This manuscript reviews two decades of projects funded by the Kirkhouse Trust (KT), a charity registered in the UK. KT was established to improve the productivity of legume crops important in African countries and in India. KT’s requirements for support are: 1) the research must be done by national scientists in their home institution, either a publicly funded agricultural research institute or a university; 2) the projects need to include a molecular biology component, which to date has mostly comprised the use of molecular markers for the selection of one or more target traits in a crop improvement programme; 3) the projects funded are included in consortia, to foster the creation of scientific communities and the sharing of knowledge and breeding resources. This account relates to the key achievements and challenges, reflects on the lessons learned and outlines future research priorities.

In the history of high-performance polymer composite parts with continuous in-plane fibre reinforcement, the comparatively moderate structural-mechanical properties in their out-of- plane-z-direction and the limited load carrying capability between individual reinforcement layers within the laminated structures have always been one of the greatest challenges. Plenty of research work has been carried out to improve load transfer capability as well as fracture toughness for crack opening events between the reinforcement layers by means of out-of-plane fibre reinforcement implementation, for example by sewing or z-pinning technologies. However, the results have not become established across a wide range of applications so far, because the technologies used have led to considerable losses of in-plane strength properties. In this paper first results are presented for a new method of a low fraction z-fibre reinforcement by means of very thin diameter laser drilled holes filled with short carbon fibres, demonstrating potential to improve Mode II fracture toughness.

The safety of vegetable food is compromised by various factors, including the inefficient or excessive use of sanitizers. Instances of individuals falling ill after consuming raw vegetables have been reported, with outbreaks of diseases caused by pathogens on fresh vegetables becoming increasingly prevalent globally, attracting significant media coverage and impacting the economic viability of vegetable cultivation. Measures to enhance food safety in postharvest horticultural produce involve controlling microbial proliferation and minimizing cross-contamination. Sanitizers were utilized in the food safety arsenal for a variety of purposes, including pathogen elimination and microbe reduction, hand, tools, and vegetable contact surface cleaning, and produce shelf life extension. Choosing an appropriate sanitizer for all vegetables is difficult due to a lack of knowledge on which sanitizers are ideal for the many types of vegetables grown on farms under different environmental circumstances. Although chlorine-based sanitizers, such as sodium or calcium hypochlorite, have been widely used for the past 50 years, recent research has revealed that chlorine reacts with an organic compound in fresh vegetables to produce trihalomethane, a carcinogen precursor, and as a result, many countries have prohibited the use of chlorine in all foods. As a result, horticulture research groups worldwide are exploring for non-chlorine, ecologically friendly sanitizers for the vegetable industry. They also want to understand more about present procedures in the vegetable business for employing alternative sanitizers, as well as the efficacy and potential dangers to the food safety of fresh salad vegetables. This review-cum-research paper presented detailed information on non-chlorine sanitizers, such as their efficacy, benefits, drawbacks, regulatory requirements, and the need for additional research to lower the risk of marketed salad vegetable food safety.

The theories of Evolution and Big Bang have brought a major impact upon the scientific and societal perception upon the origins, abilities and roles of mankind on Earth. It is conclusively evident that Mother Nature and the physical realm is autonomous and all phenomena in the world occur without an imposition against the “free will” of such events and patterns. Nevertheless, this extent of freedom does not imply that life on Earth represents an accident and has no purpose. By careful analysis of ancient religious texts, it can be suggested even otherwise, that it is especially free will that is offered as a gift from outside of the physical dimensions of existence, with the purpose of a continuous edification and improvement of the overall life conditions and of the human perception. It may be that the multi-generational focus on improvement and progress have been misattributed as a long-term evolution of species, that humans came from animal ancestors and that there is a blurred line associating humans with animals. Furthermore, it may be that scientists based their suggestions that no outside Creator would have brought the Earth into existence on physical perspectives, when the extra-dimensional process of Creation implies that all elements of the physical existence undergo a process of Creation from the outside, where time, space and physical matter do not exist, in spite of such elements possibly reflecting unseen elements of the meta-physical world. Finally, there is the following example that deserves attention within the scientific community; just because all living cells - human, animal and plant - contain DNA chromosomes, ribosomes, mitochondria and a plasma membrane, it does not indicate that humans are animals, just as this does not indicate that plants are animals. In Science, there is a golden statement, that correlation does not imply causation. This example is in complete agreement with the verses of the Book of Genesis in the Holy Scriptures regarding the origins of life; namely, that animals could have been created by an Author of all life on Earth so that man would experience companionship. An improved scientific perception of the timeline of life on Earth may be reached via an approach that combines molecular biology with quantum physics, given that the three layers of Science - Biology, Chemistry and Physics - together with their foundational layer of Mathematics, are in fact situated in a relationship of complete harmony.

We describe a new approach for integrating multiple views of data into a common latent space using non-negative tensor factorization (NTF). This approach, which we refer to as the "Integrated Sources Model" (ISM), consists of two main steps: embedding and analysis. In the embedding step, each view is transformed into a matrix with common non-negative components. In the analysis step, the transformed views are combined into a tensor and decomposed using NTF. Noteworthy, ISM can be extended to process multi-view data sets with missing views. We illustrate the new approach using two examples: the UCI digit dataset and a public cell type gene signatures dataset, to show that multi-view clustering of digits or marker genes by their respective cell type is better achieved with ISM than with other latent space approaches. We also show how the non-negativity and sparsity of the ISM model components enable straightforward interpretations, in contrast to latent factors of mixed signs. Finally, we present potential applications to single-cell multi-omics and spatial mapping, including spatial imaging and spatial transcriptomics, and computational biology, which are currently under evaluation. ISM relies on state-of-the-art algorithms invoked via a simple workflow implemented in a Jupyter Python notebook.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

The design of a mixed-mode proportional-integral-derivative (PID) controller circuit using current-feedback operational amplifiers (CFOAs) as active components is proposed. With the same circuit topology, the proposed configuration of three CFOAs, four resistors, and two capacitors is capable of performing the PID controller in all four operation modes: namely voltage mode, trans-admittance mode, current mode, and trans-impedance mode. Numerous mathematical analyses are conducted to determine the controller performance under ideal and non-ideal conditions. Additionally, the mixed-mode second-order lowpass filter is suggested, and also used to examine the workability of the proposed mixed-mode PID controller in a feedback control structure. The proposed PID controller is implemented with the commercially available IC-type CFOA AD844, and the simulation results are presented to illustrate the functionality of the controller and its closed-loop control system.

Patients with predominantly antibody deficiencies (PAD) display hypogammaglobulinemia with a high prevalence of infections, along with autoimmune manifestations, benign and malignant lymphoproliferation and granulomatous disease. It is noteworthy that PAD patients, even those with defects in the same causative genes display a variable clinical phenotype, suggesting that additional genetic polymorphisms, located in either immune-related or non-immune-related genes, may affect their clinical and laboratory phenotype. In this context, we analyzed 80 PAD patients, including 70 with common variable immunodeficiency (CVID) for SERPINA1 defects, in order to investigate their possible contribution to PAD clinical phenotype. Eight CVID patients carried heterozygous pathogenic SERPINA1 defects with normal alpha-1 antitrypsin levels. Interestingly, the presence of the Z allele (rs28929474) which was found in three patients, was significantly associated with liver disease; hepatic complications were also observed in patients carrying the p.Leu23Gln (rs1379209512) and the p.Phe76del (rs775982338) alleles. Conversely, no correlation of SERPINA1 defective variants with respiratory complications was observed, although patients with pathogenic variants exhibit a reduced probability of developing autoimmune diseases. Therefore, we recommend SERPINA1 genetic analysis in PAD, in order to identify patients with a higher risk for liver disease.

In recent years, thanks to continuous technological development, temperature data loggers have been used to collect data from the breeding progress of birds, which can be used, e.g. to obtain information on the length of incubation breaks, to detect the start of incubation or to record unsuccessful breeding. Temperature data loggers have been used in various types of bird nests, but not in a „closed“ nests such as a burrow or cavity. The study presents the results of using a temperature data loggers in natural nest holes of the common kingfisher (Alcedo atthis). Their nests, which lack substantial insulating structures, are primarily influenced by the relatively stable soil temperature. The temperature of the space inside a nest chamber was measured on a continuous basis with an interval of 1 minute between measurements. The measurement was carried out from egg laying/incubation to a successful leave of the nest chamber/death of chicks (5 nests on 3 different streams in 3 breeding seasons). The temperature curves showed the laying of the eggs, the start of incubation, the successful flight out of the nest chamber or the death of the chicks in the nest chamber. It was not always possible to determine exactly when the chicks hatched from the temperature data.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

The sheer number of gene variants and the extent of the observed clinical and molecular heterogeneity recorded in neuropsychiatric disorders (NPDs), could be due to the magnified downstream effects initiated by a smaller group of genomic higher order alterations in response to endogenous or environmental stress. Chromosomal common fragile sites (CFS) are functionally linked with microRNA’s, gene copy number variants (CNVs), sub-microscopic deletions and duplications of DNA, rare single-nucleotide variants (SNVs/SNPs) and small insertions/deletions (indels), as well as chromosomal translocations, gene duplications, altered methylation, microRNA and L1 transposon activity and 3-D chromosomal topology characteristics. These genomic structural features have been linked with various NPDs in mostly isolated reports, and have usually only been viewed as areas harboring potential candidate genes of interest. The suggestion to use a higher level entry point, (the ‘fragilome’ and associated features), activated by a central mechanism (‘stress’) for studying NPD genetics, has the potential to unify the existing vast number of different observations in this field. This approach may explain the continuum of gene findings distributed between affected and unaffected individuals, the clustering of NPD phenotypes and overlapping comorbidities, the extensive clinical and molecular heterogeneity and the association with certain other medical disorders.

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

Dissimilar welds between ferritic and austenitic steels represent a good solution for exploiting the best performance of stainless steels at high and low temperatures and in aggressive environments, while minimizing costs. Therefore, they are widely used in nuclear and petrochemical plants, however, due to the different properties of the steels involved, the welding process can be challenging. Fusion welding can be specifically addressed to connect low-carbon, or low-alloy steels, with high-alloy steels, which have similar melting point. Welding of thick plates can be performed with electric arc in multiple passes or in a single pass by means of a laser beam equipment. Since microstructure and consequently mechanical properties of the weld are closely related to composition, the choice of the filler metal and processing parameters, which in turn affects the dilution rate, plays a fundamental role. Numerous technical solutions were proposed for welding dissimilar steels and much research was developed on the weldment metallurgy; therefore, this article is aimed at a review of the most recent scientific literature on the issues relating to the fusion welding of ferritic / austenitic steels. Two specific sections are dedicated respectively to electric arc and laser beam welding; finally, metallurgical issues, related to dilution and thermal field are debated in the discussion section.

The ANSYS 2024R1 student edition was used to create a finite element model of a basketball rim and backboard. This finite element model included the use of steel for the rim and its mount, a tempered glass backboard, and an aluminum frame behind the backboard. After a mesh was created, fixed support boundary conditions were applied to the four corners of the aluminum frame. The subsequently calculated mode shapes and frequencies were compared to empirical modal analysis previously done at the United States Military Academy at West Point, New York. Four mode shapes and frequencies agreed rather well between the theoretical finite element analysis and previously published empirical modal analysis, specifically where the rim was vibrating in the vertical direction, which was the direction that the accelerometer was aligned for modal analysis. However, three mode shapes missed by the empirical modal analysis were found where the vibration of the rim was confined to the horizontal plane, which was orthogonal to the orientation of our accelerometer.

Emerging data support associations between depletion of the healthy gut microbiome and aging-related physiological decline and disease. In humans, fecal microbiota transplantation (FMT) has been used successfully to restore gut microbiome structure and function to treat C. difficile infections, but application to healthy aging has been scarcely investigated. The marmoset is an excellent model for evaluating microbiome-mediated changes with age and interventional treatments due to their relatively shorter lifespan and many social, behavioral, and physiological functions that mimic human aging. This review 1) provides an overview of the rationale for FMT to support healthy aging using the marmoset as a translational geroscience model, 2) summarizes prior use of FMT in marmosets, 3) outlines a protocol for studying FMT in aging marmosets, and 4) describes knowledge gaps and future research needs in this field.

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley, one in the west/northwest, the other in the southeast. Wavelet analysis revealed the annual cycle to be most persistent temporal mode of PM10 variability in both subregions, with intermittent signals observed at time scales of around 120, 30~90 and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere.

