Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic Syndrome Causing Cognitive Impairment in Patients With Schizophrenia: A Systematic Review

Schizophrenia often exhibits characteristics like cognitive deficits, and individuals with the condition are at a higher risk of developing metabolic syndrome. The effect of metabolic syndrome on schizophrenia-related cognitive impairment is still unknown, though. This systematic review aims to investigate the association between metabolic syndrome and cognitive impairment in patients with schizophrenia, specifically focusing on neurocognitive and social cognitive performance. Schizophrenia significantly strains the public healthcare system since it necessitates tremendous resources and care to support those suffering from the condition. Furthermore, patients with schizophrenia are more susceptible to developing obesity than the general population, leading to a higher possibility of developing metabolic syndrome. The gut microbiota has been recognized as a critical regulator of bidirectional interactions between the central nervous system and the gastrointestinal tract. Emerging evidence suggests that dysbiosis of the gut microbiota is closely linked to the development of both schizophrenia and obesity, sharing common pathophysiological mechanisms, particularly immune inflammation. In this systematic review, we examine the existing literature to explore the relationship between metabolic syndrome and cognitive impairment in individuals with schizophrenia. By synthesizing available evidence on neurocognitive and social cognitive performance, we aim to provide a comprehensive understanding of the association between metabolic syndrome and cognitive deficits in schizophrenia. The findings from this review will contribute to our knowledge of the complex interplay between metabolic abnormalities, gut microbiota dysbiosis, and cognitive impairments in patients with schizophrenia. This understanding may facilitate the development of novel interventions targeting metabolic syndrome as a potential avenue for improving cognitive outcomes in individuals with schizophrenia.
Janus Kinase Inhibitors in Rheumatoid Arthritis: An Update on the Efficacy and Safety of Tofacitinib, Baricitinib and Upadacitinib

Janus kinase inhibitors (JAKis) are the most recent new drug class to arrive to the market for rheumatoid arthritis (RA) treatment. While they have proven to be a very effective treatment option, there remains significant concern regarding the risk of cardiovascular events, thrombosis and malignancy, particularly given the findings of the post-marketing ORAL Surveillance study and FDA black box warnings. This article reviews the key findings of the most impactful cohort of studies and registry data since ORAL Surveillance. It also evaluates the role of JAKis in practice and offers guidance on risk stratifying patients and determining their suitability for a JAKi.
A Time-Scale Decomposition Approach to Statistically Downscale Summer Rainfall over North China

A time-scale decomposition (TSD) approachto statisticallydownscalesummer rainfallover North China is described. It makes use of two distinct downscaling models respectively corresponding to the interannual and interdecadal rainfall variability. The two models were developed based on objective downscaling scheme that 1) identifies potential predictors based on correlation analysis between rainfall and considered climatic variables over the global scale and 2) selects the ‘‘optimal’’ predictors from the identified potential predictors via cross-validation-based stepwise regression. The downscaling model for the interannual rainfall variability
A Modeling Study on Hypoxia Formation in the Bottom Water of the Youngsan River Estuary, Korea

ABSTRACT Cho, C. -W. ; Song, Y. -S. ; Kim, C. -K. ; Kim, T. -I. ; Han, J.-S. ; Woo, S. -B. ; An, S. , and Choi, T. , 2015. A modeling study on hypoxia formation in the bottom water of the Youngsan River estuary, Korea. Hypoxia negatively affects marine environment and organisms and is an important indicator of estuarine water quality. We conducted a field survey and a three-dimensional particle transport modeling study to investigate summer hypoxia formation in the bottom water of the Youngsan River estuary (YRE). The field survey showed that dissolved oxygen (DO) decreased upstream and toward the bottom. The lowest DO, at 4.4 mg L−1, occurred in the bottom water in front of the estuary dam. We found persistent two-layer estuarine circulation driven by freshwater discharge, which is the main mechanism for delivering offshore water mass upstream. Applying the total oxygen consumption rate (0.50 mg L−1 d−1) observed in the estuary, the offshore water mass entering the estuary loses as much as 4.4 mg L−1 of oxygen during the average travel time (8.8 days) from the mouth of the estuary to the dam. These findings indicate that bottom hypoxia can be formed in front of the estuary dam in summer if offshore water mass with relatively low DO (<8.4 mg L−1) enters the estuary. For the sound management of water quality in the YRE, therefore, we recommend improving the quality of the offshore water entering the YRE and also decreasing oxygen demand by reducing nutrient loading from the YRE dam.
Control Inference Neural Network for Motion Planning With Dynamical Systems

