Miracle-dz/UniFAR-FTUs huggingface dataset:
Wireless sensor networks security issues and challenges: A survey

Wireless Sensor Network (WSN) is a rising technology that offers a great assurance towards a variety of revolutionary applications such as military and public. As wireless sensor networks continue to develop, there is a high importance in security mechanisms. As sensor networks works with responsive data and operate in antagonistic environments, it is crucial to address the security issues. The sensing technology united with wireless communication and processing power makes it rewarding. Due to these computing and inherent constraints in resource, sensor network security has special challenges. The low cost and collaborative nature of the wireless networks (WNs) offers significant advantages upon the conventional communication techniques. The wireless communication technology has several kinds of security threats. The spotlight of this paper is towards addressing the security issues and challenges of WSNs. Here the idea is to identify the threats and security mechanism of wireless sensor networks.
Training Improves the Capacity of Visual Working Memory When It Is Adaptive, Individualized, and Targeted

The current study investigated whether training improves the capacity of visual working memory using individualized adaptive training methods. Two groups of participants were trained for two targeted processes, filtering and consolidation. Before and after the training, the participants, including those with no training, performed a lateralized change detection task in which one side of the visual display had to be selected and the other side ignored. Across ten-day training sessions, the participants performed two modified versions of the lateralized change detection task. The number of distractors and duration of the consolidation period were adjusted individually to increase the task difficulty of the filtering and consolidation training, respectively. Results showed that the degree of improvement shown during the training was positively correlated with the increase in memory capacity, and training-induced benefits were most evident for larger set sizes in the filtering training group. These results suggest that visual working memory training is effective, especially when it is adaptive, individualized, and targeted.
Prions in Milk from Ewes Incubating Natural Scrapie

Since prion infectivity had never been reported in milk, dairy products originating from transmissible spongiform encephalopathy (TSE)-affected ruminant flocks currently enter unrestricted into the animal and human food chain. However, a recently published study brought the first evidence of the presence of prions in mammary secretions from scrapie-affected ewes. Here we report the detection of consistent levels of infectivity in colostrum and milk from sheep incubating natural scrapie, several months prior to clinical onset. Additionally, abnormal PrP was detected, by immunohistochemistry and PET blot, in lacteal ducts and mammary acini. This PrPSc accumulation was detected only in ewes harbouring mammary ectopic lymphoid follicles that developed consequent to Maedi lentivirus infection. However, bioassay revealed that prion infectivity was present in milk and colostrum, not only from ewes with such lympho-proliferative chronic mastitis, but also from those displaying lesion-free mammary glands. In milk and colostrum, infectivity could be recovered in the cellular, cream, and casein-whey fractions. In our samples, using a Tg 338 mouse model, the highest per ml infectious titre measured was found to be equivalent to that contained in 6 µg of a posterior brain stem from a terminally scrapie-affected ewe. These findings indicate that both colostrum and milk from small ruminants incubating TSE could contribute to the animal TSE transmission process, either directly or through the presence of milk-derived material in animal feedstuffs. It also raises some concern with regard to the risk to humans of TSE exposure associated with milk products from ovine and other TSE-susceptible dairy species.
Evaluation of dietary and life-style habits of patients with gastric cancer: a case-control study in Turkey.

OBJECTIVE Gastric cancer is an important public health problem in the world and Turkey. In addition to Helicobacter pylori (H. pylori), smoking, alcohol consumption and family history, certain dietary factors have been associated with its occurrence. The impact of dietary habits and life-style factors on the risk of gastric cancer in Turkey were evaluated in this study. DESIGN A questionnaire was applied to 106 patients with gastric adenocarcinoma and 106 controls without cancer matched for age (range 28-85 years) and gender selected from a hospital based population. Adjusted odds ratios (ORs) and 95% confidence intervals (CI) were calculated with logistic regression analysis. RESULTS The incidence of H. pylori was 81.3% in patients. Frequent consumption of salty dishes, very salty foods like pickles, soup mixes, sausages, foods at hot temperature (ORs=3.686, 7.784, 5.264, 3.148 and 3.273 respectively) and adding salt without tasting (OR=4.198) were associated with increased gastric risk. Also heavy smoking and high amount of alcohol consumption (p=0.000) were risk factors. Frequent consumption of green vegetables, onion, garlic and dried fruits (ORs=0.569, 0.092, 0.795 and 0.041) was non- significantly associated with decreased risk. CONCLUSION Improved dietary habits, reducing salt consumption and eradication of H. pylori infection may provide protection against gastric cancer in Turkey.
Putting language back into ecological communication contexts

