Abstract: Culturally and linguistically diverse (CALD) communities are growing globally. Understanding patterns of cerebrovascular disease in these communities may improve health outcomes. We aimed to compare the rates of transient ischaemic attack (TIA), ischaemic stroke (IS), intracerebral haemorrhage (ICH), intracranial atherosclerosis (ICAD), and stroke risk factors in Vietnamese-born residents of South-Western Sydney (SWS) with those of an Australian-born cohort. A 10-year retrospective analysis (2011–2020) was performed using data extracted from the Health Information Exchange database characterising stroke presentations and risk factor profiles. The rates of hypertension (83.7% vs. 70.3%, p <0.001) and dyslipidaemia (81.0% vs. 68.2%, p < 0.001) were significantly higher in Vietnamese patients, while the rates of ischaemic heart disease (10.4% vs. 20.3%, p < 0.001), smoking (24.4% vs. 40.8%, p < 0.001), and alcohol abuse (>1 drink/day) (9.6% vs. 15.9%, p < 0.001) were lower. The rates of ICAD and ICH were higher in Vietnamese patients (30.9% vs. 6.9%, p < 0.001 and 24.7% vs. 14.4%, p = 0.002). Regression analysis revealed that diabetes (OR: 1.86; 95% CI: 1.14–3.04, p = 0.014) and glycosylated haemoglobin (OR: 1.51; 95% CI: 1.15–1.98, p = 0.003) were predictors of ICAD in Vietnamese patients. Vietnamese patients had higher rates of symptomatic ICAD and ICH, with unique risk factor profiles. Culturally specific interventions arising from these findings may more effectively reduce the community burden of disease. Full article

Reference crop evapotranspiration (ET₀) is a key factor in ecohydrological processes. Studying the variation trend of ET₀ in arid river valleys and its influencing factors is not only helpful to understanding the response of dry and hot river valleys to hydrological processes under the background of climate change but also has important guiding significance for the efficient allocation of soil and water resources and the stable maintenance of the ecosystem in this area. Based on the daily meteorological data of three representative meteorological stations in the middle Dry-hot Valley of the Jinsha River from 1988 to 2019, the ET₀ variation and its influencing factors in the middle Dry-hot Valley of the Jinsha River are analyzed by quantitative and qualitative methods. The results showed that (1) the ET₀ in the middle and middle of the Dry-hot Valley of Jinsha River showed a significant fluctuating trend (Z > 1.98), and the linear change rates were examined in Huaping, Yuanmou, and Panzhihua. (2) Grey correlation analysis and principal component analysis mutually verify that daily mean temperature is the most influential meteorological factor. (3) The sensitivity of ET₀ to the change in meteorological factors in the middle section and its sub-sections is as follows: daily average temperature, daily relative humidity, daily average wind speed, and sunshine hours. ET₀ is the most sensitive to the change in daily average temperature, followed by the strengthening of daily average wind speed and the reduction in daily relative humidity, and the sensitivity of ET₀ to the change in sunshine hours is the least. (4) Among the regions, the meteorological factors that contributed the most to the increase in ET₀ in Huaping, Panzhihua, and Yuanmou were daily average wind speed (6.086%), daily average wind speed (8.468%) and daily average temperature (3.869%), respectively. The meteorological factors that contributed the least were sunshine hours. Full article

Silicon carbide (SiC)-based metal–oxide–semiconductor field-effect transistors (MOSFETs) hold promising application prospects in future high-capacity high-power converters due to their excellent electrothermal characteristics. However, as nascent power electronic devices, their long-term operational reliability lacks sufficient field data. The power cycling test is an important experimental method to assess packaging-related reliability. In order to obtain data closest to actual working conditions, forward power cycling is utilized to carry out SiC MOSFET degradation experiments. Due to the wide bandgap characteristics of SiC MOSFETs, the short-term drift of the threshold voltage is much more serious than that of silicon (Si)-based devices. Therefore, an offline threshold voltage measurement circuit is implemented during power cycling tests to minimize errors arising from this short-term drift. Different characterizations are performed based on power cycling tests, focused on measuring the on-state resistance, thermal impedance, and threshold voltage of the devices. The findings reveal that the primary failure mode under forward power cycling tests, with a maximum junction temperature of 130 ${}^{\circ }$C, is bond-wire degradation. Conversely, the solder layer and gate oxide exhibit minimal degradation tendencies under these conditions. Full article

