The purpose of this article is to review the effects of four commonly consumed beverage types—sugar-sweetened beverages (SSBs), caffeinated beverages, green tea, and alcohol—on five common benign gynecological conditions: uterine fibroids, endometriosis, polycystic ovary syndrome (PCOS), anovulatory infertility, and primary dysmenorrhea (PD). Here we outline a plethora of research, highlighting studies that demonstrate possible associations between beverage intake and increased risk of certain gynecological conditions—such as SSBs and dysmenorrhea—as well as studies that demonstrate a possible protective effect of beverage against risk of gynecological condition—such as green tea and uterine fibroids. This review aims to help inform the diet choices of those with the aforementioned conditions and give those with uteruses autonomy over their lifestyle decisions. Full article

Water availability is a limiting factor for plant production, especially in Brazilian semi-arid regions. The main aim of the study was to investigate the physiological effects of drought during the fruiting stage of watermelon cultivation. A completely randomized block design with four replications and six treatments varied by the number of lateral drip tapes (1 or 2) and the duration of drought stress (0, 4, and 8 days) was used. The following parameters were evaluated: relative chlorophyll content, relative leaf water content, electrolyte leakage, CO₂ assimilation (A), stomatal conductance (g_s), internal CO₂ concentration, leaf temperature, transpiration (E), water use efficiency (WUE), carboxylation efficiency (CE), yield, thickness, diameter, length, and fruit °brix, at 4 and 8 days of drought. Drought negatively affected photosynthesis, particularly in treatments with a single dripper and 4 days of drought, resulting in reductions of up to 60% in A, 68% in g_s, 44% in E, 58% in WUE, and 59% in CE, but did not have a significant effect on watermelon yield after 4 or 8 days of irrigation. It was concluded that drought influences the physiological responses of watermelon plants, mainly in reducing photosynthesis, but does not drastically affect fruit productivity in short periods of stress. Full article

Xanthorrhizol, an important marker of Curcuma xanthorrhiza, has been recognized for its different pharmacological activities. A green strategy for selective xanthorrhizol extraction is required. Herein, natural deep eutectic solvents (NADESs) based on glucose and organic acids (lactic acid, malic acid, and citric acid) were screened for the extraction of xanthorrhizol from Curcuma xanthorrhiza. Ultrasound-assisted extraction using glucose/lactic acid (1:3) (GluLA) gave the best yield of xanthorrhizol. The response surface methodology with a Box–Behnken Design was used to optimize the interacting variables of water content, solid-to-liquid (S/L) ratio, and extraction to optimize the extraction. The optimum conditions of 30% water content in GluLA, 1/15 g/mL (S/L), and a 20 min extraction time yielded selective xanthorrhizol extraction (17.62 mg/g) over curcuminoids (6.64 mg/g). This study indicates the protective effect of GluLA and GluLA extracts against oxidation-induced DNA damage, which was comparable with those obtained for ethanol extract. In addition, the stability of the xanthorrhizol extract over 90 days was revealed when stored at −20 and 4 °C. The FTIR and NMR spectra confirmed the hydrogen bond formation in GluLA. Our study reported, for the first time, the feasibility of using glucose/lactic acid (1:3, 30% water v/v) for the sustainable extraction of xanthorrhizol. Full article

In this article, the main problem under investigation is the detection and diagnosis of short-circuit faults in power transmission lines. The proposed fault detection (FDD) approach is mainly based on principal component analysis (PCA). The proposed fault diagnosis/identification (FAI) approach is mainly based on sliding-window versions of the discrete Fourier transform (DFT) and discrete Hilbert transform (DHT). The main contributions of this article are (a) a fault detection approach based on principal component analysis in the two-dimensional scores space; and (b) a rule-based fault identification approach based on human expert knowledge, combined with a probabilistic decision system, which detects variations in the amplitudes and frequencies of current and voltage signals, using DFT and DHT, respectively. Simulation results of power transmission lines in Portugal are presented in order to show the robust and high performance of the proposed FDD approach for different signal-to-noise ratios. The proposed FDD approach, implemented in Python, that can be executed online or offline, can be used to evaluate the stress to which circuit breakers (CBs) are subjected, providing information to supervision- and condition-based monitoring systems in order to improve predictive and preventive maintenance strategies, and it can be applied to high-/medium-voltage power transmission lines as well as to low-voltage electronic transmission systems. Full article