Common rust (CR), caused by Puccina sorghi, is one of the major foliar diseases in maize, leading to quality deterioration and yield losses. To dissect the genetic architecture of CR resistance in maize, this study utilized the susceptible temperate inbred line Ye107 as the male parent crossed with three resistant tropical maize inbred lines (CML312, D39, and Y32) to generate 627 F7 recombinant inbred lines (RILs), aiming to identify maize disease-resistant loci and candidate genes for common rust. Phenotypic data exhibited good segregation between resistance and susceptibility, with varying degrees of resistance observed across different subpopulations. Significant genotype effects and genotype × environment interactions were noted with heritability ranging from 85.7% to 92.2%. Linkage analysis and genome-wide association analysis across three environments identified 20 QTLs and 62 significant SNPs. Among them, seven major QTLs explained 66% of the phenotypic variance. Comparison with six SNPs repeatedly identified across different environments revealed overlap between qRUST3-3 and Snp-203,116,453, and Snp-204,202,469. Haplotype analysis indicated two significantly different haplotypes for CR resistance for both of these SNPs. Based on LD decay plots, three co-located candidate genes, namely Zm00001d043536, Zm00001d043566, and Zm00001d043569, were identified within 20 kb up-stream and downstream of these two SNPs. Zm00001d043536 regulates hormone regulation, Zm00001d043566 controls stomatal opening and closure, related to trichome, and Zm00001d043569 is associated with plant disease immune responses. Additionally, we performed candidate gene screening for five additional SNPs repeatedly detected across different environments, resulting in the identification of five candidate genes. These findings contribute to the development of genetic resources for common rust resistance in maize breeding programs.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

With the increasing of China's international status and the acceleration of the process of global economic integration, the internationalization strategy of Chinese enterprises is getting deeper and deeper. This paper analyzes the problems and challenges faced by the international supply chain management of Chinese bamboo weaving and creative products, and puts forward a set of supply chain management model that ADAPTS to the international development. Firstly, the concept, connotation and types of supply chain management are sorted out through literature review. Secondly, this paper analyzes the current situation of international supply chain management of bamboo editing and creative products, and points out the existing problems. Thirdly, based on the theory and practice of international supply chain management, this paper puts forward a set of supply chain management model suitable for the international development of bamboo editing and creative products. Finally, taking a bamboo weaving and creative products enterprise as an example, the application effect of the supply chain management model is empirically analyzed. The results show that the supply chain management model can effectively reduce the cost and improve the efficiency, and is conducive to the international development of bamboo editing and creative products.

Background: Endoscopic sphincterotomy (EST) has been employed for the endoscopic treatment of common bile duct stones (CBDSs), and a high success rate of stone removal has been reported. However, EST is associated with the risk of bleeding, perforation, and sphincter of Oddi function disruption. To avoid these risks, endoscopic papillary balloon dilation (EPBD) is an option for CBDS. Sphincter of Oddi function preservation decreases long-term biliary infection and gallstone recurrence. EPBD may have advantages in children who require a long follow-up. However, there have been few reports on pediatric cases, particularly in infants. Methods: From September 2017 to December 2023, we performed EPBD for four pediatric CBDSs. The patients were aged from 5 months to 8 years; including two infants aged 5 and 6 months. Furthermore, we reviewed the stone removal rate and complications of 545 ESTs performed at high-volume centers and 13 EPBD-reported cases in children with CBDSs. Results: CBDSs of all patients who underwent EPBD in our institution were successfully removed. No bleeding or perforation was noted, and pancreatitis was observed in three patients. In an analysis of 545 ESTs in children, the stone removal rate was high, ranging from 83% to 100% (mean, 96%). The incidence of pancreatitis was 0%–9.6% (mean, 4.4%), and the grade of pancreatitis was almost mild. The bleeding frequency was 1.3%–5.4% (mean, 2.7%). According to the grade of bleeding, seven and four cases were mild (64%) and moderate (36%), respectively, Compared with adult cases who underwent EST, the frequency of pancreatitis and bleeding was almost similar in children.; however once bleeding occur, it has a higher risk of leading to blood transfusion in children. Stone removal by EPBD in children was 100% successful. All complications were pancreatitis, and its frequency was 46% (6/13 patients, including five mild cases and one moderate case), which is higher than that of EST and adult cases who underwent EPBD. In most children with pancreatitis, pancreatic enzyme levels returned to normal within 2–3 days following EPBD, and no severe cases caused by EPBD were reported. Conclusions: CBDS removal by EPBD in children has a high success rate with very low risk of bleeding and perforation. Although pancreatitis frequently occurs, most cases are mild. Sphincter of Oddi function preservation by EPBD is expected to prevent long-term stone recurrence and biliary tract infection, and EPBD is considered an effective method for CBDS removal in children.

Predominantly antibody deficiencies (PAD) represent the most common type of primary immu-nodeficiencies in humans, characterized by a wide variation in disease onset, clinical manifesta-tions, complications and outcome. Considering that the prevalence of PAD in Greece is unknown and there is limited knowledge on clinical and laboratory characteristics of affected patients, we conducted a nationwide study, including 153 patients (male/female: 66/87; median age: 43.0 years; range: 7.0-77.0) diagnosed and/or followed-up between April 2007 to September 2023. Furthermore, we classified our cohort into five Groups according to their medical history, im-munoglobulin levels, and CTLA4-mutational status: 123 had common variable immunodeficien-cy (CVID), 12 with CVID-like disease (with a history of a previous B-cell depletion immunother-apy for autoimmune or malignant disease), seven with combined IgA and IgG subclass deficien-cies, five with immune dysregulation syndrome and CTLA4 defects, and six with unclassified hypogammaglobulinemia. We demonstrated a remarkable delay of PAD diagnosis, several years after the onset of related symptoms (median: 9.0 years, range: 0-43.0). Family history of PAD was only 11.8%, with the majority of patients considered sporadic cases. Most patients were diag-nosed in the context of a diagnostic work-up for recurrent infections, or recurrent/resistant auto-immune cytopenias. Interestingly, ten patients (5.6%) had no history of infection, diagnosed due to either recurrent/resistant autoimmunity, or during a work-up of their medical/family history. Remarkable findings included an increased prevalence of lymphoproliferation (60.1%) and atopy (24.2%), while 39 patients (25.5%) developed bronchiectasis and 16 (10.5%) granulomatous dis-ease. Patients with CTLA4 defects displayed a variable clinical phenotype at diagnosis, with four patients diagnosed during a work-up of re-current infections, while one also displayed a massive splenomegaly. Cancer was a common complication in our cohort (25 patients, 16.3%), with B-cell malignancies representing the most common neoplasms (56.7%). Our findings indicate the necessity of awareness about PAD and their complications, aiming for early diagnosis and appropriate management of affected patients

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the Kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the Kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously-emitted thermal fluctuations and the background turbulence leads to the formation of non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the Kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

The antimicrobial quantitative structure–activity relationship of plant flavonoids against Gram-positive bacteria was established in our previous works, and the cell membrane was confirmed as a major site of action. To investigate whether plant flavonoids have similar antibacterial effects and mechanisms against both Gram-negative and Gram-positive bacteria, here, the minimum inhibitory concentrations (MICs) of 37 plant flavonoids against Escherichia coli were determined using the microdilution broth method, and then the correlation between their lipophilic parameter ACD/LogP or LogD_7.40 value and their MIC was analyzed. Simultaneously, the correlation between the ACD/LogP or LogD_7.40 value and the MIC of 46 plant flavonoids reported in literature against E. coli was also analyzed. Both sets of results showed that there is a significant correlation between the LogP value and the MIC of plant flavonoids against Gram-negative bacteria. However, it is difficult to effectively predict the MIC of plant flavonoids against Gram-negative bacteria from their lipophilic parameters. By comparing two regression curves derived from plant flavonoids against Gram-negative and Gram-positive bacteria, it was further discovered that the antibacterial activities of most plant flavonoids against Gram-negative bacteria are stronger than those against Gram-positive bacteria when their LogP values are less than about 3.0, but the opposite is true when their LogP values are more than about 3.6. Moreover, this comparison also suggests that unlike mainly acting on the cell membrane of Gram-positive bacteria, plant flavonoids have multiple mechanisms against Gram-negative species, while the cell membrane is also an important action site among them. Combined with the correlation analyses between the enzyme inhibitory activity and the LogP value of the reported flavonoids, it was further suggested that DNA gyrase is another important target of plant flavonoids against Gram-negative bacteria.

In this paper, a low-power Injection-Locked Clock and Data Recovery (ILCDR) using 28nm FDSOI technology is presented. The back-gate auto-biasing of UTBB-FDSOI transistors allows us to create a QRO (Quadrature Ring Oscillator) reducing both size and power consumption. By injecting a digital signal into this circuit, we realize an Injection-Locked Oscillator (ILO) with low jitter. Thanks to the good performance of this oscillator, we propose a low power ILCDR with fast locking time and low jitter for burst-mode applications. The main novelty consists in the implementation of a complementary QRO based on back-gate control using FDSOI technology to realize a simple and efficient ILCDR circuit. With a Pseudo-Random Binary Sequence (PRBS7) at 868Mbps, the recovered clock jitter is 26.7ps (2.3%UIp-p) and the recovered data jitter is 11.9ps (1%UIp-p). With a 0.6V power supply, the power consumption is 318μW. The estimated Chip area is around 6600μm².

Powdery mildew is a severe disease causing substantial yield losses in wheat production worldwide. The Chinese wheat landrace Changanhongmai (CAHM) exhibits high resistance to the physiological race E09 of powdery mildew. This study aims to characterize the powdery mildew resistance gene in CAHM, and develop molecular markers for marker-assisted selection of wheat. To investigate the genetic characteristics of this resistant gene, we developed F1 plants, F2 generation population, and F2:3 families from a cross between CAHM and SY225. Genetic analysis demonstrated that all F1 plants were resistant to the disease, while the ratio of resistant to susceptible plants was 3: 1 in both the F2 population and F2:3 families, indicating that CAHM is inherited in a manner of single dominant powdery mildew resistance gene, which was tentatively designated as PmCAHM. By using bulk segregation analysis, we constructed a genetic map encompassing Xgwm273, Xwmc626, Xgwm11, Xgwm18, Xgdm28, Xgpw7812, Xgpw5195, Xwmc694 and PmCAHM. Among these markers, Xgpw7812 and Xgpw5195 were flanking markers tightly linked to PmCAHM at a genetic distance of 2.5 cM and 8.4 cM, respectively. Furthermore, nullisomic-tetrasomic analysis revealed that PmCAHM is located on chromosome 1B. These results indicate that PmCAHM differs from the internationally recognized powdery mildew resistance genes in both location and source. In addition, a new germplasm/line NW1748 with large seeds and powdery mildew resistance was developed from the cross and back cross populations of Fengyou 1718 (FY1718)/CAHM//FY 1718. Therefore, PmCAHM can serve as a novel powdery mildew resistance source for breeding of wheat by using NW1748 as the donor in the future.

Recognition, decoding and tracking of vortex patterns is of increasing importance in many fields reaching from astronomical observation of distant galaxies to turbulence phenomena in liquids or gases. Currently, coherent light beams with orbital angular momentum (OAM) are of particular interest for optical communication, metrology, micro-machining or particle manipulation. One common task is to identify characteristic spiral patterns in pixelated intensity maps at real-world signal-to-noise ratios. Recently, Fast Fourier Transform (FFT) was applied to the quantitative analysis of spiral interference patterns of OAM beams. Our study considers this approach in more detail. It is demonstrated that specific information can be extracted by combining conformal mapping by polar transform with determining one- or two-dimensional angular frequency spectra either in spatially fixed or scanning mode. Results of proof-of-principle experiments are presented.

This study determines the equivalent stress intensity factor (SIF) model that best fits the experimental behavior of low-carbon steel under mixed mode (I and II). The study assessed Tanaka, Richard, and Pook's equivalent SIF models. The theoretical values used for comparison correspond to experimental results in a modified C(T) geometry by machining a hole ahead of the crack tip subjected to fatigue loads with a load ratio of R = 0.1. The comparison involved the SIF for six experimental points and the values computed through the numerical simulation. The Paris, Klesnil, and modified Forman-Newman crack growth models were used with each equivalent SIF to analyze the prediction in the estimated number of cycles. The Klesnil model showed the closest prediction since the error between the calculated and experimentally recorded number of cycles is the lowest. However, the material behavior reflects a reduced crack propagation rate attributed to plasticity in the crack tip. Results suggest that Asaro equivalent SIF conservatively estimates the element lifespan with increasing errors from 2.3% at the start of growth to 27 % at the end of the calculation.

