Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost-Effective Private Linear Key Agreement With Adaptive CCA Security from Prime Order Multilinear Maps and Tracing Traitors

Private linear key agreement (PLKA) enables a group of users to agree upon a common session key in a broadcast encryption (BE) scenario, while traitor tracing (TT) system allows a tracer to identify conspiracy of a troop of colluding pirate users. This paper introduces a key encapsulation mechanism in BE that provides the functionalities of both PLKA and TT in a unified cost-effective primitive. Our PLKA based traitor tracing offers a solution to the problem of achieving full collusion resistance property and public traceability simultaneously with significant efficiency and storage compared to a sequential improvement of the PLKA based traitor tracing systems. Our PLKA builds on a prime order multilinear group setting employing indistinguishability obfuscation (iO) and pseudorandom function (PRF). The resulting scheme has a fair communication, storage and computational efficiency compared to that of composite order groups. Our PLKA is adaptively chosen ciphertext attack (CCA)-secure and based on the hardness of the multilinear assumption, namely, the Decisional Hybrid Diffie-Hellman Exponent (DHDHE) assumption in standard model and so far a plausible improvement in the literature. More precisely, our PLKA design significantly reduces the ciphertext size, public parameter size and user secret key size. We frame a traitor tracing algorithm with shorter running time which can be executed publicly.
Word learning and the acquisition of syntactic-semantic overhypotheses

Children learning their first language face multiple problems of induction: how to learn the meanings of words, and how to build meaningful phrases from those words according to syntactic rules. We consider how children might solve these problems efficiently by solving them jointly, via a computational model that learns the syntax and semantics of multi-word utterances in a grounded reference game. We select a well-studied empirical case in which children are aware of patterns linking the syntactic and semantic properties of words --- that the properties picked out by base nouns tend to be related to shape, while prenominal adjectives tend to refer to other properties such as color. We show that children applying such inductive biases are accurately reflecting the statistics of child-directed speech, and that inducing similar biases in our computational model captures children's behavior in a classic adjective learning experiment. Our model incorporating such biases also demonstrates a clear data efficiency in learning, relative to a baseline model that learns without forming syntax-sensitive overhypotheses of word meaning. Thus solving a more complex joint inference problem may make the full problem of language acquisition easier, not harder.
Therapeutic Effects of Medicinal Plants on Cutaneous Wound Healing in Humans: A Systematic Review

The pharmaceutical industry has made great strides in providing drugs that are able to stimulate the healing process, but only 1–3% of all drugs that are listed in Western pharmacopoeias are intended for use on the skin or cutaneous wounds. Of these, at least one-third are obtained from plants. We sought to review the therapeutic effects of medicinal plants on human skin lesions. For this systematic review, we searched the PubMed, Scopus, and Web of Science databases to identify clinical trials that were published from 1997 to 2017. We reviewed studies that described the use of medicinal plants for the treatment of skin lesions in humans. Ten studies were selected, eight of which were published from 2007 to 2016, with a total of 503 patients. Among the plant species that were used for the treatment of human skin lesions, 12 belonged to 11 families and were included in the analysis. All of the plant species that were studied presented high therapeutic potential for the treatment of cutaneous lesions.
Resveratrol Protects Murine Chondrogenic ATDC5 Cells Against LPS-Induced Inflammatory Injury Through Up-Regulating MiR-146b

