Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also provides transformative solutions for various sectors. This research looks into open-source IIoT and edge platforms that are applicable to a range of applications with the aim of finding and developing high-potential solutions. It highlights the effect of open-source IIoT and edge computing platforms on traditional IIoT applications, showing how these platforms make development and deployment processes easier. Popular open-source IIoT platforms include DeviceHive and Thingsboard, while EdgeX Foundry is a key platform for edge computing, allowing IIoT applications to be deployed closer to data sources, thus reducing latency and conserving bandwidth. This study seeks to identify potential future domains for the implementation of IIoT solutions using these open-source platforms. Additionally, each sector is evaluated based on various criteria, such as development requirement analyses, market demand projections, the examination of leading companies and emerging startups in each domain, and the application of the International Patent Classification (IPC) scheme for in-depth sector analysis. Full article

Brain injury resulting from adverse events during pregnancy and delivery is the leading cause of neonatal morbidity and disability. Surviving neonates often suffer long-term motor, sensory, and cognitive impairments. Birth asphyxia is among the most common causes of neonatal encephalopathy. The integration of ultrasound, including Doppler ultrasound, and near-infrared spectroscopy (NIRS) offers a promising approach to understanding the pathology and diagnosis of encephalopathy in this special patient population. Ultrasound diagnosis can be very helpful for the assessment of structural abnormalities associated with neonatal encephalopathy such as alterations in brain structures (intraventricular hemorrhage, infarcts, hydrocephalus, white matter injury) and evaluation of morphologic changes. Doppler sonography is the most valuable method as it provides information about blood flow patterns and outcome prediction. NIRS provides valuable insight into the functional aspects of brain activity by measuring tissue oxygenation and blood flow. The combination of ultrasonography and NIRS may produce complementary information on structural and functional aspects of the brain. This review summarizes the current state of research, discusses advantages and limitations, and explores future directions to improve applicability and efficacy. Full article

A double optimal solution (DOS) of a least-squares problem $\mathbf{A}\mathbf{x}=\mathbf{b},\mathbf{A}\in {\mathbb{R}}^{q\times n}$ with $q\ne n$ is derived in an $m+1$-dimensional varying affine Krylov subspace (VAKS); two minimization techniques exactly determine the $m+1$ expansion coefficients of the solution $\mathbf{x}$ in the VAKS. The minimal-norm solution can be obtained automatically regardless of whether the linear system is consistent or inconsistent. A new double optimal algorithm (DOA) is created; it is sufficiently time saving by inverting an $m\times m$ positive definite matrix at each iteration step, where $m\ll min(n,q)$. The properties of the DOA are investigated and the estimation of residual error is provided. The residual norms are proven to be strictly decreasing in the iterations; hence, the DOA is absolutely convergent. Numerical tests reveal the efficiency of the DOA for solving least-squares problems. The DOA is applicable to least-squares problems regardless of whether $q<n$ or $q>n$. The Moore–Penrose inverse matrix is also addressed by adopting the DOA; the accuracy and efficiency of the proposed method are proven. The $m+1$-dimensional VAKS is different from the traditional m-dimensional affine Krylov subspace used in the conjugate gradient (CG)-type iterative algorithms CGNR (or CGLS) and CGRE (or Craig method) for solving least-squares problems with $q>n$. We propose a variant of the Karush–Kuhn–Tucker equation, and then we apply the partial pivoting Gaussian elimination method to solve the variant, which is better than the original Karush–Kuhn–Tucker equation, the CGNR and the CGNE for solving over-determined linear systems. Our main contribution is developing a double-optimization-based iterative algorithm in a varying affine Krylov subspace for effectively and accurately solving least-squares problems, even for a dense and ill-conditioned matrix $\mathbf{A}$ with $q\ll n$ or $q\gg n$. Full article

