Miracle-dz/UniFAR-FTUs huggingface dataset:
Canine MPV17 truncation without clinical manifestations

ABSTRACT Mitochondrial DNA depletion syndromes (MDS) are often serious autosomal recessively inherited disorders characterized by tissue-specific mtDNA copy number reduction. Many genes, including MPV17, are associated with the hepatocerebral form of MDS. MPV17 encodes for a mitochondrial inner membrane protein with a poorly characterized function. Several MPV17 mutations have been reported in association with a heterogeneous group of early-onset manifestations, including liver disease and neurological problems. Mpv17-deficient mice present renal and hearing defects. We describe here a MPV17 truncation mutation in dogs. We found a 1-bp insertion in exon 4 of the MPV17 gene, resulting in a frameshift and early truncation of the encoded protein. The mutation halves MPV17 expression in the lymphocytes of the homozygous dogs and the truncated protein is not translated in transfected cells. The insertion mutation is recurrent and exists in many unrelated breeds, although is highly enriched in the Boxer breed. Unexpectedly, despite the truncation of MPV17, we could not find any common phenotypes in the genetically affected dogs. The lack of observable phenotype could be due to a late onset, mild symptoms or potential tissue-specific compensatory mechanisms. This study suggests species-specific differences in the manifestation of the MPV17 defects and establishes a novel large animal model to further study MPV17 function and role in mitochondrial biology.
Rumination Mediates the Prospective Effect of Low Self-Esteem on Depression

Previous research supports the vulnerability model of low self-esteem and depression, which states that low self-esteem operates as a prospective risk factor for depression. However, it is unclear which processes mediate the effect of low self-esteem. To test for the mediating effect of rumination, the authors used longitudinal mediation models, which included exclusively prospective effects and controlled for autoregressive effects of the constructs. Data came from 663 individuals (aged 16 to 62 years), who were assessed 5 times over an 8-month period. The results indicated that low self-esteem predicted subsequent rumination, which in turn predicted subsequent depression, and that rumination partially mediated the prospective effect of low self-esteem on depression. These findings held for both men and women, and for both affective-cognitive and somatic symptoms of depression. Future studies should test for the mediating effects of additional intrapersonal and interpersonal processes.
Three Dimensional Motion Trail Model for Gesture Recognition

In this paper an effective method is presented to recognize human gestures from sequences of depth images. Specifically, we propose a three dimensional motion trail model (3D-MTM) to explicitly represent the dynamics and statics of gestures in 3D space. In 2D space, the motion trail model (2D-MTM) consists of both motion information and static posture information over the gesture sequence along the xoy-plane. Considering gestures are performed in 3D space, depth images are projected onto two other planes to encode additional gesture information. The 2D-MTM is then extensively combined with complementary motion information from additional two planes to generate the 3D-MTM. Furthermore, the Histogram of Oriented Gradient (HOG) feature vector is extracted from the proposed 3D-MTM as the representation of a gesture sequence. The experiment results show that the proposed method achieves better results on two publicly available datasets namely MSR Action3D dataset and ChaLearn gesture dataset.
Prevalence and Cognitive Bases of Subjective Memory Complaints in Older Adults: Evidence from a Community Sample

Objectives. To estimate the prevalence of subjective memory complaints (SMCs) in a sample of community-dwelling, older adults and to examine cognitive bases of these complaints. Participants. 499 community-dwelling adults, 65 and older. Measurements. A telephone survey consisting of cognitive tests and clinical and sociodemographic variables. SMCs were based on subjects' evaluations and subjects' perceptions of others' evaluations. Analysis. Logistic regression was used to model the risk for SMCs as a function of the cognitive, clinical, and sociodemographic variables. We tested for interactions of the cognitive variables with age, education, and gender. Results. 27.1% reported memory complaints. Among the younger age, better objective memory performance predicted lower risk for SMCs, while among the older age, better memory had no effect on risk. Among the better-educated people, better global cognitive functioning predicted lower risk for SMCs, while among the less-educated people, better global cognitive functioning had no effect on SMC risk. When predicting others' perceptions, better objective memory was associated with lower risk for SMCs. Conclusion. Objective memory performance and global cognitive functioning are associated with lower risk for SMCs, but these relationships are the strongest for the younger age and those with more education, respectively. Age and education may affect the ability to accurately appraise cognitive functioning.
Indian sign language to forecast text using leap motion sensor and RF classifier