Background/Aims: Resveratrol (RSV) has been reported as a promising oral supplementation for osteoarthritis treatment, while the mechanism of its action is still unclear. The specific aim of this study is to decode one of the mechanisms by which RSV protects chondrocyte. Methods: Mouse chondrogenic cell line ATDC5 was treated with 30 µM RSV for 24 h, and 10 µg/ml LPS for 12 h, after which cell viability, apoptosis, and the release of pro-inflammatory cytokines were assessed. The expression of miR-146b in ATDC5 cells was silenced by the specific inhibitor transfection, and then cell viability, apoptosis and inflammation were re-assessed. Results: The IC50 value of LPS in ATDC5 cells was about 10.27 µg/ml. LPS with a dosage of 10 µg/ml repressed cell viability, induced apoptosis, and increased the release of IL-1β, IL-6 and TNF-α. RSV pre-treatment (30 µM) significantly alleviated LPS-induced apoptosis and inflammation. More importantly, miR-146b was up-regulated by RSV, and the protective functions of RSV on ATDC5 cells were attenuated by miR-146b silence. Further, NF-κB and p38MAPK pathways were activated by LPS, and were deactivated by RSV. Besides, RSV-induced the deactivation of NF-κB and p38MAPK pathways was reversed by miR-146b silence. Conclusions: Our findings suggest that RSV protects ATDC5 cells from LPS-induced inflammatory and apoptotic injury via up-regulation of miR-146b and thereby deactivation of NF-κB and p38MAPK pathways.
A credit risk model for Italian SMEs

We use a multiple-factor credit risk model to provide new estimates of default probabilities in a sample of Italian Small and Medium-sized Enterprises. Results show that, on average, SMEs are riskier than large businesses within the retail segment. It is possible to distinguish different segments inside the SMEs’ population based on geographical location, sector of activity and juridical status.
Parameter-sparse modification of Fourier methods to analyse the shape of closed contours with application to otolith outlines

Elliptical Fourier descriptors (EFDs) have been used extensively in shape analysis of closed contours and have a range of marine applications, such as automatic identification of fish species and discrimination between fish stocks based on EFDs of otolith contours. A recent method (the ‘MIRR’ method) transforms the two-dimensional contour to a one-dimensional function by mirroring (reflecting) the lower half of the contour around a vertical axis at the right end of the contour. MIRR then applies the fast Fourier transform (FFT) to the vertical contour points corresponding to equidistant coordinate values along the horizontal axis. MIRR has the advantage of reducing the number of Fourier coefficients to two coefficients per frequency component compared with four EFDs. However, both Fourier methods require several frequency components to reproduce a pure ellipse properly. This paper shows how the methods can be easily modified so that a virtually perfect reproduction of a pure ellipse is obtained with only one frequency component. In addition, real otolith examples for cod (Gadus morhua) and Greenland halibut (Reinhardtius hippoglossoides) are used to demonstrate that the modified methods give better approximations to the large-scale shape of the original contour with fewer coefficients than the traditional Fourier methods, with negligible additional computing time.
Feature learning with component selective encoding for histopathology image classification

In this paper, we present a new feature representation method, called the Component Selective Encoding (CSE), for automated histopathology image classification. While the integration of Fisher Vector (FV) encoding with convolutional neural network (CNN) has demonstrated excellent performance in the classification of both general texture and histopathology images, the high dimensionality of FV descriptors could lead to suboptimal performance. Our proposed CSE method provides effective dimensionality reduction that is adaptive to the discriminativeness of individual Gaussian components in the FV descriptors. Evaluation on the publicly available BreaKHis dataset shows that our method outperforms the existing approaches based on deep learning and FV encoding.
A review of vagus nerve stimulation as a therapeutic intervention

In this review, we provide an overview of the US Food and Drug Administration (FDA)-approved clinical uses of vagus nerve stimulation (VNS) as well as information about the ongoing studies and preclinical research to expand the use of VNS to additional applications. VNS is currently FDA approved for therapeutic use in patients aged >12 years with drug-resistant epilepsy and depression. Recent studies of VNS in in vivo systems have shown that it has anti-inflammatory properties which has led to more preclinical research aimed at expanding VNS treatment across a wider range of inflammatory disorders. Although the signaling pathway and mechanism by which VNS affects inflammation remain unknown, VNS has shown promising results in treating chronic inflammatory disorders such as sepsis, lung injury, rheumatoid arthritis (RA), and diabetes. It is also being used to control pain in fibromyalgia and migraines. This new preclinical research shows that VNS bears the promise of being applied to a wider range of therapeutic applications.
Cerebellar direct current stimulation modulates hand blink reflex: implications for defensive behavior in humans

