Miracle-dz/UniFAR-FTUs huggingface dataset:
Bubble Cooperative Networks for Identifying Important Speech Cues

Predicting the intelligibility of noisy recordings is difficult and most current algorithms treat all speech energy as equally important to intelligibility. Our previous work on human perception used a listening test paradigm and correlational analysis to show that some energy is more important to intelligibility than other energy. In this paper, we propose a system called the Bubble Cooperative Network (BCN), which aims to predict important areas of individual utterances directly from clean speech. Given such a prediction, noise is added to the utterance in unimportant regions and then presented to a recognizer. The BCN is trained with a loss that encourages it to add as much noise as possible while preserving recognition performance, encouraging it to identify important regions precisely and place the noise everywhere else. Empirical evaluation shows that the BCN can obscure 97.7% of the spectrogram with noise while maintaining recognition accuracy for a simple speech recognizer that compares a noisy test utterance with a clean reference utterance. The masks predicted by a single BCN on several utterances show patterns that are similar to analyses derived from human listening tests that analyze each utterance separately, while exhibiting better generalization and less context-dependence than previous approaches.
Relative effectiveness of kinetic analysis vs single point readings for classifying environmental samples based on community-level physiological pro ® les ( CLPP )

The relative effectiveness of average-well-color-development-normalized single-point absorbance readings (AWCD) vs the kinetic parameters mm, l , A, and integral (AREA) of the modi®ed Gompertz equation ®t to the color development curve resulting from reduction of a redox sensitive dye from microbial respiration of 95 separate sole carbon sources in microplate wells was compared for a dilution series of rhizosphere samples from hydroponically grown wheat and potato ranging in inoculum densities of 1 £ 10 2 4 £ 10 cells ml. Patterns generated with each parameter were analyzed using principal component analysis (PCA) and discriminant function analysis (DFA) to test relative resolving power. Samples of equivalent cell density (undiluted samples) were correctly classi®ed by rhizosphere type for all parameters based on DFA analysis of the ®rst ®ve PC scores. Analysis of undiluted and 1:4 diluted samples resulted in misclassi®cation of at least two of the wheat samples for all parameters except the AWCD normalized (0.50 abs. units) data, and analysis of undiluted, 1:4, and 1:16 diluted samples resulted in misclassi®cation for all parameter types. Ordination of samples along the ®rst principal component (PC) was correlated to inoculum density in analyses performed on all of the kinetic parameters, but no such in ̄uence was seen for AWCD-derived results. The carbon sources responsible for classi®cation differed among the variable types with the exception of AREA and A, which were strongly correlated. These results indicate that the use of kinetic parameters for pattern analysis in CLPP may provide some additional information, but only if the in ̄uence of inoculum density is carefully considered. q 2001 Elsevier Science Ltd. All rights reserved.
Méthode d'enrichissement et d'élargissement d'une ontologie à partir de corpus de spécialité multilingues. (Method of ontology enrichment and population from multilingual comparable domain specific corpus)

Cette these propose une methode pour alimenter une ontologie, une structure de concepts lies par des relations semantiques, par des termes francais, anglais et allemands a partir de corpus specialises comparables. Son apport principal est le developpement des methodes d'extraction utilisant des ressources endogenes apprises a partir de corpus et d'ontologie. Exploitant des n-grammes de caracteres, elles sont disponibles et independantes vis-a-vis de la langue et du domaine. La premiere contribution porte sur l'utilisation des ressources morphologiques et morphosyntaxiques endogenes pour extraire des termes mono- et polylexicaux a partir de corpus. La deuxieme contribution vise a exploiter des ressources endogenes pour identifier leurs traductions. La troisieme contribution concerne la construction des familles morphologiques endogenes servant a alimenter l'ontologie.
Performance Analysis of Cooperative Relaying in Diffusion-Based Molecular Communication