This study aims to investigate the influence of air pollution and physical exercise on residents’ health using data from the Chinese General Social Survey (CGSS) 2018. The research is based on the Grossman Health Production Function and employs the ordered logit model to analyze the relationship between air pollution, physical exercise, and residents’ health. We find that among the Chinese population aged 18 and above, air pollution negatively affects residents’ physical health, whereas physical exercise has a significantly positive effect. Introducing gender-stratified and urban–rural stratified models, the research reveals that the negative effects of air pollution on residents’ health vary among different groups. On one hand, men and residents living in urban areas will bear heavier health damages due to air pollution. On the other hand, physical exercise positively affect the health of both men and women, whether in rural or urban areas. Additionally, age and higher income are associated with better physical health, whereas education does not show a significant impact. Based on these findings, a series of policy recommendations have been proposed to comprehensively and systematically promote ecological governance and sustainable development. The government should strengthen environmental regulations, reduce residents’ exposure to air pollution risks, improve the equality of basic public services, invest in rural sports infrastructure, promote healthy lifestyles, and provide personalized health guidance through health education and mobile health services. Moreover, when formulating policies, the government should consider the specific needs of different groups to ensure the fairness and sustainability of the policies. Full article

Muscle mass depletion is associated with unfavorable outcomes in many diseases. However, its relationship with cardiac arrest outcomes has not been explored. This retrospective single-center study determined the relationship between muscle mass depletion and the neurological outcomes of patients with out-of-hospital cardiac arrest (OHCA) by measuring muscle mass at various locations. Adult patients with OHCA, who were treated with target temperature management, and who underwent abdominal or chest computed tomography (CT) within 3 months of the cardiac arrest were included. Skeletal muscle index (SMI) was measured at the third lumbar vertebra (L3) level, psoas muscle, fourth thoracic vertebra (T4) level, and pectoralis muscle. The Youden index was used to determine a low SMI based on sex-specific cutoff values. The outcome variables were “good neurological outcome” and “survival” at hospital discharge. Multivariable analyses revealed that patients with low T4 SMI level were significantly associated with good neurological outcomes at hospital discharge (odds ratio = 0.26, 95% confidence interval: 0.07–0.88, p = 0.036). However, no significant differences were observed between good neurological outcomes and low SMI at the L3 level and psoas and pectoralis muscles; SMIs were not associated with survival at hospital discharge. T4 level SMI depletion was inversely associated with good neurological outcomes in patients with OHCA. Thoracic muscle depletion may be crucial for predicting the neurological outcomes in patients with OHCA and further investigation in larger prospective study is warranted. Full article

