Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of diabetes across the course of disease: minimizing obesity-associated complications

: Obesity increases the risk for developing type 2 diabetes mellitus (T2DM) and this in turn correlates with an elevated probability of long-term diabetes complications once diabetes is established. Interventions aimed at lowering weight via changes in diet and lifestyle have repeatedly been shown to improve glycemic control in patients with T2DM and even to reverse early disease. Weight gain, a potential side effect of treatment for patients with T2DM, is also an important concern, and it has been noted that weight increases associated with antidiabetes therapy may blunt cardiovascular risk reductions achieved by decreasing blood glucose. Among older agents, metformin and acarbose have the lowest risk for weight gain, while sulfonylureas, meglitinides, and thiazolidinediones are all associated with weight increases. Clinical trial results have also consistently demonstrated that treatment with glucagon-like peptide-1 receptor agonists and amylin lowers weight, and that dipeptidyl peptidase-4 inhibitors are weight neutral in patients with T2DM. Conventional human insulin formulations are known to increase weight in patients with T2DM. However, some insulin analogs, particularly insulin detemir, have lower liability for this adverse event. The use of both pharmacologic and surgical therapies aimed at treating obesity rather than lowering blood glucose have the potential to improve glycemic control and even resolve T2DM in some patients
Traffic state estimation from partial Bluetooth and volume observations: case study in the Brisbane metropolitan area

The application of the Bluetooth (BT) technology to transportation has been enabling researchers to make accurate travel time observations, in freeway and arterial roads. The Bluetooth traffic data are generally incomplete, for they only relate to those vehicles that are equipped with Bluetooth devices, and that are detected by the Bluetooth sensors of the road network. The fraction of detected vehicles versus the total number of transiting vehicles is often referred to as Bluetooth Penetration Rate (BTPR). The aim of this study is to precisely define the spatio-temporal relationship between the quantities that become available through the partial, noisy BT observations; and the hidden variables that describe the actual dynamics of vehicular traffic. To do so, we propose to incorporate a multi- class traffic model into a Sequential Montecarlo Estimation algorithm. Our framework has been applied for the empirical travel time investigations into the Brisbane Metropolitan region.
Sorting out cholesterol metabolism

Purpose of review Long-term exposure to elevated concentrations of low-density lipoprotein (LDL) cholesterol increases the risk of cardiovascular events. The main player in clearing LDL cholesterol is the LDL receptor (LDLR) trafficking pathway, however, our fundamental knowledge about the mechanisms regulating this pathway is still incomplete. Recent findings The LDLR pathway is very complex and involves multiple proteins. Endocytosis is regulated by two different adaptor proteins, i.e. autosomal recessive hypercholesterolemia (ARH) and disabled-2 (Dab2). The proteolysis of LDLR is regulated by inducible degrader of the LDL receptor (IDOL) and proprotein convertase subtilisin/kexin type 9 (PSCK9). However, only a few proteins have been identified that provide insights into endosomal sorting and recycling of LDLR. a individuals the it is to learn more about the LDLR trafficking pathway, as we still lack a full mechanistic understanding of how LDLR trafficking is controlled. change in the endosomes, which leads to directing the receptor to the lysosomes for degradation. In contrast to PCSK9, IDOL targets LDLR that is present in lipid rafts. IDOL binds LDLR intracellularly and ubiquitinates the receptor, as well as itself. Internalization is promoted by Epsin, after which LDLR is transported to the lysosomes by ESCRT via the multivesicular body pathway. autosomal recessive hypercholesterolemia;
Design considerations of a wearable electronic-skin for mental health and wellness: balancing biosignals and human factors

Chronic stress has been associated with a variety of pathophysiological risks including developing mental illness. Conversely, appropriate stress management, can be used to foster mental wellness proactively. Yet, there is no existing method that accurately and objectively monitors stress. With recent advances in electronic-skin (e-skin) and wearable technologies, it is possible to design devices that continuously measure physiological parameters linked to chronic stress and other mental health and wellness conditions. However, the design approach should be diﬀerent from conventional wearables due to considerations like signal-to-noise ratio and the risk of stigmatization. Here, we present a multi-part study that combines user-centered design with engineering-centered data collection to inform future design eﬀorts. To assess human factors, we conducted an n =24 participant design probe study that examined perceptions of an e-skin for mental health and wellness as well as preferred wear locations. We complement this with an n =10 and n =16 participant data collection study to measure physiological signals at several potential wear loca-30 tions. By balancing human factors and biosignals, we conclude that the upper arm and forearm are optimal wear locations.
Gaia Data Release 3. Apsis II: Stellar parameters

