Miracle-dz/UniFAR-FTUs huggingface dataset:
Modified topology-hiding multipath routing (M-THMR) protocol: Solution to the topology exposure problem in MANET

In the past few years MANETs had widespread usage in different applications. However, in-spite of having many advantages, they are prone to some serious security issues one of which being the topology exposure problem. Though there exist several Ad-hoc routing protocols that deal with some security issues in the MANETs, they hardly deal with the topology exposure problem, which makes them vulnerable to attack. Due to scarce resources MANETs tends to be difficult to be secured from malicious users. While underlining the necessity of hiding the topology of MANET when designing routing protocols, this paper presents ‘Modified Topology-Hiding Multipath Routing protocol’ (M-THMR) to address the security challenges in MANET, specifically those related to the topology exposure problem. M-THMR implements mechanisms for hiding the network topology, searching the nodes and avoiding unreliable routes. The paper analyses the general types of attacks on the MANET and shows the relationship between these attacks and the issue of topology exposure. Based on the performance evaluation, it is proposed that the M-THMR possess better capability of finding routes and nonetheless it does not degrade the performance of the network in the absence of attack. Moreover, in an adverse scenario, M-THMR is able to tackle an attack at the cost of very low overhead and short routing convergent time.
1 Visual Artificial Grammar Learning by Rhesus Macaques ( Macaca mulatta ) : 1 Exploring the Role of Grammar Complexity and Sequence Length 2 3 4 5

25 Humans and nonhuman primates can learn about the organization of stimuli in the environment 26 using implicit sequential pattern learning capabilities. However, most previous artificial grammar 27 learning studies with nonhuman primates have involved relatively simple grammars and short input 28 sequences. The goal in the current experiments was to assess the learning capabilities of monkeys on an 29 artificial grammar-learning task that was more complex than most others previously used with 30 nonhumans. Three experiments were conducted using a joystick-based, symmetrical-response serial 31 reaction time (SR-SRT) task in which two monkeys were exposed to grammar-generated sequences at 32 sequence lengths of four in Experiment 1, six in Experiment 2, and eight in Experiment 3. Over time, the 33 monkeys came to respond faster to the sequences generated from the artificial grammar compared to 34 random versions. In a subsequent generalization phase, subjects generalized their knowledge to novel 35 sequences, responding significantly faster to novel instances of sequences produced using the familiar 36 grammar compared to those constructed using an unfamiliar grammar. These results reveal that rhesus 37 monkeys can learn and generalize the statistical structure inherent in an artificial grammar that is as 38 complex as some used with humans, for sequences up to eight items long. These findings are discussed 39 in relation to whether or not rhesus macaques and other primate species possess implicit sequence 40 learning abilities that are similar to those that humans draw upon to learn natural language grammar. 41 42
Integration of Data-Level Fusion Model and Kernel Methods for Degradation Modeling and Prognostic Analysis

To prevent unexpected failures of complex engineering systems, multiple sensors have been widely used to simultaneously monitor the degradation process and make inference about the remaining useful life in real time. As each of the sensor signals often contains partial and dependent information, data-level fusion techniques have been developed that aim to construct a health index via the combination of multiple sensor signals. While the existing data-level fusion approaches have shown a promise for degradation modeling and prognostics, they are limited by only considering a linear fusion function. Such a linear assumption is usually insufficient to accurately characterize the complicated relations between multiple sensor signals and the underlying degradation process in practice, especially for complex engineering systems considered in this study. To address this issue, this study fills the literature gap by integrating kernel methods into the data-level fusion approaches to construct a health index for better characterizing the degradation process of the system. Through selecting a proper kernel function, the nonlinear relation between multiple sensor signals and the underlying degradation process can be captured. As a result, the constructed health index is expected to perform better in prognosis than existing data-level fusion methods that are based on the linear assumption. In fact, the existing data-level fusion models turn out to be only a special case of the proposed method. A case study based on the degradation signals of aircraft gas turbine engines is conducted and finally shows the developed health index by using the proposed method is insensitive for missing data and leads to an improved prognostic performance.
Theoretical analysis of dental demineralization using photothermal radiometry

