Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Approach to HIV Case Management

ABSTRACT Case management is a standard practice for assisting people living with HIV in the United States. While HIV case management has resulted in positive outcomes for clients and their families, clients still face challenges. As part of an evaluation of Utah’s Ryan White Part B Program, the Utah Department of Health and researchers from the University of Utah assessed the use of a tiered approach for case management in eight other states to determine the feasibility and potential effectiveness of this approach. Through review of publicly available materials and interviews with health department employees, we examined each state’s 1) definitions of tiers, 2) acuity scales, 3) services provided within the tiers, 4) qualifications of case managers, and 5) how evaluations were conducted. This article summarizes how these various features might be combined to create a model that states could use for tiered case management. We developed a three-tiered model using a numeric summary for nine items to assess acuity, with levels defined as maintenance outreach support services, brief-contact management, and medical/non-medical management. Since none of the states reviewed had an existing formal evaluation tool, we propose areas to be covered in an annual formal evaluation.
DeLiO: Decoupled LiDAR Odometry

Most LiDAR odometry algorithms estimate the transformation between two consecutive frames by estimating the rotation and translation in an intervening fashion. In this paper, we propose our Decoupled LiDAR Odometry (DeLiO), which – for the first time – decouples the rotation estimation completely from the translation estimation. In particular, the rotation is estimated by extracting the surface normals from the input point clouds and tracking their characteristic pattern on a unit sphere. Using this rotation the point clouds are unrotated so that the underlying transformation is pure translation, which can be easily estimated using a line cloud approach. An evaluation is performed on the KITTI dataset and the results are compared against state-of-the-art algorithms.
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds

We present an efficient coresets-based neural network compression algorithm that sparsifies the parameters of a trained fully-connected neural network in a manner that provably approximates the network's output. Our approach is based on an importance sampling scheme that judiciously defines a sampling distribution over the neural network parameters, and as a result, retains parameters of high importance while discarding redundant ones. We leverage a novel, empirical notion of sensitivity and extend traditional coreset constructions to the application of compressing parameters. Our theoretical analysis establishes guarantees on the size and accuracy of the resulting compressed network and gives rise to generalization bounds that may provide new insights into the generalization properties of neural networks. We demonstrate the practical effectiveness of our algorithm on a variety of neural network configurations and real-world data sets.
Thalamocortical synapses in the cat visual system in vivo are weak and unreliable

The thalamocortical synapse of the visual system has been central to our understanding of sensory computations in the cortex. Although we have a fair understanding of the functional properties of the pre and post-synaptic populations, little is known about their synaptic properties, particularly in vivo. We used simultaneous recordings in LGN and V1 in cat in vivo to characterize the dynamic properties of thalamocortical synaptic transmission in monosynaptically connected LGN-V1 neurons. We found that thalamocortical synapses in vivo are unreliable, highly variable and exhibit short-term plasticity. Using biologically constrained models, we found that variable and unreliable synapses serve to increase cortical firing by means of increasing membrane fluctuations, similar to high conductance states. Thus, synaptic variability and unreliability, rather than acting as system noise, do serve a computational function. Our characterization of LGN-V1 synaptic properties constrains existing mathematical models, and mechanistic hypotheses, of a fundamental circuit in computational neuroscience.
SUPERNOVA SIMULATIONS AND STRATEGIES FOR THE DARK ENERGY SURVEY

