Miracle-dz/UniFAR-FTUs huggingface dataset:
Precar: An Adaptive ML-Based Tool for Predicting Cardiovascular Disease

Predicting the probability of having a cardiovascular event during the next 10 years is a medical practice that allows physicians to provide ad-hoc treatment on time. Based on this indicator, medical doctors routinely request additional medical and clinical examinations to ascertain the presence of heart disease in patients. Previous work in Chile has shown that cardiovascular risk models built in other regions may not be directly applicable without first adapting them to the realities of the local population. In this paper, we introduce Precar, a comprehensive tool designed to predict cardiovascular risk using machine-learning models. Notably, Precar implements four powerful methods—decision trees, random forests, support vector machines, and k-nearest neighbors—with an accuracy over 90%. Additionally, the renowned Framingham risk indicator is integrated to enhance risk assessment. The early model versions were developed using the well-known Cleveland Heart Disease Dataset, ensuring a robust foundation for risk prediction. A key aspect of Precar is its support for a continuous learning approach, enabling collaboration between data scientists and medical doctors. Medical practitioners can actively decide to retrain the models with daily patient data when the model’s performance during medical practice falls below a specified threshold. This adaptive learning process ensures that the tool remains current and relevant in real-world clinical settings. Results are encouraging. The transparency and collaboration provided by Precar empower clinicians, enhancing their confidence in machine learning predictions and driving more effective decision-making in patient care.
Dynamic Mesh Recovery from Partial Point Cloud Sequence

The exact 3D dynamics of the human body provides crucial evidence to analyze the consequences of the physical interaction between the body and the environment, which can eventually assist everyday activities in a wide range of applications. However, optimizing for 3D configurations from image observation requires a significant amount of computation, whereas real-world 3D measurements often suffer from noisy observation or complex occlusion. We resolve the challenge by learning a latent distribution representing strong temporal priors. We use a conditional variational autoencoder (CVAE) architecture with a transformer to train the motion priors with a large-scale motion dataset. Then our feature follower effectively aligns the feature spaces of noisy, partial observation with the necessary input for pre-trained motion priors, and quickly recovers a complete mesh sequence of motion. We demonstrate that the transformer-based autoencoder can collect necessary spatio-temporal correlations robust to various adversaries, such as missing temporal frames, or noisy observation under severe occlusion. Our framework is general and can be applied to recover the full 3D dynamics of other subjects with parametric representations.
The Revision of Schizosaccharomycetaceae

: Although the genus Hasegawaea was introduced along with the recognition of the genus Octosporomyces in the classification of fission yeasts, the two additional genera were neither accepted nor recognized. However, the genus Schizosaccharomyces sensu Kurtzman et Robnett was taxonomically heterogeneous-natured and corresponded to a higher-ranked taxon, i
Feature and Mechanism of the Foehn Weather on East Slope Taihang Mountains II:Case Analysis of the Effects of Lee Wave on Foehn Occurring and Moving

One typial case of foehn on the east slope of Taihang Mountains is simulated using ARW-WRF V3.3. The result shows that the formation and movement of the foehn is closely related to the lee wave.Based on the relation,a conceptual model of foehn formation on the east slope of Taihang Mountains is proposed.Lee waves develop on the east slope of Taihang Mountains while the northwestly or westly flow goes over the mountains,basins and plateau in the west of Taihang Mountains.The adiabatic heating is due to the decent component of lee waves and the compression warming effect on the lower atmosphere is caused by the downdraft,which lead to the foehn on the east slope of Taihang Mountains.Being one kind of gravity wave,lee waves can propagate downstream,which results in the foehn warming areas moving eastward with the downdraft propagating downstream at the same speed.Theoretical analysis shows that Scorer number decreases upward discontinuously,meaning that the atmosphere is stable and the obvious wind shear exists in the lower atmosphere,which is helpful to the formation of lee wave.
Obstructive Sleep Apnea Syndrome (OSAS): Impact of Continuous Positive Air Way Pressure (CPAP) in improving Quality of life

