Search Results (7,726)

Futures trading analysis plays a pivotal role in the development of macroeconomic policies and corporate strategy planning. High-frequency futures data, typically presented as time series, contain valuable historical patterns. To address challenges such as non-stationary in modeling futures prices, we propose a novel architecture called FuturesNet, which uses an InceptionTime module to capture the short-term fluctuations between ask and bid orders, as well as a long-short-term-memory (LSTM) module with skip connections to capture long-term temporal dependencies. We evaluated the performance of FuturesNet using datasets numbered 50, 300, and 500 from the domestic financial market. The comprehensive experimental results show that FuturesNet outperforms other competitive baselines in most settings. Additionally, we conducted ablation studies to interpret the behaviors of FuturesNet. Our code and collected futures datasets are released. Full article

Quadruped robots possess significant mobility in complex and uneven terrains due to their outstanding stability and flexibility, making them highly suitable in rescue missions, environmental monitoring, and smart agriculture. With the increasing use of quadruped robots in more demanding scenarios, ensuring accurate and stable state estimation in complex environments has become particularly important. Existing state estimation algorithms relying on multi-sensor fusion, such as those using IMU, LiDAR, and visual data, often face challenges on non-stationary terrains due to issues like foot-end slippage or unstable contact, leading to significant state drift. To tackle this problem, this paper introduces a state estimation algorithm that integrates an invariant extended Kalman filter (InEKF) with a disturbance observer, aiming to estimate the motion state of quadruped robots on non-stationary terrains. Firstly, foot-end slippage is modeled as a deviation in body velocity and explicitly included in the state equations, allowing for a more precise representation of how slippage affects the state. Secondly, the state update process integrates both foot-end velocity and position observations to improve the overall accuracy and comprehensiveness of the estimation. Lastly, a foot-end contact probability model, coupled with an adaptive covariance adjustment strategy, is employed to dynamically modulate the influence of the observations. These enhancements significantly improve the filter’s robustness and the accuracy of state estimation in non-stationary terrain scenarios. Experiments conducted with the Jueying Mini quadruped robot on various non-stationary terrains show that the enhanced InEKF method offers notable advantages over traditional filters in compensating for foot-end slippage and adapting to different terrains. Full article

Background: The gut microbiome is increasingly recognized as a key player in metabolic health, influencing glucose and lipid metabolism through various mechanisms. However, the efficacy of gut microbiota-targeted interventions, such as probiotics, prebiotics, fecal microbiota transplantation (FMT), and diet-based treatments, remains unclear for specific metabolic outcomes. In this study, the aim was to evaluate the impact of these interventions on the glucose and lipid parameters in individuals with metabolic diseases such as diabetes mellitus (DM), obesity, and metabolic syndrome. Methods: This systematic review and meta-analysis included 41 randomized controlled trials that investigated the effects of gut microbiota-targeted treatments on metabolic parameters such as fasting glucose, glycated hemoglobin (HbA1c), homeostatic model assessment for insulin resistance (HOMA-IR), total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. A comprehensive search was conducted using databases like PubMed, Google Scholar, and Scopus, focusing on interventions targeting the gut microbiota. A meta-analysis was performed using random-effects models, with effect sizes calculated for each outcome. Risk of bias was assessed using the Cochrane Risk of Bias tool. Results: Gut microbiota-targeted interventions significantly reduced fasting glucose, HbA1c, HOMA-IR, total cholesterol, LDL-C, and triglycerides, with moderate heterogeneity observed across studies. The interventions also led to modest increases in HDL-C levels. Probiotic and synbiotic interventions showed the most consistent benefits in improving both glucose and lipid profiles, while FMT yielded mixed results. Short-term interventions showed rapid microbial shifts but less pronounced metabolic improvements, whereas longer-term interventions had more substantial metabolic benefits. Conclusions: In this study, it is demonstrated that gut microbiota-targeted interventions can improve key metabolic outcomes, offering a potential therapeutic strategy for managing metabolic diseases. However, the effectiveness of these interventions varies depending on the type, duration, and population characteristics, highlighting the need for further long-term studies to assess the sustained effects of microbiota modulation on metabolic health. Full article

