Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Algorithms Improve the Detection of Subtle Lisfranc Malalignments on Weightbearing Radiographs

Background: Detection of Lisfranc malalignment leading to the instability of the joint, particularly in subtle cases, has been a concern for foot and ankle care providers. X-ray radiographs are the mainstay in the diagnosis of these injuries; thus, improving the performance of clinicians in interpreting radiographs can noticeably affect the quality of health care in these patients. Here we assessed the performance of deep learning algorithms on weightbearing radiographs for detection of Lisfranc joint malalignment in patients with Lisfranc instability. Methods: In a retrospective study, 640 patients with Lisfranc malalignment leading to instability were recruited plus 640 individuals with uninjured feet and healthy Lisfranc joint as the control group. All radiographs were screened by orthopaedic surgeons. Two deep learning models were trained, validated, and tested (in a ratio 80:10:10) using a single-view (anteroposterior) and 3-view (anteroposterior, lateral, oblique) radiographs. The performances of the models were reported as sensitivity, specificity, positive and negative predictive values, accuracy, F score, and area under the curve (AUC). Results: No significant differences were observed between the patients and the controls regarding age, gender, race, and body mass index. The best deep learning algorithm outperformed our human interpreters (<1% vs ~10% misdiagnosis), 94.8% sensitivity, 96.9% specificity, 98.6% accuracy, 95.8% F score, and 99.4% AUC. Conclusion: Deep learning methods have shown promising potential in acting as an assistant interpreter of radiographic images in patients with Lisfranc malalignment. Developing these algorithms can hasten and improve the accuracy of diagnosis and reduce further costs and burdens on the patients and health care system. Level of Evidence: Level III, case-control Machine Learning study.
Direct to Angiosuite Versus Conventional Imaging in Suspected Large Vessel Occlusion: A Systemic Review and Meta-Analysis

Background: There is growing evidence to suggest that the direct transfer to angiography suite (DTAS) approach for patients with suspected large vessel occlusion stroke potentially requiring mechanical thrombectomy shortens treatment times and improves outcomes compared with the direct transfer to conventional imaging (DTCI) model. Therefore, we conducted this meta-analysis to compare both approaches to build more concrete evidence to support this innovative treatment concept. Methods: All potentially relevant studies published in 4 electronic databases/search engines (PubMed, Web of Science, Cochrane Library, and Scopus) from inception to November 2021 were reviewed. Eligible studies were included if they enrolled ≥10 patients in both groups, were published in English, and reported baseline and procedural characteristics and outcomes. Relevant data were then extracted and analyzed. Results: Among 4514 searched studies, 7 qualified for the analysis with 1971 patients (DTAS=675, DTCI=1296). Times from door to puncture (mean difference, −30.76 minutes [95% CI, −43.70 to −17.82]; P<0.001) as well as door-to-reperfusion (mean difference=−33.24 minutes [95% CI, −51.82 to −14.66]; P<0.001) were significantly shorter and the rates of functional independence (modified Rankin Scale score, 0–2: risk ratio [RR], 1.25 [95% CI, 1.02–1.53]; P=0.03) at 90 days were higher in the DTAS versus the DTCI approach. There was no difference across the DTAS and DTCI groups in terms of the rates of successful reperfusion (modified Thrombolysis in Cerebral Infarction score 2B–3: RR, 1.03 [95% CI, 0.95–1.12]; P=0.42), near-complete/full reperfusion (modified Thrombolysis in Cerebral Infarction 2C–3: RR, 0.89 [95% CI, 0.74–1.08]; P=0.23), symptomatic intracranial hemorrhage (RR, 0.81 [95% CI, 0.56–1.17]; P=0.26), or fair outcomes (modified Rankin Scale score, 0–3: RR, 1.14 [95% CI, 0.88–1.47]; P=0.32) or mortality (RR, 0.98 [95% CI, 0.67–1.44]; P=0.93) at 90 days. Subgroup analysis showed no significant difference in 90-day functional independence across approaches in transfer patients (RR, 1.20 [95% CI, 0.96–1.51]; P=0.11). Conclusions: Our meta-analysis showed that the DTAS approach seems to be associated with improved time metrics and functional outcomes with comparable safety to the DTCI approach. Ongoing multicenter randomized clinical trials will hopefully provide more definite data about this promising approach.
Data-Efficient Off-Policy Learning for Distributed Optimal Tracking Control of HMAS With Unidentified Exosystem Dynamics

