Miracle-dz/UniFAR-FTUs huggingface dataset:
Sonographic assessment of carpal tunnel syndrome in diabetic patients with and without polyneuropathy

Abstract The objective of this study is to determine whether the cross sectional area (CSA) measurement of the median nerve at the wrist differ between carpal tunnel syndrome (CTS) in diabetic patients with and without diabetic polyneuropathy (DPN). This study included 44 patients with type II diabete millitus (DM) with CTS, 32 patients with CTS and DPN, 46 patients with idiopathic CTS, and 42 healthy subjects. Ultrasonographic measurement of the CSA of the median nerve was made at the level of the wrist, together with nerve conduction studies. The median CSA at the wrist was significantly larger in all patient groups compared with healthy subjects. The median nerve CSA was significantly larger in diabetic patients with CTS than patients with idiopathic CTS. The median nerve CSA at wrist was significantly smaller in patients with CTS and DPN compared with diabetic patients with CTS only. The median nerve CSA at the wrist was larger in diabetic patients with CTS than patients with idiopathic CTS and CTS with DPN. Median nerve CSA can help to differentiate between diabetic patients with CTS with and without DPN.
Biofilm Building: A Simple Board Game to Reinforce Knowledge of Biofilm Formation †

The increasing risk of antibiotic resistance and correlating decrease in effective clinical treatments is a serious issue worldwide. One source antibiotic tolerance derives from biofilm infections: collectives of bacteria surrounded by an extracellular matrix that adhere to surfaces. Here we outline a board game designed to raise awareness and knowledge of biofilms in young learners.
Adaptive nonsingular guidance law against maneuvering targets

A novel three dimensional adaptive nonsingular guidance law against maneuvering targets is documented. Firstly, the nonlinear state equation is given regarding the target motion as unknown bounded external disturbance. Secondly, a new adaptive law estimating the square of the target acceleration bound is proposed based on which the adaptive nonsingular guidance law is derived, which solve the problem of non-smooth and chattering phenomenon; Thirdly, the finite time convergence of the guidance system is proved by the theory of finite time stability. Finally, simulation results of different target maneuver scenarios indicate that the proposed guidance law can not only ensure the fast convergent speed, but also provide smooth missile acceleration command, which shows its superiority.
The Moses holmium system - time is money.

INTRODUCTION The Moses technology of the holmium laser has been shown to decrease retropulsion in the ureter and procedural time in kidney stones during laser lithotripsy. Theoretically, these improvements could lead to cost savings for the patient. MATERIALS AND METHODS All patients with total laser energy data recorded who underwent ureteroscopy with laser lithotripsy by a single surgeon at a tertiary care center were included. Total lasing time was calculated from the total laser energy. Sub-analyses were done on stone size and stone composition. The procedure time using Moses technology was projected to be approximately 35% less than procedure time without the Moses technology based on prior in vitro studies. The projected cost savings was then utilized to predict cost-effectiveness of the Moses technology. RESULTS Forty patients underwent ureteroscopy with laser lithotripsy. Mean stones size was 10.2 mm and mean lasing time was 3.02 minutes. Linear regression showed a positive association between stone size and laser time, p = 0.01. There was no significant correlation between stone composition or stone Hounsfield units and lasing time. On cost analyses, for stones of all sizes the Moses system has a price differential of an increase in $292.36 when compared to the standard Holmium TracTip system. Specifically for stones larger than 10 mm, the price differential is an increase in $253.16 for the Moses technology. CONCLUSION The decrease in lasing time achieved by the Moses system does not translate into sufficient cost savings to off-set the higher cost of the laser fiber and software.
Resource and energy efficient device to device communications in downlink cellular system

