Miracle-dz/UniFAR-FTUs huggingface dataset:
A soft robotic exosuit improves walking in patients after stroke

Soft exosuits facilitate more normal walking after stroke. A softer recovery after stroke Passive assistance devices such as canes and braces are often used by people after stroke, but mobility remains limited for some patients. Awad et al. studied the effects of active assistance (delivery of supportive force) during walking in nine patients in the chronic phase of stroke recovery. A soft robotic exosuit worn on the partially paralyzed lower limb reduced interlimb propulsion asymmetry, increased ankle dorsiflexion, and reduced the energy required to walk when powered on during treadmill and overground walking tests. The exosuit could be adjusted to deliver supportive force during the early or late phase of the gait cycle depending on the patient’s needs. Although long-term therapeutic studies are necessary, the immediate improvement in walking performance observed using the powered exosuit makes this a promising approach for neurorehabilitation. Stroke-induced hemiparetic gait is characteristically slow and metabolically expensive. Passive assistive devices such as ankle-foot orthoses are often prescribed to increase function and independence after stroke; however, walking remains highly impaired despite—and perhaps because of—their use. We sought to determine whether a soft wearable robot (exosuit) designed to supplement the paretic limb’s residual ability to generate both forward propulsion and ground clearance could facilitate more normal walking after stroke. Exosuits transmit mechanical power generated by actuators to a wearer through the interaction of garment-like, functional textile anchors and cable-based transmissions. We evaluated the immediate effects of an exosuit actively assisting the paretic limb of individuals in the chronic phase of stroke recovery during treadmill and overground walking. Using controlled, treadmill-based biomechanical investigation, we demonstrate that exosuits can function in synchrony with a wearer’s paretic limb to facilitate an immediate 5.33 ± 0.91° increase in the paretic ankle’s swing phase dorsiflexion and 11 ± 3% increase in the paretic limb’s generation of forward propulsion (P < 0.05). These improvements in paretic limb function contributed to a 20 ± 4% reduction in forward propulsion interlimb asymmetry and a 10 ± 3% reduction in the energy cost of walking, which is equivalent to a 32 ± 9% reduction in the metabolic burden associated with poststroke walking. Relatively low assistance (~12% of biological torques) delivered with a lightweight and nonrestrictive exosuit was sufficient to facilitate more normal walking in ambulatory individuals after stroke. Future work will focus on understanding how exosuit-induced improvements in walking performance may be leveraged to improve mobility after stroke.
A Novel Method to Adjust Efficacy Estimates for Uptake of Other Active Treatments in Long-Term Clinical Trials

Background When rates of uptake of other drugs differ between treatment arms in long-term trials, the true benefit or harm of the treatment may be underestimated. Methods to allow for such contamination have often been limited by failing to preserve the randomization comparisons. In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study, patients were randomized to fenofibrate or placebo, but during the trial many started additional drugs, particularly statins, more so in the placebo group. The effects of fenofibrate estimated by intention-to-treat were likely to have been attenuated. We aimed to quantify this effect and to develop a method for use in other long-term trials. Methodology/Principal Findings We applied efficacies of statins and other cardiovascular drugs from meta-analyses of randomized trials to adjust the effect of fenofibrate in a penalized Cox model. We assumed that future cardiovascular disease events were reduced by an average of 24% by statins, and 20% by a first other major cardiovascular drug. We applied these estimates to each patient who took these drugs for the period they were on them. We also adjusted the analysis by the rate of discontinuing fenofibrate. Among 4,900 placebo patients, average statin use was 16% over five years. Among 4,895 assigned fenofibrate, statin use was 8% and nonuse of fenofibrate was 10%. In placebo patients, use of cardiovascular drugs was 1% to 3% higher. Before adjustment, fenofibrate was associated with an 11% reduction in coronary events (coronary heart disease death or myocardial infarction) (P = 0.16) and an 11% reduction in cardiovascular disease events (P = 0.04). After adjustment, the effects of fenofibrate on coronary events and cardiovascular disease events were 16% (P = 0.06) and 15% (P = 0.008), respectively. Conclusions/Significance This novel application of a penalized Cox model for adjustment of a trial estimate of treatment efficacy incorporates evidence-based estimates for other therapies, preserves comparisons between the randomized groups, and is applicable to other long-term trials. In the FIELD study example, the effects of fenofibrate on the risks of coronary heart disease and cardiovascular disease events were underestimated by up to one-third in the original analysis. Trial Registration Controlled-Trials.com ISRCTN64783481
Characterization of Copper-doped Silicon Dioxide Programmable Metallization Cells

