Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating and Learning the Trajectory of Mobile Phones

This project is based on the ongoing data collection campaign by Nokia Re- search Center-Lausanne. We use location data sampled everyday by mobile phones in the campaign to estimate position of the participants. It is with emerging mobile systems that combines different sensors in a mobile phone so, we can merge different information sources to improve our estimations. Positioning is a problem encountered frequently in many applications. GPS is widely used for positioning but its output is noisy and it does not work in every location. Considering the embedded sensors and processing capacity of mobile phone, we can improve positioning of clients by other data like visited GSM cell and Wireless LANs. In addition, for situations where GPS does not work such as indoors, we can lay on these information to locate the user. Although most mobile phones are equipped with GPS receivers, users prefer to keep them turned off because of their considerable battery consumption. On the other hand, people usually take determined paths when they want to travel among places that they frequently visit. Learning these trajectories helps to keep GPS receiver turned off and localize users by other sources of information. We describe a new positioning algorithm with two modes of operations: one for cases that we have GPS signals and the other for times that there is not any GPS signal. This work also outlines a new algorithm, based on undergoing Nokia data collection campaign, for positioning and navigating of participants among their recurrent locations.
The Relationships among Type D Personality, Self-Resilience, and Health Promoting Behaviors in Nursing Students

The purpose of this study was to examine the relationships among type D personality, self-resilience, and health promoting behaviors in nursing students. Participants in this cross-sectional study were 517 nursing students from three universities in South Korea who completed a structured self-report questionnaire. Data were collected from March to June 2013, and were analyzed using multiple regression analysis with SPSS ver. 18.0. The mean scores of self-resilience (t = -6.154, P < 0.001) and health promoting behaviors (t = -6.444, P < 0.001) were significantly different between the Type D and non-Type D personality groups. Grade, self-esteem, Type D personality, and self-resilience were significant predictors of health promoting behaviors, accounting for 34.8% of its variance (F = 25.714, P < 0.001). Of these four variables, self-resilience was the most significant contributor to health promoting behaviors in nursing students. Health promotion programs for nursing students should be designed and developed with consideration of interventions for psychological variables such as Type D personality and self-resilience.
Genome variation and meiotic recombination in Plasmodium falciparum: insights from deep sequencing of genetic crosses

The malaria parasite Plasmodium falciparum has a great capacity for evolutionary adaptation to evade host immunity and develop drug resistance. Current understanding of parasite evolution is impeded by the fact that a large fraction of the genome is either highly repetitive or highly variable, and thus difficult to analyse using short read technologies. Here we describe a resource of deep sequencing data on parents and progeny from genetic crosses, which has enabled us to perform the first genome-wide, integrated analysis of SNP, INDEL and complex polymorphisms, using Mendelian error rates as an indicator of genotypic accuracy. These data reveal that INDELs are exceptionally abundant, being more common than SNPs and thus the dominant mode of polymorphism within the core genome. We use the high density of SNP and INDEL markers to analyse patterns of meiotic recombination, confirming a high rate of crossover events, and providing the first estimates for the rate of non-crossover events and the length of conversion tracts. We observe several instances of recombination that modify copy number variants associated with drug resistance, demonstrating a mechanism whereby fitness costs associated with resistance mutations could be compensated and greater phenotypic plasticity could be acquired. We describe a novel web application that allows these data to be explored in detail.
Impact of Design Patterns on Software Maintainability

This paper mainly studies the effect of design patterns on the Software maintainability. Design patterns describe solutions for common design problems and they were introduced to improve software quality and accelerate software development. However, there are some difficulties to choose an optimal pattern adapted to a certain application and problem. So until now the results on the effect of design patterns on software quality are controversial. In this context, we propose a tool for design pattern guided that retrieves the appropriate pattern with respect to software maintainability from a repository of patterns. It measures the maintainability of design pattern by some metrics and candidate the more maintainable pattern to the designer or developer. It provides a support for decision making during system design and refactoring. As the results, the decision of applying a certain design pattern is usually a trade- off since the effect of design pattern on software maintainability is influenced by some factors such as the pattern size and the prior expertise of the developer.
Quality evaluation of fish and other seafood by traditional and nondestructive instrumental methods: Advantages and limitations

abstract Although being one of the most vulnerable and perishable products, fish and other seafoods provide a wide range of health-promoting compounds. Recently, the growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Several traditional physicochemical, textural, sensory, and electrical methods have been used to evaluate freshness and authentication of fish and other seafood products. Despite the importance of these standard methods, they are expensive and time-consuming, and often susceptible to large sources of variation. Recently, spectroscopic methods and other emerging techniques have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any online monitoring system. This review describes firstly and briefly the basic principles of multivariate data analysis, followed by the most commonly traditional methods used for the determination of the freshness and authenticity of fish and other seafood products. A special focus is put on the use of rapid and nondestructive techniques (spectroscopic techniques and instrumental sensors) to address several issues related to the quality of these products. Moreover, the advantages and limitations of each technique are reviewed and some perspectives are also given.
Redistribution of soluble N-ethylmaleimide-sensitive-factor attachment protein receptors in mouse sperm membranes prior to the acrosome reaction†

