Given the increase in consumers’ preferences for coffee, it is becoming important to understand their decision-making processes in the coffee chain context. To deepen the understanding of sustainable outcomes in this context, this study investigates the role of dedication- and constraint-based mechanisms in forming consumers’ repurchase and positive word-of-mouth (WOM) intentions, two critical sustainable outcomes. We examined the effects of coffee quality, the quality of the physical environment, and service quality in accelerating the formation of dedication-based factors. Moreover, this study offers an in-depth understanding of the enablers of perceived switching costs. Data collected from 238 university students that frequently visit coffee chains are empirically tested against the proposed theoretical framework by using structural equation modeling. The results confirm that both dedication- and constraint-based factors substantially predict consumers’ sustainable outcomes in the coffee chain context. Brand image and perceived switching costs play an important role in enhancing consumers’ repurchase and positive WOM intentions compared with customer satisfaction. Coffee quality is significantly associated with both customer satisfaction and brand image, whereas the quality of the physical environment and service quality are only significantly associated with brand image. Habit is found to be the key enabler of perceived switching costs, while loyalty programs have no significant impact on perceived switching costs.

This paper proposes a single-stage asymmetrical half-bridge fly-back (AHBF) converter with resonant mode using dual-mode control. The presented converter has an integrated boost converter and asymmetrical half-bridge fly-back converter and operates in resonant mode. The boost-cell always operates in discontinuous conduction mode (DCM) to achieve high power factor. The presented converter operates simultaneously using a variable-frequency-controller (VFC) and pulse-width-modulation (PWM) controller. Unlike the conventional single-stage design, the intermediate bus voltage of this controller can be regulated depending on the main power switch duty ratio. The asymmetrical half-bridge fly-back converter utilizes a variable switching frequency controller to achieve the output voltage regulation. The asymmetrical half-bridge fly-back converter can achieve zero-voltage-switching (ZVS) operation and significantly reduce the switching losses. Detailed analysis and design of this single-stage asymmetrical half-bridge fly-back converter with resonant mode is described. A wide AC input voltage ranging from 90 to 264 Vrms and output 19 V/ 120 W prototype converter was built to verify the theoretical analysis and performance of the presented converter.

The excited-state lifetimes of the anticoagulant drug warfarin (W) in water and in the absence and presence of methyl-β-cyclodextrins (Me-β-CD) were recorded using time-resolved fluorescence measurements. Selective excitation of the open and cyclic protonated isomers of W were acquired with laser emitting diodes (LED) producing 320 and 280 nm excitation pulses, respectively. Formation of the inclusion complex was checked by UV–visible absorption spectroscopy, and the values of binding constants (2.9 × 10³ M^–1 and 4.2 × 10² M^–1 for protonated and deprotonated forms, respectively) were extracted from the spectrophotometric data. Both absorption and time-resolved fluorescence results established that the interior of the macromolecular host binds preferentially the open protonated form, red shifts the maximum of its absorption of light at ~305 nm, extends its excited-state lifetime, and decreases its emission quantum yield (ФF). Collectively, sequestration of the open guest molecules decreases markedly their radiative rate constants (kr), likely due to formation of hydrogen-bonded complexes in both the ground and excited states. Due to lack of interactions, no change was observed in the excited-state lifetime of the cyclic form in the presence of Me-β-CD. The host also increases the excited-state lifetime and ФF of the drug deprotonated form (W¯). These later findings could be attributed to the increased rigidity inside the cavity of Me-β-CD. The pKa values extracted from the variations of the UV–visible absorption spectra of W versus the pH of aqueous solution showed that the open isomer is more acidic in both ground and excited states. The positive shifts in pKa values induced by three derivatives of cyclodextrins: HE-β-CD, Ac-β-CD, and Me-β-CD supported the preferential binding of these hosts to open isomers over cyclic.

The switched inertance hydraulic system (SIHS) is a novel high-bandwidth and energy-efficient digital device which can adjust or control flow and pressure by a means that does not rely on throttling the flow and dissipation of power. An SIHS can provide an efficient step-up or step-down of pressure or flow rate by using a digital control signal. In this article, analytical models of an SIHS in a four-port high-speed switching valve configuration are proposed, and the system dynamics and performance are investigated theoretically and experimentally. The flow responses, system characteristics and power consumption can be predicted effectively and accurately by using the proposed models, which were validated by comparing with experiments and with numerical simulation. The four-port configuration is compared with the three-port configuration, and it is concluded that the former one is less efficient for valves of the same size, but provides a bi-direction control capability. As bi-direction control is a common requirement, this constitutes an important contribution to the development of efficient digital hydraulics.

Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5^th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.

Given the landscape of intricate and constantly evolving cyber threats, organizations demand refined strategies to deploy a Security Information and Event Management to support the management of a Cyber Security Operations Center. The dynamic nature of cyber threats complicates the efficient allocation of the location of network intrusion detection sensors, a critical component of a robust cybersecurity framework. Our research introduces an approach that integrates the precision of biomimetic optimization algorithms with the adaptability of Deep Q–Learning. By employing different biomimetic algorithms enhanced with deep learning, we aim to refine the deployment of sensors in network infrastructures, balancing the network security imperative against deployment costs. The results of computational tests demonstrate that the improved iterations leveraging Deep Q–Learning have outperformed their native counterparts. These findings underscore the importance of reinforcement learning, specifically through Deep Q–Learning, as a powerful tool to enhance the effectiveness of metaheuristics in addressing optimization challenges.

We investigate a singularly perturbed q-difference differential Cauchy problem with polynomial coefficients in complex time and space with quadratic nonlinearity. We construct local holomorphic solutions on sectors in the complex plane with respect to the perturbation parameter with values in some Banach space of formal power series in space with analytic coefficients on shrinking domains in time. Two aspects of these solutions are addressed. One feature concerns asymptotic expansions in the parameter for which a Gevrey type structure is unveiled. The other fact deals with confluence properties as q tends to 1. In particular the built up Banach valued solutions are shown to merge in norm to a fully bounded holomorphic map in all its arguments that solves a nonlinear partial differential Cauchy problem.

Price markups and firm Tobin’s Q ratios are widely believed to have been increasing in the past several decades. Various models for the calculation of price markups have been developed, but each have methodological drawbacks and some results are poorly reflective of the near past wider macroeconomic experience. This paper defines an approach for the definition and measurement of markup pricing using the measure of Economic Rent and The Capital Asset Pricing Model. The results show limited markup pricing for The UK’s FTSE 100 companies (2018-2023), but that that certain Real Estate, Technology/Media and Financial Services/Equity Investment firms have enjoyed higher price markup levels. An analysis of the business models of these firms is used to qualitatively propose explanations for such markups. Finally, this work offers a formal proof that that expected price markup is equal to Tobin’s Q and finds that the empiric market level of markup is near equivalent to the market Tobin’s Q; differences between the markup and Tobin’s Q at the level of the firm are equally assessed.

Intermediate CAG expansions in the gene ataxin-2 (ATXN2) are a known risk factor for ALS, but little is known about their role in FTD risk. Moreover, their contribution to the risk and phenotype of patients might vary in populations with different genetic background. The aim of this study was to assess the relationship of intermediate CAG expansions in ATXN2 with the risk and phenotype of ALS and FTD in the Spanish population. Repeat-Primed PCR was performed in 620 ALS and 137 FTD patients in three referral centers of Spain to determine the exact number of CAG repeats. In our cohort, ≥27 CAG repeats in ATXN2 was associated with a higher risk of developing ALS (odds ratio [OR] = 2.666 [1.471-4.882]; p = 0.0013), but not FTD (odds ratio [OR] = 1.446 [0.558-3.574]; p = 0.44). Moreover, ALS patients with ≥27 CAG repeats in ATXN2 showed shorter survival rate compared to those with <27 repeats (hazard ratio [HR] 1.74 [1.18, 2.56], p = 0.005), more frequent limb onset (odds ratio [OR] = 2.34 [1.093-4.936]; p = 0.028), as well as family history of ALS (odds ratio [OR] = 2.538 [1.375-4.634]; p = 0.002). Intermediate CAG expansions of ≥27 repeats in ATXN2 are associated with ALS risk, but not with FTD, in the Spanish population. ALS patients carrying an intermediate expansion in ATXN2 show more frequent limb onset, but worse prognosis than those without expansions. In patients carrying C9orf72 expansions, the intermediate ATXN2 expansion might increase the penetrance and modify the phenotype.

