Miracle-dz/UniFAR-FTUs huggingface dataset:
Rôle du strontium en ingénierie tissulaire osseuse pour le développement d’une matrice composite de polysaccharides : application à la technique de Masquelet

La reconstruction de lesions osseuses complexes reste un defi dans le domaine de la chirurgie orthopedique et maxillo-faciale. A ce jour, la technique de reference reste la greffe d’os autologue. Cependant cette technique presente de nombreuses limites (risque d’infection, morbidite au site de prelevement). Dans ce contexte, l’ingenierie tissulaire peut apporter des solutions de reconstruction innovantes. En effet l’utilisation de matrices osteoconductrices et osteoinductrices permettrait de remplacer l’autogreffe. Le premier objectif de ce travail a ete de mettre au point une matrice de polysaccharides, contenant des particules d’hydroxyapatite (HA) dopees avec du strontium (Sr), afin de stimuler a la fois la regeneration osseuse, mais egalement l’angiogenese. Les resultats obtenus in vitro et in vivo nous ont permis d’optimiser la formulation de cette matrice, en termes de quantites de particules d’hydroxyapatite dopees par differents taux de substitution en strontium, dispersees au sein de la matrice. La deuxieme partie de ce travail a ete consacree a l’application de cette matrice a la technique de Masquelet afin de remplacer l’utilisation de l’autogreffe. Cette procedure chirurgicale en deux temps, basee sur la formation d’une membrane induite, est utilisee frequemment en chirurgie orthopedique et maxillo-faciale. Le premier temps operatoire utilise un ciment chirurgical, le (poly(methyl)methalcrylate, PMMA) qui entraine la formation d’une membrane induite vascularisee. Notre travail a ete de remplacer ce ciment par du silicone et d’etudier l’influence de la radiotherapie sur la qualite et la fonction de la membrane ainsi formee. Les premiers essais d’evaluation de cette matrice ont ete realises chez le rat apres resection segmentaire du femur, suivie d’une procedure de radiotherapie. Les perspectives de ce travail sont d’evaluer la performance de cette matrice dans une lesion mandibulaire de grand volume, apres irradiation, chez le gros animal.
Hopping frequency and conductivity relaxation of promising chalcogenides: AC conductivity and dielectric relaxation approaches

Ag2S doped chalcogenide glassy systems have been characterised on the basis of AC conductivity and electric modulus formalism. Various nanophases such as Ag2Se, Te0.5 Se3.5 etc. and dislocation (defects) have been identified and their roles in the conduction process have been established. XRD analysis provides that incorporation of more Ag2S content in the present system should play important role to enhance the dislocation and to decrease the crystallite sizes. The Fourier transform infrared spectra (FT-IR) confirm the characteristic vibration of Ag–S at 500–650 cm−1, stretching vibrations of the O–H bond near 3400 cm−1 and bending vibrations of the adsorbed H2O molecules on the surface of Ag2S near 1600 cm−1. Composition dependent optical phonon frequency (ν0) and Debye temperature (θ D) have been estimated from FT-IR and it is noteworthy that θ D increases with Ag2S content in the compositions up to x = 0.1, but decreases for x = 0.2. This result suggests higher kinetic energy of the constituent atoms/molecules, which may refer to higher electrical conductivity due to polaron hopping. Correlated barrier hopping (CBH) model in its modified version has been found most suitable model to explore the conduction mechanism. Short time relaxation process may be considered to be trivially associated with conduction of polaron. universal scaling approach proposed by Ghosh and Pan has been adopted to interpret electrical relaxation process from time-temperature superposition principle. AC conductivity spectra at various temperatures exhibit a perfect overlap into a single master curve. This feature must be an indication of the temperature independent relaxation process. On the other hand, conductivity spectra of all the compositions at a particular temperature do not exhibit perfect overlapping into a single master curve. This result indicates that the relaxation dynamics of charge carriers (polarons) is strongly dependent on compositions.
Blockchain Based Detection of Android Malware using Ranked Permissions