Abstract Formation of complexes between soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) proteins on opposing membranes is the minimal requirement for intracellular membrane fusion. The SNARE, syntaxin 2, is found on the sperm plasma membrane and a second SNARE, vesicle associated membrane protein 2 (VAMP2, also known as synaptobrevin 2, SYB2), is on the apposing outer acrosomal membrane. During the acrosome reaction, the outer acrosomal membrane fuses at hundreds of points with the plasma membrane. We hypothesized that syntaxin 2 and VAMP2 redistribute within their respective membranes prior to the acrosome reaction to form trans-SNARE complexes and promote membrane fusion. Immunofluorescence and superresolution structured illumination microscopy were used to localize syntaxin 2 and VAMP2 in mouse sperm during capacitation. Initially, syntaxin 2 was found in puncta throughout the acrosomal region. At 60 and 120 min of capacitation, syntaxin 2 was localized in puncta primarily in the apical ridge. Although deletion of bicarbonate during incubation had no effect, syntaxin 2 puncta were relocated in the restricted region in less than 20% of sperm incubated without albumin. In contrast, VAMP2 was already found in puncta within the apical ridge prior to capacitation. The puncta containing syntaxin 2 and VAMP2 did not precisely co-localize at 0 or 60 min of capacitation time. In summary, syntaxin 2 shifted its location to the apical ridge on the plasma membrane during capacitation in an albumin-dependent manner but VAMP2 was already localized to the apical ridge. Puncta containing VAMP2 did not co-localize with those containing syntaxin 2 during capacitation; therefore, formation of trans-SNARE complexes containing these SNAREs does not occur until after capacitation, immediately prior to acrosomal exocytosis. Summary Sentence Although the sperm plasma membrane SNARE protein syntaxin 2 moves laterally, trans-SNARE complexes are not formed during capacitation.
Semi-supervised learning in MCI-to-ad conversion prediction — When is unlabeled data useful?

This paper investigates the use of semi-supervised learning (SSL) for predicting Alzheimers Disease (AD) conversion in Mild Cognitive Impairment (MCI) patients based on Magnetic Resonance Imaging (MRI). SSL methods differ from standard supervised learning methods in that they make use of unlabeled data - in this case data from MCI subjects whose final diagnosis is not yet known. We compare two widely used semi-supervised methods (low density separation (LDS) and semi-supervised discriminant analysis (SDA)) to the corresponding supervised methods using real and synthetic MRI data of MCI subjects. With simulated data, using SSL instead of supervised learning led to higher classification performance in certain cases, however, the applicability of semi-supervised methods depended strongly on the data distributions. With real MRI data, the SSL methods achieved significantly better classification performances over supervised methods. Moreover, even using a small number of unlabeled samples improved the AD conversion predictions.
tullioFoam - A numerical model of the Tullio phenomenon

This user guide explains the numerical solver tullioFoam which is used to study the fluid dynamics behind the Tullio phenomenon. The Tullio phenomenon is a pathological effect which has been observed in patients with a superior canal dehiscence in the vestibular system of the inner ear. The corresponding C++ source code is given in the appendix, along with a test case. In order to compile and run, it requires the user to install the open source libraries of OpenFOAM-1.6-ext and Armadillo.
An Efficient Hybrid Push-Pull Based Protocol for VOD In Peer- to-Peer network

Video-on-Demand is a service where movies are delivered to distributed users with low delay and free interactivity. The traditional client-server architecture experiences scalability issues to provide video streaming services. Peer-to-Peer (P2P) techniques for video on demand (VOD) have been shown to be a good enhancement to the traditional client/server methods when trying to reduce costs, increase robustness and solve the scalability issues. Various challenges arise when building a resilient P2P video on demand systems, such as long waiting time to receive the video segments and the quality of service. A new proposed data exchange schema is called Efficient Hybrid Push-Pull based Protocol (EHP3) can reduce the initial playback delay and improve the quality of service. The downstream peer has to accelerate the downloading process of the urgent segments, i.e. those missing segments which are near their playback time. The range of the urgent segments is referred to as the priority region. The upstream peers give a strict priority to segments within the priority region. If the downstream peer has sufficient download bandwidth, it should be able to completely receive these urgent segments before playback time. If there are no missing segments in the priority region, the downstream peer uses the pull protocol to download the missing segments which are outside the priority region. The simulation result shows that the proposed data exchange schema (EHP3) can reduce the initial play back delay and reduce the burden on the server side by increasing the number of caching segments in the playback buffer. Moreover, the proposed schema improves the quality of service by reducing the number of skipped segments during the playback.
Expression of Wilms tumor 1 gene distinguishes vascular malformations from proliferative endothelial lesions.