The asymptotic behavior of the analytic solutions of a family of singularly perturbed q-difference-differential equations in the complex domain is studied. Different asymptotic expansions with respect to the perturbation parameter and to the time variable are provided: one of Gevrey nature, and another of mixed type Gevrey and q-Gevrey. This asymptotic phenomena is observed due to the modification of the norm established on the space of coefficients of the formal solution. The techniques used are based on the adequate path deformation of the difference of two analytic solutions, and the application of several versions of Ramis-Sibuya theorem.

Limited availability of expensive alloying elements elevates low-alloyed steels to a unique position in the field of lightweight construction and mass production. Quenching and partitioning (Q&P) heat treatments of low-alloyed steels with exceptional property combinations are particularly promising. In this study, we characterize for the first time a new low-alloyed steel to be processed by Q&P heat treatments. In combined experimental and numerical studies, we design a novel approach that effectively combines the short cycle times of press hardening with the excellent property profiles of Q&P-treated steels. We identify appropriate transformation parameters for Q&P heat treatments by dilatometric studies and we adjust a number of reference conditions with different isothermal holding times. By means of SEM analysis and XRD measurements, we show that different fractions of retained austenite result in different mechanical properties. Initial numerical designs of the process can identify varying temperature profiles and cooling rates depending on the position in the die. The results show that the geometry of the part plays a minor role, but the die temperature is the dominant factor for successful partitioning directly in the press hardening process.

We examine a family of nonlinear q-difference-differential Cauchy problems obtained as a coupling of linear Cauchy problems containing dilation q-difference operators, recently investigated by the author, and quasi-linear Kowalevski type problems that involve contraction q-difference operators. We build up local holomorphic solutions to these problems. Two aspects of these solutions are explored. One facet deals with asymptotic expansions in the complex time variable for which a mixed type Gevrey and q-Gevrey structure is exhibited. The other feature concerns the problem of confluence of these solutions as q tends to 1.

A linear Cauchy problem with polynomial coefficients wich combines q-difference operators for q>1 and differential operators of irregular type is examined. A finite set of sectorial holomorphic solutions w.r.t the complex time is constructed by means of classical Laplace transforms. These functions share a common asymptotic expansion in the time variable which turns out to carry a double layers structure which couples q-Gevrey and Gevrey bounds. In the last part of the work, the problem of confluence of these solutions as q tends to 1 is investigated.

In this paper, by using the q-integer, we introduce a new generalization of Fibonacci and Lucas sedenions called q-Fibonacci and q-Lucas sedenions. We present some fundamental properties of these type of sedenions such as Binet formulas, exponential generating fuctions, summation formulas, Catalan's identity, Cassini's identity and d'Ocagne's identity.

Space instable target simulator (SITS) is a vital actuator for ground verification of on-orbital capture technology, the motion performance of which directly affects simulation credibility. Different delays reduce the stability of SITS and ultimately lead to its divergence. In order to achieve high fidelity simulation, the impact of force measurement delay, discrete control cycle, and simulator response delay on stability is analyzed firstly. Then, the dynamic equation and transfer function identification model of hybrid simulator is constructed, and the necessary and sufficient conditions of its stability and convergence are obtained using the Routh criterion. After that, a switching compensator with variable gain is proposed, the compensation principle diagram of which is build, and its mathematical model including the energy observer and tracking differentiator is also established. Finally, three sets of numerical simulations are conducted to validate the correctness of the stability analysis and effectiveness of proposed compensation method. Simulation results show that all three types of delay can cause SITS to lose stability under critical stable motion state, and the delay in force measurement has the greatest impact, followed by the influence of control cycle. Compared with the force applied to simulated target, velocity and its recovery coefficient of space instable target using fixed gain and linear gain compensation, the proposed compensator has significantly better performance.

Reliable motor control design is a critical part of the electric vehicle application. Control techniques and motor control devices play an important role in achieving system reliability. In this study, motor control devices have been proposed to implement control techniques in sensorless PMSM. Motor control devices including PWM signal generation by FPGA, gate driver circuit (GDC), and power inverter were developed to be integrated into single-stage motor control devices for sensorless motor control applications. Improvements in GDC design have been the focus to increase the performance of the motor control devices used. Switching losses due to the parasitic elements caused ringing switching behavior of the power inverter circuit, which reduces the performance when the system is integrated. Moreover, in the implementation of sensorless motor control using observer techniques, these conditions affect the accuracy of rotor position estimation, which uses the current or voltage information of the power converter as a variable in the observer design model. Therefore, a GDC design using IR2110 with additional ringing suppression circuit configuration was proposed for the application of motor device control topology to improve the performance of sensorless motor control system. Furthermore, the reduction of switching losses, reduction of current distortion, and accuracy of rotor position information were confirmed by experimental results.

Nasal cavity is a primary checkpoint for the invasion of several respiratory pathogens. Numerous pathogens including SARS-CoV-2, S. pneumonia, S. aureus, etc., adhere to the nasal epithelium or mucus to invade and trigger an infection. IgA serves as the first line of defense against foreign antigens and pathogens. They exhibit cross-reactivity against a diverse variety of antigens through immune exclusion, which intercepts the invasion of pathogens through the mucosal lining. Advances in intranasal immunization technology underscore the elevated neutralizing IgA levels at local and distal mucosa in contrast to the parenteral vaccines. This review highlights the adjuvants that induce IgA class switching and the challenges of maintaining nominal IgA levels at the mucosal surface. Finally, the review features the paradigm-shifting of conventional immunization techniques to IgA-inducing vaccines to enhance protection against homologous and heterologous pathogens.

In the paper, a coordinated control methodology of single-phase (1-P) end-users switching oper-ations on the phases of an active electric distribution network (AEDN) has been proposed to ob-tain a minimum unbalance degree at the coupling common point (CCP) level with the main dis-tribution system. The phase load balancing (PLB) process considers the smart devices that switch from one phase to another phase the 1-P end-users (consumers and prosumers) to compensate for the phase load unbalance. The proposed methodology has been tested successfully in an AEDN belonging to a Romanian Distribution Network Operator (DNO) containing 114 end-users (104 consumers/10 prosumers) integrated into the Smart Metering System (SMS). The op-timal solution leads to a value of the objective function by 1.00004, represented by the unbalance factor, very close to the ideal target, 1.00. A comparative analysis was conducted considering other possible PLB cases (the consumer-level PLB and prosumer-level PLB), obtaining similar values of the UF (1.027 vs. 1.028), slightly higher than in the hybrid-level PLB. Also, the signifi-cant technical benefits were quantified through an energy-saving of 58.73% and decreasing the phase voltage unbalance rate by 91 % compared to the initial case (without PLB). These results emphasized the positive impact of the proposed coordinated control methodology on the PLB process and evidenced its effectiveness and applicability in the AEDNs.

This article deals with a finite-source stock-dependent stochastic inventory system with heterogeneous servers and retrial facility. The system can store up to S number of items, and the lifetime of each item follows an exponential distribution. The primary customers arrive in a finite waiting hall from a finite source and get service from the multi-channel (c-heterogeneous servers). The customer’s arrival rate depends on the present stock level. Those customers who arrive while the waiting hall is full enter into the finite orbit. Also, customers in the waiting hall can become impatient and enter the orbit. The (s,Q) ordering policy is adopted for the replenishment of stocks. In the steady state, the joint probability distribution of a number of items in the inventory, busy servers, customers in the waiting hall, and orbit is computed. The comparative numerical analysis of heterogeneous and homogeneous servers on the expected total cost, the average number of customers in the waiting hall and orbit, the fraction of successful retrial rate, and the average impatient customer rate are also carried out.

A family of singularly perturbed q-difference-differential equations under the action of a small complex perturbation parameter is studied. The action of the formal monodromy around the origin is present in the equation, which suggests the construction of holomorphic solutions holding logarithmic terms in both, the formal and the analytic level. We provide both solutions and describe the asymptotic behavior relating them by means of q-gevrey asymptotic expansions of some positive order, with respect to the perturbation parameter. On the way, the development of a space product of Banach spaces in the Borel plane is needed to provide a fixed point for a coupled system of equations.