Android mobile devices are a prime target for a huge number of cyber-criminals as they aim to create malware for disrupting and damaging the servers, clients, or networks. Android malware are in the form of malicious apps, that get downloaded on mobile devices via the Play Store or third-party app markets. Such malicious apps pose serious threats like system damage, information leakage, financial loss to user, etc. Thus, predicting which apps contain malicious behavior will help in preventing malware attacks on mobile devices. Identifying Android malware has become a major challenge because of the ever-increasing number of permissions that applications ask for, to enhance the experience of the users. And most of the times, permissions and other features defined in normal and malicious apps are generally the same. In this paper, we aim to detect Android malware using machine learning, deep learning, and natural language processing techniques. To delve into the problem, we use the Android manifest files which provide us with features like permissions which become the basis for detecting Android malware. We have used the concept of information value for ranking permissions. Further, we have proposed a consensus-based blockchain framework for making more concrete predictions as blockchain have high reliability and low cost. The experimental results demonstrate that the proposed model gives the detection accuracy of 95.44% with the Random Forest classifier. This accuracy is achieved with top 45 permissions ranked according to Information Value.
NDT_A_292249 315..321

1Department of Psychiatry, Tokyo Medical University Hachioji Medical Center, Hachioji-shi, Tokyo, 193-0998, Japan; 2Department of Psychiatry, Tokyo Medical University, Shinjuku-ku, Tokyo,160-0023, Japan Background: Presenteeism is the loss of work productivity of workers owing to physical and mental problems, and its socioeconomic effects are greater than those of absenteeism. Presenteeism is caused by psychological and physical dysfunctions. On the other hand, the regularity of mealtimes is an important factor associated with physical and mental health conditions. We hence assessed the association among the irregularity of mealtimes, presenteeism, psychological and physical stress responses, and sleep disturbance in office workers in companies. Methods: From May to December 2017, the data of 2905 participants who had given their consent to use their information for academic purposes, and answered a questionnaire about the survey and their lifestyle were collected. Path analysis was performed to analyze the association between the irregularity of mealtimes, psychosomatic symptoms (Brief Job Stress Questionnaire), sleep disturbance (Pittsburgh Sleep Questionnaire), and presenteeism (Work Limitations Questionnaire). Results: The direct effect of the irregularity of mealtimes on presenteeism was significant but weak. However, the irregularity of mealtimes had a strong effect on presenteeism indirectly through psychological and physical stress responses and sleep disturbance. Conclusion: Psychological and physical stress responses and sleep disturbance were identified as mediating factors of the effects of irregularity of mealtimes on presenteeism.
Exploring the Associations Between Femininity, Burnout, and Health Behaviors Among Middle Age Women

To date research on how traditional feminine traits and gender role ideology may impact burnout and health behaviors in women is limited. This paper examines how the aforementioned may be associated with higher burnout rates in a community-based cohort of middle-aged women (40-65 years). This study focuses on western traditional feminine traits and gender role ideology, which describe an individual's attitude regarding their assigned role in society and the strength of association with their role. Women who report a stronger connection to more traditional traits or ideology were expected to report higher rates of burnout. This study also assesses whether burnout is associated with engagement in specific health behaviors. The study utilizes survey data from the 2018 Online Midlife Women’s Data Collection survey to examine these factors. Traditional gender ideology was assessed using the Passive Acceptance subscale of the Feminist Identity Development Scale. Feminine traits were assessed using the Bem Sex Role Inventory. Health behaviors included intuitive eating, frequency of cigarette smoking, exercise frequency, and the average weekly number of alcoholic beverages consumed. Burnout is assessed using the Copenhagen Burnout Inventory. Findings indicate that traditional gender ideology was not associated with burnout, while feminine traits (e.g., compassionate, sympathetic) were negatively associated with both personal and work-related burnout. In addition, higher levels of burnout were associated with decreased intuitive eating. Higher levels of burnout and a strong endorsement of traditional gender roles were also associated with less frequent exercise. The frequency of cigarette smoking and number of alcoholic beverages consumed are not associated with any of the predictors assessed. This study is significant in building a stronger understanding of what may cause women to engage or disengage in specific health behaviors. The information gained may be used in future health promotion programs to enhance the lives of middle age women.
Text Mining Based on Social Media –A Survey