Nodular or keloidal scleroderma is a rare condition with unclear cause and sporadic mentions in the medical literature. It was first recognized in the 19th century, yet its classification is still debated due to the limited number of reported cases. This rare variant of scleroderma is associated with either progressive systemic sclerosis or localized morphea. Clinically, it presents with asymptomatic nodules or plaques, resembling spontaneous keloid formation, often found on the trunk and proximal extremities. Recent literature reviews show a predominance of women with a mean age of 44 years. Diagnosis relies on clinical and histopathological findings, which usually show overlapping features of both scleroderma and true keloids, secondarily to an excessive fibrosing reaction attributed to collagen formation. We present an unusual case of a 70-year-old female patient who displayed the coexistence of two distinct subtypes of morphea (nodular/keloidal and linear), and exclusive skin involvement, which contrasts with the typical presentation of nodular/keloidal scleroderma, often associated with organ-specific disease. However, recent publications have diverged from previous ones regarding systemic sclerosis, with no systemic involvement reported between 2018 and 2024, which we evaluated in our descriptive literature review. With less than 50 cases reported in total, our case underlines the importance of recognizing this rare disease, ensuring appropriate evaluation, treatment, and follow-up. Full article

The protozoan parasite, Toxoplasma gondii, has been linked to several psychiatric disorders, including schizophrenia. The aim of this study was to assess the prevalence of T. gondii IgG antibodies and risk factors associated with seroprevalence in patients diagnosed with schizophrenia. This seroepidemiological study assessed 196 participants, divided into two groups. The study group consisted of 98 schizophrenic patients and was matched with 98 healthy blood donors. A questionnaire was used to gather information regarding potential risk factors associated with T. gondii seroprevalence. Results revealed a higher seroprevalence of T. gondii IgG antibodies in schizophrenic patients (69.39%, 68/98) when compared to healthy controls (51.02%, 50/98) (OR: 2.18; 95% CI: 1.21–3.9; p = 0.01). Patients with schizophrenia who consumed raw or undercooked meat (80.65%, 25/31) (OR: 3.75; 95% CI: 1.25–11.21, p = 0.02) and those with a lower educational level (77.59%, 45/58) (OR: 3.5; 95% CI: 1.59–7.54, p = 0.002) presented increased T. gondii seropositivity rates versus their control counterparts. Our findings indicate a high T. gondii IgG seroprevalence in patients diagnosed with schizophrenia compared to healthy blood donors. Factors associated with T. gondii seroprevalence were consumption of raw or uncooked meat and a lower educational attainment. This study provided the first data regarding the potential risk factors for toxoplasmosis in Romanian patients diagnosed with schizophrenia and may serve as a foundation for future research and the development of preventive strategies. Full article

One of today’s main concerns is to bring artificial intelligence capabilities to embedded systems for edge applications. The hardware resources and power consumption required by state-of-the-art models are incompatible with the constrained environments observed in edge systems, such as IoT nodes and wearable devices. Spiking Neural Networks (SNNs) can represent a solution in this sense: inspired by neuroscience, they reach unparalleled power and resource efficiency when run on dedicated hardware accelerators. However, when designing such accelerators, the amount of choices that can be taken is huge. This paper presents SpikExplorer, a modular and flexible Python tool for hardware-oriented Automatic Design Space Exploration to automate the configuration of FPGA accelerators for SNNs. SpikExplorer enables hardware-centric multiobjective optimization, supporting target factors such as accuracy, area, latency, power, and various combinations during the exploration process. The tool searches the optimal network architecture, neuron model, and internal and training parameters leveraging Bayesian optimization, trying to reach the desired constraints imposed by the user. It allows for a straightforward network configuration, providing the full set of explored points for the user to pick the trade-off that best fits their needs. The potential of SpikExplorer is showcased using three benchmark datasets. It reaches 95.8% accuracy on the MNIST dataset, with a power consumption of 180 mW/image and a latency of 0.12 ms/image, making it a powerful tool for automatically optimizing SNNs. Full article