In this article, a data-efficient off-policy reinforcement learning (RL) approach is proposed for distributed output tracking control of heterogeneous multiagent systems (HMASs) using approximate dynamic programming (ADP). Different from existing results that the kinematic model of the exosystem is addressable to partial or all agents, the dynamics of the exosystem are assumed to be completely unknown for all agents in this article. To solve this difficulty, an identifiable algorithm using the experience-replay method is designed for each agent to identify the system matrices of the novel reference model instead of the original exosystem. Then, an output-based distributed adaptive output observer is proposed to provide the estimations of the leader, and the proposed observer not only has a low dimension and less data transmission among agents but also is implemented in a fully distributed way. Besides, a data-efficient RL algorithm is given to design the optimal controller offline along with the system trajectories without solving output regulator equations. An ADP approach is developed to iteratively solve game algebraic Riccati equations (GAREs) using online information of state and input in an online way, which relaxes the requirement of knowing prior knowledge of agents’ system matrices in an offline way. Finally, a numerical example is provided to verify the effectiveness of theoretical analysis.
Beneficial and toxicological aspects of zinc oxide nanoparticles in animals

Abstract Nanotechnology is a far‐reaching technology with tremendous applications in various aspects, including general medicine, veterinary medicine, agriculture, aquaculture, and food production. Nanomaterials have exceptional physicochemical characteristics, including increased intestinal absorption, biodistribution, bioavailability, and improved antimicrobial and catalytic properties. Although nanotechnology is gaining ground in animal management, husbandry, and production, its wide use is still hampered by occasional toxicity and side effects. Zinc oxide nanoparticles (ZnO‐NPs) have long been utilized in animal production, aquaculture, and pet animal medicine. However, the use ZnO‐NPs in animals has been associated with reports of toxicity and side effects. ZnO‐NPs may have shown numerous beneficial effects in animals; its use must be regulated with care to avoid unwanted consequences. Thus, this review emphasizes the usage of ZnO‐NPs in animal production and laboratory animals and the potential side effects associated with the use of nanoparticles as a feed supplement and therapeutic compound.
The effect of vitamin D replacement in patients with lower urinary tract complaint/erectile dysfunction resistant to Tadalafil 5 mg treatment: A pilot clinical study

The aim of this study was to evaluate the effect of vitamin D replacement in patients with lower urinary tract symptoms (LUTS)/erectile dysfunction (ED) who did not respond to tadalafil 5 mg treatment. Patients who applied to the Andrology Clinic with LUTS/ED between September 2017 and August 2020 and used 5 mg Tadalafil daily for treatment and did not benefit from treatment for 1 month were included in the study. Vitamin D levels of the patients were analysed and Vitamin D3 100,000 IU/week oral therapy was administered for a month to the patients with low levels of Vitamin D(<20 ng/ml). The values of the patients before and after Vitamin D replacement were compared. A total of 84 patients were included in the study. The mean age was 49.175 ± 11.63(28–70) years and the mean BMI was 25.93 ± 6.82(18.26–37.87). Testosterone levels of the examined patients were 3.45 ± 0.99 ng/ml. After 1 month of Vitamin D replacement + Tadalafil 5 mg/d treatment, the international index of erectile function–erectile function (IIEF‐EF) (pre‐treatment: 10.73 ± 6.12, post‐treatment: 24.18 ± 4.87; p = 0.001) and International Prostate Symptom Score (pre‐treatment: 9.12 ± 7.16, post‐treatment: 3.11 ± 1.08; p = 0.003) scores of the patients improved significantly. Evaluation of Vitamin D levels is important to improve treatment response, especially in patients who do not respond to PDE‐5 inhibitors.
A Home-based Tele-rehabilitation System With Enhanced Therapist-patient Remote Interaction: A Feasibility Study

