This paper sets forth a thorough procedure to design surface-mounted permanent magnet synchronous generators. Since synchronous generators generate the majority of electrical energy, their relevance in society nowadays is substantial. As a consequence, the methodology to design these electrical machines also holds great importance. However, even though a considerable amount of works addresses the matter, it is difficult to find a complete and thoroughly explained design procedure. The proposed method is based on analytical equations to fully consider PM generator fundamentals with a few simplifications, which implies in a considerable number of design equations and parameters. Differently from most papers on the design of PM synchronous generators, a significant level of detail and explanation is presented, all design choices are discussed, and the suggested ranges for the design parameters are shown. This results in a straightforward procedure that allows non-experienced designers to easily replicate the results and effectively enhance the comprehension of permanent magnet synchronous machines, and provides a guideline for researchers from other fields who may need to understand and perform a synchronous generator design. To show the effectiveness of the proposed design procedure, a PM generator is designed, and the results are compared with a finite element simulation, showing good accuracy. Full article

In this study, we aimed to characterize a cohort of children hospitalized due to varicella before and after the outbreak of the COVID-19 pandemic. Medical charts of all children hospitalized in the Regional Hospital of Infectious Diseases in Warsaw due to varicella in the years 2019 and 2022 were retrospectively analyzed and compared. In total, 221 children were included in the analysis; 59 of them were hospitalized in 2019, whereas 162 were hospitalized in 2022. Children hospitalized in 2022 were older than those reported in 2019 (median 4.0 vs. 3.0 years, p = 0.02). None of the hospitalized children received complete varicella vaccination. The most common complication in both years was bacterial superinfection of skin lesions, found in 156/221 (70.6%) of patients. This complication rate was higher in 2022 (50.8% in 2019 vs. 77.8% in 2022, p = 0.0001), OR = 3.38, 95% CI: 1.80–6.35. Moreover, skin infections in 2022 more often manifested with cellulitis (in 2022 13.6% vs. 3.4% in 2019, p = 0.03), OR = 4.40, 95% CI: 1.00–19.33. Sepsis as a complication of varicella was almost five-fold more prevalent in 2022 than in 2019 (p = 0.009), OR = 5.70, 95% CI: 1.31–24.77. Antibiotic use increased between 2019 and 2022 (71.2% vs. 85.2%, p = 0.01). Furthermore, patients were treated more frequently with the combination of two different antibiotics simultaneously (only 3.4% of patients in 2019 compared to 15.4% in 2022, p = 0.01). Primary infections with varicella zoster virus in 2022 led to a more severe course of the disease. Full article

This paper presents a study to accurately evaluate defects in concrete decks using ultrasonic pulse-echo signals. A reinforced concrete deck with void defects was designed and evaluated for validation, and a commercial ultrasonic pulse-echo (UPE) device was used to obtain the 2D images of the void defect inside the deck. The UPE image is based on the ultrasonic shear-wave test method and an extended synthetic aperture focusing technique (SAFT). To enhance the accuracy of the defect location in the SAFT imaging, the recorded A-scan data from UPE was analyzed using an advanced denoising approach and defect echo peak extraction, which are based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. The results demonstrated that the location and depth of the void defect in the deck can be accurately assessed by using the developed approach. The new method provides quantitative information of the anomalies inside the deck, which can be used to calibrate the qualitative images of UPC devices with the SAFT. Full article

Solventogenic Clostridium species are important for establishing the sustainable industrial bioproduction of fuels and important chemicals such as acetone and butanol. The inherent versatility of these species in substrate utilization and the range of solvents produced during acetone butanol–ethanol (ABE) fermentation make solventogenic Clostridium an attractive choice for biotechnological applications such as the production of fuels and chemicals. The functional qualities of these microbes have thus been identified to be related to complex regulatory networks that play essential roles in modulating the metabolism of this group of bacteria. Yet, solventogenic Clostridium species still struggle to consistently achieve butanol concentrations exceeding 20 g/L in batch fermentation, primarily due to the toxic effects of butanol on the culture. Genomes of solventogenic Clostridium species have a relatively greater prevalence of genes that are intricately controlled by various regulatory molecules than most other species. Consequently, the use of genetic or metabolic engineering strategies that do not consider the underlying regulatory mechanisms will not be effective. Several regulatory factors involved in substrate uptake/utilization, sporulation, solvent production, and stress responses (Carbon Catabolite Protein A, Spo0A, AbrB, Rex, CsrA) have been identified and characterized. In this review, the focus is on newly identified regulatory factors in solventogenic Clostridium species, the interaction of these factors with previously identified molecules, and potential implications for substrate utilization, solvent production, and resistance/tolerance to lignocellulose-derived microbial inhibitory compounds. Taken together, this review is anticipated to highlight the challenges impeding the re-industrialization of ABE fermentation, and inspire researchers to generate innovative strategies for overcoming these obstacles. Full article