Air pollution, climate change and global warming show direct linkage. Introduction - Background: Research in the field has proposed and demonstrated their link to increased allergenicity in plants, leading to increased allergic diseases. Allergen patterns are changing in response to climate change. Across Europe, up to 12% of the population suffers from allergic diseases (bronchial asthma and allergic rhinitis) caused by the pollen grains. The medical costs of these types of allergies are enormous and are increasing with the spread of common ragweed - Ambrosia artemisiifolia* in Europe. In practice, more and more patients are turning to allergists. Methods: Based on these data, the research aims to identify safety measures and specific legislation to control and eradicate common ragweed in the countries most affected by the spread of this plant in Europe, increase in population exposure in countries affected by the presence of common ragweed and the socio-economic impact of allergic rhinitis and bronchial asthma at European level.[1][2] Our database search did not reveal any other research that has addressed this topic to date. Results: This research identifies specific legislation to the countries most affected by the spread of this plant pollen grains at European level, changes in allergen patterns and monitoring/safety eradication measures decided by local authorities, and data on the spread of common ragweed over the last two decades, costs per treatment, increased allergic rhinitis and bronchial asthma morbidity in the most affected areas. Conclusions: At European level, there are no universally valid models for eradicating this weed. Various methods can be used to limit the spread of common ragweed and its pollen production (e.g. mowing once or twice a year of overgrown land, ploughing, chemical control, public information, etc.). Local and regional cooperation should be considered essential to promote phytosanitary & safety measures and exchange of information on methods to identify and manage the spread of common ragweed. Unified legislation at European level would help all affected countries; reduce morbidity from respiratory allergic diseases and the costs of treating these diseases.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Background: Distal sensory polyneuropathy (DSP) and distal neuropathic pain (DNP) remain significant challenges for older people with HIV (PWH), necessitating enhanced clinical attention. HIV and certain antiretroviral therapies (ART) can compromise mitochondrial function and impact mitochondrial DNA (mtDNA) replication, which is linked to DSP in ART-treated PWH. Methods: This study investigated mtDNA, mt fission and fusion protein, and mt electron transport chain protein changes in the dorsal root ganglion (DRG) and sural nerve (SuN) from 11 autopsied PWH. In antemortem standardized assessments, six had no or one sign of DSP, while five exhibited two or more DSP signs. Digital droplet polymerase chain reaction (ddPCR) measured mtDNA quantity and the common deletion (CD) in isolated DNA. Results: We found lower mtDNA copy numbers in DSP+ donors. SuN exhibited a higher proportion of mtDNA CD than DRGs in both groups. Mitochondrial electron transport chain (ETC) proteins were altered in DRG of DSP+ compared to DSP- donors, particularly complex I. Conclusion: These findings suggest reduced mtDNA quantity and increased CD abundance may contribute to DSP in PWH, indicating diminished mitochondrial activity in sensory neurons. Accumulated ETC proteins in the DRG imply impaired mitochondrial transport to the sensory neuron's distal portion. Identifying molecules to safeguard mitochondrial integrity could aid in treating or preventing HIV-associated peripheral neuropathy.

Tribenuron-methyl is used extensively in Iranian cereal cropping systems under rainfed conditions. However, there is little information on the soil persistence and carryover of this herbicide and its phytotoxicity to subsequent crops in the rotation. This study was carried out with the aim of investigating the sensitivity of different chickpea cultivars to tribenuron-methyl and also finding alternative crops. In field experiments, the chickpea fields of Ravansar County, Kermanshah province, Iran were monitored during 2023-2022, and the growth of chickpea in response to residues of tribenuron-methyl used in the previous wheat crop was evaluated. Furthermore, in a greenhouse experiment, the effect of various concentrations of tribenuron-methyl on the growth of chickpeas, lentil and common vetch was investigated. In all the investigated species in this study, presence of tribenuron-methyl decreased plant growth. Ttotally, among examined crop species, lentil had a higher tolerance to tribenuron-methyl followed by common vetch and chickpea varieties. Bivanij chickpea variety was more sensitive to the residues of tribenuron-methyl in the soil (30% reduction in grain yield) when compared to the other two varieties, namely Mansour and Adel. Based on the results of this study, residues of tribenuron-methyl applied in wheat fields is the main responsible factor reducing the height of chickpea in rai-fed cropping systems of western Iran. It is recommended to replace lentil and common vetch with chickpeas in rotation with wheat in soils heavily contaminated with the residues of tribenuron-methyl.

Abstract：The brain often switches freely between focused attention and divergent thinking, and the default mode network (DMN) is activated during brain rest. The discovery, function and characteristics of default mode network all indicate that learning does not stop when the brain "rests". Mental disease can lead to dysfunctional default mode networks, which affects learning adversely. Therefore, default mode network plays an important role in learning. Neural activities such as β-wave rhythm regulation, "subconscious" divergence mode initiation, hippocampal function and neural replay occur during default mode, which also explain that "rest" promotes learning. This paper reveals the role and neural mechanism of default mode network in learning from the neural level, discusses the essential role default mode network plays in learning, and default mode network enables rest to promote learning.

The electrical energy supply relies on the satisfactory operation of insulators. The ultrasound recorded from insulators in different conditions has a time series output, which can be used to classify faulty insulators. The random convolutional kernel transform (Rocket) algorithms use convolutional filters to extract various features from time series data. This paper proposes the combination of Rocket algorithms, machine learning classifiers, and empirical mode decomposition (EMD) methods, such as complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), empirical wavelet transform (EWT), and variational mode decomposition (VMD). The results show that the EMD methods combined with MiniRocket, significantly improve the accuracy of logistic regression in insulator fault diagnosis. The proposed strategy achieves respectively an accuracy of 0.992 using CEEMDAN, 0.995 with EWT, and 0.980 with VMD. These results highlight the potential of incorporating EMD methods in insulator failure detection models to enhance the safety and dependability of power systems.

This study aimed to determine the correlation of colour M-mode velocity propagation in the assessment of left ventricular diastolic function among acute decompensated heart failure patients with preserved ejection fraction (HFpEF). This research is an observational analytical study using a cross–sectional study design conducted from April to June 2022. The subjects of this study were patients diagnosed with acute HFpEF and treated at Dr. Soetomo General Academic Hospital, Surabaya. Patients with heart rhythm disturbances, moderate to severe valvular heart disease, and congenital heart defects were excluded from this study. Patients were measured for diastolic function including mitral valve early mitral inflow velocity (MV E Velocity), mitral peak velocity of early filling (E’) (E' Septal and E' Lateral), left atrial volume index (LAVI), The maximal tricuspid regurgitation velocity (TR V Max), Vp, the ratio of early diastolic mitral inflow velocity to early diastolic mitral annulus velocity (E/E'), the ratio between early and late ventricular filling velocity (E/A) and E/Vp Ratio. N-terminal-pro hormone B-type natriuretic peptide (NT–ProBNP) examination was also performed on study subjects as an additional diagnosis of acute heart failure. There were 33 patients who met the inclusion and exclusion criteria and were included in our study. There were 26 patients (78.8%) with grade I diastolic dysfunction, 4 patients (12.1%) with grade II diastolic dysfunction, and 3 patients (9.1%) with grade III diastolic dysfunction. There is a strong positive correlation between Vp with parameters E' Septal (p = < 0.001; r = 0.636) and E' Lateral (p = < 0.001; r = 0.650). Vp is negatively correlated with the ratio E/E' (p = 0.029; r = –0.37). The PCWP estimate with E/Vp ratio had a strong correlation with the NT–Pro BNP value > 300 pg/ml in acute HFpEF patients (p = < 0.001; r = 0.726) compared to the PCWP estimate with E/E' (p = < 0.001; r = 0.549). There is no correlation between Vp value and degree of diastolic dysfunction in patients with acute HFpEF.

a sensorless control scheme based on novel power converging law sliding mode observer is suggested to realize the sensorless control for the permanent magnet synchronous motor (PMSM). Firstly, by introducing a new power converging law, the problem of slow converging speed/large chattering value dilemma in the conventional converging law is solved; Secondly, in view of the shortcomings of the conventional position and speed estimation algorithm, the high-frequency buffeting in the sliding mode observer will be expanded, a phase-locked loop (PLL) velocity and position estimation strategy is adopted to replace it. Finally, through Matlab/Simulink modeling and motor speed regulation platform experimental results, the sensorless position and speed estimation technology proposed in this paper can respond to the starting speed command of 1000 r/min within 0.05 s, and the starting process has no overshoot. When disturbed by 10Nm loading, the speed fluctuation value can be controlled within 1%.

Carbon fiber reinforced polymer (CFRP) bending structure is widely used in the aviation field. The occurrence and propagation of delamination damage will reduce the safety of in-service bending structures. As a detection tool with high damage sensitivity, Lamb wave can effectively identify delamination damage. In this study, the signal difference coefficient (SDC) was introduced to quantify delamination damage and evaluate the sensitivity of A0 and S0 mode lamb waves to delamination damage. The simulation results show that compared with the S0 mode Lamb wave, the A0 mode Lamb wave exhibits higher delamination damage sensitivity. The delamination damage can be quantified based on the strong correlation between the SDC and the delamination damage size. The control effect of the linear array PZT phase time-delay method on Lamb wave mode was investigated by simulation. The phase time-delay method realizes the generation of a single-mode Lamb wave, which can separately excite the A0 mode and S0 mode Lamb wave to identify delamination damage of different sizes. The A0 mode Lamb wave was excited by the developed one-dimensional linear comb transducer (LCT), which was used to conduct the detection experiment on the CFRP bending plate with delamination damage sizes of Φ6.0 mm, Φ10.0 mm, and Φ15.0 mm. The experimental results verify the correctness of the simulation. According to the Hermite interpolation results of the finite-element simulation data, the relationship between the delamination damage size and the SDC was fitted by the Gaussian function, which can accurately quantify the delamination damage. The absolute error of the delamination damage quantification with fitting expression is not larger than 0.8 mm, and the percentage error is not more than 8%.

A novel reinforcement learning deep deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in the attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the studied quadrotor is derived and the attitude control problem is described by formulas. Second, a sliding mode controller including its sliding mode surface and reaching law is selected for the nonlinear dynamic system, and the stability of the designed SMC system is supported by Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adjust the switching control gain adaptively. During the training process, the input signals of agent are the actual and desired attitude angles, and the output action is the time-varying control gain. Finally, the above trained agent is applied to the SMC as a parameter regulator, to implement the adaptive adjustment of the switching control gain related to reaching law, and the simulation results verify the robustness and effectiveness of the proposed DDPG-SMC method.

We use COMSOL Multiphysics software to model optical processes in media and the effects of light propagation in whispering gallery mode resonators (WGMRs). Although plane wave irradiating on resonator does not create resonances, it was shown that they can be obtained when focused tangentially on the perimeter of the resonator. We demonstrate that resonances can be excited in resonators by prism coupling when the incident angle of the light is larger than the angle of total internal reflection. We determined the optimal distance between the prism and the resonator to get the strongest resonances. Bio-sensing principle of WGMRs is shown by demonstrating that the shift of resonances increases with a larger number of "bio-molecules" attached to the surface of WGMR. Surface functionalization and surface roughness were explored.

The utilization of smart IoT devices, commonly referred to as digital twins, is aimed at the digitalization of human knowledge within aquaculture processes. This involves the incorporation of cutting-edge technologies, including information-based management with big data and modeling, to automate machinery and gain comprehensive insights into the aquaculture environment and fish farm conditions. The ultimate objective is to empower farmers to make informed decisions, furnishing them with objective data to enhance their capacity in monitoring and controlling the various factors impacting fish production. As a result, farming decisions can be fine-tuned to enhance fish health and optimize farm output. In the context of large and modern aquaculture farms, technological innovation becomes imperative to automate processes, minimize labor requirements, and streamline fish feeding operations. Remarkably, the literature currently offers limited discussions on the digital transformation of aquaculture through the application of digital twin methodologies. A prior study underscores the critical influence of factors such as market prices and fish survival rates on the profitability of offshore caging culture. In this study, we embark on an analysis of the prerequisites for establishing a digital twin infrastructure tailored to intelligent fish feeding management. This infrastructure is designed to facilitate the integration of technology and data-driven decision-making, ultimately enhancing the efficiency of fish feeding processes. The proposed architecture for the fish feeding digital twin encompasses various digital twin components, encompassing water quality forecasting, fish population assessment, fish metrics estimation, fish feed prediction, and evaluation of fish feeding intensity. Furthermore, we optimize the daily fish feeding process through reinforcement learning algorithms. Finally, we implement a cloud-based AIoT system that provides the runtime environment for executing digital twins and controlling our intelligent fish feeding machinery. Experimental findings underscore the efficacy of the proposed digital twin system in significantly improving traditional fish feeding processes, notably in terms of reducing food costs and labor requirements.