The cerebellum is involved in a wide number of integrative functions. We evaluated the role of cerebellum in peripersonal defensive behavior, as assessed by the so‐called hand blink reflex (HBR), modulating cerebellar activity with transcranial direct current stimulation (tDCS). Healthy subjects underwent cerebellar (sham, anodal, and cathodal tcDCS) and motor cortex tDCS (anodal or cathodal; 20′, 2 mA). For the recording of HBR, electrical stimuli were delivered using a surface bipolar electrode placed on the median nerve at the wrist and EMG activity recorded from the orbicularis oculi muscle bilaterally. Depending on the hand position respective to the face, HBR was assessed in four different conditions: “hand‐far,” “hand‐near” (eyes open), “side hand,” and “hand‐patched” (eyes closed). While sham and cathodal cerebellar stimulation had no significant effect, anodal tcDCS dramatically dampened the magnitude of the HBR, as measured by the area under the curve (AUC), in the “hand‐patched” and “side hand” conditions only, for ipsilateral (F(4,171) = 15.08, P < 0.0001; F(4,171) = 8.95, P < 0.0001) as well as contralateral recordings (F(4,171) = 17.96, P < 0.0001); F4,171) = 5.35, P = 0.0004). Cerebellar polarization did not modify AUC in the “hand‐far” and “hand‐near” sessions. tDCS applied over the motor area did not affect HBR. These results seem to support a role of the cerebellum in the defensive responses within the peripersonal space surrounding the face, thus suggesting a possible cerebellar involvement in visual‐independent defensive behavior.
Combining electrospun nanofibers with cell-encapsulating hydrogel fibers for neural tissue engineering

Abstract A promising component of biomaterial constructs for neural tissue engineering are electrospun fibers, which differentiate stem cells and neurons as well as direct neurite growth. However, means of protecting neurons, glia, and stem cells seeded on electrospun fibers between lab and surgical suite have yet to be developed. Here we report an effort to accomplish this using cell-encapsulating hydrogel fibers made by interfacial polyelectrolyte complexation (IPC). IPC-hydrogel fibers were created by interfacing acid-soluble chitosan (AsC) and cell-containing alginate and spinning them on bundles of aligned electrospun fibers. Primary spinal astrocytes, cortical neurons, or L929 fibroblasts were mixed into alginate hydrogels prior to IPC-fiber spinning. The viability of each cell type was assessed at 30 min, 4 h, 1 d, and 7 d after encapsulation in IPC hydrogels. Some neurons were encapsulated in IPC-hydrogel fibers made from water-soluble chitosan (WsC). Neurons were also stained with Tuj1 and assessed for neurite extension. Neuron survival in AsC-fibers was worse than astrocytes in AsC-fibers (p < 0.05) and neurons in WsC-fibers (p < 0.05). As expected, neuron and glia survival was worse than L929 fibroblasts (p < 0.05). Neurons in IPC-hydrogel fibers fabricated with WsC extended neurites robustly, while none in AsC fibers did. Neurons remaining inside IPC-hydrogel fibers extended neurites inside them, while others de-encapsulated, extending neurites on electrospun fibers, which did not fully integrate with IPC-hydrogel fibers. This study demonstrates that primary neurons and astrocytes can be encapsulated in IPC-hydrogel fibers at good percentages of survival. IPC hydrogel technology may be a useful tool for encapsulating neural and other cells on electrospun fiber scaffolds.
Management of Candida infections in liver transplant recipients: current perspectives

: Liver transplantation has emerged as a widely accepted lifesaving therapeutic option for many patients with a variety of liver diseases. Improved surgical and medical management has led to significant improvements in post-transplant survival rates with a 1 year and 5 year patient survival of 87% and 73%, respectively. A high mortality rate due to infections during the first post-transplant year persists. Invasive candidiasis is recognized as a significant problem associated with high morbidity and mortality. Recent surveillance data has helped to understand the changes in the epidemiology and the evolving trends in the use of antifungal agents for prophylaxis and treatment combined with the challenges of managing these invasive fungal infections, which has led the transplant community to explore the best management strategies. The emergence of resistant fungi and excess costs in managing these invasive fungal infections has added to the complexities of management. In this context, current perspectives in the management of Candida infections in liver transplant recipients will be reviewed.
ProcHarvester: Fully Automated Analysis of Procfs Side-Channel Leaks on Android

