Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement Properties of the Smartphone-Based B-B Score in Current Shoulder Pathologies

This study is aimed at the determination of the measurement properties of the shoulder function B-B Score measured with a smartphone. This score measures the symmetry between sides of a power-related metric for two selected movements, with 100% representing perfect symmetry. Twenty healthy participants, 20 patients with rotator cuff conditions, 23 with fractures, 22 with capsulitis, and 23 with shoulder instabilities were measured twice across a six-month interval using the B-B Score and shoulder function questionnaires. The discriminative power, responsiveness, diagnostic power, concurrent validity, minimal detectable change (MDC), minimal clinically important improvement (MCII), and patient acceptable symptom state (PASS) were evaluated. Significant differences with the control group and significant baseline—six-month differences were found for the rotator cuff condition, fracture, and capsulitis patient groups. The B-B Score was responsive and demonstrated excellent diagnostic power, except for shoulder instability. The correlations with clinical scores were generally moderate to high, but lower for instability. The MDC was 18.1%, the MCII was 25.2%, and the PASS was 77.6. No floor effect was observed. The B-B Score demonstrated excellent measurement properties in populations with rotator cuff conditions, proximal humerus fractures, and capsulitis, and can thus be used as a routine test to evaluate those patients.
The Intel 80/spl times/86 processor architecture: pitfalls for secure systems

An in-depth analysis of the 80/spl times/86 processor families identifies architectural properties that may have unexpected, and undesirable, results in secure computer systems. In addition, reported implementation errors in some processor versions render them undesirable for secure systems because of potential security and reliability problems. We discuss the imbalance in scrutiny for hardware protection mechanisms relative to software, and why this imbalance is increasingly difficult to justify as hardware complexity increases. We illustrate this difficulty with examples of architectural subtleties and reported implementation errors. <<ETX>>
Design and Implementation of Mobile Robot for Nodes Replacement in Wireless Sensor Networks

Most wireless sensor networks consist of a large number of static, low-power, short-lived, and unreliable sensors. In this paper, we considered sensor networks con- sisting of both static and mobile nodes. Integrating both types of devices enables new applications, such as nodes replacement, hole and partition recovery, and autonomous deployment and redeployment. We designed a smart mobile robot and implemented an application of nodes replacement to demonstrate its use, via our nodes replacement algo- rithm. In this algorithm, the mobile robots can navigate towards low-energy sensor nodes and replace them automatically, with new sensor nodes, having no location information. The navigation algorithm is based on received signal strength between the mobile robot and the communicating node. The experimental results confirm that the mobile robots successfully achieved their assigned tasks.
Galaxy-X: A Novel Approach for Multi-class Classification in an Open Universe

Classification is a fundamental task in machine learning and artificial intelligence. Existing classification methods are designed to classify unknown instances within a set of previously known classes that are seen in training. Such classification takes the form of prediction within a closed-set. However, a more realistic scenario that fits the ground truth of real world applications is to consider the possibility of encountering instances that do not belong to any of the classes that are seen in training, $i.e.$, an open-set classification. In such situation, existing closed-set classification methods will assign a training label to these instances resulting in a misclassification. In this paper, we introduce Galaxy-X, a novel multi-class classification method for open-set problem. For each class of the training set, Galaxy-X creates a minimum bounding hyper-sphere that encompasses the distribution of the class by enclosing all of its instances. In such manner, our method is able to distinguish instances resembling previously seen classes from those that are of unseen classes. To adequately evaluate open-set classification, we introduce a novel evaluation procedure. Experimental results on benchmark datasets as well as on synthetic datasets show the efficiency of our approach in classifying novel instances from known as well as unknown classes.
Density of in-vitro fertilization centers and its correlation with socioeconomic factors in Maharashtra state, India

Background: The infertility due to various reasons is increasing and correspondingly the number in vitro fertilization (IVF) centers is also increasing. Some procedures in these centers can deliver desired sex of the unborn child. The gender discrimination in India has already resulted unfavorable child sex ratio for girls. Maharashtra is one of the badly affected states. It is feared that the child sex ratio may further decline due to IVF centers. The study was carried out to measure correlation between number of IVF centers with various indicators of sex ratio infertility, and some socio-economic factors.Methods: The study was conducted in 2014 using secondary data. District wise internet search by using words ‘In-Vitro Fertilization center’ and ‘infertility treatment center’ was carried out. Whenever IVF center/procedure was noticed on the internet, the center with its address was included in that district list.Results: There was positive correlation between IVF centers and urbanization, per capita income, female literacy and negative correlation with population sex ratio and no correlation with sex ratio at birth or child sex ratio. The best correlation was observed with urbanization, which explains the observed correlation with other variables.Conclusions: The number of IVF centers is not related with magnitude of infertility and not affecting sex ratio whereas IVF density seems to be an outcome of extent of urbanization.
Performance of data querying operations in Universal Mobile Telecommunication Systems (UMTS)