These A compact and accurate device recently magnets attraction: The Leap Motion Sensor. It's a novel 3D acquisition device which has depth cameras to obtain various depth description of hand gesture, which can be used for accurate gesture recognition. This sensor device specially targeted for hand gesture recognition and provides only specific number of relevant points. Our proposed system involve recognition of Indian Sign Language (ISL) using Leap Motion Sensor. The device extracts significant characters/ attributes from the dataset such that high-accuracy angle between fingers cab be retrieved, and this can be used for robust prediction. Then, System maps all the frames recognized by sensor to attributes. Feature classifier is used to identify which gesture is being performed. Here, Random Forest (RF) classifier model is used as feature classification. Our method trains a RF to recognize hand gestures for given set of data presented in training dataset. A block-list classifier is used to remove all non-gestures frames, after which accurate gesture frames are recognized by RF to form a meaningful word. This meaningful word is then displayed on LCD. Our proposed method outweighs other state-of-art methods for gesture recognition.
Compositional Symbolic Execution with Memoized Replay

Symbolic execution is a powerful, systematic analysis that has received much visibility in the last decade. Scalability however remains a major challenge for symbolic execution. Compositional analysis is a well-known general purpose methodology for increasing scalability. This paper introduces a new approach for compositional symbolic execution. Our key insight is that we can summarize each analyzed method as a memoization tree that captures the crucial elements of symbolic execution, and leverage these memoization trees to efficiently replay the symbolic execution of the corresponding methods with respect to their calling contexts. Memoization trees offer a natural way to compose in the presence of heap operations, which cannot be dealt with by previous work that uses logical formulas as summaries for compositional symbolic execution. Our approach also enables efficient target oriented symbolic execution for error detection or program coverage. Initial experimental evaluation based on a prototype implementation in Symbolic Path Finder shows that our approach can be up to an order of magnitude faster than traditional non-compositional symbolic execution.
Design of Successively Re nable Scalar

The problem of successively reenable scalar quantizer design is considered. The weighted average of the expected distortion at each level of reenement is used as a quantizer gure of merit. Quantizers designed using this criterion can nd application in many practical situations. Algorithms are presented for the design of both xed and variable rate quantizers and for quantizers subject to a complexity (uniformity) constraint and for quantizers subject to no such constraint. Performance of quantizers designed using these algorithms is presented and appropriate comparisons are rendered.
The time-domain equalization research of underground high-speed cable transmission based on OFDM and its realization in DSP

The high-rate communication service is increasingly in line with public demand whether in the field of wireless communication or wired communication. The Orthogonal Frequency Division Multiplexing (OFDM) has gradually received wide attention in recent years due to its advantages of high bandwidth efficiency as well as capability of anti-interference and anti-multipath; besides, its modem technology can also improve the logging cable transmission rate. This article is based on technologies of channel estimation and time domain equalization in OFDM systems of underground cable transmission, and conducts simulation of channel estimation and time domain equalization algorithms on MATLAB software to test its practicability. The two algorithms are transplanted to the hardware DSP algorithm as a way to realize the time domain equalization of collected data. Simulation results show that: the channel estimation and time domain equalization methods can recover the distorted signal to original signal with high precision.
The Pathological Buying Screener: Development and Psychometric Properties of a New Screening Instrument for the Assessment of Pathological Buying Symptoms

The study was designed to develop a new screening instrument for pathological buying (PB), and to examine its psychometric properties in a large-scale sample. By using a facet theoretical approach and based on literature as well as on clinical experience, a 20-item Pathological Buying Screener (PBS) was developed and administered to a representative German sample (n = 2,539). Valid data were available from 2,403 participants who were subjects for three subsequent empirical studies. The first study explored the factor structure using exploratory factor analyses in a subsample of 498 participants. Based on factor loadings, a 13-item version with the two factors loss of control / consequences and excessive buying behavior was revealed. This two-factor model was confirmed in study 2 by confirmatory factor analysis performed on another subsample (n = 1,905). Study 3 investigated age and gender effects and convergent validity of the PBS using the Compulsive Buying Scale (CBS) in the full sample (N = 2,403). The total PBS score was adequately correlated with the CBS score. Hierarchical regression analyses with the CBS score as the dependent variable and the two PBS factors as the predictors indicated an own incremental validity of the two factors in participants ≤ 65 years. The reliability of the total score as well as of the two subscales was good to excellent. Overall, the PBS represents a useful measure for PB. Future studies are needed to replicate the two-factor structure in clinical samples and to define a valid cutoff for PB.
On-line change mechanisms: the software architectural level