Our understanding of the divergence of bacteria, archaea, viruses, and mobile elements from the last universal common ancestor (LUCA) has not improved substantially since the crystallization hypothesis (explaining transition from cellular machinery to cellular life) was proposed by Woese. Here, we propose a hypothesis for the simultaneous emergence of bacteria, archaea, viruses, and mobile elements by sequential and concrete biochemical and cellular pathways. According to the hypothesis, the LUCA was a non-free-living pool of single operon type genomes composed of single-stranded (ss) RNA, double-stranded (ds) RNA, RNA/DNA hybrid, ssDNA, or dsDNA at an ancient submarine alkaline vent. Each dsDNA operon was transcribed by different systems in σ, TFIIB, or TBP genomes. Upon the fusion of multiple dsDNA operons by recombinase, the transcription system (in the σ, TFIIB, or TBP genome) was preferentially selected, leading to the first genetic linkage (described by Morgan). Vertical inheritance eventually led to Bacteria (σ genome) and Archaea (TBP genome). Eigen’s paradox (error catastrophe) can be overcome by the parallel gain of DNA replication and DNA repair mechanisms in both genomes. Enlarged DNA enabled efficient local biochemical reactions. Both genomes independently recruited lipids to facilitate reactions by forming coacervates (liquid droplets) at the chamber of the vent, leading to the lipid divide. Bilayer lipid membrane formation, proto-cell formation with a permeable membrane, proto-cell division, and the evolution of membrane-associated biochemistry are presented in detail. Simultaneous crystallization of systems in non-free-living bacteria and non-free-living archaea triggered the co-crystallization of primitive viruses and mobile elements. An arms race between non-free-living cells and primitive viruses finally led to free-living cells with a cell wall and mature viruses at the original vent. Cells and viruses spread to all vents on the planet, explaining the universality of the genetic code on Earth. The proposed scenario provides a plausible explanation for the origin of diverse taxa from the LUCA vertical and horizontal gene transfer.

When overhead lines are impacted by lightning, the traveling wave of the fault contains a wealth of fault information. The accurate extraction of feature quantities from transient components and their classification is fundamental to the identification of lightning faults. The extraction process may involve modal aliasing, optimal wavelet base issues, and inconsistencies between the lightning strike distance and the fault point, which have the potential to impact the effectiveness of recognition. This paper presents a method for identifying lightning strike faults by utilizing Kullback-Leibler (KL) divergence enhanced Variational Mode Decomposition (VMD) and Symmetric Geometry Mode Decomposition (SGMD) improved with Permutation Entropy (PE) to address the aforementioned issues. A model of a 220 kV overhead line is constructed using real faults to replicate scenarios of winding strike, counterstrike, and short-circuit. The three-phase voltage is chosen and then sub-jected to Karenbaren decoupling in order to transform it into zero mode, line mode 1, and line mode 2. The zero mode voltage is decomposed using KL-VMD and PE-SGMD methods, and lightning identification criteria are developed based on various transient energy ratios. The research findings demonstrate that the criteria effectively differentiate between winding strike, counterstrike, and short-circuit faults, thus confirming the accuracy and efficacy of the lightning fault identification criteria utilizing KL-VMD and PE-SGMD.

Spectral image analysis has the potential to replace traditional approaches for assessing plant responses to different types of stress including herbicide, through non-destructive and high-throughput screening (HTS). Therefore, this study was conducted to develop a rapid bioassay method using a multi-well plate and spectral image analysis for diagnosis of herbicide activity and mode of action. Crabgrass (Digitaria ciliaris) as a model weed was cultivated in multi-well plates and subsequently treated with 6 herbicides with different modes of action when they reached the 1-leaf stage, using only a quarter of the recommended dose. To detect plant response to herbicides, plant spectral images were acquired after herbicide treatment using RGB, infrared (IR) thermal, and chlorophyll fluorescence (CF) sensors and analyzed for diagnosing herbicide efficacy and mode of action. Principal Component Analysis (PCA) using all spectral data successfully distinguished herbicides and clustered depending on their modes of action. The performed experiments have shown that the multi-well plate assay combined with spectral image analysis can be successfully applied for herbicide bioassay. In addition, the use of spectral image sensors, especially in CF image, would facilitate HTS by enabling rapid observation of herbicide response, as early as 3 hours after herbicide treatment.

To address the trajectory tracking issue for quadrotors working under the influence of external disturbances, a control scheme is designed for position and attitude trajectory tracking. Firstly, the quadrotor dynamic model is derived for control design. Secondly, adaptive integral backstepping control (AIBS) is employed in the position loop in which adaptive estimation is used to estimate the upper bounds of disturbances. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) is proposed to follow desired Euler angles. The intro-duction of fast nonsingular terminal sliding mode and integral element is to realize fast convergence and accurate tracking. Dead zone technique is applied to minimize estimation errors. Besides, a saturation function is utilized to eliminate chattering phenomenon. Finally, simulation experiments are conducted under the Simulink environment. The proposed control is verified by comparing it with traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS).

This article describes a novel electrochemical on-chip biosensor that utilizes anti-PSA antibody (Ab) and silver nanoparticles (AgNPs) to enhance the sensing and detection capability of prostate specific antigen (PSA) in the blood. The AgNPs are prepared, characterized, and applied onto a silicon photonic on-chip biosensing receptor platform designed to enhance the accurate detection of PSA. The AgNPs were synthesized by a chemical reduction method using silver nitrate (AgNO₃) as the precursor. Transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersion X-ray spectroscopy (EDS), small angle X-ray scattering (SAXS), X-ray diffraction (XRD), and light microscopy were among the methods used in the characterization and analysis of the AgNPs. Each stage of the immunosensor fabrication was characterized using cyclic voltammetry. The proposed immunosensor was applied in the detection of PSA, a prostate cancer biomarker, with a high sensitivity and a limit of detection of 0.17 ng/mL over a linear concentration range of 2.5 to 11.0 ng/mL. The immunosensor displayed good stability and was selective in the presence of interfering species like immunoglobulin (Ig) in human serum, ascorbic acid (AA), and diclofenac (Dic). The detectivity and sensitivity are significantly higher than previous reports on similar or related technologies.

Background: Chronic Myeloid Leukemia (CML) is initiated in bone marrow due to chromosomal translocation t(22;9) leading to fusion oncogene BCR-ABL. Targeting BCR-ABL by tyrosine kinase inhibitors (TKI) have changed fatal CML into an almost curable disease. Despite that, TKIs lose their effectiveness due to disease progression. Unfortunately, mechanism of CML progression is poorly understood and common biomarkers for CML progression are unavailable. This study was conducted to find out novel biomarkers of CML progression by employing whole exome sequencing (WES).Materials and Methods: WES of accelerated phase (AP-) and blast crisis (BC-) CML patients was carried out, with chronic phase CML (CP-CML) patients as control. After DNA library preparation and exome enrichment, clustering and sequencing was carried out using Illumina platforms. Statistical analysis was carried out using [SAS/STAT] software version 9.4 and R package employed to find mutations shared exclusively by all AP-/BC-CML. Confirmation of mutations was carried out using Sanger sequencing and protein structure modelling using I-Tasser followed by mutant generation and visualization using PyMOL. Results: Three novel genes (ANKRD36, ANKRD36B and PRSS3) were mutated exclusively in all AP-/BC-CML patients. Only ANKRD36 gene mutations (c.1183_1184 delGC and c.1187_1185 dupTT) were confirmed by Sanger sequencing. Protein modelling studies showed that mutations induce structural changes in ANKRD36 protein. Conclusions: Our studies show that ANKRD36 is a potential common biomarker and drug target of early CML progression. ANKRD36 is yet uncharacterized in human. It has the highest expression in bone marrow, specifically myeloid cells. We recommend carrying out further studies to explore the role of ANKRD36 in biology and progression of CML.

Electrochemical sensors have been used for many decades. Yet, modeling of such sensors used in electrolysis mode is poorly documented, especially in the case parallel action of multiple gases. Those ones are of great interest since they constitute the first brick to bring information on natures and concentrations of a gaseous mixture composition thanks to grey box modeling of sensors array for example. Based on Butler Volmer’s equations, a model assuming parallel reactions at gold cathode has been introduced in this article and confronted to experimental results. Establishment of the model is based on the extraction of 3 variables: the charge transfer coefficient “α”, the reaction order γ, and the reaction constant rate k0. Tests performed without pollutants and with different concentrations of oxygen could be nicely fitted by the model. Then, the influence of polarization current on the 3 variables of the model has been evaluated showing a clear influence on the constant rate and the reaction order. Also, increasing the polarization current enabled us to get selectivity to oxidant gases. Similarly, the effect of the oxygen concentration was evaluated. Results showed that, in this case, the charge transfer coefficients “α” obtained for oxidant gases is quite different that the ones obtained in the polarization current varying conditions. Therefore, the model will be interesting in situations where polarization current and oxygen content are not varied together. Variation of polarization current can be quite interesting to get increased information for multivariate analysis purpose in constant oxygen content situations. Besides, other parameters have are required for applications in which the oxygen content is bound to change like exhaust gases or combustion.

There is a growing concern about climate change being a serious threat to insurance business sustainability. Knowing if climate warming is a cause for claims and losses increase, and how this cause-effect relationship will develop in the future are two open major questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We measure climate change thanks to the Spanish Actuarial Climate Index (SACI). We use a database containing all the claims caused by hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, monthly number of loss costs equal to one, and monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We try to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change as measured by SACI explains these three dependent variables. We also give an estimation of the increase of the monthly total losses Value at Risk, corresponding to a future increase in climate change measured in units of SACI. Spanish crop insurance managers should carefully incorporate these conclusions into their decision-making process to keep this line of business sustainable in the future.

In recent years, green and healthy foods have attracted much attention. Plant-based foods have become a new trend to replace animal-derived foods. In this study, we used walnut and purple rice as the primary raw materials to produce yogurt. The process included boiling, mixing, grinding, inoculation, fermentation, and sterilization. We then analyzed the similarities and differences between the resulting walnut purple rice yogurt and unfermented walnut purple rice milk, as well as dairy-based yogurt, in terms of physical chemistry, flavor, and sensory characteristics. We also examined the similarities and differences between fermented walnut purple rice milk and conventional warm yogurt. The study results revealed that walnut purple rice yogurt exhibited greater viscosity than walnut purple rice milk and conventional dairy-based yogurt. Additionally, the former displayed enhanced stability and recovery ability. Notably, distinguishable differences were observed between the three types of yogurts in terms of the presence of unknown volatiles and the umami signal as indicated by electronic nose/tongue and GC-IMS analyses. The umami flavour of walnut purple rice yogurt surpasses that of traditional dairy-based yogurt, whilst its salty taste is lower than that of walnut purple rice milk. Despite possessing a weaker aroma than dairy-based yogurt, it is more potent than walnut purple rice milk. Additionally, its relative abundance of olefins, ketones, and alcohols enhances its unique flavour profile, surpassing both other options. Based on sensory analysis, it can be deduced that walnut purple rice yogurt has the highest overall acceptance rate.

Cornelian cherry (Cornus mas L.) fruits, abundant in iridoids and anthocyanins, are natural products with proven beneficial impact on the functions of the cardiovascular system and the liver. The aim of this study is to stipulate and compare whether and to what extent two different doses of resin-purified cornelian cherry extract (10 mg/kg b.w. or 50 mg/kg b.w.) applied in a cholesterol-rich diet rabbit model affect the levels of ATP-binding cassette transporter A1, ATP-binding cassette transporter G1, CCAAT/enhancer binding protein α, sterol regulatory ele-ment-binding protein 1c, fatty acid synthase, endothelial lipase, carnitine palmitoyltransferase 1A, and adiponectin receptor 2 in liver tissue; lipoprotein lipase, visceral adipose tissue-derived serine protease inhibitor, and retinol-binding protein 4 in visceral adipose tissue; resistive index of com-mon carotid arteries and aortas, and histopathological changes in CCAs. Obtained outcomes are referred to the results of our previous works. Moreover, our study, to our knowledge, test the in-fluence of Cornus derivative on CPT1A, AdipoR2, RBP4, LIPG, and vaspin for the first time, with a relevant outcome for the first three. Oral administration of the cornelian cherry extract decreased the SREBP-1c and C/EBPα in both doses. The dose of 10 mg/kg b.w. increased ABCA1 and de-creased FAS, CPT1A, and RBP4, and the dose of 50 mg/kg b.w. enhanced ABCG1 and AdipoR2. Mitigation in atheromatous changes in rabbits’ CCAs was also observed. The beneficial results confirm that cornelian cherry fruit extract may constitute a potentially effective product in the prevention and treatment of obesity-related disorders.

