Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of nerve in ultrasound images using U-net architecture

Surgery is undesirable because it is painful and often causes at least a short-term discomfort. Anesthesia is used for reducing the pain during the surgery. When the surgery involves only a local procedure, regional anesthesia is employed instead of total anesthesia. Regional Anesthesia consists of injecting the anesthetic in a nerve block as close to the nerve as possible in order to immobilize a part of the body. While human anatomy is known reasonably perfectly, it has been noticed that anatomy changes from person to person, making it impossible to know the exact location of a nerve. Ultrasound images provide some information on the anatomy of the particular patient under surgery, and it is possible to use this information for improving regional anesthesia. This paper considers the problem of detecting nerve in an ultrasound image of a part of the neck, known as Brachial Plexus. A supervised method is used in the form of artificial neural networks in order to develop a classification rule for the said purpose. A set of ultrasound images is used as the training set, while another set of similar images is used as the test set, and is used for cross-validation of the resulting classification. The images are pre-processed using Linear Gabor Binary Patterns (LGBP) before segmenting them, and the segments are then supplied to the ANN for developing the detection function.
Navigating the Host Cell Response during Entry into Sites of Latent Cytomegalovirus Infection

The host cell represents a hostile environment that viruses must counter in order to establish infection. Human cytomegalovirus (HCMV) is no different and encodes a multitude of functions aimed at disabling, re-directing or hijacking cellular functions to promulgate infection. However, during the very early stages of infection the virus relies on the outcome of interactions between virion components, cell surface receptors and host signalling pathways to promote an environment that supports infection. In the context of latent infection—where the virus establishes an infection in an absence of many gene products specific for lytic infection—these initial interactions are crucial events. In this review, we will discuss key host responses triggered by viral infection and how, in turn, the virus ameliorates the impact on the establishment of non-lytic infections of cells. We will focus on strategies to evade intrinsic antiviral and innate immune responses and consider their impact on viral infection. Finally, we will consider the hypothesis that the very early events upon viral infection are important for dictating the outcome of infection and consider the possibility that events that occur during entry into non-permissive cells are unique and thus contribute to the establishment of latency.
Nutrition and husbandry conditions of Palearctic tortoises (Testudo spp.) in captivity

ABSTRACT Mediterranean and Russian tortoises (Testudo spp.) are popular companion animals (pets), despite ongoing controversy concerning privately keeping reptiles. The arguments used during these controversial discussions have often been based on outdated facts. Therefore, a survey was developed to evaluate the current population structure, husbandry conditions, diet regime, and health status of Testudo species in captivity. More than 75% of the 1075 respondents housed their tortoises in an outdoor enclosure containing a greenhouse or cold frame, which is considered the most species-appropriate way of husbandry. Of the respondents, 67.7% fed their tortoises with the optimum diet of more than 80% grasses and weeds during the summer vegetation period. Only 8.2% of respondents owned a tortoise with a diagnosed disease. According to the results, the likelihood of tortoises developing pyramidal growth syndrome, which can be used as an indicator of the quality of tortoise husbandry, was high in tortoises kept in a terrarium and/or fed a diet of less than 80% grasses and weeds in summer. This likelihood varied among species, with a higher incidence in Hermann’s tortoises (Testudo hermanni).
Routing Around Congestion: Defeating DDoS Attacks and Adverse Network Conditions via Reactive BGP Routing