In this paper, we investigate the energy efficiency (EE) optimization for a downlink orthogonal frequency division multiple access (OFDMA) system with overlaying Device-to-Device (D2D) communications. Joint EE optimization is highly complex while a two-stage solution will utilize most of the bandwidth for cellular users and not providing sufficient bandwidth for D2D users. Using resource efficiency (RE) optimization approach that balances the bandwidth usage and EE, we propose a two-stage solution that optimizes RE for base station (BS) and EE for D2D pairs. To achieve higher EE, D2D communications operate in non-orthogonal mode, where each resource block (RB) not being assigned to the cellular users are reused by multiple D2D pairs. By exploiting a range of optimization tools including fractional programming, Dinkelbach approach, Lagrange dual decomposition, difference of convex functions, and concave-convex procedure, the original non-convex problem is transformed and we present an iterative two-stage RE-EE solution. Simulation results demonstrate that the proposed resource allocation scheme provides comparable EE performance to a two-stage EE-EE solution with significant gain on EE for D2D users, and achieves much higher EE compared to a sum rate maximization scheme.
How Usable Are Rust Cryptography APIs?

Context: Poor usability of cryptographic APIs is a severe source of vulnerabilities. Aim: We wanted to find out what kind of cryptographic libraries are present in Rust and how usable they are. Method: We explored Rust's cryptographic libraries through a systematic search, conducted an exploratory study on the major libraries and a controlled experiment on two of these libraries with 28 student participants. Results: Only half of the major libraries explicitly focus on usability and misuse resistance, which is reflected in their current APIs. We found that participants were more successful using rust-crypto which we considered less usable than ring before the experiment. Conclusion: We discuss API design insights and make recommendations for the design of crypto libraries in Rust regarding the detail and structure of the documentation, higher-level APIs as wrappers for the existing low-level libraries, and selected, good-quality example code to improve the emerging cryptographic libraries of Rust.
Arabic corpus implementation: Application to speech recognition

This paper presents an Arabic speech recognition system using different features such as MFCC, PLP, LPC We propose to handle noisy data in order to evaluate the robustness of our system under noise conditions. The paper explores, also, the mechanism of building a corpus of the Arabic Tunisian language. Thus, we present the implementation of an automatic speech recognition system under the HTK platform. Experimental tests are performed to prove the effectiveness of different features for Arabic speech samples recognition. The performances on noisy samples from Arabic Tunisian and TIMIT databases show the robustness of the proposed system especially with noisy environments.
Private and efficient set intersection protocol for RFID-based food adequacy check

Radio Frequency Identification (RFID) is a technology for automatic object identification that has been implemented in several real-life applications. In this work, we expand a novel relevant application of RFID tags for grocery stores, which aims to check the adequacy of food items with respect to the shoppers' personal preferences. Unlike similar works, we focus on shoppers' privacy and running time efficiency. For this aim, we propose a novel private set intersection (PSI) protocol to be used in matching the shoppers' personal preferences with the set of each item's adequate profiles that are held by the back-end server of the store. We provide a standard security proof against curious stores and malicious customers. For efficiency concern, we build our protocol without cryptographic operations, and we achieve a linear asymptotic complexity of O (v + c) for communications and store-side computations, where v and c are the numbers of profiles in the store's back-end server and the shopper's list of preferences respectively. Moreover, experimental results and comparisons with state-of-the art solutions reveal the scalability of our novel PSI protocol for big market stores.
Beam-based vehicular position estimation in 5G radio access

Positioning is recognized as an important feature in cellular networks due to regulatory requirements on emergency calls, but also to its potential for massive commercial applications, such as intelligent transportation, entertainment, industry automation, robotics, remote operation, healthcare, smart parking, etc. The standardization of the fifth generation (5G) has started, and one fundamental feature is beamforming, where it is possible to support both connected and idle mode users via fixed or flexible beams. 5G positioning is yet to be defined, and in this paper we show positioning results based on data from beam tracking and uplink timing alignment in a 5G radio access testbed. This specific testbed is operating at a carrier frequency of 28 GHz and is deployed with multiple transmission points at a race track to show 5G performance at different vehicular speeds. In this paper, positioning is based on estimated angle of arrival (AoA) using the MUltiple SIgnal Classification (MUSIC) algorithm and estimated range using the uplink time alignment procedure. The position estimation is evaluated with Global Positioning System (GPS) data as reference. The evaluation studies show that horizontal position error at 70 percentile is 1 meter for 10 km/h tested speed and 3 meters for 120 km/h tested speed.
Preparation of TiO2/Carbon Nanotubes/Reduced Graphene Oxide Composites with Enhanced Photocatalytic Activity for the Degradation of Rhodamine B

