Miracle-dz/UniFAR-FTUs huggingface dataset:
A Digital Lifestyle Coach (E-Supporter 1.0) to Support People With Type 2 Diabetes: Participatory Development Study

Background A healthy lifestyle, including regular physical activity and a healthy diet, is becoming increasingly important in the treatment of chronic diseases. eHealth interventions that incorporate behavior change techniques (BCTs) and dynamic tailoring strategies could effectively support a healthy lifestyle. E-Supporter 1.0 is an eCoach designed to support physical activity and a healthy diet in people with type 2 diabetes (T2D). Objective This paper aimed to describe the systematic development of E-Supporter 1.0. Methods Our systematic design process consisted of 3 phases. The definition phase included the selection of the target group and formulation of intervention objectives, and the identification of behavioral determinants based on which BCTs were selected to apply in the intervention. In the development phase, intervention content was developed by specifying tailoring variables, intervention options, and decision rules. In the last phase, E-Supporter 1.0 integrated in the Diameter app was evaluated using a usability test in 9 people with T2D to assess intervention usage and acceptability. Results The main intervention objectives were to stimulate light to moderate-vigorous physical activities or adherence to the Dutch dietary guidelines in people with T2D. The selection of behavioral determinants was informed by the health action process approach and theories explaining behavior maintenance. BCTs were included to address relevant behavioral determinants (eg, action control, self-efficacy, and coping planning). Development of the intervention resulted in 3 types of intervention options, consisting of motivational messages, behavioral feedback, and tailor-made supportive exercises. On the basis of IF-THEN rules, intervention options could be tailored to, among others, type of behavioral goal and (barriers to) goal achievement. Data on these variables could be collected using app data, activity tracker data, and daily ecological momentary assessments. Usability testing revealed that user experiences were predominantly positive, despite some problems in the fixed delivery of content. Conclusions The systematic development approach resulted in a theory-based and dynamically tailored eCoach. Future work should focus on expanding intervention content to other chronic diseases and lifestyle behaviors, enhancing the degree of tailoring and evaluating intervention effects on acceptability, use, and cost-effectiveness.
Fluorescence lifetime-based assay reports structural changes in cardiac muscle mediated by effectors of contractile regulation

Dvornikov et al. test a new high-throughput fluorescence lifetime-based assay using a human cardiac troponin C probe in cardiac myofibrils. The assay sensitivity and precision allow for the detection of key structural changes in cTnC that reports changes in thick and filament proteins in health and disease, which promises to have utility in screening therapeutic compounds that target these proteins.
Dopamine Receptor Supports the Potentiation of Intrinsic Excitability and Synaptic LTD in Temporoammonic-CA1 Synapse

Dopaminergic projection to the hippocampus from the ventral tegmental area or locus ceruleus has been considered to play an essential role in the acquisition of novel information. Hence, the dopaminergic modulation of synaptic plasticity in the hippocampus has been widely studied. We examined how the D1 and D2 receptors influenced the mGluR5-mediated synaptic plasticity of the temporoammonic-CA1 synapses and showed that the dopaminergic modulation of the temporoammonic-CA1 synapses was expressed in various ways. Our findings suggest that the dopaminergic system in the hippocampal CA1 region regulates the long-term synaptic plasticity and processing of the novel information.
An Improved MIP Formulation for Products of Discrete and Continuous Variables

Abstract This note provides a new way of formulating common nonlinear conditions which can be expressed as products of discrete and continuous variables. Our formulation provides a continuous relaxation that can’t be tightened, and uses one less constraint and one less variable for each product than the standard formulation (reducing the total nunber of constraints by half and the total number of variables by a third).
Thioredoxin reductase 1 regulates hepatic inflammation and macrophage activation during acute cholestatic liver injury