follow Programmable Metallization Cell (PMC) is a resistance-switching device based on migration of nanoscale quantities of cations in a solid electrolyte and formation of a conducting electrodeposit by the reductions of these cations. This dissertation presents electrical characterization results on Cu-SiO2 based PMC devices, which due to the nature of materials can be easily integrated into the current Complimentary metal oxide semiconductor (CMOS) process line. Device structures representing individual memory cells based on W bottom electrode and n-type Si bottom electrode were fabricated for characterization. For the W bottom electrode based devices, switching was observed for voltages in the range of 500mV and current value as low as 100 nA showing the electrochemical nature and low power potential. The ON state showed a direct dependence on the programming current, showing the possibility of multi-bit storage in a single cell. Room temperature retention was demonstrated in excess of 105 seconds and endurance to approximately 107 cycles. Switching was observed for microsecond duration 3 V amplitude pulses. Material characterization results from Raman, X-ray diffraction, Rutherford backscattering and Secondary-ion mass spectroscopy analysis shows the influence of processing conditions on the Cu concentration within the film and also the presence of Cu as free atoms. The results seemed to indicate stress-induced void formation in the SiO2 matrix as the driving mechanism for Cu diffusion into the SiO2 film. Cu/SiO2/nSi based PMC devices were characterized and were shown to have inherent isolation characteristics, proving the feasibility of such a structure for a passive array. The inherent isolation property simplifies fabrication by avoiding the need for a separate diode element in an array. The isolation characteristics were studied mainly in terms of the leakage current. The nature of the diode interface was further studied by extracting a barrier potential which shows it can be approximated to a Cu-nSi metal semiconductor Schottky diode.
Review of the ENCHANTED Trial (Enhanced Control of Hypertension and Thrombolysis Stroke Study): How Low Can We Go With Intravenous Tissue-Type Plasminogen Activator Dose and Blood Pressure Level?

ENCHANTED (Enhanced Control of Hypertensionn and Thrombolysis Stroke Study) was a 2-by-2 quasi-factorial, open-label, noninferiority trial assigning randomly 3310 thrombolysis-eligible patients to low-dose intravenous alteplase (0.6 mg/kg body weight) or to standard dose (0.9 mg per kilogram of body weight). The reported arm of the trial also included 935 patients who were randomly assigned to intensive or guideline-recommended blood pressure management.1 The investigators pointed out that surprisingly little research on the optimal dose of alteplase was conducted compared with cardiovascular studies using thrombolytic therapy and that the standard dose for the NINDS trial (National Institute of Neurological Disorders and Stroke) was chosen on the basis of small pilot dose-escalation studies.2 Furthermore, the Japanese drug authority has approved the lower dose based on an uncontrolled open-label study showing equivalent outcomes and lower frequency of intracerebral hemorrhagic complications compared with the standard dose. Other Asian registry studies showed inconsistent results. However, it would seem that one important aspect driving the idea of the lower dose was affordability of the treatment, and the investigators stated that low-dose alteplase has become a low-cost and possibly safer option for patients who cannot afford the standard dose or are elderly.3 The primary objective of the ENCHANTED trial was to show noninferiority of the low dose compared with the standard one (3-month disability or death, modified Rankin scale score of 2–6). In contrast to equivalence or superiority trials, the noninferiority trials try to show that the tested treatment is not …
More Rounds, Less Security?

This paper focuses on a surprising class of cryptanalysis results for symmetric-key primitives: when the number of rounds of the primitive is increased, the complexity of the cryptanalysis result decreases. Our primary target will be primitives that consist of identical round functions, such as PBKDF1, the Unix password hashing algorithm, and the Chaskey MAC function. However, some of our results also apply to constructions with non-identical rounds, such as the PRIDE block cipher. First, we construct distinguishers for which the data complexity decreases when the number of rounds is increased. They are based on two well-known observations: iterating a random permutation increases the expected number of fixed points, and iterating a random function decreases the expected number of image points. We explain that these effects also apply to components of cryptographic primitives, such as a round of a block cipher. Second, we introduce a class of key-recovery and preimage-finding techniques that correspond to exhaustive search, however on a smaller part (e.g. one round) of the primitive. As the time complexity of a cryptanalysis result is usually measured by the number of full-round evaluations of the primitive, increasing the number of rounds will lower the time complexity. None of the observations in this paper result in more than a small speed-up over exhaustive search. Therefore, for lightweight applications, implementation advantages may outweigh the presence of these observations.
Genomic typing and phylogenetic analysis of canine parvovirus detected in the state of Odisha, India.

