect was observed when dmrFABP5 was used in combination with Enzalutamide on the androgen-responsive PC cells 22RV1. A highly significant synergic effect was also observed when dmrFABP5 was combined with Docetaxel on 22RV1 cells and on the highly malignant, androgen-receptor (AR)-negative DU145 cells. These combined applications exhibited a highly significant inhibitory action on the viability, migration, invasion and colony formation abilities of both 22RV1and DU145 cells. However, dmrFABP5 did not produce any suppression effect when used on FABP5-negative cell line LNCaP, although Enzalutamide can significantly suppress LNCaP cells as a single agent. Further investigations suggested that these synergistic effects were produced by interrupting the FABP5-related signal transduction pathway in PC cells.

Grain shape and chalkiness are important appearance quality traits of rice, which also affect the yield and milling quality. In this study, 190 F2 families derived from the cross between Hua 5178S and Hua 611 were sequenced to construct a genetic linkage map. Combined with F2 and F2:3 generations grain shape and chalkiness phenotype, a total of 15 QTL were detected. There are 8 grain shape QTL distributed on chromosomes 2, 5, 6, 8, and 10; 7 chalkiness QTL distributed on chromosomes 2, 3, and 6. A QTL cluster affecting multiple chalkiness traits was found on chromosome 6, qWBR6.1, qWCR6 and qCR6 were selected for genetic effect verification. It was found that qWBR6.1, qWCR6 and qCR6 explained 13% and 24%, and 29% of the phenotypic variations respectively, and qWCR6 and qCR6 were co-mapped. This study laid a foundation for further cloning of rice appearance quality genes.

In resent years, China’s digital economy has achieved significant global recognition for its instrumental role in supporting sustainable economic and social development. Based on the panel data from China's provinces between 2013-2021, this paper investigates the impact and transmission mechanism of financial deepening on digital economy development. The study finds that financial deepening significantly improves digital economy development. Heterogeneity analysis indicates that financial deepening offers greater support to digital economy development in central and western regions than in the east. Further analysis shows that financial deepening improves technological innovation, which in turn promotes the digital economy development. After applying a test of robustness, the results proved significant.

Bioelectric effect is known as combinatorial biofilm treatment with low dose of antibiotics with small electricity. When external electric field or current are applied, biofilms can be affected by the electrostatic force, non-uniform distribution of essential electrolytes, induction of low activity of enzyme, and increase of permeability of biofilms. In this work, we have focused on the reduction of applied electric power consumption that could avoid water electrolysis which was one of major challenges for biomedical applications. We have developed a new type of electrical signal that enhances the efficacy of biofilm removal. The results show combination of alternating and direct current remove biofilm effectively without causing electrolysis. We further developed an oral healthcare device as a bioelectric toothbrush and tested in dental clinic. The results demonstrated 75% reduction of gingivitis. In addition, we have tested a mimicked air conditioner biofilms that are root causes of aerobic hygiene infection. The result demonstrates 81.8% increased biofilm removal. In conclusion, a new bioelectric technology has been developed and demonstrated the biofilm removal efficacy without the electrolysis.

Mild traumatic brain injury (mTBI) is the most common brain injury, seen in sports, falls, vehicle, or workplace injuries. Concussion is the most common type of mTBI. Assessment of impairments from concussion are evolving, with oculomotor testing suggested as a key component in a multi-modality diagnostic protocol. The aim of this study was to evaluate the reliability of one eye-tracking system, the EyeGuide Focus. Seventy-five healthy adolescent and adult participants (adolescents: n=28; female=11, male=17, mean age 16.5 ± 1.4 years; adults n=47; female=22; male=25, mean age 26.7 ± 7.0 years) completed three repetitions of the EyeGuide Focus within the one session. Intraclass correlation coefficient (ICC) analysis showed the EyeGuide Focus had overall good reliability (ICC 0.79, 95%CI: 0.70, 0.86). However, a familiarization effect showing improvements in subsequent trials was noticeable in both cohorts (p<0.001) with adolescent participants showing greater familiarisation effects than adults. No differences were observed between sexes (p=0.69). Overall, the EyeGuide Focus was found to be reliable, but the observation of familiarization effects suggests that a standardized protocol of a minimum of three trials be employed, similar to other eye-movement testing applications.

Plant loss in experimental plots occurs occasionally in field experiments with coffee crops. In breeding programmes, such loss can be extremely harmful, especially when the statistical analysis methods used are not consistent with the data generated in the experiments. In this study, we analysed a set of productivity data to determine whether the compensatory effect occurs in coffee crops, analyse the need for correcting the number of failures in experiments, and identify the best stand correction method to use. Productivity data from six harvests of 11 experiments with Coffea arabica plants were used. The experiments were implemented in a randomised block design, with four replications and six plants per plot. The following stand correction methods were evaluated: rule of three, Zuber [1], Vencovsky and Cruz [2]covariance of the average or ideal stands, and Cruz [3] and compared to data without correction adjustments. The most adequate correction methods were chosen based on the existence of genetic variance, selective accuracy, and progeny ordering. The compensatory effect was evident from the analysed data, with stand correction shown to be beneficial in progeny competition experiments. The covariance methods using average or ideal stands presented the best results, followed by the method proposed by Cruz [3]. The rule of three and Zuber [1] methods showed unsatisfactory results and are not recommended for stand correction in progeny competition experiments with coffee crops

The non-therapeutic use of antimicrobials in poultry production contribute to the spread of drug-resistant pathogens in both birds and humans. Antibiotics are known to enhance feed effi-ciency and promote growth and weight gain of poultry. New regulatory requirements and con-sumer preferences have led to a reduced use of antibiotics in poultry production and discover natural alternatives to the antibiotic growth promoters. This interest is not just focused on the di-rect removal or inhibition of the causative microorganisms but also the prevention diseases caused by enteric pathogens using a range of feed additives. A group of promising feed additives is short- and medium-chain fatty acids and their derivatives. MCFAs possess antibacterial, anticoccidial and antiviral effects. Also, it has been proven that these acids act synergistically if they are used together with organic acids, essential oils, or probiotics. These fatty acids also benefit intestinal health integrity and homeostasis in broilers. Other effects have also been documented, including increases in intestinal angiogenesis and gene expression of tight junctions. The aim of this review is to give an overview of SCFA, MCFA as alternatives of antibiotic growth promoters and by sum-marizing the current finding in the literature, to show their possible benefits on production, meat quality and gut health in poultry.

The Covid 19 pandemic threaten the life of individuals and there was a lack of information in treatment, handling of patients and disposal of waste. The psychological and behavioral impact on Humans due to outbreak of Covid is studied and based on that a person-centered care center is suggested. The research methodology used are surveys, interviews among stake holders and design details of person-centered care center. Based on the surveys and interviews conducted during pandemic, it is found that 94% of the respondents prefer to use private vehicles with at least one member to ac-company them. People prefer to use 3 ply facemasks, followed by cotton masks and N95. Existing literature discusses the physical effects on the individual, but this paper focuses more on pros and cons on human life during the pandemic and lock down period. Based on the study, care center with facilities to treat patients with different levels of infections and counselling center for the persons suffered from Covid and other infectious diseases to overcome their psycho-logical and behavior changes are recommended.

The simultaneous breaking of time-reversal and inversion symmetry, in connection to superconductivity, leads to transport properties with disrupting scientific and technological potential. Indeed, the anomalous Josephson effect and the superconducting diode effect hold promises to enlarge the technological applications of superconductors and nanostructures in general. In this context, the system we theoretically analyze is a Josephson junction (JJ) with coupled reconstructed topological channels as a link; such channels are at the edges of a two-dimensional topological insulator (2DTI). We find a robust $\varphi_0$ Josephson effect without requiring the presence of external magnetic fields. Our results, which rely on a fully analytical analysis, are substantiated by means of symmetry arguments: Our system breaks both time-reversal symmetry and inversion symmetry. Moreover, the anomalous current increases as a function of temperature. We interpret this surprising temperature dependence by means of simple qualitative arguments based on Fermi's golden rule.

The 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors, also known as statins, are administered as first-line therapy for hypercholesterolemia, both as primary and secondary prevention. Besides the lipid-lowering effect, statins have been suggested to inhibit the development of cardiovascular disease through anti-inflammatory, antioxidant, vascular endothelial function-improving, plaque-stabilizing, and platelet aggregation-inhibiting effects. The preventive effect of statins on atherothrombotic stroke has been well established, but statins can influence other cerebrovascular diseases. This suggests that statins have many neuroprotective effects in addition to lowering cholesterol. Furthermore, research suggests that statins cause pro-apoptotic, growth-inhibitory, and pro-differentiation effects in various malignancies. Preclinical and clinical evidence suggests that statins inhibit tumor growth and induce apoptosis in specific cancer cell types. The pleiotropic effects of statins on cardiovascular and cerebrovascular diseases have been well established; however, the effects of statins on cancer patients have not been fully elucidated and are still controversial. This review discusses the recent evidence on the effects of statins on cardiovascular and cerebrovascular diseases and cancer. Additionally, this study describes the pharmacological action of statins, focusing on the aspect of ‘beyond lipid-lowering.’