Background and Aims: Cholestatic liver diseases, including primary sclerosing cholangitis, are characterized by periportal inflammation with progression to hepatic fibrosis and ultimately cirrhosis. We recently reported that the thioredoxin antioxidant response is dysregulated during primary sclerosing cholangitis. The objective of this study was to examine the impact of genetic and pharmacological targeting of thioredoxin reductase 1 (TrxR1) on hepatic inflammation and liver injury during acute cholestatic injury. Approach and Results: Primary mouse hepatocytes and intrahepatic macrophages were isolated from 3-day bile duct ligated (BDL) mice and controls. Using wildtype and mice with a liver-specific deletion of TrxR1 (TrxR1LKO), we analyzed the effect of inhibition or ablation of TrxR1 signaling on liver injury and inflammation. Immunohistochemical analysis of livers from BDL mice and human cholestatic patients revealed increased TrxR1 staining in periportal macrophages and hepatocytes surrounding fibrosis. qPCR analysis of primary hepatocytes and intrahepatic macrophages revealed increased TrxR1 mRNA expression following BDL. Compared with sham controls, BDL mice exhibited increased inflammation, necrosis, and increased mRNA expression of pro-inflammatory cytokines, fibrogenesis, the NLRP3 inflammatory complex, and increased activation of NFkB, all of which were ameliorated in TrxR1LKO mice. Importantly, following BDL, TrxR1LKO induced periportal hepatocyte expression of Nrf2-dependent antioxidant proteins and increased mRNA expression of basolateral bile acid transporters with reduced expression of bile acid synthesis genes. In the acute BDL model, the TrxR1 inhibitor auranofin (10 mg/kg/1 d preincubation, 3 d BDL) ameliorated BDL-dependent increases in Nlrp3, GsdmD, Il1β, and TNFα mRNA expression despite increasing serum alanine aminotransferase, aspartate aminotransferase, bile acids, and bilirubin. Conclusions: These data implicate TrxR1-signaling as an important regulator of inflammation and bile acid homeostasis in cholestatic liver injury.
Exercise induced myelin protein zero improvement in neuropathic pain rats

Abstract Purpose Aerobic exercise including swimming plays a suitable role in improving somatosensory injuries. Neuropathic pain is a debilitating condition that occurs following injury or diseases of somatosensory system. In the present study, we tried to investigate the effect of exercise on myelin protein zero of sciatic nerve injured rats. Materials and methods Forty male rats (180–220 g) were divided into five groups (intact, sham, sham + exercise, neuropathy, and neuropathy + exercise). Right Sciatic nerve of anesthetized rats was exposed and loosely ligated (four ligations with 1 mm apart) using catgut chromic sutures to induce neuropathy. After 3 days of recovery, swimming exercise began (20 min/day/5 days a week/4 weeks). Mechanical allodynia and thermal hyperalgesia were detected using Von Frey filaments and plantar test, respectively. Sciatic nerve at the place of injury was dissected out to measure the myelin protein zero by western blot analysis. In the intact and sham groups, sciatic nerve removed at the place similar to injured group. Results We found that neuropathy significantly (p < 0.05) reduced paw withdrawal mechanical and thermal thresholds and swimming exercise significantly (p < 0.05) increased paw withdrawal mechanical and thermal thresholds compared to the neuropathy group. Moreover, we found that MPZ level significantly (p < 0.01) decreased in neuropathy group against that in sham group, and exercise prominently (p < 0.05) reversed MPZ level towards control level. Conclusions Swimming exercise improves myelin protein zero level in neuropathic rats along with attenuating neuropathic pain. This is a promising approach in improving neuropathological disorders including Charcot-Marie-Tooth and Dejerine–Sottas disease.
Construction a novel detection method for Trichomonas vaginalis based on recombinant enzyme polymerase amplification targeting the Actin gene

