Miracle-dz/UniFAR-FTUs huggingface dataset:
Eye Bleeding Due to Leech Infestation in an Ischemic Heart- Disease Patient

A 49-year-old Iranian male with diagnosis of ischemic heart disease (IHD) and arterial hypertension (AH) was admitted at Emergency Ward of Vase’ee Hospital of Sabzevar, Iran. As well, the patient had red eye and left eye bleeding. On eye examination, leech infestation was found to be the cause of the eye bleeding. In the endemic regions in a patient presenting red eye and eye bleeding, leech infestation came up to be an important differential diagnosis. Therefore, to prevent leech infestation in endemic regions, local people are advised to be informed more effectively about the necessity to use safe, clean, and filtered drinking water, and a perfect scrutiny for leeches or other sources of infestation that should be undertaken before bathing.
Request generation for a peer-based PVR

Capacity planning, as well as protocol design and storage system design for video distribution systems are dependent on an understanding of the anticipated workload. Previous studies have focused on aggregate statistics of video popularity over time, and only recently has work been done which analyzes user behaviour variability over time. We are interested in a video storage/distribution system that uses peer resources to help content providers distribute video content to nodes in a network over long periods of time. Such a system is intended to operate on local principles of utility associated with each peer. More than ever, a workload model based on long-term user behaviour is required. In particular, it is unclear how request patterns driven by local utility can be shaped to match expected large-scale aggregate request characteristics such as a Zipf-distribution for overall popularity. In this paper, we describe early work in developing a workload generator for a Peer-based PVR (Personal Video Recorder) system to demonstrate some of these challenges.
Ellipsis: Functional Heads, Licensing, and Identification

Lobeck elaborates a theory of ellipsis which brings the phenomenon under the aegis of very general and universal principles. She argues that the Empty Category Principle (ECP) constrain the distribution of ellipsis just as it constrains the distributions of traces and null pronouns, which has implications not only for ellipsis but for the study of empty categories as well.
Temporal and spatial localization of prediction-error signals in the visual brain

It has been suggested that the brain pre-empts changes in the visual environment through generating predictions, although real-time eletrophysiological evidence of prediction violations remains elusive. In a series of experiments we showed participants sequences of images that followed a predictable implied sequence or whose final image violated the implied sequence. Through careful design we were able to use the same final image transitions across predictable and unpredictable conditions, ensuring that any differences in neural responses were due only to preceding context and not to the images themselves. EEG and MEG recordings showed that early/mid-latency visual evoked potentials were robustly modulated by images that violated the implied sequence across a range of types of image change (expression deformations, rigid-rotations and visual field location). This modulation occurred irrespective of stimulus object category. Although the stimuli were static images, MEG source reconstruction of the early latency signal (N/M170) localised expectancy violation signals to brain areas associated with motion perception. Our findings suggest that the N/M170 can index mismatches between predicted and actual visual inputs in a system that predicts trajectories based on ongoing context. This has important implications for understanding the N/M170 and investigating how the brain represents context to generate perceptual predictions.
Specific detection of Salmonella typhimurium proteins synthesized intracellularly

Studies of the proteins Salmonella typhimurium synthesizes under conditions designed to more closely approximate the in vivo environment, i.e., in cell and tissue culture, are not easily interpreted because they have involved chemical inhibition of host cell protein synthesis during infection. The method which we have developed allows specific labeling of bacterial proteins without interfering with host cell metabolic activities by using a labeled lysine precursor which mammalian cells cannot utilize. We have resolved the labeled proteins using two-dimensional electrophoresis and autofluorography. We were able to detect 57 proteins synthesized by S. typhimurium during growth within a human intestinal epithelial cell line. Of the 57 proteins detected, 34 appear to be unique to the intracellular environment, i.e., they are not seen during growth of the bacteria in tissue culture medium alone. Current (and future) efforts are directed at organizing the 34 proteins into known stress response groups, determining the cellular locations of the proteins (outer or inner membrane, etc.), and comparing the pattern of proteins synthesized within an intestinal epithelial cell to the pattern synthesized during growth within other tissues.
Predictive rule inference for epistatic interaction detection in genome-wide association studies

MOTIVATION Under the current era of genome-wide association study (GWAS), finding epistatic interactions in the large volume of SNP data is a challenging and unsolved issue. Few of previous studies could handle genome-wide data due to the difficulties in searching the combinatorially explosive search space and statistically evaluating high-order epistatic interactions given the limited number of samples. In this work, we propose a novel learning approach (SNPRuler) based on the predictive rule inference to find disease-associated epistatic interactions. RESULTS Our extensive experiments on both simulated data and real genome-wide data from Wellcome Trust Case Control Consortium (WTCCC) show that SNPRuler significantly outperforms its recent competitor. To our knowledge, SNPRuler is the first method that guarantees to find the epistatic interactions without exhaustive search. Our results indicate that finding epistatic interactions in GWAS is computationally attainable in practice. AVAILABILITY http://bioinformatics.ust. hk/SNPRuler.zip
Single-case and small-n experimental designs: a practical guide to randomization tests