Propolis was widely used in health preservation and disease healing, it contains many ingredients. The previous study had been revealed that the propolis has a wide range of efficacy, such as antiviral, immune enhancement, anti-inflammatory and so on, but its antiviral components and underlying mechanism of action remain unknown. In this study, we investigated the chemical composition, and anti-PPV and immunological enhancement of Propolis Flavonoid(PF). Chemical composition of PF was distinguished by UPLC-Q/TOF-MS/MS analysis.The presence and characterized of 26 major components was distinguished in negative ionization modes.To evaluate the effects of PF used as adjuvant on the immune response porcine parvovirus (PPV). Thirty Landrace-Yorkshire hybrid sows were randomly assigned to 3 groups, and the sows in adjuvant groups were intramuscular injected PPV vaccine with 2.0 mL PF adjuvant (PA), oilemulsion adjuvant (OA), respectively. After that, serum hemagglutination inhibition antibody titers, IgM and IgG subclasses, eripheral lymphocyte proliferation activity, and concentrations of cytokines were measured. Results indicated an enhancing effect of PA on IgM, IL-2, IL-4, IFN-γ and the IgG subclass responses. These findings suggested that PA could significantly enhance the immune responses. Furthermore, we screened the chemical components the effective of anti-PPV, Ferulic acid have an excellently anti-PPV effective.

The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implement FQ-AGO on the NS-3 simulator and compare the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we consider various network metrics to compare the performance of the routing protocols. Our simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay.

Spinal and bulbar muscular atrophy (SBMA), also known as Kennedy’s disease, is a debilitating neuromuscular disease characterized by progressive muscular weakness and neuronal degeneration, affecting 1-2 individuals per 100,000 globally. While SBMA is relatively rare, recent studies have shown a significantly higher prevalence of the disease within the indigenous population of Western Canada compared to the general population. The disease is caused by a pathogenic expansion of polyglutamine residues in the androgen receptor protein, which acts as a key transcriptional regulator for numerous genes. SBMA has no cure, and current treatments are primarily supportive and focused on symptom management. Recently, a form of precision medicine known as antisense therapy has gained traction as a promising therapeutic option for numerous neuromuscular diseases. Antisense therapy uses small synthetic oligonucleotides to confer therapeutic benefit by acting on pathogenic mRNA molecules, serving to either degrade pathogenic mRNA transcripts or helping to modulate splicing. Recent studies have explored the suitability of antisense therapy for the treatment of SBMA, primarily focused on antisense-mediated mRNA knockdown approaches. Advancements in understanding the pathogenesis of SBMA and the development of targeted therapies offer hope for improved quality of life for individuals affected by this debilitating condition. Continued research is essential to optimize these genetic approaches, ensuring their safety and efficacy.

Wall–stabilized arcs dominated by nozzle–ablation are key elements of self–blast circuit breakers. In the present study, high–current arcs were investigated using a model circuit breaker (MCB) in CO2 as gas alternative to SF6 and in addition a long polytetrafluoroethylene nozzle under ambient conditions for stronger ablation. The assets of different methods for optical investigation were demonstrated, e.g. high-speed imaging with channel filters and optical emission spectroscopy. Particularly the phase near current zero (CZ) crossing was studied in two steps. In the first step using high-speed cameras, radial temperature profiles have been determined until 0.4 ms before CZ in the nozzle. Broad temperature profiles with a maximum of 9400 K have been obtained from analysis of fluorine lines. In the second step, the spectroscopic sensitivity was increased using an intensified CCD camera, allowing single-shot measurements until few microseconds before CZ in the MCB. Ionic carbon and atomic oxygen emission were analyzed using absolute intensities and normal maximum. The arc was constricted and the maximum temperature decreased from >18000 K at 0.3 ms to about 11000 K at 0.010 ms before CZ. The arc plasma needs about 0.5-1.0 ms after both the ignition phase and the current zero crossing to be completely dominated by the ablated wall material.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

In this study, the microbial strain was isolated from the humus soil to ferment Sophora flavescens and Eleutherococcus sessiliflorus extracts. The isolated microbial was identified as Bacillus genus by 16S rRNA sequence analysis. The fermented plant extracts exhibited the antifungal effects against four types of the plant pathogens such as P. carotorum, B. cinerea, C. fructicola Sau-3, and C. gloeosporioides according to incubation time. Especially, the fermented plant extracts showed the most active activities for Colletotrichum genus to inhibit mycelium growth. Metabolite changes in fermented S. flavescens and E. sessiliflorus extracts were confirmed through LC-Q-TOF/MS. Flavonoid and peptide derivatives were improved in fermented S. flavescens and E. sessiliflorus extracts compared to their unfermented one, respectively. This study suggested that the isolated Bacillus microbial fermentation could be a valuable tool in improving the bioactivity of S. flavescens and E. sessiliflorus extracts to have potential with more environmentally-friendly antifungal agents.

Rice false smut caused by Ustilaginoidea virens is one of the most devastating diseases on rice worldwide, which results in serious reduction of rice quality and yield. As an airborne fungal disease, early diagnosis of rice false smut, monitoring the epidemics and distribution of its pathogens, is particularly important to management the infection. In this study, a quantitative loop-mediated isothermal amplification (q-LAMP) method for the U. virens detection and quantifying was developed. This method has higher sensitivity and efficiency compared to quantitative real-time PCR (q-PCR) method. The species-specific primer sets UV-2 used was design based on the unique sequence of U. virens ustiloxins biosynthetic gene (NCBI accession number: BR001221.1). The q-LAMP assay was able to detect a concentration of 6.4 spores/mL at an optimal reaction temperature of 63.4℃ within 60 min. Moreover, the q-LAMP assay can even achieve accurate quantitative detection when there were only 9 spores on the tape. A linearized equation for the standard curve, y =-0.2866x + 13.829 (x is the amplification time, the spore number = 100.65y), was established for detection and quantifying of U. virens. In field detection applications, this q-LAMP method is more accurate and faster than traditional observation method. Collectively, this study has established a powerful and simple monitoring tool for U. virens, which provide valuable technical supports for forecast and management of rice false smut, and theoretical basis for precise fungicide application.

This present work explores the performance of a thermal-magnetic engine of Otto type, considering as a working substance an effective interacting spin model corresponding to the q− state clock model. We obtain all the thermodynamic quantities for the q = 2, 4, 6, 8 cases in a small lattice size (3×3 with free boundary conditions) by using the exact partition function calculated from the energies of all the accessible microstates of the system. The extension to bigger lattices was performed using the mean-field approximation. Our results indicate that the total work extraction of the cycle is highest for the q=4 case, while the performance for the Ising model (q=2) is the lowest of all cases studied. These results are strongly linked with the phase diagram of the working substance and the location of the cycle in the different magnetic phases present, where we find that the transition from a ferromagnetic to a paramagnetic phase extracts more work than one of the Berezinskii–Kosterlitz–Thouless to paramagnetic type. Additionally, as the size of the lattice increases, the extraction work is lower than smaller lattices for all values of q presented in this study.

Amid to the COVID-19 pandemic, digital health literacy (DHL) has become a significant public health concern. This research aims to assess information seeking behavior, as well as the ability to find relevant information and deal with DHL among university students in Pakistan. An online-based cross-sectional survey, using a web-based interviewing technique, was conducted to collect data on DHL. Simple bivariate and multivariate linear regression was performed to assess the association of key characteristics with DHL. The results show a high DHL related to COVID-19 in 54.3% of students. Most of the Pakistani students demonstrated ~50% DHL in all dimensions, except of reliability. Multivariate findings showed that gender, sense of coherence and importance of information were found to be significantly associated with DHL. However, a negative association was observed with students’ satisfaction with information. This led to the conclusion that critical operational and navigations skills are essential to achieve COVID-19 DHL and cope with stress, particularly to promote both personal and community health. Focused interventions and strategies should be designed to enhance DHL amongst university students to combat the pandemic.

Integrated ultra-low-loss waveguides are highly desired for integrated photonics to enable applications that require long delay lines, high-Q resonators, narrow filters, etc. Here we present an ultra-low-loss silicon waveguide on 500 nm thick SOI platform. Meter-scale delay lines, million-Q resonators and tens of picometer bandwidth grating filters are experimentally demonstrated. We design a low-loss low-reflection taper to seamlessly integrate the ultra-low-loss waveguide with standard heterogeneous Si/III-V integrated photonics platform to allow realization of high-performance photonic devices such as ultra-low-noise lasers and optical gyroscopes.