The anticipated emergence of third-generation mobile systems, referred to as Universal Mobile Telecommunication Systems (UMTS), raises the problem of reconsidering the design of the databases destined to contain the user information. In particular, it is expected that the key concepts of the new database architectures will be high distribution and fast updating of information. This paper presents a methodology which allows for structural alternatives of DDB architectures differing in the number of levels and branches in the hierarchy, to be evaluated in terms of query loads and mean response times, according to a given user mobility characterization. The paper also discusses a case study concerning a query operation arising from a location updating procedure.
Performance of some evapotranspiration equations at a site in Quebec

Evapotranspiration (ET) estimates were made for a reference crop using the Modified Penman, Jensen-Haise, Baier-Robertson (Laval), FAO Blaney-Criddle, and SCS Blaney-Criddle equations. Results obtained from the five equations were compared to pan-based evapotranspiration data taken from a site at St. Esprit, Quebec. On a seasonal basis, the Baier-Robertson (Laval) equation provided seasonal potential ET estimates within 10% of adjusted pan evaporation values. The Modified Penman, FAO Blaney-Criddle, and SCS Blaney-Criddle equations produced seasonal ET estimates within 10 to 25% of corrected pan ET data. The Jensen-Haise equation consistently predicted lower seasonal values of ET, with an average seasonal difference of approximately 50% compared to the corrected pan evaporation values. Seasonal ET estimates with the Baier-Robertson equation were not significantly different than corrected pan ET data at the 0.05 level of significance.
Visualisation d'événements enrichis par des images satellites et des données ouvertes : application aux données sismiques

Cet article presente un mecanisme d'enrichissement d'evenements a partir de sources de donnees ouvertes, geolocalisees et datees, en exploitant les relations spatiales et temporelles. Nous validons cette approche sur des donnees sismiques, des enregistrements de metadonnees d'images satellites et des donnees meteorologiques. On peut ainsi voir les zones impactees par un seisme et connaitre les conditions meteorologiques avant, pendant et apres l'evenement. Nous presentons un outil de visualisation qui permet de selectionner une zone d'interet et de visualiser les donnees enrichies correspondantes.
Studying the evolution of the Eclipse Java editor

In evolutionary software development, knowing how design evolves with features can be valuable in guiding future projects. It helps answer questions like "How much upfront design should and can be done? " and "How and why are designs changed? " To shed light on these questions, we report on a study of the evolution history of the Eclipse Java editor. We find that the MVC-based design was cleanly laid out in the beginning of the project and carefully followed and maintained, which has contributed positively to the continuous growth of the editor features. Although design changes at the individual feature level happened for reasons like extensibility and reusability, they appear to be local and manageable. The AST facility is a key service that enables more than one half of the Java editor features.
Guidelines for large photovoltaic system integration

The paper summarizes the result of a research project funded by the Department of Energy (DOE) in collaboration with the University of California at San Diego (UCSD), [1]. One presents a planning guideline and establishes interconnection criteria for integrating Photo Voltaic Generation (PVG) into the power systems (transmission and distribution). Some of the experiences/guidelines in the field of wind farm integration are used here since wind generation and PVG generation share many common power electronics devices used in their control schemes and both generation types are intermittent resources with similar degree of predictability and forecast methodology. Recommendations are given on the best practice promising standards for interconnecting large PV generation to power system.
Weighted difference entropy based similarity measure at two levels in a recommendation framework

Presenting small chunks of interesting information to a target user from the large pool of information available on World Wide Web are the primary task of a recommender system. Memory based Collaborative Filtering generates recommendations based on preferences of those users whose past preferences are similar to the current preferences of the target user. These users collectively form the Nearest Neighbor Set (NN Set) of the target user. The better the selection of NN Set, the better is the generation of recommendations. In the proposed scheme, the user ratings (preferences) on the available items are divided into two levels. Level I consist of ratings on popular items and Level II consist of ratings on unpopular items. The proposed similarity measure, “TSimD(UX1,UX2)”, between two users is based on weighted difference entropy. Modified memory based Collaborative Filtering calculates the proposed similarity measure at both the levels to improve the selection of users in the NN Set of the target user. It selects those users in the NN Set who are more similar to the target user with respect to items at Level II as compared to similarity between them with respect to items at Level I. The results on Movie Lens dataset depicted that the proposed similarity measure had higher accuracy than the Weighted Difference Entropy based similarity measure which worked on the entire preferences of the users. The proposed similarity measure was also compared with other similarity measures (like Cosine, Pearson Correlation, Spearman and Rating Frequency based Similarity Measure) which were also obtained at two levels.
A visual–textual fused approach to automated tagging of flood-related tweets during a flood event