In this report, ternary titanium dioxide (TiO2)/carbon nanotubes (CNTs)/reduced graphene oxide (rGO) composites were fabricated by a facile and environmentally friendly one-pot solvethermal method for the removal of Rhodamine B (RhB). Its structures were represented by X-ray powder diffraction (XRD), Raman spectrometry, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The photocatalytic performance was tested by the degradation efficiency of RhB under UV-vis light irradiation. The experimental results indicated that photocatalytic activity improved as the ratio of CNTs:TiO2 ranged from 0.5% to 3% but reduced when the content increased to 5% and 10%, and the TiO2/CNTs/rGO-3% composites showed superior photocatalytic activity compared with the binary ones (i.e., TiO2/CNTs, TiO2/rGO) and pristine TiO2. The rate constant k of the pseudo first-order reaction was about 1.5 times that of TiO2. The improved photocatalytic activity can be attributed to the addition of rGO and CNTs, which reduced the recombination of photo-induced electron-hole pairs, and the fact that CNTs and rGO, with a high specific surface area and high adsorption ability to efficiently adsorb O2, H2O and organics, can increase the hydroxyl content of the photocatalyst surface.
Novel DDM-OFDM-PON with Hybrid Sub-Nyquist Sampling Rates Featuring Heterogeneous ONUs with Different Capacities

We propose a delay-division-multiplexing-OFDM-PON (DDM-OFDM-PON) with hybrid sub-Nyquist sampling rates, wherein heterogeneous ONUs can request different capacities. 26-dB loss budget in 25-km 25-Gbps DDM-OFDM-PON was achieved using hybrid sampling at 1/32 / 1/16 / 1/8 or 1/32 / 1/8 / 1/2 Nyquist rates.
A three-stage buck in buck, boost in boost grid-tied inverter

A new type of buck in buck, boost in boost grid tied inverter is investigated. In this family of inverters only a single power stage works at high frequency at a time. This reduces the switching losses and hence improves efficiency. There is only minimum filtering inductance in the power loop and overfiltering does not take place. The operating modes of the inverter are analysed by equivalent circuits of various stages in a half-bridge configuration of the inverter. Investigation was furthered via a software simulation with pertinent observations. The closed loop simulation of a 230V, 50Hz, 4000W system with and without solar input and MPPT is included.
Using a knowledge graph for hypernymy detection between Chinese symptoms

Hypernymy relationship plays a critical role in language understanding because it enables generalization, which lies at the core of human cognition. As an important part of medical text understanding, Chinese symptom hypernymy detection is important for some medical applications, such as intelligent diagnosis, drug mining, and similar medical record analysis. However, there exists the problems that some symptoms are not included in the training data, and some pairs of symptoms do not appear in the same sentences when path-based methods are used. In light of that, we propose a new method which use a knowledge graph to detect Chinese symptom hypernymy relationship. Specifically, we first construct a symptom component knowledge graph, including atom-symptoms, body parts, headwords, and their synonyms and hypernyms. Then we use the constructed knowledge graph to standardize symptom pairs and detect hypernymy relationship between them. Experiments show that our method achieves state-of-the-art performance, with 98.90%, 87.25%, and 94.34% in Precision, Recall, and F-score, respectively.
Hazard ratio estimation and inference in clinical trials with many tied event times

The medical literature contains numerous examples of randomized clinical trials with time‐to‐event endpoints in which large numbers of events accrued over relatively short follow‐up periods, resulting in many tied event times. A generally common feature across such examples was that the logrank test was used for hypothesis testing and the Cox proportional hazards model was used for hazard ratio estimation. We caution that this common practice is particularly risky in the setting of many tied event times for two reasons. First, the estimator of the hazard ratio can be severely biased if the Breslow tie‐handling approximation for the Cox model (the default in SAS and Stata software) is used. Second, the 95% confidence interval for the hazard ratio can include one even when the corresponding logrank test p‐value is less than 0.05. To help establish a better practice, with applicability for both superiority and noninferiority trials, we use theory and simulations to contrast Wald and score tests based on well‐known tie‐handling approximations for the Cox model. Our recommendation is to report the Wald test p‐value and corresponding confidence interval based on the Efron approximation. The recommended test is essentially as powerful as the logrank test, the accompanying point and interval estimates of the hazard ratio have excellent statistical properties even in settings with many tied event times, inferential alignment between the p‐value and confidence interval is guaranteed, and implementation is straightforward using commonly used software.
FUSO: Fast Multi-Path Loss Recovery for Data Center Networks

