Miracle-dz/UniFAR-FTUs huggingface dataset:
The Molecular Architecture of Cell Adhesion: Dynamic Remodeling Revealed by Videonanoscopy

The plasma membrane delimits the cell, which is the basic unit of living organisms, and is also a privileged site for cell communication with the environment. Cell adhesion can occur through cell-cell and cell-matrix contacts. Adhesion proteins such as integrins and cadherins also constitute receptors for inside-out and outside-in signaling within proteolipidic platforms. Adhesion molecule targeting and stabilization relies on specific features such as preferential segregation by the sub-membrane cytoskeleton meshwork and within membrane proteolipidic microdomains. This review presents an overview of the recent insights brought by the latest developments in microscopy, to unravel the molecular remodeling occurring at cell contacts. The dynamic aspect of cell adhesion was recently highlighted by super-resolution videomicroscopy, also named videonanoscopy. By circumventing the diffraction limit of light, nanoscopy has allowed the monitoring of molecular localization and behavior at the single-molecule level, on fixed and living cells. Accessing molecular-resolution details such as quantitatively monitoring components entering and leaving cell contacts by lateral diffusion and reversible association has revealed an unexpected plasticity. Adhesion structures can be highly specialized, such as focal adhesion in motile cells, as well as immune and neuronal synapses. Spatiotemporal reorganization of adhesion molecules, receptors, and adaptors directly relates to structure/function modulation. Assembly of these supramolecular complexes is continuously balanced by dynamic events, remodeling adhesions on various timescales, notably by molecular conformation switches, lateral diffusion within the membrane and endo/exocytosis. Pathological alterations in cell adhesion are involved in cancer evolution, through cancer stem cell interaction with stromal niches, growth, extravasation, and metastasis.
Evaluation of an Electrochemical Point‐of‐Care Meter for Measuring Glucose Concentration in Blood from Periparturient Dairy Cattle

Background The Precision Xtra® meter is a promising low cost electrochemical point‐of‐care unit for measuring blood glucose concentration ([gluc]) in cattle blood. The meter uses an algorithm that assumes the intra‐erythrocyte [gluc] equals the plasma [gluc] on a molal basis, and that the hematocrit is similar in humans and cattle. Objectives The primary objective was to determine the accuracy of the meter for measuring plasma [gluc] in dairy cattle. Secondary objectives were to characterize the influence of hematocrit and sample temperature on the measured value for [gluc]. Animals A total of 106 periparturient Holstein‐Friesian cattle. Methods Blood and plasma samples (1,109) were obtained and Deming regression and Bland–Altman plots were used to determine the accuracy of the meter against the reference method (plasma hexokinase assay). Multivariable regression and linear regression were used to determine the effect of hematocrit and sample temperature on the plasma [gluc] measured by the meter. Results Intra‐erythrocyte [gluc] was 18% of plasma [gluc] on a molar basis. Sample temperature had a significant linear effect on plasma [gluc] as measured by the meter for 3/5 plasma samples when measured [gluc] > 160 mg/dL. Conclusions and clinical importance The meter utilizes an algorithm that is optimized for human blood and is inaccurate when applied to bovine blood. Until a cattle‐specific algorithm is developed, we recommend using plasma as the analyte instead of blood and calculating plasma [gluc] using the equation: [gluc] = 0.66 × [gluc]p‐meter + 15, where [gluc]p‐meter is the value reported by the meter. If blood is measured, then we recommend using the equation: [gluc] = 0.90 × [gluc]b‐meter + 15.
A discriminant probabilistic model for TSGs

Standard stochastic grammars use generative probabilistic models, focusssing on rewriting probabilities conditioned by the symbol to be rewritten. Such grammars therefore tend to give penalty to longer derivations of the same input, which could be a drawback when they are used for analysis (e.g. parsing, language modelling for speech recognition). In this contribution, we propose a novel non-generative probabilistic model of TSGs, where probabilities are conditioned by the leaves (i.e. the input symbols) rather than by the root of the parse tree. Several experiments with this new model are presented.
MENTAL MODELS IN HUMAN-COMPUTER INTERACTION