The longleaf pine (Pinus palustris P. Mill.) forest type occupied a much greater area in the United States prior to the arrival of Europeans, estimated to be around 37.2 million hectares. This area has been greatly reduced, and these ecosystems now occupy only about 1.2 to 1.6 million hectares. However, there has been a great interest in the restoration of this forest type mainly due to concerns about the loss of ecosystem services associated with these forests; the improved seedling quality and yield potentials bolster those efforts. Beyond that, existing stands are actively managed through different types of practices, including thinnings, prescribed burns often to manipulate the vegetation of other species, and the various timings of clearcuts. Thus, managers need tools to estimate site quality and ultimately productivity. A commonly used measure of site quality is site index, or the height of some defined dominant portion of the stand at a standardized base or index age. The primary objectives are to summarize the 16 existing equations to estimate site index and dominant height in naturally regenerated longleaf pine stands and to examine and visually compare their predicted behavior across a range of site quality and age conditions. Important considerations when using site index of anamorphism and polymorphism as well as base-age invariance are reviewed. Biologically, polymorphism is often considered advantageous since for many species differences in site quality not only result in different asymptotic dominant heights, but also varying rates in their approach to the asymptote. Of the 16 equations examined, only nine of them were polymorphic in nature, but all equations were base-age invariant. There is not an individual equation that is clearly superior because, for instance, it is either anamorphic in nature, is polymorphic but developed based on anamorphic curves, fit using data obtained from temporary plots, or it is limited geographically. Given these limitations, others can use this publication as a reference to determine which equation they feel is best for their particular situation. Full article

Objective: To evaluate the preference of primary HCWs and residents on vaccination consultation in community health services to provide evidence for vaccine hesitancy intervention strategies. Methods: A discrete choice model (DCM) was constructed to evaluate the preference difference between primary HCWs and residents on vaccination consultation in community health services in China during May–July 2022. Results: A total of 282 residents and 204 HCWs were enrolled in this study. The residents preferred consulting with an HCW-led approach (β = 2.168), with specialized content (β = 0.954), and accompanied by telephone follow-up (β = 1.552). In contrast, the HCWs preferred face-to-face consultation (β = 0.540) with an HCW-led approach (β = 0.458) and specialized content (β = 0.409), accompanied by telephone follow-up (β = 0.831). College residents and residents with underlying self-reported disease may be near-critically inclined to choose traditional consultation (an offline, face-to-face consultation with standardized content and more prolonged duration) rather than a new-media consulting group (an online consultation with specialized content within 5 min). Urban HCWs preferred long-term consultation groups (the resident-led offline consultation with follow-up lasting more than 5 min). In contrast, rural HCWs preferred efficient consultation (the HCW-led, short-duration, standardized offline consultation mode). Conclusion: The selection preference for vaccine consultation reveals a gap between providers and demanders, with different groups exhibiting distinct preferences. Identifying these targeted gaps can help design more acceptable and efficient interventions, increasing their likelihood of success and leading to better resource allocation for policymakers to develop targeted vaccination policies. Full article

The aim of this work was to analyze the influence of acute normobaric hypoxia on quadricep oxygenation. Muscle oxygen saturation (SmO₂) was measured using near-infrared spectrometry (NIRS) technology during a normobaric hypoxia tolerance test (NHTT). SmO₂ was measured with a Humon Hex^® device. In total, 54 healthy subjects participated, 68.5 of which were males and 31.5% of which were females. They performed an NHTT with the IAltitude^® simulator, breathing air with an FiO₂ level of 11% (equivalent to 5050 m). The maximum duration of the NHTT was set at 10 min, stopping if it reached 83% SpO₂. The initial values (PRE) were compared with those obtained at the end of the test (POST) and after 10 min of recovery. The participants were divided into two groups based on whether (G1) they completed the ten minutes or not (G2). In total, 35.1% of men and 41.2% of women completed the 10 min. In both groups, significant differences were observed in the decrease in SmO₂ values (p < 0.0001) (G1: PRE = 59.5 ± 12.48%; POST = 55.95 ± 14.30%; G2: PRE = 60.06 ± 13.46%; POST = 57.2 ± 12.3%). There were no differences between groups in any of the three periods. Exposure to normobaric hypoxia produces a decrease in quadricep levels of SmO₂ in both sexes, regardless of whether the test is completed. Two patterns appeared: A.—less time and more hypoxia; B. a longer duration and less hypoxia. Full article