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system. Full article

This paper explores the development of pottery technology in the Trieste Karst region (North-East Italy) from the Neolithic to the Early Bronze Age (EBA). It also seeks to identify cultural links with other areas by examining potentially imported vessels. Archaeometric analyses (X-ray diffraction and optical microscopy) reveal significant differences between Neolithic ceramics (Danilo–Vlaška Group) and the majority of Late Copper Age (LCA)/Early Bronze Age (EBA) pottery (primarily associated with the Ljubljana Culture and a few with the Cetina Culture). Neolithic pottery displays consistent characteristics across all vessel types, including coarse grain, prevalent sparry calcite temper, and the absence of grog. In contrast, most LCA and EBA vessels exhibit distinct features such as very fine-grained paste, no sparry calcite, notable use of grog temper, higher quartz, muscovite, and flint content. Notably, from a technological perspective, the analyzed Cetina vessels bear a strong resemblance to the majority of LCA ceramics. The differences between Neolithic and LCA/EBA vessels clearly suggest the use of new raw materials, recipes, and techniques, likely reflecting changes in cultural and social contexts and potential connections with the core area of the Ljubljana Culture. Full article

Insulators are key components to ensure the normal operation of power facilities in transmission corridors. Existing insulator identification methods mainly use image data and lack the acquisition of three-dimensional information. This paper proposes an efficient insulator extraction method based on UAV (unmanned aerial vehicle) LiDAR (light detection and ranging) point cloud, using five histogram features: horizontal density (HD), horizontal void (HV), horizontal width (HW), vertical width (VW) and vertical void (VV). Firstly, a voxel-based method is employed to roughly extract power lines and pylons from the original point cloud. Secondly, the VV histogram is used to categorize the pylons into suspension and tension types, and the HD histogram is used to locate the tower crossarm and further refine the roughly extracted powerlines. Then, for the suspension tower, insulators are segmented based on the HV histogram and HD difference histogram. For the tension tower, the HW histogram is used to recognize the jumper conductor (JC) and transmission conductor (TC) from the power line. The HW histogram and VW histogram are used to extract the tension insulator in the TC and suspension insulator in the JC, respectively. Finally, considering the problem of setting a suitable grid width when constructing the feature histogram, an adaptive method of multi-scale histograms is proposed to refine the extraction result. Two 220 kV long transmission lines are used for the validation, and the overall object-based accuracy for suspension and tension towers are 100% and 97.3%, respectively. Compared with the point feature-based method, the mean F1 score of the proposed method improved by 0.3, and the runtime for each tower is within 2 s. Full article

Neutrinoless double beta decay nuclear matrix element ($M_{0\nu }$) for ¹³⁶Xe was recently analyzed using a statistical approach (Phys. Rev. C 107, 045501 (2023)). In the analysis, three initial shell model effective Hamiltonians were randomly altered, and their results for 23 measured observables were used to infer credibility for the $M_{0\nu }$ nuclear matrix element (NME) based on a Bayesian Model Averaging approach. In that analysis, a reasonable Gamow-Teller quenching factor of 0.7 was assumed for each starting effective Hamiltonian. Given that the result of the statistical analysis was sensible to this choice, we are here improving that analysis by assuming that the Gamow-Teller quenching factor is also randomly chosen within reasonabe limits for all three starting Hamiltonians. The outcomes are slightly higher expectation values and uncertainties for the $M_{0\nu }$ NME. Full article

Machine learning (ML) has become integral in educational decision-making through technologies such as learning analytics and educational data mining. However, the adoption of machine learning-driven tools without scrutiny risks perpetuating biases. Despite ongoing efforts to tackle fairness issues, their application to educational datasets remains limited. To address the mentioned gap in the literature, this research evaluates the effectiveness of four bias mitigation techniques in an educational dataset aiming at predicting students’ dropout rate. The overarching research question is: “How effective are the techniques of reweighting, resampling, and Reject Option-based Classification (ROC) pivoting in mitigating the predictive bias associated with high school dropout rates in the HSLS:09 dataset?" The effectiveness of these techniques was assessed based on performance metrics including false positive rate (FPR), accuracy, and F1 score. The study focused on the biological sex of students as the protected attribute. The reweighting technique was found to be ineffective, showing results identical to the baseline condition. Both uniform and preferential resampling techniques significantly reduced predictive bias, especially in the FPR metric but at the cost of reduced accuracy and F1 scores. The ROC pivot technique marginally reduced predictive bias while maintaining the original performance of the classifier, emerging as the optimal method for the HSLS:09 dataset. This research extends the understanding of bias mitigation in educational contexts, demonstrating practical applications of various techniques and providing insights for educators and policymakers. By focusing on an educational dataset, it contributes novel insights beyond the commonly studied datasets, highlighting the importance of context-specific approaches in bias mitigation. Full article