: The paper discusses a subset of existing theoretical and experimental results on mental models and their application to problems in human-computer interaction. Mental models research is considered as representing a step towards a more fine-grained study of user models than standard HCI studies of human competence and performance. The logical next step in this direction, it is argued, is to focus on the development of a "procedural semantics" of mental models dealing with the construction and use of mental models in the context of computerized work.
Towards an open question answering architecture

Billions of facts pertaining to a multitude of domains are now available on the Web as RDF data. However, accessing this data is still a difficult endeavour for non-expert users. In order to meliorate the access to this data, approaches imposing minimal hurdles to their users are required. Although many question answering systems over Linked Data have being proposed, retrieving the desired data is still significantly challenging. In addition, developing and evaluating question answering systems remains a very complex task. To overcome these obstacles, we present a modular and extensible open-source question answering framework. We demonstrate how the framework can be used by integrating two state-of-the-art question answering systems. As a result our evaluation shows that overall better results can be achieved by the use of combination rather than individual stand-alone versions.
Energy-aware multi-hop transmission for sensor networks based on adaptive modulation

Wireless Sensor networks (WSN) have become a focus of research in the last few years. WSN is composed of small battery-powered devices that has sensors and wireless communication capabilities. Energy management is one of the key issues in WSNs because it directly impacts the network life-time. In order to overcome this restriction, several energy-efficient approaches for different layers have been investigated. In this paper, energy optimization on physical layer is analyzed. The node's power consumption is optimized through scaling the modulation scheme used in node communications. Results show that an optimal modulation scheme can lead to the minimum power consumption over the whole wireless sensor network.
Investor's satisfaction in portfolio selection problem

Empirical studies show that individual investors do not always behave rationally and do not use standard investment portfolio selection tasks. In this paper we focus on investor choices and the basic elements affecting them. The paper presents optimization model based on a measure of investor satisfaction. The model is created on the basis of surveys conducted among Polish individual investors. The fuzzy sets are used to model preference and expectation of investors and the uncertain future return rate of portfolio are fuzzy variable.
A Hybrid Model for Experts Finding in Community Question Answering

As a means to share knowledge, the community question answering (CQA) service provides users a chance to obtain or provide help by raising or answering questions. After a question is posted, the system must find an appropriate individual to answer this question. Several approaches have recently been proposed to find experts in CQA. In this paper, a new method to find experts in CQA is proposed by considering user post contents, answer votes, ratio of best answers, and user relation. The votes are used in post relation analysis to calculate user authority. The user's knowledge score can be calculated through topic analysis. Considering that a question usually includes many trivial words, an accurate distribution is nearly impossible to obtain with LDA. To solve this problem, vocabulary is extended by including the link information shown in a question, the top 10 relevant words from Wikipedia are provided for each tag. Tag-LDA models the user topic distribution and predicts the topic distribution of new questions. An experiment is conducted on Stack Overflow dataset, which is the world's largest computer programming CQA site. Experimental results showed approximately 2.97% to 7.79% performance improvement in nDCG@N metrics.
Design a secure composite key-management scheme in Ad-Hoc Networks using Localization

Summary A mobile Ad-Hoc network is a collection of wireless mobile nodes, dynamically forming a temporary network without the use of any existing network infrastructure or centralized Administration. Providing security support for mobile Ad-Hoc networks is hard to achieve due to the vulnerability of the links, the limited physical protection of the nodes, and also this fact that wireless networks are susceptible to attacks ranging from passive eavesdropping to active interfering and also mobile users demand “anywhere, anytime” services. In this paper, we present a new Composite Key Management scheme in Ad-Hoc networks. our approach works to decrease complexity of PKI in traditional public-key certificated-based systems and securely improves key-revocation and key-renewal approaches in ID-based systems. in this approach third trusted party (TTP), in which gives offline secret shared-key to each user, securely generates users private key( like PKG in ID-based systems) and also can play the role of directory service in Certificated-Authority like traditional certificated-based public key systems. More precisely if one user wants to obtain certificated public-key of another user, he can ask from TTP and get his desirable public-key.
Dissecting the Syndrome of Schizophrenia: Progress toward Clinically Useful Biomarkers