This work is devoted to the study of the pyroelectric effect on the qualities of optical waveguides formed in a lithium niobate crystal by proton exchange. In the present work, we investigated the cessation effect of the radiation channeling during thermocycling of Y-splitters samples. We examined the spectral dependence of optical losses on a wavelength using an optical spectrum analyzer. The results demonstrate that in the range of 1530–1570 nm, all wavelengths are suppressed equally. The optical reflectometry method in the frequency domain shows that the increase of optical losses is observed along the entire waveguide, but not only at the Y-distribution point, as supposed earlier.

An accurate understanding of jointed rock mass behavior is important in many applications ranging from deep geological disposal of nuclear waste to deep mining to urban geoengineering projects. The roughness of rock fractures and the matching of the fracture surfaces are the key contributors to the shear strength of rock fractures. In this research, push shear tests with three normal stress levels of 3.6, 6.0, and 8.5 kPa were conducted with two granite samples with artificially induced well-matching tensile fractures with sizes of 500 mm × 250 mm and 1000 mm × 500 mm. The large sample reached on average a -60 % weaker peak shear stress than the medium-sized sample, and a strong negative scale effect was observed in the peak shear strength. The roughness of the surfaces was measured using a profilometer and photogrammetry. The scale-corrected profilometer-based method (JRC) underestimates the peak friction angle for the medium-sized slabs by -27 % for the medium sample and -9 % for the large sample. The photogrammetry-based (Z’2) method produces an estimate with -7% (medium) and +12 % (large) errors. The photogrammetry-based Z’2 is an objective method that consistently produces usable estimates for the JRC and peak friction angle.

One of the biggest challenges in modern physics is how to unify gravity with quantum theory. There is an absence of a complete quantum theory of gravity, and conventionally it is thought that the effects of quantum gravity occur only at high energies (Planck scale). Here we suggest that certain novel quantum effects of gravity can become significant even at lower energies and could be tested at laboratory scales. We also suggest a few indirect effects of dark energy that can show up at laboratory scales. Using these ideas, we set observational constraints on radio recombination lines of the Rydberg atoms. We further suggest that high-precision measurements of Casimir effects for smaller plate separation could also show some manifestations of the presence of dark energy.

Considering that the electric refrigeration temperature range of 0.94BNT-0.06BT ceramic materials is 100~140˚C, the electric refrigeration performance of the 0.94BNT-0.06BT ceramic material system was modified by LiNbO3 doping to reduce the cooling temperature. As a result, the refrigeration temperature range of the 0.94BNT-0.06BT ceramic material system was lowered to 25~80 ˚C, achieving its cooling effect near room temperature, and in this temperature range, the adiabatic temperature changes ∆T&gt;0.6K.

Parents’ attitudes and practices may support the children’s reactions to treatments for leukemia and their general adjustment. This study has two aims: to explore parenting depending on child's age and to develop and test a model on how family processes influence the psycho-social development of children with leukemia. Patients were 118 leukemic children and their parents recruited at the Haematology-Oncologic Clinic of the Department of Pediatrics, University of Padua. All parents were Caucasian with a mean age of 37.39 years (SD = 6.03). Children’s mean age was 5.89 years (SD = 4.21). After the signature of the informed consent, the parents were interviewed using the EFI-C from which we derived Parenting dimension and 3 parental perceptions on child’s factors. One year later, the clinical psychologist interviewed again parents using the VABS scales. The analyses revealed the presence of a significant difference in parenting by child’s age: Infants required a higher and more intensive parenting. Child’s coping to medical procedures at the second week after the diagnosis, controlled for parenting effect, impacted upon child’s adaptation one-year post diagnosis. Specific intervention programmes are proposed in order to help children more at risk just after the diagnosis for developmental delays.

In this work we theoretically investigate the responsivity/noise equivalent power (NEP) trade-off in graphene/semiconductor Schottky photodetectors (PDs) operating in the near-infrared regime and working at room temperature. Our analysis shows as the responsivity/NEP ratio is strongly dependent on the Schottky barrier height (SBH) of the junction and we derive a closed analytical formula for maximizing it. In addition, we theoretically discuss as the SBH is linked to the bias applied to the junction in order to show how these devices could be optimized in practice for different semiconductors. We discover that graphene/n-silicon (Si) Schottky PDs could be optimized at 1550nm showing a responsivity and NEP of 133mA/W and 500fW/Hz, respectively, by a low reverse bias of only 0.66V. Moreover, we show that graphene/n-germanium (Ge) Schottky PDs optimized in term of responsivity/NEP ratio could be employed at 2000nm with a responsivity and NEP of 233mA/W and 31pW/Hz, respectively. We believe that our insights are of great importance in the field of silicon photonics for the realization of Si-based PDs to be employed in power monitoring, lab-on-chip and environment monitoring applications.

The aim of this study was to identify MFIs specific determinants of capital structure of selected micro finance institutions in Ethiopia. The researcher employed quantitative research approach with explanatory research design. The result of regression analysis showed that out that variables like growth, profitability, firm size, age, and asset tangibility have positive and statistically significant effect on leverage ratio. Whereas, profitability has statistically significant and negative effect on capital structure. Based on the findings of the study, the researcher concluded that the firm specific determinants of capital structure of micro finance institutions in Ethiopia were growth, profitability, firm size, age, and asset tangibility.

Currently, natural philosophy (Physics) lacks the most fundamental model and a complete set of self-consistent explanations. This article attempts to address several issues to fill in the gaps. Starting from the most basic philosophical paradoxes, I deduce a physical model (the natural philosophical outlook) to describe the laws governing the operation of the universe. Based on this model, a mathematical model is established to describe the generalized diffusion behavior of a moving particle swarm, and its simple verification is carried out. In this article, the gravitational force and relativistic effects are interpreted for the first time as a statistical effect of randomly moving particles. Thus, the gravitational force and special relativistic effects are integrated into a single equation (achieved by selecting an initial wave function with a specific norm when solving it), and the cause of stable particle formation is also revealed. The derived equation and the method of acquiring the initial wave function are fully self-consistent with the hypotheses stated in the physical model, thereby also proving the reliability of the physical model to some extent. Some of these ideas may have potential value as a basis for understanding the essence of quantum mechanics, relativity and superstring theory, as well as for gaining a further understanding of nature and the manufacture of quantum computers.

This paper reassesses the detrimental effect on fatigue performance due to thicker sections based on extensive fatigue strength test database, taken from research program worldwide over the past half of a century in offshore oil &amp; gas and renewable industry. The data entries in the database have been evaluated to ensure its data integrity. Statistical analyses on these S-N data are performed with or without the thickness correction at different exposure level to corrosive environment, in order to re-evaluate the suitability of current standards in regard to the thickness effect. The study has concentrated on T-joint, transverse butt welded joint and tubular joint as these are the most commonly used joint types in the offshore wind industry. The analysis indicates general agreement of fatigue strength with the thickness effects in current standard for in air conditions but great conservatism for corrosive environment.

The interest in dry EEG electrodes has increased in recent years and especially as everyday suitability earplugs for measuring drowsiness or focus of auditory attention. However, the challenge is still the need for a good electrode material, which is reliable and can be easily processed for highly personalized applications. Laser processing as used here is a fast and very precise method to produce personalized electrode configurations that meet the high requirements of in-ear EEG electrodes, for example. The arrangement of the electrodes on the very flexible and compressible mats allows an exact alignment of the electrodes to the ear mold and contributes to a high wearing comfort, as no edges or metal protrusions are present. For better transmission properties, an adapted coating process for surface enlargement of platinum electrodes is used, which allows easy control of the thickness and growth form of the porous layer. The porous platinum-copper alloy is chemically very stable, shows no exposed copper residues and enlarges the effective surface area by 40. In a proof-of-principle experiment, these porous platinum electrodes could be used to measure the Berger effect in a dry state using just one ear of a test person. Their signal-to-noise ration and frequency transfer function is comparable to gel-based silver/silver chloride electrodes.