In recent years, the trend toward plant-based beverages has continued to grow rapidly. This study aimed to assess the effects of sociodemographic characteristics and knowledge about plant-based beverages, subjective norms, perceived price, environmental protection, animal welfare, availability, and trust on attitudes and buying behavior toward these products. This study was conducted online using a two-part questionnaire prepared by considering the literature. This study included 935 participants, and our findings confirmed that the variable of environmental protection affects the attitude toward these products ($\mathsf{\beta }=$ 0.095; p = 0.007). Furthermore, gender, income level, lactose intolerance, and bloating due to cow’s or sheep’s milk influenced actual buying behavior (p < 0.05; p < 0.001). These findings indicate that people’s increased environmental protection awareness will positively influence attitudes towards plant-based beverages and that individuals who do not experience lactose intolerance and bloating due to cow’s or goat’s milk will have lower actual buying behavior. It was also determined that individuals with lower incomes bought more plant-based beverages. In conclusion, plant-based beverage marketers need to take into account individuals’ sociodemographic characteristics and environmental protection awareness when planning their marketing strategies. Full article

In this work, an analog front-end (AFE) circuit for an electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using an advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter—all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the $g_m/I_D$ methodology. Both the pre-layout and post-layout simulation are carried out. The layout consumes an area of 0.00628 mm² without the resistors and capacitors. Analysis of various simulation results are carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz, with a variable gain between 44 and 58 dB, a notch depth of −56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of −59.65 dB (less than 1%), an input-referred noise spectral density of <34 $\mathsf{\mu }$Vrms/$\sqrt{\mathrm{Hz}}$ at the pass-band, a dynamic range of 52.71 dB, and a total power consumption of 10.88 μW with a supply of ±0.6 V. Hence, the AFE exhibits the promise of high-quality signal acquisition capability required for portable ECG detection systems in modern healthcare. Full article

A variety of process capability indices are applied to the quantitative measurement of the potential and performance of processes in manufacturing. As it is easy to understand the formulae of these indices, this method is easy to apply. Furthermore, a process capability index is frequently utilized by a manufacturer to gauge the quality of a process. This index can be utilized by not only an internal process engineer to assess the quality of the process but also as a communication tool for an external sales department. When the manufacturing process deviates from the target value T, the process capability index C_PMK can be quickly detected, which is conducive to the promotion of smart manufacturing. Therefore, this study applied the index C_PMK as an evaluation tool for process quality. As noted by some studies, process capability indices have unknown parameters and therefore must be estimated from sample data. Additionally, numerous studies have addressed that it is essential for companies to establish a rapid response mechanism, as they wish to make decisions quickly when using a small sample size. Considering the small sample size, this study proposed a 100 (1 − α)% confidence interval for the process capability index C_PMK based on suggestions from previous studies. Subsequently, this study built a fuzzy testing model on the 100 (1 − α)% confidence interval for the process capability index C_PMK. This fuzzy testing model can help enterprises make decisions rapidly with a small sample size, meeting their expectation of having a rapid response mechanism. Full article

The inhibitory activity of peptides on angiotensin-converting enzyme (ACE) is a measure of their antihypertensive potential. Quantitative structure–activity relationship (QSAR) models obtained based on the analysis of sequences of amino acids are suggested. The average determination coefficient for the active training sets is 0.36 ± 0.07. The average determination coefficient for validation sets is 0.79 ± 0.02. The paradoxical situation is caused by applying the vector of ideality of correlation, which improves the statistical quality of a model for the calibration and validation sets but is detrimental to the statistical quality of models for the training sets. Full article