The third Gaia data release contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the Gaia prism spectra (BP and RP) and the spectrograph (RVS). This data release opens a new window on the chemo-dynamical properties of stars in our Galaxy, essential knowledge for understanding the structure, formation, and evolution of the Milky Way. To provide insight into the physical properties of Milky Way stars, we used these data to produce a uniformly-derived, all-sky catalog of stellar astrophysical parameters (APs): Teff, logg, [M/H], [$\alpha$/Fe], activity index, emission lines, rotation, 13 chemical abundance estimates, radius, age, mass, bolometric luminosity, distance, and dust extinction. We developed the Apsis pipeline to infer APs of Gaia objects by analyzing their astrometry, photometry, BP/RP, and RVS spectra. We validate our results against other literature works, including benchmark stars, interferometry, and asteroseismology. Here we assessed the stellar analysis performance from Apsis statistically. We describe the quantities we obtained, including our results' underlying assumptions and limitations. We provide guidance and identify regimes in which our parameters should and should not be used. Despite some limitations, this is the most extensive catalog of uniformly-inferred stellar parameters to date. These comprise Teff, logg, and [M/H] (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (5 million), diffuse interstellar band analysis (1/2 million), activity indices (2 million), H{$\alpha$} equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). More precise and detailed astrophysical parameters based on epoch BP, RP, and RVS are planned for the next Gaia data release.
Jurnal Penelitian Sains

: Accurate and consistent basis weight of a paper or pulp product is essential to ensure the quality of the product. This study aims to measure basis weight using radiation and analyze the influences that affect the measurement results. This study was conducted for three months at PT Tanjungenim Lestari using the comparative causal method. Data taken in the form of measurements using Strontium-90 ( β ) radiation and data calculated manually by the laboratory. The results showed that the two data obtained, there were differences in the results of measuring the basis weight. The difference between the actual measurement results and the laboratory data is caused by the radiation received by the detector which is random, so that the particles coming out of the core do not necessarily enter the detector entirely. In addition, differences in the measurement process also affect the size results, where in the actual data, the basis weight is measured using the ABB Scanner NP-1200 instrument.
Oracle-Based Local Search for Pseudo-Boolean Optimization

Significant advances have been recently made in the development of increasingly effective in-exact (or incomplete) search algorithms—particularly geared towards finding good though not provably optimal solutions fast—for the constraint optimization paradigm of maximum satisfiability (MaxSAT). One of the most successful recent approaches is a new type of stochastic local search in which a Boolean satisfiability (SAT) solver is used as a decision oracle for moving from a solution to another. In this work, we strive for extending the success of the approach to the more general realm of pseudo-Boolean optimization (PBO), where constraints are expressed as linear inequalities over binary variables. As a basis for the approach, we make use of recent advances in practical approaches to satisfiability checking pseudo-Boolean constraints. We outline various heuristics within the oracle-based approach to anytime PBO solving, and show that the approach compares in practice favorably both to a recently-proposed local search approach for PBO that is in comparison a more traditional instantiation of the stochastic local search paradigm as well as a recent exact PBO approach when used as an anytime solver.
Lectures on modern convex optimization - analysis, algorithms, and engineering applications

This is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.
Halting misconceived?

The halting problem is considered to be an essential part of the theoretical background to computing. That halting is not in general computable has been (cid:16)proved(cid:17) in many text books and taught on many computer science courses, and is supposed to illustrate the limits of computation. However, there is a dissenting view that these proofs are misconceived. In this paper we look at what is perhaps the simplest such proof, based on a program that interrogates its own halting behaviour and then decides to thwart it. This leads to a contradiction that is generally held to show that a halting function cannot be implemented. The dissenting view agrees with the conclusion that the halting function, as described, cannot be implemented, but suggests that this is because its speci(cid:28)cation is inconsistent. Our paper uses Forth to illustrate complex abstract arguments.
Evaluating Adversarial Robustness of Low dose CT Recovery