Active front-end (AFE) rectifiers have been becoming widely employed in power systems to achieve unity power factor and harmonic mitigations. The typical modeling approaches applied for AFE rectifiers in the literature mostly relied on two baselines named the detailed model and the time average model. The former approach deals with the switching element model (SEM) leads to significant harmonics in currents with distorted waveforms. The latter approach uses the average-value model (AVM) to overcome the currents’ harmonics as well as provide fast responses. However, even the AVM baseline has contained problems during the starting stage (lack of control signals) and over the dead-time periods which causes serious issues in the implementation process. This paper presents an improved dynamic AVM for AFE rectifiers by precisely considering the issues mentioned above along with the practical starting procedure and desirable initialization. The studied AFE rectifier is developed using the voltage-oriented control (VOC) technique based on the different modeling methodologies including SEM, Conventional AVM, and the proposed AVM. The performance of all models is analyzed and compared using simulation results with MATLAB/Simulink R2023a Function blocks for all the algorithm parts and SimScape elements for the electrical circuit model. The simulation results illustrate that the performance of the proposed AVM approach can closely resemble the behavior of the SEM baseline with low harmonic distortion.

This paper investigates whether currency risk is priced differently in the different sectors (industrial, financial, and basic materials) of equity markets in a sample of developed United States of America (USA) and developing economies (Brazil, India, Poland, and South Africa). The paper makes use of the following techniques: (i) Univariate Autoregressive Fractionally Integrated Moving Average and Exponential General Autoregressive Conditional Heteroskedastic (ARFIMA-EGARCH), (ii) the Markov-Switching method (MS), and (iii) the Canonical Vine Copulas (C-Vine) techniques. Using a sample of daily data made of the foreign exchange rate against the domestic currency and equity market sectors; our findings show that there is an asymmetry effect between equities markets and the foreign exchange rate: there is a heterogeneous, strong, and positive dependence between the two. Higher equities prices are associated with depreciation of local currencies, according to US dollar (USD) exchange rates. In addition, we find that the selected emerging economies are pricing a positive and considerable currency risk. The pricing of currency risk has a varied effect in both regimes representing the states of the economy. In fact, when currency risk pricing has a beneficial impact on certain sectors of the economy, investors predict better returns.

Flux-switching permanent magnet (FSPM) motors have gained increasing attention in the electric vehicles (EVs) applications due to the advantages of high power density, high efficiency. However, the heat sources of both permanent magnet (PM) and armature winding are located on the limited stator space in the FSPM motors, which may result in the PM overheated and irreversible demagnetization caused by temperature rise and it is often ignored in the conventional thermal analysis. In this paper, a new electrical-thermal two-way coupling design method is proposed to analyze the electromagnetic performances, where the change of PM material characteristics under different temperatures is taken into consideration. Firstly, the motor topology and design equations are introduced. Secondly, the demagnetization curves of PM materials under different temperatures are modeled due to PM materials are sensitive to the temperature. And based on the electrical-thermal two-way coupling method, the motor performances are evaluated in details, such as the load PM flux linkage and output torque. Then, the motor is optimized, and the electromagnetic performances between initial and improved motors are compared. Finally, a prototype motor is manufactured, and the results are validated by experimental measurements.

An all-dielectric metasurface composed of orthogonal-slit silicon disks is proposed in this study. By modifying the unit structure of the metasurface with the bound states in the continuum (BIC) theory, a sharp Fano resonance can be generated. The resonance properties of the metasurface are investigated by analyzing the effects of the structural parameters on the resonance using the eigenmode analysis method. The Q factor and the resonance wavelength can be adjusted by varying the slit width, the disk thickness, and the disk radius. The electromagnetic characteristics and mechanism of the toroidal dipole-BIC (TD-BIC) are explored in depth through an analysis of the multipole expansion of the scattered power, along with the electromagnetic field and the current distribution at resonance. This research provides a novel approach for excitation of a strong TD-BIC resonance and proposes potential applications in optical switches, high-sensitivity optical sensors, and related areas.

Aiming at the problem of hypersonic morphing vehicle avoiding no-fly zones and reaching the target, an improved predictor-corrector guidance method is proposed. Firstly, the aircraft motion model and the constraint model are established. Then, the basic algorithm is given, the Q-learning method is used to design the attack angle and sweep angle scheme to ensure that the aircraft can fly over the low-altitude zones. The B-spline curve is used to design the location of flight path points and the bank angle scheme is designed according to the predictor-corrector method, so that the aircraft can fly around to avoid high-altitude zones. Next, Monte Carlo reinforcement learning(MCRL) method is used to improve predictor-corrector method and Deep Neural Network(DNN) is used to fit reward function. The improved method can generate trajectory with better performance. Simulation results verify the effectiveness of the proposed algorithm.

In tunnel excavation with boring machines, the tunnel face is supported to avoid collapse and minimise settlement. This article proposes the use of reinforcement learning, specifically the Deep Q-Network algorithm, to predict the face support pressure. The approach is tested both analytically and numerically. By using the soil properties ahead of the tunnel face and the overburden depth as the input, the algorithm is capable of predicting the optimal tunnel face support pressure, adapting to changes in geological and geometrical conditions.

We propose a notion of $(q,\sigma,\tau)$-differential graded algebra, which generalizes the notions of $(\sigma,\tau)$-differential graded algebra and $q$-differential graded algebra. We construct two examples of $(q,\sigma,\tau)$-differential graded algebra, where the first one is constructed by means of generalized Clifford algebra with two generators (reduced quantum plane), where we use a $(\sigma,\tau)$-twisted graded $q$-commutator. In order to construct the second example, we introduce a notion of $(\sigma,\tau)$-pre-cosimplicial algebra.

The paper deals with one new property of the linear time-optimal control problems with real eigenvalues of the system, no matter of the number of eigenvalue multiplicity. This property unveils a prospective of synthesizing the time-optimal control without the need of describing the switching hyper-surfaces. The already chrestomathy example of the time-optimal control of a double integrator is resolved by the new technique and compared with the classical synthesis.

In the heterogeneous wireless networked control system (WNCS), age of information (AoI) of the actuation update and actuation update cost are important performance metrics. To reduce the monetary cost, the control system can wait for the availability of WiFi network of the actuator and then conduct the update by using WiFi network in an opportunistic manner, but it leads to the increased AoI of the actuation update. To assess this problem, this paper proposes a priority-aware actuation update scheme (PAUS) where the control system decides whether to deliver or delay the actuation update to the actuator by considering the control priority (i.e., robustness of AoI of the actuation update). For the optimal decision, we formulate a Markov decision process model and derive the optimal policy based on Q-learning. Simulation results demonstrate that PAUS outperforms the comparison schemes in terms of the expected reward.

In this paper, we introduce a new generalization of the r-Stirling numbers of the second kind based on the q-numbers via an exponential generating function. We investigate their some properties and derive several relations among q-Bernoulli numbers and polynomials, and newly de…ned (q, r, w)-Stirling numbers of the second kind. We also obtain q-Bernstein polynomials as a linear combination of (q, r, w)-Stirling numbers of the second kind and q-Bernoulli polynomials in w.

In the present paper, we introduce (p, q)-extension of Apostol type Frobenius-Euler polynomials and numbers and investigate some basic identities and properties for these polynomials and numbers, including addition theorems, difference equations, derivative properties, recurrence relations and so on. Then, we provide integral representations, explicit formulas and relations for these polynomials and numbers. Moreover, we discover (p, q)-extensions of Carlitz's result [L. Carlitz, Mat. Mag., 32 (1959), 247–260] and Srivastava and Pintér addition theorems in [H. M. Srivastava, A. Pinter, Appl. Math. Lett., 17 (2004), 375–380].

Transformer models have emerged as frontrunners in the field of natural language processing, primarily due to their adept use of self-attention mechanisms to grasp the semantic linkages between words in sequences. Despite their strengths, these models often face challenges in single-task learning scenarios, particularly when it comes to delivering top-notch performance and crafting strong latent feature representations. This challenge is more pronounced in the context of smaller datasets and is particularly acute for under-resourced languages such as Arabic. In light of these challenges, this study introduces a novel methodology for text classification of Arabic texts. This method harnesses the newly developed Reverse Positional Encoding (RPE) technique. It adopts inductive-transfer learning (ITL) framework combined with a switching self-attention shared encoder, thereby increasing the model's adaptability and improving its sentence representation accuracy. The integration of Mixture of Experts (MoE) and Reverse Positional Encoding (RPE) techniques empowers the model to process longer sequences more effectively. This enhancement is notably beneficial for Arabic text classification, adeptly supporting both the intricate five-point and the simpler ternary classification tasks. The empirical evidence points to its outstanding performance, achieving accuracy rates of 87.20% for the HARD dataset, 72.17% for the BRAD dataset, and 86.89% for the LABR dataset, as evidenced by the assessments conducted on these datasets.

