Miracle-dz/UniFAR-FTUs huggingface dataset:
Discrete modeling and calculation of traction return-current network for 400 km/h high-speed railway

The planned 400 km/h high-speed train capable of cross-border intermodal transportation will inevitably cause a greater return-current and bring more challenges to signaling infrastructure and integrated grounding while achieving stronger traction. Based on the existing AC autotransformer power supply mode, this paper proposes a discrete modeling and calculation method of the traction return-current network concerning impedance equivalent, realizing the simulation and quantitative analysis of the return-current distribution of multiple current-carrying conductors in the block section and station yard under the double-track condition. Then, the dynamic distribution is analyzed comprehensively considering traction power supply, signaling, and integrated grounding systems. Also, the method is verified with field test data. Finally, the simulation of the return-current proportion of multiple conductors is carried out under the dynamic operating conditions of high speed, and the distribution characteristics are compared and analyzed under different ballast resistances. In the most unfavorable case, the maximum return-current in the rails, grounding wire, and protective wire can reach 1046 A, 180 A, and 126 A, respectively. This work helps evaluate the electromagnetic compatibility between signaling and strong currents in engineering practice, further optimize the capacity configuration of equipment along the railway lines, and improve the signaling immunity design.
Assessment of Various Machine Learning Models for Peach Maturity Prediction Using Non-Destructive Sensor Data

To date, many machine learning models have been used for peach maturity prediction using non-destructive data, but no performance comparison of the models on these datasets has been conducted. In this study, eight machine learning models were trained on a dataset containing data from 180 ‘Suncrest’ peaches. Before the models were trained, the dataset was subjected to dimensionality reduction using the least absolute shrinkage and selection operator (LASSO) regularization, and 8 input variables (out of 29) were chosen. At the same time, a subgroup consisting of the peach ground color measurements was singled out by dividing the set of variables into three subgroups and by using group LASSO regularization. This type of variable subgroup selection provided valuable information on the contribution of specific groups of peach traits to the maturity prediction. The area under the receiver operating characteristic curve (AUC) values of the selected models were compared, and the artificial neural network (ANN) model achieved the best performance, with an average AUC of 0.782. The second-best machine learning model was linear discriminant analysis with an AUC of 0.766, followed by logistic regression, gradient boosting machine, random forest, support vector machines, a classification and regression trees model, and k-nearest neighbors. Although the primary parameter used to determine the performance of the model was AUC, accuracy, F1 score, and kappa served as control parameters and ultimately confirmed the obtained results. By outperforming other models, ANN proved to be the most accurate model for peach maturity prediction on the given dataset.
Effect of Level and Duration of High Temperatures on Rest in the Peach

Rooted ‘Redhaven’ peach [Prunus persica (L.) Batsch] cuttings were exposed to diurnal temperature cycles. A severe reduction in lateral vegetative bud break was found in plants refrigerated at 4°C and given 8 hr daily exposure to 19° (±0.1°). Nearly complete chilling negation occurred in plants exposed to diurnal cycles including 8 hr of 20° or 21°. Also, effect decreased with increased time (0 to 8 hr per day) of exposure to 24°. Buds on plants exposed to cycles including 20° for 2 and 4 hr showed no chilling negation, but gradual increases in chilling negation occurred with longer exposures to 20°. ‘Harvester’ peach plants were exposed to 2, 7, or 12 days of 23° following the accumulation of one-fourth, one-half, or three-fourths of the chilling requirement. Chilling negation occurred only with the 12-day exposure to 23° when high temperatures were applied following the accumulation of one-fourth and one-half of the chilling requirement. No chilling negation was found after 12 days’ exposure to 23° if three-fourths of the chilling requirement had accumulated before exposure.
Photoluminescence of CuGaS2 epitaxial layers grown by metalorganic vapor phase epitaxy