We present an analysis of supernova light curves simulated for the upcoming Dark Energy Survey (DES) supernova search. The simulations employ a code suite that generates and fits realistic light curves in order to obtain distance modulus/redshift pairs that are passed to a cosmology fitter. We investigated several different survey strategies including field selection, supernova selection biases, and photometric redshift measurements. Using the results of this study, we chose a 30 deg2 search area in the griz filter set. We forecast (1) that this survey will provide a homogeneous sample of up to 4000 Type Ia supernovae in the redshift range 0.05 <z < 1.2 and (2) that the increased red efficiency of the DES camera will significantly improve high-redshift color measurements. The redshift of each supernova with an identified host galaxy will be obtained from spectroscopic observations of the host. A supernova spectrum will be obtained for a subset of the sample, which will be utilized for control studies. In addition, we have investigated the use of combined photometric redshifts taking into account data from both the host and supernova. We have investigated and estimated the likely contamination from core-collapse supernovae based on photometric identification, and have found that a Type Ia supernova sample purity of up to 98% is obtainable given specific assumptions. Furthermore, we present systematic uncertainties due to sample purity, photometric calibration, dust extinction priors, filter-centroid shifts, and inter-calibration. We conclude by estimating the uncertainty on the cosmological parameters that will be measured from the DES supernova data.
Real-time skin color detection under rapidly changing illumination conditions

Skin color provides a useful cue for vision based human-computer interaction (HCI). However, rapidly changing illumination conditions under HCI application environment make skin color detection a challenging task, as skin colors in an image highly depend on the illumination under which the image was taken. This paper presents a method for skin color detection under rapidly changing illumination conditions. Skin colors are modeled under the Bayesian decision framework. Face detection is employed to online sample skin colors and a dynamic thresholding technique is used to update the skin color model. When there is no face detected, color correction strategy is employed to convert the colors of the current frame to those as they appear under the same illuminant of the last model updated frame. Skin color detection is then applied on the color corrected image. Face detection is time-consuming and hence should not be applied to every frame in real-time applications on general consumer hardware. To improve efficiency, a novel method is proposed to detect illumination changes, and face detection is used to update the skin color model only if the illumination has changed. Experimental results show that the proposed method can achieve satisfactory performance for skin color detection under rapidly changing illumination conditions in real-time on general consumer hardware.
Hawking emission of gravitons in higher dimensions: non-rotating black holes

We compute the absorption cross section and the total power carried by gravitons in the evaporation process of a higher-dimensional non-rotating black hole. These results are applied to a model of extra dimensions with standard model fields propagating on a brane. The emission of gravitons in the bulk is highly enhanced as the spacetime dimensionality increases. The implications for the detection of black holes in particle colliders and ultrahigh-energy cosmic ray air showers are briefly discussed.
Changes in cell density and morphology of selected cells of the ageing human dental pulp.

OBJECTIVES The aim of this study was to determine the changes in cell density and morphology of selected cells of the ageing human dental pulp. BACKGROUND Changes in cell density and morphology of dental pulp cells over time may affect their capability to respond to tooth injury. MATERIALS AND METHODS One hundred thirty-one extracted teeth were obtained from individuals between the ages of 6 and 80 years. The apical 1/3 of the root region was removed from all teeth prior to routine processing for producing histological slides. The histology slides were used to study the changes in cell density and morphology of selected pulp cells; odontoblasts, subodontoblasts and fibroblasts in the crown and root regions of the dental pulp. Student's t-test and one-way anova were used for statistical analyses. RESULTS In all age groups, the cell density for all types of cells was found to be higher in the crown than in the root (p < 0.05). In general, the pulp cell density was found to decrease with age in both the crown and root regions. However, it was noted that the reduction of coronal odontoblasts occurred later in life (40-49 years) when compared to that of subodontoblasts or fibroblasts (30-39 years). CONCLUSIONS The density of the coronal pulp cells reduces and these cells undergo morphological changes with ageing of individuals and this may affect the pulp's ability to resist tooth injury.
Linearized two-layers neural networks in high dimension