There have been several sea changes in the ways that research has been conducted in the behavioural sciences. In the early days of psychology, for example, major discoveries were made by researchers using very small numbers of participants. Ebbinghaus (1885) established major features of human memory using just himself as subject; Pavlov discovered some important features of learning using a small number of animal subjects. Both researchers were meticulous in the design of experiments and in the recording of results (other notable examples of researchers whose work on small numbers of people generated entire research arenas include Freud’s work on psychoanalysis and Watson’s work on Behaviorism). Studies based on comparing a treatment group with an experimental group became dominant in the 1930s, following Fisher’s (1935) seminal work in statistics. Studies based on experimental and control groups are particularly useful when participants are homogeneous, when they can be assigned randomly to groups, and when standard treatments can be applied throughout the study. This is not always the case. In many situations, the focus is on an individual with a unique combination of characteristics for example, an individual with special educational needs, clinical problems, or a patient with neurological damage. In these situations, the focus of attention will be on detailed behavioural description, and interventions tailored to specific client needs. The research focus is on single cases, or on small numbers of people. Knowledge is built up from the analysis of a large collection of single case studies, rather than from studies involving groups of people. Adjacent measures of the performance of these individuals are rarely independent (for example, if a researcher is assessing a client’s emotional state at ten minute intervals, adjacent measures are likely to be similar) and so the assumptions underlying t and F tests are violated. This book sets out to offer a practical guide to randomisation tests for anyone who wants to analyse data from single case or small n experiments. It assumes a basic knowledge of statistics (e.g., of analysis of variance (ANOVA)), of the Statistical Reference
Informing ankle-foot prosthesis prescription through haptic emulation of candidate devices

Robotic prostheses can improve walking performance for amputees, but prescription of these devices has been hindered by their high cost and uncertainty about the degree to which individuals will benefit. The typical prescription process cannot well predict how an individual will respond to a device they have never used because it bases decisions on subjective assessment of an individual's current activity level. We propose a new approach in which individuals `test drive' candidate devices using a prosthesis emulator while their walking performance is quantitatively assessed and results are distilled to inform prescription. In this system, prosthesis behavior is controlled by software rather than mechanical implementation, so users can quickly experience a broad range of devices. To test the viability of the approach, we developed a prototype emulator and assessment protocol, leveraging hardware and methods we previously developed for basic science experiments. We demonstrated emulations across the spectrum of commercially available prostheses, including traditional (e.g. SACH), dynamic-elastic (e.g. FlexFoot), and powered robotic (e.g. BiOM® T2) prostheses. Emulations exhibited low error with respect to reference data and provided subjectively convincing representations of each device. We demonstrated an assessment protocol that differentiated device classes for each individual based on quantitative performance metrics, providing feedback that could be used to make objective, personalized device prescriptions.
Towards Practical Attacks on Argon2i and Balloon Hashing

The algorithm Argon2i-B of Biryukov, Dinu and Khovratovich is currently being considered by the IRTF (Internet Research Task Force) as a new de-facto standard for password hashing. An older version (Argon2i-A) of the same algorithm was chosen as the winner of the recent Password Hashing Competition. An important competitor to Argon2i-B is the recently introduced Balloon Hashing (BH) algorithm of Corrigan-Gibs, Boneh and Schechter. A key security desiderata for any such algorithm is that evaluating it (even using a custom device) requires a large amount of memory amortized across multiple instances. Alwen and Blocki (CRYPTO 2016) introduced a class of theoretical attacks against Argon2i-A and BH. While these attacks yield large asymptotic reductions in the amount of memory, it was not, a priori, clear if (1) they can be extended to the newer Argon2i-B, (2) the attacks are effective on any algorithm for practical parameter ranges (e.g., 1GB of memory) and (3) if they can be effectively instantiated against any algorithm under realistic hardware constrains. In this work we answer all three of these questions in the affirmative for all three algorithms. This is also the first work to analyze the security of Argon2i-B. In more detail, we extend the theoretical attacks of Alwen and Blocki (CRYPTO 2016) to the recent Argon2i-B proposal demonstrating severe asymptotic deficiencies in its security. Next we introduce several novel heuristics for improving the attack's concrete memory efficiency even when on-chip memory bandwidth is bounded. We then simulate our attacks on randomly sampled Argon2i-A, Argon2i-B and BH instances and measure the resulting memory consumption for various practical parameter ranges and for a variety of upperbounds on the amount of parallelism available to the attacker. Finally we describe, implement, and test a new heuristic for applying the Alwen-Blocki attack to functions employing a technique developed by Corrigan-Gibs et al. for improving concrete security of memory-hard functions. We analyze the collected data and show the effects various parameters have on the memory consumption of the attack. In particular, we can draw several interesting conclusions about the level of security provided by these functions. ● For the Alwen-Blocki attack to fail against practical memory parameters, Argon2i-B must be instantiated with more than 10 passes on memory — beyond the "paranoid" parameter setting in the current IRTF proposal. ● The technique of Corrigan-Gibs for improving security can also be overcome by the Alwen-Blocki attack under realistic hardware constraints. ● On a positive note, both the asymptotic and concrete security of Argon2i-B seem to improve on that of Argon2i-A.
Babesia bovis: lipids from virulent S2P and attenuated R1A strains trigger differential signalling and inflammatory responses in bovine macrophages