To achieve low TCP flow completion time (FCT) in data center networks (DCNs), it is critical and challenging to rapidly recover loss without adding extra congestion. Therefore, in this paper, we propose a novel loss recovery approach fast multi-path loss recovery (FUSO) that exploits multi-path diversity in DCN for transport loss recovery. In FUSO, when a multi-path transport sender suspects loss on one sub-flow, recovery packets are immediately sent over another sub-flow that is not or less lossy <italic>and</italic> has spare congestion window slots. FUSO is <italic>fast</italic> in that it does not need to wait for timeout on the lossy sub-flow, and it is <italic>cautious</italic> in that it does not violate the congestion control algorithm. Testbed experiments and simulations show that FUSO decreases the latency-sensitive flows’ <inline-formula> <tex-math notation="LaTeX">$99^{th}$ </tex-math></inline-formula> percentile FCT by up to ~82.3% in a 1-Gb/s testbed, and up to ~87.9% in a 10 Gb/s large-scale simulated network.
Deficiency of host CD96 and PD-1 or TIGIT enhances tumor immunity without significantly compromising immune homeostasis

ABSTRACT Multiple non-redundant immunosuppressive pathways co-exist in the tumor microenvironment and their co-targeting can increase clinical responses. Indeed, concurrent blockade of CTLA-4 and PD-1 in patients with advanced melanoma increased clinical responses over monotherapy alone although the frequency and severity of immune related adverse events (irAEs) also increased. Nevertheless, a substantial number of patients still display an innate resistance phenotype and are unresponsive to current approved immunotherapies even when utilized in combination. In this study, we generated Pdcd1−/−CD96−/− and Tigit−/−CD96−/− mice to investigate how loss of CD96 in combination with PD-1 or TIGIT impacts on immune homeostasis and hence the potential of inducing immune related toxicities following co-targeting of these pairs of receptors. The ability of Pdcd1−/−CD96−/− and Tigit−/−CD96−/− mice to suppress primary tumor growth was also assessed using the MC38 colon carcinoma and SM1WT1 BRAF-mutated melanoma tumor models. Both Pdcd1−/−CD96−/− or Tigit−/−CD96−/− mice displayed no overt perturbations in immune homeostasis over what was previously reported with Pdcd1−/− or Tigit−/− mice even when aged for 22 months. Interestingly, increased suppression of subcutaneous tumor growth and complete responses was seen in Pdcd1−/−CD96−/− mice compared to Pdcd1−/− or CD96−/− mice depending upon the tumor model. In contrast, in these models, growth suppression in Tigit−/−CD96−/− were similar to Tigit−/− or CD96−/− . This enhanced anti-tumor efficacy of Pdcd1−/−CD96−/− appeared to be due to favorable changes in the ratio of CD8+ T cells to T regulatory cells or CD11b+GR-1hi myeloid cells in the tumor microenvironment. Co-targeting CD96 and PD-1 may increase anti-tumor immunity over targeting PD-1 alone and potentially not induce serious immune-related toxicities and thus appears a promising strategy for clinical development.
Healing Multimodal Confident Information Coverage Holes in NB-IoT-Enabled Networks