A coupled diffuse-photon-density-wave and thermal-wave theoretical model was developed to describe the biothermophotonic phenomena in a turbid medium under photothermal radiometry experimental conditions. The solution of the radiative transport equation in the limit of the diffuse-photon-density field was considered as a source term in the thermal-wave field equation. The model was used to analyze laser induced photothermal phenomena in a demineralized tooth sample as a function of depth. The analysis is based on a three-layer approach (demineralized enamel + healthy enamel + dentin) and considering the influence of thermal and optical properties of each layer on the resulting optical and thermal field.
Learning Deep Semantic Embeddings for Cross-Modal Retrieval

Deep learning methods have been actively researched for cross-modal retrieval, with the softmax cross-entropy loss commonly applied for supervised learning. However, the softmax cross-entropy loss is known to result in large intra-class variances, which is not not very suited for cross-modal matching. In this paper, a deep architecture called Deep Semantic Embedding (DSE) is proposed, which is trained in an end-to-end manner for image-text cross-modal retrieval. With images and texts mapped to a feature embedding space, class labels are used to guide the embedding learning, so that the embedding space has a semantic meaning common for both images and texts. This way, the difference between different modalities is eliminated. Under this framework, the center loss is introduced beyond the commonly used softmax cross-entropy loss to achieve both inter-class separation and intraclass compactness. Besides, a distance based softmax cross-entropy loss is proposed to jointly consider the softmax cross-entropy and center losses in fully gradient based learning. Experiments have been done on three popular image-text cross-modal retrieval databases, showing that the proposed algorithms have achieved the best overall performances.
Update in the Surgical Management of Decubitus Ulcers

Decubitus ulcers remain a common and recurring problem amongst overly ill patients, especially those who are bed-bound. They are caused by unrelieved pressure over tissues, mainly over bony prominences, such as the trochanteric, ischial, and sacral areas, and are classified from stage I to IV. Many forms of management have been described, with prevention being the most important of them. For stages I and II a conservative, non-surgical approach can be used, compared to stages III and IV which normally require surgical management. Post-operative care has also been shown to play a major role in avoiding the high rate of recurrences. Because of their location, high recurrence rates and increase in mortality, pressure sores continue to be a challenge for the medical and nursing staff, and are extremely costly to treat. In this manuscript we review the literature to expose the latest non-surgical and surgical techniques for the management of Decubitus Ulcers.
Biocontrol Potential of Drought tolerant Rhizospheric bacteria Isolated from Stressed Ecosystems against Dry Root Rot of Chickpea (Cicer arietinum L.) Caused by Rhizoctonia bataticola

Drought is regarded as one of the major constraint in the productivity of crop plants around the world. Application of drought tolerant bacteria mitigating the effect of drought would be a novel approach in this regard. In the present study, the effect of Bacillus sp. BHU 08 was observed on growth promotion and disease suppression in chickpea. The treatment T8 (Bacillus sp. BHU 08) shows the highest value of morpho-physiological parameters that were observed at 30, 60 and 90 DAS. Application of Bacillus sp. BHU 08 induced accumulation of high level of phenol, proline, activities of PAL, SOD and catalase in chickpea plants when compared with its control. The treatment T7 recorded the highest value of all these enzymes at different hours after the pathogen challenge that varied from 48-72 h which then declined. Increased levels of these plant defense enzymes upon pathogen attack suggests that the ISR and SAR mechanism of the plant gets initiated and thus it will trigger a defense response in the host. These antioxidant enzymes quench the toxic reactive oxygen species and in turn protects the plant from oxidative damage. PAL activity precedes rapid recognition of a microbial invader which potentiates the accumulation of disease resistance factors including phenolics, phytoalexins and lignin. An increase in lignification is often observed in response to the attack by pathogen and is believed to represent one of the chief mechanisms adopted to block pathogen invasion due to its highly non-degradable and antimicrobial nature.
Hypohydrotic Ectodermal Dysplasia in Black Africans