Immune checkpoint inhibitors (ICI) have revolutionised cancer treatment in people. Immune checkpoints are important regulators of the body’s reaction to immunological stimuli. The most studied immune checkpoint molecules are programmed death (PD-1) with its ligand (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with its ligands CD80 (B7-1) and CD86 (B7-2). Certain tumours can evade immunosurveillance by activating these immunological checkpoint targets. These proteins are often upregulated in cancer cells and tumour-infiltrating lymphocytes, allowing cancer cells to evade immune surveillance and promote tumour growth. By blocking inhibitory checkpoints, ICI can help restore the immune system to effectively fight cancer. Several studies have investigated the expression of these and other immune checkpoints in human cancers and have shown their potential as therapeutic targets. In recent years, there has been growing interest in studying the expression of immune checkpoints in dogs with cancer, and a few small clinical trials with ICI have already been performed on these species. Emerging studies in veterinary oncology are centred around developing and validating canine-targeted antibodies. Among ICIs, anti-PD-1 and anti-PD-L1 treatments stand out as the most promising, mirroring the success in human medicine over the past decade. Nevertheless, the efficacy of caninized antibodies remains suboptimal, especially for canine oral melanoma. To enhance the utilisation of ICIs, the identification of predictive biomarkers for treatment response and the thorough screening of individual tumours are crucial. Such endeavours hold promise for advancing personalised medicine within veterinary practice, thereby improving treatment outcomes. This article aims to review the current research literature about the expression of immune checkpoints in canine cancer and the current results of ICI treatment in dogs. Full article

In the majority of children with growth hormone (GH) deficiency (GHD), normal GH secretion may occur before the attainment of final height. The aim of the study was to assess the incidence of persistent and transient GHD and the effectiveness of recombined human GH (rhGH) therapy in children with isolated, idiopathic GHD with respect to the moment of therapy withdrawal and according to different diagnostic criteria of GHD. The analysis included 260 patients (173 boys, 87 girls) with isolated, idiopathic GHD who had completed rhGH therapy and who had been reassessed for GH and IGF-1 secretion. The incidence of transient GHD with respect to different pre- and post-treatment criteria was compared together with the assessment of GH therapy effectiveness. The incidence of transient GHD, even with respect to pediatric criteria, was very high. Normal GH secretion occurred before the attainment of near-final height. Application of more restricted criteria decreased the number of children diagnosed with GHD but not the incidence of transient GHD among them. Poor response to GH therapy was observed mainly in the patients with normal IGF-1 before treatment, suggesting that their diagnosis of GHD may have been a false positive. Further efforts should be made to avoid the overdiagnosis GHD and the overtreatment of patients. Full article

Utilizing the discrete fracture model (DFM), a transient flow model is established for fractured horizontal wells in tight oil reservoirs, accounting for threshold pressure gradient (TPG), stress sensitivity effect, hydraulic fracture parameters, and fracture distribution pattern. This model is solved using the finite-volume method (FVM), and an important sensitivity analysis is conducted. The findings reveal that the models incorporated by the threshold pressure gradient result in an upward trend in the pressure-derivative curve. As the threshold pressure gradient increases, this upward trend becomes more pronounced, rendering the distinction between flow regimes more challenging. The stress sensitivity effect predominantly impacts the pressure-derivative curve during the later flow period. Additionally, as the fracture half-length increases, the pressure performance of both fracture radial flow and formation radial flow becomes more difficult. Fracture conductivity has a significant influence during the early flow period, facilitating the identification of flow regimes with the trend of increasing fracture conductivity. Full article

Research has confirmed the positive impact of social interaction behaviors, including improved mental health, creativity, and stress reduction. Notably, a relationship exists between the spatial characteristics of university campuses and social interaction behaviors. The theories of supportive environment and ecological psychology were used to investigate the quantitative relationship between spatial features of informal spaces and social interactions at a university in a cold region to determine supportive features. Deep learning-based computer vision methods were employed to collect and analyze crowd behavior data, and multiple regression analysis was used to determine the relationship between the features and social interactions. The results indicate that functional features significantly influence social interactions, whereas physical features have a relatively minor impact on social interaction frequency. This finding confirms the efficacy of informal space design at cold-region universities in promoting social interaction behaviors. The deep learning method enables quantitative analysis of the effect of environmental features on social behaviors on cold-region university campuses, providing valuable design suggestions and insights for campuses in other regions and research related to social interaction behaviors. Full article