Digital agricultural technology extension service and sustainable food production have attracted attention from academia. However, the association between digital agricultural technology extension service and sustainable food production has not yet been fully investigated. This research investigates the average and heterogeneous impacts of digital agricultural technology extension service use on eco-efficiency among 1302 maize producing farmers from Northeast China major maize producing area in 2022 to fill this knowledge gap. The slack-based measure model with undesirable outputs is applied to calculate the eco-efficiency of maize production. To obtain an unbiased estimation of the average effect, the self-selection problem generated by observable and unobservable factors is solved by the endogenous switching regression model. Quantile regression is utilized to analyze the heterogeneous effect. Notably, the mediated effects model is utilized to examine the potential mechanism between them. Our findings indicate that digital agricultural technology extension service use can increase maize production's eco-efficiency. Digital agricultural technology extension service users would reduce eco-efficiency by 0.148 (21.11%) if they had not used the digital agricultural technology extension service. Digital agricultural technology extension service nonusers would improve eco-efficiency by 0.214 (35.20%) if they had used it. The robustness check reconfirms the results. Moreover, digital agricultural technology extension service use is more helpful to maize farmers who have lower eco-efficiency than those who have higher eco-efficiency. Digital agricultural technology extension service use can improve eco-efficiency of maize production through the application of organic fertilizers, green pesticides and biodegradable agricultural films.

Cinnamomum tamala leaf (CTL), also known as tejpat and Indian bay leaf, is used all over the world for seasoning, flavouring, and medicinal purposes. Numerous researchers are interested in exploring the nutritional and medicinal benefits of CTL due to their potential as nutraceuticals. These characteristics could be explained by the presence of several essential bioactive substances and lipid derivatives. There are no reports available on this species about its metabolites profile. In this work, rapid screen and identify chemical compounds in supercritical (SC)-CO2 extracts of CTL by use of UPLC-Q-TOF-MSE with multivariate statistical analysis approach was established in both negative and positive mode. As a results, a total of 166 compounds, including 66 monocarboxylic fatty acids, 52 dicarboxylic fatty acids, 27 fatty acid amides, and 21 others were tentatively identified based on accurate mass, and the mass spectrometric fragmentation pattern, out of which 142 compounds are common and found in all five CTL extracts. They displayed robust [M+H]+ and/or [M-H]- ions in both low- and high-energy collision-induced dissociations (CIDs). Based on chemical profiling and chemometric analysis, CTL4 (300bar/55°C) extract was found significantly more potent in other CTL’s extracts. A new mono- and di-carboxylic fatty acids, fatty acid amides and other essential bioactive compounds were separated within 20 min runtime and identified in CTL for the first time. The combination of UPLC-Q-TOF-MSE and chemometric analysis is a powerful method to rapidly screen the metabolites profile for the quality control of C. tamala leaf.

In this study, we introduce a new class of bi-univalent functions using q-Janowski Function. We derive the Fekete-Szegö functional problems for functions in this new subclass, as well as estimates for the Taylor-Maclaurin coefficients |α2| and |α3|. Furthermore, a collection of fresh outcomes are3 presented by customizing the parameters employed in our initial discoveries.

Firstly, we present a more explicit formulation of the complete system $D(N)$ of representatives of Manin's symbols over $\mathbb{Q}$, which was initially given by Shimura. Then we establish a bijection between $D(M)\times D(N)$ and $D(MN)$ for $(M,N)=1$, which reveals a recursive structure between Manin's symbols of different levels. Based on Manin's complete system $\Pi (N)$ of representatives of cusps on $X_0(N)$ and Cremona's characterization of the equivalence between cusps, we establish a bijection between a subset $C(N)$ of $D(N)$ and $\Pi (N)$, and then establish a bijection between $C(M)\times C(N)$ and $C(MN)$ for $(M,N)=1$. We also provide a recursive structure for elliptical points on $X_0(N)$. Based on these recursive structures, we obtain recursive algorithms for constructing Manin symbols over $\mathbb{Q}$, cusps and elliptical points on $X_0(N)$. This gives rise to a more efficient algorithms for modular elliptic curve. As direct corollaries of these recursive structures, we present a recursive version of the genus formula and an elementary proof of formulas of the numbers of $D(N)$, cusps and elliptical points on $X_0(N)$.

The steep rise in reinforcement learning (RL) in various applications in energy as well as the penetration of home automation in recent years are the motivation for this article. It surveys the use of RL in various home energy management system (HEMS) applications. There is a focus on deep neural network (DNN) models in RL. The article provides an overview of reinforcement learning. This is followed with discussions on state-of-the-art methods for value, policy, and actor–critic methods in deep reinforcement learning (DRL). In order to make the published literature in reinforcement learning more accessible to the HEMS community, verbal descriptions are accompanied with explanatory figures as well as mathematical expressions using standard machine learning terminology. Next, a detailed survey of how reinforcement learning is used in different HEMS domains is described. The survey also considers what kind of reinforcement learning algorithms are used in each HEMS application. It suggests that research in this direction is still in its infancy. Lastly, the article proposes four performance metrics to evaluate RL methods.

The main objective of the paper is to provide a thorough analysis of currently used modulation control schemes for single phase bidirectional dual active bridge DC/DC converter. In this article, it will be shown that single phase shift, extended phase shift and Dual phase shift modulation schemes are special cases of triple phase shift (TPS) modulation scheme. The article aims to highlight six TPS switching modes and their complements with the operational constraints. Unlike previous studies that regarded TPS as a complex scheme, this paper simplifies the analysis of each mode and aims to standardize the understanding of TPS modulation in DAB converters. Power equations, range of power transferred and zero voltage switching (ZVS) are derived for all the modes under TPS without assuming fundamental component analysis. Additionally, a generic optimization algorithm is developed to show the advantages of TPS modulation and thus, detailed analysis presented in this paper provides valuable insights for single phase DAB converter designers in identifying a wide range of optimization algorithms to achieve higher efficiency under TPS modulation. This analysis contributes to the advancement of bidirectional DAB converter technology and facilitates its application in various power electronic systems.

Plasmonic nanocomposites have the ability to enhance light-matter interaction due to the plasmonic effects leading to promising potential applications. In this paper, we theoretically study the group index of the silver nanoparticle-gold nanoparticle-quantum dot plasmonic hybrid system in the optical region of the electromagnetic spectrum using the density matrix approach. The quantum dot is considered to be a three-level atomic system of a lambda configuration, interacting with strong control and weak probe fields. We find that the plasmonic hybrid system exhibits at near resonance a strong switching between slow and fast light, which can be controlled by the inclination angle of the gold nanoparticle and the size of the metals nanoparticles, in addition to the strength and detuning of the control field. Thus, the silver nanoparticle-gold nanoparticle-quantum dot could potentially be used in optoelectronic devices.

Humankind has entered a new era wherein a main characteristic is the convergence of various technologies providing services exerting major impact upon all aspects of human activity, be it social interactions as well as interactions with the natural environment. Fixed networks are about to play a major role in this convergence, since they form, along with mobile networks, the backbone that provides access to a broad gamut of services, accessible from any point of the globe. It is for this reason that we introduce a forward-looking approach for fixed networks, particularly focused on Fixed 6th Generation (F6G) networks. First, we adopt a novel classification scheme for the main F6G services, comprising six categories. This classification is based on the key service requirements, namely latency, capacity and connectivity. F6G networks differ from those of previous generations (F1G-F5G) in that they concurrently support multiple key requirements. We then propose concrete steps towards transforming the main elements of fixed networks, such as optical transceivers, optical switches etc. such that they satisfy the new F6G service requirements. Our study categorizes the main networking paradigm of optical switching into two categories namely ultra-fast and ultra-high capacity switching, tailored to different service categories. With regard to the transceiver physical layer, we propose: a) use of all-optical processing to mitigate performance barriers of analog to digital and digital to analog converters (ADC/DAC); b) exploitation of optical multi-band transmission, space division-multiplexing and adoption of more efficient modulation formats.