In this paper, we present Nyx, the first system to both effectively mitigate modern Distributed Denial of Service (DDoS) attacks regardless of the amount of traffic under adversarial control and function without outside cooperation or an Internet redesign. Nyx approaches the problem of DDoS mitigation as a routing problem rather than a filtering problem. This conceptual shift allows Nyx to avoid many of the common shortcomings of existing academic and commercial DDoS mitigation systems. By leveraging how Autonomous Systems (ASes) handle route advertisement in the existing Border Gateway Protocol (BGP), Nyx allows the deploying AS to achieve isolation of traffic from a critical upstream AS off of attacked links and onto alternative, uncongested, paths. This isolation removes the need for filtering or de-prioritizing attack traffic. Nyx controls outbound paths through normal BGP path selection, while return paths from critical ASes are controlled through the use of specific techniques we developed using existing traffic engineering principles and require no outside coordination. Using our own realistic Internet-scale simulator, we find that in more than 98% of cases our system can successfully route critical traf? c around network segments under transit-link DDoS attacks; a new form of DDoS attack where the attack traf? c never reaches the victim AS, thus invaliding defensive filtering, throttling, or prioritization strategies. More significantly, in over 95% of those cases, the alternate path provides complete congestion relief from transit-link DDoS. Nyx additionally provides complete congestion relief in over 75% of cases when the deployer is being directly attacked.
Traumatic Floating Bone. About 11 Cases and a Literature Review

Introduction: Floating bone injury or bipolar dislocation is a concurrent dislocation at both ends of a long bone or a flat bone. It is an exceptional injury. We report 11 consecutives cases of floating bones. Objectives: The aim of the study is to analyze the frequency, the mechanism of injury and clinical forms of floating bones, and to present the results of their management. Material and Methods: A ten years ongoing retrospective study was held in four trauma departments. Eleven cases of floating bones were identified. The floating bones characteristics such as the injured bone, the patient age and sex, the mechanism of injury, the dislocations directions, the associated complications, the treatment and the outcome were studied. Results: Nine male and two female patients, with a mean age of 37 years [19 - 65 years range] presented a concurrent bipolar dislocation of one bone or a group of bones. They sustained a road traffic accident (n = 5), a workplace accident (n = 3), a fall from height (n = 2), and a sport accident (n = 1). The clavicle (n = 3) and the first metatarsal (n = 3) were the most frequently involved. The others floating bones were the radius-ulna complex (n = 1), the radius-lunatum complex (n = 1), the first metacarpal (n = 1), the first phalanx (n = 1) and the femur (n = 1). The floating bones ends displacement occurred in the sagittal plane (the forearm, the femur, the first phalanx and the first metatarsal) and in the horizontal plane (the clavicle, the first metatarsal and the first metacarpal). We defined direction displacements as bidirectional asymmetric (n = 10) or unidirectional symmetric (n = 1). Associated complications were fractures (wrist, hip, tarso-metatarsal joints) and wounds (fingers, metatarso-phalangeal joint). Dislocations were treated conservatively (n = 5) and surgically (n = 17) with excellent results (n = 13/16 joints). Three patients were lost of view. Conclusion: Our study described the characteristics of this exceptional injury. For any joint dislocation, we promote the systematic examination of the other end of the dislocated bone.
Do police officers and firefighters have a higher risk of disease than other public officers? A 13-year nationwide cohort study in South Korea

Objectives The work of public officers involves repeated and long-term exposure to heavy workloads, high job strain and workplace violence, all of which negatively impact physical and mental health. This study aimed to evaluate and compare the incidences of diseases among different categories of public officers in Korea, in order to further understand the health risks associated with these occupations. Design A cohort study using the National Health Insurance data. Participants We collated claims data between 2002 and 2014 for 860 221 public officers. Primary and secondary outcome measures Age-standardised rates were calculated using the direct standardisation method, and HRs were calculated using the Cox proportional hazard regression models. Results Overall, we found that police officers and firefighters had a higher incidence of a range of diseases when compared with national and regional government officers (NRG). The most prominent HRs were observed among police officers for angina pectoris (HR: 1.52, 95% CI 1.49 to 1.54), acute myocardial infarction (HR: 1.84, 95% CI 1.77 to 1.92) and cerebrovascular disease (HR: 1.36, 95% CI 1.31 to 1.40). Firefighters were more susceptible to physical ailments and were at a significantly higher risk for traumatic stress disorders (HR: 1.40, 95% CI 1.26 to 1.56) than NRGs. Conclusion Compared withNRGs, police officers had higher HRs for all measured diseases, except for traumatic stress disorders. While firefighters had higher HRs for almost all diseases examined, public education officers had a higher HR for traumatic stress disorders, when compared with NRGs.
Electrochemical Estimation and Control for Lithium-Ion Battery Health-Aware Fast Charging

Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage the batteries. To harness these competing objectives, including safety, lifetime, and charging time, this paper proposes a health-aware fast charging strategy synthesized from electrochemical system modeling and advanced control theory. The battery charging problem is formulated in a linear time-varying model predictive control algorithm. In this algorithm, a control-oriented electrochemical–thermal model is developed to predict the system dynamics. Constraints are explicitly imposed on physically meaningful state variables to protect the battery from hazardous operations. A moving horizon estimation algorithm is employed to monitor battery internal state information. Illustrative results demonstrate that the proposed charging strategy is able to largely reduce the charging time from its benchmarks while ensuring the satisfaction of health-related constraints.
Residual Tensile Properties of GFRP Reinforcing Bars after Loading in Severe Environments

The long-term behavior of glass fiber-reinforced polymer (GFRP) reinforcing bars is one of the most critical issues for the acceptance of these materials as reinforcement for concrete structures. There is a high demand for experimental studies to investigate the stability of the tensile strength, ultimate elongation, and elasticity modulus. GFRP reinforcing bars inherently have a low elasticity modulus, which must not significantly decrease over time under loading or the serviceability behavior of the concrete element containing them will be jeopardized. This paper evaluates the residual tensile properties of three sizes of sand-coated GFRP reinforcing bars in alkaline and water environments combined with sustained loading and elevated temperature. Bar diameters of 15.9 (No. 5), 12.7 (No. 4), and 9.5 mm (No. 3) were loaded for different durations, then tested in axial tension for residual tensile properties. The test periods varied from 1 to 4 months under elevated temperature to hasten degradation and si.
Slow lorises (Nycticebus spp.) display evidence of handedness in the wild and in captivity

ABSTRACT It has been suggested that strepsirrhines (lemurs, lorises, and galagos) retain the more primitive left-hand preference, whilst monkeys and apes more regularly display a right-hand preference at the individual-level. We looked to address questions of laterality in the slow loris (Nycticebus spp.) using spontaneous observations of 7 wild individuals, unimanual tests in 6 captive individuals, and photos of 42 individuals in a bilateral posture assessing handedness at the individual- and group-level. During the unimanual reach task, we found at the individual-level, only 4 slow lorises showed a hand use bias (R: 3, L: 1), Handedness index (HI) ranged from −0.57 to 1.00. In the wild unimanual grasp task, we found at the individual-level two individual showed a right-hand bias, the HI ranged from −0.19 to 0.70. The bilateral venom pose showed a trend toward a right-hand dominant grip in those photographed in captivity, but an ambiguous difference in wild individuals. There are many environmental constraints in captivity that wild animals do not face, thus data collected in wild settings are more representative of their natural state. The presence of right-handedness in these species suggests that there is a need to re-evaluate the evolution of handedness in primates.
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks

Objective: Accelerated magnetic resonance (MR) image acquisition with compressed sensing (CS) and parallel imaging is a powerful method to reduce MR imaging scan time. However, many reconstruction algorithms have high computational costs. To address this, we investigate deep residual learning networks to remove aliasing artifacts from artifact corrupted images. Methods: The deep residual learning networks are composed of magnitude and phase networks that are separately trained. If both phase and magnitude information are available, the proposed algorithm can work as an iterative k-space interpolation algorithm using framelet representation. When only magnitude data are available, the proposed approach works as an image domain postprocessing algorithm. Results: Even with strong coherent aliasing artifacts, the proposed network successfully learned and removed the aliasing artifacts, whereas current parallel and CS reconstruction methods were unable to remove these artifacts. Conclusion: Comparisons using single and multiple coil acquisition show that the proposed residual network provides good reconstruction results with orders of magnitude faster computational time than existing CS methods. Significance: The proposed deep learning framework may have a great potential for accelerated MR reconstruction by generating accurate results immediately.
Regulation of NCAPG by miR‐99a‐3p (passenger strand) inhibits cancer cell aggressiveness and is involved in CRPC