Ectodermal dysplasia is an uncommon genodermatosis which may be associated with mental retardation. The diagnosis is often missed in newborns or delayed due to its varied overlapping clinical presentation in affected individuals. We report two maternal blood related males with complaints of heat intolerance since birth, lack of sweating and dry scaly skin. Both had normal developmental milestone and mental acuity. The treatment is symptomatic and patient dependant while overall management requires a multidisciplinary team approach.
Scalable Hash Ripple Join on Spark

Hash Ripple join is an online aggregation algorithm that can rapidly give good approximate join results increases with the progress of the join operation and converges to the real result when the join finishes. Luo et al. proposed a parallel hash ripple join (PHRJ) that runs in a distributed setting. However, the PHRJ has two drawbacks when handling large-scale data: 1) PHRJ updates approximate results in fine grain which induces extra communication cost in a distributed environment 2) When data is out of memory, PHRJ cannot provide unbiased approximate result. In this thesis, a scalable hash ripple join is proposed that 1) runs on a distributed framework that can process distributed data in coarse-grain to speed up the join performance; 2) continuously gives unbiased and consistent approximate join results even in the presence of memory overflow; and 3) has good scalability handling growing amount of data. We have implemented a prototype of the scalable hash ripple join (SHRJ) algorithm on Spark. Experiment results show that SHRJ can give good approximate join result while taking less than 10% of the time of Spark's own join operator.
Cell Vaccination Benefits Relapsing Progressive Multiple Sclerosis Patients : A Randomized , Double-Blind Clinical Trial

Background: T-cell vaccination (TCV) for multiple sclerosis (MS) refers to treatment with autologous anti-myelin T-cells, attenuated by irradiation. Previously published clinical trials have been all open-labeled. Aim: To evaluate the safety and efficacy of TCV in progressive MS, in a double-blind, controlled clinical trial. Methodology: Twenty-six patients with relapsing-progressive MS were enrolled in the study (mean age: 3969.8 years; mean EDSS: 4.461.7). T-cell lines reactive to 9 different peptides of the myelin antigens, MBP, MOG and PLP were raised from the patients’ peripheral blood. The patients were randomized into two groups: 19 were treated with TCV (four subcutaneous injections of 10–30610 T-cells, attenuated by irradiation, on days 1, 30, 90 and 180) and 7 patients were treated with sham injections. Twenty-four patients (17 in the TCV group and 7 in the placebo) were eligible for per-protocol analysis. Results: At one year following the inclusion, an increase in the EDSS (+0.50) and an increase in 10-meter walking time (+0.18 sec), were observed in the placebo group; in the TCV group there was a decrease in the EDSS (20.44; p,0.01) and in the 10-meter walking time (0.84 sec; p,0.005). Sixteen of the 17 patients (94.1%) in the TCV group remained relapse-free during the year of the study, as compared to 42.9% in the placebo group (p = 0.01 and p = 0.03 with adjustment). The proportion of patients with any relapse during the year of the study in the TCV-group, was reduced by 89.6%. , as compared to the placebo-treated group. MRI parameters did not change significantly. Conclusions: This is the first controlled, double-blind trial with TCV in progressive MS. The results demonstrate the feasibility and safety of the procedure, and provide significant indications of clinical efficacy. Further studies with larger groups of subjects are warranted. Trial Registration: ClinicalTrials.gov NCT01448252 Citation: Karussis D, Shor H, Yachnin J, Lanxner N, Amiel M, et al. (2012) T Cell Vaccination Benefits Relapsing Progressive Multiple Sclerosis Patients: A Randomized, Double-Blind Clinical Trial. PLoS ONE 7(12): e50478. doi:10.1371/journal.pone. 0050478 Editor: Alexandre Salgado Basso, Escola Paulista de Medicina UNIFESP, Brazil Received December 4, 2011; Accepted October 25, 2012; Published December 14, 2012 Copyright: 2012 Karussis et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by grants from the I. Horowitz Association and the Institute for Advanced Therapy, New York, New York, United States of America. The funders have no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: rivka_abulafia@yahoo.com (RAL); karus@cc.huji. ac.il (DK)
Dynamic optical activity and self-oscillation in torsional metamaterials