Canine parvovirus type 2 (CPV-2) comprises three major antigenic variants CPV-2a, CPV-2b and CPV-2c. Their mutated variants in geographically distinct locations need to be investigated to understand viral evolution and for development of effective management measures. In the present study, 71 faecal and 12 blood samples from suspected dogs in the state of Odisha, India were analyzed by PCR. Faecal lysate, extracted by the fast boiling method was found to be more sensitive as a template for PCR compared to DNA extracted from faecal samples by the phenol-chloroform method. The results revealed 29 positive cases (583 bp amplicon) out of 71 faecal samples, and 5 positive cases out of 12 blood samples examined, with a few variations in the results from blood and faecal samples in the same cases, thus suggesting the necessity of screening both blood and faecal samples for diagnosis. Restriction digestion of the 583 bp PCR amplicon with MboII (PCR-RFLP) confirmed the strain not to be CPV-2c. Further sequencing of the 583 bp fragments recognized the variant as one of the mutated CPV-2a strain. Interestingly, an additional presence of CPV-2a mutant of 525 bp was observed in eleven *Corresponding author: Dr. Monalisa Behera, PhD Scholar, Department of Veterinary Pathology, College of Veterinary Science and Animal Husbandry, Orissa University of Agriculture and Technology, Bhubaneswar-751003, Odisha, India, Phone: +91 943 820 8810; E-mail: drmonalisabehera@gmail.com
Shadow-Routing Based Dynamic Algorithms for Virtual Machine Placement in a Network Cloud

We consider a <italic>shadow routing</italic> based approach to the problem of real-time adaptive placement of virtual machines (VM) in large data centers (DC) within a network cloud. Such placement in particular has to respect <italic>vector packing</italic> constraints on the allocation of VMs to host physical machines (PM) within a DC, because each PM can potentially serve multiple VMs simultaneously. Shadow routing is attractive in that it allows a large variety of system objectives and/or constraints to be treated within a common framework (as long as the underlying optimization problem is convex). Perhaps even more attractive feature is that the corresponding algorithm is very simple to implement, it runs continuously, and adapts automatically to changes in the VM demand rates, changes in system parameters, etc., without the need to re-solve the underlying optimization problem “from scratch”. In this paper we focus on the <italic>min-max-DC-load</italic> problem. Namely, we propose a combined VM-to-DC routing and VM-to-PM assignment algorithm, referred to as <italic>Shadow scheme</italic>, which minimizes the maximum of appropriately defined DC utilizations. We prove that the Shadow scheme is asymptotically optimal (as one of its parameters goes to <inline-formula><tex-math notation="LaTeX">$0$</tex-math><alternatives> <inline-graphic xlink:href="guo-ieq1-2464795.gif"/></alternatives></inline-formula>). Simulation confirms good performance and high adaptivity of the algorithm. Favorable performance is also demonstrated in comparison with a baseline algorithm based on VMware implementation <xref ref-type="bibr" rid="ref7">[7]</xref> , <xref ref-type="bibr" rid="ref8">[8]</xref> . We also propose a simplified – “more distributed” – version of the Shadow scheme, which performs almost as well in simulations.
Stacked Hourglass Network for Robust Facial Landmark Localisation

With the increasing number of public available training data for face alignment, the regression-based methods attracted much attention and have become the dominant methods to solve this problem. There are two main factors, the variance of the regression target and the capacity of the regression model, affecting the performance of the regression task. In this paper, we present a Stacked Hourglass Network for robust facial landmark localisation. We first adopt a supervised face transformation to remove the translation, scale and rotation variation of each face, in order to reduce the variance of the regression target. Then we employ a deep convolutional neural network named Stacked Hourglass Network to increase the capacity of the regression model. To better evaluate the proposed method, we reimplement two popular cascade shape regression models, SDM and LBF, for comparison. Extensive experiments on four challenging datasets prove the effectiveness of the proposed method.
Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor

A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver’s point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR)-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR) camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB). The proposed method demonstrated greater accuracy than the previous gaze classification methods.
A Man-Made ATP-Binding Protein Evolved Independent of Nature Causes Abnormal Growth in Bacterial Cells