: are in need for different types of support the aim of this study to evaluate the impact of continuous positive air way pressure (CPAP) in improving Quality of life for patients with obstructive sleep apnea. Patient and Methods: Quiz experimental (before and after) research design was conducted at the Sleep center in Chest Department at Assiut University Hospital. Sample: A convenience sample of 100 adult patients from both sexes with OSA. Tools: a Patients' interviewing questionnaire sheet, Pulmonary function tests, the St. George’s Respiratory Questionnaire (SGRQ), Respiratory disturbed index (RDI) after full polysomnographic study, and designed nursing intervention protocol. Results: The study findings revealed that 52% were female, 44% of the studied patients were illiterate, read and write. Moreover, 88% of them were overweight and obese the BMI < 25, added to them about 28% of them were smoker. Majority of the studied patients had tired and fatigued & day time sleepiness. All of studied patients had moderate and severe OSA and not present any mild case. Conclusion: OSA patients before used CPAP machine had moderate level of air way limitation, severe OSA, fear from a wearing of CPAP mask, tired, fatigue & reduce of HRQL. After nursing intervention about important of continuous using of CPAP machine appear reduced feeling of fear from machine and from CPAP mask, reduced of tired, fatigue, sleepiness and increased number of normal sleeping hours, and improving of patients knowledge about CPAP machine and improved work of respiratory systems and health related quality of life
(2015). A hybrid TIM-NOMA scheme for the SISO Broadcast Channel. In 2015 ICC - 2015 IEEE International

—Future mobile communication networks will require enhanced network efﬁciency and reduced system overhead due to their user density and high data rate demanding applications of the mobile devices. Research on Blind Interference Alignment (BIA) and Topological Interference Management (TIM) has shown that optimal Degrees of Freedom (DoF) can be achieved, in the absence of Channel State Information (CSI) at the transmitters, reducing the network’s overhead. Moreover, the recently emerged Non-Orthogonal Multiple Access (NOMA) scheme suggests a different multiple access approach, compared to the current orthogonal methods employed in 4G networks, resulting in high capacity gains. Our contribution is a hybrid TIM-NOMA scheme in Single-Input-Single-Output (SISO) K - user cells, in which users are divided into T groups, and 1 /T DoF is achieved for each user. By superimposing users in the power domain, we introduce a two-stage decoding process, managing “inter-group” interference based on the TIM principles, and “intra-group” interference based on Successful Interference Cancellation (SIC), as proposed by NOMA. We show that for high SNR values the hybrid scheme can improve the sum rate by at least 100% when compared to Time Division Multiple Access (TDMA).
Advanced space surveillance with the imaging radar IoSiS

The Microwaves and Radar Institute of German Aerospace Center (DLR) has developed and constructed an experimental radar system called IoSiS (Imaging of Satellites in Space). The overall goal of that system is research on concepts for advanced acquisition of high-resolution radar images of objects in a low earth orbit (LEO). Compared to existing radar-based space surveillance systems, which has monostatic antenna configurations, in future IoSiS will use not one but more spatial distributed antennas in order to handle the upcoming amount of orbiting satellites and more important to realize bi-static imaging geometries. The latter allows the enhancement of the image information content compared to existing monostatic radar-based images of satellites. The paper outlines first the basic theory of radar-based satellite imaging using an inverse synthetic aperture radar (ISAR). Further a short description of the IoSiS system is addressed. The atmospheric effects on radar images are illustrated based on simulated imaging results and the advantages of a multi-channel system is introduced based on interferometric imaging results providing spatial resolution in three dimensions. A measurement result obtained by the IoSiS system of a real space object with spatial resolution in the centimeter region show the successively implemented error correction strategies.
An Automated System to Discover and Track Unknown Geosynchronous Objects Using Ground-based Optical Telescopes