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

In a thin-volume photobioreactor where a concentrated suspension of microalgae is circulated throughout the established spatial irradiance gradient, microalgal cells experience a time-variable irradiance. Deploying this feature is the most convenient way of obtaining the so-called “flashing light” effect, improving biomass production in high irradiance. This work investigates the light flashing features of sloping wavy photobioreactors, a recently proposed type, by introducing and validating a Computational Fluid Dynamics model. Two characteristic flow zones (straight top-bottom stream and local recirculation stream), both effective toward light flashing, have been found and characterised: a recirculation-induced frequency of 3.7 Hz and straight flow-induced frequency of 5.6 Hz were estimated. If the channel slope is increased, the recirculation area becomes less stable while the recirculation frequency is nearly constant with flow rate. The validated CFD model is a mighty tool that could be reliably used to further increase the flashing frequency by optimising the design, the dimensions, the installation and the operational parameters of the sloping wavy photobioreactor.

Designing the future energy supply in accordance with ambitious climate change mitigation goals is a challenging issue. Common tools for planning and calculating future investments in renewable and sustainable technologies are often linear energy system models based on cost optimisation. However, input data and the underlying assumptions of future developments are subject to uncertainties that negatively affect the robustness of results. This paper introduces a quadratic programming approach to modifying linear, bottom-up energy system optimisation models in order to take cost uncertainties into account. This is accomplished by implementing specific investment costs as a function of the installed capacity of each technology. In contrast to established approaches like stochastic programming or Monte Carlo Simulation, the computation time of the quadratic programming approach is only slightly higher than that of linear programming. The model’s outcomes were found to show a wider range as well as a more robust allocation of the considered technologies than the linear model equivalent.

The corrosion inhibition performance of pyridine derivatives (4-methylpyridine and its quaternary ammonium salts) and sulfur-containing compounds (thiourea and mercaptoethanol) with different molar ratios on carbon steel in CO2-saturated 3.5 wt.% NaCl solution was investigated by weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy and scanning electron microscopy. The synergistic corrosion inhibition mechanism of mixed inhibitors was elucidated by the theoretical calculation and simulation. The molecule of pyridine derivatives compound with larger volume has the priority to adsorb on the metal surface, while the molecules of sulfur-containing compounds with smaller volume fill in vacancies. A dense adsorption film would be formed when 4-PQ and sulfur-containing compounds are added at a proper mole ratio.

We study the effect of polymer coating, pressure, temperature and light on the electrical characteristics of monolayer WSe₂ back-gated transistors with quasi-ohmic Ni/Au contacts. We prove that the removal of a layer of poly(methyl methacrylate) or a decrease of the pressure change the device conductivity from p to n-type. We demonstrate a gate-tunable Schottky barrier at the contacts and measure a barrier height of ~70 meV in flat-band condition. We report and discuss a temperature-driven change in the mobility and the subthreshold slope which we use to estimate the trap density at the WSe₂/SiO₂ interface. We study the spectral photoresponse of the device, that can be used as a photodetector with a responsivity of ~0.5 AW^-1 at 700 nm wavelength and 0.37 mW/cm² optical power.

In this study, the model proposed by Yang et al. to generalize the stress–strain model for unconfined concrete with consideration of the size effect is expanded. Sim et al.’s compressive strength model that is based on the function of specimen width and aspect ratio was used for the maximum stress. In addition, a strain at the maximum stress was formulated as a function of compressive strength by considering the size effect using the regression analysis of datasets compiled from a wide variety of specimens. The descending branch after the peak stress was formulated with consideration of less dissipated area of fracture energy with the increase in specimen width and aspect ratio in the compression damage zone (CDZ) model. The key parameter for the slope of the descending branch was formulated as a function of specimen width and aspect ratio, concrete density, and compressive strength of concrete considering the size effect. Consequently, a rational stress–strain model for unconfined concrete was proposed. This model explains the trends of the peak stress and strain at the peak stress to decrease and the slope of the descending branch to increase, as the specimen width and aspect ratio increase. The proposed model agrees well with the test results, irrespective of the compressive strength of concrete, concrete type, specimen width and aspect ratio. In particular, the proposed model for the stress–strain curve rationally considered the effect of decreasing peak stress and increasing the descending branch slope, with the increase in specimen width and aspect ratio.

Gold nanoparticles (AuNPs) are currently under intense investigation for biomedical and biotechnology applications, thanks to their ease in preparation, stability, biocompatibility, multiple surface functionalities and size-dependent optical properties. The most commonly used method for AuNPs synthesis in aqueous solution is the reduction of tetrachloroauric acid (HAuCl₄) with trisodium citrate. We observed variations in the pH and concentration of the gold colloidal suspension synthesized under standard conditions, verifying a reduction in the reaction yield by around 46% from pH 5.3 (2.4 nM) to pH 4.7 (1.29 nM). Citrate-capped AuNPs were characterized by UV-visible spectroscopy, TEM, EDS and zeta-potential measurements, revealing a linear correlation between pH and the concentration of the generated AuNPs. This result can be attributed to the adverse effect of protons both on citrate oxidation and on citrate adsorption onto the gold surface, which is required to form the stabilization layer. Overall, this study provides insight into the effect of the pH over the synthesis performance of the method, which would be of particular interest from the point of view of large-scale manufacturing processes.

Ionic liquids (ILs) have gained interest among researchers due to its tunable properties that can be used in wide applications. However, toxicity and bio-degradation studies of ILs proved that most of the aromatic ILs, such as imidazolium is highly toxic and non-biodegradable. Several advance oxidation processes (AOPs) have been investigated by researchers to evaluate the efficiency of the systems for the removal of ILs from wastewater. However, the issue on relative high cost and environmental concern has limited the application of these AOPs in industry. In this research, photocatalytic study using hybrid nano-materials was conducted to evaluate the efficiency of this system as an alternative AOP system for removal of ILs from wastewater. The synergistic effect of adsorption-photodegradation was introduced by depositing Fe-TiO₂ onto the functionalized activated carbon (AC). Nano-TiO₂ was synthesized using micromulsion method before modification with transition metal and deposited onto the oxidized AC. Photodegradation reaction of 1-butyl-3-methylimidazolium chloride [bmim]Cl was investigated under simulated visible light irradiation. It was observed that the overall efficiency of the system was increased with the increasing amount of Fe dopant. Investigation on the extrinsic factors such as solution pH, initial concentration of ILs and photocatalyst dosage showed to significantly affect the overall efficiency of the systems where the optimum condition for the system was observed at pH 10, with initial ILs at 1mM at 1 g/L of photocatalyst. The best performance photocatalyst was 0.2Fe-TiO₂/AC.

This paper investigates the problem of a relativistic Dirac half-integer spin free particle tunneling through a rectangular quantum-mechanical barrier. If the energy difference between the barrier and the particle is positive, and the barrier width is large enough, there is proof that the tunneling may be superluminal. For first spinor components of particle and antiparticle states, the tunneling is always superluminal regardless the barrier width. Conversely, the second spinor components of particle and antiparticle states may be either subluminal or superluminal depending on the barrier width. These results derive from studying the tunneling time in terms of phase time. For the first spinor components of particle and antiparticle states, it is always negative while for the second spinor components of particle and antiparticle states, it is always positive, whatever the height and width of the barrier. In total, the tunneling time always remains positive for particle states while it becomes negative for antiparticle ones. Furthermore, the phase time tends to zero, increasing the potential barrier both for particle and antiparticle states. This agrees with the interpretation of quantum tunneling that the Heisenberg uncertainty principle provides. This study’s results are innovative with respect to those available in the literature. Moreover, they show that the superluminal behaviour of particles occurs in those processes with high-energy confinement.

Long memory plays an important role in many fields by determining the behaviour and predictability of systems; for instance, climate, hydrology, finance, networks and DNA sequencing. In particular, it is important to test if a process is exhibiting long memory since that impacts the accuracy and confidence with which one may predict future events on the basis of a small amount of historical data. A major force in the development and study of long memory was the late Benoit B. Mandelbrot. Here we discuss the original motivation of the development of long memory and Mandelbrot's influence on this fascinating field. We will also elucidate the sometimes contrasting approaches to long memory in different scientific communities

This study examines the exchange rate rebound effects of the Central Bank intervention in the selected ECOWAS economies. An empirical understanding of these effects is very important to trade adjustment as well as the macroeconomic stability in these countries. Using the panel data modelling framework, the study finds that the impact of the Central Bank intervention on exchange rate is insignificant and it does not lead to the exchange rate rebound. In addition, money supply as well as monetary policy rate implemented by the monetary authorities significantly influences the level of exchange rate in a positive direction.