The procfs has been identified as a viable source of side-channel information leaks on mobile devices. Starting with Android M (Android 6), access to the procfs has been continuously restricted in order to cope with these attacks. Yet, more recent papers demonstrated that even if access to process-specific information is restricted within the procfs, global statistics can still be exploited. However, with state-of-the-art techniques, the search for procfs information leaks requires a significant amount of manual work. This makes an exhaustive analysis of existing and newly introduced procfs resources in terms of information leaks impractical. We introduce ProcHarvester, a systematic and fully automated technique to assess procfs information leaks. ProcHarvester automatically triggers events of interest and later on applies machine learning techniques to identify procfs information leaks. We demonstrate the power of ProcHarvester by identifying information leaks to infer app starts from a set of 100 apps with an accuracy of 96% on Android N (Android 7). Thereby, we outperform the most accurate app inference attack by about 10 percentage points. We also demonstrate the ease of applicability of ProcHarvester by showing how to profile other events such as website launches as well as keyboard gestures, and we identify the first procfs side channels on Android O (Android 8). ProcHarvester advances investigations of procfs information leaks to the next level and will hopefully help to reduce the attack surface of side-channel attacks.
Prevalence of Ovine Fasciolosis in Adigrat, North East Ethiopia

A cross-sectional survey was conducted from November 2009 up to March 2010 to determine the prevalence of ovine fasciolosis in Adigrat, Tigray regional state, northeast Ethiopia. Two villages namely Sasun and Betehawariat were purposively selected considering the number of sheep population of the area. Parasitological examination of fecal samples randomly collected from 384 sheep revealed an overall fasciolosis prevalence of 39.5% (95% CI; 34.7-44.5%). The prevalence was higher in Betehawariat than in Sasun, in male animals than in females and in younger animals than adult ones; nevertheless, the differences were not statistically significant (P>0.05). With regard to the body condition of the animals, the prevalence was significantly higher (P<0.05) in those animals with poor body conditions than in those with good body conditions. Considering the huge negative effect of the parasite on health and productivity of the livestock sector, the results of our study suggests that the prevalence of fasciolosis in sheep in the current study was high. Hence, strategic parasite control method with an integrated approach is required to be implemented to improve the health and productivity of sheep in the area.
Improper Learning Equals Refutation — Theory of Machine Learning

Sample complexity is the information theoretical threshold on the number of samples required to learn. There is a vast body of literature showing that VC-dimension is the correct measure of sample complexity for learning, and Rademacher complexity is the correct measure if we are looking at finegrained distribution (and even, data) dependent sample complexity. However, the number of samples required to ‘efficiently’ learn can be significantly different from sample complexity, depending on the notion of efficiency involved. An extreme (and incredibly surprising) instructive example of this is a result of Ran Raz [3] that shows that learning parity under uniform distribution requires exponential samples if allowed less than n2/25 bits of space, while if allowed more than n2 bits, can be done in linear number of samples by simple Gaussian elimination.
On point processes in multitarget tracking

The finite-set statistics (FISST) approach to multitarget tracking was introduced in the mid-1990s. Its current extended form dates from 2001. In 2008, an "elementary" alternative to FISST was proposed, based on "finite point processes" rather than RFS's. This was accompanied by single-sensor and multisensor versions of a claimed generalization of the PHD filter, the "iFilter. " Then in 2013 in the Journal of Advances in Information Fusion (JAIF) and elsewhere, the same author went on to claim that the FISST p.g. fl. /functional derivative approach is actually "due to" (a "corollary" of) a 50-year-old pure-mathematics paper by Moyal; and described a "point process" p.g. fl. /functional derivative approach to multitarget tracking supposedly based on it. In this paper it is shown that: (1)non-RFS point processes are a phenomenologically erroneous foundation for multitarget tracking; (2) nearly every equation, concept, discussion, derivation, and methodology in the JAIF paper originally appeared in FISST publications, without being so attributed; (3) FISST cannot possibly be "due to Moyal"; (4) the "point process" approach described in JAIF differs from FISST only in regard to terminology and notation, and thus in this sense appears to be an obscured, phenomenologically erroneous, and improperly attributed copy of FISST. It is also shown that the derivations of the single-sensor and multisensory iFilter appear to have had major errors, as did a subsequent recasting of the multisensor iFilter as a "traffic mapping filter. "
Efficient Approximation for Streaming Video Processing Pipelines