This letter proposes an approach that combines the use of sampling-based motion planning with machine learning algorithms. In particular, the asymptotically optimal planner SST* is used to generate asymptotically minimum time trajectories, considering systems with motion constraints (nonholonomic systems) and different orders in the dynamics of the models. The intermediate states that form the trajectories obtained by the SST* planner, together with the controls that generated them, constitute the inputs and outputs, respectively, of the training set for a new variant of the MPNet network. This contrasts with other works in which neural networks are proposed that infer states that serve as a guide for another complementary method to generate controls that respect the dynamics of the system. The proposed method uses a neural network to directly infer the controls of the system (plus an application time of those controls), accelerating the generation time of trajectories up to three orders of magnitude in comparison to other methods based on learning. The proposed approach is evaluated with different dynamical systems and environments, including maps with concave obstacles and narrow passages.
The Multidomain Metaverse Cancer Care Digital Platform: Development and Usability Study

Background As cancer treatment methods have diversified and the importance of self-management, which lowers the dependence rate on direct hospital visits, has increased, effective cancer care education and management for health professionals and patients have become necessary. The metaverse is in the spotlight as a means of digital health that allows users to engage in cancer care education and management beyond physical constraints. However, it is difficult to find a multipurpose medical metaverse that can not only be used in the field but also complements current cancer care. Objective This study aimed to develop an integrated metaverse cancer care platform, Dr. Meta, and examine its usability. Methods We conducted a multicenter, cross-sectional survey between November and December 2021. A descriptive analysis was performed to examine users’ experiences with Dr. Meta. In addition, a supplementary open-ended question was used to ask users for their suggestions and improvements regarding the platform. Results Responses from 70 Korean participants (male: n=19, 27% and female: n=51, 73%) were analyzed. More than half (n=37, 54%) of the participants were satisfied with Dr. Meta; they responded that it was an interesting and immersive platform (n=50, 72%). Less than half perceived no discomfort when using Dr. Meta (n=34, 49%) and no difficulty in wearing and operating the device (n=30, 43%). Furthermore, more than half (n=50, 72%) of the participants reported that Dr. Meta would help provide non–face-to-face and noncontact services. More than half also wanted to continue using this platform in the future (n=41, 59%) and recommended it to others (n=42, 60%). Conclusions We developed a multidomain metaverse cancer care platform that can support both health professionals and patients in non–face-to-face cancer care. The platform was uniquely disseminated and implemented in multiple regional hospitals and showed the potential to perform successful cancer care.
Intolerance towards Uncertainty and Self-Adjustment of Women Working in Essential and Critical Sectors

Women who work in essential and critical sectors experience increased stress and anxiety during the Covid-19 pandemic. The results of previous research explain that intolerance to uncertainty and adjustment are related to psychological disorders such as stress, conflict, tension, frustration, depression, worry, and anxiety disorders. This research aims to determine the relationship between intolerance of uncertainty and the adjustment of women working in essential and critical sectors. The instruments used were the Personal Adjustment Scale and The Intolerance of Uncertainty Scale-Revised Italian Version (IUS-R Italian). The respondents in this study were 473 female workers in essential and critical sectors who worked in Jakarta, Bogor, Depok, Tangerang, and Bekasi. The research results show that place of work, type of work, and marital status can influence the level of intolerance of uncertainty in working women. The results of the correlation analysis show that the intolerance of uncertainty variable is correlated with the self-adjustment of working women. The results explain that the intolerance of uncertainty contributes to 10.4% of the self-adjustment variable. These results also explain that the self-adjustment variable contributes 10.4% to the intolerance of uncertainty variable.
Gavilea araucana (Phil.) M.N. Correa: first record of an orchid for Chile on Sphagnum peatland in Magallanes