Phytophthora infestans is the causal agent of late blight in potato. The occurrence of P. infestans with both A1 and A2 mating types in the field may result in sexual reproduction and the generation of recombinant strains. Such strains with new combinations of traits can be highly aggressive, resistant to fungicides, and can make the disease difficult to control in the field. Metalaxyl-resistant isolates are now more prevalent in potato fields. Understanding the genetic structure and rapid identification of mating types and metalaxyl response of P. infestans in the field is a prerequisite for effective late blight disease monitoring and management. Molecular and phenotypic assays involving molecular and phenotypic markers such as mating types and metalaxyl response are typically conducted separately in the studies of the genotypic and phenotypic diversity of P. infestans. As a result, there is a pressing need to reduce the experimental workload and more efficiently assess the aggressiveness of different strains. We think that employing genetic markers to not only estimate genotypic diversity but also to identify the mating type and fungicide response using machine learning techniques can guide and speed up the decision-making process in late blight disease management, especially when the mating type and metalaxyl resistance data are not available. This technique can also be applied to determine these phenotypic traits for dead isolates. In this study, over 600 P. infestans isolates from different populations—Estonia, Pskov region, and Poland—were classified for mating types and metalaxyl response using machine learning techniques based on simple sequence repeat (SSR) markers. For both traits, random forest and the support vector machine demonstrated good accuracy of over 70%, compared to the decision tree and artificial neural network models whose accuracy was lower. There were also associations (p < 0.05) between the traits and some of the alleles detected, but machine learning prediction techniques based on multilocus SSR genotypes offered better prediction accuracy. Full article

Objectives: Metatarsalgia continues to be a problem in patients with rheumatoid arthritis (RA) in remission (remRA), as well as in the non-rheumatic population, with a mechanical origin. Identify and compare clinical, morphological, disability, synovitis (ultrasound), and radiological osteoarticular damage characteristics in two groups of patients with lesser-ray metar-tarsalgia, with remRA, and without RA. Methods: Cross-sectional study with 84 patients with remRA (mRA) and 60 patients without RA (nmRA). The study evaluated five clinical variables (pain, Foot Function Index (FFI), joint mobility, digital deformities, and foot type), a radiological variable (osteoarticular damage), and an ultrasound variable (metatarsal synovitis). The data were analysed using descriptive and correlational techniques. Results: There were no significant differences in sex, age, body mass index (BMI), or degree of pain. Both groups showed a high prevalence of limited joint mobility for the ankle and first metatarsal phalanx (DF1st MTPJ) and digital deformities, with no statistically significant differences. Similarly, there were no differences in lesser-ray synovitis. On the other hand, there were differences in mRA with greater disability and activity limitation (FFI), LDD (lesser-ray digital deformities) stiffness, first-ray deformities, radiological damage, synovitis in 1st MTPJ, and positive Doppler (five patients). Conclusions: Metatarsalgia presents similarities in both populations. Biomechanical factors may influence the symptoms and presence of synovitis in patients with RA in remission. Other characteristics are more frequent in mRA, which could be related to the disease; thus, future research should include both biomechanical and ultrasound exploration of the foot in the valuation of patients in remission. Full article

The paper introduces a powerful method for developing lightweight designs and enhancing the load-bearing capacity of common structures. The method, referred to as the ‘method of aggregation’, has been derived from reverse engineering of sub-additive and super-additive algebraic inequalities. The essence of the proposed method is consolidating multiple elements loaded in bending into a reduced number of elements with larger cross sections but a smaller total volume of material. This procedure yields a huge reduction in material usage and is the first major contribution of the paper. For instance, when aggregating eight load-carrying beams into two beams supporting the same total load, the material reduction was more than 1.58 times. The second major contribution of the paper is in demonstrating that consolidating multiple elements loaded in bending into a reduced number of elements with larger cross sections but the same total volume of material leads to a big increase in the load-bearing capacity of the structure. For instance, when aggregating eight cantilevered or simply supported beams into two beams with the same volume of material, the load-bearing capacity until a specified tensile stress increased twice. At the same time, the load-bearing capacity until a specified deflection increased four times. Full article