(1) Background: The wording of informed consent forms could hinder their comprehension and hinder patients’ autonomous choice. The objective of this study was to analyze the readability and comprehension of anesthesia informed consent forms in a Spanish county hospital. (2) Methods: Descriptive and cross-sectional study carried out on patients who were going to undergo anesthetic techniques. The readability of the forms was analyzed using the INFLESZ tool and their subjective comprehension using an ad hoc questionnaire. (3) Results: The analyzed forms presented a “somewhat difficult” legibility. A total of 44.2% of the patients decided not to read the form, mainly because they had previously undergone surgery with the same anesthetic technique. The language used in the forms was considered inadequate by 49.5% of the patients and 53.3% did not comprehend it in its entirety. A statistically significant negative correlation of age and INFLESZ readability score with the overall questionnaire score was found. A statistically significant association was observed as a function of age and educational level with the different criteria of the questionnaire. (4) Conclusions: The anesthesia informed consent forms presented low readability with limited comprehension. It would be necessary to improve their wording to favor comprehension and to guarantee patients’ freedom of choice. Full article

This paper addresses the phenomenon of sloshing and the issues that arise during liquid handling at visual inspection stations. The pharmaceutical industry, recently put under pressure by the pandemic, has long adopted modular solutions consisting mainly of robotic islands. This work focuses on a visual inspection island for glass vials and ampules called VRU. This machine uses robotic arms to optimize the inspection process and enables automated control of a wide range of products using image recognition techniques and AI algorithms. However, the handling of containers in the presence of liquids requires special precautions to avoid the occurrence of bubbles inside the fluid that can prevent the cameras from correctly capturing any defects present. The banal solution involves a drastic reduction in the speeds and accelerations to which the liquids are subjected. However, using appropriate techniques makes it possible to achieve performance values similar to those obtainable when manipulating solid materials. The developed algorithms were tested using multibody simulations in the Mathworks Simscape environment and then validated using a six-axis Fanuc robot. In this study, however, the analysis conducted aimed to determine the correlations between trajectories, laws of motion, and sloshing in containers handled at high speed in industrial applications. In this study a multibody model was developed using a CFD analysis. The container consisted of a glass vial for pharmaceutical uses containing a liquid inside. The results obtained from the CFD analysis allowed us to calibrate the multibody model for the next phase of optimization of the laws of motion to be followed by the manipulator. Full article

Since their release, the medical community has been actively exploring large language models’ (LLMs) capabilities, which show promise in providing accurate medical knowledge. One potential application is as a patient resource. This study analyzes and compares the ability of the currently available LLMs, ChatGPT-3.5, GPT-4, and Gemini, to provide postoperative care recommendations to plastic surgery patients. We presented each model with 32 questions addressing common patient concerns after surgical cosmetic procedures and evaluated the medical accuracy, readability, understandability, and actionability of the models’ responses. The three LLMs provided equally accurate information, with GPT-3.5 averaging the highest on the Likert scale (LS) (4.18 ± 0.93) (p = 0.849), while Gemini provided significantly more readable (p = 0.001) and understandable responses (p = 0.014; p = 0.001). There was no difference in the actionability of the models’ responses (p = 0.830). Although LLMs have shown their potential as adjunctive tools in postoperative patient care, further refinement and research are imperative to enable their evolution into comprehensive standalone resources. Full article

In this study, we explore backward stochastic differential equations driven by a Poisson process and an independent Brownian motion, denoted for short as BSDEJs. The generator exhibits logarithmic growth in both the state variable and the Brownian component while maintaining Lipschitz continuity with respect to the jump component. Our study rigorously establishes the existence and uniqueness of solutions within suitable functional spaces. Additionally, we relax the Lipschitz condition on the Poisson component, permitting the generator to exhibit logarithmic growth with respect to all variables. Taking a step further, we employ an exponential transformation to establish an equivalence between a solution of a BSDEJ exhibiting quadratic growth in the z-variable and a BSDEJ showing a logarithmic growth with respect to y and z. Full article