The Sunyaev-Zeldovich effect (SZe) is a global distortion of Cosmic Microwave Bckground (CMB) spectrum as result of its interaction with a hot electron plasma in the intracluster medium for large gravitational virialized structures such as galaxy clusters. Furthermore, this hot gas of electrons emits X-Rays due to its fall in the gravitational potential well of the cluster. The analysis of SZe and X-Ray data, provide a method for calculating distances to galaxy clusters at any redshift (Angular diameter distance (d_A) and gas mass fraction (f_gas)). On the other side, many of these galaxy clusters produce a Strong Gravitational Lens effect (SGL), which has become an useful astrophysical tool for cosmology. We use these cosmological tests, in addition to the more traditional ones (SNIa, CMB, BAO), to constraint alternative models of dark energy (ωCDM, CPL, IDE, EDE) and study the history of expansion through the cosmographic parameters (H(z), q(z), j(z)). Using Akaike and Bayesian Information Criterion (AIC, BIC) we find that the ωCDM and ΛCDM models are the most favored by the observational data. In addition, we found that at low redshift appears an peculiar behavior of slowdown of aceleration, which occurs only on dynamical dark energy models using only galaxy clusters (d_A,clusters + f_gas).

The Mann-Whitney effect is a measure for comparing survival distributions between two groups. The Mann-Whitney effect is interpreted as the probability that a randomly selected subject in a group survives longer than a randomly selected subject in the other group. Under the independence assumption of two groups, the Mann-Whitney effect can be expressed as the traditional integral formula of survival functions. However, when the survival times in two groups are not independent each other, the traditional expression of the Mann-Whitney effect has to be modified. In this article, we propose a copula-based approach to compute the Mann-Witney effect with parametric survival models under dependence of two groups, which may arise in the potential outcome framework. In addition, we develop a Shiny web app that can implement the proposed method via simple commands (https://nkosuke.shinyapps.io/shiny_survival/). Through a simulation study, we show the correctness of the proposed calculator. We apply the proposed methods to two real datasets.

Backscatter communication, which transmits information by passively reflecting radio 1 frequency (RF) signals, has become a focal point of interest due to its potential to significantly enhance 2 the energy efficiency of Wireless Power Mobile Edge Computing (WPMEC) networks and extend the 3 operational lifespan of terminal devices. However, there is little research on the integration of user 4 cooperation in WPMEC scenarios within volatile network environments. In this paper, we propose 5 a dynamic task offloading scheme for a Backscatter-assisted WPMEC system, which involves two 6 mobile devices (MDs) and a Hybrid Access Point (HAP) with user cooperation. We formulate the 7 energy efficiency (EE) maximization problem as a stochastic programming problem, considering 8 the randomness of task arrivals and time-varying wireless channels. By leveraging Dinkelbach’s 9 method and stochastic network optimization technique, we transform the problem into a series of 10 deterministic sub-problems for each time slot, and convert the non-convex sub-problem into convex 11 ones. We propose a low-complex EE maximization algorithm to solve the convex problems efficiently. 12 Extensive simulations are conducted to validate the performance of our algorithm under various 13 system parameter settings. Experiment results demonstrate that our algorithm not only outperforms 14 the benchmark algorithms by approximately 23%, but also stabilize all queues within the MEC 15 system.

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 Industrial Internet of Things (IIoT) paradigm is a key research area derived from the Internet of Things (IoT). The emergence of IIoT has enabled a revolution in manufacturing and production, through the employment of various embedded sensing devices connected with each other by an IoT network, along with a collection of enabling technologies such as artificial intelligence (AI) and edge/fog computing. One of the unrivaled characteristics of IIoT is the inter-connectivity provided to industries; however, this characteristic might open the door for cyber-criminals to launch various attacks. In fact, one of the major challenges hindering the prevalent adoption of the IIoT paradigm is IoT security. Inevitably, an increasing number of research proposals have been introduced over the last decade to overcome these security concerns. To obtain an overview of this research area, conducting a literature survey of the published research is necessary, eliciting the various security requirements and their considerations. This paper provides a literature survey of IIoT security, focused on the period from 2017 to 2023. We identify IIoT security threats and classify them into three categories, based on the IIoT layer they exploit to launch these attacks. Additionally, we characterize the security requirements that these attacks violate. Finally, we highlight how emerging technologies, such as AI and edge/fog computing, can be adopted to address security concerns and enhance IIoT security.

With the proliferating of video surveillance system deployment and related applications, real-time video analysis is very critical to achieve intelligent monitoring, autonomous driving, etc. It is non-trivial to achieve high accuracy and low latency video stream analysis through the traditional cloud computing. In this paper, we propose a non-orthogonal multiple access (NOMA) based edge real-time video analysis framework with one edge server (ES) and multiple user equipments (UEs). A cost minimization problem composed of delay, energy and accuracy is formulated to improve the QoE of UEs. In order to efficiently solve this problem, we propose the joint video frame resolution scaling, task offloading, and resource allocation algorithm based on the Deep Q-Learning Network (JVFRS-TO-RA-DQN), which effectively overcomes the sparsity of the single-layer reward function and accelerates the training convergence speed. JVFRS-TO-RA-DQN consists of two DQN networks to reduce the curse of dimension, which respectively select the offloading and resource allocation action, the resolution scaling action. Experimental results show that JVFRS-TO-RA-DQN can effectively reduce the cost of transmission and computation, and have better performance in convergence compared to other baseline.

The Internet of Things (IoT) is experiencing widespread adoption across industry sectors ranging from supply chain management to smart cities, buildings, and health monitoring. However, most software architectures for IoT deployment rely on centralized cloud computing infrastructures to provide storage and computing power, as cloud providers have high economic incentives to organize their infrastructure into clusters. Despite these incentives, there has been a recent shift from centralized to decentralized architecture that harnesses the potential of edge devices, reduces network latency, and lowers infrastructure cost to support IoT applications. This shift has resulted in new edge computing architectures, but many still rely on centralized solutions for managing applications. A truly decentralized approach would offer interesting properties required for IoT use cases. To address these concerns, we introduce a decentralized architecture tailored for large scale deployments of peer-to-peer IoT sensor networks and capable of run-time application migration. The solution combines a blockchain consensus algorithm and verifiable random functions to ensure scalability, fault tolerance, transparency, and no single point of failure. We build on our previously presented theoretical simulations with many protocol improvements and an implementation tested in a use case related to monitoring a Slovenian cultural heritage building located in Bled, Slovenia.

The Industrial Internet of Things (IIoT) is bringing evolution with remote monitoring, intelligent analytics, and control of industrial processes. A reference architecture provides the general layout information for the flexible integration of IIoT systems; however, as the industrial world is currently in its initial stage of adopting the full-stack development solutions with IIoT, some challenges need to be addressed. To cope with the rising challenges and provide the blueprint guidelines to develop and implement IIoT in real-time, researchers around the globe have proposed IIoT architectures based on different architectural layers and emerging technologies. In this paper, we first review and compare some widely accepted IIoT reference architectures and present a state-of-the-art review of conceptual and experimental IIoT architectures in literature. We highlight scalability, interoperability, security, privacy, reliability, and low latency as the main IIoT architectural requirements and compare how the current architectures address these challenges. We also highlight the role of emerging technologies in current IIoT architectures to address these requirements and present the literature gap for future research work to address the challenges.

Nanostructured polymer dispersed liquid crystals (nano-PDLCs) are transparent and optically isotropic materials, in which submicron-sized liquid crystal (LC) domains are dispersed within a polymer matrix. Nano-PDLCs can induce their birefringence by applying an electric field (E-field) based on reorientation of LC molecules. If nano-PDLCs are utilized as light scattering-less birefringence memory materials, it is necessary to suppress the relaxation of LC molecules orientation after removal of the E-field. We focused on a ferroelectric smectic A (SmA) to suppress the relaxation of LC molecules due to their layered structure and high viscosity. Although nano-PDLCs require a strong E-field to reorient LC molecules due to the anchoring effect on the LC/polymer interface, the required field strength can be reduced by using a ferroelectric smectic A (SmAF) LC with a large dielectric constant. In this study, we fabricated a nano-PDLC by irradiating an ultraviolet light to a mixture comprising of a SmAF LC, photocurable monomers and a photo-initiator and its electro-birefringence effect was evaluated using a polarizing optical microscopy. After removal of an E-field, enhanced memory effect was observed on the sample using SmAFLC comparing to nematic LC based nano-PDLCs. (193 words/ 200 words)