Accumulating evidence suggests that multiple sclerosis (MS) is an environmentally influenced disorder with contributions from life-time exposure to factors including Epstein–Barr virus infection or shifts in microbiome, diet and lifestyle. One suggested factor is a deficiency in propionic acid, a short-chain fatty acid produced by gut bacteria that may contribute to the disease pathology both in animal models and in human cases of MS. Propionate appears to exert beneficial effects on the immune, peripheral and central nervous systems of people with MS (pwMS), showing immunoregulatory, neuroprotective and neurogenerative effects. These functions are crucial, given that MS is characterized by immune-mediated damage of myelin in the central nervous system. Accordingly, propionate supplementation or a modulated increase in its levels through the microbiome and diet may help counteract the pro-inflammatory state in MS by directly regulating immune system and/or by decreasing permeability of gut barrier and blood–brain barrier. This could potentially improve outcomes when used with immune-modulating therapy. However, while its broad effects are promising, further large clinical trials are necessary to evaluate its efficacy and safety in pwMS and clarify its role as a complementary therapeutic strategy. This review provides a comprehensive analysis of the evidence, challenges and limitations concerning propionic acid supplementation in MS. Full article

The study of multilevel dual-active-bridge (DAB) converters has garnered significant attention in recent years thanks to their advantages with respect to the conventional two-level (2L) DAB; namely, its greater performance and its capability to operate at higher voltage. The analysis of the converter high-frequency inductor current ($i_{\mathrm{L}}$) is crucial, for instance, to compute its root mean square (RMS) value, required to estimate the conduction losses in the converter. The mathematical expression of $i_{\mathrm{L}}$ is piecewise and multiple variations, i.e., modes, exist depending on the modulation parameter values. This increases the complexity of converter performance analytical study. Thus, a more practical and generalizable expression of $i_{\mathrm{L}}$ current is desirable. This paper proposes novel compact analytic expressions for the instantaneous and RMS inductor current in the 2L-NL DAB converter, leveraging binary functions to define the piecewise intervals and to identify the mode as a function of the modulation parameter values. The proposed method paves the way for more simple and computationally efficient DAB performance optimization software tools that allow exploring any given converter structures and modulation strategies. Full article

The objective of this study was to investigate the effect of straw return on the formation of Fe-Mn colloids in arsenic-contaminated soils and its subsequent influence on arsenic behavior. It was observed that organic matter (SD) resulting from straw decomposition interacted with iron/manganese (hydr)oxides (Fe/Mn (hydr)oxides) present in the soil, leading to the formation of colloidal particles. These particles significantly influenced the fixation and release of arsenic. The experimental results indicated that an increase in SD content facilitated the formation of colloidal particles. The highest concentration of colloidal particles was observed at a C/Fe-Mn ratio of 2.2, which significantly reduced the bioavailability and mobility of arsenic in the soil. The increase in SD content also diminished the depositional attachment efficiency of SD/Fe-Mn, thereby enhancing its migration through the soil. The actual field soil-filled column experiments further demonstrated that the content of SD significantly influenced arsenic bioavailability and mobility. Specifically, at a C/Fe-Mn ratio of 2.2, the inhibition of arsenic migration and bioavailability was found to be 1.46 times more effective compared to a C/Fe-Mn ratio of 0.4. Therefore, the return of straw to the field represents an effective soil remediation strategy for mitigating the bioavailability of arsenic by modulating the C/Fe-Mn ratio. This approach offers a novel perspective on strategies for heavy metal remediation. Full article

Current wireless capsule endoscopy (WCE) is limited in the long examination time and low flexibility since the capsule is passively moved by the natural peristalsis. Efforts have been made to facilitate the active locomotion of WCE using magnetic actuation and localization technologies. This work focuses on the motion control of the robotic capsule under magnetic actuation in a complex gastrointestinal (GI) tract environment in order to improve the efficiency and accuracy of its motion in dynamic, complex environments. Specifically, a magnetic actuation system based on a four-electromagnetic coil module is designed, and a control strategy for the system is proposed. In particular, the proportional–integral–derivative (PID) control parameters and current values are optimized online and in real time using the adaptive particle swarm optimization (APSO) algorithm. In this paper, both simulations and real-world experiments were conducted using acrylic plates with irregular shapes to simulate the GI tract environment for evaluation. The results demonstrate the potential of the proposed control methods to realize the accurate and efficient inspection of the intestine using active WCE. The methods presented in this paper can be integrated with current WCE to improve the diagnostic accuracy and efficiency of the GI tract. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is a growing health concern worldwide, affecting more than 1 billion adults. It may progress to metabolic dysfunction-associated steatohepatitis (MASH), cirrhosis, and ultimately hepatocellular carcinoma (HCC). Emerging evidence has demonstrated the role in this transition of microRNAs (miRNAs), which regulate the expression of genes associated with lipid metabolism, inflammation, fibrosis, and cell proliferation. Specific miRNAs have been identified to exacerbate or mitigate fibrotic and carcinogenic processes in hepatic cells. The modulation of these miRNAs through synthetic mimics or inhibitors represents a promising therapeutic strategy. Preclinical models have demonstrated that miRNA-based therapies can attenuate liver inflammation, reduce fibrosis, and inhibit tumorigenesis, thus delaying or preventing the onset of HCC. However, challenges such as delivery mechanisms, off-target effects, and long-term safety remain to be addressed. This review, focusing on recently published preclinical and clinical studies, explores the pharmacological potential of miRNA-based interventions to prevent MASLD/MASH and progression toward HCC. Full article