Our interest in the field of software architecture is focused on the application in technical systems, such as control systems. Our current research in this field is centered around a real-life case study, a control system for unmanned vehicles transporting containers on the "Maasvlakte" , an area in the ports of Rotterdam.Important issues in this control system are scalability, evolvability, and on-line change capacities.In this paper, we discuss two mechanisms for on-line change in the distributed control system for the Maasvlakte system, which we have implemented in Java. The software architecture we use is a configuration of distributed processes, communicating according to the subscription model. We will focus on the software architectural aspects of the mechanisms for on-line change. One of these mechanisms is associated with the decoupling of processes as a result of the subscription-based communication model. The other mechanism is based on the late-binding properties of Java.
The D 10 R 4 term in type IIB string theory

The modular invariant coeﬃcient of the D 2 k R 4 term in the eﬀective action of type IIB superstring theory is expected to satisfy Poisson equation on the fundamental domain of SL (2 , Z ). Under certain assumptions, we obtain the equation satisﬁed by D 10 R 4 using the tree level and one loop results for four graviton scattering in type II string theory. This leads to the conclusion that the perturbative contributions to D 10 R 4 vanish above three loops, and also predicts the coeﬃcients at two and three loops.
Robust scheduling in team-robotics

In most cooperating teams of robots each robot has about the same set of sensors. Distributed sensor fusion is a technique that enables a team to take advantage of this redundancy to get a more complete view of the world with a better quality of the provided information. This paper sketches a fusion algorithm for laser-scanner data and derives the requirements that the execution of this algorithm has on the underlying system infrastructure, especially CPU-scheduling. It shows that a scheduling algorithm is needed that fulfills timing guarantees without using worst case execution times (WCET). The time-aware fault-tolerant (TAFT) scheduler provides this feature: each execution entity is divided into a MainPart, with possibly unknown timing behavior, and in an ExceptionPart, with known execution time. The integrated scheduling of both parts is done by a combination of two earliest deadline scheduling strategies. One focuses on enhancing the CPU utilization and the other on guaranteeing the timely execution. The paper discusses the proposed scheduling strategy, briefly describes its implementation in a real-time OS and presents results that show the achieved real-time behavior with an increased acceptance rate, a higher throughput, and a graceful degradation in transient overload situations compared to standard schedulers.
A priori and a posteriori error estimations for the dual mixed finite element method of the Navier‐Stokes problem

This article is concerned with a dual mixed formulation of the Navier‐Stokes system in a polygonal domain of the plane with Dirichlet boundary conditions and its numerical approximation. The gradient tensor, a quantity of practical interest, is introduced as a new unknown. The problem is then approximated by a mixed finite element method. Quasi‐optimal a priori error estimates are obtained. These a priori error estimates, an abstract nonlinear theory (similar to (Verfürth, RAIRO Model Math Anal Numer 32 (1998), 817–842)) and a posteriori estimates for the Stokes system from (Farhloul et al., Numer Funct Anal Optim 27 (2006), 831–846) lead to an a posteriori error estimate for the Navier‐Stokes system. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009
Soil‐based habitat partitioning in understorey palms in lower montane tropical forests

Aim Dispersal assembly and niche assembly are two competing theories proposed to explain the maintenance of species diversity in tropical forests. Dispersal theory emphasizes the role of chance colonization events and distance‐limited seed dispersal in explaining species abundance and distribution, whereas niche theory emphasizes differences among species in requirements for potentially limiting resources. Species distribution patterns in tropical forests often correlate with geology and topography, but tests of the relative importance of dispersal and niche partitioning have been hampered by an inadequate characterization of resource availability. The aim of this study was to explore how soil chemical and physical properties, climate, and geographic distance affect understorey palm communities in lower montane forests.
Spot volatility estimation using delta sequences

We introduce a unifying class of nonparametric spot volatility estimators based on delta sequences and conceived to include many of the existing estimators in the field as special cases. The full limit theory is first derived when unevenly sampled observations under infill asymptotics and fixed time horizon are considered, and the state variable is assumed to follow a Brownian semimartingale. We then extend our class of estimators to include Poisson jumps or financial microstructure noise in the observed price process. This work makes different approaches (kernels, wavelets, Fourier) comparable. For example, we explicitly illustrate some drawbacks of the Fourier estimator. Specific delta sequences are applied to data from the S&P 500 stock index futures market.
Immune system for virus detection and elimination