We report the first historical record of the orchid Gavilea araucana (Phil.) M.N. , for a Spha gnum peatland in Chile, close to Torres del Paine National Park. Moreover, a brief description of the peatland and information about associated flora are provided. Southern Patagonia; Sphagnum moss; peatland.
Credit Risk and Market Risk on Stock Prices

This study aims to determine effect of credit risk and market risk on stock price. This research was conducted on bank sector listed on Indonesia Stock Exchange in 2019-2021. The research method used is descriptive and verification with a quantitative approach. The sampling method is purposive sampling method, obtained 37 companies with 111 observations. The data analysis technique used in this research is panel data regression analysis with E-Views 12 software. The results of this study show that either partially or simultaneosly credit risk and market risk has a significant effect on stock prices.
Low-Complexity SVD Precoding for Faster-Than-Nyquist Signaling Using High-Order Modulations

To address the low spectrum efficiency of satellite communications, faster-than-Nyquist (FTN) signaling has proven a promising technology to improve the spectrum efficiency without requiring additional bandwidth or antennas. However, FTN signaling violates the Nyquist criterion, thereby resulting in intersymbol interference (ISI). While existing singular value decomposition (SVD) precoding can eliminate FTN-induced ISI, it ignores interblock interference, leading to low estimation accuracy. Besides, existing SVD precoding requires high complexity due to the lack of efficient and convenient implementation method. Replacing the linear convolution in FTN shaping by the circular convolution, we construct the circular FTN (CFTN) signaling and propose a CFTN-SVD precoding, which offers several advantages over the existing SVD precoding. First, the proposed CFTN-SVD precoding does not require the transmitter to acquire any accurate information about the receiver, streamlining the transmission process. Second, the proposed CFTN-SVD precoding is designed with low implementation complexity, leveraging fast Fourier transform (FFT) and inverse FFT (IFFT) to facilitate the practical implementation. Last but not least, the proposed CFTN-SVD precoding takes all FTN-induced ISI into consideration, resulting in improved estimation accuracy and making it suitable for high-order modulations. Simulation results show that compared with the bit error rate (BER) of Nyquist signaling, the BER loss of the proposed CFTN-SVD precoding is about 0.8 and 0.25 dB for uncoded and coded FTN signaling, respectively, when adopting 256-amplitude phase shift keying.
Parallel and Distributed Bayesian Network Structure Learning

Bayesian networks (BNs) are graphical models representing uncertainty in causal discovery, and have been widely used in medical diagnosis and gene analysis due to their effectiveness and good interpretability. However, mainstream BN structure learning methods are computationally expensive, as they must perform numerous conditional independence (CI) tests to decide the existence of edges. Some researchers attempt to accelerate the learning process by parallelism, but face issues including load unbalancing, costly dominant parallelism overhead. We propose a multi-thread method, namely Fast-BNS version 1 (Fast-BNS-v1 for short), on multi-core CPUs to enhance the efficiency of the BN structure learning. Fast-BNS-v1 incorporates a series of efficiency optimizations, including a dynamic work pool for better scheduling, grouping CI tests to avoid unnecessary operations, a cache-friendly data storage to improve memory efficiency, and on-the-fly conditioning sets generation to avoid extra memory consumption. To further boost learning performance, we develop a two-level parallel method Fast-BNS-v2 by integrating edge-level parallelism with multi-processes and CI-level parallelism with multi-threads. Fast-BNS-v2 is equipped with careful optimizations including dynamic work stealing for load balancing, SIMD edge list deletion for list updating, and effective communication policies for synchronization. Comprehensive experiments show that our Fast-BNS achieves 9 to 235 times speedup over the state-of-the-art multi-threaded method on a single machine. When running on multi-machines, it further reduces the execution time of the single-machine implementation by 80%.
Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data