As most of the current dynamic positioning systems are based on model ships, they cannot accu-rately reflect the motion state, position changes, and mutual influence of each part of the dynamic positioning system of actual ships in complex environments. Other actual ships such as cargo ships cannot add various sensors and auxiliary equipment to verify and analyze the positioning system. This article takes the intelligent research and training dual-use ship of Dalian Maritime University, which integrates scientific research and training, as the object of study. This ship will not be affected by the voyage period and route and can choose a suitable sea area for research. Therefore, in order to improve the accuracy and reliability of the dynamic positioning system, research on the ship’s dynamic positioning system was carried out. Firstly, an accurate mathematical model of ship motion was established, and the hydrodynamic derivatives of ship model motion were obtained by nu-merical calculation, and applied to the three-degree-of-freedom model of the intelligent research and training dual-use ship. Then, the model was used as part of the closed-loop simulation model of the ship’s dynamic positioning system, and the terminal sliding mode controller was used for sim-ulation and emulation, thereby obtaining ideal simulation test results. This research helps to im-prove the accuracy and reliability of the dynamic positioning system and provides new ideas and methods for ship motion control.

Soil salinity is seen as a major restriction for crop production, and with water scarcity this problem becomes more complicated. Mulching is crucial to salinity dynamics management by decreasing evaporation with improving the soil’s characteristics. Using chitosan as an eco-friendly biostimulant can enhance plant defense genes during different abiotic stresses. Recently, agricultural research has recognized nanoparticles as a pioneer material due to their distinctive physicochemical features. Therefore, a lysimeter experiment was conducted to investigate the interactive effects of mulching (UNM: un-mulched, WPM: white plastic, RSM: rice straw and SDM: sawdust) and chitosan foliar application (Ch0: control, Ch1: 250 mg chitosan L-1, Ch2: 125 mg nano chitosan L-1, and Ch3: 62.5 mg nano chitosan L-1) on the biochemical soil characteristics and common beans productivity under salt affected soil conditions. Organic mulching (RSM and SDM) treatments significantly improved the soil's organic carbon, available nutrient content, and total count of bacteria. WPM treatment lowered soil EC to 6.63 dS m-1 and increased soil water content to 34.13%. The application of Ch3 caused considerable increases in the plant height, shoot dry weight, root dry weight, grain yield, and nutrient content in the seed. The total fungi count in the soil and Na% in the seed was significantly decreased due to chitosan foliar applications. Moreover, the interactive effect of different mulch materials plus foliar by chitosan applications gave a statistically similar seed yield in both seasons. Overall, this study revealed the potential of the mulching treatments and foliar application of nano chitosan in improved biochemical soil characteristics and common bean productivity under saline soil conditions.

Although lymphoma is the most frequent malignancy in common variable immunodeficiency (CVID), solid tumors, especially under influence of oncogenic viruses, are not considered. Furthermore, in vitro genetic studies and cell cultures are not adequate for immune system and HBV interaction. We adopted previously introduced clinical model of host-virus interaction (i.e. infectious process in immunodeficiency) for analysis of B cells and specific IgG role (observational study of a CVID patient who received intravenous immunoglobulin (IVIG)) Suddenly, the patient deteriorated with positive result of HBs, HBV-DNA (369x106copies). In spite of lamivudine therapy and IVIG escalation (from 0.3 to 0.4g/kg), CT showed 11cm intrahepatic tumor (hepatocellular carcinoma). Anti-HBs had been positive in time-lapse analysis (range 111-220 IU/ml). Replacement therapy intensification was complicated by immune complex disease with renal failure. The fulminant HCC in CVID and the development of the tumor as the first sign is interesting. Unfortunately, treatment with hepatitis B immune globulins (HBIG) plays a major role in posttransplant maintenance therapy. Anti-HBs substitution has not been proven to be effective, oncoprotective nor safe. Therefore, immunosuppression in HBV-infected recipients should be carefully minimized, patient selection more precise with the exclusion of HBV-positive donors. Our clinical model show HCC pathway with important humoral host factors, contrary to epidemiological/cohort studies highlighting risk factors only (e.g. chronic hepatitis). Lack of cell cooperation, B cell deficiency observed in CVID plays a crucial role in high HBV replication, especially in carcinogenesis.

Optical beam splitter is used for dividing an input optical beam into several separate beams with specific power ratio. Usually, conventional beam splitters have bulky dimensions and fixed dividing ratio which significantly limit the design of new miniaturized optical devices and integrated optical circuits. We propose and investigate a novel physical concept of a miniaturized planar optical splitter/coupler with a switching element in the form of a photonic molecule (PM) pair dispersing input optical fluxes along multiple ways with variable power proportions. The structural design of the proposed splitter is based on a silicon-on-insulator (SOI) platform and composed of high-quality resonators in the form of electromagnetically coupled submicron-sized microcylinders. The control on the power division ratio and the selection of optical beam directions is realized by tuning the photonic splitter structure to the corresponding resonance of PM supermode. Compared to known analogues, the proposed design is easy to fabricate, suitable for integration into a "System-on-a-chip" platform and can dynamically change the beam power division ratio by input wave-phase manipulation.

The integration of renewable energy and hybrid energy storage system (HESS) into electrified railways to build electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the energy management effectiveness for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow among the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

Every land plant exists in close relationship with microbial communities of several niches: rhizosphere, endosphere, phyllosphere, etc. The growth and yield of potato – a critical food crop worldwide – highly depend on the diversity and structure of bacterial and fungal communities with which the potato plant coexists. The potato plant has a specific part – tubers, and the soil near the tubers as sub-compartment is usually called “geocaulosphere”, which is associated with storage process and tare soil microbiome. Specific microbes can help the plant to adapt to particular environment conditions and resist to pathogens. There is a number of approaches to modulate the microbiome that provides organisms with desired traits during inoculation. The mechanisms of plant–bacterial communication remain understudied, and for the further engineering of microbiomes with particular features the knowledge on potato microbiome should be summarized. The most recent approaches to microbiome engineering include construction of a synthetic microbial community or management of plant microbiome using genome engineering. In this review, the various factors that form the microbiome of potato and the role of these factors in overcoming the negative impact of drought and pathogens are surveyed.

In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble methods, to enhance credit card fraud detection. Through an extensive review of existing literature, we identified limitations in current fraud detection technologies, including issues like data imbalance, concept drift, false positives/negatives, limited generalisability, and challenges in real-time processing. To address some of these shortcomings, we propose a novel ensemble model that integrates a Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), Bagging, and Boosting classifiers. This ensemble model tackles the dataset imbalance problem associated with most credit card datasets by implementing under-sampling and the Synthetic Over-sampling Technique (SMOTE) on some machine learning algorithms. The evaluation of the model utilises a dataset comprising transaction records from European credit card holders, providing a realistic scenario for assessment. The methodology of the proposed model encompasses data pre-processing, feature engineering, model selection, and evaluation, with Google Colab computational capabilities facilitating efficient model training and testing. Comparative analysis between the proposed ensemble model, traditional machine learning methods, and individual classifiers reveals the superior performance of the ensemble in mitigating challenges associated with credit card fraud detection. Across accuracy, precision, recall, and F1-score metrics, the ensemble outperforms existing models. This paper underscores the efficacy of ensemble methods as a valuable tool in the battle against fraudulent transactions. The findings presented lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, crucial as credit card fraud techniques continue to evolve.

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, poses a significant and widespread threat to the common bean crop. The use of plant genetic resistance has proven to be the most effective strategy for managing anthracnose disease. The Amendoim Cavalo (AC) Andean cultivar has resistance against multiple races of C. lindemuthianum, which is conferred by the Co-AC gene. Fine mapping of this resistance gene to common bean chromosome Pv01 enabled the identification of Phvul.001G244300, Phvul.001G244400, and Phvul.001G244500 candidate genes for further validation. In this study, we assessed the relative expression of Co-AC candidate genes, as well as other putative genes in vicinity of this locus and known resistance genes, in the AC cultivar following inoculation with the race 73 of C. lindemuthianum. Gene expression analysis revealed significantly higher expression levels of Phvul.001G244500. Notably, Phvul.001G244500 encodes a putative Basic Helix-Loop-Helix transcription factor, suggesting its involvement in the regulation of defense responses. Furthermore, we observed a significant modulation of the expression of defense related genes PR1a, PR1b, and PR2, in a time-course experiment. These findings contribute to the development of improved strategies for breeding anthracnose-resistant common bean cultivars, thereby mitigating the impact of this pathogen on crop yields and ensuring sustainable bean production.

Reactions of N‚N'-bis(3-methylpyridyl)oxalamide (L1), N,N’-bis(3-methylpyridyl)adipoamide (L2) and N,N’-bis(3-methylpyridyl)sebacoamide (L3) with tricarboxylic acids and Cu(II) salts afforded {[Cu(L1)(1,3,5-HBTC)]·H2O}n (1,3,5-H3BTC = 1,3,5-benzenetricarboxylic acid), 1, {[Cu1.5(L2)1.5(1,3,5-BTC)(H2O)2]·6.5H2O}n, 2, [Cu(L2)0.5(1,3,5-HBTB)]n (1,3,5-H3BTB = 1,3,5-tri(4-carboxyphenyl)benzene), 3, [Cu4(L3)(OH)2(1,3,5-BTC)2]n, 4, {[Cu3(L3)2(1,3,5-BTB)2]·2.5MeOH·2H2O}n, 5, and {[Cu3(L3)2(1,3,5-BTB)2 ]·DMF·2H2O}n, 6, which have been structurally characterized by using single crystal X-ray crystallography. Complexes 1 – 4 form a 2D layer with the {44.62}-sql topology, a 2D layer with the (4.62)2(42.62.82)-bex topology, a 3-fold interpenetrated 3D net with the (412.63)-pcu topology and a 3D framework with the (410.632.83)(42.6)2(43.63) topology, respectively, whereas 5 and 6 are 3D frameworks with the (63)2(64.82)(68.85.102) topology. Complex 5 shows a better iodine-adsorption factor of 290.0 mg g-1 at 60 oC for 360 minutes than the other ones, revealing that the flexibility of the spacer ligand governs the structural diversity and the adsorption capacity.

The Centers for Disease Control and Prevention (CDC) indicates that individuals with prediabetes are significantly less likely to develop type 2 diabetes if they participate in a lifestyle change program that results in at least 5% weight loss and 150 minutes of physical activity per week. The CDC recognizes distance learning as an effective delivery mode for lifestyle change programs to prevent type 2 diabetes. The purpose of this study was to assess enrollment, engagement, and effectiveness of a type 2 diabetes prevention program (DPP) using synchronous distance technology. Eat Smart, Move More, Prevent Diabetes (ESMMPD) is an intensive 12-month DPP delivered using synchronous distance technology. Throughout 26 lessons, participants focused on healthy eating, physical activity, and mindfulness behaviors. Study findings showed a significant decrease in A1C (-0.24 p<.0001). Weight loss averaged 5.66% for those who completed the program. Based on the Wilcoxon signed-rank test, participants demonstrated statistically significant changes in self-reported confidence in their ability to perform all 18 health-promoting behaviors assessed (p<.0001). Participation in the program also resulted in the adoption of health promoting behaviors. A DPP using synchronous distance technology is an effective delivery mode to help participants adopt healthy behaviors, increase physical activity, and achieve the weight loss necessary to prevent or delay the onset of type 2 diabetes.

The purpose of water treatment through ultraviolet (UV) radiation is to interrupt the development and multiplication of microorganisms by preventing their growth and reproduction.Ultraviolet treatment has become a very affordable solution to produce clean water of optimal quality in regions where access to drinking water is essential. The experimental water treatment unit is powered by a photovoltaic (PV) source. It incorporates a discharge lamp used to generate ultraviolet radiation, which is harnessed to address bacteriological issues related to water quality. This lamp is continuously powered by a photovoltaic (PV) source through an inverter and an electronic ballast. The water treatment system also includes a motor pump designed to draw contaminated water from the input reservoir, a flow control valve to adjust flow rates as needed, and a filter aimed at enhancing the quality of the contaminated water. The water circulates between the input reservoir (contaminated water) and the output reservoir (treated water) through the UV lamp. The relationship between the intensity of the UV lamp and the water flow rate can ensure an adequate water quality.