High quality epitaxial layers of CuGaS2 have been grown on GaAs and GaP substrates by low-pressure metalorganic vapor phase epitaxy using cycropentadienylcoppertriethylphosphine, normal-tripropylgallium, and ditertiallybutyl sulphide precursors. Photoluminescence (PL) studies at 8 K have been carried out, and exciton-related PL peaks at 2.489 and 2.477 eV have been observed in addition to PL peaks at 2.43 (free-to-bound), 2.39 (donor-acceptor pair), and broad band at 1.65 eV. Temperature and excitation intensity dependences of the PL peaks have been studied in detail, and PL properties are compared with those for the bulk CuGaS2 crystals grown by the chemical vapor transport (CVT) method. PL spectra for nearly stoichiometric CuGaS2 epilayers exhibited the intense free exciton-related PL peak over the entire temperature range (8–300 K), which are in contrast to PLs dominated by defect-related deep peaks for Ga-rich or Cu-rich epilayers and the impurity related near-band edge PL for the CVT bulk crystal. These PL results show that the nearly stoichiometric CuGaS2 epilayers grown in this study are the highest quality reported so far.High quality epitaxial layers of CuGaS2 have been grown on GaAs and GaP substrates by low-pressure metalorganic vapor phase epitaxy using cycropentadienylcoppertriethylphosphine, normal-tripropylgallium, and ditertiallybutyl sulphide precursors. Photoluminescence (PL) studies at 8 K have been carried out, and exciton-related PL peaks at 2.489 and 2.477 eV have been observed in addition to PL peaks at 2.43 (free-to-bound), 2.39 (donor-acceptor pair), and broad band at 1.65 eV. Temperature and excitation intensity dependences of the PL peaks have been studied in detail, and PL properties are compared with those for the bulk CuGaS2 crystals grown by the chemical vapor transport (CVT) method. PL spectra for nearly stoichiometric CuGaS2 epilayers exhibited the intense free exciton-related PL peak over the entire temperature range (8–300 K), which are in contrast to PLs dominated by defect-related deep peaks for Ga-rich or Cu-rich epilayers and the impurity related near-band edge PL for the CVT bulk crystal. Th.
The immune microenvironment and tissue engineering strategies for spinal cord regeneration

Regeneration of neural tissue is limited following spinal cord injury (SCI). Successful regeneration of injured nerves requires the intrinsic regenerative capability of the neurons and a suitable microenvironment. However, the local microenvironment is damaged, including insufficient intraneural vascularization, prolonged immune responses, overactive immune responses, dysregulated bioenergetic metabolism and terminated bioelectrical conduction. Among them, the immune microenvironment formed by immune cells and cytokines plays a dual role in inflammation and regeneration. Few studies have focused on the role of the immune microenvironment in spinal cord regeneration. Here, we summarize those findings involving various immune cells (neutrophils, monocytes, microglia and T lymphocytes) after SCI. The pathological changes that occur in the local microenvironment and the function of immune cells are described. We also summarize and discuss the current strategies for treating SCI with tissue-engineered biomaterials from the perspective of the immune microenvironment.
Electrospun Biodegradable Poly(L-lactic acid) Nanofiber Membranes as Highly Porous Oil Sorbent Nanomaterials

Crude oil spills seriously harm the ocean environment and endanger the health of various animals and plants. In the present study, a totally biodegradable polymer, poly(L-lactic acid) (PLLA), was employed to fabricate highly porous oil absorbent nanofibrous materials by using a combination of electrospinning technique and subsequent acetone treatment. We systematically investigated how the electrospinning parameters affected formation of the porous structure of PLLA nanofibers and demonstrated that PLLA nanofibers with decreased and uniform diameter and improved porosity could be rapidly prepared by adjusting solution parameters and spinning parameters. We also demonstrated that the acetone treatment could obviously enhance the pore diameter and specific surface area of as-optimized electrospun PLLA nanofibers. The acetone treatment could also improve the hydrophobic property of as-treated PLLA nanofiber membranes. All these led to a significant increase in oil absorption performance. Through our research, it was found that the oil absorption of PLLA nanofiber membrane increased by more than double after being treated with acetone and the oil retention rate was also improved slightly.
Probing the Electrochemical Li Insertion–Extraction Mechanism in Sputtered LiNi0.5Mn1.5O4 Thin Film Cathode for Li‐Ion Microbattery