Monitoring surface and atmospheric parameters—like water vapor—is challenging in the Arctic, despite the daily Arctic‐wide coverage of spaceborne microwave radiometer data. This is mainly due to the difficulties in characterizing the sea ice surface emission: sea ice and snow microwave emission is high and highly variable. There are very few data sets combining relevant in situ measurements with co‐located remote sensing data, which further complicates the development of accurate retrieval algorithms. Here, we present a multi‐parameter retrieval based on the inversion of a forward model for both, atmosphere and surface, for non‐melting conditions. The model consists of a layered microwave emission model of snow and ice. Since snow scattering and emission effects, as well as temperature gradients, are taken into account, a high variability in brightness temperatures can be simulated. For ocean regions and the atmosphere existing parameterized forward models are used. By using optimal estimation, the forward model can be inverted allowing for the simultaneous and consistent retrieval of nine variables: integrated water vapor, liquid water path, sea ice concentration, multi‐year ice fraction, snow depth, snow‐ice interface temperature and snow‐air interface temperature as well as sea‐surface temperature and wind speed (over open ocean). In addition, the method provides retrieval uncertainty estimates for each retrieved parameter. To evaluate the forward model as well as the retrieval, we use the extensive data sets acquired during the year‐long Arctic expedition Multidisciplinary drifting Observatory for the Study of Arctic Climate (2019–2020) as a reference.
High-pressure fluid at hypocentral depths in the L'Aquila region inferred from earthquake focal mechanisms

We apply a new analysis technique using earthquake focal mechanisms to infer the 3-D fluid pressure field at depth in the source region of the A.D. 2009 L9Aquila earthquake/aftershock sequence. The technique, termed focal mechanism tomography, inverts for fluid pressure by examining the fault orientation relative to the regional tectonic stress pattern. We identify three large-scale pockets of high fluid pressure (up to 50 MPa above hydrostatic pressure) at depths of 7–10 km that strongly correlates with an independent data set of well-located foreshocks and aftershocks. The shape of overpressured regions and the evolution of seismicity indicate a plausible scenario that this sequence is being driven in part by the poro-elastic response of trapped reservoirs of high-pressure fluid, presumably CO 2 , and postseismic fluid flow initiated by the main shock.
Vertigo and its burden of disease—Results from a population‐based cohort study

Vertigo describes symptoms of abnormal movement of the environment or the patient's own body. As such, it affects patients' quality of life, prevents them from following their daily activities, and increases healthcare utilization. The Global Burden of Disease Project aims to quantify morbidity and mortality worldwide. In 2013, a separate disability weight for vertigo was introduced. The aim of this study is to estimate the symptom burden of disease caused by vertigo.
Application of different types of microphones in room impulse response measurements

The features of the acoustic field in a room are generally described using omnidirectional and spatial parameters. Those are determined from the recorded Room Impulse Responses (RIR). Standardized RIR recording methods are described in ISO 3382 and require three different types of microphones. An omnidirectional microphone to determine the RIR at a given point in the room and bidirectional or binaural microphone to get RIRs containing the spatial properties of the acoustic field. Instead, popular but not standardized ambisonic technology makes it possible to measure a Spatial Room Impulse Response (SRIR). Signal processing technology lets to obtain omnidirectional and binaural RIRs from an SRIR. In this study, RIRs were recorded using the following types of microphones: omnidirectional, binaural (2 different types of acoustic manikin) and ambisonic (first and third order). Presented results show the comparison of room acoustic parameters calculated from RIRs measured with different microphone techniques. The results show ambisonic technology’s usefulness in assessing room acoustic parameters.
Analysis of the Effect of Market and Proactive Orientation with Market Capabilities on Export Performance in East Java Export-Oriented MSMEs