Molecular communications (MC) is a promising paradigm which utilizes molecules to implement communication among nano-machines. Cooperative relaying strategies can be used to extend communication distance and achieve reliable remote communications. In this paper, a two-hop diffusion-based molecular communication with three nano-machine nodes is considered. To mitigate the drawback of traditional cooperative relay strategies in diffusion-based MC, such as decode-and-forward and amplify-and-forward, an opportunistic cooperative relaying strategy is proposed. Closed-form expressions of bit error probability for these three cooperative relaying strategies are derived. Analytical and simulation results show that the opportunistic decode-amplify-forward relaying strategy achieve the best gain over other two schemes to implement the reliable remote communications.
FAMILY VIOLENCE AMONG ASIAN AMERICANS

have shown considerable strength and resilience through their varied experiences in adapting to different cultural and environmental contexts in the United States, they have also encountered problems that are often left un-named. One such problem is that of family violence. Through mounting advocacy and intervention efforts, the women’s movement, media attention, and research efforts, the problem of family violence has gained national and international attention over the past three decades. Our general aim in this chapter is to specifically name many of the challenging issues involved in family violence among Asian Americans. Although family violence covers many types of physical, sexual, emotional, financial, and psychological abuse among various members of the kinship system, we focus primarily on intimate partner violence and child abuse in Asian American communities. Specifically, we examine the following issues with regard to 21
Collision-Aware Neighbor Discovery with Directional Antennas

The integration of directional antennas in ad-hoc networks offers tremendous potential for improving the overall network performance. However, the use of directional antennas makes the neighbor discovery process difficult due to the asymmetric nature of the directional gain. Recently, several neighbor discovery schemes have been proposed in this context. But the effect of packet collisions has been is ignored in these schemes. In this paper, we propose a novel collision-aware neighbor discovery scheme based on a two-way handshaking mechanism. We introduce a collision resolution mechanism that enables a faster convergence of the neighbor discovery process. We also derive a relation to compute the optimal contention window size for collision resolution. We then propose an upgraded version (i.e., peer-assisted node discovery) of the scheme involving cooperation among the neighbor nodes. Simulation results demonstrate that the proposed scheme achieves a significantly faster network-wide neighbor discovery than existing schemes.
Perindopril 3.5 mg/amlodipine 2.5 mg versus renin–angiotensin system inhibitor monotherapy as first-line treatment in hypertension: a combined analysis

Background: Many patients are diagnosed with hypertension each year, making rapid and effective control of blood pressure (BP) crucial. Appropriate first-line treatment is important, and special attention should be paid to the positive effects of lowering BP early. Perindopril 3.5 mg/amlodipine 2.5 mg (P3.5/A2.5) is a single-pill combination suitable for first-line use. The doses of each component of the single-pill combination were selected for a first-line setting. Objective: To investigate the effectiveness of the P3.5/A2.5 combination at lowering BP compared with renin–angiotensin system (RAS)-inhibitor monotherapies, after 1 month of treatment. Methods: Individual patient data from three randomized controlled trials were used to evaluate the efficacy of P3.5/A2.5 versus RAS-inhibitor monotherapies after 1 month in 5496 patients with hypertension, in a combined analysis. Results: P3.5/A2.5 was well tolerated and significantly more effective at reducing BP after 1 month than RAS-inhibitor monotherapies (perindopril 5 mg, irbesartan 150 mg or valsartan 80 mg). P3.5/A2.5 was associated with a significantly lower SBP (P = 0.002) and DBP (P = 0.005) after 1 month of treatment compared with RAS-inhibitor monotherapies. Conclusion: In a large patient population, early administration of P3.5/A2.5 resulted in a significantly greater BP-lowering effect than perindopril, irbesartan or valsartan monotherapies after 1 month. Reducing BP levels within a month of treatment may reasonably be expected to lead to a reduced risk of cardiovascular events.
Modified stemmer for a medical system — evaluated using predefined metrics

This study explores the importance of stemmers, its strength, and similarity metrics with newly defined stemmer called modified stemmer and also with predefined stemmers or stemming algorithms. This paper also evaluates the performance using metrics such as SWF (Stemmed Word's Factor), WCSF (Word's Correct Stemmed Factor), and WACF (Word's Average Conflation Factor). When compared with other stemmers, the precision of proper root form seems to be good with paice/husk and with modified stemmers.
Classification and diagnosis of aggressive periodontitis