The search for clinically useful biomarkers has been one of the holy grails of schizophrenia research. This paper will outline the evolving notion of biomarkers and then outline outcomes from a variety of biomarkers discovery strategies. In particular, the impact of high-throughput screening technologies on biomarker discovery will be highlighted and how new or improved technologies may allow the discovery of either diagnostic biomarkers for schizophrenia or biomarkers that will be useful in determining appropriate treatments for people with the disorder. History tells those involved in biomarker research that the discovery and validation of useful biomarkers is a long process and current progress must always be viewed in that light. However, the approval of the first biomarker screen with some value in predicting responsiveness to antipsychotic drugs suggests that biomarkers can be identified and that these biomarkers that will be useful in diagnosing and treating people with schizophrenia.
Impact of IPR System on Patent Based Innovation in China: Empirical Studies over Chinese Patent Reform in 2000

Although there are three time amendments of Patent Law in China since 1985, empirical studies on impact over such changes have not been fully conducted. This study analyzes the differences of patenting movement before and after the patent reforms in China, and investigates the impact of Chinese patent reform in 2000 on local innovation activities with research window covering 30 provinces during 1993-2007. Major finding include that the patent reform in China not only stimulates directly local patent output, but also improves indirectly the innovation by strengthening the positive impact of innovation input on patent output and reducing the negative impact of foreign direct investment on patent output. The regions of more R&D intensive and technology accumulative advantage benefit more from the improvement of patent protection, which further implies that patent reform can raise R&D efficiency over those innovation intensive regions in China. On the other hand, less innovation intensive regions may need more focused policy assistant to encourage local innovation performance.
Collaborative Target Tracking Based on Energy Consideration in WSNs

A target tracking algorithm with energy consideration in wireless sensor networks is studied. In order to balance the local energy consumption of a dynamic clustering owing to excessive use of an individual node, a assess strategy based on the energy consumption model is applied to describe the relation of the residual energy of some node and the distance between two sensors. According to tracking accuracy, a dynamic cluster is formed as tasking sensors to track target. Simulation results show that, the algorithm can achieve the required tracking accuracy, and solve the problem of node redundancy so as to balance the consumption of energy in local wireless sensor networks.
Social Skills Instruction for Urban Learners with Emotional and Behavioral Disorders: A Culturally Responsive and Computer-Based Intervention

This study examined the effects of culturally relevant/responsive, computer-based social skills instruction on the social skill acquisition and generalization of 6 urban African American sixth graders with emotional and behavioral disorders (EBD). A multiple-probe across participants design was used to evaluate the effects of the social skills intervention on following adult directions. Results revealed increases in students following adult directions in the treatment phases; however, generalization results were modest for four students. These results support the use of a social skill package consisting of computer-based instruction and culturally responsive materials for urban adolescents with EBD. The specific components of this intervention are discussed along with implications for future research and study limitations.
Canonical Realizations of Linear Time-Varying Systems

In this article, general scalar linear time-varying systems are addressed. In particular, canonical realizations with integrators, multipliers and adders are presented. Essentially, it is shown that the well-known configurations for constant systems can be generalized to the time-varying context by replacing the conventional eigenvalues by the earlier introduced dynamic eigenvalues. However, it is also shown that at least one configuration is not suitable for such a generalization.
Children with Learning Disabilities: Theories, Diagnosis, Teaching Strategies

