Miracle-dz/UniFAR-FTUs huggingface dataset:
Power Allocation and Parameter Estimation for Multipath-Based 5G Positioning

We consider a single-anchor multiple-input multiple-output orthogonal frequency-division multiplexing system with imperfectly synchronized transmitter (Tx) and receiver (Rx) clocks, where the Rx estimates its position based on the received reference signals. The Tx, having (imperfect) prior knowledge about the Rx location and the surrounding geometry, transmits reference signals based on a set of fixed beams. We develop strategies for the power allocation among the beams aiming to minimize the expected Cramér-Rao lower bound for Rx positioning. Additional constraints on the design are included to make the optimized power allocation robust to uncertainty on the line-of-sight (LOS) path direction. Furthermore, the effect of clock asynchronism on the proposed allocation strategies is studied. Our evaluation results show that, for non-negligible synchronization error, it is optimal to allocate a large fraction of the available power for the illumination of the non-LOS (NLOS) paths, which help resolve the clock offset. In addition, the complexity reduction achieved by our proposed suboptimal approach incurs only a small performance degradation. We also propose an off-grid compressed sensing-based position estimation algorithm, which exploits the information on the clock offset provided by NLOS paths, and show that it is asymptotically efficient.
Deviations from tidal torque theory: Evolution of the halo spin–filament alignment

The alignment between halo spins and the cosmic web is still poorly understood despite being a widely studied topic. Here, we study this alignment within the context of tidal torque theory (TTT) and deviations from it. To this end, we analyze the evolution of the shape and spin direction of proto-haloes, i.e. of all the volume elements associated to a $z=0$ halo, with respect to the present-day filaments. We find that the major axis of proto-haloes undergoes a major change, from being strongly perpendicular to the filament spine in the initial conditions, to being preferentially aligned at the present time. In comparison, the spin orientation shows only a mild evolution: it starts slightly parallel to the filament spine, but the subsequent evolution, up to $z{\sim}1$, gradually changes its orientation to preferentially perpendicular. In order to analyze these signals in the TTT framework, we split the haloes according to their net spin growth with respect to the median TTT expectation, finding a clear correlation with the spin--filament alignment. At the present time, haloes whose spin grew the most are the ones most perpendicular to the filament spine, while haloes whose spin grew below the median TTT expectation are typically more aligned. The dependence of spin directions on net spin growth is already present in the initial conditions, and gets further modified by late-time, $z<2$, evolution. Also, spin directions mildly deviate from the TTT predictions even at high redshift, indicating the need for extensions to the model.
Systematic Review of Sequencing Studies and Gene Expression Profiling in Familial Meniere Disease

Familial Meniere Disease (FMD) is a rare inner ear disorder characterized by episodic vertigo associated with sensorineural hearing loss, tinnitus and/or aural fullness. We conducted a systematic review to find sequencing studies segregating rare variants in FMD to obtain evidence to support candidate genes for MD. After evaluating the quality of the retrieved records, eight studies were selected to carry out a quantitative synthesis. These articles described 20 single nucleotide variants (SNVs) in 11 genes (FAM136A, DTNA, PRKCB, COCH, DPT, SEMA3D, STRC, HMX2, TMEM55B, OTOG and LSAMP), most of them in singular families—the exception being the OTOG gene. Furthermore, we analyzed the pathogenicity of each SNV and compared its allelic frequency with reference datasets to evaluate its role in the pathogenesis of FMD. By retrieving gene expression data in these genes from different databases, we could classify them according to their gene expression in neural or inner ear tissues. Finally, we evaluated the pattern of inheritance to conclude which genes show an autosomal dominant (AD) or autosomal recessive (AR) inheritance in FMD.
Delay-Dependent Stability Analysis for Switched Stochastic Networks With Proportional Delay