Google Scholar produces about 278 hits for the term “inertial propulsion”. If patents are also included, the number of hits increases to 536. This paper discusses, in a critical way, some characteristic aspects of this controversial topic. The review starts with the halteres of athletes in the Olympic games of ancient times and then continues with some typical devices which have been developed and/or patented from the second quarter of the twentieth century to the present day. Full article

This paper pioneers a novel approach in electromagnetic (EM) system analysis by synergistically combining Bayesian Neural Networks (BNNs) informed by Latin Hypercube Sampling (LHS) with advanced thermal–mechanical surrogate modeling within COMSOL simulations for high-frequency low-pass filter modeling. Our methodology transcends traditional EM characterization by integrating physical dimension variability, thermal effects, mechanical deformation, and real-world operational conditions, thereby achieving a significant leap in predictive modeling fidelity. Through rigorous evaluation using Mean Squared Error (MSE), Maximum Learning Error (MLE), and Maximum Test Error (MTE) metrics, as well as comprehensive validation on unseen data, the model’s robustness and generalization capability is demonstrated. This research challenges conventional methods, offering a nuanced understanding of multiphysical phenomena to enhance reliability and resilience in electronic component design and optimization. The integration of thermal variables alongside dimensional parameters marks a novel paradigm in filter performance analysis, significantly improving simulation accuracy. Our findings not only contribute to the body of knowledge in EM diagnostics and complex-environment analysis but also pave the way for future investigations into the fusion of machine learning with computational physics, promising transformative impacts across various applications, from telecommunications to medical devices. Full article

Background and Objectives: Besides classical stapedotomy, reverse stapedotomy has been used for many years in the management of otosclerosis. Our study aims to investigate whether reversing the surgical steps in stapedotomy impacts vestibular function and hearing improvement. Materials and Methods: A cohort of 123 patients underwent either classic or reverse stapedotomy procedures utilizing a fiber–optic argon laser. Audiological assessments, following the guidelines of the Committee on Hearing and Equilibrium, were conducted, including pure tone average, air–bone (AB) gap, overclosure, and AB gap closure. Vestibular evaluation involved pre- and postoperative comparison of rotatory test parameters, including frequency, amplitude, and slow phase velocity of nystagmus. Results: The study demonstrated an overall median overclosure of 3.3 (3.3, 5.0) dB and a mean AB gap closure of 20.3 ± 8.8 dB. Postoperative median AB gap was 7.5 (7.5, 11.3) dB in the reverse stapedotomy group and 10.0 (10.0, 12.5) dB in the classic stapedotomy group. While overclosure and AB gap closure were marginally superior in the reverse stapedotomy group, these differences did not reach statistical significance. No significant disparities were observed in the frequency, slow phase velocity, or amplitude of nystagmus in the rotational test. Conclusions: Although not always possible, reverse stapedotomy proved to be a safe surgical technique regarding postoperative outcomes. Its adoption may mitigate risks associated with floating footplate, sensorineural hearing loss, and incus luxation/subluxation, while facilitating the learning curve for less experienced ear surgeons. Full article