This paper describes RTMN 2.0 - an extension of the modeling language RTMN. RTMN combines process modeling and robot execution. The reusability and intuitive robot programming allows people without programming expertise to plan and control robots. While RTMN focuses on the ease of use and flexibility of robot programming by providing an intuitive modelling language, RTMN 2.0 concentrates on Human Robot Collaboration (HRC), which represents the current trend of the industry shift from ‘mass-production’ to ‘mass-customization’. While traditional robot systems provide high payload capabilities and repeatability, they suffer from limited flexibility and dexterity. Therefore, human-robot collaboration is a suitable arrangement to leverage the unique capabilities of both humans and robots for increased efficiency and quality in industrial scenarios. HRC has made a great impact on the robotic industry: increased efficiency, reduced costs and improved productivity, which can be adopted to make up for the skill gap of a shortage of workers in the manufacturing industry. The extension in RTMN 2.0 includes the following notations: HRC tasks, requirement, Key Performance Indicator (KPI), condition check and decision making, join/split and data association. With all these additional elements RTMN 2.0 covers the full scale of agile manufacturing – light out and collaborative.

The heat generated during the startup process of dry gas seals, such as the friction heat of the asperities, viscous shear heat, and the expansion heat of the gas film, easily leads to seal failure and endangers the stable operation of turbomachinery. This study combines the statistically modified contact model and the average Reynolds equation by considering the adiabatic index and the microscale effects of dry gas seals to explore the heat generation characteristics of dry gas seals formed in series at multiple times. In particular, the change laws and influencing factors among the components, including the friction heat of asperities and the shear heat and expansion heat of the gas film and total heat, are investigated. A comparative analysis indicates that the slip flow effect increases the total heat during the startup process. The friction heat is much greater than expansion heat and shear heat. Despite constant acceleration, exponential acceleration, or Harrision acceleration, the heat changes are uneven during the startup process. In particular, the heat changes sharply in the early stage and gently in the later stage. The Harrision acceleration mode is the most conducive to sealing stability.

This paper presents a new low-voltage versatile mixed-mode filter which uses a multi-ple-input/output differential difference transconductance amplifier (MIMO-DDTA). The multi-ple-input of the DDTA is realized using a multiple-input bulk-driven MOS transistor (MI-BD-MOST) technique to maintain a single differential pair, thereby achieving simple structure with minimal power consumption. In a single topology, the proposed filter can provide five standard filtering functions (low-pass, high-pass, band-pass, band-stop, and all-pass) in four modes: voltage (VM), current (CM), transadmittance (TAM), and transimpedance (TIM). This provides the full capability of a mixed mode filter (i.e., twenty filter functions). Moreover, the VM filter offers high-input and low-output impedances and the CM filter offers high-output impedance; therefore, no buffer circuit is needed. The natural frequency of all filtering functions can be electronically controlled by a setting current. The voltage supply is 0.5 V and for a 4 nA setting current, the power consumption of the filter was 281 nW. The filter is suitable for low-frequency biomedical and sensor applications that require extremely low supply voltages and nano-watt power consumption. For the VM low-pass filter, the dynamic range was 58.23 dB @ 1 % total harmonic distortion. The proposed filter was designed and simulated in the Cadence Virtuoso System Design Platform using the 0.18 µm TSMC CMOS technology.

Spray technology is widely used in various industries, including medicine, food production, mechanical engineering, and nanopowder manufacturing. Achieving high dispersion and a narrow particle size distribution is crucial for many applications. Ultrasonic spraying is commonly used to achieve this. On other hand, hydraulic nozzles provide high atomization performance. Combining these two technologies promises to offer significant benefits, but the complex processes that occur simultaneously in such a device require careful study. This work proposes a fundamental design for an acoustic-hydraulic nozzle and investigates the physical processes when a liquid is sprayed using this nozzle, both theoretically and experimentally. The study identifies the critical modes of spraying and confirms that the simultaneous use of ultrasound and hydraulic pressure can produce a fine spray (droplet size less than 50 μm) with high productivity (5-10 ml/s). This approach has significant potential for modern industries and technologies.

An algorithm is proposed for discriminating the fatigue state of air traffic controllers based on ap-plying multispeech feature fusion using an FSVM to voice data, and for extracting eye-fatigue-state discrimination features based on PERCLOS eye data. For the speech algorithm and an eye-fatigue index, a new controller fatigue-state evaluation index based on the entropy weight method is proposed based on decision-level fusion of fatigue discrimination results for speech and the eyes. Experimental results show that the fatigue-state recognition accuracy rate was 84.81% for the fatigue state evaluation index, which was 3.36% and 1.86% higher than those for speech and eye assessments, respectively. The comprehensive fatigue evaluation index provides important reference values for controller scheduling and mental-state evaluations.

The utilization of dual-potential mode of integrated array (IDA) electrodes and other two-electrode systems has revolutionized electrochemical detection by enabling the simultaneous and independent detection of two species, accompanied by the exhibition of unique characteristics. In contrast to conventional dual-potential electrodes, the rotating ring disk electrodes (RRDE), IDA electrodes demonstrate analogous yet vastly improved performance metrics, characterized by remarkable collection efficiency and sensitivity. Notably, due to the distinctive microscale structure of IDA electrode, the special “feedback” effect makes IDA a unique signal amplifier. In recent decades, the research surrounding IDA electrodes has garnered escalating interest due to their attractive attributes. This review centers its focus on the fabrication and applications of IDA electrodes. In the realm of fabrication, two critical breakthroughs are poised for realization: the achievement of reduced dimensions and the diversification of materials. Established fabrication methods for IDA electrodes encompass photolithography, inkjet printing, and direct laser writing, each affording distinct advantages in terms of size and precision in IDA construction. Predominantly employed materials for IDA electrodes include gold, platinum, and carbon, with the selection of fabrication methods guided by considerations such as material properties, desired dimensions, cost-efficiency, and specific application requisites. Within the domain of applications, IDA electrodes, capitalizing on their distinctive attributes, have found utility in diverse fields. This review summarizes the applications of IDA electrodes based on their fundamental working principles, encompassing redox cycling, resistance modulation, capacitance variations, and more. The potential for further development of this specialized tool to exhibit enhanced properties holds substantial promise.

The security of several fully homomorphic encryption (FHE) schemes depends on the intractability assumption of the approximate common divisor (ACD) problem over integers. Subsequent efforts on solving the ACD problem as well as its variants were also developed during the past decade. In this paper, an improved orthogonal lattice (OL) based algorithm, AIOL, is proposed to solve the general approximate common divisor (GACD) problem. The conditions for ensuring the feasibility of AIOL are also presented. Compared to the Ding-Tao’s OL algorithm, the well-know LLL reduction is used only once in AIOL, and when the error vector r is recovered in AIOL, the possible difference between the restored and the true value of p is given. The experimental comparisons towards the Ding-Tao’s algorithm and ours are also provided for validating our improvements.

Magnetorheological (MR) fluids have been known to react to magnetic fields of sufficient magnitudes. While in the presence of the field the material develops a yield stress. The tunable property has made it attractive in e.g. semi-active damper applications in vibration control domain in particular. Within the context of a given application the fluids can be exploited in at least one of the fundamental operating modes of which the so-called gradient pinch mode has been least explored. Contrary to the other operating modes, the MR fluid volume in the flow channel is exposed to a non-uniform magnetic field in such a way that the Venturi-like contraction is developed in a flow channel solely by means of a solidified material in the regions near the walls rather than mechanically driven changes of the channel’s geometry. The pinch mode rheology of the material has made it a potential candidate in developing on a new category of MR valves. By convention, a pinch mode valve features a single flow channel with poles over which non-uniform magnetic field is induced. In this study the authors examine ways of extending the dynamic range of pinch mode valves by employing a number of such arrangements (stages) in series. To accomplish this, the authors developed a prototype of a multi-stage (three-stage) valve, and then compared its performance against that of a single-stage valve across a wide range of hydraulic and magnetic stimuli. To summarize, improvements in the pinch mode valve dynamic range are evident, however, at the same time it is hampered by the presence of serial air gaps in the flow channel.

A micro-ring resonator structure was fabricated via two-photon polymerization (2PP) technique directly on a single-mode fiber tip and tested for refractive index sensing application. The micro-ring structure was used to excite whispering gallery modes (WGMs) and observations of the changes in resonance spectrum introduced by changes in refractive index of the environment served as the sensing principle. The proposed structure has the advantages of a very simple design, allowing for measurements in reflection mode, relatively easy and fast fabrication and integration with a single tip of a standard single-mode fiber, which allowed for quick and convenient measurements in the optical setup. The performance of structure was characterized, resonant spectrum giving high potential for refractive index sensing was measured. Future perspectives of the research are discussed.

The investigation on the issue of damage diagnosis based on strain modal parameters is conducted in this paper using simply supported wooden Beams as the study's object. First, ABAQUS is utilized to create finite element models of intact wooden beams as well as wooden beams with varying degrees of damage and perform modal analyses on them. Next, damage identification studies are conducted on the wooden beam structure using various strain modal parameters (strain mode strain modal difference, strain modal curvature difference), the timber beam damage identification test then yields the modal parameters of timber beams under various damage situations, and the test findings are contrasted with those of the numerical simulation. The outcomes demonstrate that the damage identification of the test data using the three types of damage identification indexes is consistent with the results of the numerical simulation; the three types of damage identification indexes can locate the damage to timber beams, but the identification effect of the indexes is different, the best-recognized metric is the strain mode curvature difference; the next best is the strain mode difference, and the worst is the strain modes. The study's findings can serve as a guide for future damage detection on wood beams.

This study presents an innovative approach named Optimal Adaptive Continuous Barrier Function Terminal Sliding Mode Control (OACBF-TSMC) approach with a novel switching manifold, to control mathematical model of nonlinear systems under model uncertainties and external disturbances. The proposed OACBF-TSMC approach combines the advantages of adaptive control, continuous barrier functions, and terminal sliding mode control to achieve robust stability of the mathematical model of nonlinear systems, and by using a genetic algorithm that tries to optimize the controller parameters as much as possible so that the proposed controller is the most to have efficiency and performance. The proposed method is designed to address the challenges of systems and provide superior performance in terms of stabilization accuracy, disturbance rejection, and robustness against uncertainties. However, the critical challenge facing the proposed controller is the complete elimination of the chattering phenomenon, which is the most important problem of ordinary sliding mode controllers. The simulation results show that the system trajectories in the proposed approach have converged to the origin with minimal overshoot and under-shoot in a finite time; In addition, the chattering problem in the control inputs has been well eliminated, which makes the proposed method suitable for various systems, including chaotic systems, energy sources, and distributed production systems. Furthermore, the OACBF-TSMC approach has the potential to enhance the stability and reliability of control systems, contributing to the integration of the system states.

The Review examines studies aimed at the organization of energy (non-mechanical) control of high-speed flow/flight using spatially multi-component plasma structures and combined energy deposition. The Review covers selected works on experimental obtaining and numerical modeling multi-component plasma structures and use of sets of actuators based on the plasma of such a spatially type for the purposes of control of shock wave/bow shock wave – energy source interaction, as well as control of shock wave – boundary layer interaction. A series of works on repetitive multiple laser pulse plasma structures is also analyzed from the point of view of examining shock wave/bow shock wave boundary layer interaction. Self-sustained theoretical models for laser dual-pulse, multi-mode laser pulses and self-sustained glow discharge are also considered. Separate sections are devoted to high-speed flow control using combined physical phenomena and numerical prediction of flow control possibilities using thermal longitudinally layered plasma structures. The wide possibilities for organization and applying spatially multi-component structured plasma for the purposes of high-speed flow control are demonstrated.

In recent years, the use of long-term seismic monitoring systems for the protection of structures is becoming increasingly widespread. This is because more and more awareness is gradually developing regarding the importance of keeping structures under observation so as to prevent any damage scenarios. Within the field of Structural Health Monitoring, data driven techniques allow to process and analyze data collected on site. This paper presents a Mode Tracking procedure to obtain the time-histories of the natural frequencies of a monumental structure. The procedure is applied on the Sanctuary of Vicoforte, an important monumental structure site in Piedmont known for its imposing oval dome and characterized by a permanent structural monitoring system. Through the procedure presented in the paper it has been possible to obtain and observe the time series of the first natural frequencies of the structure considering various aspects, including the temperature variation.