ABSTRACT Language is a multi-faceted form of communication. It is not until recently though that language research moved on from simple stimuli and protocols toward a more ecologically valid approach, namely “shifting” from words and simple sentences to stories with varying degrees of contextual complexity. While much needed, the use of ecologically valid stimuli such as stories should also be explored in interactive rather than individualistic experimental settings leading the way to an interactive neuroscience of language. Indeed, mounting evidence suggests that cognitive processes and their underlying neural activity significantly differ between social and individual experiences. We aim at reviewing evidence, which indicates that the characteristics of linguistic and extra-linguistic contexts may significantly influence communication – including spoken language comprehension. In doing so, we provide evidence on the use of new paradigms and methodological advancements that may enable the study of complex language features in a truly interactive, ecological way.
Mathematical Approach towards Fault Detection and Isolation of Linear Dynamical Systems

— The main objective of this work is to provide a fault detection and isolation based on Markov parameters for residual generation and a neural network for fault classification. The diagnostic approach is accomplished in two steps: In step 1, the system is identified using a series of input / output variables through an identification algorithm. In step 2, the fault is diagnosed comparing the Markov parameters of faulty and non faulty systems. The Artificial Neural Network is trained using predetermined faulty conditions serves to classify the unknown fault. In step 1, the identification is done by first formulating a Hankel matrix out of Input/ output variables and then decomposing the matrix via singular value decomposition technique. For identifying the system online sliding window approach is adopted wherein an open slit slides over a subset of ‘n’ input/output variables. The faults are introduced at arbitrary instances and the identification is carried out in online. Fault residues are extracted making a comparison of the first five Markov parameters of faulty and non faulty systems. The proposed diagnostic approach is illustrated on benchmark problems with encouraging results.
Studying the electronic and phononic structure of penta-graphane

Abstract In this paper, we theoretically consider a two dimensional nanomaterial which is a form of hydrogenated penta-graphene; we call it penta-graphane. This structure is obtained by adding hydrogen atoms to the sp2 bonded carbon atoms of penta-graphene. We investigate the thermodynamic and mechanical stability of penta-graphane. We also study the electronic and phononic structure of penta-graphane. Firstly, we use density functional theory with the revised Perdew–Burke–Ernzerhof approximation to compute the band structure. Then one–shot GW (G0W0) approach for estimating accurate band gap is applied. The indirect band gap of penta-graphane is 5.78 eV, which is close to the band gap of diamond. Therefore, this new structure is a good electrical insulator. We also investigate the structural stability of penta-graphane by computing the phonon structure. Finally, we calculate its specific heat capacity from the phonon density of states. Penta-graphane has a high specific heat capacity, and can potentially be used for storing and transferring energy.
The efficacy of intrauterine instillation of granulocyte colony-stimulating factor in infertile women with a thin endometrium: A pilot study