OBJECTIVE Since the initial description of aggressive periodontitis (AgP) in the early 1900s, classification of this disease has been in flux. The goal of this manuscript is to review the existing literature and to revisit definitions and diagnostic criteria for AgP. STUDY ANALYSIS An extensive literature search was performed that included databases from PubMed, Medline, Cochrane, Scopus and Web of Science. Of 4930 articles reviewed, 4737 were eliminated. Criteria for elimination included; age > 30 years old, abstracts, review articles, absence of controls, fewer than; a) 200 subjects for genetic studies, and b) 20 subjects for other studies. Studies satisfying the entrance criteria were included in tables developed for AgP (localized and generalized), in areas related to epidemiology, microbial, host and genetic analyses. The highest rank was given to studies that were; a) case controlled or cohort, b) assessed at more than one time-point, c) assessed for more than one factor (microbial or host), and at multiple sites. RESULTS Epidemiologic studies provided insight into ethnic and societal factors affecting AgP. DNA analysis of microbes showed some consistency but significant variability. Host factor analysis was less consistent. Many genetic studies were conducted but few had either sufficient power or looked at multiple genes in AgP. CONCLUSIONS Conflicting data resulted for several reasons; 1) the classification was too broad, 2) the disease (AgP) was not studied from its inception, at differing time points (temporal), and at different locations (topographic). New technologic advances coupled with a more delimiting definition of disease will allow for genetic, host and microbial factor analyses in an unbiased manner. As such we predict that progress can be made in identifying a robust group of genetic, host, and microbial risk-markers associated with periodontal disease that can improve diagnostic capability in disease associated with juveniles, adolescents, and post-adolescent individuals.
Multi Level Malicious Behaviour Detection and Analysis Using Genetic Algorithm for Social Network

Protect sensitive information of different social network. We propose taking benefits of real-life social trust between different users as well as threshold cryptography. This leads to a new type of complex systems, the increase in network based attacks in general, and the world-wide access to computer networks and systems in particular, those responsible for network and computer system security need to utilize every tool available. First, in this paper will examine detailed implementation of applying genetic algorithm to intrusion detection Genetic Algorithm(Fitness ,Fitness_threshhold,X,Y,Z) Then, genetic algorithms will be discussed. After this, the Combining of genetic algorithms with intrusion detection will be reviewed. Finally, future steps will be discussed in the use of a genetic algorithm within intrusion detection.
The Blurred Appraise of Heavy Metal Pollutions on Soils in Wolongquan River Basin

The appraisal of the present heavy metals pollution is made by blurred mathematics in the soil-plant system of Wolongquan river basin.The results indicated that the heavy metals pollution are terribly serious in the soil-plant system upper and medium Wolongquan river basin.Thereinto,the contaminative factors of soil are mainly Cu,Pb and the contaminative factors of paddy and maize are respectively Pb,Cu,Cr,As and Pb,Cr,Hg in upper Wolongquan River basin,and the contaminative factors of paddy and maize are respectively Pb,Cu,Cd,Cr,As and Pb,Cr,As,Hg in Wangjiawaizi district.The extent of heavy metal pollution are less in dryfarming soils of hydrogenide plant and in woodland soil of Kaoshan village and contaminative factors are respectively Pb,Zn,Cu,Hg and Hg,As,Pb,Cd,Zn.The levels of heavy metals are less than correspounding background of soil heavy metal in dry farming soil of Wanfu district down Wolongquan River and surfacial soil in west hill land of Wangjiawaizi district.The pollution of Pb,Zn,Hg in the leeks are grievous in Wangjiawaizi district and in Wanfu district.Different plants in same district have different contaminative factors and the ripe or maize in different districts have different contaminative factors.
Which Parameters Are Important? Differential Importance Under Uncertainty