Soft robots claim the architecture of actuators, sensors, and computation demands with their soft bodies by obtaining fast responses and adapting to the environment. Sensory-motor coordination is one of the main design principles utilized for soft robots because it allows the capability to sense and actuate mutually in the environment, thereby achieving rapid response performance. This work intends to study the response for a system that presents coupled actuation and sensing functions simultaneously and is integrated in an arbitrary elastic structure with ionic conduction elements, called as soft sensory-motor system based on ionic solution (SSMS-IS). This study provides a comparative analysis of the performance of SSMS-IS prototypes with three diverse designs: toroidal, semi-toroidal, and rectangular geometries, based on a series of performance experiments, such as sensitivity, drift, and durability. The design with the best performance was the rectangular SSMS-IS using silicon rubber RPRO20 for both internal and external pressures applied in the system. Moreover, this work explores the performance of a bioinspired soft robot using rectangular SSMS-IS elements integrated in its body. Further, it investigated the feasibility of the robot to adapt its morphology online for environment variability, responding to external stimuli from the environment with different levels of stiffness and damping. Full article

The frictional properties of lithium compound grease (LCG) with different percentage compositions of few-layer graphene (FLG) were investigated, and the mechanisms of temperature and loading effects on LCG containing FLG are also considered. The concluding effect shows that 1 wt% FLG is more appropriate for friction and wear modifiers for lithium compound grease at elevated temperatures and less suitable at ordinary temperatures. Thickener chemisorption film, FLG layering film, and tribo-reaction film consisting of FeO(OH), Fe₂O₃, Fe₃O₄, Li₂O, and other oxides assist in the establishment of a lubricating boundary film on the friction interfaces lubricated with LCG containing FLG. The poor fluidity of lithium compound grease at low temperatures leads to poor dispersion of FLG, decreasing friction reduction capability. Under elevated temperature and low load condition, adding 1wt% FLG to LCG can only improve its wear-resistant property, the abrasion volume of steel plate reduced by 24.49%. Under elevated temperature and high load condition, adding 1wt% FLG to LCG can only enhance its anti-friction characteristics.. Conversely, FLG is unsuitable as an anti-friction and wear-resistant additive for LCG at low-temperature conditions. Full article

Motivated by the growing threat of distributed denial-of-service (DDoS) attacks and the emergence of quantum computing, this study introduces a novel “quanvolutional autoencoder” architecture for learning representations. The architecture leverages the computational advantages of quantum mechanics to improve upon traditional machine learning techniques. Specifically, the quanvolutional autoencoder employs randomized quantum circuits to analyze time-series data from DDoS attacks, offering a robust alternative to classical convolutional neural networks. Experimental results suggest that the quanvolutional autoencoder performs similarly to classical models in visualizing and learning from DDoS hive plots and leads to faster convergence and learning stability. These findings suggest that quantum machine learning holds significant promise for advancing data analysis and visualization in cybersecurity. The study highlights the need for further research in this fast-growing field, particularly for unsupervised anomaly detection. Full article

In this paper, a frequency discrimination method using a multiplicative-integral and linear transformation network is proposed. In this method, two preset differential frequency signals and frequency modulation signals are transformed by multiplication and integration, and then the instantaneous frequency parameters of the frequency modulation signal are accurately analyzed by the linear transformation network to restore the original modulation signal. Compared with the phase discriminator, the simulation results show that this method has a higher frequency discrimination bandwidth. In addition, this method has better anti-noise performance, and the frequency discrimination distortion caused by noise with a different Signal-to-Noise Ratio is reduced by 33.80% on average compared with the phase discriminator. What is more, the carrier center frequency error has little influence on the frequency discrimination quality of this method, which solves the problem that most common frequency discriminators are seriously affected by the carrier center frequency error. This method requires a low accuracy of carrier center frequency, which makes it extremely suitable for digital frequency discrimination technology and can meet the needs of various frequency discrimination occasions. Full article