As a promising alternative to hospital-based manual therapy, robot-assisted tele-rehabilitation therapy has shown significant benefits in reducing the therapist's workload and accelerating the patient's recovery process. However, existing telerobotic systems for rehabilitation face barriers to implementing appropriate therapy treatment due to the lack of effective therapist-patient interactive capabilities. In this paper, we develop a home-based tele-rehabilitation system that implements two alternative training methods, including a haptic-enabled guided training that allows the therapist to adjust the intensity of therapeutic movements provided by the rehabilitation device and a surface electromyography (sEMG)-based supervised training that explores remote assessment of the patient's kinesthetic awareness. Preliminary experiments were conducted to demonstrate the feasibility of the proposed alternative training methods and evaluate the functionality of the developed tele-rehabilitation system. Results showed that the proposed tele-rehabilitation system enabled therapist-in-the-loop to dynamically adjust the rehabilitation intensity and provided more interactivity in therapist-patient remote interaction.
EKG Signals – De-noising and Features Extraction

The need of effective method to obtain and analyse electrocardiogram (EKG) signal has inspired This research paper to designed an efficient algorithm that can handle any (EKG), remove the most dominant noises associated with it, and extract the important futures. EKG signal is an electrical signal represents the physical human’s heart activity. Nonetheless, this signal is affected by various noise including baseline wondering and power interference. These noises affect the signal to noise ratio (SNR) especially in P and T waves which have less amplitudes than R peaks. Removing these noises result in cleaner signal that can be conveniently processed to extract important features such as heart health condition. EKG features play the main role in diagnosing the heart rate, normality and abnormality of heart activities, and heart diseases. For a healthy person, one heart beat consists of P, QRS Complex, T, and in some signals U waves. In this paper, a robust and numerically sufficient algorithm is developed to de-nosing EKG signal and extract all major features. For de-nosing EKG signal, FIR Equiripple High pass filter is used. FIR Equiripple Low pass filter follows this filter to remove the power interference noises. Haar wavelet transform is used to accurately detect the R peaks. Haar wavelet is found to be better than other common methods that are used to detect R peaks. Haar wavelet shows high accuracy when it is applied on EKG signal to detect R peaks. In fact, it succeeded to detect all R peaks in hundreds of EKG signals (obtained from Physio net website). All other features are detected based on the R peaks by creating a set of windows which their lengths depend on the maximum normal wave durations and locations. These filters and algorithm have been implemented in Matlab. The algorithm has been applied on 108 EKG signals collected from physionet website and could detect all EKG signals’ heart rates successfully despite the fact that some signals were extremely distorted.
Norepinephrine activates β1‐adrenergic receptors at the inner nuclear membrane in astrocytes

Norepinephrine exerts powerful influences on the metabolic, neuroprotective and immunoregulatory functions of astrocytes. Until recently, all effects of norepinephrine were believed to be mediated by receptors localized exclusively to the plasma membrane. However, recent studies in cardiomyocytes have identified adrenergic receptors localized to intracellular membranes, including Golgi and inner nuclear membranes, and have shown that norepinephrine can access these receptors via transporter‐mediated uptake. We recently identified a high‐capacity norepinephrine transporter, organic cation transporter 3 (OCT3), densely localized to outer nuclear membranes in astrocytes, suggesting that adrenergic signaling may also occur at the inner nuclear membrane in these cells. Here, we used immunofluorescence and western blot to show that β1‐adrenergic receptors are localized to astrocyte inner nuclear membranes; that key adrenergic signaling partners are present in astrocyte nuclei; and that OCT3 and other catecholamine transporters are localized to astrocyte plasma and nuclear membranes. To test the functionality of nuclear membrane β1‐adrenergic receptors, we monitored real‐time protein kinase A (PKA) activity in astrocyte nuclei using a fluorescent biosensor. Treatment of astrocytes with norepinephrine induced rapid increases in PKA activity in the nuclear compartment. Pretreatment of astrocytes with inhibitors of catecholamine uptake blocked rapid norepinephrine‐induced increases in nuclear PKA activity. These studies, the first to document functional adrenergic receptors at the nuclear membrane in any central nervous system cell, reveal a novel mechanism by which norepinephrine may directly influence nuclear processes. This mechanism may contribute to previously described neuroprotective, metabolic and immunoregulatory actions of norepinephrine.
A supervised deep neural network approach with standardized targets for enhanced accuracy of IVIM parameter estimation from multi‐SNR images