SUMMARY The intra-erythrocytic protozoan Babesia bovis is an economically important pathogen that causes an acute and often fatal infection in adult cattle. Babesiosis limitation depends on the early activation of macrophages, essential cells of the host innate immunity, which can generate an inflammatory response mediated by cytokines and nitric oxide (NO). Herein, we demonstrate in bovine macrophages that lipids from B. bovis attenuated R1A strain (LA) produced a stronger NO release, an early TNFα mRNA induction and 2-fold higher IL-12p35 mRNA levels compared to the lipids of virulent S2P strain (LV). Neither LA nor LV induced anti-inflammatory IL-10. Regarding signalling pathways, we here report that LA induced a significant phosphorylation of p38 and extracellular signal-regulated kinases 1 and 2 (ERK1/2) whereas LV only induced a reduced activation of ERK1/2. Besides, NF-κB was activated by LA and LV, but LA produced an early degradation of the inhibitor IκB. Interestingly, LV and the majority of its lipid fractions, exerted a significant inhibition of concanavalin A-induced peripheral blood mononuclear cell proliferation with respect to LA and its corresponding lipid fractions. In addition, we determined that animals infected with R1A developed a higher increase in IgM anti-phosphatidylcholine than those inoculated with S2P. Collectively, S2P lipids generated a decreased inflammatory response contributing to the evasion of innate immunity. Moreover, since R1A lipids induced a pro-inflammatory profile, we propose these molecules as good candidates for immunoprophylactic strategies against babesiosis.
Minutiae set to bit-string conversion using multi-scale bag-of-words paradigm

Minutiae-based matching is commonly used in fingerprint recognition systems due to its proven performance. However, such matching procedure usually involves unordered and variable size templates and it does not favour emerging bio-cryptography applications and most classifiers. This paper proposes a solution by converting the original minutiae set into a bit-string through the amalgamation of bag-of-words modelling, multi-scale construction and dynamic quantization. Experimental results show that the proposed method has high potential in biocryptography applications due to its outstanding EER of <; 0:51% and entropy of 723 bits. Further security and privacy concerns are also analyzed.
Giving at Risk? Examining Perceived Risk and Blood Donation Behaviour

This paper builds on previous research into blood donation behaviour, focusing on perceptions of risk associated with blood donation in the UK. It compares indicators of risk perceptions obtained through probability and importance indicators and calculated using additive versus multiplicative models. It examines the relationships between perceived risk and blood donation with specific attention to donation frequency. The findings demonstrate that apparent perceived risk in blood donation varies substantially depending on the indicator that is used and that a more accurate indicator of risk is obtained if two components of risk are combined through a multiplicative model rather than an additive one. Social risk emerged as the more prominent aspect of perceived risk, implying a high level of trust by donors in the Blood Transfusion Service. Perceived risk was found to be significantly associated with donation frequency, highlighting the need to keep track of donors and to communicate with those whose donations lapse.
Leukocytes in a Plasmodium falciparum-infected blood meal reduce transmission of malaria to Anopheles mosquitoes

Mosquitoes are infected with Plasmodium falciparum by taking a blood meal from a gametocyte carrier. Since a mosquito takes a volume of 1 to 2 microl, a blood meal may contain 1 x 10(4) to 3 x 10(4) leukocytes (WBC). The majority of WBC are composed of neutrophils which may phagocytose and kill developing gametes inside the mosquito midgut. Phagocytosis was measured in vitro by a luminol-dependent chemiluminescence (CL) assay. In the presence of P. falciparum gametes, sera from areas of endemicity had an increased CL response compared to controls. In mosquito membrane feeding experiments some such sera showed a transmission reduction which was related to the presence of viable WBC. The results of this study suggest that phagocytosis of opsonized gametes inside the mosquito midgut occurs and can contribute to a reduction in the transmission of P. falciparum parasites.
Application of fuzzy semantic similarity measures to event detection within tweets