ABSTRACT In recent years, social media such as Twitter have received much attention as a new data source for rapid flood awareness. The timely response and large coverage provided by citizen sensors significantly compensate the limitations of non-timely remote sensing data and spatially isolated river gauges. However, automatic extraction of flood tweets from a massive tweets pool remains a challenge. Taking the Houston Flood in 2017 as a study case, this paper presents an automated flood tweets extraction approach by mining both visual and textual information a tweet contains. A CNN architecture was designed to classify the visual content of flood pictures during the Houston Flood. A sensitivity test was then applied to extract flood-sensitive keywords that were further used to refine the CNN classified results. A duplication test was finally performed to trim the database by removing the duplicated pictures to create the flood tweets pool for the flood event. The results indicated that coupling CNN classification results with flood-sensitive words in tweets allows a significant increase in precision while keeps the recall rate in a high level. The elimination of tweets containing duplicated pictures greatly contributes to higher spatio-temporal relevance to the flood.
Effect of Macrograzers (Campostoma spp. and Faxonius spp.) on Periphyton in Ozark Streams with Considerations Given to Macrograzer Biomass, Phosphorus, and Season: Mensurative and Manipulative Studies

Nutrient and benthic algal biomass relationships can guide numeric nutrient criteria development in lotic systems. However, herbivorous macrograzers may confound this relationship by reducing the slope of the positive relationship between nutrients and periphyton biomass in streams. I conducted a mensurative field study to determine if stoneroller and crayfish abundance related to algal biomass at varying nutrient concentrations and manipulated macrograzer presence with electrical exclosures in streams to examine macrograzer effects on algal biomass and understand whether these effects on periphyton varied with total phosphorus (TP) or season. Macrograzer density was quantified across a TP gradient (n=15 streams; range = 0.009-0.100 mg TP/L) in August 2015 and manipulative exclosure experiments were completed in a subset of these streams in late summer 2016 (n=5, range = 0.0025-0.140 mg TP/L) and winter 2017 (n=3, range 0.001-0.49 mg TP/L). Multiple linear regression of mensurative field data revealed a statistically-significant positive relationship between macrograzer abundance, nutrient levels, and algal biomass. In the manipulative experiments, macrograzer presence did not influence algal biomass. Benthic algal biomass did vary over time in 3 of the 5 stream, which may be due to stream flow permanence or intermittence. Macrograzer effect on algal biomass was not significant and did not depend on TP or season. The positive relationship between macrograzers on algal biomass measures in the mensurative abundance study was not corroborated by the manipulative experiment, but indirect positive effects of macrograzers may have been equal to direct negative consumptive effects making grazed and ungrazed algal biomass equal. Many previous studies observed a negative influence of macrograzers on filaments lengths of benthic algae with mixed effect on chlorophyll a and ash-free dry mass measures (algal biomass measures), but no or positive relationships were found in the present study. Effects abundance and exclosure study may indicate indirect stimulatory effects of macrograzers on stream algal biomass where high abundances of macrograzers and TP may produce systems dominated by autotrophic processes. These studies highlight the importance of considering indirect effects of macrograzers on periphyton biomass.
Expression of liver alpha-amylase in obese mouse hepatocytes

Aim: The aim of this study is to demonstrate the relation between the expression of liver alpha-amylase and obesity. Background: Alpha-amylase catalyses the hydrolysis of 1, 4-alpha-glucosidic linkages in polysaccharides and has three main subtypes, including: salivary, pancreatic, and hepatic. Hepatic alpha-amylase is involved in glycogen metabolism, and has a role in obesity and its management. In this study, we aimed to analyze the expression of liver alpha-amylase in overweight and obese mouse. Material and methods: In this study, NMRI male mice were randomly divided into two groups. The sample group (obese) took a high-fat and carbohydrate diet, while the control group (normal) took a laboratory pellet chow for eight weeks. During this period, their weight was measured. After eight weeks, liver hepatocytes were isolated using an enzymatic digestion method. Immunocytochemistry (ICC) and flow cytometry analysis were performed to measure alpha amylase protein expression in mouse liver hepatocyte cells. Results: A significant difference in the body weight was observed between the two groups (p<0.05). The qualitative protein expression of liver alpha-amylase was found to be higher in the obese group in both tests (immunocytochemistry and flow cytometry). Animals from the test group presented higher alpha-amylase expression, which suggests that this hepatic protein may constitute a potential indicator of susceptibility for fat tissue accumulation and obesity. The present data demonstrates an increased expression of liver amylase in obese mice. Conclusion: These results suggest that liver amylase secretion might be useful for predicting susceptibility to obesity induced by consumption of a high-fat and carbohydrate diet.
Improved Dual Boost Inverter With Half Cycle Modulation