Metabolic reprogramming of immune cells within the tumor microenvironment (TME) plays a pivotal role in shaping tumor progression and responses to therapy. The intricate interplay between tumor cells and immune cells within this ecosystem influences their metabolic landscapes, thereby modulating the immune evasion tactics employed by tumors and the efficacy of immunotherapeutic interventions. This review delves into the metabolic reprogramming that occurs in tumor cells and a spectrum of immune cells, including T cells, macrophages, dendritic cells, and myeloid-derived suppressor cells (MDSCs), within the TME. The metabolic shifts in these cell types span alterations in glucose, lipid, and amino acid metabolism. Such metabolic reconfigurations can profoundly influence immune cell function and the mechanisms by which tumors evade immune surveillance. Gaining a comprehensive understanding of the metabolic reprogramming of immune cells in the TME is essential for devising novel cancer therapeutic strategies. By targeting the metabolic states of immune cells, it is possible to augment their anti-tumor activities, presenting new opportunities for immunotherapeutic approaches. These strategies hold promise for enhancing treatment outcomes and circumventing the emergence of drug resistance. Full article

Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, presents a growing health challenge in Spain. This review examines the current understanding of IBD through the lens of genetics, epigenetics, and metabolism, offering insights into future directions for research and clinical management. Recent advancements in genetic studies have identified numerous susceptibility loci, highlighting the complex interplay between genetic predisposition and environmental triggers. Epigenetic modifications, including DNA methylation and histone modification, further elucidate the pathogenesis of IBD, underscoring the role of gene–environment interactions. Metabolic alterations, particularly in the gut microbiome, emerge as crucial factors influencing disease onset and progression. The integration of multi-omics approaches has enhanced our comprehension of the molecular mechanisms underlying IBD, paving the way for personalized medicine. Looking forward, this review emphasizes the need for longitudinal studies and advanced bioinformatics tools to decode the intricate networks involved in IBD. Additionally, we discuss the potential of novel therapeutic strategies, including epigenetic drugs and microbiome modulation, as promising avenues for improved patient outcomes. This comprehensive overview provides a foundation for future research aimed at unraveling the complexities of IBD and developing innovative treatments tailored to the Spanish population. Full article

Oxidative stress (OS) plays a crucial role in placental pathogenesis and pregnancy-related complications. This review explores OS’s impact on placental development and function, focusing on novel biomarkers for the early detection of at-risk pregnancies and emerging therapeutic strategies. We analyzed recent research on OS in placental pathophysiology, examining its sources, mechanisms, and effects. While trophoblast invasion under low-oxygen conditions and hypoxia-induced OS regulate physiological placental development, excessive OS can lead to complications like miscarriage, preeclampsia, and intrauterine growth restriction. Promising OS biomarkers, including malondialdehyde, 8-isoprostane, and the sFlt-1/PlGF ratio, show potential for the early detection of pregnancy complications. Therapeutic strategies targeting OS, such as mitochondria-targeted antioxidants, Nrf2 activators, and gasotransmitter therapies, demonstrate encouraging preclinical results. However, clinical translation remains challenging. Future research should focus on validating these biomarkers in large-scale studies and developing personalized therapies to modulate placental OS. Emerging approaches like extracellular vesicle-based therapies and nanomedicine warrant further investigation for both diagnostic and therapeutic applications in pregnancy-related complications. Integrating OS biomarkers with other molecular and cellular markers offers improved potential for the early identification of at-risk pregnancies. Full article