Long-chain n-3 polyunsaturated fatty acid (PUFA) supplementation has shown potential benefits in the prevention of coronary heart disease (CHD); however, the impact of omega-3 fatty acid levels on CHD risk remains a subject of debate. Here, we aimed to investigate the association between n-3 PUFA levels and the risk of CHD, with particular reference to the subtypes of n-3 PUFA. Methods: Prospective studies and retrospective case-control studies analyzing n-3 PUFA levels in CHD, published up to July 30, 2022, were selected. A random effects meta-analysis was used for pooled assessment, with relative risks (RRs) expressed as 95% confidence intervals (CIs) and standardized mean differences expressed as weight mean differences (WMDs). Subgroup and meta-regression analyses were conducted to assess the impact of n-3 PUFA exposure interval on the CHD subtype variables of the study. Results: We included 20 prospective studies (cohort and nested case-control) and 16 retrospective case-control studies, in which n-3 PUFAs were measured. Higher levels of n-3 PUFAs (ALA, EPA, DPA, DHA, EPA + DHA, total n-3 PUFAs) were associated with a reduced risk of CHD, with RRs (95% CI) of 0.89 (0.81, 0.98), 0.83 (0.72, 0.96); 0.80 (0.67,0.95), 0.75 (0.64, 0.87), 0.83 (0.73, 0.95), and 0.80 (0.70, 0.93), respectively, p < 0.05. CHD patients had significantly lower n-3 PUFA levels compared to healthy controls (p < 0.05). In the subgroup analysis, a significant inverse trend was found for both fatal CHD and non-fatal CHD with n-3 PUFA (EPA + DHA) levels. Also, the link between n-3 PUFA levels in erythrocytes with total CHD was generally stronger than other lipid pools. Conclusions: n-3 PUFAs are significantly related to CHD risk, and these findings support the beneficial effects of n-3 PUFAs on CHD. Full article

Psoriasis is an inflammatory skin disease with a chronic relapsing course and an often-detrimental impact on patients’ quality of life. Thanks to incredible advances in research over the past few decades, the therapeutic armamentarium of psoriasis is now reasonably broad and structured, with several therapeutic agents that have demonstrated successful long-term control of this condition. However, there are still unfulfilled gaps resulting from the inherent limitations of existing therapies, which have paved the way for the identification of new therapeutic strategies or the improvement of existing ones. A great deal of attention has recently been paid to the JAK/STAT pathway, playing a crucial role in chronic inflammatory skin diseases, including psoriasis. Indeed, in a disease with such a complex pathogenesis, the possibility to antagonize multiple molecular pathways via JAK/STAT inhibition offers an undeniable therapeutic advantage. However, data from clinical trials evaluating the use of oral JAK inhibitors in immune-mediated disorders, such as RA, have arisen safety concerns, suggesting a potentially increased risk of class-specific AEs such as infections, venous thromboembolism, and malignancies. New molecules are currently under investigation for the treatment of psoriasis, such as deucravacitinib, an oral selective inhibitor that binds to the regulatory domain of TYK2, brepocitinib (PF-06700841) and PF-06826647 that bind to the active site in the catalytic domain. Due to the selective TYK2 blockade allowing the inhibition of key cytokine-mediated signals, such as those induced by IL-12 and IL-23, anti-TYK2 agents appear to be very promising as the safety profile seems to be superior compared with pan-JAK inhibitors. The aim of our review is to thoroughly explore the rationale behind the usage of JAK inhibitors in PsO, their efficacy and safety profiles, with a special focus on oral TYK2 inhibitors, as well as to provide a forward-looking update on novel therapeutic strategies targeting the TYK2 pathway in psoriasis. Full article