Children with Learning Disabilities: Theories, Diagnosis, Teaching Strategies (2nd ed.). Janet Lerner. * Boston: Houghton Mifflin, 1976, 442pp. Price: $1 1.50. Lerner’s 1976 second edition is an updated, slightly modified, and expanded (the original was 312 pages) version of her successful 1971 textbook. Lemer identifies her intended audience as “present and prospective teachers, educational clinicians and therapists, administrators, psychologists, language pathologists, counselors, and other professionals preparing to work with the learning disabled child. The book is also intended for regular classroom teachers who wish to better understand learning disabled children in their classrooms, and it can serve parents by providing necessary background information” (p. ix).
Robust 3D Multi-Modal Registration of MRI Volumes Using the Sum of Conditional Variance

Multi-modal registration is a fundamental step for many medical imaging procedures. In this paper, the sum of conditional variance (SCV) similarity measure is proposed for 3D multi-modal medical image registration. The SCV similarity measure is based on minimizing the sum of conditional variances that are calculated using the joint histogram of the two images to be registered. Standard Gauss-Newton optimization is used to automatically minimize this measure which allows fast computational time and high accuracy. Experimental results show that our proposed approach is robust, computationally efficient and also more accurate when compared with the standard mutual information (MI) based approach and also the recently proposed sum-of-squared-difference on entropy images (eSSD) approach.
A dynamic load balancer for a parallel branch and bound algorithm

This paper presents a load-balancing scheme for a parallel branch and bound (PBB) algorithm utilizing a dynamic load balancer (DLB). The PBB algorithm is used to solve a resource scheduling problem on the Hypercube. The DLB is included in the PBB algorithm and is distributed to each node to balance the workload during run time. The DLB is evaluated by implementing two PBB algorithms, with DLB and without DLB. Results show that the PBB with DLB is 3.14 times faster than the algorithm without DLB.
The challenges of introducing internal social media – the coordinators’ roles and perceptions

Purpose The purpose of this paper is to explore the challenges associated with introducing internal social media (ISM) into organizations in order to help them reap the benefits of coworker communication on ISM. Design/methodology/approach The paper is based on an exploratory study in ten organizations. The data were collected in semi-structured interviews with ISM coordinators in Spring 2014. Findings According to the ISM coordinators, four challenges were associated with introducing ISM: coworkers could perceive communication on ISM as not work related; coworkers might not understand the informal nature of communication on ISM, and self-censorship might stop them communicating on ISM; ISM was not considered a “natural” part of the daily routines in the organizations; and top managers mainly supported ISM in words, not in action. Research limitations/implications The study is based on the perceptions of ISM coordinators. Further research is called for to explore both coworker perceptions and actual communication on ISM. Practical implications Practitioners introducing ISM should be aware of these four challenges, and should help coworkers to make sense of communication on ISM as work-related communication among coworkers. ISM coordinators’ perceptions of their own role in relation to coworker communication on ISM make a difference. Originality/value The study provides insights into the key challenges associated with introducing ISM, as well as the role of ISM coordinators as community facilitators and sense-givers.
A Study on Peculiarities, which Increase Social Identification among the Foreign Students

During study abroad, they are confronted with new culture and environment. In effect, social identity is important for students to adapt the culture of Korea. The issue of social identity has been investigated several viewpoints. For enhancing social identity, we investigate what kind of peculiarity could enhance social identity. This research focuses on the peculiarities which are foreign language ability, person-culture fit, social behavior and investigate their effects on social identity. Furthermore, such peculiarities would make the students to adapt successfully to the new environment and lead to positive performance for students who study abroad over time. From the regression analysis, all the peculiarities had positive effects on the social identity. It shows that if improve such peculiarities, the social identity will be better and stronger. Moreover, students adapt the culture of Korea successfully and they are satisfied with their life in studying abroad. Keyword:social identity, foreign language, student, culture.
Group testing for image compression