The output voltage of a traditional full-bridge inverter is lower than the input dc voltage. In applications when the input voltage is low, the front-end step-up converter is usually required, presenting a two-stage power conversion. Dual boost inverter (DBI) can realize single-stage conversion, which has the advantages of a simple structure, less power devices, and buck–boost ability. The traditional modulation strategy of DBI makes all power switches operate in high frequency and sustain high voltage/current stress, which leads to heavy conduction and switching loss. This paper proposed a modulation strategy, namely, half cycle modulation (HCM), which makes power switches work in high frequency just in half cycle, and can greatly reduce the conduction and switching loss of the power devices. Furthermore, to reduce the current circulation loss in DBI, an improved DBI with two clamping switches is proposed based on HCM, which can bypass the inductor current with low stress switches; therefore, the loss caused by circulation current can be greatly reduced. A detailed analysis and comparison between the traditional and HCM strategies are given in this paper. Finally, a 500 VA DBI prototype is designed in the lab. The advantages of the proposed HCM strategy and improved DBI with two clamping switches are verified by experimental results.
Decreased adiponectin levels in familial combined hyperlipidemia patients contribute to the atherogenic lipid profile Published, JLR Papers in Press, August 16, 2005. DOI 10.1194/jlr.M500212-JLR200

Familial combined hyperlipidemia (FCH) is characterized by increased levels of total cholesterol, triglycerides, and/or apolipoprotein B. Other features of FCH are obesity and insulin resistance. Adiponectin is a secretory product of the adipose tissue. Low levels of adiponectin are associated with insulin resistance and accelerated atherosclerosis. The aim of this study was to determine whether decreased adiponectin levels are associated with FCH and its phenotypes. The study population comprised 644 subjects, including 158 patients with FCH. Serum adiponectin levels were determined using a commercially available ELISA. For both males and females, the mean adiponectin level (μg/ml) was significantly lower in FCH patients [2.0 (1.8–2.2) and 2.5 (2.3–2.8), respectively] compared with normolipidemic relatives [2.3 (2.2–2.5) and 3.1 (2.8–3.3), respectively] and spouses [2.4 (2.1–2.7) and 3.2 (2.8–3.6), respectively]. These differences remain significant after adjusting for waist circumference and insulin resistance. Low adiponectin level in FCH patients was a superior independent predictor of the atherogenic lipid profile, including high triglyceride levels, low HDL-cholesterol levels, and the amount of small, dense LDL present, compared with both obesity and insulin resistance. Low adiponectin levels may contribute to the atherogenic lipid profile in FCH, independent of insulin resistance and obesity, as measured by waist circumference. This finding implies a role of adipose tissue metabolism in the pathophysiology of FCH.
Propagating Users' Similarity towards Improving Recommender Systems

In this paper we examine an advanced collaborative filtering method that uses similarity transitivity concepts. By propagating "similarity" between users, in a similar way as with "trust", we can significantly expand the space of potential recommenders and system's coverage, improving also the recommendations' accuracy. While "trust" information might be missing or be misleading and incorrect, "similarity" between two users can be directly calculated using the information from users' item ratings. A recent study observed a strong correlation between trust and preference similarity in online rating systems, therefore it makes sense that transitivity concepts can also be applied to "similarity", much as they are applied to "trust". In contrast to a vast amount of work that seeks to exploit existed social information, like trust, from social networks to improve the recommendation process, we propose the other way round towards the same goal: use similarity transitivity concepts exploiting the rating history of the recommender system's users to lead to the formation of new relationships and even social communities that were not previously existed. We propose a novel similarity propagation scheme to confront the data sparsity problem in recommender systems and evaluate our method over two datasets with different characteristics, exhibiting a much higher recommendation coverage and better accuracy than classical collaborative filtering methods even under very sparse data conditions.