In this article, the issue of exponential stability (ES) is investigated for a class of switched stochastic neural networks (SSNNs) with proportional delay (PD). The key feature of PD is an unbounded time-varying delay. By considering the comparison principle and combining the extended formula for the variation of parameters, we conquer the difficulty in consideration of PD effects for such networks for the first time, where the subsystems addressed may be stable or unstable. New delay-dependent conditions with respect to the mean-square ES of systems are established by employing the average dwell-time (ADT) technique, stochastic analysis theory, and Lyapunov approach. It is shown that the acquired minimum average dwell time (MADT) is not only relevant to the stable subsystems (SSs) and unstable subsystems (USs) but also dependent on the decay ratio (DR), increasing ratio (IR), as well as PD. Finally, the availability of the derived results under an average dwell-time-switched regulation (ADTSR) is illustrated through two numerical simulation examples.
Initial fouling of nontoxic coatings in fresh, brackish, and sea water

Objectives of this project were to evaluate benefits — over the short term — that might derive from control of the surface properties of materials used in energy transfer devices; and to identify preferred ranges of surface parameters that might be specified to minimize deposits of biological fouling known to deteriorate energy exchange efficiencies in seawater, brackish water, and freshwater systems. By modifying the surface chemistry and surface energy of test plates with very thin coatings (nontoxic) and examining the acquired films at various time intervals, the earliest events of biofouling caused by macromolecules and microbial organisms were defined. Overall, the results were remarkably similar for all systems tested in showing that deliberate modification of the initial material surface qualities can significantly reduce the retention of biofouling layers. L'objectif de ce projet est d'kvaluer les avantages-a court terme -issus d'un meilleur controle des proprietes de surface des materiaux utilises dans les systemes de transfert energetique, et de determiner les differents parametres de surface susceptibles de reduire I'accumulation de depots biologiques. Ces depots, en effet, sont a I'origine de pertes de rendement significatives de transfert de chaleur dans les installations d'eau de mer, d'eau saumâtre et d'eau douce. En modifiant la chimie et 1'energie de surface des plateaux d'essai avec des revetements tres minces (non toxiques) et en examinant les films obtenus a differents intervalles de temps, on a pu mettre en evidence les premiers effets de bio-deposition causes par les macromolecules et les organismes microbiens. Globalement, les resultats sont remarquablement similaires pour tous les systemes testes et montrent que la modification volontaire des proprietes initiales de surface des materiaux peut reduire de maniere significative la retention des differentes couches de depots biologiques.
Establishment of a Molecular Tumor Board (MTB) and Uptake of Recommendations in a Community Setting

In the precision medicine era, molecular testing in advanced cancer is foundational to patient management. Molecular tumor boards (MTBs) can be effective in processing comprehensive genomic profiling (CGP) results and providing expert recommendations. We assessed an MTB and its role in a community setting. This retrospective analysis included patients with MTB recommendations at a community-based oncology practice January 2015 to December 2018; exclusions were death within 60 days of the MTB and/or no metastatic disease. Potentially actionable genomic alterations from CGP (immunohistochemistry, in-situ hybridization, next-generation sequencing) were reviewed bi-weekly by MTB practice experts, pathologists, genetic counselors, and other support staff, and clinical care recommendations were provided. Subsequent chart reviews determined implementation rates of recommendations. In 613 patients, the most common cancers were lung (23%), breast (19%), and colorectal (17%); others included ovarian, endometrial, bladder, and melanoma. Patients received 837 actionable recommendations: standard therapy (37%), clinical trial (31%), germline testing and genetic counseling (17%), off-label therapy (10%), subspecialty multidisciplinary tumor board review (2%), and advice for classifying tumor of unknown origin (2%). Of these recommendations, 36% to 78% were followed by the treating physician. For clinical trial recommendations (n = 262), 13% of patients enrolled in a clinical trial. The median time between CPG result availability and MTB presentation was 12 days. A community oncology-based comprehensive and high-throughput MTB provided useful clinical guidance in various treatment domains within an acceptable timeframe for patients with cancer in a large community setting.
A Systematic Review of Pharmacologic and Rehabilitative Treatment of Small Fiber Neuropathies