We consider the problem of learning an unknown function $f_{\star}$ on the $d$-dimensional sphere with respect to the square loss, given i.i. d. samples $\{(y_i,{\boldsymbol x}_i)\}_{i\le n}$ where ${\boldsymbol x}_i$ is a feature vector uniformly distributed on the sphere and $y_i=f_{\star}({\boldsymbol x}_i)$. We study two popular classes of models that can be regarded as linearizations of two-layers neural networks around a random initialization: (RF) The random feature model of Rahimi-Recht; (NT) The neural tangent kernel model of Jacot-Gabriel-Hongler. Both these approaches can also be regarded as randomized approximations of kernel ridge regression (with respect to different kernels), and hence enjoy universal approximation properties when the number of neurons $N$ diverges, for a fixed dimension $d$. We prove that, if both $d$ and $N$ are large, the behavior of these models is instead remarkably simpler. If $N \le d^{2-\delta_d}$ for $\delta_d^2\log d\to\infty$, then RF performs no better than linear regression with respect to the raw features ${\boldsymbol x}_i$, and NT performs no better than linear regression with respect to degree-one and two monomials in the ${\boldsymbol x}_i$. More generally, if $N\le d^{\ell+1-\delta_d}$ then RF fits at most a degree-$\ell$ polynomial in the raw features, and NT fits at most a degree-$(\ell+1)$ polynomial. As a direct consequence of our main theorem, we obtain an equally simple bound on the generalization error of Kernel Ridge Regression (KRR). In the same setting of ${\boldsymbol x}_i$ i.i. d. uniformly distributed on the sphere and for any rotational-invariant kernel, if the number of samples is $n \le d^{\ell +1-\delta_d}$, then KRR only captures degree-$\ell$ polynomials in the raw features.
Ratio of transmitral early filling velocity to early diastolic strain rate predicts long-term risk of cardiovascular morbidity and mortality in the general population

Aims It has previously been demonstrated that the ratio of early mitral inflow velocity to global diastolic strain rate (E/e'sr) is a significant predictor of cardiac events in specific patient populations. The utility of this measurement to predict cardiovascular events in a general population has not been evaluated. Methods and results A total of 1238 participants in a general population study underwent a health examination including echocardiography where global longitudinal strain (GLS) and E/e'sr were determined. The primary endpoint was the composite of incident heart failure (HF), acute myocardial infarction (AMI) or cardiovascular death (CVD). During follow-up (median 11 years), 140 (11.3%) participants reached the composite endpoint. E/e'sr was associated with adverse outcome [HR 1.17 95% CI (1.13-1.21); P < 0.001, per 10 cm increase]. After multivariable adjustment for echocardiographic and clinical parameters, E/e'sr remained an independent predictor of the composite endpoint [HR 1.08, 95% CI (1.02-1.13); P = 0.003] as opposed to E/e' [HR 1.03, 95% CI (0.99-1.06); P = 0.11 per 1 unit increase]. Global longitudinal strain modified the relationship between E/e'sr and outcome (P for interaction = 0.015). E/e'sr was a stronger predictor in participants with good systolic function as determined by GLS (GLS > 18%) after multivariable adjustment, when compared to participants with reduced systolic function (GLS < 18%) [HR 1.28 95% CI (1.06-1.54); P = 0.011, and HR 1.08 95% CI (1.02-1.14); P = 0.012, respectively). E/e'sr provided incremental information [Harrell's C-index: 0.839 (0.81-0.87) vs. 0.844 (0.82-0.87); P = 0.045] beyond the SCORE risk chart. Conclusion In the general population, E/e'sr provides independent and incremental prognostic information regarding cardiovascular morbidity and mortality. Additionally, E/e'sr is a stronger predictor of cardiac events than E/e'.
NMR structure of a full‐length single‐pass membrane protein NRADD

Structural study of any single‐pass membrane protein is both an important and challenging task. In this report, we present the structure of a neurotrophin receptor‐alike death‐domain protein. The structure and dynamics of the protein was investigated by conventional nuclear magnetic resonance techniques in the solution of phospholipid bicelles. The receptor contains two folded regions—α‐helical transmembrane domain and globular C‐terminal death domain with more than 50% of the rest of backbone being disordered. This is the first structure of a full‐length single‐pass membrane receptor‐alike protein solved by the single method.
Hypocretin underlies the evolution of sleep loss in the Mexican cavefish