Antisense oligonucleotide (ASO)-mediated exon skipping has become a valuable tool for investigating gene function and developing gene therapy. Machine learning-based computational methods such as eSkip-Finder have been developed to predict the efficacy of ASOs via exon skipping. However, these methods are computationally demanding, and the accuracy of predictions remains suboptimal. In this study, we propose a new approach to reduce computational burden and improve prediction performance by using feature selection within machine learning algorithms and ensemble learning techniques. We evaluated our approach using a dataset of experimentally validated exon skipping events, dividing it into training and testing sets. Our results demonstrate that using a 3-way voting approach with random forest, gradient boosting, and XGBoost can significantly reduce computation time to under ten seconds while improving prediction performance, as measured by R2 for both 2’-O-methyl nucleotides (2OMe) and phosphorodiamidate morpholino oligomers (PMOs). Additionally, the feature importance ranking derived from our approach is in good agreement with previously published results. Our findings suggest that our approach has the potential to enhance the accuracy and efficiency of predicting ASO efficacy via exon skipping. It could also facilitate the development of novel therapeutic strategies. This study could contribute to the ongoing efforts to improve ASO design and optimize gene therapy approaches.

Antisense oligonucleotide (ASO)-mediated exon skipping has emerged as a powerful tool for examining the function of genes and exons in basic research, as well as gene therapy. Computational methods, such as eSkip-Finder, have been developed to predict the efficacy of ASOs via exon skipping using machine learning. However, these methods can be computationally demanding and the prediction accuracy of the tool is not yet optimal. In this study, we propose an approach to reduce computational burden and improve prediction performance by utilizing feature selection within machine learning algorithms and employing ensemble learning techniques. The method was evaluated using a dataset of genes with experimentally validated exon skipping events. The dataset was divided into training and testing sets to assess the accuracy of the algorithm. Our results demonstrate that using a 3-way voting approach with random forest, gradient boosting, and XGBoost can significantly reduce computation time to under ten seconds while improving prediction performance, as measured by R2 for both 2’-O-methyl nucleotides (2OMe) and phosphorodiamidate morpholino oligomers (PMOs). Additionally, the feature importance ranking derived from our approach is in good agreement with previously published results. These findings suggest that this approach has the potential to enhance the efficiency and accuracy of predicting ASO efficacy via exon skipping, facilitating the development of novel therapeutic strategies.

Molecule radiation can be used as a tool to study colder regions in switching arc plasmas like arc fringes in contact to walls and ranges around current zero (CZ). This is demonstrated in the present study for the first time for the case of ablation-dominated high–current arcs as key elements of self–blast circuit breakers. The arc in a model circuit breaker (MCB) in CO2 with and an arc in a long nozzle under ambient conditions with peak currents between 5 and 10 kA were studied by emission and absorption spectroscopy in the visible spectral range. The nozzle material was polytetrafluoroethylene (PTFE) in both cases. Imaging spectroscopy was carried out either with high-speed cameras or with intensified CCD cameras. A pulsed high-intensity Xe lamp was applied as background radiator for the broad-band absorption spectroscopy. Emission of Swan bands from carbon dimers was observed at the edge of nozzles only or across the whole nozzle radius with highest intensity in the arc center, depending on current and nozzle geometry. Furthermore, absorption of C2 Swan bands and CuF bands were found with the arc plasma serving as background radiator. After CZ, only CuF was detected in absorption experiments.

Electrical properties of the thin films of poly(arylene ether ketone) copolymers (co-PAEKs) with the fraction of phthalide-containing units of 3, 5 and 50 mol% in the main chain were investigated by using radiation induced conductivity (RIC) measurements. Transient current signals and current-voltage (I-V) characteristics were obtained under exposing 20÷25 thick films of the co-PAEKs to monoenergetic electron pulses of the energy ranged from 3 to 50 keV in the electric field ranged from 5 to 40 V/μm. The Rose-Fowler-Vaisberg semi-empirical model based on a multiple trapping formalism was used for an analysis of the RIC data and the parameters of the highly dispersive charge carrier transport were evaluated. The analysis revealed that charge carriers moved in isolation from each other and the applied electric fields were below the threshold field triggering the switching effect (a reversible high-to-low resistivity transition) in the co-PAEK films. It was also found that the co-PAEK films due to the super-linear I-V characteristics are highly resistant to electrostatic discharges arising from the effects of ionizing radiation. This property is important for the development of protective coatings for electronic devices.

In recent years, numerous topologies of single phase and three phase Field Excited Flux-Switching Machine (FEFSM) have been developed for several applications. Comparative study of three types of single-phase low-priced Field Excited Flux-Switching Machine (FEFSM) is presented in this paper. Both the conventional 8S/4P sub-part rotor design and 6S/3P salient rotor design have an overlapped winding arrangements between armature coil and field excitation coil that depicts high copper losses as well as results in increased size of motor. Additionally, FEFSM with salient structure of the rotor have high flux strength in the stator-core that has much impact on high iron losses. Copper consumption and iron loss being a crucial proportion in total machine losses. Therefore a novel topology of single phase modular rotor field excited FSM with 8S/6P configuration is proposed, which enable non-overlap arrangement between armature coil and FEC winding that facilitates devaluation in the copper losses. The proposed modular rotor design acquires reduced iron losses as well as reduced active rotor mass comparatively to conventional rotor design. It is very persuasive to analyze the best range of speed for these rotors to avoid cracks and deformation, the maximum tensile strength (can be measured with principal stress in research) of the rotor analysis is conducted using JMAG. A deterministic optimization technique is used to enhance the performance of 8S/6P modular rotor design. The electromagnetic performance of conventional sub-part rotor design, F1-A3-3P design and proposed novel-modular rotor design are analyzed by 3D-Finite Element Analysis (3D-FEA), includes flux linkage, flux distribution, flux strength, back-EMF, cogging torque, torque characteristics, iron losses and efficiency.

In computer networks, loss of data packets is inevitable, in particular, because of the buffer memory overflow of at least one of the nodes located on the path from the source to the receiver, including the latter. Such losses associated with overflows are hereinafter referred to as congestion of network nodes. There are many ways to prevent and eliminate overloads; these methods, in the majority, are based on the management of data flows. A special place is taken by the maintenance of packages, taking into account their priorities. The article considers a number of original technical solutions to improve the quality of control and reduce the required amount of buffer memory of network nodes. The ideas of these solutions are quite simple for their implementation in the development of appropriate software and hardware for telecommunication devices.

INTRODUCTION: Breast sensibility following reconstruction surgery, though often overlooked, holds significant importance due to its widespread occurrence and profound effects on patients’ well-being and safety. Our objective is to compare the sensory outcomes between DIEP flap microsurgery reconstruction and implant-based reconstruction. Additionally, we explored the potential influence of sociodemographic and clinical factors on sensory recovery, along with assessing temperature discrimination abilities and evaluating quality of life. MATERIAL AND METHODS: We conducted an ambispective descriptive-analytical study, involving women who underwent mastectomy with reconstruction using either DIEP flap and implants at our hospital between 1990 and 2021. Data were collected from medical records, patient histories, physical examination, and validated quality of life questionnaires (BREAST-Q). RESULTS: A total of 99 women with breast reconstruction were included, 47 with DIEP flap and 52 with implants. Sensory recovery in implant-based reconstruction was found to be superior to DIEP flap reconstruction (5.03 and 5.18 respectively, p-value <0.005). A direct correlation was observed between sensory improvement and thermal discrimination (Spearman coefficient 0.9, p-value <0.001). Factors such as radiotherapy, delayed reconstruction with DIEP flap, and height with implants were associated with poorer sensory recovery in the breast. Women experiencing better breast sensibility reported higher satisfaction with their surgeon, medical team, and psychosocial quality of life. CONCLUSION: Women reconstructed with implants or DIEP abdominal flap exhibit suboptimal overall sensory recovery of the reconstructed breast, with slightly better outcomes observed in women reconstructed with implants.

One third of a person’s life is spent on sleep, therefore the quality and habit of sleep affects health. A single case study indicated that perspiration could serve as a prognostic marker. Diagnosing nocturnal perspiration is common clinical practice, since this serves as a major symptom in many pathologies. Till this day no specific evidence-based approach for diagnosing nocturnal perspiration exists. By introducing the Q-strip, a device which quantitatively measures nocturnal perspiration, this could be acquired. The Q-strip could serve a purpose in diagnosing nocturnal perspiration more efficient without being intrusive. In addition to its health sensing potentials, the Q-strip makes it possible to visualise perspiration patterns. This introduces the possibility to examine the quality of sleep. Future research is recommended to investigate this.