The aim of this systematic review is to guide the physician in defining the pharmacologic and rehabilitative therapeutic approaches for adopting the best strategies described in the current literature. The search was conducted in PubMed, EMBASE, Cochrane Library and Web of Science to identify the treatment of small fiber neuropathies. Two reviewers independently reviewed and came to a consensus on which articles met inclusion/exclusion criteria. The authors excluded the duplicates, animal studies and included the English articles in which the treatment of patients with small fiber neuropathies was described. The search identified a total of 975 articles with the keywords “small fiber neuropathy” AND “rehabilitation” OR “therapy” OR “treatment”. Seventy-eight selected full-text were analyzed by the reviewers. Forty-two publications met the inclusion criteria and were included in the systematic review to describe the rehabilitative and pharmacologic treatment of small fiber neuropathies. Despite the range of different protocols of treatment for small fiber neuropathy, other robust trials are needed. In addition, always different therapeutic approaches are used; a unique protocol could be important for the clinicians. More research is needed to build evidence for the best strategy and to delineate a definitive therapeutic protocol.
Survival and adequate preoperative staging in patients undergoing gastric cancer surgery at a Peruvian Police Hospital

Gastric cancer is the fifth most common malignant neoplasm and the third leading cause of cancer‐related death worldwide. In Peru, its incidence is 15.8 per 100,000 population, and it is associated with high mortality rates, especially in areas with low socioeconomic status. The aim of this study was to compare preoperative, postoperative, and anatomopathological staging results and their relation to disease recurrence and survival.
Habitual Caffeine Consumption Does Not Affect the Ergogenicity of Coffee Ingestion During a 5 km Cycling Time Trial.

There is growing evidence that caffeine and coffee ingestion prior to exercise provide similar ergogenic benefits. However, there has been a long-standing paradigm that habitual caffeine intake may influence the ergogenicity of caffeine supplementation. The aim of the present study was to investigate the effect of habitual caffeine intake on 5-km cycling time-trial performance following the ingestion of caffeinated coffee. Following institutional ethical approval, in a double-blind, randomized, crossover, placebo-controlled design, 46 recreationally active participants (27 men and 19 women) completed a 5-km cycling time trial on a cycle ergometer 60 m in following the ingestion of 0.09 g/kg coffee providing 3 mg/kg of caffeine, or a placebo. Habitual caffeine consumption was assessed using a caffeine consumption questionnaire with low habitual caffeine consumption defined as <3 and ≥6 mg · kg-1 · day-1 defined as high. An analysis of covariance using habitual caffeine intake as a covariant was performed to establish if habitual caffeine consumption had an impact on the ergogenic effect of coffee ingestion. Sixteen participants were classified as high-caffeine users and 30 as low. Ingesting caffeinated coffee improved 5-km cycling time-trial performance by 8 ± 12 s; 95% confidence interval (CI) [5, 13]; p < . 001; d = 0.30, with low, 9±14 s; 95% CI [3, 14]; p = . 002; d = 0.18, and high, 8 ± 10 s; 95% CI [-1, 17]; p = . 008; d = 0.06, users improving by a similar magnitude, 95% CI [-12, 12]; p = . 946; d = 0.08. In conclusion, habitual caffeine consumption did not affect the ergogenicity of coffee ingestion prior to a 5-km cycling time trial.
Front-back asymmetry controls the impact of viscoelasticity on helical swimming

We conduct experiments with force-free magnetically-driven rigid helical swimmers in Newtonian and viscoelastic (Boger) fluids. By varying the sizes of the swimmer body and its helical tail, we show that the impact of viscoelasticity strongly depends on the swimmer geometry: it can lead to a significant increase of the swimming speed (up to a factor of five), a similar decrease (also up to a factor of five) or it can have approximately no impact. Analysis of our data along with theoretical modeling shows that the influence of viscoelasticity on helical propulsion is controlled by a snowman-like effect, previously reported for dumbbell swimmers, wherein the front-back asymmetry of the swimmer leads to a non-Newtonian elastic force that can either favor or hinder locomotion.
Haloadaptative Responses of Aspergillus sydowii to Extreme Water Deprivation: Morphology, Compatible Solutes, and Oxidative Stress at NaCl Saturation