—Social Media plays a vital role in the world. These technologies are effectively used to connect friends, family and presently act as effective tool in business communication, vide photos, videos and messages. They basically use tools like Twitter, Facebook, Instagram, Pinterest, Youtube, etc. Social Media is a very useful tool to connect with people and it has some privacy and security. It also provides valuable data in areas of Education, Industries, Web mining, Textmining, Agriculture etc. Among these Text Mining plays a valuable role to Social Media. The Social Media also provides interesting data and also guide in identifying resource-ful contexts. Analyzing social media is slightly complicated process. It also provides solution in areas of Machine Learning, Fuzzy and Support Vector Machine (SVM). This survey deals with papers on Text mining
prace oryginalne or ig in al p a pe rs

Introduction. Nowadays, obesity is an increasing problem in population of schoolchildren. It is connected with oral health, altered facial and stomatognathic system morphology and higher occurence of some ethiological factors leading to malocclusions. Aim. The aim of the study was to check the malocclusions prevalence in overweight/obese schoolchildren children with respect to chosen external ethiological factors as caries, dysfunctions and bad habits. Material and methods. The study was conducted on the group of 120 children aged from 7 to 15 years old, including 60 children with alimentary (simple) overweight and obesity, 26 girls and 34 boys (mean age 10 ± 10 months). The control group was composed of the same number of children adjusted by gender and age to the study sample. Extra and intraoral clinical trial and questionnaire were subjected to statistical analysis χ2. Results. All kind of malocclusions except vertical ones were found out more frequent in overweight children however without statistical difference. In ethiological factors analysis only breathing problems had statistically significant difference.
LiMn2O4 microspheres as high-performance cathode materials for Li-ion batteries

Spinel LiMn2O4 microspheres were prepared by lithiating MnCO3 solid microspheres and MnO2 hollow microspheres, respectively. Li2CO3 was used as lithium source. The spinel LiMn2O4 microspheres samples annealed at different temperatures were characterized by XRD, SEM, and galvanostatic charge/discharge profile measurement. The LiMn2O4 microspheres show an initial discharge capacity reaches 128 mAh/g at 1 C, more than 120 mAh/g of capacity is retained after 80 cycles and the best cycling stability. These results indicate that the LiMn2O4 microspheres could be a promising cathode material for lithium ion batteries.
Using soil and canopy temperature to support efficient management of irrigated vineyards

Extreme heat and drought events are becoming more frequent and erratic in Mediterranean Europe. Better comprehension of spatial and temporal dynamics of heat fluxes and thermal microclimate in vineyards can support vineyard’s management and minimize the impact of climate variability. Field experiments were carried out in South Portugal with two red cvs. Touriga Nacional and Aragonez (syn. Tempranillo) under deficit irrigation. Canopy temperature (Tc) is a robust predictor of plant water status, especially when measured under more stressful conditions. In parallel, soil temperature (TS) had a positive influence on TC especially at the cluster zone.
Modeling of I/O-Intensive Applications in a virtualized Environments