A review is here provided about the thermal effects on the optical chirality. To this goal, chiral objects dispersed in an embedding fluid are examined for their magnetoelectric coupling. Thermal effects on several chiral meta-atoms and their ensembles are examined. To this goal, DNA-like helical structures are examined in detail. Mechanical aspect of thermo-elasticity is reviewed along with transverse deformations, while drawing analogies from condensed-matter physics. In this respect, chirality-induced spin selection is reviewed along with the temperature-mediated elec-tron-phonon interactions. A wide range of materials such as polymers and biological cells are also examined for temperature effects. A transition temperature delineating a sign flip in the chirality parameter is identified as well. Chirality-associated functionalities such as ratchet motions, switching, and modulations are investigated for their respective thermal effects. Issues of fabri-cating chiral meta-atoms are also discussed.

A review is here provided on the thermal effects on the optical chirality. To this goal, chiral objects dispersed in an embedding fluid are examined for their magnetoelectric coupling. Archetypal twisted-Omega particles are examined with respect to electron transport, phonon dynamics, and temperature effects. Continuum-mechanical aspect of thermo-elasticity is reviewed along with transverse deformations. A transition temperature delineating a sign flip in the chirality parameter is identified as well.

The development of saltiness enhancement peptides is important in reducing salt intake and promoting dietary health. Our study aimed to analyze and identify straw mushroom enzymatic peptides with salty taste enhancing effects. The taste-related peptides within the straw mush-room extract were isolated via ultrafiltration and identified using UPLC-Q-TOF-MS/MS. Sub-sequent, E-tongue and sensory analyses unveiled that the ultrafiltration fraction (500-2000 Da) of straw mushroom peptides exhibited a saltiness enhancement effect. The UPLC-Q-TOF-MS/MS analysis identified 220 peptides within the ultrafiltration fractions (500-2000 Da), which were then assessed for their interaction with the T1R1/T1R3 receptor. The investigation underscored the significant involvement of Asp223, Gln243, Leu232, Asp251, and Pro254 in the binding of peptides from triple enzymatically hydrolyzed straw mushrooms to T1R1/T1R3. Based on the binding energy and active site analysis, three peptides were selected for synthesis: DFNALPFK (-9.2 kcal/mol), YNEDNGIVK (-8.8 kcal/mol), and VPGGQEIKDR (-8.9 kcal/mol). Notably, 3.2 mmol of VPGGQEIKDR enhanced a 0.05% NaCl solution to the saltiness level of a 0.15% NaCl solution. Also, 0.8 mmol of YNEDNGIVK elevated a 0.05% NaCl solution to the saltiness of a 0.1% NaCl solution.

Full-order state-space models represent the starting point for the development of advanced control methods for wind turbine systems (WTSs). Regarding existing control-oriented WTS models, two research gaps must be noted: (i) There exists no full-order WTS model in form of one overall ordinary differential equation that considers all dynamical effects which significantly influence the electrical power output; (ii) all existing reduced-order WTS models are subject to rather arbitrary simplifications and are not validated against a full-order model. Therefore, in this paper, two full-order nonlinear state-space models (of 11th and 9th-order in the (a, b, c)- and (d, q)-reference frame, resp.) for variable-speed variable-pitch permanent magnet synchronous generator WTSs are derived. The full-order models cover all relevant dynamical effects with significant impact on the system’s power output, including the switching behavior of the power electronic devices. Based on the full-order models, by a step-by-step model reduction procedure, two reduced-order WTS models are deduced: A non-switching (averaging) 7th-order WTS model and a non-switching 3rd-order WTS model. Comparative simulation results reveal that all models capture the dominant system dynamics properly. The full-order models allow for a detailed analysis covering the high frequency oscillations in the instantaneous power output due to the switching in the power converters. The reduced-order models provide a time-averaged instantaneous power output (which still correctly reflects the energy produced by the WTS) and come with a drastically reduced complexity making those models appropriate for large-scale power grid controller design.

In this paper, we investigate p-adic q-integral (q-Volkenborn integral) on Z_p of p-adic gamma function via their Mahler expansions. We also derived two q-Volkenborn integrals of p-adic gamma function in terms of q-Daehee polynomials and numbers and q-Daehee polynomials and numbers of the second kind. Moreover, we discover q-Volkenborn integral of the derivative of p-adic gamma function. We acquire the relationship between the p-adic gamma function and Stirling numbers of the first kind. We finally develop a novel and interesting representation for the p-adic Euler constant by means of the q-Daehee polynomials and numbers.

This study seeks to determine how economic policy uncertainty (EPU) influences investment decisions and the market value of the Pakistan Stock Exchange. The study examines investment and operational data from 249 energy and petroleum companies between 2015 and 2020, in addition to macroeconomic variables such as EPU. This study investigates the moderating effects of EPU on investments in fixed and intangible assets, as well as its effect on Tobin's Q and the market price per share. The outcomes demonstrate that EPU reduces the costs of both tangible and intangible assets for businesses. In addition, companies with a greater Tobin's Q and market price per share are more impacted by uncertain corporate investment policies. However, financial leverage is found to be negatively correlated with share price and positively correlated with earnings per share and earnings per unit. Tobin's Q is positively correlated with financial leverage, indicating that firms that raise capital through debt are more likely to create value for investors. The research indicates that market-dependent enterprises are more susceptible to the unpredictability of monetary policy. Eventually, the findings suggest that consistent and transparent economic policies may increase the efficiency of corporate investment.

Motivated by Kurt's work [Filomat 30 (4) 921-927, 2016], we first consider a class of a new generating function for (p, q)-analog of Apostol type polynomials of order a including Apostol-Bernoulli, Apostol-Euler and Apostol-Genocchi polynomials of order a. By making use of their generating function, we derive some useful identities. We also introduce (p, q)-analog of Stirling numbers of second kind of order v by which we construct a relation including aforementioned polynomials.

We discuss two queueing-inventory systems with catastrophes in the warehouse. Catastrophes occur according to Poisson process and upon arrival of a catastrophe all inventory in the system is instantly destroyed. But consumer customers in the system (in the server or in the buffer) continue still waiting for the replenishment of the stock. The arrivals of the consumer customers follow a Markovian Arrival Process (MAP) and they can be queued in an infinite buffer. Service time of a consumer customer follows a phase-type distribution. The system receives negative customers whose have Poisson flows to service facility and upon arrival of a negative customer one consumer customer is pushed out from the system, if any. One of two replenishment policies can be used in the system: either (s,S) or (s,Q). If upon arrival of the consumer customer, the inventory level is zero, then according to the Bernoulli scheme, this customer is either lost (lost sale scheme) or join the queue (backorder sale scheme). The system is formulated by a four-dimensional continuous-time Markov chain. Steady state distribution is obtained using the matrix-geometric method. A comprehensive numerical study is performed on the performance measures under various replenishment policies. Finally, an optimization study is presented.

This article focuses on developing a continuous authentication system using behavioral biometrics to recognize users accessing computing devices. The user’s distinct behavioral biometric is captured through keystroke dynamics, and reward-based reinforcement learning (RL) ideas are applied to recognize them throughout the session. The suggested system adds an extra layer of security to traditional authentication methods, forming a robust continuous authentication system that can be added to static authentication systems. The methodology involves training a RL model to detect unusual user typing patterns and flag suspicious activity. Each user has an agent trained on their historical data, which is preprocessed and used to create episodes for the agent to learn from. The environment involves fetching observations and randomly corrupting them to learn out-of-order behavior. The observation vector includes both running features and summary features. The re-ward function is binary and minimalistic. The Principal Component Analysis (PCA) model is used to encode the running features, and the Double Deep Q-Network (DDQN) algorithm with a fully connected neural network is used as the policy net. The evaluation achieved an average training accuracy and EER (equal error rate) of 94.7% and 0.0126 and test accuracy and ERR of 81.06% and 0.0323 for all users when the number of encoder features was increased. Therefore, it is concluded that by continuously learning and adapting to changing behavior patterns, this approach can provide more secure and personalized authentication, lowering the possibility of unauthorized access and cyberattacks. Overall, the use of reinforcement learning and behavioral biometrics for continuous authentication has the potential to significantly enhance security in the digital age and are effective in identifying each user.

(1) Background: This work aimed to conduct the first comparative study providing long-term data about patient reported outcome measures as well as donor-site scar assessment and aesthetic evaluation of the reconstructed breasts in patients with DIEP versus PAP flap breast reconstruction. (2) Methods: This prospective, single-center, matched cohort study included a total of 36 patients after DIEP and PAP flap breast reconstruction. Evaluation was done using the Breast-Q and POSAS questionnaire as well as the Breast Aesthetic Scale for cosmetic analysis by four plastic surgeons. (3) Results: Post-operative Breast-Q evaluation revealed no significant differences between both patient groups for the categories physical well-being donor-site, physical well-being breast and satisfaction with the breast. Scar evaluation of the donor-site region showed equivalent results for the thigh and the abdomen concerning the overall opinion of patients and observers. There was no significant difference between both methods of reconstruction for all aspects of breast aesthetics. (4) Conclusions: Similar results of donor-site morbidity, scar quality and aesthetic outcome of the breast in both the DIEP and PAP patient group have been demonstrated. Hence, in cases suitable for both types of reconstruction, the decision can be based on factors such as patients’ lifestyle, leisure activities and preferences.