Many video streaming applications require low-latency processing on resource-constrained devices. To meet the latency and resource constraints, developers must often approximate filter computations. A key challenge to successfully tuning approximations is finding the optimal configuration, which may change across and within the input videos because it is content-dependent. Searching through the entire search space for every frame in the video stream is infeasible, while tuning the pipeline offline, on a set of training videos, yields suboptimal results. We present VIDEOCHEF, a system for approximate optimization of video pipelines. VIDEOCHEF finds the optimal configurations of approximate filters at runtime, by leveraging the previously proposed concept of canary inputs—using small inputs to tune the accuracy of the computations and transferring the approximate configurations to full inputs. VIDEOCHEF is the first system to show that canary inputs can be used for complex streaming applications. The two key innovations of VIDEOCHEF are (1) an accurate error mapping from the approximate processing with downsampled inputs to that with full inputs and (2) a directed search that balances the cost of each search step with the estimated reduction in the run time. We evaluate our approach on 106 videos obtained from YouTube, on a set of 9 video processing pipelines with a total of 10 distinct filters. Our results show significant performance improvement over the baseline and the previous approach that uses canary inputs. We also perform a user study that shows that the videos produced by VIDEOCHEF are often acceptable to human subjects.
A lexical semantic hub for heteromodal naming in middle fusiform gyrus

Semantic memory underpins our understanding of objects, people, places, and ideas. Anomia, a disruption of semantic memory access, is the most common residual language disturbance and is seen in dementia and following injury to temporal cortex. While such anomia has been well characterized by lesion symptom mapping studies, its pathophysiology is not well understood. We hypothesize that inputs to the semantic memory system engage a specific heteromodal network hub that integrates lexical retrieval with the appropriate semantic content. Such a network hub has been proposed by others, but has thus far eluded precise spatiotemporal delineation. This limitation in our understanding of semantic memory has impeded progress in the treatment of anomia. We evaluated the cortical structure and dynamics of the lexical semantic network in driving speech production in a large cohort of patients with epilepsy using electrocorticography (n = 64), functional MRI (n = 36), and direct cortical stimulation (n = 30) during two generative language processes that rely on semantic knowledge: visual picture naming and auditory naming to definition. Each task also featured a non-semantic control condition: scrambled pictures and reversed speech, respectively. These large-scale data of the left, language-dominant hemisphere uniquely enable convergent, high-resolution analyses of neural mechanisms characterized by rapid, transient dynamics with strong interactions between distributed cortical substrates. We observed three stages of activity during both visual picture naming and auditory naming to definition that were serially organized: sensory processing, lexical semantic processing, and articulation. Critically, the second stage was absent in both the visual and auditory control conditions. Group activity maps from both electrocorticography and functional MRI identified heteromodal responses in middle fusiform gyrus, intraparietal sulcus, and inferior frontal gyrus; furthermore, the spectrotemporal profiles of these three regions revealed coincident activity preceding articulation. Only in the middle fusiform gyrus did direct cortical stimulation disrupt both naming tasks while still preserving the ability to repeat sentences. These convergent data strongly support a model in which a distinct neuroanatomical substrate in middle fusiform gyrus provides access to object semantic information. This under-appreciated locus of semantic processing is at risk in resections for temporal lobe epilepsy as well as in trauma and strokes that affect the inferior temporal cortex-it may explain the range of anomic states seen in these conditions. Further characterization of brain network behaviour engaging this region in both healthy and diseased states will expand our understanding of semantic memory and further development of therapies directed at anomia.