We study the nonlinear dynamic properties of coupled torsional meta-molecules. We find that this structure may exhibit self-oscillation behaviour, and we analyse two different mechanisms leading to this effect. Contrary to many previously studied optomechanical systems, self-oscillations of torsional meta-molecules can be extremely robust against mechanical damping and they can be manipulated by the polarisation of electromagnetic waves. We also study the dynamic nonlinear optical activity arising in the system and its active control.
The Effects of Filler Contents and Particle Sizes on the Mechanical and End-Use Properties of Snail Shell Powder Filled Polypropylene

Polypropylene composites of snail shell powder were prepared at filler contents, 0 to 40 wt%. The particle sizes of the snail shell powder investigated were 0.150, 0.30, and 0.42 µm. Talc, of particle size, 0.150 µm was used as the reference filler. The polypropylene composites were prepared in an injection moulding machine and the resulting composites were extruded as sheets. Some mechanical and end-use properties of the prepared composites were determined. Results showed that the snail shell powder improved the tensile modulus, flexural strength, and impact strength of polypropylene and these properties increased with increases in the filler content and decreases in the filler particle size. The elongation at break of the composites was however observed to decrease with increases in the filler content, and particle size. The elongation at break of talc filled polypropylene was zero, an indication of the brittle nature of polypropylene composites of talc. The hardness, water sorption (24-hr) and specific gravity of the composites were found to increase with increases in the filler content, and decreases in the filler particle size. The level of water absorbed by snail shell powder composites of polypropylene is considerably higher than that of talc filled polypropylene. The flame retardant properties of the prepared composites were however found to decrease with increases in the filler content, and particle size. Generally, snail shell powder was found to show greater property improvement over talc in the prepared composites.
HSF1-mediated oxidative stress response to menadione in Saccharomyces cerevisiae KNU5377Y3 by using proteomic approach

The hat shock transcription factor HSF1 inthe yeast Saccharomyces cerevisiae regulates a wide range of genes and functions in diverse cellular reactions. To investigate the physiological response of HSF1 inthe presence of menadione (MD) in S. cerevisiae KNU 5377Y3, wild-type (k3wt) and isogenic hsf1 mutant (k3h1) cells were introduced. HSF1 was induced when k3wt cells were exposed to the superoxide-generating agent MD and k3h1 cells were hypersensitive to MD. Under MD stress, k3h1 cells down-regulated the expression of metabolic enzymes (Hxk, Fba1, Pgk1, Eno2, and Adh1), antioxidant enzymes (Trx2 and porin), and molecular chaperones and their cofactors (Hsp104, Ssb1, Hsp60, Hsp42, Hsp26, Hsp12, Cpr1, and Sti1). In addition, k3h1 cells increased cellular hydroperoxide levels and protein carbonylation under MD stress as compared to k3wt cells. However, there was a moderate difference in the wild-type (b3wt) and mutant (b3h1) cells derived from S. cerevisiae S288Cunder the same conditions. Thus, these results show that HSF1 is an important component of the stress response system, acting as an activator of cell rescue genes in S. cerevisiae KNU5377Y3, and its expression protects the cells from MD-induced oxidative damage by maintaining redox homeostasis and proteostasis in the presence of MD.
Mechanisms and potential treatments for declining olfactory function and neurogenesis in the ageing brain