In this paper, we present a fully automatic system to discover and track unknown objects in geosynchronous orbits (GSO) using an optical telescope. This study is motivated by occurrences where there is limited occupation time on a narrow field of view (FoV) telescope per night and the precise observation time is unknown due to how the telescope is operated. In the method proposed here, the system is initially tasked to survey a wide field of the sky with a fixed number of telescope observations per night. If any GSO object is discovered by the proposed unsupervised machine learning-based detector, the system will start to track the satellite and accordingly schedule future telescope observations. We use particle filters as the tracker which are designed for non-linear problems and will be used to estimate the object states with more sensible uncertainty representations. The system runs in a closed loop and maintains the track of the discovered target with as few telescope tasks as possible.
Foreground-Background Distribution Modeling Transformer for Visual Object Tracking

Visual object tracking is a fundamental research topic with a broad range of applications. Benefiting from the rapid development of Transformer, pure Transformer trackers have achieved great progress. However, the feature learning of these Transformer-based trackers is easily disturbed by complex backgrounds. To address the above limitations, we propose a novel foreground-background distribution modeling transformer for visual object tracking (F-BDMTrack), including a fore-background agent learning (FBAL) module and a distribution-aware attention (DA2) module in a unified transformer architecture. The proposed F-BDMTrack enjoys several merits. First, the proposed FBAL module can effectively mine fore-background information with designed fore-background agents. Second, the DA2 module can suppress the incorrect interaction between foreground and background by modeling fore-background distribution similarities. Finally, F-BDMTrack can extract discriminative features under ever-changing tracking scenarios for more accurate target state estimation. Extensive experiments show that our F-BDMTrack outperforms previous state-of-the-art trackers on eight tracking benchmarks.
ТА ІНЖЕНЕРІЯ

In this work, the field distribution in structures such as a gold grating, a graphene layer, and a silicon substrate was studied. The conditions for maximum electromagnetic field distribution (absorption) by this structure to use in photonics and electronics devices were established . The magnitude of the electromagnetic field of a gold diffraction grating with a graphene layer increases with decreasing slit width. At the same time, an increase in the period leads to small changes in the electromagnetic field distribution . The maximum value of the distribution of the electromagnetic field is increased significantly, almost twice reducing the thickness of the graphene layer .
Cs 598csc: Approximation Algorithms

Notes edited by instructor in 2011. We introduce the use linear programming (LP) in the design and analysis of approximation algorithms.The topics include Vertex Cover, Set Cover, randomized rounding, dual-fitting. It is assumed that the students have some background knowledge in basics of linear programming. 1 Vertex Cover via LP Let G = (V, E) be an undirected graph with arc weights w : V → R +. Recall the vertex cover problem from previous lecture. We can formulate it as an integer linear programming problem as follows. For each vertex v we have a variable x v. We interpret the variable as follows: if x v = 1 if v is chosen to be included in a vertex cover, otherwise x v = 0. With this interprtation we can easily see that the minimum weight vertex cover can be formulated as the following integer linear program.
JOURNAL OF WELLNESS

practice. Dispositional mindfulness levels were assessed using the Mindfulness Attention Awareness Scale (MAAS) before and after the thirty-day intervention. Results: Eighty-three students, residents, and fellows completed the 30-day program, including the baseline and follow-up measures. Overall levels of mindfulness significantly increased among medical students ( p < 0.001). Higher MAAS scores were associated with a longer duration of meditation (10-20 days: p = 0.046, >20 days: p = 0.006). MAAS scores also significantly increased in female participants ( p < 0.001). Conclusion: Our intervention demonstrates that a 30-day meditation program may aid in fostering dispositional mindfulness among medical students while potentially promoting better wellness outcomes amongst physician learners. ABSTRACT
Tree Species Inﬂuence Nitrate and Nitrous Oxide Production in Forested Riparian Soils