Water deficit (drought) is still one of the most important stress factors affecting not only yields, but also production quality. Breeders are focusing on breeding cultivars and crop lines that are more resistant to water shortages. In addition to breeding, for example, for the size of the roots and changes in the color of the leaves, focus on changing the morphotype i.e. long chaff, multirowed ear. It is predicted that wheat genotypes with a morphotype change should be more drought tolerant. Therefore, our research focused on the study of changes in the physiological parameters of wheat (cv. ´Bohemia´) with a changed morphotype (genotypes ´284-17´ [long chaff] and genotype ´29-17´ [multirowed ear]) in relation to exposure to drought. Pigment content, photosynthesis and transpiration rate, water potential were measured in plants irrigated and affected by water deficit. Water deficit was shown to have a statistically significant effect on transpiration rate, photosynthetic rate, water potential and total chlorophyll content. Furthermore, the influence of the genotype on the observed parameters and on the effect of water deficit was demonstrated. Due to the fact that cv. ´Bohemia´, increases during such periods of transpiration, so for this reason it is not suitable for dry areas. Genotype ́29-17 ́ appears promising with respect to drought resistance.

Knowing the reasons for mobility choices, how users evaluate the characteristics of public transport and how satisfied they are with the travel experience is essential to promote the use of LTP (Local Public Transport), especially in rural or suburban areas where the use of private car is often prevalent. The present study aimed to investigate the mobility experience and the reasons for use and non-use of the LPT in a suburban area by the people travelling to a large Hospital Centre in a Province of the North-east of Italy. An anonymous questionnaire was completed by people from different categories travelling to the hospital (students, employees, clients), user and non-users of the LPT. The results showed that insufficient hourly coverage and accessibility of the service are the primary reasons for opting not to use LPT and together with reliability and comfort, these factors contribute to user satisfaction with their travel experience. Perceived sustainability of LPT contributes to overall travel satisfaction. However perceived sustainability alone does not appear to influence the choice of LPT if the service lacks adequate accessibility and does not meet the needs of travelers in terms of hourly coverage

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

In Uganda, the common bean (Phaseolus vulgaris) is often infested by a complex of insect pests, but the bean stem maggots, aphids, bean leaf beetles, and flower thrips are the most important. Whereas yield losses due to these pests have been established, there is limited information on their population dynamics at different stages of crop growth and their effect on yield and yield components. In order to describe the population dynamics of selected common bean pests at various phases of bean crop growth, and their impact on yield and yield components, a study was carried out in Uganda during 2016 second rains and 2017 first rains in three agro-ecological zones. Bean fly, bean aphids, bean leaf beetles, whitefly, striped bean weevil, leaf hoppers, and caterpillars of Lepidopteran species were the main insects observed. Pesticide spray schedules were imposed to generate different populations of insect pests whose effects on yield and its components were determined. The findings indicate that spray regimes significantly influenced the abundance of bean fly, aphids, whitefly, striped bean weevil, and leaf hoppers but not bean leaf beetles and caterpillars. Additionally, except caterpillars, insect pests were significantly influenced by crop growth stages, but only aphids, whiteflies, bean flies and leaf hoppers exhibited a significant negative relationship with grain yield. Furthermore, yield and yield components varied significantly between spray regimes, agro-ecological zones, and seasons. Our study is important in informing growers on the stage of crop growth at which management tactics such as use of insecticides can be applied for different insect pests.

Active transportation, such as walking, cycling, and micro-mobility modes, has received a lot of attention in recent years due to its potential benefits to urban residents, such as less traffic, better air quality, more opportunities to get exercise, and an overall higher quality of life. In this study, we used Classification and Regression Trees (CART) to compare and contrast three mobility options: shared micro-mobility, individual micro-mobility, and walking. We surveyed 219 people living in Budapest, Hungary, to learn more about their travel habits and investigate the demographic elements that influence people's mode choice, such as age, gender, ownership of micro-mobility modes, education, job, and income. Results showed that ownership of personal micro-mobility modes, and age as important predictors of active travel mode choice. Males seem to prioritize cost and weather conditions when choosing shared micromobility modes, while females value safety and weather conditions. Our findings can guide policy decisions and urban planning initiatives by identifying the most significant predictors of mode choice and evaluating the possible benefits and drawbacks of each mode.

Lizards in Bulgaria hibernate in winter. Yet, individuals of many species were found active in this period. Cases of winter activity of Podarcis muralis and P. erhardii in the country have been published, but this behavior has not been studied in detail. The purpose of this research was to observe and analyze the winter activity of these two species in the city of Blagoevgrad. The observations took place at two sites in days with high solar radiation in December, January, and February 2015–2017. One of the sites was a typical urban territory, inhabited only by P. muralis. The other site was a suburban area, inhabited by P. erhardii. The number of the active individuals of the Common Wall Lizard recorded was about 8.5 times higher than that of the Erhard's Wall Lizard. The lowest air temperature at which P. muralis was observed was -4°C and for P. erhardii it was +0.5°C. Individuals of both species were registered only at positive substrate temperatures. Representatives of all age groups of P. muralis were recorded often with dorsoventrally flattened bodies while basking. On the other hand, few juveniles of P. erhardii were found active and they flattened their bodies very rarely.

In this paper for every number field K generated by a root α of a trinomial x⁷ + ax + b ∈ Z[x] and for every prime integer p, we calculate ν_p(i(K)), the highest power of p dividing the index i(K) of the field K. In particular, we calculate the index i(K). As application, when the index of K is not trivial, then K is not monogenic.

Considering the aging society and budget constraints, a strategy for reforming public transportation welfare policies is essential for sustainability. Among the various transportation welfare policies, fare discount policies are provided to specific age groups, and most countries offer benefits to several public transportation. South Korea provides a fare-free policy limited to subways, and the need for policy modification is emerging due to sustainability problems caused by an aging society. Hence, the scope of the policy should be expanded to all travel modes, but the discount rate should be reduced, or the target group should be reduced in consideration of the budget. This study proposes a travel mode to focus on by city through the preference of the elderly. The latent class model is employed to classfy stated preference data collected from the survey. The estimation results show a significant preference heterogeneity depending on the level of subway supply by region, and a policy focused on subways would be more reasonable in cities with sufficient subway infrastructure. Hence, regarding sustainability, it may be more appropriate to focus on specific means than to provide the same discount policy for all public transport.

Anthracnose (ANT) and angular leaf spot (ALS) are significant diseases in common bean, leading to considerable yield losses under specific environmental conditions. The California Dark Red Kidney (CDRK) bean cultivar is known for its resistance to multiple races of both pathogens. Previous studies have identified the CoPv01CDRK/PhgPv01CDRK resistance loci on chromosome Pv01. Here, we evaluated the expression levels of ten candidate genes near the CoPv01CDRK/PhgPv01CDRK loci and plant defense genes using quantitative real-time PCR in CDRK cultivar inoculated with races 73 of Colletotrichum lindemuthianum and 63-39 of Pseudocercospora griseola. Gene expression analysis revealed that the Phvul.001G246300 gene exhibited the most elevated levels, showing remarkable 7.8-fold and 8.5-fold increases for ANT and ALS, respectively. The Phvul.001G246300 gene encodes an abscisic acid (ABA) receptor pyrabactin resistance - PYR1-like (PYL) protein, which plays a central role in crosstalk between ABA and jasmonic acid responses. Interestingly, our results also showed that the other defense genes were initially activated. These findings provide critical insights into the molecular mechanisms underlying plant defense against these diseases and could contribute to the development of more effective disease management strategies in the future.

With the realization of the Grand Canal's full water supply and the strong pursuit of green and low-carbon transportation in contemporary society, the value of the Grand Canal's water transport has been further affirmed, and its coordinated development with other transportation modes has become inevitable and important. This paper analyzes and combs through the characteristics, development status and existing problems of Grand Canal water transport and other transport modes in depth, and takes Jiangsu as an example. A collaboration model of Grand Canal water transport and other transport modes was built and their collaboration degree has been calculated. It is believed that the coordinated development of Grand Canal water transport and other transport modes can be greatly promoted via four aspects: optimizing the construction and governance of Grand Canal water transport, building an integrated management platform of transport modes, improving the integrated transport network structure, and promoting the deep integration of integrated shipping and tourism.

This work investigates the sliding mode control (SMC) problem for a class of uncertain switched systems subject to asynchronous switching and an assigned finite time constraint. Two important issues are how to ensure the reachability of state trajectories within the assigned time and the input-to-output finite-time stability (IO-FTS) of the closed-loop switched systems during the whole phase under asynchronous switching. To achieve these objectives, an asynchronous sliding mode controller with adjustable parameters is constructed to drive the state trajectories onto the sliding surface during the assigned finite-time interval. By means of the partitioning strategy, sufficient conditions for the IO-FTS of the closed-loop switched are derived during the whole phase [0,T] using the multiple Lyapunov function (MLF) approach. Additionally, the asynchronous characteristics are detailedly investigated while analyzing the reachability of a specified sliding surface. Finally, an illustrative example is given to illustrate the effectiveness of the proposed method.

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common one has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Nowadays, brain signal processing is performed rapidly in various brain-computer interface (BCI) applications. Most researchers focus on developing new methods for the future or improving the basic implemented models to identify the optimum standalone feature set. Our research focuses on four ideas. One of them introduces future communication models, and the others are for improving old models or methods. These are: 1) new communication imagery model instead of speech imager using the mental task: Due to speech imagery is very difficult, and it is impossible to imagine sound for all of the characters in all of the languages. Our research introduces a new mental task model for all languages that call Lip-sync imagery. This model can use for all characters in all languages. This paper implemented two lip-sync for two sounds, characters or letters. 2) New combination Signals: Selecting an inopportune frequency domain can lead to inefficient feature extraction. Therefore, domain selection is so important for processing. This combination of limited frequency ranges proposes a preliminary for creating Fragmentary Continuous frequency. For the first model, two s intervals of 4 Hz as filter banks were examined and tested. The primary purpose is to identify the combination of filter banks with 4Hz (scale of each filter bank) from the 4Hz to 40Hz frequency domain as new combination signals (8Hz) to obtain well and efficient features using increasing distinctive patterns and decreasing similar patterns of brain activities.3) new supplement bond graph classifier for SVM classifier: When SVM linear uses in very noisy, the performance is decreased. But we introduce a new bond graph linear classifier to supplement SVM linear in noisy data. 4) a deep formula recognition model: it converts the data of the first layer into a formula model (formula extraction model). The main goal is to reduce the noise in the subsequent layers for the coefficients of the formulas. The output of the last layer is the coefficients selected by different functions in different layers. Finally, the classifier extracts the root interval of the formulas, and the diagnosis does based on the root interval. For all of the ideas achieved the results of implementing methods. The results are between 55% to 98%. Less result is 55% for the deep detection formula, and the highest result is 98% for new combination signals.

In this paper, a robust nonlinear dynamic controller is designed for a wind turbine with a permanent magnet synchronous generator. The wind turbine is subject to variations in all the parameters appearing in its mathematical model. Furthermore, the wind velocity is considered unavailable for direct measurement. This situation is of particular interest in practical applications, where only the nominal parameter values are known, and accurate wind velocity measurement is challenging due to perturbations caused by the turbine itself, even with appropriate sensors. The problem addressed in this work involves tracking the reference angular velocity corresponding to the wind velocity. To achieve accurate tracking, appropriate compensation of the perturbation terms resulting from parameter uncertainties and wind estimation errors is required. To address this problem, an estimator of the wind velocity is utilized, along with high–order sliding mode parameter estimators, to ensure high–performance operation of the turbine.

Peripheral nerve injury remains a medical challenge with no easy resolution. Over the last few decades, significant advances have been achieved in promoting peripheral nerve regeneration, and new assessment tools have been developed, both functional and imaging, to quantify the proportion and quality of nerve recovery. The exploration of new animal models, larger, more complex and with more similarities to humans, has made it possible to reduce the gap between the results obtained in classic animal models such as rodents and the application of new therapies in humans and animals of clinical interest. Ultrasonography is an imaging technique recurrently used in clinical practice to assess the peripheral nerves, allowing its anatomical and topographic characterization, and aiding in the administration of anesthesia and in the performance of nerve blocks. The use of this technique in animal models is scarce, but it could be a useful tool in monitoring the progression of nerve regeneration after the induction of controlled experimental lesions. In this work, sheep, a promising animal model in the area of peripheral nerve regeneration, were subjected to an ultrasonographic study of three peripheral nerves of the hind limb, the common peroneal, tibial and sciatic nerves, in order to establish values of dimensions and ultrasound appearance in healthy nerves and also landmarks for their identification. At the same time, an echographic evaluation of the cranial tibial muscle, an effector muscle of the common peroneal nerve, was also carried out, establishing normal values for the echographic aspect and dimensions. The results obtained will allow the use of these data as control values in future work exploring new therapeutic options for nerve regeneration after induction of common peroneal nerve injuries in sheep.