—We construct resource-utilization models for virtual machines running on cloud computing systems. This study is motivated by rapid growth in demand for computation resources in data centers and widespread of cloud computing. Modeling system behaviors of clouds is a grand challenge, because the resource utilization in VMs are heterogeneous in nature due to variability in workload conditions. We address this challenging issue by uniquely (1) objectifying the usage prediction of virtualized resources and (2) predicting the performance trends of programs running on clouds. At the heart of the modeling system, we pay particular attention to CPU cores, disk size, main memory space, and input data volume, which serve as important factors for the developed prediction module. We devise two resource-utilization prediction algorithms driven by two distinctive sets of I/O benchmarks, where one algorithm deals with execution time and another revolves around input data size. We investigate the correlation between the CPU/disk utilization and VM live migrations. Our system aims at not only providing performance optimization for virtualized resources, and Quality of Service (QoS). The model ﬁts the curve quite well, thereby advocating for the efﬁciency of the algorithm. The case studies conducted in this project draw the comparisons between the performance of striped and monolithic disks as well as bringing forth the problem of cache coherence that causes hindrance to the experiment. We also deal with the cache-coherence problem to improve the accuracy of our prediction algorithms.
An Versatile Distinction Structure Based Haze Elimination Method

: Fog cover is by and large present in open air scenes, which restricts the potential for effective data extraction from pictures. In this paper, the objective of the created algorithm is to acquire an optimal transmission delineate well as to expel fogs from a solitary information picture. To take care of the issue, we meticulously dissect the optical model and recast the underlying transmission delineates an extra limit earlier. For better conservation of the outcomes, the distinction structure-safeguarding word reference could be realized with the end goal that the nearby consistency highlights of the transmission guide could be very much saved after coefficient shrinkage. Trial comes about demonstrate that the technique protects the natural appearance of the picture.
Automatic Identi�cation of Upper Extremity Rehabilitation Exercise Type and Dose Using Body-Worn Sensors and Machine Learning: A Pilot Study

Background: Prior studies suggest that participation in rehabilitation exercises improves motor function post-stroke; however, studies on optimal exercise dose and timing have been limited by the technical challenge of quantifying exercise activities over multiple days. Objective: In this exploratory study, we assessed the feasibility of using body-worn sensors to track rehabilitation exercises in the inpatient setting and investigated which recording parameters and data analysis strategies are su�cient for accurately identifying and counting exercise repetitions. Methods: MC10 BioStampRC® sensors were used to measure accelerometry and gyroscopy data from arms of healthy controls (n=13) and patients with upper extremity (UE) weakness due to recent stroke (n=13) while the subjects performed three pre-selected UE exercises. Sensor data was then labeled by exercise type, and this labeled data set was used to train a machine learning classi�cation algorithm for identifying exercise type. The machine-learning algorithm and a peak-nding algorithm were used to count exercise repetitions in non-labeled data sets. Results: We achieved a repetition counting accuracy of 95.6 ± 2.4 % overall, and 95.0 ± 2.3 % in patients with UE weakness due to stroke. Accuracy was decreased when using fewer sensors or using accelerometry data alone. Conclusions: Our exploratory study suggests that body-worn sensor systems are technically feasible, well-tolerated in subjects with recent stroke, and may ultimately be useful for developing a system to measure total exercise “dose” in post-stroke patients during clinical rehabilitation or clinical trials.
Despeckle Filtering for Ultrasound Imaging and Video

It is well known that speckle is amultiplicative noise that degrades image and video quality and the visual expert’s evaluation in ultrasound imaging and video. is necessitates the need for robust despeckling image and video techniques for both routine clinical practice and tele-consultation. e goal for this book (book 1 of 2 books) is to introduce the problem of speckle occurring in ultrasound image and video as well as the theoretical background (equations), the algorithmic steps, and the MATLABTM code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering, and wavelet filtering. is book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts. Despeckle noise reduction through the application of these filters will improve the visual observation quality or it may be used as a pre-processing step for further automated analysis, such as image and video segmentation, and texture characterization in ultrasound cardiovascular imaging, as well as in bandwidth reduction in ultrasound video transmission for telemedicine applications. e aforementioned topics will be covered in detail in the companion book to this one. Furthermore, in order to facilitate further applications we have developed in MATLABTM two different toolboxes that integrate image (IDF) and video (VDF) despeckle filtering, texture analysis, and image and video quality evaluation metrics. e code for these toolsets is open source and these are available to download complementary to the two books.
Culture and Collective Teacher Efficacy: A Case Study in Efficacy