: Abundance of soil microbial nitrogen (N) cycling genes responsible for nitriﬁcation, denitri-ﬁcation, and nitrous oxide reduction may vary with tree species and N inputs, and these variables may be used to predict or mediate nitrate (NO 3 − ) and nitrous oxide (N 2 O) from soil. Nitriﬁcation and denitriﬁcation rates have also been linked to tree mycorrhizal associations, as soil beneath species associated with arbuscular mycorrhiza (AM) shows greater nitriﬁcation rates than species forming ectomycorrhizal (ECM) associations. In this study, we integrated N microbial functional gene abundance in the soil inﬂuenced by six tree species in two sub-catchments receiving either high or low N inputs. The soils beneath the two ECM-associated tree species and the four AM-associated tree species were analyzed for inorganic N content and potential N 2 O ﬂux and microbial gene abundance ( nirK and nosZ ) was quantiﬁed using qPCR techniques. Other parameters measured include soil pH, moisture, and organic matter. We determined that tree species inﬂuence NO 3 − and N 2 O production in riparian soils, particularly under high N enrichment. The soil beneath black cherry had the lowest pH, NO 3 − concentration, potential N 2 O production, and OM, though this result did not occur in the low N catchment. The strongest predictors of soil NO 3 − and N 2 O across the study sites were N enrichment and pH, respectively. These results provide a framework for species selection in managed riparian zones to minimize NO 3 − and N 2 O production and improve riparian function.
Bridging Constraint-based Sequential Pattern Mining and Machine Learning

In this tutorial, we focus on constraint-based sequential pattern mining and present a hands-on introduction to the open-source Seq2Pat : Sequence-to-Pattern generation library. Seq2Pat is designed to search for frequent patterns in large-scale sequence databases with a declarative modeling front-end to specify constraints on the desired properties of patterns. Beyond traditional pattern mining, the particular focus of this tutorial is to bridge pattern mining and machine learning to utilize patterns found in training predictive models. We show how Seq2Pat can serve as an integrator technology between raw sequential data and learning tasks. This is demonstrated on real-world applications from digital behavior analysis for intent prediction and intruder detection.
Structural controls on hydrothermal flow in a segmented rift system, Taupo Volcanic Zone, New Zealand

Vigorous hydrothermal convection transfers 10 times the average continental heat ﬂow through the central Taupo Volcanic Zone (TVZ), a region of active extension (approximately 8 mm year ) 1 ) and productive rhyolitic volcanism. Over 20 high-temperature (>250 (cid:1) C) geothermal ﬁelds occur within Quaternary pyroclastic basins, with convective circulation to depths of 7–8 km presumably extending through basement rocks. Parallel-striking normal faults, fractures and dikes dissect the convective regime, interacting with ﬂuids to either enhance or restrict ﬂow according to the relative permeability of structure and host rock. In the basement, high bulk permeability is maintained by focussed ﬂow through faults and associated fractures well oriented for reactivation in the prevailing stress ﬁeld. In contrast, distributed ﬂow through fault-bounded compartments prevails within Quaternary basins, masking any signal of deeper structural control. Exceptions occur where more competent rocks are exposed at the surface. As in narrow magmatic rifts elsewhere, the extensional fabric is partitioned into discrete rift segments linked along strike by accommodation zones. Eighty per cent of TVZ geothermal ﬁelds correlate spatially with rift architecture, with 60% located in accommodation zones. We suggest that segmented rift fabrics generate bulk permeability anisotropy that is to some extent predictable, with rift segments characterized by enhanced axial ﬂow, and accommodation zones characterized by locally enhanced vertical permeability that is tectonically maintained. This provides a plausible explanation for the common occurrence of geothermal ﬁelds within accommodation zones and their notable absence within densely faulted rift segments. Maintenance of structural permeability in zones of active hydrothermal precipitation necessarily requires repeated brittle failure. Geothermal plumes therefore exploit tectonically maintained permeability within accommodation zones, with rift segments functioning mostly as drawdown regions. The inﬂuence of rift architecture on ﬂow paths has important implications for geothermal extraction and epithermal mineral exploration within the TVZ and other structurally segmented hydrothermal systems, both active and extinct.
PAPR reduction in CP-OFDM (5G) using hybrid technique

The Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) is a 5G multicarrier waveform that offers great data speeds and improvements in spectrum utilisation. The primary CP-OFDM’s weakness is its excessive peak-to-average power ratio (PAPR), which is a characteristic of all multicarrier modulation techniques. We study the application of a hybrid technique approach how to lower the peak to average power ratio (PAPR) in a CP-OFDM system. We also evaluated the outcomes of peak to average power ratio (PAPR) decrease in CP-OFDM, utilising a hybrid technique with Group Codeword Shift (GCS), Median Codeword Shift, Selective Codeword Shift (SCS), and Conventional CP-OFDM. When compared to the non-hybrid technique, the simulation results indicate that the hybrid approach is superior in reducing the peak PAPR by more than 65 percent.
Tectonic boundary between the Sanbagawa belt and the Shimanto belt in central Shikoku, Japan

In order to make it clear the mode of occurrence of the Sanbagawa belt, we carried out in situ U-Pb isotope analyses of igneous zircon grains from the Oboke area that was a type area of the Sanbagawa belt in central Shikoku, Japan. Analyzed igneous zircons were separated from psammitic schist in the Minawa and Kawaguchi Formations and from igneous cobbles in the Koboke Formation. Spot analyses were performed on the laser ablation-inductively coupled plasma mass spectrometer (LA-ICP-MS). The youngest U-Pb ages of zircon grains from the Koboke Formation and the Kawaguchi Formation showed 92±4 Ma and 82±11 Ma, respectively. On the other hand, zircons from the Minawa Formation yielded remarkably older ages clustered around 1900-1800 Ma. There is a large chronological gap between protolith sedimentary clasts of the Minawa and those of the other two formations. The protolith sedimentary ages of the Sanbagawa belt have been well constrained as older than 130 Ma based on fossil and U-Pb isotopic ages. The peak metamorphism occurred in 120-110 Ma. Therefore, both Koboke and Kawaguchi Formations must not belong to the Sanbagawa belt, because the timing of formation of accretionary complex must be later than 92±4 Ma for the Koboke Formation and 82±11 Ma for the Kawaguchi Formation. Both the Koboke and Kawaguchi Formations correspond to the late Cretaceous accretionary complex, and they are equivalent to the Northern Shimanto belt. The tectonic boundary between the Sanbagawa and the Northern Shimanto belts is reverse fault and the Northern Shimanto belt appears as a tectonic window in the Sanbagawa belt, central Shikoku. The whole package of the Sanbagawa and underlying Shimanto belts are deformed by the secondary fault movement and doming after the tectonic juxtaposition at the mid-crustal levels.
Development and Evaluation of Polyherbal Formulation with Carminative Effect

Carminative drugs, which reduce or prevent gastrointestinal flatulence and colic and have historically been used to enhance human health, is examined in this study. The carminative qualities of spices like clove, coriander, cardamom, fennel, nutmeg, black pepper, and ajowan are highlighted in particular. Numerous health benefits, including anti-inflammatory, antiseptic, anti-hypertensive, and myorelaxant qualities, are demonstrated by these spices. To enhance their effects, formulations were made utilizing a geometrical approach and different weights of these powders were combined and evaluated. To confirm the quality and safety of the carminative powder, organoleptic evaluation, physicochemical characteristics, rheological evaluation, and carminative potential were evaluated. The carminative powder, had a pH of 6.5, is free-flowing, non-sticky, and aesthetically pleasing, according to the results. Given the rising popularity of natural treatments and holistic healthcare, the future of carminative herbal medications is bright. Due to their digestive advantages, many herbs and mixtures have grown in popularity, and this pattern is predicted to continue. New carminative herbs and novel formulations may be found as a result of research and development in herbal medicine in the upcoming years. The market for carminative herbal medicines is projected to grow as consumer interest in plant-based treatments for digestive problems rises.