The duration of sleep varies dramatically between species, yet little is known about genetic bases or evolutionary factors driving this variation in behavior. The Mexican cavefish, Astyanax mexicanus, exists as surface populations that inhabit rivers, and multiple independently derived cave populations with convergent evolution on sleep loss. The number of Hypocretin/Orexin (HCRT)-positive hypothalamic neurons is increased significantly in cavefish, and HCRT is upregulated at both the transcript and protein levels. Pharmacological or genetic inhibition of HCRT signaling increases sleep duration in cavefish without affecting sleep in surface fish, suggesting enhanced HCRT signaling underlies sleep loss in cavefish. Ablation of the lateral line or starvation, manipulations that selectively promote sleep in cavefish, inhibit hcrt expression in cavefish while having little effect in surface fish. These findings provide the first evidence of genetic and neuronal changes that contribute to the evolution of sleep loss, and support a conserved role for HCRT in sleep regulation.
Study on the Coupling Mechanism of the Orthogonal Dipoles with Surface Plasmon in Green LED by Cathodoluminescence

We analyzed the coupling behavior between the localized surface plasmon (LSP) and quantum wells (QWs) using cathodoluminescence (CL) in a green light-emitting diodes (LED) with Ag nanoparticles (NPs) filled in photonic crystal (PhC) holes. Photoluminescence (PL) suppression and CL enhancement were obtained for the same green LED sample with the Ag NP array. Time-resolved PL (TRPL) results indicate strong coupling between the LSP and the QWs. Three-dimensional (3D) finite difference time domain (FDTD) simulation was performed using a three-body model consisting of two orthogonal dipoles and a single Ag NP. The LSP–QWs coupling effect was separated from the electron-beam (e-beam)–LSP–QW system by linear approximation. The energy dissipation was significantly reduced by the z-dipole introduction under the e-beam excitation. In this paper, the coupling mechanism is discussed and a novel emission structure is proposed.
The effect of varying crude protein level and the proportions of fibre in diets containing a mixture of meat-and-bone meal and wheat bran as the only protein source on nitrogen balance indices and energy digestibility in the rat

1. The experiment was designed to investigate the effect of protein level in diets on apparent protein digestibility (AD), true protein digestibility (TD), biological value (BV), net protein utilization (NPU) and energy digestibility (DE) in rats. The design involved fourteen dietary treatments in which a combination of wheat bran and meat-and-bone meal (1:1, w/w dry matter (DM) basis) was the only nitrogen source. Crude protein (N x 6.25; CP) level ranged from 60 to 329 g/kg DM in approximately even increments. All diets contained a constant level of minerals and vitamins. The balance of the diet consisted of a N-free mixture. 2. AD increased from 0.602 at 60 g CP/kg DM to 0.702 at 120 g CP/kg DM, with little change at the higher levels of dietary protein. The fitting of a curve indicated an asymptote of 0.721. 3. TD did not vary significantly between 60 and 225 g CP/kg DM (mean 0.781). At the higher protein levels there was a slight but significant reduction in the mean value (0.758). 4. BV increased from 0.475 at 60 g CP/kg DM to 0.498 at 80 g CP/kg DM where it plateaued, and then from 160 g CP/kg DM it decreased at an increasing rate to 0.216 at 329 g CP/kg DM. 5. The response in NPU closely reflected that obtained with BV, rising from 0.370 to 0.384, then declining to 0.162 at the highest CP concentration. 6. DE decreased linearly from 0.851 at 60 g CP/kg DM to 0.617 at 329 g CP/kg DM. 7. The results confirmed that AD values should only be compared at a defined protein level. TD was essentially independent of dietary CP level, except for a small reduction above 250 g CP/kg, whereas BV and NPU were stable only within the range 80-140 g CP/kg DM. DE was negatively related to dietary CP and fibre level.
In Situ Biomass Production of a Hot Spring Sulfur-Turf Microbial Mat

Sulfur-turf microbial mats develop in sulfide-containing hot spring water dominated by chemolithoautotrophic sulfur-oxidizing bacteria. The sulfur-turf mat that developed at a source of hot water (72°C, pH 6.8) exhibited a growth rate of 0.48±0.04 h and biomass production of 4.6±1.0 mg of C h. On a per-cell basis, this biomass production was at least an order of magnitude higher than the CO2 uptake rate calculated for a photosynthetic mat dominated by thermophilic Synechococcus spp. at 70°C. The sulfur-turf-associated microbial community likely contributes to carbon fixation and primary production in this geothermal habitat.
Genetic polymorphism of seven populations of Capsella bursa- pastoris based on RAPD markers