Culture and Collective Teacher Efficacy: A Case Study in Efficacy Scott Jason Benson Department of Educational Leadership and Foundations, BYU Doctor of Education The concept of collective teacher efficacy was first introduced by Bandura (1997) in the 1990’s. Hattie’s (2016) identification of collective teacher efficacy as the number one influence on student achievement has led to the idea that educators within a school have the ability to positively impact student achievement. In his research, Bandura identified four sources of both individual and collective teacher efficacy: mastery experiences, vicarious experiences, social persuasion, and affective state. The purpose of this qualitative research study is to identify aspects of school culture that support collective teacher efficacy. This was done by interviewing 32 members of the faculty and staff at a K-8 school in New Zealand through a lens of social cognitive theory. Qualitative analysis of these interviews identified five core aspects of school culture that contribute to collective teacher efficacy: shared vision for learning, school systems, relationships, well-being, and collaboration. Based on the assumption that collective teacher efficacy can have a positive effect on student achievement, it is my assertion that understanding and applying these five aspects of school culture could have a significant and positive impact on student achievement.
Clinical Outcomes and Prognostic Factors of Salvage Stereotactic Body Radiotherapy for Post-Surgical Thoracic Oligo-Recurrence/ Metastasis of Non-Small-Cell Lung Cancer

Purpose: The study aimed to assess the efficacy and safety of stereotactic body radiotherapy (SBRT) using CyberKnife (CK) in patients with postoperative thoracic oligo-recurrence/metas-tasis of non-small-cell lung cancer (NLCLC), and to analyze the prognostic factors affecting overall survival after SBRT. Patients and Methods: A total of 44 patients with postoperative thoracic oligo-recurrence/metastatic of NLCLC treated with SBRT were reviewed. Thoracic oligo-recurrence/was defined as 1–3 loco-regional confined to lung lobe, hilar/mediastinal lymph nodes, bronchial stump, or chest wall. Primary endpoints included local control (LC), overall survival (OS), progression-free survival (PFS) and toxicity. Prognostic factors that affected these patients were analyzed by the univariate and multivariate analysis by Kaplan–Meier methods and Cox regression models, respectively. Results: The median follow-up time after salvage SBRT was 48.5 months. Measuring from the date of salvage SBRT, the median OS of the 44 patients was 52.60 (95% CI: 29.59–-75.60) months. 1-,3-and 5-year OS rates were 97.7%, 65.3% and 47.7%, respectively. The 1-,3-year and 5-year LC rates were 97.7%, 85.1% and 80.1%, respectively. At 1, 3 and 5 years, the PFS rates were 77.1%, 28.8% and 5.3%, respectively. Multivariate analysis demonstrated that pre-SBRT neutrophil-to-lymphocyte ratio (NLR) and Charlson comorbidity index (CCI) were independent prognostic factors (p < 0.05). The treatment-related side-effects were well tolerated. No patients developed grade 3 or greater pulmonary toxicity. Conclusion: SBRT is a promising salvage therapeutic option for postoperative thoracic oligo-recurrence/metastasis of non-small-cell lung cancer with acceptable toxicity. Low pre-SBRT neutrophil-to-lymphocyte ratio (NLR) and low Charlson comorbidity index (CCI) were associated with a better prognosis and longer survival and might be considered as reliable and independent prognostic factors in these patients treated with SBRT.
The Trojan Horse: Epistemological Explorations Concerning Practice-based Research

Since 00 , art students with a MA title in the Netherlands have been offered the opportunity to obtain a PhD degree. The doctoral dissertation should consist of a work of art, supplemented by a written thesis. This essay discusses the consequences of this development for the academic world. Implicitly it is namely admitted that there exists knowledge that can only be articulated through (non-discursive) art works. The article focuses on the (positive) contribution that artistic research might make to the already existing corpus of knowledge as produced at universities. What this artistic knowledge is, how it can be valued and evaluated and other questions are investigated through the work of Heidegger, Foucault, and Merleau-Ponty.