Clinical and basic science applications using adipose-derived stem cells (ADSCs) are gaining popularity. The current adipose tissue harvesting procedures introduce nonphysiological conditions, which may affect the overall performance of the isolated ADSCs. In this study, we elucidate the differences between ADSCs isolated from adipose tissues harvested within the first 5 min of the initial surgical incision (well-vascularized, nonpremedicated condition) versus those isolated from adipose tissues subjected to medications and deprived of blood supply during elective free flap procedures (ischemic condition). ADSCs isolated from well-vascularized and ischemic tissues positively immunostained for several standard stem cell markers. Interestingly, the percent change in the CD36 expression for ADSCs isolated from ischemic versus well-vascularized tissue was significantly lower in males than females (p < 0.05). Upon differentiation and maturation to adipocytes, spheroids formed using ADSCs isolated from ischemic adipose tissue had lower triglyceride content compared to those formed using ADSCs isolated from the well-vascularized tissue (p < 0.05). These results indicate that ADSCs isolated from ischemic tissue either fail to uptake fatty acids or fail to efficiently convert those fatty acids into triglycerides. Therefore, more robust ADSCs suitable to establish in vitro adipose tissue models can be obtained by harvesting well-vascularized and nonpremedicated adipose tissues. Full article

This article explores the intertwining connections among artificial intelligence, machine learning, digital transformation, and computational sustainability, detailing how these elements jointly empower citizens within a smart city framework. As technological advancement accelerates, smart cities harness these innovations to improve residents’ quality of life. Artificial intelligence and machine learning act as data analysis powerhouses, making urban living more personalized, efficient, and automated, and are pivotal in managing complex urban infrastructures, anticipating societal requirements, and averting potential crises. Digital transformation transforms city operations by weaving digital technology into every facet of urban life, enhancing value delivery to citizens. Computational sustainability, a fundamental goal for smart cities, harnesses artificial intelligence, machine learning, and digital resources to forge more environmentally responsible cities, minimize ecological impact, and nurture sustainable development. The synergy of these technologies empowers residents to make well-informed choices, actively engage in their communities, and adopt sustainable lifestyles. This discussion illuminates the mechanisms and implications of these interconnections for future urban existence, ultimately focusing on empowering citizens in smart cities. Full article

Electrochemical measurements are vital to a wide range of applications such as air quality monitoring, biological testing, food industry, and more. Integrated circuits have been used to implement miniaturized and low-power electrochemical potentiostats that are suitable for wearable devices. However, employing modern integrated circuit technologies with low supply voltage precludes the utilization of electrochemical reactions that require a higher potential window. In this paper, we present a novel circuit architecture that utilizes dynamic voltage at the working electrode of an electrochemical cell to effectively enhance the supported voltage range compared to traditional designs, increasing the cell voltage range by 46% and 88% for positive and negative cell voltages, respectively. In return, this facilitates a wider range of bias voltages in an electrochemical cell, and, therefore, opens integrated microsystems to a broader class of electrochemical reactions. The circuit was implemented in 180 nm technology and consumes 2.047 mW of power. It supports a bias potential range of 1.1 V to −2.12 V and cell potential range of 2.41 V to −3.11 V that is nearly double the range in conventional designs. Full article

Privacy-preserving neural networks offer a promising solution to train and predict without user privacy leakage, and fully homomorphic encryption (FHE) stands out as one of the key technologies, as it enables homomorphic operations over encrypted data. However, only addition and multiplication homomorphisms are supported by FHE, and thus, it faces huge challenges when implementing non-linear functions with ciphertext inputs. Among the non-linear functions in neural networks, one may refer to the activation function, the argmax function, and maximum pooling. Inspired by using a composition of low-degree minimax polynomials to approximate sign and argmax functions, this study focused on optimizing the homomorphic argmax approximation, where argmax is a mathematical operation that identifies the index of the maximum value within a given set of values. For the method that uses compositions of low-degree minimax polynomials to approximate argmax, in order to further reduce approximation errors and improve computational efficiency, we propose an improved homomorphic argmax approximation algorithm that includes rotation accumulation, tree-structured comparison, normalization, and finalization phases. And then, the proposed homomorphic argmax algorithm was integrated into a neural network structure. Comparative experiments indicate that the network with our proposed argmax algorithm achieved a slight increase in accuracy while significantly reducing the inference latency by $58\%$, as the homomorphic sign and rotation operations were rapidly reduced. Full article