BACKGROUND Vascular malformations and hemangiomas, which are endothelial lesions of childhood, may result in considerable morbidity because they can cause discomfort and functional impairment and have a negative affect on the patient's appearance. Although vascular malformations may initially appear very similar to hemangiomas, they have distinct clinical courses. Infantile hemangiomas progress through 3 stages: proliferative, involuting, and involuted. The proliferative phase is characterized by clinical growth. Once hemangiomas reach their maximum size, they begin to regress or involute. Histologically, this stage is characterized by endothelial apoptosis. Finally, the involuted stage of the hemangioma occurs when the original lesion is replaced by a connective tissue remnant. In contrast to hemangiomas, vascular malformations do not involute but continue to enlarge as the patient grows. OBSERVATIONS The biochemical differences between hemangiomas, which involute, and vascular malformations, which do not involute, are not well understood. We found that the transcription factor encoded by the Wilms tumor 1 (WT1) gene is expressed in the endothelium of hemangiomas but not in vascular malformations. CONCLUSIONS Defects in WT1 signaling may underlie the inability of malformation endothelial cells to undergo physiologic apoptosis and remodeling. The availability of WT1 staining in hospital laboratories may allow the clinician to distinguish hemangiomas from vascular malformations and thus to give appropriate therapy to the patient.
Features, modularity, and variation points

A feature interaction algebra (FIA) is an abstract model of features, feature interactions, and their compositions. A structured document algebra (SDA) defines modules with variation points and how such modules compose. We present both FIA and SDA in this paper, and homomorphisms that relate FIA expressions to SDA expressions. This leads to mathematically precise formalizations of fundamental concepts used in software product lines, which can be used for improved FOSD tooling and teaching material.
Deriving Linear Algebra Libraries FLAME Working Note # 57

Starting in the late 1960s computer scientists including Dijkstra and Hoare advocated goal-oriented programming and formal derivation of algorithms. The problem was that for loop-based programs, a priori determination of loop-invariants, a prerequisite for developing loops, was a task too complex for any but the simplest of operations. We believe that no practical progress was made in the field until around 2000 when we discovered how to systematically determine loop-invariants for operations in the domain of high-performance dense linear algebra libraries. This has led to a multitude of papers, mostly published in the ACM Transactions for Mathematical Software. It has yielded a system for mechanical derivation of algorithms and a high-performance linear algebra library, libflame, that is largely derived to be correct and includes more than a thousand algorithmic variants of algorithms for more than a hundred linear algebra operations. To our knowledge, this success story has unfolded without any awareness on the part the formal methods community. This paper is meant to raise that awareness.
Two-Component Signaling Regulates Osmotic Stress Adaptation via SskA and the High-Osmolarity Glycerol MAPK Pathway in the Human Pathogen Talaromyces marneffei

This is the first study in a dimorphic fungal pathogen to investigate the role of a response regulator downstream of two-component signaling systems and its connection to the high-osmolarity glycerol pathway. This study will inspire further research into the downstream components of two-component signaling systems and their role during pathogenic growth. ABSTRACT For successful infection to occur, a pathogen must be able to evade or tolerate the host’s defense systems. This requires the pathogen to first recognize the host environment and then signal this response to elicit a complex adaptive program in order to activate its own defense strategies. In both prokaryotes and eukaryotes, two-component signaling systems are utilized to sense and respond to changes in the external environment. The hybrid histidine kinases (HHKs) at the start of the two-component signaling pathway have been well characterized in human pathogens. However, how these HHKs regulate processes downstream currently remains unclear. This study describes the role of a response regulator downstream of these HHKs, sskA, in Talaromyces marneffei, a dimorphic human pathogen. sskA is required for asexual reproduction, hyphal morphogenesis, cell wall integrity, osmotic adaptation, and the morphogenesis of yeast cells both in vitro at 37°C and during macrophage infection, but not during dimorphic switching. Comparison of the ΔsskA mutant with a strain in which the mitogen-activated protein kinase (MAPK) of the high-osmolarity glycerol pathway (SakA) has been deleted suggests that SskA acts upstream of this pathway in T. marneffei to regulate these morphogenetic processes. This was confirmed by assessing the amount of phosphorylated SakA in the ΔsskA mutant, antifungal resistance due to a lack of SakA activation, and the ability of a constitutively active sakA allele (sakAF316L) to suppress the ΔsskA mutant phenotypes. We conclude that SskA regulates morphogenesis and osmotic stress adaptation in T. marneffei via phosphorylation of the SakA MAPK of the high-osmolarity glycerol pathway. IMPORTANCE This is the first study in a dimorphic fungal pathogen to investigate the role of a response regulator downstream of two-component signaling systems and its connection to the high-osmolarity glycerol pathway. This study will inspire further research into the downstream components of two-component signaling systems and their role during pathogenic growth.
High-sensitivity C-reactive protein is a good marker of cardiovascular risk in obese children and adolescents.