This paper examines the suitability of applying fuzzy semantic similarity measures (FSSM) to the task of detecting potential future events through the use of a group of prototypical event tweets. FSSM are ideal measures to be used to analyse the semantic textual content of tweets due to the ability to deal equally with not only nouns, verbs, adjectives and adverbs, but also perception based fuzzy words. The proposed methodology first creates a set of prototypical event related tweets and a control group of tweets from a data source, then calculates the semantic similarity against an event dataset compiled from tweets issued during the 2011 London riots. The dataset of tweets contained a proportion of tweets that the Guardian Newspaper publically released that were attributed to 200 influential Twitter users during the actual riot. The effects of changing the semantic similarity threshold are investigated in order to evaluate if Twitter tweets can be used in conjunction with fuzzy short text similarity measures and prototypical event related tweets to determine if an event is more likely to occur. By looking at the increase in frequency of tweets in the dataset, over a certain similarity threshold when matched with prototypical event tweets about riots, the results have shown that a potential future event can be detected.
Priority-Aware Near-Optimal Scheduling for Heterogeneous Multi-Core Systems with Specialized Accelerators

To deliver high performance in power limited systems, architects have turned to using heterogeneous systems, either CPU+GPU or mixed CPU-hardware systems. However, in systems with different processor types and task affinities, scheduling tasks becomes more challenging than in homogeneous multi-core systems or systems without task affinities. The problem is even more complex when specialized accelerators and task priorities are included. In this paper, we provide a formal proof for the optimal scheduling policy for heterogeneous systems with arbitrary number of resource types, including specialized accelerators, independent of the task arrival rate, task size distribution, and resource processing order. We transform the optimal scheduling policy to a nonlinear integer optimization problem and propose a fast, near-optimal algorithm. An additional heuristic is proposed for the case of priority-aware scheduling. Our experimental results demonstrate that the proposed algorithm is only 0.3% from the optimal and superior to conventional scheduling policies.
An architecture for flexible auto-tuning: The Periscope Tuning Framework 2.0

Due to the complexity and diversity of new parallel architectures, automatic tuning of parallel applications has become increasingly important for achieving acceptable performance levels, as well as performance portability. The European AutoTune project developed a tuning framework that closely integrates and automates performance analysis and performance tuning. The Periscope Tuning Framework (PTF) relies on a flexible plugin mechanism and provides tuning plugins for various different tuning aspects. Each plugin provides codified expert knowledge for performance or energy efficiency tuning. PTF is able to tune serial and parallel codes for homogeneous and heterogeneous target hardware. The output of the framework is tuning recommendations that can be integrated into the production version of the code. In this paper, we present the latest development in the design of PTF aiming at (1) achieving higher portability and scalability by using the Score-P measurement infrastructure, (2) extending Score-P with tuning capabilities, (3) increasing analysis capabilities by providing new analysis strategies, and (4) increasing tuning capabilities by providing new plugins.
Synthesis and extracellular accumulation of silver nanoparticles by employing radiation-resistant Deinococcus radiodurans, their characterization, and determination of bioactivity

There has been rapid progress in exploring microorganisms for green synthesis of nanoparticles since microbes show extraordinary diversity in terms of species richness and niche localization. Microorganisms are easy to culture using relatively inexpensive and simple nutrients under varied conditions of temperature, pressure, pH, etc. In this work, Deinococcus radiodurans that possesses the ability to withstand extremely high radiation and desiccation stress has been employed for the synthesis of silver nanoparticles (AgNPs). D. radiodurans was able to accumulate AgNPs in medium under various conditions, and process optimization was carried out with respect to time, temperature, pH, and concentration of silver salt. AgNPs were characterized using UV/vis spectroscopy, scanning electron microscopy, transmission electron microscopy, X-ray diffraction, energy-dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy. The microbially synthesized AgNPs exhibited good antimicrobial activity against both Gram-negative and Gram-positive organisms and anti-biofouling activity. Their ability to inhibit growth and proliferation of cancer cell line was also examined, and it could be seen that AgNPs synthesized using D. radiodurans exhibited excellent anticancer activity.
Disaster scene reconstruction: modeling and simulating urban building collapse rubble within a game engine

Various natural and human-made events can occur in urban settings resulting in buildings collapsing and trapping victims. The task of a structural engineer is to survey the resulting rubble to assess its safety and arrange for structural stabilization, where necessary. Urban Search and Rescue (USAR) operations can then begin to locate and rescue people. Our previous work reported the use of an Unmanned Aerial Vehicle (UAV) equipped with a RGB-Depth sensor to build 3D point cloud models of disaster scenes. In this paper we extend this work by converting the point clouds into 3D models and importing them into a state-of-the-art game engine. We present a method to use these models to allow first responders to interact with the simulated rubble environment in real-time, without risk to human life. Experiments are conducted measuring traversal time both in the real world environment and using the simulation. We argue that this work will improve the safety of workers and allow a better understanding of extremely dangerous environments without unnecessary exposure during disaster response planning.