Research aims: This study examines the causal relationships affecting export performance, including market orientation, proactive orientation, and market capability. Design/Methodology/Approach: This study used a quantitative approach, which was carried out by distributing questionnaires to 140 MSMEs in East Java that had already exported. This study was tested utilizing SmartPLS 4 with partial least squares-structural equation model (PLS-SEM) analysis.Research findings: The results exhibited that market orientation significantly affected export performance and market capability. Proactive orientation substantially affected export performance and market capabilities. Besides, market capability directly and significantly influenced the relationship between market orientation, proactive orientation, and export performance.Theoretical Contribution/Originality: Adding market capability as a mediating variable to test the influence of market orientation and proactive orientation on export performance in export MSMEs in Surabaya.Practitioners/Policy Implications: In improving the export performance of MSMEs, oversight institutions or policymakers are expected to provide regular education, training, and guidance on how to observe and take advantage of changes in the export market, obtain information about customers and the export market situation and study and identify opportunities that exist in the export market.Research Limitations/Implications: In this study, the research locations were limited to the Surabaya area, so further researchers can expand the research locations. Data collection can also be done by interviewing, so that respondents are more open to answering questions. In addition, there were only three variables affecting export performance in this study: market orientation, proactive orientation, and market capability. Because the R-Square value of market capability was still at 0.392, or 40%, other independent variables can influence as much as 60%, such as customer orientation, international orientation, demographic orientation, strategic orientation, and others. Besides, the R-Square value of export performance was 0.538, or 54%, so other mediating variables may affect as much as 467%, such as innovation, production, and productive and dynamic capabilities.
Limnological Studies on Khop Niwari Tank with Special Reference to Phytoplanktons

Every scientific investigation is evaluated in terms of extends of its contribution to the welfare of human and other living beings. Standing water bodies have great importance as they are recharging resources for drinking, domestic and agricultural use before the civilization. Water quality of pond is important for health and economy of people. The present study is going to centralize on the Khop Niwari Tank of Chhatarpur district in Madhya Pradesh.
The Potential Genetic Effect for Yield and Foliar Disease Resistance in Faba Bean (Vicia faba L.) Assessed via Morphological and SCoT Markers

Faba bean is considered one of the most prominent grain legumes, with high protein content for human food consumption and livestock feed. The present study evaluated the nature of gene action and determined the genetic diversity among different populations of three crosses for resistance to foliar diseases at the molecular level. Analysis of variance exposed significant differences among the generations for all measured traits. Both dominance and additive gene effects were essential, but dominance genes, for the most part, exhibited greater effects than additive ones. This indicates an essential role for dominant genes alongside the additives one in inheriting such traits. The third cross (Marina × Giza 40) gave desired significant and positive (additive × additive) values for the number of pods/plant, seeds/plant, and seed yield/plant, in addition to desirable negative values for chocolate spot and rust characteristics. Furthermore, assessing the lines under study using seven SCoT primers disclosed three bands with recorded molecular weights of 260, 207, and 178 bp, generated by SCoT-1, SCoT-4, and SCoT-7 primers, respectively. These bands exist in the resistant parent (Marina), which could be attributed to the high-disease-resistance phenotypes, and they are absent in the sensitive parent (Giza 40) and other putative sensitive lines. Based on the molecular profiles and the genetic similarity between parents and the selected lines, the highest similarity value (0.91) was detected between Marina genotype and BC1, revealing a high foliar disease resistance. Meanwhile, Giza 40 (susceptible to foliar diseases) exhibited the maximum value (0.93) with F2. Additionally, cluster analysis based on genetic relationships was performed, and a high level of correlation between the results of PCR-based SCoT analysis and the foliar disease reactions was observed in the field. Consequently, this study concluded that SCoT markers created reliable banding profiles for evaluating genetic polymorphism among faba bean lines, which could be a foundation for developing an efficient breeding program.