Effective treatments for patients with castration‐resistant prostate cancer (CRPC) have not yet been established. Novel approaches for identification of putative therapeutic targets for CRPC are needed. Analyses of RNA sequencing of microRNA (miRNA) expression revealed that miR‐99a‐3p (passenger strand) is significantly downregulated in several types of cancers. Here, we aimed to identify novel miR‐99a‐3p regulatory networks and therapeutic targets for CRPC. Ectopic expression of miR‐99a‐3p significantly inhibited cancer cell proliferation, migration, and invasion in PCa cells. Non‐SMC condensin I complex subunit G (NCAPG) was a direct target of miR‐99a‐3p in PCa cells. Overexpression of NCAPG was detected in CRPC clinical specimens and was significantly associated with shorter disease‐free survival and advanced clinical stage. Knockdown of NCAPG inhibited cancer cell aggressiveness. The passenger strand miR‐99a‐3p acted as an antitumor miRNA in naïve PCa and CRPC. NCAPG was regulated by miR‐99a‐3p, and its overexpression was involved in CRPC pathogenesis. Involvement of passenger strand of miRNA in cancer pathogenesis is novel concept, and identification of antitumor miRNA regulatory networks in CRPC might be provided novel prognostic markers and therapeutic targets for this disease.
In-The-Wild Residual Data Research and Privacy

As the world becomes increasingly dependent on technology, researchers in both industry and academia endeavor to understand how technology is used, the impact it has on everyday life, the artifact life-cycle and overall integrations of digital information. In doing so, researchers are increasingly gathering 'real-world' or 'in-the-wild' residual data, obtained from a variety of sources, without the explicit consent of the original owners. This data gathering raises significant concerns regarding privacy, ethics and legislation, as well as practical considerations concerning investigator training, data storage, overall security and data disposal. This research surveys recent studies of residual data gathered in-the-wild and analyzes the challenges that were confronted. Amalgamating these insights, the research presents a compendium of practices for addressing the issues that can arise in-the-wild when conducting residual data research. The practices identified in this research can be used to critique current projects and assess the feasibility of proposed future research.
Learning Descriptor Networks for 3D Shape Synthesis and Analysis

This paper proposes a 3D shape descriptor network, which is a deep convolutional energy-based model, for modeling volumetric shape patterns. The maximum likelihood training of the model follows an "analysis by synthesis" scheme and can be interpreted as a mode seeking and mode shifting process. The model can synthesize 3D shape patterns by sampling from the probability distribution via MCMC such as Langevin dynamics. The model can be used to train a 3D generator network via MCMC teaching. The conditional version of the 3D shape descriptor net can be used for 3D object recovery and 3D object super-resolution. Experiments demonstrate that the proposed model can generate realistic 3D shape patterns and can be useful for 3D shape analysis.
Very low power event-based surface EMG acquisition system with off-the-shelf components

An acquisition system exploiting event-based approach applied to surface ElectroMyoGraphy (sEMG) was developed, with the goal of reducing the device size and minimizing the power consumption. The device has a modular four-channels architecture; each single acquisition module is characterized by a power consumption of 0.635 mW, a body area of 414 mm2 and a weight of 2 g, making it a good fit for wearable applications. In-vivo experiments have been conducted on 11 subjects, during isometric contraction with increasing load of the Biceps Brachii and Vastus Lateralis muscles. The device was able to discriminate different muscular activation levels, through the average number (over time) of threshold-crossing events, providing promising results in terms of correlation with the weight (median values of 0.97 and 0.95 respectively), compared to standard sEMG parameters described in literature.
Investigating the Configurations in Cross-Shareholding: A Joint Copula-Entropy Approach