Objective The study aimed to investigate the efficacy of intrauterine instillation of granulocyte colony-stimulating factor (G-CSF) on the day of ovulation triggering or oocyte retrieval in infertile women with a thin endometrium. Methods Fifty women whose endometrial thickness (EMT) was ≤8 mm at the time of triggering during at least one previous in vitro fertilization (IVF) cycle and an index IVF cycle were selected. On the day of triggering (n=12) or oocyte retrieval (n=38), 300 µg of G-CSF was instilled into the uterine cavity. Results In the 50 index IVF cycles, the mean EMT was 7.2±0.6 mm on the triggering day and increased to 8.5±1.5 mm on the embryo transfer day (p<0.001). The overall clinical pregnancy rate was 22.0%, the implantation rate was 15.9%, and the ongoing pregnancy rate was 20%. The clinical pregnancy rate (41.7% vs. 15.8%), the implantation rate (26.7% vs. 11.7%), and the ongoing pregnancy rate (41.7% vs. 13.2%) were higher when G-CSF was instilled on the triggering day than when it was instilled on the retrieval day, although this tendency was likewise not statistically significant. Aspects of the stimulation process and mean changes in EMT were similar in women who became pregnant and women who did not. Conclusion Intrauterine instillation of G-CSF enhanced endometrial development and resulted in an acceptable pregnancy rate. Instillation of G-CSF on the triggering day showed better outcomes. G-CSF instillation should be considered as a strategy for inducing endometrial growth and good pregnancy results in infertile women with a thin endometrium.
Cross recurrence plot analysis based method for TDOA estimation of underwater acoustic signals

In this paper, we propose to use cross recurrence plot analysis (CRPA) to estimate the time-difference of arrival (TDOA) of underwater acoustic signals arriving on an array of hydrophones. Instead of considering the signal as a whole to estimate the TDOA, like classical methods do, we first detected the series of samples that look alike on each pair of hydrophones of the array by using cross-recurrence plot analysis. The TDOA is then estimated by relying only on these common sample series. The TDOA estimator is based on quantification measures specifically designed for CRPA. The proposed method is successfully validated on real data containing frequency-modulated sounds from beluga whales.
Pattern-based algorithm for Part-of-Speech tagging Arabic text

Building a generic Part-of-Speech (POS) tagger system without a lexicon (dictionary) depends on the language and the characteristics of its grammar, both the morphological and the syntactical systems of that language. Arabic language has a valuable and important feature, called diacritics, which are marks placed over and below the letters of Arabic word. This paper presents a novel algorithm to assign the correct POS tag to those words belonging to a verb or a noun class in an Arabic text. The algorithm is based on the pattern (wazn) of the word instead of using a huge manually tagged lexicon from which large amounts of training data can be extracted. An experiment was ran on a data set that contains 5,000 words belonging to a noun and a verb class to evaluate the accuracy of the algorithm. The algorithm is achieved an accuracy of 91%.
Classes of fast and specific search mechanisms for proteins on DNA

Problems of search and recognition appear over different scales in biological systems. In this review we focus on the challenges posed by interactions between proteins, in particular transcription factors, and DNA and possible mechanisms which allow for fast and selective target location. Initially we argue that DNA-binding proteins can be classified, broadly, into three distinct classes which we illustrate using experimental data. Each class calls for a different search process and we discuss the possible application of different search mechanisms proposed over the years to each class. The main thrust of this review is a new mechanism which is based on barrier discrimination. We introduce the model and analyze in detail its consequences. It is shown that this mechanism applies to all classes of transcription factors and can lead to a fast and specific search. Moreover, it is shown that the mechanism has interesting transient features which allow for stability at the target despite rapid binding and unbinding of the transcription factor from the target.
FACTORS INFLUENCING CAREER CHOICE AMONG NURSING STUDENTS

Choosing a career is a complex and multi-factorial decision-making process that is based on several personal, situational and organizational factors. The purpose of this study is a literature review to determine factors influencing career choice among nursing students. The literature review displays that nursing students make their career decisions from a combination of personal interests in health care and their desire to help others. From the beginning of the studies students may have strong career preferences. Before they graduate and eventually decide about the future workplace, their career choices undergo several transitions. Career choices are influenced both by the students inclination before starting medical school as well as any exposure during training in medical school. Experiences in chosen specialties during training as well as the social environment of the medical school, the teaching programme and clinical staff role models can influence career preferences.
Molecular Pathogenesis of MALT Lymphoma