The A-star algorithm (A*) is a traditional and widely used approach for route planning in various domains, including robotics and automobiles in smart agriculture. However, a notable limitation of the A-star algorithm is its tendency to generate paths that lack the desired smoothness. In response to this challenge, particularly in agricultural operations, this research endeavours to enhance the evaluation of individual nodes within the search procedure and improve the overall smoothness of the resultant path. So, to mitigate the inherent choppiness of A-star-generated paths in agriculture, this work adopts a novel approach. It introduces utilizing Bezier curves as a postprocessing step, thus refining the generated paths and imparting their smoothness. This smoothness is instrumental for real-world applications where continuous and safe motion is imperative. The outcomes of simulations conducted as part of this study affirm the efficiency of the proposed methodology. These results underscore the capability of the enhanced technique to construct smooth pathways. Furthermore, they demonstrate that the generated paths enhance the overall planning performance. However, they are also well suited for deployment in rural conditions, where navigating complex terrains with precision is a critical necessity. Full article

The third-person omniscient narrator of fiction texts for children holds the ability to access characters’ thoughts, fly where they will within the story, and interact with time and tense. Philip Pullman characterises this kind of narrator as a multiscient sprite, not a human seeing and telling, but something else which possesses unhuman-like qualities. This paper uses an analysis of the narrator’s voice, character, and choices to access two other characters created by the story being told—the narratee and the implied reader, both of whom may well be thought of as child characters produced by the text. A profile of these two products is then presented. Through a close textual analysis, which draws out untagged parts of Northern Light’s narrator’s speech, an examination of the kinds of characters the narratee, and implied reader could be seen to be is gathered. The narrator’s ability to intensely empathise with characters is passed onto the narratee and also normalised by aspects of the story, including the alethiometer, a device from the created world of the story which is imbued with strikingly similar qualities to the narrator. Lyra, the book’s protagonist, and the instrument interact with each other in a manner akin to the narrator and narratee, both having an agency which the implied reader could be bestowed with from reading the text. Full article

The seasonal characteristics of air pollutant concentrations are important for understanding variations in emissions released into the air and in atmospheric chemistry. The patterns seen can be influenced by anthropogenic emissions, meteorological conditions, and the transport of pollutants over long and short distances. Whilst seasonality is well understood for some pollutants such as ozone and polycyclic aromatic hydrocarbons, it is poorly understood and under-investigated for heavy metals in particulate matter (PM). This work studies long-term datasets of heavy metals in PM from a relevant UK air quality monitoring network, demonstrating the seasonal characteristics of the concentrations of these metals for the first time. Surprisingly, both ‘high in winter–low in summer’ and ‘low in winter–high in summer’ seasonality was observed, with some metals showing little or no seasonality. The ‘high in winter–low in summer’ seasonality (particularly for As) is attributable to the dominant contribution being from local primary sources, such as burning process producing larger PM sizes. The ‘low in winter–high in summer’ seasonality (particularly for V) is attributable to weak or non-seasonal local sources being dominated by contributions from medium and long-range transport during the summer months, when pollutant transport is more efficient. The findings contribute significantly to our understanding of the seasonality of metals in PM concentrations and the role played by the long-range transport of pollutants. Conclusions are also drawn about the implications for the calculation of annual averages on compliance-based air quality networks if data from a time series of a pollutant that displays seasonal characteristics are missing. Full article

This review highlights the significant interaction between microplastic (MP) pollution and its impact on wastewater treatment systems, focusing on optimizing biogas production. We explore various sources of MPs, including tire-derived MPs, and their introduction into wastewater environments. This review delves into the mechanical and physicochemical challenges MPs pose in treatment processes, emphasizing the need for comprehensive mitigation strategies. The biological effects of MPs on microbial consortia essential for biogas production are analyzed, particularly how these pollutants interfere with each stage of anaerobic digestion—hydrolysis, acidogenesis, acetogenesis, and methanogenesis—and, consequently, biogas generation. We examine MPs’ quantitative and qualitative impacts on biogas output and production rates, uncovering how MPs disrupt microbial activity in these stages. This review also discusses novel mitigation strategies combining different sludge pretreatment methods with MPs. Our goal is to enhance the sustainability of wastewater management by promoting efficient biogas production and environmental protection in the presence of persistent MP contamination. Full article