Drought and water scarcity are significant factors limiting the development of China's maize industry. Deep sowing, as a method to mitigate drought and preserve soil moisture and seedlings, can effectively mitigate the adverse effects of drought stress on their growth. However, deep sowing can influence the emergence of maize seedlings and has a certain impact on their growth and development. To investigate the physiological and transcriptomic changes in maize inbred lines under deep sowing stress, and the alleviation effects of exogenous hormones, this study investigated the response of mesocotyl in deep-seeding tolerant maize inbred line Qi319 and deep-seeding sensitive maize inbred line Zi330 to deep-seeding stress under exogenous MeJA treatment. The physiological and transcriptomic mechanisms underlying the alleviation of deep-seeding stress by exogenous MeJA were elucidated. Results showed that compared to normal sowing depth, mesocotyl length (MES), mesocotyl and coleoptile length (MESCOL) significantly increased under deep-seeding stress for both inbred lines, while seedling length (SDL) was significantly inhibited. However, after adding 1.5 μmol·L^-1 MeJA, MES, MESCOL, and SDL significantly increased compared to deep-seeding stress alone. Exogenous MeJA promoted cell elongation, enhanced mesocotyl length, and improved seedling emergence ability. RNA-Seq sequencing revealed differentially expressed genes (DEGs). Under deep-seeding stress compared to normal sowing depth conditions, 1248 DEGs were identified in Qi319 and 1288 DEGs were identified in Zi330. After adding exogenous MeJA under deep-seeding stress compared to normal sowing depth with exogenous MeJA treatment conditions, 538 DEGs were identified in Qi319 and 2284 DEGs were identified in Zi 330. GO enrichment analysis showed that differentially expressed genes were mainly concentrated in biological processes, cell components and molecular functions. KEGG enrichment analysis showed that differentially expressed genes were mainly concentrated in transport and catabolism, signal transduction, amino acid metabolism and lipid metabolism processes. Compared with the deep-seeded treatment, 12 differentially expressed genes were co-expressed in the two inbred lines under exogenous MeJA treatment, and 10 key genes, including ornithine decarboxylase, terpene synthase 7 and ethylene reaction transcription factor 11, were screened out. Our findings elucidate the molecular mechanism underlying maize's tolerance response to deep seeding and offer valuable insights into candidate gene resources for improving deep seeding tolerance in maize.

The authors propose a novel approach for a comprehensive evaluation of neuroprotective effects using both in vitro and in vivo methods. This approach allows for the initial screening of numerous newly synthesized chemical compounds and substances from plant and animal sources while preserving animal life. In vitro techniques, including mitochondrial suspensions and neuronal cell cultures, enable assessment of neuroprotective activity, which can be challenging in intact organisms. The preliminary methods help outline the neuroprotection mechanism depending on the neurodestruction agent. The authors have validated a model of acute cerebrovascular accident, which simulates key cerebrovascular phenomena such as reduced cerebral blood flow, energy deficit, glutamate-calcium excitotoxicity, oxidative stress, and early gene expression. A significant advantage of this model is its ability to reproduce the clinical picture of cerebral ischemia: impaired motor activity, signs of neurological deficits (paresis, paralysis, etc.), as well as disturbances in attention, learning, and memory. Crucial to this approach is the selection of biochemical, molecular, and cellular markers to evaluate nerve tissue damage and characterize potential neuroprotective agents. Additionally, a comprehensive set of molecular, biochemical, histological, and immunohistochemical methods is proposed for evaluating neuroprotective effects and underlying mechanisms of potential pharmaceutical compounds.

Croton grewioides Baill., a species native to the Caatinga, popularly known as canela de cunhã, is used in traditional medicine to treat gastrointestinal diseases such as diarrhea, gastritis and stomach ulcers. This study aimed to identify the chemical composition of the essential oil of C. grewioides (OECG) and evaluate its antibacterial and antibiotic-modulating activities against both standard and multidrug-resistant bacteria. To analyze the compounds, present in the oil, gas chromatography coupled with mass spectrometry (GC/MS) and gas chromatography with flame ionization detector (GC/FID) techniques were used. In the bacteriological tests, the Minimum Inhibitory Concentration (MIC) was obtained using the broth microdilution technique. The modulating effect of the essential oil was determined by calculating the subinhibitory concentration followed by serial microdilution of the antibiotics. The MIC reduction factor (FRC) was calculated and its data expressed as a percentage. Analysis of the chemical composition identified the presence of the major compound estragole with a relative abundance of 50.34%. The MIC values obtained demonstrated efficacy in K. pneumoniae isolated from urine with MIC values of 512 µg/mL. OECG potentiated the effects of all antibiotics tested on S. aureus ATCC 29213, K. pneumoniae Carbapnemase, E. coli ATCC 25922 and S. aureus ATCC 29213 strains with their FRC of 97.65 %, 99.80 %, 99.85 % and 99.88 %, respectively. Thus, the essential oil of C. growioides presents synergistic effects when combined with the tested antibiotics, in addition to acting in the fight against bacterial resistance to antibiotics.

Cacalol (C), a sesquiterpene isolated from Psacalium decompositum, has demonstrated anti-inflammatory and antioxidant activities. Its cytotoxic, antiproliferative, and pro-apoptotic effects have been previously shown in an in vitro breast cancer model. A derivative, Cacalol Acetate (CA), shows potential in regulating these processes, which had not been previously reported. This study focused on an in vitro cervical cancer model, assessing CA's anti-proliferative, pro-apoptotic, cytostatic, and anti-migratory activities using the HeLa cell line. The natural anticancer agent I3C was used as a control for comparison. CA demonstrated significant antitumor activities, including inhibiting cell growth, inducing apoptosis, arresting cells in the G2 phase of the cell cycle, and inhibiting cell migration. These effects were notably greater compared to I3C. I3C, while following a similar trend, did not induce Cas-3 expression, suggesting a different apoptotic pathway. Neither CA nor I3C increased p62 and LC3B levels, indicating they do not stimulate autophagy marker expression. Both compounds inhibited HeLa cell migrate on and induced cell cycle arrest. Despite both holding promise as anticancer agents for cervical cancer, CA's lower cytotoxicity and stronger regulation of tumor phenotypes make it a more promising agent compared to I3C.

This review critically evaluates the role of Antibody-drug conjugates (ADCs) in the treatment of urothelial cancer, exploring their therapeutic potential and addressing the scientific and clinical challenges encountered in the development of these agents. It also discusses the recent approvals and clinical trials that are shaping the future of ADC therapy in this field. Through a detailed examination of the mechanism of action of ADCs, including the bystander effect, this paper aims to highlight both the successes and the limitations of these drugs in clinical settings. The main objective of this work is to provide a thorough overview of the current state of ADCs in urothelial cancer treatment, elucidating how these drugs can offer improved outcomes for patients. By discussing the broader implications of ADC technology and its integration into existing treatment paradigms, this review outlines the next steps in research and application necessary to overcome the existing challenges and harness the full potential of ADCs in cancer therapy.

Abstract: Epidemiological, experimental, and ecological data have indicated the controversial effect of in utero chronic low dose rate (100 mGy) dose radiation exposure. Our main goal of this study was to examine if different low dose rates of chronic pre- or/and post-natal radiation exposure with accumulative high doses could induce hippocampal cellular, mRNA, and miRNA changes leading to neuropsychiatric disorders. The comprehensive mouse phenotypic traits, organ weight pathological, blood mRNA and miRNA changes were also studied. Using different approaches including SmithKline, Harwell, Imperial College, Royal Hospital, Phenotype Assessment (SHIRPA), neurobehavioral tests, pathological examination, immunohistochemistry, mRNA and miRNA sequencing, and real-time quantitative polymerase chain reaction ( qRT-PCR) validation, we found that in prenatally irradiated (100 mGy/d for 18 days with an accumulative dose of 1.8 Gy) 1-year-old mice, no cellular changes including neurogenesis, mature neurons and glial cells in the hilus of the dentate gyrus and development of cognitive impairment, neuropsychiatric disorders occurred. However, a significant reduction in body weight and mass index (BMI) was indicated by the SHIRPA test. A reduced exploratory behavior was shown by an open field test. Organ weight measurement showed a significant reduction of the testes, kidneys, heart, liver, and epididymides although no abnormal changes from pathological examination. mRNA and miRNA sequencing and qRT-PCR validation revealed the upregulation of Rubcnl, Abhd14b and downregulation of Hspa1b, P4ha1, and Banp genes in both hippocampus and blood of mice prenatally irradiated with 100 mGy/d. Meanwhile, downregulation of miR-448-3p, miR1298-5p in the hippocampus, miR-320-3p, miR-423-5p, miR-486b-5p, miR-486b-3p, miR-423-3p, miR-652-3p, miR-324-3p, miR-181b-5p, miR-let-7b and miR-6904-5p in the blood was induced. The target scan revealed that Rubcnl is one of the miR-181b-5p targets in the blood. We, therefore, concluded that prenatal chronic irradiation with a low dose rate of 100 mGy/d and accumulative dose of 1.8Gy or below may not induce significant adverse health effects on the offspring. Further study of different low dose rate radiation exposure with accumulative high doses may provide threshold doses for authorities or regulators to set new radiation safety guidelines to replace those extrapolated from acute high dose/dose rate irradiation to reduce unnecessary emergency evacuation or expanding once a nuclear accident or leakage occurs.