In the prediction of single-well production in gas reservoirs, the traditional empirical formula of gas reservoirs generally shows poor accuracy. In the process of machine learning training and prediction, the problems of small data volume and dirty data are often encountered. In order to overcome the above problems, a single-well production prediction model of gas reservoirs based on CNN-BILSTM-AM is proposed. The model is built by long-term and short-term memory neural networks, convolutional neural networks and attention modules. The input of the model includes the production of the previous period and its influencing factors. At the same time, the fitting production and error value of the traditional gas reservoir empirical formula are introduced to predict the future production data. The loss function is used to evaluate the deviation between the predicted data and the real data, and the Bayesian hyperparameter optimization algorithm is used to optimize the model structure and comprehensively improve the generalization ability of the model. Three single wells in the Daniudi D28 well area were selected as the database, and the CNN-BILSTM-AM model was used to predict the single-well production. The results show that compared with the prediction results of the convolutional neural network (CNN) model, long short-term memory neural network (LSTM) model and bidirectional long short-term memory neural network (BILSTM) model, the error of the CNN-BILSTM-AM model on the test set of three experimental wells is reduced by 6.2425%, 4.9522% and 3.0750% on average. It shows that on the basis of coupling the empirical formula of traditional gas reservoirs, the CNN-BILSTM-AM model meets the high-precision requirements for the single-well production prediction of gas reservoirs, which is of great significance to guide the efficient development of oil fields and ensure the safety of China’s energy strategy. Full article

The use of chiral organic ligands as linkers and metal ion nodes with specific coordination geometry is an effective strategy for creating homochiral structures with potential ferroelectric properties. Natural Cinchona alkaloids, e.g., quinine and cinchonine, as compounds with a polar quinuclidine fragment and aromatic quinoline ring, are suitable candidates for the construction of molecular ferroelectrics. In this work, the compounds [CnZnCl₃]·MeOH and [CnZnBr₃]·MeOH, which crystallize in the ferroelectric polar space group P2₁, were prepared by reacting the cinchoninium cation (Cn) with zinc(II) chloride or zinc(II) bromide. The structure of [CnZnBr₃]·MeOH was determined from single-crystal X-ray diffraction analysis and was isostructural with the previously reported chloride analog [CnZnCl₃]·MeOH. The compounds were characterized by infrared spectroscopy, and their thermal stability was determined by thermogravimetric analysis and temperature-modulated powder X-ray diffraction experiments. The intermolecular interactions of the different cinchoninium halogenometalate complexes were evaluated and compared. Full article

In recent years, the increasing number of long-duration space missions has prompted the scientific community to undertake a more comprehensive examination of the impact of microgravity on the human body during spaceflight. This review aims to assess the current knowledge regarding the consequences of exposure to an extreme environment, like microgravity, on the human body, focusing on the role of heat-shock proteins (HSPs). Previous studies have demonstrated that long-term exposure to microgravity during spaceflight can cause various changes in the human body, such as muscle atrophy, changes in muscle fiber composition, cardiovascular function, bone density, and even immune system functions. It has been postulated that heat-shock proteins (HSPs) may play a role in mitigating the harmful effects of microgravity-induced stress. According to past studies, heat-shock proteins (HSPs) are upregulated under simulated microgravity conditions. This upregulation assists in the maintenance of the proper folding and function of other proteins during stressful conditions, thereby safeguarding the physiological systems of organisms from the detrimental effects of microgravity. HSPs could also be used as biomarkers to assess the level of cellular stress in tissues and cells exposed to microgravity. Therefore, modulation of HSPs by drugs and genetic or environmental techniques could prove to be a potential therapeutic strategy to reduce the negative physiological consequences of long-duration spaceflight in astronauts. Full article

The gut microbiota, a diverse collection of microorganisms in the gastrointestinal tract, plays a critical role in regulating metabolic, immune, and cognitive functions. Disruptions in the composition of these microbial communities, termed dysbiosis, have been linked to various neurodegenerative diseases (NDs), such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). One of the key pathological features of NDs is neuroinflammation, which involves the activation of microglia and peripheral immune cells. The gut microbiota modulates immune responses through the production of metabolites and interactions with immune cells, influencing the inflammatory processes within the central nervous system. This review explores the impact of gut dysbiosis on neuroinflammation, focusing on the roles of microglia, immune cells, and potential therapeutic strategies targeting the gut microbiota to alleviate neuroinflammatory processes in NDs. Full article