Trichomoniasis is a common and curable sexually transmitted disease worldwide. The rapid, convenient, and accurate diagnosis of trichomoniasis is an important link in the prevention and treatment of the disease. The current detection methods of Trichomonas vaginalis are mainly wet mount microscopy, culture, nested PCR, and loop‐mediated isothermal amplification. However, these detection methods have some shortcomings. In this study, a recombinant enzyme polymerase amplification (RPA) assay had been conducted to detect T. vaginalis. The target gene and the corresponding primers were screened, and the reaction system and conditions were optimized in the assay of RPA. The sensitivity and specificity of this detection method were analyzed. The detection efficiency of wet mount microscopy, culture, nested PCR, and RPA was compared by testing 53 clinical samples from vaginal secretions. By screening, the actin gene of T. vaginalis could be used as a target gene for RPA detection of T. vaginalis, and the optimum reaction condition to amplify the actin gene by RPA was at 39°C for 30 min. The detection limit of T. vaginalis DNA using RPA was 1 pg, corresponding to a sensitivity of approximately five trophozoites. The RPA assay demonstrated high specificity for T. vaginalis, and there was no cross‐reactivity with Giardia lamblia, Escherichia coli, Lactobacillus, Toxoplasma gondii, Staphylococcus aureus, and Candida albicans. Of the 53 clinical samples, the positive rates of T. vaginalis detected by wet mount microscopy, culture, nested PCR and RPA were 50.9 4% (27/53), 71.7% (38/53), 71.7% (38/53), and 69.81% (37/53), respectively. Compared with culture which was used as the gold standard for diagnosing trichomoniasis, testing clinical samples by wet mount microscopy showed 71.05% sensitivity, 100% specificity, and moderate diagnostic agreement with the culture (K = 0.581, Z = 4.661, p < 0.001). The nested PCR showed 100% sensitivity, 100% specificity, and excellent diagnostic agreement (K = 1, Z = 7.28, p < 0.001), while RPA displayed 97.37% sensitivity, 100% specificity, and excellent diagnostic agreement (K = 0.954, Z = 6.956, p < 0.001). At the present study, rapid amplification of actin gene by RPA could be used as a tool for detection of T. vaginalis. The detection method of RPA was more sensitive than wet mount microscopy and displayed excellent specificity. Moreover, RPA amplification of actin gene did not require a PCR instrument and the amplification time was shorter than that of ordinary PCR. Therefore, the RPA assay was proposed in this study as a point‐of‐care examination and a diagnostic method of T. vaginalis infection, which exhibited the potential value in the treatment and prevention of trichomoniasis.
New unorthodox semiconductor devices

A distinctive feature in the development of solid-state electronic devices has been the long time interval that has usually elapsed between the initial conception of the device, and its experimental realisation. The technology bottleneck which gives rise to this phenomenon has recently been significantly widened by the emergence of several new technologies which are enabling the realisation of device structures which, although not entirely new in concept, are receiving a revived interest because they are now technologically feasible. The author discusses a range of new device structures, many of which fall into the above category, and the ways in which new advances in technology have made them realistic contenders for many device applications. In addition a number of structures which rely upon entirely new phenomena are presented, with experimental demonstration considerably enhanced, and in some cases only made possible by the emergence of ion-implantation and molecular beam epitaxy.
Estimation of Over-parameterized Models from an Auto-Modeling Perspective

From a model-building perspective, in this paper we propose a paradigm shift for fitting over-parameterized models. Philosophically, the mindset is to fit models to future observations rather than the observed sample. Technically, choosing an imputation model for generating future observations, we fit over-parameterized models to future observations via optimizing an approximation to the desired expected loss function based on its sample counterpart and what we call an adaptive \it {dual function}. This technique is discussed in detail for both creating bootstrap imputation and final estimation with bootstrap imputation. The method is illustrated with the many-normal-means problem, $n<p$ linear regression, and deep convolutional neural networks for image classification of MNIST digits. The numerical results demonstrate superior performance across these three different types of applications. For example, For the many-normal-means problem, our method uniformly dominates James-Stein and Efron's $g-$modeling, and for the MNIST image classification, it shows state-of-the-art performance in common model structures. While this paper is largely expository because of the ambitious task of taking a look at over-parameterized models from a new perspective, fundamental theoretical properties are also investigated. We conclude the paper with a few remarks.
Nonlinear parabolic differential equations and inequalities

The paper starts with a short review on the history of PDEs and their related inequalities. We present a unified approach to the basic parabolic differential inequalities. It starts in Section 2 with the famous Lemma of Nagumo and leads to recent and new result on parabolic equations with singular nonlinear elliptic operators (7) that include the p-Laplacian and the operator of capillary surfaces. Sections 3 and 4 deal with the one-dimensional case and radial solutions. A Semi-Strong Minimum Principle is found in Section 6.
Influence of the Agulhas Current on Summer Rainfall along the Southeast Coast of South Africa