Low dose computed tomography (CT) acquisition using reduced radiation or sparse angle measurements is recommended to decrease the harmful effects of X-ray radiation. Recent works successfully apply deep networks to the problem of low dose CT recovery on bench-mark datasets. However, their robustness needs a thorough evaluation before use in clinical settings. In this work, we evaluate the robustness of different deep learning approaches and classical methods for CT recovery. We show that deep networks, including model-based networks encouraging data consistency, are more susceptible to untargeted attacks. Surprisingly, we observe that data consistency is not heavily affected even for these poor quality reconstructions, motivating the need for better regularization for the networks. We demonstrate the feasibility of universal attacks and study attack transferability across different methods. We analyze robustness to attacks causing localized changes in clinically relevant regions. Both classical approaches and deep networks are affected by such attacks leading to changes in the visual appearance of localized lesions, for extremely small perturbations. As the resulting reconstructions have high data consistency with the original measurements, these localized attacks can be used to explore the solution space of the CT recovery problem.
Using Photographs to Enhance Videos of a Static Scene

We present a framework for automatically enhancing videos of a static scene using a few photographs of the same scene. For example, our system can transfer photographic qualities such as high resolution, high dynamic range and better lighting from the photographs to the video. Additionally, the user can quickly modify the video by editing only a few still images of the scene. Finally, our system allows a user to remove unwanted objects and camera shake from the video. These capabilities are enabled by two technical contributions presented in this paper. First, we make several improvements to a state-of-the-art multiview stereo algorithm in order to compute view-dependent depths using video, photographs, and structure-from-motion data. Second, we present a novel image-based rendering algorithm that can re-render the input video using the appearance of the photographs while preserving certain temporal dynamics such as specularities and dynamic scene lighting.
Innocent Strategies as Presheaves and Interactive Equivalences for CCS 1

Seeking a general framework for reasoning about and comparing programming languages, we derive a new view of Milner’s CCS [34]. We construct a category E of plays, and a subcategory V of views. We argue that presheaves on V adequately represent innocent strategies, in the sense of game semantics [20]. We equip innocent strategies with a simple notion of interaction. We then prove decomposition results for innocent strategies, and, restricting to presheaves of finite ordinals, prove that innocent strategies are a final coalgebra for a polynomial functor [27] derived from the game. This leads to a translation of CCS with recursive equations. Finally, we propose a notion of interactive equivalence for innocent strategies, which is close in spirit to Beffara’s interpretation [1] of testing equivalences [7] in concurrency theory. In this framework, we consider analogues of fair testing and must testing. We show that must testing is strictly finer in our model than in CCS, since it avoids what we call ‘spatial unfairness’. Still, it differs from fair testing, and we show that it coincides with a relaxed form of fair testing.
Optimal Arms Identification with Knapsacks

Best Arm Identification (BAI) is a general online pure exploration framework to identify optimal decisions among candidates via sequential interactions. We pioneer the Optimal Arms identification with Knapsacks (OAK) problem, which extends the BAI setting to model the resource consumption. We present a novel OAK algorithm and prove the upper bound of our algorithm by exploring the relationship between selecting optimal actions and the structure of the feasible region. Our analysis introduces a new complexity measure, which builds a bridge between the OAK setting and bandits with knapsacks problem. We establish the instance-dependent lower bound for the OAK problem based on the new complexity measure. Our results show that the proposed algo-rithm achieves a near-optimal probability bound for the OAK problem. In addition, we demonstrate that our algorithm recovers or improves the state-of-the-art upper bounds for several special cases, including the simple OAK setting and some classical pure exploration problems.
Mobile Transport and Computing Platform for 5G Verticals: Resource Abstraction and Implementation

The 5G-TRANSFORMER project aims at transforming today’s mobile transport networks into an SDN/NFV-based platform, which offers slices tailored to the needs of vertical industries. The paper describes the 5G-TRANSFORMER resource management layer, namely MTP, and its main functionalities such as resource abstraction, resource information modeling and orchestration, and service instantiation. Then, it focuses on the ETSI-based interfaces exploited for the interaction between the control and management plane elements. Finally, the paper reports an MTP implementation including messages reporting resource abstraction.
Clinical Aspects of Neuroimmunology

As known, adventure and experience about lesson, entertainment, and knowledge can be gained by only reading a book. Even it is not directly done, you can know more about this life, about the world. We offer you this proper and easy way to gain those all. We offer many book collections from fictions to science at all. One of them is this clinical aspects of neuroimmunology that can be your partner.
Dynamic Risk Management: Investment, Capital Structure, and Hedging