The complex nature of the interlacement of economic actors is quite evident at the level of the Stock market, where any company may actually interact with the other companies buying and selling their shares. In this respect, the companies populating a Stock market, along with their connections, can be effectively modeled through a directed network, where the nodes represent the companies, and the links indicate the ownership. This paper deals with this theme and discusses the concentration of a market. A cross-shareholding matrix is considered, along with two key factors: the node out-degree distribution which represents the diversification of investments in terms of the number of involved companies, and the node in-degree distribution which reports the integration of a company due to the sales of its own shares to other companies. While diversification is widely explored in the literature, integration is most present in literature on contagions. This paper captures such quantities of interest in the two frameworks and studies the stochastic dependence of diversification and integration through a copula approach. We adopt entropies as measures for assessing the concentration in the market. The main question is to assess the dependence structure leading to a better description of the data or to market polarization (minimal entropy) or market fairness (maximal entropy). In so doing, we derive information on the way in which the in- and out-degrees should be connected in order to shape the market. The question is of interest to regulators bodies, as witnessed by specific alert threshold published on the US mergers guidelines for limiting the possibility of acquisitions and the prevalence of a single company on the market. Indeed, all countries and the EU have also rules or guidelines in order to limit concentrations, in a country or across borders, respectively. The calibration of copulas and model parameters on the basis of real data serves as an illustrative application of the theoretical proposal.
Polarity particles revisited

Claus et al. (2017) present novel experimental evidence concerning polarity particle responses in German, and discuss the challenges these findings raise for three approaches to such responses, namely the saliency approach of Krifka (20130, the feature model of Roelofsen and Farkas (2015), and the ellipsis approaches of Kramer and Rawlins (2012), and Holmberg (2016). The authors then sketch a way to account for the data within the feature model, as well as a revised version of the saliency account. The first goal of this paper is to work out in full detail an account of the new German data in the feature model. In the process, we will clarify and better articulate those aspects of the feature model that are responsible for how preference patterns are to be explained. Our second goal is to deepen the comparison between this model and the saliency approach by taking a wider cross-linguistic perspective. EARLY ACCESS
MEASURING THE EVOLUTIONARY RATE OF COOLING OF ZZ Ceti

We have finally measured the evolutionary rate of cooling of the pulsating hydrogen atmosphere (DA) white dwarf ZZ Ceti (Ross 548), as reflected by the drift rate of the 213.13260694 s period. Using 41 yr of time-series photometry from 1970 November to 2012 January, we determine the rate of change of this period with time to be dP/dt = (5.2 ± 1.4) × 10−15 s s−1 employing the O − C method and (5.45 ± 0.79) × 10−15 s s−1 using a direct nonlinear least squares fit to the entire lightcurve. We adopt the dP/dt obtained from the nonlinear least squares program as our final determination, but augment the corresponding uncertainty to a more realistic value, ultimately arriving at the measurement of dP/dt = (5.5 ± 1.0) × 10−15 s s−1. After correcting for proper motion, the evolutionary rate of cooling of ZZ Ceti is computed to be (3.3 ± 1.1) × 10−15 s s−1. This value is consistent within uncertainties with the measurement of (4.19 ± 0.73) × 10−15 s s−1 for another similar pulsating DA white dwarf, G 117-B15A. Measuring the cooling rate of ZZ Ceti helps us refine our stellar structure and evolutionary models, as cooling depends mainly on the core composition and stellar mass. Calibrating white dwarf cooling curves with this measurement will reduce the theoretical uncertainties involved in white dwarf cosmochronometry. Should the 213.13 s period be trapped in the hydrogen envelope, then our determination of its drift rate compared to the expected evolutionary rate suggests an additional source of stellar cooling. Attributing the excess cooling to the emission of axions imposes a constraint on the mass of the hypothetical axion particle.