Abstract Summer rainfall on the southeast coast of Africa is shown to be influenced by the proximity and temperature of the adjacent warm Agulhas Current. Student's t-test correlations between coastal rainfall and local sea surface temperature (r = +0.88), shelf width (r = −0.92), and offshore distance to the thermal core (r = −0.73) all exceed significance at the 99% confidence limit. Summer rainfall patterns indicate the existence of a large-scale gradient from northeast to southwest, in the same direction as that of the SST. Alongshore variations in the rainfall gradient appear related to the distance between the coast and the warm current at the shelf edge, and to orographic effects. It is thought that a quasi-stationary mesoscale circulation system over the Agulhas Current interests with transient weather systems to produce alongshore changes in the rainfall gradient. Additionally, the modification of onshore moving air by surface heat fluxes gives rise to the close relationships between summer rainf.
Heat and mass transfer in the boundary layers on an exponentially stretching continuous surface

The similarity solutions describing the steady plane (flow and thermal) boundary layers on an exponentially stretching continuous surface with an exponential temperature distribution are examined both analytically and numerically. The mass- and heat-transfer characteristics of these boundary layers are described and compared with the results of earlier authors, obtained under the more familiar power-law boundary conditions.
An algebraic construction of sonar sequences using M -sequences

An algebraic construction of sonar sequences that is based on the properties of q-ary M -sequences for q a prime power is presented. Sonar sequences give two-dimensional synchronization patterns that have two-dimensional spatial aperiodic autocorrelation functions with minimum out-of-phase values. The best sonar sequences with length $q^m \leqq 128$ that are obtained from the construction are tabulated. Based on a comparison with the limited number of known optimal values, the construction performs quite well, producing optimal sonar sequences in the majority of applicable cases.
Optirank: classification for RNA-Seq data with optimal ranking reference genes

Classification algorithms using RNA-Sequencing (RNA-Seq) data as input are used in a variety of biological applications. By nature, RNA-Seq data is subject to uncontrolled fluctuations both within and especially across datasets, which presents a major difficulty for a trained classifier to generalize to an external dataset. Replacing raw gene counts with the rank of gene counts inside an observation has proven effective to mitigate this problem. However, the rank of a feature is by definition relative to all other features, including highly variable features that introduce noise in the ranking. To address this problem and obtain more robust ranks, we propose a logistic regression model, optirank, which learns simultaneously the parameters of the model and the genes to use as a reference set in the ranking. We show the effectiveness of this method on simulated data. We also consider real classification tasks, which present different kinds of distribution shifts between train and test data. Those tasks concern a variety of applications, such as cancer of unknown primary classification, identification of specific gene signatures, and determination of cell type in single-cell RNA-Seq datasets. On those real tasks, optirank performs at least as well as the vanilla logistic regression on classical ranks, while producing sparser solutions. In addition, to increase the robustness against dataset shifts, we propose a multi-source learning scheme and demonstrate its effectiveness when used in combination with rank-based classifiers.
Symmetric Kondo Lattice States in Doped Strained Twisted Bilayer Graphene.