This paper develops a dynamic model to determine a firm’s optimal risk management strategy when it faces uncertainty about its future profitability and investment opportunities. To address the complexity that results from a realistic description of the firm’s environment, this article combines numerical methods and sensitivity analysis to study the optimal policies implied by the model. The interactions between financing, hedging, and investment decisions, as well as the effects of the firm’s business environment on these interactions are analyzed.
Comparison of Percutaneous Nephrolithotomy Success Rate and Complications in Patients with a History of Different Therapeutic Interventions for Kidney Stone

Background: Percutaneous nephrolithotomy (PCNL) is one of the five interventions offered to patients with renal stones. Objectives: This study compared the effects of previous therapeutic interventions for renal stones on subsequent PCNL regarding success rate and complications. Methods: In this descriptive-analytical study, the data from 375 patients who had undergone PCNL were reviewed retrospectively. Patients were categorized into four groups based on their previous therapeutic interventions as no history of open renal stone surgery (n = 196), PCNL (n = 64), extracorporeal shockwave lithotripsy (ESWL) (n = 88), and open surgery (n = 27). We compared surgery duration, the surgical procedure's success rate, complications, as well as the site and size of the stone between the groups. Results: The mean operation duration was significantly longer in the fourth group (61.66 ± 19.85), while there were no statistically significant differences in surgery duration between other groups (P = 0.88). The mean hospital stay, stone size, and site were also similar between the groups. All groups had a high number of pelvic stones, and the rate of upper calyceal stones was higher than middle calyceal and ureteral stones in all groups. Access time was higher in groups one and four, but no significant difference was observed (P = 0.31). Grade 1 and 2 complications were frequent among the patients. The overall immediate success rate was high in all groups. Conclusions: The present study indicates that patients with a history of open surgery for kidney-related conditions may have higher blood loss and longer surgery duration, likely due to anatomical and histological changes in the kidney.
Vanda Studio – Instructive, Rapid Experiment Development

Statistical machine translation research routinely involves conducting experiments on a computer. Designing and running those experiments is tedious, because many different programs have to be operated in concert, and the threshold for novices is high. This paper reports on Vanda Studio, an integrated development environment that allows for rapid incremental design of small-scale experiments, both for teaching and prototyping.
Non-steady-state stomatal conductance modeling and its implications: from leaf to ecosystem

Abstract. Accurate and efficient modeling of stomatal conductance (gs) has been a key challenge in vegetation models across scales. Current practice of most land surface models (LSMs) assumes steady-state gs and predicts stomatal responses to environmental cues as immediate jumps between stationary regimes. However, the response of stomata can be orders of magnitude slower than that of photosynthesis and often cannot reach a steady state before the next model time step, even on half-hourly timescales. Here, we implemented a simple dynamic gs model in the vegetation module of an LSM developed within the Climate Modeling Alliance and investigated the potential biases caused by the steady-state assumption from leaf to canopy scales. In comparison with steady-state models, the dynamic model better predicted the coupled temporal response of photosynthesis and stomatal conductance to changes in light intensity using leaf measurements. In ecosystem flux simulations, while the impact of gs hysteresis response may not be substantial in terms of monthly integrated fluxes, our results highlight the importance of considering this effect when quantifying fluxes in the mornings and evenings, as well as interpreting diurnal hysteresis patterns observed in ecosystem fluxes. Simulations also indicate that the biases in the integrated fluxes are more significant when stomata exhibit different speeds for opening and closure. Furthermore, prognostic modeling can bypass the A-Ci iterations required for steady-state simulations and can be robustly run with comparable computational costs. Overall, our study demonstrates the implications of dynamic gs modeling for improving the accuracy and efficiency of LSMs and for advancing our understanding of plant–environment interactions.
Progress Report Title: Determining uptake of nitrate vs ammonium nitrogen in blueberry

Name, Mailing and Email Address of Principal Investigator(s): Principal Investigator: Anish Malladi 1121 Miller Plant Sciences, Department of Horticulture, University of Georgia, Athens, GA 30602 Email: malladi@uga.edu; Phone: 706-542-0783 Co-Principal Investigator: Miguel Cabrera Department of Crop and Soil Sciences, University of Georgia, Athens, GA 30602 Email: mcabrera@uga.edu; Phone: 706-542-1242