Few studies have explored the gender wage gap among farmworkers, and there is a notable absence of research on how farm wages impact household welfare differently based on gender. This study aims to fill this gap by examining how farm wages affect gender disparities in household welfare among farmworkers in Nigeria. Using survey data from 720 farmworkers, we investigated gender-based differences in household welfare. Our approach combined parametric methods (Blinder-Oaxaca decomposition) to assess gender gaps in household welfare and non-parametric techniques (Propensity Score Matching, PSM) to estimate the effects of farm wages. The analysis reveals that female farmworkers experience significantly lower per capita food consumption expenditure (₦11,486.51 less) compared to their male counterparts. These disparities partly stem from differences in socioeconomic factors, job characteristics, and enterprise attributes between male and female farmworkers. The study underscores the role of farm wages in mitigating gender gaps in household welfare, demonstrating that farm wages have increased per capita food consumption expenditure for female farmworkers by ₦6,640.698. This finding highlights the potential of wage increases to enhance livelihoods, underscoring the importance of equitable wage policies in farming. Furthermore, our findings emphasize that the impact of farm wages on welfare varies with household characteristics, suggesting the need for targeted interventions tailored to enhance identified household attributes. Addressing these factors could effectively reduce gender inequalities in farm work and contribute to overall welfare improvements.

Elemental sulfur, commonly known for its wide range of biological activity, has a long history of being used to protect all garden and vegetable crops from a range of pests and diseases, including powdery mildew, ascochyta blight, clubroot, plant mites, oidium, anthracnose, and scab. In the present study, a quick and environmentally friendly approach has been developed for the synthesis of sulfur nanoparticles with antibacterial activity. Sulfur nanoparticles (SNPs) were prepared by modifying the surface of elemental sulfur using various polyelectrolyte-surfactant mixtures (PSM) including NaCMC-SDBS and PHMG-CTAB. The SNPs were characterized by UV–visible spectrophotometry, X-ray diffraction (XRD), and thermogravimetric analysis (TG/DSC), scanning electron microscopy (SEM), with the SNPs showing an almost spherical shape with an average size in the range of 150-200 nm. The antibacterial activity of the sulfur nanoparticles was tested using against gram-positive S. aureus and E. faecium and gram-negative E. coli and P. aeruginosa bacteria. From this, it could be seen that SNPs exhibited significant antimicrobial activity against gram-positive bacteria, i.e., S. aureus and E. faecium. The in vitro cytotoxicity of the SNPs-1 and SNPs-2 studied to normal (MeT-5A) and tumorous (MCF-7) human cell lines was assessed in the concentration range from 500 μg/ml to 0.12 mg/ml, from which it was determined as being non-cytotoxic. The received products can be considered for potential application in agriculture and medicine.

The yeast Saccharomyces cerevisiae ensures successful fermentation in winemaking, although the persistent use of commercial strains lead the loss of aroma complexity of wines. Hence, the research of indigenous S. cerevisiae with proper oenological features and well adapted to specific wine-growing area become of great interest for winemakers. Here, 206 S. cerevisiae strains were isolated from two wineries during two-year sampling campaign and bio-typed with the aim to evaluate the occurrence and persistence of S. cerevisiae wild population linked to each winery. Both wineries belonging to the same Verdicchio DOC wine area (Castelli di Jesi), and never used commercial yeasts during fermentation. Results showed a specific and varied population of S. cerevisiae in each winery without cross-contamination each other and with commercial starter strains. Moreover, inside each winery it was observed a persistent of some dominant biotypes over the time, indicating a sort of “winery-effect”. The evaluation of S. cerevisiae populations for the oenological characters showed a proper and well distinct aromatic imprinting on the resulted wines confirming the “winery effect”.

For some persistent pollutants, such as recalcitrant pesticides, the polluted water (urban, agricultural and/or industrial) treated by conventional wastewater treatment plants is in some cases insufficient to achieve the legally required level of purity. This issue is of particular concern in areas where low rainfall does not provide sufficient water resources to meet the needs of agriculture, requiring increased reuse of water from wastewater treatment plants. In this context, Advanced Oxidation Processes (AOPs) hold great promise for the removal of organic pollutants. This study first evaluates the effectiveness of UV/S2O8= compared to heterogeneous photocatalysis using UV/TiO2 processes on the degradation of two commonly used herbicides (terbutylazine and isoproturon) in aqueous solutions using a photoreactor. In addition. the effect of UV wavelength on the degradation efficiency of both herbicides was investigated. Although degradation rate was higher under UV-254/S2O8= nm than under UV-365/S2O8= nm, complete degradation of the herbicides (0.2 mg L-1) was achieved within 30 min under UV-366 nm using a Na2S2O8 dosage of 250 mg L-1 in the absence of inorganic anions. To assess the impact of water matrix, the individual and combined effects of sulphate, bicarbonate and chloride were evaluated. They can react with hydroxyl and sulphate radicals formed during AOPs to form new radicals with a lower redox potential. The results showed negligible effects of sulphate, while the combination of bicarbonate and chloride seemed to be the key for the decrease in herbicide removal efficiency found when working with complex matrices. Finally, the main intermediates detected during the photodegradation process were identified and the likely pathways are proposed and discussed.

Benveniste’s experiments – known in the lay press as the “water memory” phenomenon – are generally considered to be a closed case. However, the amount of data generated by twenty years of well-conducted experiments prevents closing the file so simply. An issue, which has been little highlighted so far, merits to be emphasized. Indeed, if Benveniste failed to persuade his peers of the value of his experiments, it was mainly because of a stumbling block, namely the difficulty of convincingly proving the causal relationship between the supposed cause (“informed water”) and the experimental outcomes in different biological models. To progress in the understanding of this phenomenon, we abandon the idea of any role of water in these experiments (“water memory” and its avatars). In other words, we assume that “control” and “test” conditions to be evaluated were physically identical and differed only by their respective designations. We show in this article how simple probabilistic considerations allow to build a model that accounts for all aspects of Benveniste’s experiments. In this model based on probability amplitudes, constructive and destructive interferences emerge – or not – according to the experimental context. The recording of a statistical regularity shapes the intertwined whole constituted by the probability amplitudes of the states of the experimenter’s cognitive structures and of the experimental system. This model provides an alternative explanation to Benveniste’s experiments where water plays no role and where the place of the experimenter is central.

Using a detailed atmospheric radiative transfer model, we derive macroscopic relationships of downwelling and outgoing longwave radiation, useful for hydrological practice. We validate them using empirical formulae based on downwelling radiation data, which are in common use in hydrology, as well as satellite data for the outgoing radiation. We use the macroscopic relationships to infer the relative importance of carbon dioxide and water vapour in the greenhouse effect. The results show that the contribution of the former is 4% – 5%, while water and clouds dominate with a contribution of 87% – 95%. The minor effect of carbon dioxide is also confirmed by the small, non-discernible effect of the recent escalation of atmospheric CO2 concentration from 300 to 420 ppm, which is quantified at 0.5% for both downwelling and outgoing radiation. Water and clouds also perform other important functions in climate, such as regulating the heat storage and the albedo, as well as cooling the Earth’s surface though latent heat transfer, with a contribution of 50%. By confirming the major role of water on climate, these results suggest that hydrology should have a more prominent and more active role in climate research.

Rare earth elements (REEs) are a type of new material resources, which have attracted significant attention in recent years. REEs have emerged as essential metals in modern-day technology due to their unique functions. Long-term large-scale mining and utilization of rare earths have caused serious environmental pollution and constitutes a global health issue, which raised concerns about human health safety. However, the toxicity profile of suspended particulate matter of REEs in the environment interacts with the human body in remain largely unknown. Studies have shown that REEs can enter the human body through a variety of pathways, leading to a variety of organ and system dysfunctions through changes in genetics, epigenetics, and signaling pathways. Through an extensive literature search and critical analysis, we provide a comprehensive overview of the available evidence, identify knowledge gaps, and make recommendations for future research directions.

Optical current sensors have been developed and improved in recent decades, and their use has been widespread in power systems, including smart grids. Like any measuring instrument or system, the result of its measurements is associated with a measurement uncertainty, which quantifies its precision. This article presents a review of the main uncertainty contributions that affect the quality and performance of optical current sensors.

Background: Multiple drug delivery systems obtained by loading nanoparticles (NPs) with different drugs with different physicochemical properties present a promising strategy to achieve synergistic effects between drugs or overcome undesired effects. This study aims to develop a new NP by loading Quercetin (Que) and valproic acid (VPA) onto chitosan. In this context, our study investigated the antioxidant activities of chitosan NPs loaded with single and dual drugs containing Que against oxidative stress. Method: The synthesis of single (Que or VPA) and dual-drug (Que and VPA) loaded chitosan NPs, characterization of the NPs, conducting in vitro antioxidant activity studies, and analysis of the cytotoxicity and antioxidant activity of the NPs in SH-SY5Y cell lines were performed. Result: The NP applications that protected cell viability to the greatest extent against H2O2-induced cell damage were, respectively, 96 µg/ml of Que-loaded chitosan NP (77.30%, 48 h), 2 µg/ml of VPA-loaded chitosan NP (70.06%, 24 h), 96 µg/ml of blank chitosan NP (68.31%, 48 h), and 2 µg/ml of Que and VPA-loaded chitosan NP (66.03%, 24 h). Conclusion: Our study establishes a successful paradigm in developing drug-loaded NPs, with uniform and homogeneous distribution of drugs onto NPs. Chitosan NPs loaded with both single and dual drugs possessing antioxidant activity were successfully developed.