The chalkiness, starch fine structure, and physiochemical properties of rice starch were analyzed and their correlations were investigated under different nighttime temperatures during the early grain-filling stage. Compared to MT, medium temperature (MT) and low (LNT) and high (HNT) nighttime temperatures resulted in an increased chalky grain rate (CGR) and chalkiness degree (CD). LNT mainly affected the chalkiness by increasing peak1 (short branch chains of amylopectin), the branching degree, and the proportion of small starch granules but decreasing peak2 (long branch chains of amylopectin) and peak3 (amylose branches). This altered the pasting properties, such as by increasing the peak viscosity and final viscosity. However, HNT mainly affected the chalkiness by increasing peak2 and the crystallinity degree but decreasing peak1 and peak3. Regarding the thermal properties, HNT also elevated peak and conclusion temperatures. The CGR and CD were significantly and positively correlated with the proportions of small and medium starch granules, peak1, branching degree, gelatinization enthalpy, setback viscosity, and pasting time but markedly and negatively correlated with the proportion of large starch granules, amylose content, peak3, peak viscosity, and breakdown viscosity. These findings suggest that LNT and HNT disrupted the starch structure, resulting in increased chalkiness. However, their mechanisms of action differ. Full article

The challenge of denoising low-dose computed tomography (CT) has garnered significant research interest due to the detrimental impact of noise on CT image quality, impeding diagnostic accuracy and image-guided therapies. This paper introduces an innovative approach termed the Wavelet Domain Dual Forward Denoising Stream Network (WaveletDFDS-Net) to address this challenge. This method ingeniously combines convolutional neural networks and Transformers to leverage their complementary capabilities in feature extraction. Additionally, it employs a wavelet transform for efficient image downsampling, thereby preserving critical information while reducing computational requirements. Moreover, we have formulated a distinctive dual-domain compound loss function that significantly enhances the restoration of intricate details. The performance of WaveletDFDS-Net is assessed by comparative experiments conducted on public CT datasets, and results demonstrate its enhanced denoising effect with an SSIM of 0.9269, PSNR of 38.1343 and RMSE of 0.0130, superior to existing methods. Full article

Change-point detection is a challenging problem that has a number of applications across various real-world domains. The primary objective of CPD is to identify specific time points where the underlying system undergoes transitions between different states, each characterized by its distinct data distribution. Precise identification of change points in time series omics data can provide insights into the dynamic and temporal characteristics inherent to complex biological systems. Many change-point detection methods have traditionally focused on the direct estimation of data distributions. However, these approaches become unrealistic in high-dimensional data analysis. Density ratio methods have emerged as promising approaches for change-point detection since estimating density ratios is easier than directly estimating individual densities. Nevertheless, the divergence measures used in these methods may suffer from numerical instability during computation. Additionally, the most popular $\alpha$-relative Pearson divergence cannot measure the dissimilarity between two distributions of data but a mixture of distributions. To overcome the limitations of existing density ratio-based methods, we propose a novel approach called the Pearson-like scaled-Bregman divergence-based (PLsBD) density ratio estimation method for change-point detection. Our theoretical studies derive an analytical expression for the Pearson-like scaled Bregman divergence using a mixture measure. We integrate the PLsBD with a kernel regression model and apply a random sampling strategy to identify change points in both synthetic data and real-world high-dimensional genomics data of Drosophila. Our PLsBD method demonstrates superior performance compared to many other change-point detection methods. Full article