In this thesis we consider the aspects of designing a computer immune system for virus detection and elimination using components and techniques found in the biological immune system. Already published proposals for constructing computer immune systems are described and analysed. Based on these analyses and a general introduction to modelling the biological immune system in a computer we design a computer immune system for virus detection. In the modelling of the biological immune system we consider the use of three different kinds of loose matching: Hamming Distance, R-Contiguous Symbols, and Hidden Markov Models (HMMs). A complete and in depth introduction to the theory of HMMs will be given and the algorithms used in connexion with HMMs will be explained. A framework for representing the HMMs together with the algorithms are implemented in Java as part of the CIS package which is thought of as being a preliminary version of a computer immune system. Experiments with virus infected programs and HMMs are presented. HMMs are trained on static code from non-infected programs and on traces of systems calls generated by executions of non-infected programs. The programs are infected with a virus and the HMMs ability to detect the infections are tested. It is concluded that HMMs successfully can detect virus infections in programs from static code and from traces of system calls generated by executions of programs.
Emotion detection using keywords spotting and semantic network IEEE ICOCI 2006

Emotion can be expressed in ways that can be seen such as facial expression and gestures. Emotion can also be heard by detecting prosody features and other vocal characteristics. However in this research, we are interested to detect emotions from textual information. Our main objective is to predict the emotions from textual material such as e-mails that is related to relationship. We work on emotion detection by using keywords spotting method and semantic network method. We examined both the methods and achieved a better result with the semantic network model.
The half-life of RAG-1 protein in precursor B cells is increased in the absence of RAG-2 expression

Site-specific recombination of immunoglobulin and T cell receptor gene segments in B and T lymphocytes is dependent on the expression of two recombinant activation genes, Rag-1 and Rag-2. Here, we show that RAG-1 protein turnover in pre-B cells depends on the expression of RAG-2. The apparent half-life of RAG-1 protein is increased when RAG-2 is not expressed in differentiating pre-B cells.
Mining and tracking in evolving software

Every large program contains a small fraction of functionality that resists clean encapsulation. Code for, e.g., debugging or locking is hard to keep hidden using objectoriented mechanisms alone. This problem gave rise to aspect-oriented programming: such cross-cutting functionality is factored out into so-called aspects and these are woven back into mainline code during compilation. However, for existing software systems to benefit from AOP, the cross-cutting concerns must be identified first (aspect mining) before the system can be re-factored into an aspect-oriented design. This thesis on mining and tracking cross-cutting concerns makes three contributions: firstly, it presents aspect mining as both a theoretical idea and a practical and scalable application. By analysing where developers add code to a program, our history-based aspect mining (HAM) identifies and ranks cross-cutting concerns. Its effectiveness and high precision was evaluated using industrial-sized open-source projects such as Eclipse. Secondly, the thesis takes the work on software evolution one step further. Knowledge about a concern’s implementation can become invalid as the system evolves. We address this problem by defining structural and textual patterns among the elements identified as relevant to a concern’s implementation. The inferred patterns are documented as rules that describe a concern in a formal (intensional) rather than a merely textual (extensional) manner. These rules can then be used to track an evolving concern’s implementation in conjunction with the development history. Finally, we implemented this technique for Java in an Eclipse plug-in called ISIS4J and evaluated it using a number of concerns. For that we again used the development history of an open-source project. The evaluation shows not only the effectiveness of our approach, but also to what extent our approach supports the tracking of a concern’s implementation despite, e.g., program code extensions or refactorings.
ATP and Energy Charge as Criteria of Growth and Metabolic Activity of Mollicutes: Application to Spiroplasma citri

Summary: Intracellular ATP concentrations and energy charge were monitored during the growth of Spiroplasma citri and related to the number of colony-forming units, to the pH of the medium and to incorporation of radioactive precursors. Of three different methods used for extracting nucleotides - trichloroacetic acid, perchloric acid and boiling Tris/H2SO4 buffer - the trichloroacetic acid treatment was the most effective. During the active growth phase the ATP concentration increased exponentially, in the same way as other growth parameters. However, as soon as the metabolic activity slowed down, there was a rapid drop of ATP concentration and of total adenylate content, which was followed much later by a parallel decrease in the number of colony-forming units. During active growth, energy charge remained at around 0·9 and decreased only slowly during the stationary phase. Incorporation of labelled thymidine or phenylalanine followed a different pattern during the late phase of the culture and gave less information concerning the viability of the organisms.
Contrastive Analysis of P2SP Network and P2P Network

The performance of P2SP (peer-to-servers& peer) network and Peer to Peer (P2P) network is studied and compared in this paper. Two important key parameters are used to judge the performance: the time of file downloading and the speed of chunk propagation. The difference of the first parameter between P2SP and P2P has been studied first. P2SP has higher performance than P2P in two different assumptions has also been proved. A systematical model is built to study the second parameter. The result also shows that P2SP system has better performance than pure p2p system.