Capsella bursa-pastoris is considered to be a potential vegetable crop. Together with two accessions of mustard (Brassica juncea) as outgroups, seven populations of C. bursa-postoris were used to study genetic polymor- phism using random amplified polymorphic DNA (RAPD) markers. Using 12 primers, a total of 158 RAPD markers were selected among these populations. Among them, 91 are either specific for C. bursa-postris or present in both C. bursa-postoris and B. juncea. In Capsella populations, 40 RAPD markers are polymorphic, 5 markers are population specific, and 46 markers are monomorphic with variation of banding density. Each RAPD marker was treated as either having unweighted character or weighted character. Using UPGMA for cluster analysis, the polymorphic tree structures based on unweighted and weighted character have a similar phylogenetic relationship among these tested populations. With one exception, the phylogenetic relationship of Taiwan origin is correlated with the geographical distribution of these populations. These results may provide us information of genetic variation to be used in a varietal development program and to find specific markers linked to important traits.
Characterization of a New Staphylococcus aureus Kayvirus Harboring a Lysin Active against Biofilms

Staphylococcus aureus is one of the most relevant opportunistic pathogens involved in many biofilm-associated diseases, and is a major cause of nosocomial infections, mainly due to the increasing prevalence of multidrug-resistant strains. Consequently, alternative methods to eradicate the pathogen are urgent. It has been previously shown that polyvalent staphylococcal kayviruses and their derived endolysins are excellent candidates for therapy. Here we present the characterization of a new bacteriophage: vB_SauM-LM12 (LM12). LM12 has a broad host range (>90%; 56 strains tested), and is active against several MRSA strains. The genome of LM12 is composed of a dsDNA molecule with 143,625 bp, with average GC content of 30.25% and codes for 227 Coding Sequences (CDSs). Bioinformatics analysis did not identify any gene encoding virulence factors, toxins, or antibiotic resistance determinants. Antibiofilm assays have shown that this phage significantly reduced the number of viable cells (less than one order of magnitude). Moreover, the encoded endolysin also showed activity against biofilms, with a consistent biomass reduction during prolonged periods of treatment (of about one order of magnitude). Interestingly, the endolysin was shown to be much more active against stationary-phase cells and suspended biofilm cells than against intact and scraped biofilms, suggesting that cellular aggregates protected by the biofilm matrix reduced protein activity. Both phage LM12 and its endolysin seem to have a strong antimicrobial effect and broad host range against S. aureus, suggesting their potential to treat S. aureus biofilm infections.
Beneficial Effects of Different Flavonoids on Vascular and Renal Function in L-NAME Hypertensive Rats

Background: we have evaluated the antihypertensive effect of several flavonoid extracts in a rat model of arterial hypertension caused by chronic administration (6 weeks) of the nitric oxide synthesis inhibitor, L-NAME. Methods: Sprague Dawley rats received L-NAME alone or L-NAME plus flavonoid-rich vegetal extracts (Lemon, Grapefruit + Bitter Orange, and Cocoa) or purified flavonoids (Apigenin and Diosmin) for 6 weeks. Results: L-NAME treatment resulted in a marked elevation of blood pressure, and treatment with Apigenin, Lemon Extract, and Grapefruit + Bitter Orange extracts significantly reduced the elevated blood pressure of these animals. Apigenin and some of these flavonoids also ameliorated nitric oxide-dependent and -independent aortic vasodilation and elevated nitrite urinary excretion. End-organ abnormalities such as cardiac infarcts, hyaline arteriopathy and fibrinoid necrosis in coronary arteries and aorta were improved by these treatments, reducing the end-organ vascular damage. Conclusions: the flavonoids included in this study, specially apigenin, may be used as functional food ingredients with potential therapeutic benefit in arterial hypertension.