Seismic reflection data and implicitly sonic velocity are undoubtedly the most important source of information for large-scale subsurface characterization. Yet, deriving reservoir and fluid flow properties from acoustic data is still challenging in carbonates, which display large acoustic velocity variations that contest many of the conventional assumptions regarding wave propagation in porous media. In this comprehensive study on 370 carbonate samples (247 limestones and 123 dolomites), we re-evaluate the impact of mineral velocity on bulk rock acoustic properties of dolomite and limestone by assessing the link between sonic velocity and the rock’s pore geometry. We quantify pore size and pore network complexity using parameters from both digital image analysis (DIA) and the extended Biot theory (EBT). We then compare DIA and EBT parameters to assess the impact of pore network geometry versus mineral velocity on the acoustic velocity of carbonate rocks. We explore the usefulness of EBT parameter γ_k in improving permeability estimates. Published values of velocity indicate that dolomites exhibit higher velocities than limestones at any given porosity. Our laboratory measurements of acoustic velocity, however, reveal that both dolomites and limestones show extreme variations in sonic velocities where samples with compressional velocity of ~5000 m/s may range in porosity from 5% to 25% and samples with porosity of ~20% may range in velocity from ~4000 m/s to 5700 m/s. Through the quantitative assessment of the pore network in our samples we document that pore network geometry has much more impact on the acoustic velocity of carbonates than variations in mineralogy, in this case dolomite and calcite. Most of the dolostone samples studied are dominated by small pores, resulting in relatively low velocities for their given porosity, while limestones with similar velocity–porosity values often possess simpler pore networks with larger pores. This pore size difference offsets the faster velocity of dolomite. The extended Biot theory parameter γ_k, captures this variation in pore size and internal geometry and exhibits a strong correlation to specific surface. Moreover, γ_k captures the impact of internal pore geometry on acoustic velocity, providing the basis for challenging existing assumptions regarding the importance of mineral velocity. By quantifying internal geometry, γ_k can improve permeability estimates in reservoir characterization and enhance evaluations of producibility and injectability. With that, it has direct implications on general geophysics, hydrocarbon exploration, and CCS initiatives. Full article

This study addresses the co-pyrogasification of municipal solid waste (MSW) from the Environmental Technology Park, San Juan, Argentina. This process involves heating waste at high temperatures in a low-oxygen or oxygen-free atmosphere as a sustainable strategy for waste management and energy generation. The principal objective is to focus on understanding the MSW co-pyrogasification kinetics to enhance performance in reactor design. A representative sample of MSW collected over a month was analyzed, focusing on the variation in mass proportions of plastic, organic matter, and paper. The empirical methodology included the deconvolution of macro-TGA curves and deep learning algorithms to predict and validate macro-TG data during co-pyrogasification. The findings reveal that MSW is a solid matrix more easily treated on thermochemical platforms, with kinetic and thermodynamic parameters favoring its processing. This approach suggests that MSW co-pyrogasification may represent a feasible alternative for resource recovery and bioenergy production, supporting the policies for the transition to a cleaner future and a circular economy. Full article

The well-known deletion of coda sibilants in Old French (11th–14th centuries) induced a compensatory lengthening effect on the preceding vowel, generally described as applying uniformly where coda /s/ was lost. This study highlights and analyzes phonological contexts where lengthening likely did not occur, examining their interaction with stress assignment, vowel quality, schwa adjustment, prothesis, and morphological structure. The Stratal OT analysis formalizes the proposed pattern differentiating the long and short vowel reflexes identified especially for mid vowels: while categorical in tonic syllables and low vowels /a, ɑ/ irrespective of stress, lengthening only prevails in atonic mid vowels when coda /s/ deletion impacts a syllable assigned stress within the specific stratal phonological cycle when /s/ is deleted from input. The resulting length is transmitted and preserved in subsequent stratal cycles regardless of eventual word-level stress reassignment, especially (but not exclusively) because of word-level schwa adjustment, allowing a shift to word-final stress and producing an opacity effect of a long atonic mid vowel inherited from an earlier cycle. The stratal account formalizes observed analogical effects between lexical items and derived forms with respect to vowel quality and length and proposes them to result instead from the interplay of morphology and phonology. Full article