Due to its great theoretical capacity (147 mAh g−1) and high operating potential (4.7 V vs Li+/Li), Co‐free spinel LiNi0.5Mn1. 5O4 (LNMO) is one of the most promising thin film cathodes allowing designing Li‐ion micro‐batteries with a high specific energy. In this work, the Li extraction–insertion mechanism in sputtered LNMO thin films is investigated by X‐ray diffraction and Raman spectroscopy during the first electrochemical cycle. A one‐step phase transition involving two cubic phases is revealed, consisting of a wide solid solution region (0.3 ≤ x ≤ 1 in LixNMO) and a narrow biphasic domain (0 < x ≤ 0.3). Remarkably, significant variations are observed in the Raman spectra, which are linked to the activity of the Ni redox system at 4.7 V. It is demonstrated that an appropriate analysis of the bands corresponding to pure Ni–O stretching modes leads to an accurate estimation of the electrode states of charge and depth of discharge, which opens the way for a reliable quantification of the self‐discharge phenomenon. The mechanism of Li extraction insertion here pictured for the first time for LNMO thin layers is consistent with their disordered nature and accounts for their good electrochemical performance.
The Influence of High Blood Pressure on Developing Symptomatic Lumbar Epidural Hematoma after Posterior Lumbar Spinal Fusion Surgery: Clinical Data Warehouse Analysis

Background: Determining the risk factors for symptomatic lumbar epidural hematoma (SLEH) is important for preventing postoperative SLEH. However, the relationship between blood pressure and SLEH is still debatable. The purpose of our study was to determine the risk factors for postoperative SLEH, to assess the influence of high blood pressure on developing SLEH after posterior lumbar spinal fusion surgery, and to evaluate the usefulness of big data analysis utilizing a clinical data warehouse (CDW). Methods: The clinical data of patients who had undergone posterior lumbar spinal fusion surgery were acquired from the CDW of Hallym University Medical Center. The acquired clinical data were compared between patients without postoperative SLEH and with postoperative SLEH. Results: Postoperative SLEH that required hematoma evacuation surgery within 72 h after posterior lumbar spinal fusion surgery occurred in 17 (1.3%) of 1313 patients. According to the multivariate logistic regression analysis, the risk factors for postoperative SLEH are platelet count difference (OR 1.28, p = 0.03), postoperative international normalized ratio (INR) difference (OR 31.4, p = 0.028), and postoperative systolic blood pressure (SBP) difference (≥10 mmHg) (OR 1.68, p = 0.048). An increase in postoperative SBP (OR 1.68, p = 0.048) had a statistically significant influence on the occurrence of postoperative SLEH. Conclusions: Big data analysis utilizing a CDW could be useful for extending our knowledge of the risk factors for postoperative SLEH and preventing postoperative SLEH after posterior lumbar spinal fusion surgery.
Game Analysis of Supply Chain Enterprises’ Choice of Carbon Emission Reduction Behavior under Environmental Regulation and Consumers’ Low Carbon Preference

Under the background of low-carbon economy, in order to explore the internal mechanism of enterprises implementing carbon emission reduction behavior, this paper uses evolutionary game theory and numerical simulation method to study the evolutionary stability strategy and its influencing factors of carbon emission reduction behavior of supply chain enterprises in a two-level supply chain composed of a single supplier and a single manufacturer from a dynamic perspective, considering environmental regulation and consumers’ preference for low carbon emission. The results show that there are certain conditions that make supply chain enterprises converge to carbon emission reduction investment behavior under the effect of command-and-control environmental regulation and consumer low-carbon preference, and converge to cooperative carbon emission reduction behavior under the effect of market-based environmental regulation and consumer low-carbon preference. On this basis, the factors significantly influence the carbon emission reduction investment behavior of supply chain enterprises are the carbon emission reward and punishment coefficient and the low carbon preference coefficient of consumers. Increasing the carbon tax rate, carbon emission trading price and the proportion of cost subsidies, as well as encouraging consumers to consume low-carbon products will help promote the realization of cooperative carbon emission reduction.
Colorectal Cancer Screening Prevalence, Perceived Barriers, and Preference for Screening Colonoscopy Among Hospitalized Women