Water activity (aw) is critical for microbial growth, as it is severely restricted at aw < 0.90. Saturating NaCl concentrations (~5.0 M) induce extreme water deprivation (aw ≅ 0.75) and cellular stress responses. Halophilic fungi have cellular adaptations that enable osmotic balance and ionic/oxidative stress prevention to grow at high salinity. Here we studied the morphology, osmolyte synthesis, and oxidative stress defenses of the halophile Aspergillus sydowii EXF-12860 at 1.0 M and 5.13 M NaCl. Colony growth, pigmentation, exudate, and spore production were inhibited at NaCl-saturated media. Additionally, hyphae showed unpolarized growth, lower diameter, and increased septation, multicellularity and branching compared to optimal NaCl concentration. Trehalose, mannitol, arabitol, erythritol, and glycerol were produced in the presence of both 1.0 M and 5.13 M NaCl. Exposing A. sydowii cells to 5.13 M NaCl resulted in oxidative stress evidenced by an increase in antioxidant enzymes and lipid peroxidation biomarkers. Also, genes involved in cellular antioxidant defense systems were upregulated. This is the most comprehensive study that investigates the micromorphology and the adaptative cellular response of different non-enzymatic and enzymatic oxidative stress biomarkers in halophilic filamentous fungi.
Towards Defending Multiple $\ell_p$-norm Bounded Adversarial Perturbations via Gated Batch Normalization

There has been extensive evidence demonstrating that deep neural networks are vulnerable to adversarial examples, which motivates the development of defenses against adversarial attacks. Existing adversarial defenses typically improve model robustness against individual specific perturbation types (\eg, $\ell_{\infty}$-norm bounded adversarial examples). However, adversaries are likely to generate multiple types of perturbations in practice (\eg, $\ell_1$, $\ell_2$, and $\ell_{\infty}$ perturbations). Some recent methods improve model robustness against adversarial attacks in multiple $\ell_p$ balls, but their performance against each perturbation type is still far from satisfactory. In this paper, we observe that different $\ell_p$ bounded adversarial perturbations induce different statistical properties that can be separated and characterized by the statistics of Batch Normalization (BN). We thus propose Gated Batch Normalization (GBN) to adversarially train a perturbation-invariant predictor for defending multiple $\ell_p$ bounded adversarial perturbations. GBN consists of a multi-branch BN layer and a gated sub-network. Each BN branch in GBN is in charge of one perturbation type to ensure that the normalized output is aligned towards learning perturbation-invariant representation. Meanwhile, the gated sub-network is designed to separate inputs added with different perturbation types. We perform an extensive evaluation of our approach on commonly-used dataset including MNIST, CIFAR-10, and Tiny-ImageNet, and demonstrate that GBN outperforms previous defense proposals against multiple perturbation types (\ie, $\ell_1$, $\ell_2$, and $\ell_{\infty}$ perturbations) by large margins.
Demographic and Admission Predictors of Students with Perceived Difficulty in Entry-Level Doctor of Physical Therapy Programs.