As urban populations and transport demand expand, Pakistani metropolitan centers face traffic congestion and environmental challenges. This research aims to assess carpooling (CP) to alleviate traffic congestion, fuel demand, and pollution. This study was conducted in Islamabad, a fast-growing city with a high percentage of personal cars in Pakistan, to assess the travelers’ perceptions, and public acceptance of CP and determine the effects on traffic congestion, fuel consumption, and CO2 emissions. The investigation of travelers' perceptions towards CP was conducted through a stated preference questionnaire survey. A total of 700 responses from one million population of Islamabad were collected as per Sloven's Formula. SPSS and Smart PLS software were used for data analysis. Various factors influencing peoples’ travel perceptions, mode choice, and tendency to carpool, were categorized to evaluate the relationship between travelers’ perception and the tendency to carpool in the presence of mode choice as a mediating variable. Confirmatory factor analysis was conducted in SMART PLS to refine the number of scale items for each variable. One-way ANOVA, step-wise and mediated multiple regression analysis was conducted in SPSS to check the direct and mediating relationship between different variables. Moreover, the probability of reducing traffic congestion and assessing fuel reduction resulting from CP was also analyzed. The findings imply that travelers’ mode choice acts as a mediator between the relationship between travelers’ perception and tendency to carpool. Furthermore, results predicted that CP might reduce 0.25 million cars on the road, about 33.6% of the total private vehicles. Thereby, saving up to 546,810 barrels per year, about 3.42% of Pakistan's total petrol consumption. The findings of this study could be helpful for transport planners, environmentalists, and policymakers to implement carpool systems. Thus, reducing traffic congestion and harmful CO2 emissions and maintaining a sustainable environment.

In this paper, a dual-band WiFi antenna and its Multiple Input Multiple Output (MIMO) system application is designed, fabricated, and measured based on the Chinese characters “Men” and “Wei”. The antenna uses a 40×40×1.6 mm3 Fr4 substrate to analyze the combinatorial structure of Chinese characters using the theory of characteristic modes (TCM), to optimize the antenna dimensions by analyzing the mode current distribution, and to broaden the antenna bandwidth by etching rectangular slots on the ground. The measured and simulated results show that the four-element MIMO antenna covers 5.68-8.01 GHz, the isolation between the antennas is higher than 20 dB in the working band, the Envelope Correlation Coefficient (ECC) and the channel capacity losses (CCLs)of the simulation is lower than 0.001 and 0.18 bits/s/HZ, respectively. The efficiency of the antenna is higher than 90%, and it can be used for WiFi communication band (5.8 GHz and 6 GHz).

The bean weevil (Acanthoscelides obtectus (Say.)) is one of the main pests of stored beans in the world. Heterogeneous Inbreed Families (HIF) Population of Near Isogenic Lines (NILs) could be an exceptional strategy to study the inheritance of the resistance against A. obtectus. We developed a HIF population of NILs of R-bufa-80-12 (Phaseolus vulgaris) to study the inheritance related to bean weevil resistance and to search NILs with high resistance to the pest within the HIF population. The objective of this research was to study the inheritance in a HIF population and to identify the best lines to provide weevil resistance in bean breeding for commercial genotypes that could reduce pesticide applications. To achieve this objective, we developed a set of 148 NILs which were near-homozygous in the genome, except in the region under study. The HIF were evaluated in two environments under natural infestation with A. obtectus in free choice bioassays in a warehouse highly infested. The population showed wide variability for the traits studied, from 17.2 to 29.2 g for 100 seed weight, 0.0-0.8 for consumption in grams, 2.0-30.0 for consumption in percent and 1.2-9.6 for preference (number of adults in the bottle to the end of the experiments. The heritabilities for resistance traits were from very low to low 0.0 to 0.19. The heritability for 100 seed weight was the highest, with a value of 0.90. All traits studied in this research have a normal distribution, so they are considered to be quantitatively inherited. However, a great variability was found for the traits studied, which allows selecting lines with a high level of resistance within the R-bufa-80-12 HIF population. All traits studied in present research are of quantitative inheritance. The best lines of the HIF population for resistance to A. obtectus were the Line-45, Line-129, Line-124, Line-108 and Line-47.

Asphalt pavement temperature has several applications, including pavement structural design and evaluation, asphalt mixture design, asphalt binder grade determination and material aging characterization. However, available asphalt pavement temperature prediction models were mostly developed for temperate climatic conditions, outside of the tropics. Before such models are adopted for use in a tropical climate, their applicability must be evaluated. This study evaluated five empirical asphalt pavement temperature prediction models developed by Lukanen et al. [1], Park et al. [2], Diefenderfer et al. [3], Taamneh [4] all in the United States and Asefzadeh et al. [5] in Canada to ascertain their prediction accuracy in tropical climate, using Ghana as a case study. In-situ asphalt pavement temperature data were measured at two sites for eight months: Kumasi and Tamale in the Forest and Savannah climatic zones, respectively. The measured pavement temperature data were statistically compared with predicted temperatures, and it was found that the Park et al. [2] model provided a more accurate pavement temperature prediction in both climatic zones. The other models either over-predicted or under-predicted asphalt pavement temperature with significant error margins. However, there is a need to improve the prediction accuracy of the Park et al. [2] model or a local model developed.

This paper presents a case study on using Emacs and Org-mode for literate programming in undergraduate data science courses. Over three academic terms, the author mandated these tools across courses in R, Python, C++, SQL, and more. Onboarding relied on simplified Emacs tutorials and starter configurations. Students gained proficiency after initial practice. Live coding sessions demonstrated the flexible instruction enabled by literate notebooks. Assignments and projects required documentation alongside functional code. Student feedback showed enthusiasm for learning a versatile IDE, despite some frustration with the learning curve. Skilled students highlighted efficiency gains in a unified environment. However, uneven adoption of documentation practices pointed to a need for better incorporation into grading. Additionally, some students found Emacs unintuitive, desiring more accessible options. This highlights a need to match tools to skills levels, potentially starting novices with graphical IDEs before introducing Emacs. Key takeaways include literate programming aids comprehension but requires rigorous onboarding and reinforcement; Emacs excels for advanced workflows but has a steep initial curve. With proper support, these tools show promise for data science education.

(1) Background: The study presents an assessment of the psychometric properties of the Polish version the Short Schema Mode Inventory (SMI) adaptation. (2) Methods: First, the original version of the scale was translated. Subsequently, a validity and reliability study was conducted on a sample of 240 patients and 400 non-patients. In particular: the factor structure of the inventory was checked, internal reliability and intercorrelations between subscales were tested, differences between the clinical and non-clinical groups in terms of the severity of each factor were examined, and construct validity was assessed by comparing the association of results with external variables. (3) Results: The results did not conclusively confirm the 14-factor structure postulated in the original scale. Nevertheless, relatively the best fit indices were obtained for such a model. Internal reliability for the 14 subscales was in the acceptable to excellent range. Correlations between subscales took moderate to high values. The existence of differences between the clinical and non-clinical groups and the construct validity were confirmed. (4) Conclusions: The psychometric evaluation performed is mostly similar to the results obtained for other adaptations, and the results entitle the inventory to be used for research and clinical purposes with the knowledge of its limitations.

A class of controlled plants, whose dynamics is governed by a vector system of ordinary differential equations with a partially known right-hand side, is considered. The state variables and their velocities are assumed to be measurable. The aim is to design a controller which minimizes a loss function under certain constraints which arguments is the current state of the controlled plant. The designed control action is admitted to be a function of the current sub-gradient only, which supposed to be measurable on-line. The control design is based on ASG (Average Sub-Gradient method) — version of Integral Sliding Mode (ISM) concept, aimed to minimize on average a given convex (not obligatory strongly convex) cost function of the current state under a set of given constraints. An optimization type algorithm is developed and analyzed using ideas of SDM technique. The main results consist in proving the reachability of the "desired regime" (nonstationary analogue of sliding surface) from the beginning of the process and obtaining an explicit upper bound for the averaged loss function decrement, that is, the averaged in time functional convergence is proven and the rate of such convergence is estimated.

Switched-mode power supplies (SMPS) often utilize electrolytic capacitors due to their substantial energy density and economical pricing. However, their ability to function at low temperatures is essential for dependable operation in several sectors, including telecommunications, automotive, and aerospace. This study includes an experimental evaluation of how well standard SMPS electrolytic capacitors operate at low temperatures. This paper investigates the suitability of standard electrolytic capacitors used in switched-mode power supplies (SMPS) for low-temperature applications. The experimental evaluation exposed the capacitors to temperatures ranging from - 5 ∘C to - 40 ∘C, assessing capacitance (Cp), impedance (Z), dissipation factor (DF), and equivalent series resistance (ESR) at each temperature. The capacitor’s time-domain electrical signals were analyzed using the Pearson correlation coefficient to extract discriminative features. These features were input into an Artificial Neural Network (ANN) for training and testing. Results indicated a significant impact of low temperatures on capacitor performance. Capacitance decreased with lower temperatures, while ESR and leakage current increased, affecting stability and efficiency. Impedance proved to be a valuable diagnostic tool for identifying potential capacitor failure, showing a 98.44% accuracy drop at - 5 degrees and 88.75% at the peak temperature, indicating proximity to the manufacturer’s specified limit. The study suggests further research and development to improve electrolytic capacitors’ performance in SMPS systems under cold conditions to enhance efficiency and reliability.

With the continuous improvement and observable benefits of electric vehicles (EVs), major logistic companies are introducing more EVs into their conventional fleets. This gives rise to a new type of vehicle routing problem with mixed vehicles, where heterogeneous internal combustion vehicles (ICVs) and electric vehicles are considered in route planning. In addition, certain deliveries that are not efficient on any type of vehicles, are outsourced to third-party common carriers. In this paper, we define this problem as a mixed vehicle routing problem with common carriers (MVRPC). The objective of such problems is to minimize the transportation costs by considering routes with ICVs and EVs, the possibility of visiting recharging stations, outsourcing options, and drivers’ layover regulations. This variant of the vehicle routing problems has many practical applications, particularly in the design of long-haul transportation and last-mile delivery services. Effective MVRPC solutions play a key role in promoting the going Green image and optimally allocating resources. The problem has received limited attention in the literature likely because addressing all the needed aspects is especially challenging. To solve the large-scale problem, we develop a branch-and-cut pricing framework that relies on strong cuts and customized labeling algorithms. Numerical experiments highlight the effectiveness of our algorithm. This success can be attributed to tailored critical resources, dynamically bounded bidirectional labeling procedures, strong dominance criteria, and implementation strategies.

One of the most burning topics in cybersecurity in 2023 will undoubtedly be the compliance with the Software Bill of Materials. Since the US president issued the Executive Order 14028 on Improving the Nation’s Cybersecurity, software developers have prepared and bills are transmitted to vendors, customers, and users, but they don’t know what to do with the reports they are getting. In addition, since software developers have identified the values of the Software Bill of Materials, they have been using the reports extensively. This article presents an estimate of 270 million requests per month, just from form one popular tool to one vulnerability index. This number is expected to double every year and a half. This simple estimate explains the urgency for automating the process. We propose solutions based on artificial intelligence and machine learning, and we base our tools on the existing FAIR principles (Findable, Accessible, Interoperable, and Reusable). This methodology is supported with a case study research and Grounded theory, for categorising data into axis, and for verifying the values of the tools with experts in the field. We showcase how to create, and share Vulnerability Exploitability eXchange data, and automate the Software Bill of Materials compliance process with AI models and a unified computational framework combining solutions for the following problems: (1) the data utilisation problem, (2) the automation and scaling problem, (3) the naming problem, (4) the alignment problem, (5) the pedigree, and provenance problem, and many other problems that are on the top of mind for many security engineers at present. The uptake of these findings will depend on collaborations with government and industry, and on the availability and the ease of use of automated tools.

As a fast and nondestructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel spectral denoising method based on variational mode decomposition (VMD) was introduced to solve the above problem. The spectrum is decomposed into a series of modes (uk) by VMD. Then, the high frequency noise modes are removed and the remaining modes are reconstructed to obtain the denoised spectrum. The proposed method was verified by two artificial noised signals and two actual Raman spectra. As comparison, empirical mode decomposition (EMD), Savitzky-Golay (SG) smoothing and discrete wavelet transformation (DWT) are also investigated. At the same time, signal-to-noise ratio (SNR) was introduced as evaluation indicators to verify the performance of the proposed method. The results show that compared with EMD, VMD can significantly improve mode mixing and endpoint effect. Some information of the small sharp peak is lost after VMD denoising. However, VMD lost fewer information than that of EMD, SG smoothing and DWT. Moreover, the Raman spectrum by VMD denoising is more excellent than that of EMD, SG smoothing and DWT in terms of visualization and SNR. Therefore, VMD provides superior denoising capabilities for Raman spectra.