We use the topological heavy fermion (THF) model and its Kondo lattice (KL) formulation to study the possibility of a symmetric Kondo (SK) state in twisted bilayer graphene. Via a large-N approximation, we find a SK state in the KL model at fillings ν=0,±1,±2 where a KL model can be constructed. In the SK state, all symmetries are preserved and the local moments are Kondo screened by the conduction electrons. At the mean-field level of the THF model at ν=0,±1,±2,±3 we also find a similar symmetric state that is adiabatically connected to the symmetric Kondo state. We study the stability of the symmetric state by comparing its energy with the ordered (symmetry-breaking) states found in [H. Hu et al., Phys. Rev. Lett. 131, 026502 (2023). PRLTAO0031-900710.1103/PhysRevLett.131. 026502, Z. -D. Song and B. A. Bernevig, Phys. Rev. Lett. 129, 047601 (2022). PRLTAO0031-900710.1103/PhysRevLett.129. 047601] and find the ordered states to have lower energy at ν=0,±1,±2. However, moving away from integer fillings by doping the light bands, our mean-field calculations find the energy difference between the ordered state and the symmetric state to be reduced, which suggests the loss of ordering and a tendency toward Kondo screening. In order to include many-body effects beyond the mean-field approximation, we also performed dynamical mean-field theory calculations on the THF model in the nonordered phase. The spin susceptibility follows a Curie behavior at ν=0,±1,±2 down to ∼2 K where the onset of screening of the local moment becomes visible. This hints to very low Kondo temperatures at these fillings, in agreement with the outcome of our mean-field calculations. At noninteger filling ν=±0.5,±0.8,±1.2 dynamical mean-field theory shows deviations from a 1/T susceptibility at much higher temperatures, suggesting a more effective screening of local moments with doping. Finally, we study the effect of a C_{3z}-rotational-symmetry-breaking strain via mean-field approaches and find that a symmetric phase (that only breaks C_{3z} symmetry) can be stabilized at sufficiently large strain at ν=0,±1,±2. Our results suggest that a symmetric Kondo phase is strongly suppressed at integer fillings, but could be stabilized either at noninteger fillings or by applying strain.
Fully-dynamic risk measures: horizon risk, time-consistency, and relations with BSDEs and BSVIEs

In a dynamic framework, we identify a new concept associated with the risk of assessing the financial exposure by a measure that is not adequate to the actual time horizon of the position. This will be called horizon risk. We clarify that dynamic risk measures are subject to horizon risk, so we propose to use the fully-dynamic version. To quantify horizon risk, we introduce h-longevity as an indicator. We investigate these notions together with other properties of risk measures as normalization, restriction property, and different formulations of time-consistency. We also consider these concepts for fully-dynamic risk measures generated by backward stochastic differential equations (BSDEs), backward stochastic Volterra integral equations (BSVIEs), and families of these. Within this study, we provide new results for BSVIEs such as a converse comparison theorem and the dual representation of the associated risk measures.
An 8.0% Determination of the Baryon Fraction in the Intergalactic Medium from Localized Fast Radio Bursts

The dispersion measure (DM)–redshift relation of fast radio bursts (FRBs) has been proposed as a potential new tool for probing the intergalactic medium (IGM) and for studying cosmology. However, poor knowledge of the baryon fraction in the IGM (f IGM) and its degeneracy with cosmological parameters impose restrictions on the cosmological applications of FRBs. Furthermore, DMs contributed by the IGM (DMIGM) and host galaxy (DMhost), important cosmological quantities, cannot be exactly extracted from observations, which would bring uncontrolled systematic uncertainties in FRB cosmology. In this work, we use 17 localized FRBs to constrain f IGM and its possible redshift evolution. Other cosmological probes such as type Ia supernovae, baryon acoustic oscillations, and cosmic microwave background radiation are combined to break parameter degeneracy. Taking into account the probability distributions of DMIGM and DMhost derived from the IllustrisTNG simulation, we obtain a robust measurement of f IGM = 0.927 ± 0.075, representing a precision of 8.0%. We find that there is no strong evidence for the redshift dependence of f IGM at the current observational data level. The rapid progress in localizing FRBs will significantly improve the constraints on f IGM.
Improving Inference Performance of Machine Learning with the Divide-and-Conquer Principle

Many popular machine learning models scale poorly when deployed on CPUs. In this paper we explore the reasons why and propose a simple, yet effective approach based on the well-known Divide-and-Conquer Principle to tackle this problem of great practical importance. Given an inference job, instead of using all available computing resources (i.e., CPU cores) for running it, the idea is to break the job into independent parts that can be executed in parallel, each with the number of cores according to its expected computational cost. We implement this idea in the popular OnnxRuntime framework and evaluate its effectiveness with several use cases, including the well-known models for optical character recognition (PaddleOCR) and natural language processing (BERT).