The role of olfactory function in maintaining quality of life and as a potential surrogate marker of neurogenic activity in the elderly brain is an underappreciated topic. The olfactory system is complex and is unusual in that its function is maintained by neurogenesis at multiple sites throughout the lifetime of an organism, which in humans may be over 80 years in length. Declines in olfactory function are common with advancing age and this is associated with reductions in the quality of life, the perception of flavour and neurogenesis. These reductions in neurogenesis may simply be a consequence of advancing age or may reflect the nascent development of underlying neurological dysfunction. There are a number of potential therapeutic interventions that can result in a gain of olfactory function, these range from behavioural modification, to dietary supplementation and pharmaceutical intervention but they are all thought to work in part by increasing hippocampal and olfactory neurogenesis. This review discusses the mechanisms underlying olfactory decline in the elderly, reviews a number of potential strategies for improving olfactory function and hypotheses that increasing the rate of neurogenesis in the ageing brain would improve the quality of life not only by improving olfaction but by improving a range of cognitive processes that are dependent on neurogenesis including mood.
Atherosclerotic Events: The Role of Air Particulate Matter

Epidemiological studies associate the increase of respiratory and cardiovascular mortality and morbidity with high levels of air pollution particulate matter (PM). However, the underlying mechanisms of actions by which PM induce adverse health effects remain to be clearly elucidated. Evidence from experimental studies suggests that particle composition can play an important role in PM-toxicity; however, little is known about the specific participation of components (individually or acting in groups) present in such a complex mixture that accounts for toxicity. Correlations between exposure to PM with an aerodynamic diameter 2.5 or 10 µm (PM2.5 and PM10, respectively) with cardiovascular effects have been demonstrated. Mechanisms of PM at cellular level involve free radical production (by transition metals and organic compounds), oxidative stress, cytokine release, inflammation, endotoxin-mediated damage, stimulation of capsaicin receptors, autonomic nervous system activity, covalent modification of key cellular molecules and increased pro-coagulant activity. The various interaction between particulate matter (e.g carcinogenic polyaromatic hydrocarbon components) and biological molecules trigger cascade events which initiate or aid the progression of disease conditions through cellular responses which could give rise to oxidized and/or mutagenic lesions such as are found within the atherosclerotic plaque and cancers with the most important mechanisms possibly being reactive oxygen species (ROS) generation, oxidative stress and inflammation.
Controllable-Domain-Based Fuzzy Rule Extraction for Copper Removal Process Control

In copper removal process control, the commonly used technique is the so-called rule-based control, which is largely dependent upon the operators' experience, likely leading to unstable process production due to each individual's characters and favors. In this paper, to enhance the effectiveness of process control, a controllable-domain-based fuzzy rule extraction strategy is proposed. New definitions of representative controlled samples are introduced, by which the input variable space is divided into several controllable domains by applying positive and unlabeled learning algorithm. Also, the unreasonable removed and the controllable domains are accordingly determined. Then, support vector machine method is employed to extract fuzzy control rules for different domains. Finally, an industrial experiment is presented to demonstrate the effectiveness and advantages of the developed new design scheme.
The unique qualities Nonmedical Use of Stimulants Among Medical Students

The Journal of the American Osteopathic Association August 2014 | Vol 114 | No. 8 643 From the Department of Biomedical Sciences at Oakland University William Beaumont School of Medicine in Rochester, Michigan (Dr Wasserman), and the departments of institutional effectiveness and accreditation (Dr Cole), physiology (Dr Suminski), and clinical affairs (Dr Dougherty) at the Kansas City University of Medicine and Biosciences in Missouri. Drs Fitzgerald and Sunny were osteopathic medical students at the Kansas City University of Medicine and Biosciences College of Osteopathic Medicine in Missouri at the time of this study. They hold master’s degrees in bioethics.