Screening is critical for prevention and early detection of cervical cancer but it is time-consuming and laborious. Supervised deep convolutional neural networks have been developed to automate pap smear screening and the results are promising. However, the interest in using only normal samples to train deep neural networks has increased owing to the class imbalance problems and high-labeling costs that are both prevalent in healthcare. In this study, we introduce a method to learn explainable deep cervical cell representations for pap smear cytology images based on one-class classification using variational autoencoders. Findings demonstrate that a score can be calculated for cell abnormality without training models with abnormal samples, and we localize abnormality to interpret our results with a novel metric based on absolute difference in cross-entropy in agglomerative clustering. The best model that discriminates squamous cell carcinoma (SCC) from normals gives $0.908\pm 0.003$ area under operating characteristic curve (AUC) and one that discriminates high-grade epithelial lesion (HSIL) $0.920\pm 0.002$ AUC. Compared to other clustering methods, our method enhances the V-measure and yields higher homogeneity scores, which more effectively isolate different abnormality regions, aiding in the interpretation of our results. Evaluation using an external dataset shows that our model can discriminate abnormality without the need for additional training of deep models. Full article

The Advanced Encryption Standard (AES) is widely recognized as a robust cryptographic algorithm utilized to protect data integrity and confidentiality. When it comes to lightweight implementations of the algorithm, the literature mainly emphasizes area and power optimization, often overlooking considerations related to performance and security. This paper evaluates two of our previously proposed lightweight AES implementations using both profiled and non-profiled attacks. One is an unprotected implementation, and the other one is a protected version using Domain-Oriented Masking (DOM). The findings of this study indicate that the inclusion of DOM in the design enhances its resistance to attacks at the cost of doubling the area. Full article

Objective: Following a mild traumatic brain injury (mTBI), the most prevalent and profoundly debilitating occurrence is the emergence of an acute and persistent post-traumatic headache (PTH), for which there are presently no approved treatments. A crucial gap in knowledge exists regarding the consequences of an mTBI, which could serve as a foundation for the development of therapeutic approaches. The activation of trigeminal sensory nerve terminals that innervate the calvarial periosteum (CP)—a densely innervated tissue layer covering the calvarial skull—has been implicated in both migraines and PTHs. We have previously shown that trigeminal oxytocin receptors (OTRs) may provide a therapeutic target for PTHs. This study examined the expression of oxytocin receptors on trigeminal nerves innervating the periosteum and whether these receptors might serve as a therapeutic target for PTHs using a direct application of oxytocin to the periosteum in a rodent model of PTH. Methods: We used retrograde tracing and immunohistochemistry to determine if trigeminal ganglion (TG) neurons innervating the periosteum expressed OTRs and/or CGRPs. To model the impact of local inflammation that occurs following an mTBI, we applied chemical inflammatory mediators directly to the CP and assessed for changes in immediate-early gene expression as an indication of neuronal activation. We also determined whether mTBI would lead to expression changes to OTR levels. To determine whether these OTRs could be a viable therapeutic target, we assessed the impact of oxytocin injections into the CP in a mouse model of PTH-induced periorbital allodynia. Results: The results of these experiments demonstrate the following: (1) the cell bodies of CP afferents reside in the TG and express both OTRs and CGRPs; (2) inflammatory chemical stimulation of the periosteum leads to rapid activation of TG neurons (phospho-ERK (p-ERK) expression), (3) mTBI-induced inflammation increased OTR expression compared to the sham group; and (4) administration of oxytocin into the periosteum on day 2 and day 40 blocked cutaneous allodynia for up to one hour post-administration for both acute and persistence phases in the PTH model—an effect that was preventable by the administration of an OTR antagonist. Conclusion: Taken together, our observations suggest that periosteal trigeminal afferents contribute to post-TBI craniofacial pain, and that periosteum tissue can be used as a potential local target for therapeutics such as oxytocin. Full article

Religion in Europe has been undergoing two fundamental changes in the past four decades. As a side effect of secularization, religious fields have been pluralizing. On the other hand, religions themselves have taken a qualitative shift towards lived, material characteristics. Focusing exclusively on the diversification of European religious fields, we are interested in the concept of religious literacy as a tool for competent engagement in contemporary religious plural societies. To better understand the role of public media in fostering religious literacy, we offer an analysis of the public broadcaster’s coverage of smaller religious communities in Slovenia. Focusing particularly on Muslims as the largest religious minority in Slovenia, we provide an analysis of 245 episodes, consisting of 540 items, in the 2015–2020 period. We show that the coverage given to smaller religious communities is unevenly spread amongst the communities, with disproportional airtime given to Christian churches and communities. Furthermore, we pinpoint the key qualitative difference in portrayals of Slovenian Muslims and non-Catholic Christians, explaining how the process of racialized Islamophobia may continue beyond explicit hate speech. In conclusion we set out limitations of our study and provide guidelines for future research. Full article