Approximately 8% of all non-Hodgkin lymphomas are extranodal marginal zone B cell lymphoma of mucosa associated lymphoid tissue (MALT), also known as MALT lymphoma, which was first described in 1983 by Isaacson and Wright. MALT lymphomas arise at a wide range of different extranodal sites, with the highest frequency in the stomach, followed by lung, ocular adnexa, and thyroid, and with a low percentage in the small intestine. Interestingly, at least 3 different, apparently site-specific, chromosomal translocations and missense and frameshift mutations, all pathway-related genes affecting the NF-κB signal, have been implicated in the development and progression of MALT lymphoma. However, these genetic abnormalities alone are not sufficient for malignant transformation. There is now increasing evidence suggesting that the oncogenic product of translocation cooperates with immunological stimulation in oncogenesis, that is, the association with chronic bacterial infection or autoaggressive process. This review mainly discusses MALT lymphomas in terms of their genetic aberration and association with chronic infections and summarizes recent advances in their molecular pathogenesis.
Computational Modeling of Human Social Intention

In this paper, we propose to analyze the kinematic of human arm to predict social intention (personal vs. social intention). We propose to use infrared markers placed on the arms of two human subjects. The trajec-tories of different markers are defined as shape spaces and subsequently analyzed as a Riemannian manifold for the purposes of characterizing the intention (personal vs. social). The first results show that the best results are obtained with the wrist marker (69.2%).
A new type of hybrid features for human detection

Human detection is one of the hard problems in object detection field. There are many challenges like variation in human pose, different clothes, non-uniform illumination, cluttered background and occlusion which make this problem much harder than other object detection problems. Defining good features, which can be robust to this wide range of variations, is still an open issue in this field. To overcome this challenge, in this paper we proposed a new set of hybrid features. We combined the Histogram of Oriented Gradient (HOG) with the new features called Histogram of Small Edges (HOSE) which is introduced in this paper. These two kinds of features have two different approaches for extracting features and have the complementary role for each other. Our experimental results on INRIA dataset showed that using the proposed hybrid features provides better detection rate in comparison with state of the art features.
Achieving privacy in trust negotiations with an ontology-based approach

The increasing use of Internet in a variety of distributed multiparty interactions and transactions with strong real-time requirements has pushed the search for solutions to the problem of attribute-based digital interactions. A promising solution today is represented by automated trust negotiation systems. Trust negotiation systems allow subjects in different security domains to securely exchange protected resources and services. These trust negotiation systems, however, by their nature, may represent a threat to privacy in that credentials, exchanged during negotiations, often contain sensitive personal information that may need to be selectively released. In this paper, we address the problem of preserving privacy in trust negotiations. We introduce the notion of privacy preserving disclosure, that is, a set that does not include attributes or credentials, or combinations of these, that may compromise privacy. To obtain privacy preserving disclosure sets, we propose two techniques based on the notions of substitution and generalization. We argue that formulating the trust negotiation requirements in terms of disclosure policies is often restrictive. To solve this problem, we show how trust negotiation requirements can be expressed as property-based policies that list the properties needed to obtain a given resource. To better address this issue, we introduce the notion of reference ontology, and formalize the notion of trust requirement. Additionally, we develop an approach to derive disclosure policies from trust requirements and formally state some semantics relationships (i.e., equivalence, stronger than) that may hold between policies. These relationships can be used by a credential requestor to reason about which disclosure policies he/she should use in a trust negotiation.
Nephrology Dialysis Transplantation the Janus-faced Aspect of 'dry Weight'