Background: Sarcopenic obesity (SO) is the combination of excess fat, skeletal muscle and muscular strength/function deficit. The ESPEN/EASO have proposed new diagnostic criteria, but the SO prevalence in patients with severe obesity remains to be established. The aim of this study was to establish the SO prevalence in a large cohort of inpatients with obesity, considering sex, age, BMI, type, and number of concomitant diseases. Methods: Patient data of both genders aged between 18 and 90 years with a body mass index (BMI) of ≥30 kg/m² underwent hospital evaluation including bioelectrical impedance analysis (BIA) and handgrip strength (HS). QoL scores were obtained by the Psychological General Well-Being Index questionnaire. The study was approved by the institutional Ethic Committee. Results: Among the 3858 patients, 444 (11.51%) exhibited a strength deficit, while 3847 (99.71%) had skeletal muscle mass deficit. The prevalence of SO was then 11.48%, with higher rates in women (12.39%), in individuals aged >70 years (27%), and in those reporting a ‘poor’ QoL (12.6%). No significant difference in SO prevalence was found when stratifying by BMI (30–40 kg/m² vs. >40 kg/m², p = 0.1710). In SO patients, osteoarticular diseases (57%), hypertension/heart failure (38%), type 2 diabetes mellitus (34%), and obstructive sleep apnea (32%) were the more frequent comorbidities. Conclusions: The application of ESPEN/EASO-SO criteria in a cohort of inpatients with severe obesity revealed 11.48% SO prevalence, which was associated with age (particularly > 70 years), gender (women), but not BMI, as determinants. Disease staging and QoL screening may improve the identification of SO high-risk patients. Full article

Sound and heat insulation are among the most important concerns in modern life and nonwoven composite structures are highly effective in noise reduction and heat insulation. In this study, three layered nonwoven composite structures composed of a recycled polyester (r-Pet)-based thermo-bonded nonwoven outer layer and meltblown nonwovens from Polypropylene (PP) and Polybutylene terephthalate (PBT) as inner layers were formed to provide heat and sound insulation. Fiber fineness and cross-section of the thermo-bonded outer layer, fiber type (PP/PBT), areal weight (100/200 g/m²) and process conditions (calendared/non-calendared) of the meltblown inner layer were changed systematically and the influence of these independent variables on thickness, bulk density, air permeability, sound absorption coefficient and thermal resistance of composite structures were analyzed statistically by using Design Expert 13 software. Additionally, the results were compared with composite structures including an electrospun nanofiber web inner layer and with structures without an inner layer. It was concluded that comparable or even better sound absorption values were achieved with the developed nonwoven composites containing meltblown layers compared to nanofiber-included composites and the materials in previous studies. Full article

The shift towards sustainable transportation is an urgent worldwide issue, leading to the investigation of creative methods to decrease the environmental effects of traditional vehicles. Electric vehicles (EVs) are a promising alternative, but the issue lies in establishing efficient and environmentally friendly charging infrastructure. This review explores the existing research on the subject of photovoltaic-powered electric vehicle charging stations (EVCSs). Our analysis highlights the potential for economic growth and the creation of robust and decentralized energy systems by increasing the number of EVCSs. This review summarizes the current knowledge in this field and highlights the key factors driving efforts to expand the use of PV-powered EVCSs. The findings indicate that MATLAB was predominantly used for theoretical studies, with projects focusing on shading parking lots. The energy usage varied from 0.139 to 0.295 kWh/km, while the cost of energy ranged from USD 0.0032 to 0.5645 per kWh for an on-grid system. The payback period (PBP) values are suitable for this application. The average PBP was demonstrated to range from 1 to 15 years. The findings from this assessment can guide policymakers, researchers, and industry stakeholders in shaping future advancements toward a cleaner and more sustainable transportation system. Full article

The aim of this work is to obtain novel and interesting results for mild solutions to a semilinear differential inclusion involving a w-weighted, $\Phi$-Hilfer, fractional derivative of order $\mu \in (1,2)$ with non-instantaneous impulses in Banach spaces with infinite dimensions when the linear term is the infinitesimal generator of a strongly continuous cosine family and the nonlinear term is a multi-valued function. First, we determine the formula of the mild solution function for the considered semilinear differential inclusion. Then, we give sufficient conditions to ensure that the mild solution set is not empty or compact. The desired results are achieved by using the properties of both the w-weighted $\Phi$-Laplace transform, w-weighted $\psi$-convolution and the measure of non-compactness. Since the operator, the w-weighted $\Phi$-Hilfer, includes well-known types of fractional differential operators, our results generalize several recent results in the literature. Moreover, our results are novel because no one has previously studied these types of semilinear differential inclusions. Finally, we give an illustrative example that supports our theoretical results. Full article