Risk estimation holds significant importance in the selection of risk reduction measures and ensuring machinery safety. However, subjective influences of assessors lead to an inconsistent understanding of risk among relevant stakeholders, hindering the achievement of safety. As similarities exists in product updates or applications in engineering practice, the historical risk information of similar products or applications has essential application value. A novel deep learning approach was established to estimate risks based on historical risk information. To address the issue of overfitting caused by a limited dataset, a data augmentation technique was employed. Our experiment was conducted on the raw, 2×, and 6× hazard event dataset of an industrial robot, demonstrating a substantial improvement in both accuracy and stability. On the validation dataset, there was an increase in median accuracy from 55.56% to 96.92%, with a decrease in standard deviation from 0.118 to 0.015. On the new dataset, the trained network also showed near-perfect performance on similar hazard events and trustworthiness on completely different ones. In cases of risk deviations, approximately 80% of them were small deviations (|RI_deviation| ≤ 2) without a noticeable bias (RI_dis is close to 1). The LSTM-based deep learning network makes risk estimation “black-boxed” and “digitized”. Assessors just need to focus on hazard identification with risk being determined by the trained network, mitigating the impact of individual factors. Moreover, the historical risk estimation information can be transformed into a trained network, facilitating the development of a standardized benchmark within project teams, enterprises, and relevant stakeholders to promote coordinated safety measures. Full article

Numerous studies are based on the correlation among stock factors, which affects the measurement value and interpretability of such studies. Research on the causality among stock factors primarily relies on statistical models and machine learning algorithms, thereby failing to fully exploit the formidable computational capabilities of deep learning models. Moreover, the inference of causal relationships largely depends on the Granger causality test, which is not suitable for non-stationary and non-linear stock factors. Also, most existing studies do not consider the impact of confounding variables or further validation of causal relationships. In response to the current research deficiencies, this paper introduces a deep learning-based algorithm aimed at inferring causal relationships between stock closing prices and relevant factors. To achieve this, causal diagrams from the structural causal model (SCM) were integrated into the analysis of stock data. Subsequently, a sliding window strategy combined with Gated Recurrent Units (GRUs) was employed to predict the potential values of closing prices, and a grouped architecture was constructed inspired by the Potential Outcomes Framework (POF) for controlling confounding variables. The architecture was employed to infer causal relationships between closing price and relevant factors through the non-linear Granger causality test. Finally, comparative experimental results demonstrate a marked enhancement in the accuracy and performance of closing price predictions when causal factors were incorporated into the prediction model. This finding not only validates the correctness of the causal inference, but also strengthens the reliability and validity of the proposed methodology. Consequently, this study has significant practical implications for the analysis of causality in financial time series data and the prediction of stock prices. Full article

Spintronics, utilizing both the charge and spin of electrons, benefits from the nonvolatility, low switching energy, and collective behavior of magnetization. These properties allow the development of magnetoresistive random access memories, with magnetic tunnel junctions (MTJs) playing a central role. Various spin logic concepts are also extensively explored. Among these, spin logic devices based on the motion of magnetic domain walls (DWs) enable the implementation of compact and energy-efficient logic circuits. In these devices, DW motion within a magnetic track enables spin information processing, while MTJs at the input and output serve as electrical writing and reading elements. DW logic holds promise for simplifying logic circuit complexity by performing multiple functions within a single device. Nevertheless, the demonstration of DW logic circuits with electrical writing and reading at the nanoscale is still needed to unveil their practical application potential. In this review, we discuss material advancements for high-speed DW motion, progress in DW logic devices, groundbreaking demonstrations of current-driven DW logic, and its potential for practical applications. Additionally, we discuss alternative approaches for current-free information propagation, along with challenges and prospects for the development of DW logic. Full article