Background: Barriers to colorectal cancer screening persist despite screening campaigns, especially among women. This study explores the prevalence, preferences, and barriers associated with colorectal cancer screening and evaluates the effect of an inpatient intervention (one-on-one bedside education and handout about colorectal cancer) on screening adherence among hospitalized women. Methods: A prospective intervention study among 510 hospitalized women, who are cancer-free (except for skin cancer) at enrollment, aged between 50 and 75 years was conducted at an academic center. Socio-demographic, family history, and medical comorbidities data were collected for all patients. A post-hospitalization follow-up survey determined the effect of inpatient intervention on colorectal cancer screening adherence. Unpaired t-test and chi-square tests were used to compare characteristics, perspectives, and preferences for screening among adherent and non-adherent groups. Results: Mean age was 60.5 years, 45% reported an annual household income of <$20 000, 36% of women were African American, 27% of women were overdue for colorectal cancer screening, and 33% never had a screening colonoscopy. The most frequently reported barriers to colorectal cancer screening were “I have other problems more important than getting a colonoscopy,” “No transportation to get to the test,” and “Not counseled by primary care provider. ” Sixty-six percent of the non-adherent women would agree to have an inpatient screening colonoscopy if offered. Conclusion: A significant number of hospitalized women are non-adherent to colorectal cancer screening, while the educational intervention was partially successful in enhancing colorectal cancer screening, most hospitalized women remained non-adherent after hospitalization. A majority of these women were amenable to inpatient screening colonoscopy if offered during a hospital stay.
FOSTERING DIGITAL LITERACY WITHIN THE SERBIAN EDUCATION SYSTEM

Digital revolution has deeply influenced and changed the way we learn and work, often blurring the boundaries between these two fields of human activity. Bearing in mind that modern ICTs are providing access to an immense stock of knowledge and information that is freely available online, knowledge workers, as ambassadors of the 21 st century workforce, must possess a high degree of digital skills and competences. In order to prepare students for digital era labour market, educational institutions (higher education institutions in particular) are obliged to respond to the challenges that our highly digitized knowledge societies are imposing by incorporating digital literacy courses into their curricula. Such courses strive to instruct students as to how to critically use modern ICTs for retrieving, assessing, storing, producing, presenting and exchanging information, as well as for participating in collaborative networks in online environment
Nutrient composition of some important Brazilian savanna trees and their potential for animal feed

Brazilian savanna (Cerrado) trees present high diversity, whether they are being used by fauna and traditional populations as food or medicine. However, little research has been done to evaluate the nutrient composition of different species relevant to society, which may highlight new uses of these species. The objective of this study was to characterize nutritional aspects of the leaves of different Cerrado native species. Bromatological analyses (i.e. dry matter (DM), total digestible nutrients (TDN), crude protein (CP), ether extract (EE), crude fiber (CF), mineral matter (MM), and nutrient concentration were performed on five native tree species (Inga cylindrica; Platymiscium floribundum, Piptadenia gonoacantha, Anadenanthera macrocarpa, and Dipteryx alata) that presented potential for animal feed, according to farmer’s reports. The chemical characteristics of the leaves of Cerrado trees were characterized and compared between them. All five species evaluated in this study showed nutritional characteristics that suggest their potential use for animal feed, especially the P. floribundum, I. cylindrica, and P. gonoacantha for their high protein value.
Neighborhood graph embedding interpretable fault diagnosis network based on local and non-local information balanced under imbalanced samples

Currently, the monitoring of the health status of mechanical systems is becoming more and more critical, and the actual monitoring data is massive and high-dimensional, and these data are characterized mainly by imbalance. To solve the problem of low fault recognition rate caused by data imbalance, this article proposed a novel local and non-local information balanced neighborhood graph embedding interpretable deep autoencoder (LGBNGEDAE) method for rotating machinery fault diagnosis. Specifically, the local and non-local neighborhood information graph is embedded into the original objective function of the deep autoencoder to smooth the manifold structure of the data in LGBNEDSAE, which endows the deep learning model with better data learning capability and robustness of feature extraction as well as more reasonable network interpretability, making it more suitable for feature learning and classification of unbalanced data. Further, the method’s excellent fault diagnosis capability and generalization performance are verified on two opposed experimental cases of gearboxes. Compared with other deep learning architectures and shallow learning models, the method performs better in the face of unbalanced datasets.
Avaliação econômica da aplicação da produção mais limpa em uma estação de tratamento de efluentes: estudo de caso em uma empresa metal mecânico