Recent advances in de novo protein evolution have made it possible to create synthetic proteins from unbiased libraries that fold into stable tertiary structures with predefined functions. However, it is not known whether such proteins will be functional when expressed inside living cells or how a host organism would respond to an encounter with a non-biological protein. Here, we examine the physiology and morphology of Escherichia coli cells engineered to express a synthetic ATP-binding protein evolved entirely from non-biological origins. We show that this man-made protein disrupts the normal energetic balance of the cell by altering the levels of intracellular ATP. This disruption cascades into a series of events that ultimately limit reproductive competency by inhibiting cell division. We now describe a detailed investigation into the synthetic biology of this man-made protein in a living bacterial organism, and the effect that this protein has on normal cell physiology.
Medication discrepancies across multiple care transitions: A retrospective longitudinal cohort study in Italy

Purpose Medication discrepancies are defined as unexplained differences among regimens across different sites of care. The problem of medication discrepancies that occur during the entire care pathway from hospital admission to a local care setting discharge (namely all types of settings dedicated to formal care other than hospitals) has received little attention in the medical literature. The present study aims to (1) determine the prevalence of medication discrepancies that occur during the entire care pathway from hospital admission to local care setting discharge, (2) describe the discrepancy and medication type, and (3) identify potential risk factors for experiencing medication discrepancies in patient care transitions. Evidence from an integrated health care system, such as the Italian one, may explain results from other studies in different healthcare systems. Methods A retrospective longitudinal cohort study of patients admitted from July 2015 to July 2016 to the Giovanni Bosco Hospital serving Turin, Italy and its surrounding territory was performed. Discrepancies were recorded at the following four care transitions: T1: Hospital admission; T2: Hospital discharge; T3: Admission into local care settings; T4: Discharge from local care settings. All evaluations were based on documented regimens and were performed by a team (doctor, nurse and pharmacists). Results Of 366 included patients, 25.68% had at least one discrepancy. The most frequent type of discrepancy was from medication omission (N = 74; 71.15%). Only discharge from a long-stay care setting (T4) was significantly associated with the onset of discrepancies (p = 0.045). When considering a lack of adequate documentation, not as missing data but as a discrepancy, 43.72% of patients had at least one discrepancy. Conclusions This study suggests that an integrated health care system, such as Italian system, may influence the prevalence of discrepancies, thus highlighting the need for structured multidisciplinary and, if possible, computerized medication reconciliation to prevent medication discrepancies and improve the quality of medical documentation.
Tactile-Sensing Based on Flexible PVDF Nanofibers via Electrospinning: A Review

The flexible tactile sensor has attracted widespread attention because of its great flexibility, high sensitivity, and large workable range. It can be integrated into clothing, electronic skin, or mounted on to human skin. Various nanostructured materials and nanocomposites with high flexibility and electrical performance have been widely utilized as functional materials in flexible tactile sensors. Polymer nanomaterials, representing the most promising materials, especially polyvinylidene fluoride (PVDF), PVDF co-polymer and their nanocomposites with ultra-sensitivity, high deformability, outstanding chemical resistance, high thermal stability and low permittivity, can meet the flexibility requirements for dynamic tactile sensing in wearable electronics. Electrospinning has been recognized as an excellent straightforward and versatile technique for preparing nanofiber materials. This review will present a brief overview of the recent advances in PVDF nanofibers by electrospinning for flexible tactile sensor applications. PVDF, PVDF co-polymers and their nanocomposites have been successfully formed as ultrafine nanofibers, even as randomly oriented PVDF nanofibers by electrospinning. These nanofibers used as the functional layers in flexible tactile sensors have been reviewed briefly in this paper. The β-phase content, which is the strongest polar moment contributing to piezoelectric properties among all the crystalline phases of PVDF, can be improved by adjusting the technical parameters in electrospun PVDF process. The piezoelectric properties and the sensibility for the pressure sensor are improved greatly when the PVDF fibers become more oriented. The tactile performance of PVDF composite nanofibers can be further promoted by doping with nanofillers and nanoclay. Electrospun P(VDF-TrFE) nanofiber mats used for the 3D pressure sensor achieved excellent sensitivity, even at 0.1 Pa. The most significant enhancement is that the aligned electrospun core-shell P(VDF-TrFE) nanofibers exhibited almost 40 times higher sensitivity than that of pressure sensor based on thin-film PVDF.