must also be prepared to increase it to compensate for anabolism and to avoid episodes of hypotension. Background. The goal of haemodialysis treatment in end-stage renal disease (ESRD) patients is to correct Key words: dry weight; post-dialysis bodyweight ; the complications of the uraemic condition. Among blood pressure; haemodialysis; cellulosic membrane the main complications are fluid overload and subsequent hypertension that are corrected by achievement of 'dry weight'. We report in this study the evolution of post-dialysis bodyweight and blood pressure in Introduction patients who began their HD treatment in our unit. Methods. We studied the monthly evolution of post-Extracellular fluid overload is a common condition in dialysis bodyweight (expressed as a percentage of pre-end-stage renal disease (ESRD) patients. It is one of dialysis bodyweight at the first HD treatment) and the main factors of hypertension in this setting [1]. predialysis mean arterial pressure (MAP) over 24 Haemodialysis (HD) treatment is supposed to correct months in 61 patients (21 females; mean age 59.8 the fluid overload by achievement of dry-weight, a sort years; 20% diabetic), treated with cellulosic membranes of 'Holy Grail' in the HD practice. Dry weight has for 8 h, 3 times a week. been previously defined [2]. In our experience, it is the Results. The post-dialysis bodyweight decreased post-dialysis bodyweight that allows the pre-dialysis between the onset of HD and month 2 (M2) blood pressure to remain normal (i.e. ∏130/80 mmHg (−4.40±0.52%). Then it went up, reaching or mean arterial pressure (MAP) ∏96 mmHg), despite −1.56±0.96% at M6, +0.3±1.27% at M12, the interdialytic weight gain and without the need of +1.27±1.38% at M18 and +1.64±1.33% at M24. antihypertensive drugs. Also, at dry weight, the patient The post-dialysis bodyweight increased by 6% between has no clinical signs or symptoms of fluid overload or M2 and M24. The mean arterial pressure (MAP) hypovolaemia. decreased from 111.3±2.5 mmHg at M0 to 94.4±1.7 Moreover, improvement of nutritional status by the at M6, and then remained stable after M6. Between onset of the HD treatment has been an early observa-M2 and M6 the post-dialysis bodyweight increased, tion [3]. Then, in the first months of the HD treatment, whereas the predialysis MAP continued to decline. The the evolution of the bodyweight is the net result of incidence of hypotension episodes was maximal during two opposing processes, i.e. control of the extracellular the first 4 months of HD treatment. fluid volume to reverse hypertension …
Text Generation Methods for Dialog Systems

Text generation systems are typically more powerful than generation components of dialog systems. In order to exploit their advanced capabilities for dialog purposes, we discuss the extension potential of NL generation components of dialog systems on the basis of methods embedded in text generation system. We investigate architectural concerns and crucial system features in a comparison, and we formulate conditions for a successful reuse of generation techniques. Finally, we sketch how we envision to substantiate this investigation for promoting the proof explanation system P.rex into a generation component of a tutorial dialog system for teaching theorem proving skills.
3-D Object Tracking with the Adaptive Hyperplane Approach Using SIFT Models for Initialization

Object tracking is still a challenging task, especially if it is d o ne in a realistic enviro nm ent. T he o ngo ing increase o f co m pu tatio nal po w er and the efficiency o f the algo rithm s allo w real-tim e estim atio n o f the o bjectis po se in six d egrees o f freed o m . One o f these algo rithm s is the 3 -D hyperplane appro ach, w hich is u sed thro u gho u t this paper, as it has been pro ven to be fast and accu rate. W e sho w ho w to enhance its ro bu stness by u sing a linear illu m inatio n m o d el to gain m o re insensitivity to variatio ns o f the illu m inatio n co nd itio ns. W e also present an ad aptio n to co m pensate appearence changes in case o f external ro tatio ns. A ltho u gh so m e i six d egrees o f freed o m i trackers have been established , the necessary initializatio n is o ften igno red o r is o nly so lved ru d im entarily. In co ntrast to this, w e sho w ho w to u se a 3 -D S IF T o bject m o d el fo r initializatio n o f the w ho le tracking system and pro ve its efficiency by experim ental resu lts u sing real im age seq u ences.