Doping can alter the electronic and thermoelectric attributes of an organic semiconductor system. These alterations can enable viable tunable devices that have applications in temperature sensing for environmental controls. Here we demonstrate a dual-modulation organic field-effect transistor (OFET) where temperature effectively modulates the current-voltage characteristics of the OFET and gate voltage modulates the thermoelectric properties of the active layer. Poly(3-hexylthiophene-2,5-diyl) (P3HT) was utilized as the host donor polymer, iodine was utilized as the dopant acceptor molecule Finished devices were characterized by a semiconductor analyzer system with temperature controlled by two thermoelectric cooling plates. The doping of iodine in the range of 0.25% to 0.5% mole ratio with respect to the P3HT exhibited the greatest on-off ratio of the investigated dopant concentrations. Iodine doping concentrations of 0.5% mole ratio or less can greatly improve the thermoelectric properties of a binary P3HT-based system and the current-voltage performance of the dual-modulation device.

In this study, the potential of whey protein hydrolysate (WPH) containing LDIQK peptide and treadmill exercise to prevent cognitive decline was investigated along with the neuroprotective mechanisms. Cognitive dysfunction was induced in mice by 1 mg/kg scopolamine, followed by administration of WPH at 100 and 200 mg/kg and/or treadmill exercise at 15 m/min for 30 min five days per week. Both WPH administration and treadmill exercise significantly improved memory in mice with scopolamine-induced cognitive impairment, which was attributed to several key mechanisms, including a reduction in oxidative stress based on decreased levels of reactive oxygen species and malondialdehyde in the brain tissue and an increase in acetylcholine by increasing choline acyltransferase and decreasing acetylcholine esterase levels. Exercise and WPH also exerted neuroprotective effects by inhibiting the hyperphosphorylation of tau protein, enhancing the expression of brain-derived neurotrophic factor, and inhibiting apoptosis by reducing the Bax/Bcl2 ratio in conjunction with downregulation of the mitogen-activated protein kinase pathway. Moreover, the impact of WPH and treadmill exercise extended to the gut microbiome, suggesting a potential link with cognitive improvement. These findings suggest that both WPH intake and treadmill exercise are effective strategies for mitigating cognitive impairment, providing promising avenues for treating neurodegenerative diseases.

The field of human microbiome and gut microbial diversity research has witnessed a profound transformation, driven by advances in omics technologies. These advancements have unveiled essential connections between microbiome alterations and severe conditions, spurring the development of new frameworks through epidemiological studies. Traditionally, each individual was thought to harbor unique microbial communities acquired early in life, but recent research challenges this belief. The neonatal microbiome's onset, influenced by factors like delivery mode and maternal health, remains a subject of intense debate, hinting at potential intrauterine microbial processes. In-depth research reveals associations between microbiome profiles and specific health outcomes, ranging from obesity to neurodevelopmental disorders. Understanding these diverse microbiome profiles is essential for unraveling the intricate relationships between the microbiome and health outcomes.

The plant Allium hookeri, belonging to the Allium genus, has a history of being used both as a common food ingredient and in herbal medicine. It has recently been reported to have anti-oxidant and anti-inflammatory effects. A. hookeri has been also shown to exhibit neuroprotective and anti-neuroinflammatory activities, but the active compounds responsible for these effects have not been identified in previous studies. This study aimed to perform a metabolite profiling using an HRESI-qTOF MS/MS-based molecular networking approach and identify the active compounds from A. hookeri that target senescent cell-associated secretory phenotype (SASP) inhibitory effects, which contribute to neuroprotective activities. As a result, ten compounds, including one new flavonoid (2) and nine known compounds (1 and 3–10), were identified, and their biological activity was tested. The most potent compound was N-trans-feruloyltyramine (7), which inhibited SASP markers and contributed to the senomorphic activities of A. hookeri. These findings suggest that the phenolamides from A. hookeri could be a promising source of bioactive compounds for preventing senescence-associated diseases.

Consumer preference for products made from transgenic technology has been widely studied, yet few studies exist exploring the factors influencing producers’ adoption of transgenic technology. Based on field surveys in Chinese provinces of Shanxi, Henan and Shandong, we employed a gambling experiment to capture producers’ risk preferences by estimating their risk aversion coefficients. We further estimated producers’ risk amplification and risk perception of GM technology. Using ordered logit model and Poisson model we identified the major factors influencing producers’ adoption of transgenic technology. We found the factors impacted the decision of producers from different regions in different ways. The results showed that over 60% of participants amplified the risk of transgenic crops. When there was potential risk, producers might not be rational even if they had high level of knowledge and cognition about the technology. Our results shed light on government policies aiming to increase the adoption of new technologies by producers.

Influenced by the quasi-stationary Mei-yu front and the development of mesoscale low vortices on the Mei-yu front, a torrential rain event occurred in Suzhou on July 6, 2020. The 24-hour rainfall recorded by the automatic station exceeded 200 millimeters, with the highest hourly intensity surpassing 70 millimeters, accompanied by thunderstorms and strong winds. This heavy precipitation process was characterized by suddenness, extremity, long duration, high precipitation efficiency, and backward propagation. Using various data sources such as the European ERA5 reanalysis data, ground-based automatic stations, sounding, Doppler weather radar, and wind profile radar, this paper analyzed in detail the circulation characteristics and radar echo structures of this torrential rain event, and further studied the triggering, feature evolution, and maintenance mechanisms of the heavy precipitation.The results show: (1) The continuously strengthening low-level jet stream propagates downward forming an ultra-low-level jet stream. Heavy precipitation is located on the left front side of the jet exit area, where strong convergence and lifting in the boundary layer overlap with the ascending branch of the secondary circulation above the shear line, resulting in heavy precipitation. (2) A supercell storm with intense precipitation produced this heavy rainfall event, characterized by a low centroid of strong echo; echo-free vault, bounded weak echo region, and other supercell structural features. During this event, the high reflectivity factor areas corresponded to high KDP value areas, indicating a large amount of liquid water content. Vertically, the KDP column can track the rainwater mixing ratio well, and its location corresponds to the vicinity of the short-term heavy precipitation occurrence. The high KDP value area mainly consists of numerous precipitation particles, and the vertical vortex wind field structure causes rapid growth of precipitation particles through continuous rolling. Furthermore, it can be found through correlation coefficients (CC) that there are always high-value areas for CC since they correspond to areas of intense precipitation. (3) Continuous triggering of mesoscale convective cloud clusters on the east-west ground convergence line leads to new development and forms a "train effect." Strong frontogenesis in both horizontal and vertical directions triggers and sustains this heavy precipitation event. The significant increase in liquid water and water vapor density has indicative significance for the occurrence of heavy precipitation.

GaN-based micro-size light-emitting diodes (µLEDs) have a number of appealing and distinctive benefits for display, visible-light communication (VLC), and other novel applications. The smaller size of LEDs affords them the benefits of enhanced current expansion, less self-heating effects, and higher current density bearing capacity. Low external quantum efficiency (EQE) resulting from non-radiative recombination and quantum confined stark effect (QCSE) is the serious barrier for applications of µLEDs. In this work, the reasons for the poor EQE of µLEDs are reviewed, as well as the optimization techniques for improving the EQE of µLEDs.

Lithium-sulfur (Li-S) battery has been regarded as an important candidate for the next-generation energy storage system due to its high theoretical capacity (1675 mAh g-1) and high energy density (2600 Wh kg-1). However, the shuttle effect of polysulfide seriously affects the cycling stability of the Li-S battery. Here, a novel Fe3C decorated folic acid-derived graphene-like N-doped carbon sheet (Fe3C@N-CS) was successfully prepared as the polysulfide catalyst to modify the separator of Li-S battery. The porous layered structures can successfully capture polysulfide as a physical barrier, and the encapsulated Fe3C catalyst can effectively trap and catalyze the conversion of polysulfide, thus accelerating the redox reaction kinetics. Together with the highly conductive networks, the cell with Fe3C@N-CS modified separator evinces superior cycling stability with 0.06% capacity decay per cycle at 1 C rate over 500 cycles and excellent specific capacity with an initial capacity of 1260 mAh g-1 at 0.2 C. Besides, at a high sulfur loading of 4.0 mg cm-2, the batteries also express superb cycle stability and rate performance.