While public service motivation (PSM) and teamwork are widely recognized as crucial drivers for effective public service delivery, researchers primarily analyze these factors independently and at a personal level. The existing literature rarely explores the interplay between PSM, the project team learning process (PTLP), and psychological safety (PS) within research and development (R&D) project teams, particularly in national R&D organizations. This study addresses this gap by proposing a theoretical model that examines the combined effect of individual motivation and team collaboration, mediated by PS, on R&D PTLP. Additionally, it investigates the moderating influence of project management (PM) styles—fully agile and partially agile—on these relationships. The proposed method utilizes partial least squares structural equation modeling (PLS-SEM) for quantitative data analysis. Our findings revealed a positive relationship between PSM, PS, and R&D PTLP, with PS acting as a significant mediator. Notably, the relationship between PSM and R&D PTLP was stronger under fully agile project management compared to partially agile settings. These findings suggest that both project teams and organizations should prioritize promoting PS and consider the moderating effects of project management styles to foster a sustainable R&D team learning process, particularly within national R&D institutions. Full article

Serbia has recently begun facing a serious problem with the Brown Marmorated Stink Bug, Halyomorpha halys (Stål), which was first recorded in October 2015. This species belongs to the Pentomidae family and is notorious for causing extensive damage to plants. During the winter, it tends to gather in urban areas, such as houses and different man-made facilities, which has raised concerns among producers and citizens. The population of this species has rapidly increased, causing significant economic damage to cultivated plants. However, despite the alarming situation no natural enemies have yet been identified in Serbia. Therefore, research in 2022 was focused on collecting stink bug eggs to investigate the presence of egg parasitoids. The study identified two foreign Hymenoptera species for the European region, Trissolcus japonicus (Ashmead) and Tr. mitsukurii (Ashmead) (Scelionidae), recorded for the first time in Serbia. Additionally, the list of egg parasitoid species belonging to the Hymenoptera order includes seven local species: Anastatus bifasciatus (Geoffroy), from the Eupelmidae family; Ooencyrtus sp., from the Encyrtidae family; and Telenomus turesis (Walker), Tr. basalis (Wollaston), Tr. belenus (Walker), Tr. colemani (Crawford), and Tr. semistriatus (Nees von Esenbeck), from the Scelionidae family. In total, nine egg parasitoid species were, for the first time, reported as parasitizing H. halys and related species in Serbia. Full article

Japanese Brown (JBR) cattle have moderately marbled beef compared to the highly marbled beef of Japanese Black (JBL) cattle; however, their skeletal muscle properties remain poorly characterized. To unveil interbreed metabolic differences over the previous results, we explored the metabolome network changes before and after postmortem 7-day aging in the trapezius muscle of the two cattle breeds by employing a deep and high-coverage metabolomics approach. Using both capillary electrophoresis (CE) and ultra-high-performance liquid chromatography (UHPLC)–Fourier transform mass spectrometry (FT/MS), we detected 522 and 384 annotated peaks, respectively, across all muscle samples. The CE-based results showed that the cattle were clearly separated by breed and postmortem age in multivariate analyses. The metabolism related to glutathione, glycolysis, vitamin K, taurine, and arachidonic acid was enriched with differentially abundant metabolites in aged muscles, in addition to amino acid (AA) metabolisms. The LC-based results showed that the levels of bile-acid-related metabolites, such as tauroursodeoxycholic acid (TUDCA), were high in fresh JBR muscle and that acylcarnitines were enriched in aged JBR muscle, compared to JBL muscle. Postmortem aging resulted in an increase in fatty acids and a decrease in acylcarnitine in the muscles of both cattle breeds. In addition, metabolite set enrichment analysis revealed that JBR muscle was distinctive in metabolisms related to pyruvate, glycerolipid, cardiolipin, and mitochondrial energy production, whereas the metabolisms related to phosphatidylethanolamine, nucleotide triphosphate, and AAs were characteristic of JBL. This suggests that the interbreed differences in postmortem trapezius muscle are associated with carnitine/acylcarnitine transport, β-oxidation, tricarboxylic acid cycle, and mitochondrial membrane stability, in addition to energy substrate and AA metabolisms. These interbreed differences may characterize beef quality traits such as the flavor intensity and oxidative stability. Full article