Extraction of intravoxel incoherent motion (IVIM) parameters from noisy diffusion‐weighted (DW) images using a biexponential fitting model is computationally challenging, and the reliability of the estimated perfusion‐related quantities represents a limitation of this technique. Artificial intelligence can overcome the current limitations and be a suitable solution to advance use of this technique in both preclinical and clinical settings. The purpose of this work was to develop a deep neural network (DNN) approach, trained on numerical simulated phantoms with different signal to noise ratios (SNRs), to improve IVIM parameter estimation. The proposed approach is based on a supervised fully connected DNN having 3 hidden layers, 18 inputs and 3 targets with standardized values. 14 × 103 simulated DW images, based on a Shepp–Logan phantom, were randomly generated with varying SNRs (ranging from 10 to 100). 7 × 103 images (1000 for each SNR) were used for training. Performance accuracy was assessed in simulated images and the proposed approach was compared with the state‐of‐the‐art Bayesian approach and other DNN algorithms. The DNN approach was also evaluated in vivo on a high‐field MRI preclinical scanner. Our DNN approach showed an overall improvement in accuracy when compared with the Bayesian approach and other DNN methods in most of the simulated conditions. The in vivo results demonstrated the feasibility of the proposed approach in real settings and generated quantitative results comparable to those obtained using the Bayesian and unsupervised approaches, especially for D and f, and with lower variability in homogeneous regions. The DNN architecture proposed in this work outlines two innovative features as compared with other studies: (1) the use of standardized targets to improve the estimation of parameters, and (2) the implementation of a single DNN to enhance the IVIM fitting at different SNRs, providing a valuable alternative tool to compute IVIM parameters in conditions of high background noise.
Donor Acceptor Complexes between the Chalcogen Fluorides SF2, SeF2, SeF4 and TeF4 and an N‐Heterocyclic Carbene

Abstract The majority of binary chalcogen fluorides are fiercely reactive and extremely difficult to handle. Here, we show that access to crystalline donor‐acceptor complexes between chalcogen difluorides (sulfur, selenium) and tetrafluorides (selenium, tellurium) with the N‐heterocyclic carbene (NHC) 1,3‐bis(2,6‐diisopropylphenyl)imidazol‐2‐ylidene (IPr) is possible conveniently and safely without the need to generate the highly unstable EF2 (E=S, Se) or the very toxic and corrosive SeF4.
Bacterial Diversity and Community Structure of the Jujube Rhizosphere in Southern Xinjiang Uygur Autonomous Region, China

Jujube is an important economic crop in the Xinjiang Uygur Autonomous Region. Microbial diversity in the rhizosphere is essential for plant quality; however, soil bacterial diversity and community structure in the jujube rhizosphere have not been characterized in this region. In this study, we used pyrosequencing to analyze bacterial diversity and community structure at different growth stages in the jujube rhizosphere in Hetian, Kashi, and Aksu prefectures. These results revealed a greater bacterial diversity in the 8-year jujube rhizosphere as compared with the 3-year-old rhizosphere taken from the same sampling area. Moreover, samples obtained from Kashi prefecture showed the largest diversity among the different areas. The most abundant phyla across all soil samples were Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, and Firmicutes. Dominant phyla in the 8-year jujube rhizosphere accounted for the increased observed diversity. Furthermore, comparative analysis of the bacterial communities with respect to rhizosphere age and sampling areas revealed a significant correlation between soil properties and phyla diversity. To the best of our knowledge, this is the first study of jujube rhizosphere bacterial diversity and community structure in the southern Xinjiang Uygur Autonomous Region, and we hope that our research provides a reference for future studies.
The MAPS: Toward a Novel Mobility Assistance System for Visually Impaired People