Esse trabalho tem como objetivo demonstrar por meio da metodologia de estudo de caso, a avaliação econômica da aplicação da Produção Mais Limpa na Estação de Tratamento de Efluentes de uma pequena empresa brasileira do ramo metal mecânico, na qual o ganho econômico foi de R$ 4.994,67 por mês obtidos com um investimento de R$ 4.560,00, demonstrando que a Produção Mais Limpa proporciona, com pouco investimento inicial, resultados econômicos positivos em curto prazo por meio do uso consciente dos recursos hídricos e atendendo a legislação ambiental local que trata de efluentes industriais, evidenciando que a Produção Mais Limpa é um instrumento que possibilitando obter ganhos econômicos por meio de ações direcionadas à minimização dos impactos causados ao meio ambiente pelos processos produtivos industriais.
Towards the geographies of loneliness: interpreting the spaces of loneliness in farming contexts

ABSTRACT Loneliness is a ‘silent epidemic’, challenging people’s emotional and ontological sense of being in the world. Whilst loneliness has been the focus of medical and psychological research, often being synonymous with discourses of mental ill health, trauma and relationship breakdowns, it has remained under-theorised from a geographical perspective. In offering a critical engagement of how and where loneliness exists geographically, this paper identifies three key spatial dimensions that Geographers can proceed from. First, that loneliness is experienced relationally ‘in place’ through everyday practice and behaviour. Second, that loneliness has the capacity to infiltrate felt socio-emotional relationships and interactions. Third, that loneliness is multi-scalar, affecting bodies, families, friendships, workplaces, neighbourhoods and communities in diverse and intersecting ways. Focusing on farming and farm workers (a group recently referred to in the popular press as potentially facing isolation and loneliness) we draw on interviews with young UK farmers to examine how loneliness can be expressed through labour and routine, how farming loneliness becomes entrenched in the spaces of farming practice and habitus and the relational (and contested) responsibilities of farming communities in identifying, supporting and mediating problem loneliness in increasingly solitary contexts.
CD, UV, and In Silico Insights on the Effect of 1,3-Bis(1′-uracilyl)-2-propanone on Serum Albumin Structure

1,3-diaryl-2-propanone derivatives are synthetic compounds used as building blocks for the realization not only of antimicrobial drugs but also of new nanomaterials thanks to their ability to self-assemble in solution and interact with nucleopeptides. However, their ability to interact with proteins is a scarcely investigated theme considering the therapeutic importance that 1,3-diaryl-2-propanones could have in the modulation of protein-driven processes. Within this scope, we investigated the protein binding ability of 1,3-bis(1′-uracilyl)-2-propanone, which was previously synthesized in our laboratory utilizing a Dakin–West reaction and herein indicated as U2O, using bovine serum albumin (BSA) as the model protein. Through circular dichroism (CD) and UV spectroscopy, we demonstrated that the compound, but not the similar thymine derivative T2O, was able to alter the secondary structure of the serum albumin leading to significant consequences in terms of BSA structure with respect to the unbound protein (Δβ-turn + Δβ-sheet = +23.6%, Δα = −16.7%) as revealed in our CD binding studies. Moreover, molecular docking studies suggested that U2O is preferentially housed in the domain IIIB of the protein, and its affinity for the albumin is higher than that of the reference ligand HA 14−1 (HDOCK score (top 1–3 poses): −157.11 ± 1.38 (U2O); −129.80 ± 6.92 (HA 14−1); binding energy: −7.6 kcal/mol (U2O); −5.9 kcal/mol (HA 14−1)) and T2O (HDOCK score (top 1–3 poses): −149.93 ± 2.35; binding energy: −7.0 kcal/mol). Overall, the above findings suggest the ability of 1,3-bis(1′-uracilyl)-2-propanone to bind serum albumins and the observed reduction of the α-helix structure with the concomitant increase in the β-structure are consistent with a partial protein destabilization due to the interaction with U2O.