The Internet of Things (IoT) evolving from the conventional wireless sensor networks (WSNs) with more smart sensors has attracted significant attention. As one of the most crucial metrics for evaluating the quality of service (QoS) of both IoT and WSNs, sensing coverage characterizes the monitoring status of a sensing field of interest. However, the existence of coverage holes will remarkably degrade the QoS of the IoT. Based on the novel confident information coverage (CIC) model, this paper provides an in-depth study on how to energy-efficiently heal the multimodal CIC holes (MCICH) in a narrowband IoT (NB-IoT)-enabled hybrid IoT deployed for radiological pollution monitoring, where both mobile and stationary sensors equip multimodal sensing units for sensing dissimilar multimodal physical attributes and the NB-IoT provides satisfied network connectivity. We pinpoint the MCICH healing (MCICHH) problem with the objective of energy-efficiently dispatching a series of multimodal mobile IoT sensors to the CIC holes such that the MCIC holes can be headed and the CIC performance can be satisfied. After proving the NP-completeness of MCICHH by reducing it to the set partition problem, we develop a family of effective heuristic schemes including the centralized-MCICHH, the distributed-MCICHH and random CIC hole healing, all of which target for efficiently healing the MCIC holes while minimizing the total moving energy consumption of the dispatched multimodal mobile sensors or maximizing the average remaining energy of the multimodal mobile sensors. Extensive experiments verify the effectiveness and practicality of the proposed schemes.
An Inductive Linear Displacement Sensor Based on Planar Coils

This paper presents a non-contact inductive linear displacement sensor which is based on planar coils realized by the printed circuit board (PCB) technique. The sensor mainly consists of a ferromagnetic stator, a ferromag-netic mover, several excitation coil-PCBs, and a pickup coil-PCB. Excitation coil-PCBs are embedded in the mover and generate quadrature magnetic fields both in temporal- and spatial-domains. The stator and mover confine the magnetic fields to propagate between them. Pickup coil-PCB is located between the stator and mover to receive the magnetic fields and outputs a signal whose phase is proportional to the displacement of the mover. Simulations of a 3-D sensor model and final experiment of a prototype are introduced and both verify the feasibility of this sensor. In order to overcome inexact quadrature in spatial domain of magnetic fields caused by asymmetric mover structure, a simple but effective compensation method realized in temporal domain is employed by the prototype. Experimental results show that the prototype has original measurement error of less than 50 $\mu \text{m}$ in the range of 0 –208 mm, and moreover, the error is still of great regularity so that the sensor may have better performance if there is digital calibration for measurement data or improvement in sensor structure.
Fabric Defect Detection Based on Biological Vision Modeling

Fabric defect detection plays a key role in the quality control of textiles. Existing fabric defect detection methods adopt traditional pattern recognition methods; however, these methods lack adaptability and present poor detection performance. Because biological vision system has the ability to quickly locate salient objects, we propose a novel fabric defect detection algorithm based on biological vision modeling by simulating the mechanism of biological visual perception. First, a distinct, efficient, and robust feature descriptor from the biological modeling of P ganglion cells, which was proposed in our previous work, is adopted to improve the representation of fabric images with complex textures. To account for the low-rank and sparsity characteristics of biological vision, the low-rank representation (LRR) technique is adopted to model biological visual saliency, and it can decompose the fabric image into backgrounds and salient defect objects. Meanwhile, dictionary learning and Laplacian regularization are integrated into the LRR model as follows: 1) dictionary learning is used to denoise the saliency map; and 2) Laplacian regularization enlarges the gaps between defective regions and the background. Finally, the linearized accelerated direction method with adaptive penalty is adopted to solve the proposed model. The experimental results emphasize that the proposed algorithm has good detection performance for plain or twill fabrics with simple textures as well as for patterned fabrics with complex textures. Moreover, the proposed method is superior to the state-of-the-art methods in terms of its adaptability and detection efficiency.
Sampling Informative Training Data for RNN Language Models

We propose an unsupervised importance sampling approach to selecting training data for recurrent neural network (RNNs) language models. To increase the information content of the training set, our approach preferentially samples high perplexity sentences, as determined by an easily queryable n-gram language model. We experimentally evaluate the heldout perplexity of models trained with our various importance sampling distributions. We show that language models trained on data sampled using our proposed approach outperform models trained over randomly sampled subsets of both the Billion Word (Chelba et al., 2014 Wikitext-103 benchmark corpora (Merity et al., 2016).