This paper introduces the design of a novel indoor and outdoor mobility assistance system for visually impaired people. This system is named the MAPS (Mobility Assistance Path Planning and orientation in Space), and it is based on the theoretical frameworks of mobility and spatial cognition. Its originality comes from the assistance of two main functions of navigation: locomotion and wayfinding. Locomotion involves the ability to avoid obstacles, while wayfinding involves the orientation in space and ad hoc path planning in an (unknown) environment. The MAPS architecture proposes a new low-cost system for indoor–outdoor cognitive mobility assistance, relying on two cooperating hardware feedbacks: the Force Feedback Tablet (F2T) and the TactiBelt. F2T is an electromechanical tablet using haptic effects that allow the exploration of images and maps. It is used to assist with maps’ learning, space awareness emergence, path planning, wayfinding and effective journey completion. It helps a VIP construct a mental map of their environment. TactiBelt is a vibrotactile belt providing active support for the path integration strategy while navigating; it assists the VIP localize the nearest obstacles in real-time and provides the ego-directions to reach the destination. Technology used for acquiring the information about the surrounding space is based on vision (cameras) and is defined with the localization on a map. The preliminary evaluations of the MAPS focused on the interaction with the environment and on feedback from the users (blindfolded participants) to confirm its effectiveness in a simulated environment (a labyrinth). Those lead-users easily interpreted the system’s provided data that they considered relevant for effective independent navigation.
Retrospective comparisons of competing demographic models give clarity from “messy” management on a Scottish grouse moor

Abstract Retrospective comparison of predictive models that describe competing hypotheses regarding system function can shed light on regulatory mechanisms within the framework of adaptive resource management. We applied this approach to a 28‐year study of red grouse (Lagopus lagopus scotica) in Scotland, with the aims of reducing uncertainty regarding important drivers of grouse population dynamics, and of evaluating the efficacy of using seasonal versus annual model assessments. We developed three sets of models that predicted pre‐breeding and post‐breeding grouse density, matching the timing of grouse counts on the ground. We updated conditions and management through time in the spirit of a real‐time, adaptive management program and used a Bayesian model weight updating process to compare model predictions with empirical grouse densities. The first two model sets involved single annual updates from either pre‐breeding or post‐breeding counts; the third set was updated twice a year. Each model set comprised seven models representing increasingly complex hypotheses regarding potentially important drivers of grouse: the baseline model included weather and parasite effects on productivity, shooting losses and density‐dependent overwinter survival; subsequent models incorporated the effect of habitat gain/loss (HAB), control of non‐protected predators (NPP) and predation by protected hen harriers (Circus cyaneus, HH) and buzzards (Buteo buteo, BZ). The weight of evidence was consistent across model sets, settling within 10 years on the harrier (NPP + HH), buzzard (NPP + HH + BZ) and buzzard + habitat (NPP + HH + BZ + HAB) models, and downgrading the baseline + habitat, non‐protected predator, and non‐protected predator + habitat models. By the end of the study only the buzzard and buzzard + habitat models retained substantial weights, emphasizing the dynamical complexity of the system. Habitat inclusion failed to improve model predictions, implying that over the period of this study habitat quantity was unimportant in determining grouse abundance. Comparing annually and biannually assessed model sets, the main difference was in the baseline model, whose weight increased or remained stable when assessed annually, but collapsed when assessed biannually. Our adaptive modeling approach is suitable for many ecological situations in which a complex interplay of factors makes experimental manipulation difficult.
2 × VDD output buffer with 36.4% slew rate improvement using leakage current compensation

A 2 × VDD output buffer using leakage current compensation is demonstrated. With the proposed leakage current compensation circuit, the SR (slew rate) is improved 36.4-101.89% based on on-silicon measurement results given different VDDIO (1.0/1.2/1.8 V) and temperatures (from 0 to 100°C). The data rate is 510/630/400 MHz for VDDIO at 1.8/1.2/1.0 V, respectively. Moreover, the reliability problem, the gate oxide overstress and the hot carrier degradation is avoided. The proposed design is implemented using a typical 90 nm CMOS process. The active area is 0.425 × 0.0563 mm. The SR is measured in the range from 0.766 to 2.585 V/ns.