The aim of this study was to evaluate the findings of CT scans in patients with pathologically confirmed primary colorectal squamous-cell carcinoma (SCC). The clinical presentation and CT findings in eight patients with pathologically confirmed primary colorectal squamous-cell carcinoma were retrospectively reviewed by two gastrointestinal radiologists. Hematochezia was the most common symptom (n = 5). The tumors were located in the rectum (n = 7) and sigmoid colon (n = 1). The tumors showed circumferential wall thickening (n = 4), bulky mass (n = 3), or eccentric wall thickening (n = 1). The mean maximal wall thickness of the involved segment was 29.1 mm ± 13.4 mm. The degree of tumoral enhancement observed via CT was well enhanced (n = 4) or moderately enhanced (n = 4). Necrosis within the tumor was found in five patients. The mean total number of metastatic lymph nodes was 3.1 ± 3.3, and the mean short diameter of the largest metastatic lymph node was 16.6 ± 5.7 mm. Necrosis within the metastatic node was observed in six patients. Invasions to adjacent organs were identified in five patients (62.5%). Distant metastasis was detected in only one patient. In summary, primary SCCs that arise from the colorectum commonly present as marked invasive wall thickening or a bulky mass with heterogeneous well-defined enhancement, internal necrosis, and large metastatic lymphadenopathies. Full article

In this article, I consider how the epistemic problem of religious disagreement has been viewed within the Islamic tradition. Specifically, I consider two religious epistemological trends within the tradition: Islamic Rationalism and Islamic Traditionalism. In examining the approaches of both trends toward addressing the epistemic problem, I suggest that neither is wholly adequate. Nonetheless, I argue that both approaches offer insights that might be relevant to building a more adequate response. So, I attempt to combine insights from both by drawing a distinction between inferential and noninferential reflective responsibility. Given this distinction, I argue that it may be possible for a theist to remain steadfast in upholding their tradition-specific theistic belief, without having to hold that belief by way of inference; but nevertheless, having to be sufficiently reflectively responsible in forming their theistic belief noninferentially. Full article

The intelligent reflective surface (IRS) is a novel network node that consists of a large-scale passive reflective array to obtain a customized reflected wave direction by modulating the amplitude phase, which can be easily deployed to change the wireless signal propagation environment and enhance the communication performance under a non-line-of-sight (NLOS) environment, where location services cannot perform accurately. In this study, a low-rank matrix reconstruction-enabled fingerprint-based localization algorithm for IRS-assisted networks is proposed. Firstly, a 5G positioning system based on IRSs is constructed using multiple IRSs deployed to reflect signals. This enables the base station to overcome the influence of NLOS and receive the positioning signal of the point to be positioned. Then, the angular domain power expectation matrix of the received signal is extracted as a fingerprint to form a partial fingerprint database. Next, the complete fingerprint database is reconstructed using the low-rank matrix fitting algorithm, thereby considerably reducing the workload of building the fingerprint database. Finally, maximal ratio combining is used to increase the gap between the fingerprint data, and the Weighted K-Nearest Neighbor (WKNN) algorithm is used to match the fingerprint data and estimate the location of the points to be located. The simulation results demonstrate the feasibility of the proposed method to achieve sub-meter accuracy in an NLOS environment. Full article

The flatness of semiconductor substrates is an important parameter for evaluating the surface quality of semiconductor substrates. However, existing technology cannot simultaneously achieve high measurement efficiency, large-range thickness measurement, and nanometer-level measurement accuracy in the thickness measurement of semiconductor substrates. To solve the problems, we propose to apply the method that combines spectral-domain optical coherence tomography (SD-OCT) with the Hanning-windowed energy centrobaric method (HnWECM) to measure the thickness of semiconductor substrates. The method can be employed in the full-chip thickness measurement of a sapphire substrate, which has a millimeter measuring range, nanometer-level precision, and a sampling rate that can reach up to 80 kHz. In this contribution, we measured the full-chip thickness map of a sapphire substrate by using this method and analyzed the machining characteristics. The measurement results of a high-precision mechanical thickness gauge, which is widely used for thickness measurement in the wafer fabrication process, were compared with the proposed method. The difference between these two methods is 0.373%, which explains the accuracy of the applied method to some extent. The results of 10 sets of repeatability experiments on 250 measurement points show that the maximum relative standard deviation (RSD) at this point is 0.0061%, and the maximum fluctuation is 71.0 nm. The above experimental results prove that this method can achieve the high-precision thickness measurement of the sapphire substrate and is of great significance for improving the surface quality detection level of semiconductor substrates. Full article