Environmental factors, such as drought stress, significantly impact maize growth and productivity worldwide. To improve yield and quality, effective strategies for early detection and mitigation of drought stress in maize are essential. This paper presents a detailed analysis of three imaging trials conducted to detect drought stress in maize plants using an existing, custom-developed, low-cost, high-throughput phenotyping platform. A pipeline is proposed for early detection of water stress in maize plants using a Vision Transformer classifier and analysis of distributions of near-infrared (NIR) reflectance from the plants. A classification accuracy of 85% was achieved in one of our trials, using hold-out trials for testing. Suitable regions on the plant that are more sensitive to drought stress were explored, and it was shown that the region surrounding the youngest expanding leaf (YEL) and the stem can be used as a more consistent alternative to analysis involving just the YEL. Experiments in search of an ideal window size showed that small bounding boxes surrounding the YEL and the stem area of the plant perform better in separating drought-stressed and well-watered plants than larger window sizes enclosing most of the plant. The results presented in this work show good separation between well-watered and drought-stressed categories for two out of the three imaging trials, both in terms of classification accuracy from data-driven features as well as through analysis of histograms of NIR reflectance. Full article

The primary research question driving this paper is the following: “What are the schooling experiences of young people who are at risk of or experiencing homelessness?” Through interviews with 28 young people in two cities in Ontario, Canada, the authors identified several common experiences, including the following: lack of available information that could help them cope with their housing difficulties; prejudice and bullying from other students, sometimes stemming from their housing problems but also due to factors such as racialization, gender identity, poverty, and substance use; and individual support from some teachers and support staff, although this was dependent on being in school. They proposed changes to help young people still in school, including the inclusion of non-judgmental information and guidance on dealing with poverty and homelessness in school curricula, educating school staff about the ‘symptoms’ of homelessness to help them identify students at risk, and creating more safe and supportive school environments overall. Full article

Steel structures are susceptible to corrosion due to their exposure to the environment. Currently used non-destructive techniques require inspector involvement. Inaccessibility of the defective part may lead to unnoticed corrosion, allowing the corrosion to propagate and cause catastrophic structural failure over time. Autonomous corrosion detection is essential for mitigating these problems. This study investigated the effect of the type of encoder–decoder neural network and the training strategy that works the best to automate the segmentation of corroded pixels in visual images. Models using pre-trained DesnseNet121 and EfficientNetB7 backbones yielded 96.78% and 98.5% average pixel-level accuracy, respectively. Deeper EffiecientNetB7 performed the worst, with only 33% true-positive values, which was 58% less than ResNet34 and the original UNet. ResNet 34 successfully classified the corroded pixels, with 2.98% false positives, whereas the original UNet predicted 8.24% of the non-corroded pixels as corroded when tested on a specific set of images exclusive to the investigated training dataset. Deep networks were found to be better for transfer learning than full training, and a smaller dataset could be one of the reasons for performance degradation. Both fully trained conventional UNet and ResNet34 models were tested on some external images of different steel structures with different colors and types of corrosion, with the ResNet 34 backbone outperforming conventional UNet. Full article

Although studies have found that job satisfaction has an impact on workers’ physical and mental health, research has generally not focused on the psychological well-being of adult workers and a gender differential analysis has not been conducted. The aim of the current research is to determine the importance of job satisfaction for mental symptoms and well-being among adult working women and men. We also examine gender differences in job satisfaction. A non-probability sample of 1977 Spanish workers (51.6% men and 48.4% women) aged between 36 and 65 years was used in this cross-sectional study. Six questionnaires and self-report scales were used to assess the participants. For both men and women, higher job satisfaction was associated with lower depressive, somatic, anxiety, and social dysfunction symptoms; higher life satisfaction; and greater psychological well-being. Hierarchical multiple regression analyses showed that after controlling for the effects of self-esteem and social support, higher job satisfaction predicted greater life satisfaction, fewer mental symptoms, and greater psychological well-being, although the effect of job satisfaction on psychological well-being was somewhat stronger for men than for women. We conclude that job satisfaction is important for the mental health, psychological well-being, and life satisfaction of adult working women and men. Full article

Young carers face a variety of challenges at school. While schools can be vital places of support, the assistance they receive at school often seems selective and fails to consider the unique life situations of individual students. This paper examines the perspective of multiple actors in the student’s school environment and explores how schools can develop comprehensive, sustainable support systems for young carers—systems that consider and involve as many actors as possible in the student’s school environment. In a secondary analysis of two interview studies, we analyzed how young carers as well as their parents, teachers, and school counsellors perceived the school support the carers received. We then developed an integrated model that incorporates these differing perspectives. The model offers an approach for implementing low-threshold support for young carers within existing school structures in relation to their family situation and outlines conditions that can support both recognized and “invisible” young carers, as well as other students. Full article