BACKGROUND Admission committees have the difficult task of selecting candidates with the greatest likelihood of success for their programs and the profession. Because of limitations in defining the successful candidate, we attempted to predict who will become a "student with perceived difficulty" within a doctor of physical therapy (DPT) program using data available during the time of application. METHODS A retrospective analysis of 479 students from three entry-level DPT programs. The dependent variable was student with perceived difficulty status. Student characteristics were compared using unpaired t-tests (or non-parametric equivalent) and chi-squared tests. Receiver operating characteristic curves were constructed for variables significantly associated with student status to compare the predictive capabilities of the student characteristics and identify cutpoints that maximized sensitivity and specificity. We examined the predictive capabilities of clusters of characteristics that differed significantly between groups by calculating likelihood ratios and estimating odds ratios from logistic regression. RESULTS The cluster of characteristics that best identified students with perceived difficulty was prerequisite GPA <3.7, Analytical Writing GRE <4, and attended >2 undergraduate institutions. Twenty students met these criteria and 8 (40%) were identified as students with perceived difficulty. The positive likelihood ratio for this cluster of characteristics was 6.9 and the odds ratio was 8.7 (95% CI: 3.2, 23.0). CONCLUSIONS These results suggest that this cluster of variables, available at the time of admission, can be used to identify students whose progress in the program may need to be more closely monitored and who may benefit from additional services to minimize difficulties for the student and faculty.
Empirical Model for Discharge Current and Momentum Injection in Dielectric Barrier Discharge

Dielectric Barrier Discharge (DBD) plasma actuators with an asymmetric, straight edge electrode configuration generate a wall-bounded jet without moving parts. Mechanistic description of the interaction between the Coulombic forces and fluid motion as a function of DBD parameters remains unclear. This paper presents an experimental investigation of DBD actuator, including electrical current associated with microdischarges, plasma volume, and the wall jet momentum over a range of AC frequencies (0.5 - 2 kHz) and peak-to-peak voltages up to 19.5 kV. Discharge current is measured with a high temporal resolution, and plasma volume is characterized optically, and the momentum induced by the DBD wall jet is computed based on the axial velocities measured downstream of the actuator using a custom-built pitot tube. Discharge current analysis demonstrated asymmetry between the positive and negative semi-cycle; both currents yielded a power-law relationship with empirical fitting coefficients. Plasma length varies linearly and volume quadratically with voltage. Although plasma length reached an asymptotic value at a higher frequency, the plasma volume grows due to the increasing height of the ionization region. In a simple 2D configuration, the DBD wall jet momentum shows near-linear dependency with discharge current in the range of voltages and frequencies considered in this work. The presented empirical model characterizes the DBD wall jet momentum and the discharge current based only on the AC inputs. With the estimation of plasma volume, the model can be applied for determining more realistic boundary conditions in numerical simulations.
Pattern of greenhouse gas emission from a Prairie Pothole agricultural landscape in Manitoba, Canada

To obtain accurate N2O and CH4 emission estimates from the Prairie Pothole Region of North America, knowledge of landscape pattern and soil factors is important. A field study was conducted investigating the temporal and spatial variation in N2O and CH4 emissions from spring to fall 2005 and spring-thaw to post-fertilizer application period 2006 using static-vented chambers located at upper, middle and lower landscape elements planted to spring wheat in 2005 and flax in 2006 and riparian areas in an undulating terrain in southern Manitoba. N2O was emitted during spring-thaw and post-fertilizer application periods for cropped positions and CH4 was emitted about 7 wk after soil thaw for lower and riparian elements. While there was no statististical difference in N2O emission from upper, middle and lower landscape elements, there was greater occurrence of N2O emission hotspots at the lower element, associated with its comparatively higher soil moisture and carbon availability. A location of intense CH4 emiss.
Fine-Grained Few-Shot Classification with Feature Map Reconstruction Networks

In this paper we reformulate few-shot classification as a reconstruction problem in latent space. The ability of the network to reconstruct a query feature map from support features of a given class predicts membership of the query in that class. We introduce a novel mechanism for few-shot classification by regressing directly from support features to query features in closed form, without introducing any new modules or large-scale learnable parameters. The resulting Feature Map Reconstruction Networks are both more performant and computationally efficient than previous approaches. We demonstrate consistent and significant accuracy gains on four fine-grained benchmarks with varying neural architectures. Our model is also competitive on the non-fine-grained mini-ImageNet benchmark with minimal bells and whistles.