The compound, C27H23N3 (1), crystallizes in the triclinic system of the P-1 space group. The unit cell comprises a dimer of 1, in which the monomers are linked by two complementary hydrogen bonds between N1 and H1-C1 of another molecule. The dimers form chains along the a-axis through intermolecular interactions between the N2 acceptor atoms and C17 donors from molecules in the nearest neighbouring dimer. These interactions form extended sheets of the dimers of 1, along the ab plane. The quinolinylmeth-2-yl groups of 1 lie in almost orthogonal planes and their N1/2(q) donor atoms being away from the apical amino N3 atom.

In this paper, we introduce the (ρ,q)-analogue of the p-adic factorial function. By utilizing some properties of (ρ,q)-numbers, we obtain several new and interesting identities and formulas. We then construct the p-adic (ρ,q)-gamma function by means of the mentioned factorial function. We investigate several properties and relationships belonging to the foregoing gamma function, some of which are given for the case p = 2. We also derive more representations of the p-adic (ρ,q)-gamma function in general case. Moreover, we consider the p-adic (ρ,q)-Euler constant derived from the derivation of p-adic (ρ,q)-gamma function at x = 1. Furthermore, we provide a limit representation of aforementioned Euler constant based on (ρ,q)-numbers. Finally, we consider (ρ,q)-extension of the p-adic beta function via the p-adic (ρ,q)-gamma function and we then investigate various formulas and identities.

In this paper, we investigate several relations for p-adic gamma function by means of their Mahler expansion and fermionic p-adic q-integral on ℤ_{p}. We also derive two fermionic p-adic q-integrals of p-adic gamma function in terms of q-Boole polynomials and numbers. Moreover, we discover fermionic p-adic q-integral of the derivative of p-adic gamma function. We acquire a representation for the p-adic Euler constant by means of the q-Boole polynomials. We finally develop a novel, explicit and interesting representation for the p-adic Euler constant including Stirling numbers of the first kind.

In this paper, we investigate p-adic q-integral (q-Volkenborn integral) on ℤ_{p} of p-adic gamma function via their Mahler expansions. We also derived two q-Volkenborn integrals of p-adic gamma function in terms of q-Daehee polynomials and numbers and q-Daehee polynomials and numbers of the second kind. Moreover, we discover q-Volkenborn integral of the derivative of p-adic gamma function. We acquire the relationship between the p-adic gamma function and Stirling numbers of the first kind. We finally develop a novel and interesting representation for the p-adic Euler constant by means of the q-Daehee polynomials and numbers.

In the present paper, the (p,q)-Hermite based Apostol type Frobenius-Euler polynomials and numbers are firstly considered and then diverse basic identities and properties for the mentioned polynomials and numbers, including addition theorems, difference equations, integral representations, derivative properties, recurrence relations. Moreover, we provide summation formulas and relations associated with the Stirling numbers of the second kind.

A novel effective vibrational mode was discovered in the conventional transducer with an array of orthogonal (square) regular piezoelectric rods in 1-3 piezocomposite, containing the damping backing and front matching layers. The operational resonance in the structure was determined as the Surface Acoustic Wave (SAW) on the backing boundary excited by the adjacent piezo-rods, with its frequency typically near 3 times lower the fundamental half-lambda conventional piezocomposite resonance. Pulse-echo sensitivity and transmitting sound-pressure-level (SPL) in air showed that the signal strength is roughly comparable to the industrial similar air transducers at the frequency range 100…700 kHz, where at these frequencies the lateral and longitudinal piezoelement dimensions in the conventional transducer design are typically close to each other causing interference with unwanted coupling modes. As was determined theoretically and proved in experiments, the backing SAW resonance effect in the transducer performance is inherent just to the regular periodic 1-3 piezocomposite structure, and does occur neither with randomly located/oriented piezo-rods, nor in the homogeneous piezo-plate at least with the same lateral cross-section as the connected to it backing. The purpose of the article is to investigate a newly discovered operational vibrational mode of a SAW type in 1-3 regular piezocomposite, other than piezoelectric resonance. The investigated phenomena can improve the transceiver sensitivity, bandwidth, providing lower drive voltage, and smaller and lighter weight ultrasonic transducers. Based on the piezocomposites with thickness’ 1…1.5 mm (rod resonance near 2…3 MHz), pillar width 0.2…0.8 mm, kerf width 0.1…0.4 mm, the transceivers with an operating frequency from 140 kHz to 650 kHz were designed and fabricated with a conventional backing of a mixture of high-density tungsten powder and epoxy, and a matching layer of a mixture of low-density glass bubbles and epoxy. Experimental evaluation of their acoustical performance showed expected characteristics suitable for practical applications.

In this paper, we derive multifarious relationships among the two types of higher order q-Daehee polynomials and p-adic gamma function via Mahler theorem. Also, we compute some weighted p-adic q-integrals of the derivative of p-adic gamma function related to the Stirling numbers of the both kinds and the q-Bernoulli polynomials of order k.

In this article, two elliptical-ovel-shaped cylindrical dielectric resonator based wideband Graphene inspired reconfigurable metasurface absorber is designed on diffused quartz substrate having a relative permittivity of 3.75 and conductivity 2200Kg/m3 with height of 25μm. This metasurface having gold plated ground in microstrip with 5μm which is essential by calculating skin depth at 2.0THz frequency. Two elliptical ovel shaped patches with Graphene plated having built in potential varies 0-2.5eV and relaxation time 1.0ps at 290oK. By changing the relaxation time of Graphene 0.1ps-0.3ps its resonance frequency also varies i.e., reconfigurable property they provide without adding any active i.e., PIN diode components. The proposed MS is designed having a dimension of 100×100μm2 is designed on a microstrip. This MS works in the range of 1.6-2.38THz having more than 90% absorbance with two transmission zero at 2.1THz and 2.3THz having high Q ˃ 50 which is used to determine the sensitivity where the proposed MS used as a sensor to determine hemoglobin (Blood Glucose level) and urine (Uric acid) by changing their refractive index from 1.34-1.43. Maximum sensitivity achieved at 2000GHz/RIU and average sensitivity for hemoglobin and urine sensing achieved 833.33GHz/RIU, FOM-8.33 and 4277.7733GHz/RIU, FOM-555.55 respectively.

Matiyasevich's theorem states that there is no algorithm to decide whether or not a given Diophantine equation has a solution in non-negative integers. Smorynski's theorem states that the set of all Diophantine equations which have at most finitely many solutions in non-negative integers is not recursively enumerable. We prove: (1) Smorynski's theorem easily follows from Matiyasevich's theorem, (2 ) Hilbert's Tenth Problem for Q has a negative solution if and only if the set of all Diophantine equations with a finite number of rational solutions is not recursively enumerable.

Assuming a two component, positive and negative mass, superfluid/supersolid for space (the Winterberg model), we model the Higgs field as a condensate made up of a positive and a negative mass, planckion pair. The connection is shown to be consistent (compatible) with the underlying field equations for each field, and the continuity equation is satisfied for both species of planckions, as well as for the Higgs field. An inherent length scale for space (the vacuum) emerges, which we estimate from previous work to be of the order of,

Soft-Core architecture for Analogue to Digital Converter (ADC) sampling is useful for mixed signal applications. Soft-core architecture for cutting edge odd or even ADC sampling with interface to block RAM memory has not been found. Soft-core architecture as a concept has become popular due to the advantage of customization for different applications as compared to general-core architecture suited for single application. The latest generation of piece wise sampling is odd sampling and was introduced in the second decade of the 20th century. Odd and even order sampling techniques are analogue in nature driven by a tuned (tuned for odd or even) mixer. This paper proposes a third-generation piece wise sampling with soft-core architecture that enables an option to select both odd and even while interfacing to memory mapping. The proposed odd/even has superior SNR performance of 6 dB as compared to existing architecture such as Mod-∆ which recorded worst performance of 18 dB. Advances in soft-core technology have allowed a niche odd/even switching field to be identified and studied, the study has also been extended to include memory architecture.