OBJECTIVE We intend to assess the utility of the high-sensitivity C-reactive protein (hs-CRP) as a marker of cardiovascular risk in obese children and adolescents. METHODS The study included children and adolescents between 6 and 18 years of age with a body mass index (BMI) higher than 2 SDS. All the patients had their blood pressure taken and hs-CRP, hepatic function, lipid profile and uric acid were determined after 12 h of fasting. Likewise, an oral glucose tolerance test was performed, determining basal glucose and insulin levels, and after stimulus. We considered the presence of metabolic syndrome when the obese children and teenagers showed at least two of the following conditions: decreased high density lipoprotein (HDL)-cholesterol, hypertriglyceridemia, hypertension or alteration in glucose metabolism. RESULTS Out of the 115 obese children studied, 24% showed signs of metabolic syndrome. Those with metabolic syndrome presented higher levels of hs-CRP (mean: 3.8 mg/l; 95% CI: 2.8-4.8) in comparison with the obese patients who did not show signs of metabolic syndrome (mean: 2 mg/l; 95% CI: 1.5-2.5). After a multivariate analysis, the variables that appear to influence the changes in hs-CRP were BMI, triglycerides and HDL-cholesterol levels. CONCLUSION The hs-CRP is a useful tool for early diagnosis of cardiovascular risk in obese children and teenagers.
Assessing ADHD Across Settings: Contributions of Behavioral Assessment to Categorical Decision Making

Adapted methods of behavioral assessment to assess home and school functioning in a way that maps directly to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., [DSM-IV]; American Psychiatric Association, 1994). The study was conducted in a school-based sample with 5- to 12-year-old children referred to a school intervention team. A multigate set of procedures was used to assign children to one of 3 groups: attention deficit hyperactivity disorder (ADHD), inattentive group; ADHD, combined group; and a non-ADHD control group. The ADHD Rating Scale-IV was used to assess parent and teacher ratings of ADHD symptoms as delineated in DSM-IV. The findings suggest that the use of a fixed cutoff point (i.e., 6 or more symptoms), which is employed in the DSM-IV, is often not the best strategy for making diagnostic decisions. The optimal approach depends on whether diagnostic information is being provided by the parent or teacher and whether the purpose of assessment is to conduct a screening or a diagnostic evaluation. Also, the results indicate that a strategy that aggregates symptoms in the order in which they are accurate in predicting a diagnosis of ADHD is a more effective strategy than the approach used in DSM-IV, which aggregates any combination of a specific number of items. Implications for using methods of behavioral assessment to make diagnostic decisions using DSM-IV criteria are discussed.
MRMOGA: a new parallel multi‐objective evolutionary algorithm based on the use of multiple resolutions

In this paper, we introduce MRMOGA (Multiple Resolution Multi‐Objective Genetic Algorithm), a new parallel multi‐objective evolutionary algorithm which is based on an injection island approach. This approach is characterized by adopting an encoding of solutions which uses a different resolution for each island. This approach allows us to divide the decision variable space into well‐defined overlapped regions to achieve an efficient use of multiple processors. Also, this approach guarantees that the processors only generate solutions within their assigned region. In order to assess the performance of our proposed approach, we compare it to a parallel version of an algorithm that is representative of the state‐of‐the‐art in the area, using standard test functions and performance measures reported in the specialized literature. Our results indicate that our proposed approach is a viable alternative to solve multi‐objective optimization problems in parallel, particularly when dealing with large search spaces. Copyright © 2006 John Wiley & Sons, Ltd.
Image demosaicing by non-local similarity and local correlation

Conventional single-chip digital cameras use color filter arrays(CFA) to sample different spectral components. Image demosaicing is a problem of interpolating these data to complete red, green, and blue values for each image pixel, to produce an RGB image. Many color demosaicing(CDM) methods assume that the high local spatial redundancy exists among the color samples. Such an assumption, however, may be fail for images with high color saturation and sharp color transitions. This paper presents an adaptive demosaicing algorithm by exploiting both the non-local similarity and the local correlation(NLS-LC) in the color filter array image. First, the most flattest nonlocal image patches are searched in the searching window centered on the estimated pixel. Second, the patch, which is the most similar to the current patch, is selected among the most smoothest nonlocal patches. Third, according to the similar degree and the local correlation degree, the obtained nonlocal image patch and the current patch are adaptively chosen to estimate the missing color samples. Experimental results indicate that the proposed method exhibits superior performance over many state-of-the-art color interpolation methods.