This paper presents the group testing for wavelets algorithm (GTM), which is a novel embedded wavelet-based image compression technique based on the concept of group testing. We explain how group testing is a generalization of the zerotree coding technique for wavelet-transformed images. We also show that Golomb coding is equivalent to Hwang's (Du and Hwang, 1993) group testing algorithm. GTW is similar to SPIHT (Said and Pearlman, 1996) but replaces SPIHT's sorting pass with a new group testing based method. Although no arithmetic coding is implemented, GTW performs competitively with SPIHT's arithmetic coding variant in terms of rate-distortion performance.
Efficient Nonlinear Filtering Methods for Detection of Dim Targets by Passive Systems

In this paper, we outline an efficient system for detection of dim small targets that consists of three main parts: clutter rejection, track-before-detect (TBD), and detection subsystems. Detection and tracking of dim targets requires accumulation of sensor signal in time in order to resolve the target. There exist a number of powerful methods for detecting small low observable targets with stationary dynamics in image sequences provided by infrared (IR) and other imaging sensors. However, these methods need to be extended to handle maneuvering targets. We use a multiple switching model along with an optimal nonlinear filtering method to build an efficient TBD algorithm. We demonstrate that banks of interacting (nonlinear) Bayesian Matched filters (BIBMF) can be utilized for this purpose. The target’s dynamics is modeled by jump-linear systems. We present a computationally efficient (real time) TBD algorithm. The performance of the developed algorithm is compared to a Dynamic Programming (Viterbi) scheme and a bank of 3D Matched Filters (3DMF). The analysis shows that BIBMF outperforms the 3DMF algorithm and the sequential modification of Viterbi scheme. In addition, we develop a multi-target adaptive sequential detection algorithm that utilizes the estimates of targets’ positions obtained at the output of the TBD/BIBMF block. The performance of the algorithms is evaluated using real IR backgrounds obtained from SPAWAR Systems Center, San Diego (staring shipboard IR sensors). The results of this experimentation show that both developed algorithms, the TBD algorithm and the adaptive CFAR detection algorithm, perform very well for quite low effective signal-to-noise ratios.
Kinematic path-planning for formations of mobile robots with a nonholonomic constraint

A method of planning paths for formations of mobile robots with nonholonomic constraints is presented. The kinematics equations presented in this paper allow a general geometrical formation of mobile robots to be maintained while the group as a whole travels an arbitrary path. It is possible to represent a formation of mobile robots by a single entity with the same type of nonholonomic constraint as the individual members. Thus, any path-planner or control method may be used with the formation as would be applied to an individual robot. Equations are developed for changing the geometrical formation and hardware results are presented from the Stanford MARS Testbed.
Statins Reduce Mortality After Non-severe but Not After Severe Pneumonia: A Systematic Review and Meta-Analysis.

PURPOSE The objective of this study was to perform a systematic review and meta-analysis of the effects of statins on mortality for patients with non-severe pneumonia or severe pneumonia. METHODS PubMed, EMBASE, Cochrane Database of Systematic Reviews, Cochrane central register of controlled trials and Clinicaltrials.gov were searched for the association between statins and non-severe/severe pneumonia. Eligible articles were analyzed in Stata 12.0. RESULTS The database search yielded a total of 566 potential publications, 24 studies involving 312,309 patients met the eligibility criteria. Pooled unadjusted data showed that statin use was associated with lower mortality after non-severe pneumonia (odds ratio [OR] 0.70, 95% confidence interval [CI], 0.66-0.73), but not severe pneumonia (OR 1.05; 95% CI, 0.86-1.28). However, this protective effect of statins was weakened using adjusted estimates (OR 0.78, 95% CI, 0.75-0.82). Besides, protective effect of statins was attenuated by confounders in a subgroup analysis, especially when accounting for pneumonia severity indicators (OR 0.88; 95% CI, 0.80-0.96). CONCLUSIONS Statin use was associated with reduced mortality after non-severe pneumonia but not severe pneumonia and this protective effect was weakened in subgroups.