Aortic dissection (AD) is a critical heart condition with potentially severe outcomes. Our study aims to investigate the existence of a "weekend effect" in AD by examining the correlation between patient outcomes and the timing of their treatment during weekdays vs weekends. Specifically, we assessed prospectively the effects of the timing of treatment on patient outcomes for acute aortic dissection, both before surgical intervention and during hospitalization, as well as during the follow-up period. The mean age of the study population used here was 62.5 years with a high degree of variability. We recorded a rate of mortality before surgery of 8.65% for the weekend group and 15% for the weekday group, with no significant differences noted in the results of statistical tests. During hospitalization, mortality was found to be 50% (n=52) in the weekend group and 25% (n=5) in the weekday group, again with no significant differences observed in the results of the same statistical tests. Patient mortality after discharge was 9.61% (n=10) in the weekend group and 5% (n=1) in the weekday group. Our findings suggest that there is no significant difference in mortality rates between patients admitted to the hospital on weekends versus weekdays. Therefore, the period of the week when a patient presents to the hospital with aortic dissection appears to not affect their mortality outcomes.

In recent years, various optical measurement technologies such as far-infrared spectroscopy, low-frequency Raman spectroscopy, optical Kerr effect spectroscopy, and two-dimensional Raman-terahertz spectroscopy have developed vigorously. By comparing the complementary aspects detected by various linear and nonlinear spectroscopic techniques, a coherent picture emerges from studies of dynamics in water. Numerous molecular dynamics experiments and theoretical investigations have demonstrated low-frequency molecular motions in liquid water. For example, intermolecular hydrogen bond vibration, molecular reorientation motion, and the interaction between molecule/ionic solute and hydrogen bond all occur in the THz region, which are closely related to their physical/chemical properties and structural dynamics. However, precise probing of various modes of motion is difficult due to the complexity of the collective and cooperative motion of molecules and the spectral overlap of related modes. With the development of THz optical technology, current state-of-the-art THz sources can generate pulsed electric fields with peak intensities on the order of ~MV/cm. Such strong fields make it possible to use THz waves as the driving light source for nonlinear polarization of the medium, which in turn leads to the development of the emerging terahertz Kerr effect (TKE) spectroscopy technique. Many low-frequency molecular motion modes, such as the collective directional motion of molecules and the cooperative motion under the constraint of weak intermolecular interactions, are resonantly excited to unprecedentedly strong amplitudes driven by the THz electric field. Thereby the collected responses are increased. The TKE technique thus creates an interesting prospect for investigating low-frequency dynamics in these media. In view of this, this paper firstly summarizes the research work on the measurement mechanism of TKE spectroscopy by taking the solid material without low-frequency molecular dynamics process as an example. Starting from the principle of TKE technology and the exploration of the properties of solid matter using this technology, its application in the exploration of low-frequency molecular dynamics of liquid water and aqueous solutions is introduced. Liquid water is considered the building block of life and possesses many extraordinary physical and biochemical properties. Its hydrogen bonding network plays a crucial role in these properties. It is generally believed that the ability of water to form complex hydrogen-bonding networks is the main reason for its various kinetic and thermodynamic properties that are different from other liquids. However, the exact structure of the hydrogen-bonding network, the spatial extent of its existence, and the associated timescale are not known. And the relevant spectral information of the basic properties of the reaction water is still not known. Therefore, it is of great significance to evaluate the hydrogen bond-related kinetic properties of liquid water by optical means.

This review critically examines the various ways in which the mechanical properties of wood have been understood. Despite the immense global importance of wood in construction, most understanding of its elastic and inelastic properties is based on models developed for other materials. Such models neglect wood’s cellular and fibrous nature. This review thus questions how well models that were originally developed for homogeneous and effectively continuous materials can describe wood’s mechanical properties. For example, the elastic moduli of wood have been found by many authors to depend on the size of the test specimen. Such observations are incompatible with classical elasticity theory. There is also much uncertainty about how well elastic moduli can be defined for wood. An analysis of different models for size effects of various inelastic properties of wood shows that these models only approximate the observed behaviour, and do not predict or explain the scatter in the results. A more complete understanding of wood’s mechanical properties must take account of it being in some sense intermediate between a material and a structure.

The wide use of cadmium (Cd) in industry causes great environmental health problems to humans and animals. The aim of this study was to investigate the protective effects of Xylopia aethiopica fruit ethanol extract (XAFEE) on cadmium-induced inflammation and dyslipidemia in male albino rats. Thirty albino rats weighing 120–180 g were randomly selected into six groups (n = 5): control rats (administered distilled water only), Cd alone group (10 mg/ kg bw), Cd + 150 mg/kgbw XAFEE, Cd + 300 mg/kgbw XAFEE, 150 mg/kgbw XAFEE and 300 mg /kgbw XAFEE groups after 2-week acclimatization. The experiment lasted for 21 days, after which blood sample was collected by cardiac puncture. Changes in tumor necrosis factor (TNF-α), interleukin 10 (IL-10), total cholesterol (TC), triacylglycerol (TAG), phospholipids and free fatty acids (FFAs) concentrations in serum were determined. The results of the present study indicated that Cd exposure remarkably increased (p < 0.05) the TC, TAG, phospholipids, FFAs and TNF-α concentrations, and significantly decreased IL-10 concentration (p < 0.05). These findings suggest that inflammatory changes and alterations in lipid metabolism might be one of the mechanisms underlying the subtle effects of Cd toxicity, “dyslipidemia.” XAFEE expressed protective role against toxic influence of Cd on affected parameters in rats. The results raised the possibility of Xylopia aethiopica fruit being considered as a condiment in soup, local drinks, supplements or herbs preparations in areas where there are chances of Cd exposure, occupationally or environmentally.

The wide use of cadmium (Cd) in industry causes great environmental health problems to humans and animals. The aim of this study was to investigate the protective effects of Xylopia aethiopica fruit ethanol extract (XAFEE) on cadmium-induced inflammation and dyslipidemia in male albino rats. Thirty albino rats weighing 120–180 g were randomly selected into six groups (n = 5): control rats (administered distilled water only), Cd alone group (10 mg/ kg bw), Cd + 150 mg/kgbw XAFEE, Cd + 300 mg/kgbw XAFEE, 150 mg/kgbw XAFEE and 300 mg /kgbw XAFEE groups after 2-week acclimatization. The experiment lasted for 21 days, after which blood sample was collected by cardiac puncture. Changes in tumor necrosis factor (TNF-α), interleukin 10 (IL-10), total cholesterol (TC), triacylglycerol (TAG), phospholipids, free fatty acids (FFAs) and HDL-TAG concentrations in serum were determined. The results of the present study indicated that Cd exposure remarkably increased (p < 0.05) the TC, TAG, phospholipids, FFAs, HDL-TAG, TNF-α concentrations, and significantly decreased IL-10 concentration (p < 0.05). These findings suggest that inflammatory changes and alterations n lipid metabolism might be one of the mechanisms underlying the subtle effects of Cd toxicity, “dyslipidemia.” XAFEE expressed protective role against toxic influence of Cd on affected parameters in rats. The results raised the possibility of Xylopia aethiopica fruit being considered as a condiment in soup, local drinks, supplements or herbs preparations in areas where there are chances ofCd exposure, occupationally or environmentally.

Currently, a large part of the wells for agricultural use located in the state of Sonora are overexploited, which generates a high degree of saline intrusion and abandonment by nearby communities. In this paper the temperature effect on the final concentration of permeate water was evaluated through voltage and intel concentration variations in a batch electrodialysis reversal process (EDR), in order to identify optimal operating conditions with emphasis on the reduction of energy consumption and cost of desalinated water. Thirty-six samples were prepared: eighteen 2,000 mg/L total dissolved solids (TDS) samples and eighteen 5,000 mg/L TDS samples; brackish well water of 639 mg/L TDS and synthetic salt were mixed to obtain those concentrations. 3 different temperatures (25, 30, 35 °C) and 2 different voltages (10 and 20 V) were tested for each sample. The best salt removal occurred in the 20 V arrays, with 18.34% higher removal for 2,000 mg/L TDS experiments and 25.05% for 5,000 mg/L experiments (average between the 25 to 35 °C tests). Temperature positively affected EDR, especially in the experiments at 10 V voltage, where increasing 10 °C increased its efficiency by 10.83% and 24.69% for 2,000 and 5,000 mg/L TDS, respectively. Energy consumption was lower with increasing temperature (35 °C), as it decreased by 1.405% and 1.613% for 2,000 and 5,000 mg/L TDS concentrations, respectively (average between 10 and 20 V tests), decreasing the cost per m3 of water.