In probabilistic risk assessment, attention is often focused on the expected value of a risk metric. The sensitivity of this expectation to changes in the parameters of the distribution characterizing uncertainty in the inputs becomes of interest. Approaches based on differentiation encounter limitations when (i) distributional parameters are expressed in different units or (ii) the analyst wishes to transfer sensitivity insights from individual parameters to parameter groups, when alternating between different levels of a probabilistic safety assessment model. Moreover, the analyst may also wish to examine the effect of assuming independence among inputs. This work proposes an approach based on the differential importance measure, which solves these issues. Estimation aspects are discussed in detail, in particular the problem of obtaining all sensitivity measures from a single Monte Carlo sample, thus avoiding potentially costly model runs. The approach is illustrated through an analytical example, highlighting how it can be used to assess the impact of removing the independence assumption. An application to the probabilistic risk assessment model of the Advanced Test Reactor large loss of coolant accident sequence concludes the work.
Big data application in medical domain

Large volume of data which is a combination of both structured as well as unstructured data is referred by the term Big Data. As the amount of data produced is very huge, it becomes really difficult and time consuming to manage this data. Hadoop is a Big Data technology that is extensively used for the manipulation and analysis of Big Data. The applications of Big Data introduce new scope to determine knowledge. In this paper, applications of Big Data in medical domain is presented. Also, the challenges and benefits of various tools of Big Data in various scenarios are discussed.
(InxGa1−x)2O3  Photodetectors Fabricated on Sapphire at Different Temperatures by PLD

The (In<italic><sub>x</sub></italic>Ga<sub>1−</sub><italic><sub>x</sub></italic>)<sub>2</sub>O<sub>3</sub> photodetectors were fabricated on the single-crystalline (In<italic><sub>x</sub></italic>Ga<sub>1−</sub><italic> <sub>x</sub></italic>)<sub>2</sub>O<sub>3</sub> films deposited on sapphire substrate by pulsed laser deposition. The structural and optical properties of the epilayers were investigated using high-resolution X-ray diffraction, X-ray photoelectron spectroscopy, spectroscopic ellipsometry, and transmittance spectra. With decreasing the growth temperature, the indium composition increased and the bandgap decreased from 4.99 eV to 4.89 eV (In<sub>0.05 </sub>Ga<sub>0.95</sub>)<sub>2</sub>O<sub>3</sub> and 4.78 eV (In<sub>0.08</sub>Ga<sub>0.92</sub>)<sub>2</sub>O <sub>3</sub>. Furthermore, the photoelectrical characteristics of (In<italic><sub>x</sub></italic>Ga<sub>1−</sub> <italic><sub>x</sub></italic>)<sub>2</sub>O<sub>3</sub> detectors were also studied. The enhanced <inline-formula> <tex-math notation="LaTeX">$I_{{\text{photo}}}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX"> $I_{{\text{dark}}}$</tex-math></inline-formula>, and responsivity <italic>R</italic> were achieved in the devices with higher In composition, while a larger number of defects were introduced, resulting in the significant persistent photoconductivity.
Multiple Losses of Social Resources Following Collective Trauma: The Case of the Forced Relocation From Gush Katif

Collective trauma may lead to a pervasive loss of personal and social resources. The current study used a mixed method design to explore losses of social connections and affiliations following the collective trauma of forced relocation. A sample of 269 relocated residents from Gush Katif completed open-ended questionnaires regarding their ability to cope following the relocation, as well as questionnaires regarding their sense of belonging to the country, their sense of alienation from government institutions, post traumatic symptoms, and well-being. Three themes emerged in the qualitative stage of the study as the primary losses experienced by participants: loss of physical place and landscape, loss of a sense of belonging to Israeli society, and loss of trust and alienation from the country’s institutions. The quantitative stage revealed a complementary picture, with lower place commitment and higher alienation contributing directly both to post traumatic symptoms and to a reduced sense of well-being. In addition, a sense of alienation from the institutions of the country mediated the associations between the sense of belonging to the country and post traumatic symptoms and well-being. These findings are discussed in relation to the concept of social capital as a key factor in explaining one’s ability to cope with collective trauma.
Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy

The diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) — the most popular kind of deep learning algorithms — enjoyed great success in the field of image analysis and recognition. Therefore, we leverage CNN networks to diagnose the diabetic retinopathy and its current stage, based on analysis of the photographs of retina. The utilized models were trained using dataset containing over 88000 retina photographs, labeled by specialist clinicians. To enhance the performance of the system, we proposed a special class coding technique that enabled to include the information about value of difference between predicted score and target score into the objective function being minimized during the neural networks training. To evaluate classification ability of employed models we used standard accuracy metrics and quadratic weighted Kappa score that is calculated between the predicted scores and scores provided in the dataset. The best tested model achieved an accuracy of about 82% in detecting the retinopathy and 51% in assessing its stage. Moreover, system obtained decent Kappa score equal 0.776. Achieved results showed that deep learning algorithms can be successfully employed to solve this very hard to analyze problem.
On redundancy resolution and energy consumption of kinematically redundant planar parallel manipulators

SUMMARY Novel kinematic architectures can be alternatives for designing energy efficient robotic systems. In this work, the impact of kinematic redundancies in the energy consumption of a planar PKM, the 3PRRR manipulator, is experimentally verified. Because of the presence of the kinematic redundancies, the inverse kinematic problem presents infinity solutions. In this way, a redundancy resolution scheme based on the Model Predictive Control technique is proposed and exploited. It can be concluded that the energy consumption of the non-redundant parallel manipulator 3RRR for executing predefined tasks can be considerably reduced by the inclusion of kinematic redundancies.
Identification of High Crash Road Segment using Genetic Algorithm and Dynamic Segmentation

This paper presents an evolutionary algorithm for recognizing high and low crash road segments using Genetic Algorithm as a dynamic segmentation method. Social and economic costs as well as physical and mental injuries make the governments perceiving to road safety indexes in order to diminish the consequences of road accidents. Due to the limitation of budget for safety improvement of all parts of the road, the road segments with more accidents should be recognized for safety budget assignment. So, considering this fact it's important to identify the segments with high and low number of accidents to optimize the road safety program. In this study, a novel chromosome coding method and a fitness function which are consistent with Genetic Algorithm are proposed. The proposed methodology is also validated by using two mathematical parameters so that the results confirm that the proposed modeling works properly. Afterward, the proposed dynamic segmentation method is compared with the other static segmentation methods along 51 km of Shahrood–Sabzevar highway. The proposed method may have more advantages comparing to static segmentation methods for all of the performance indexes which were considered in this study. The proposed method has a variance about two times higher than the one for accident density in comparison with the other static segmentation methods. About 62% and 34% improvement is achieved in average of segments accident density and total segments density respectively in comparison with the other fixed methods.
Impact of age on acute post-TBI neuropathology in mice expressing humanized tau: a Chronic Effects of Neurotrauma Consortium study

ABSTRACT Objectives: We hypothesized that polypathology is more severe in older than younger mice during the acute phase following repetitive mild traumatic brain injury (r-mTBI). Methods: Young and aged male and female mice transgenic for human tau (hTau) were exposed to r-mTBI or a sham procedure. Twenty-four hours post-last injury, mouse brain tissue was immunostained for alterations in astrogliosis, microgliosis, tau pathology, and axonal injury. Results: Quantitative analysis revealed a greater percent distribution of glial fibrillary acid protein and Iba-1 reactivity in the brains of all mice exposed to r-mTBI compared to sham controls. With respect to axonal injury, the number of amyloid precursor protein-positive profiles was increased in young vs aged mice post r-mTBI. An increase in tau immunoreactivity was found in young and aged injured male hTau mice. Conclusions: We report the first evidence in our model that r-mTBI precipitates a complex sequelae of events in aged vs young hTau mice at an acute time point, typified by an increase in phosphorylated tau and astroglisosis, and a diminished microgliosis response and axonal injury in aged mice. These findings suggest differential age-dependent effects in TBI pathobiology.