Miracle-dz/UniFAR-FTUs huggingface dataset:
Kidney Mass and Relative Medullary Thickness of Rodents in Relation to Habitat, Body Size, and Phylogeny

We tested the hypotheses that relative medullary thickness (RMT) and kidney mass are positively related to habitat aridity in rodents, after controlling for correlations with body mass. Body mass, mass‐corrected kidney mass, mass‐corrected RMT, mass‐corrected maximum urine concentration, and habitat (scored on a semiquantitative scale of 1–4 to indicate increasing aridity) all showed statistically significant phylogenetic signal. Body mass varied significantly among habitats, with the main difference being that aquatic species are larger than those from other habitats. Mass‐corrected RMT and urine concentration showed a significant positive correlation (N = 38; conventional r = 0.649, phylogenetically independent contrasts [IC] r = 0.685), thus validating RMT as a comparative index of urine concentrating ability. RMT scaled with body mass to an exponent significantly less than 0 (N = 141 species; conventional allometric slope = −0.145 [95% confidence interval (CI) = −0.172, −0.117], IC allometric slope = −0.132 [95% CI = −0.180, −0.083]). Kidney mass scaled to an exponent significantly less than unity (N = 104 species; conventional slope = 0.809 [95% CI = 0.751, 0.868], IC slope = 0.773 [95% CI = 0.676, 0.871]). Both conventional and phylogenetic analysis indicated that RMT varied among habitats, with rodents from arid areas having the largest values of RMT. A phylogenetic analysis indicated that mass‐corrected kidney mass was positively related to habitat aridity.
Architecture of Multicast Network Based on Quantum Secret Sharing and Measurement

1 Senior lecturer, Information Technology Department, AL-Zahra College for women, Oman 2 Professor of Computer Sciences , Faculty of Computer and Information Sciences, Mansoura University, Egypt 3 Professor of Computer Sciences, Faculty of Computer and Information Sciences , Cairo University, Egypt 4 Professor of Engineering Mechanics, Faculty of Engineering, Cairo University, Egypt ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Multicast Classical transmission means
Protecting the privacy of user's QoS preferences for multimedia applications

Privacy violation is a serious and pressing problem for Internet users that requires immediate solution. This problem is very serious for applications that require the user's identity and QoS preferences like IP-telephony and videoconference applications. In this paper, we will identify the risks of privacy invasion during the setup of interactive multimedia applications, and introduce three schemes to solve the problem of protecting the user's privacy, with varying degree of complexities. The first approach is based on the use of a trusted third party; this has been a common approach for the Public Switched Telephony Network (PSTN). The second approach is based on the trust relationship between the communicating parties, and the third approach is based on primitives from the field of secure distributed computation
Hydrogen-rich water attenuates experimental periodontitis in a rat model.

AIM Reactive oxygen species (ROS) contribute to the development of periodontitis. As molecular hydrogen can act as a scavenger of ROS, we examined the effects of treatment with hydrogen-rich water on a rat model of periodontitis. MATERIAL & METHODS A ligature was placed around the maxillary molars for 4 weeks to induce periodontitis, and the animals were given drinking water with or without hydrogen-rich water. RESULTS The rats with periodontitis which were treated with pure water showed a time-dependent increase in serum ROS level. Compared with the rats without periodontitis, the periodontitis-induced rats which were given pure water also showed polymorphonuclear leucocyte infiltration and alveolar bone loss at 4 weeks. Hydrogen-rich water intake inhibited an increase in serum ROS level and lowered expression of 8-hydroxydeoxyguanosine and nitrotyrosine in the periodontal tissue at 4 weeks. Such conditions prevented polymorphonuclear leucocyte infiltration and osteoclast differentiation following periodontitis progression. Furthermore, inflammatory signalling pathways, such as mitogen-activated protein kinases, were less activated in periodontal lesions from hydrogen-rich water-treated rats as compared with pure water-treated rats. CONCLUSION Consuming hydrogen-rich water might be beneficial in suppressing periodontitis progression by decreasing gingival oxidative stress.
Person-organization fit and organizational citizenship behavior: Time perspective1

Abstract Viewing organizational citizenship behavior (OCB) engagement from the time cost perspective, this study not only investigates the direct effect of person—organization (P—O) fit on OCB but also examines the moderating effect of time evaluation on the effective magnitude of P—O fit on OCB. Specifically, I hypothesized that the positive relationship between P—O fit and OCB will be strengthened (weakened) if employees have a higher future (present) orientation time perspective. A sample of 262 bank financial specialists with supervisor-rated dependent variables is used to examine the hypothesized relationships. Research findings suggest that P—O fit can predict OCB engagement. I also found that time evaluation plays a moderating role in the relationship between P—O fit and OCB such that P—O fit will have a weaker predictive power if the employees have a higher present-orientation time perspective. The research results provide further understanding of why employees engage in OCB.
Implicit Human-computer Interaction: Two Complementary Approaches

One of the main goals in Human Computer Interaction (HCI) is improving the interface between users and computers: Interfacing should be intuitive, effortless and easy to learn. We approach the goal from two opposite but complementary directions: On the one hand, computer-user interaction can be enhanced if the computer can assess users differences in an automated manner. Therefore we collected physiological and psychological data from people exposed to emotional stimuli and created a database for the community to use for further research in the context of automated learning to detect the differences in the inner states of users. We employed the data both to not only predict the emotional state of users but also their personality traits. On the other hand, users need information dispatched by a computer to be easily, intuitively accessible. To minimize the cognitive effort of assimilating information we use a tactile device in form of a belt and test how it can be best used to replace or augment the information received from other senses (e.g., visual and auditory) in a navigation task. We investigate how both approaches can be combined to improve specific applications.
Compiling several classes of communication patterns on a multithreaded architecture

Communication optimizations play a crucial role in performance of parallel applications which are compiled and executed on distributed memory machines. Multithreaded architectures can support multiple threads of execution on each processor, with low-cost thread initiation, low-overhead communication, and efficient data transfer and synchronization between threads on different processors. These mechanisms can be used for achieving an effective overlap between communication and computation, and therefore, good performance on communication intensive parallel applications. We focus on generating correct and efficient multithreaded code for array based programs that involve different classes of communication patterns. We consider producer-consumer, scalar reductions, and near-neighbor communication patterns. We describe multithreaded programming methodologies suitable for handling loops with each of these patterns. We further show how a compiler can generate threaded code for loops with such patterns. We present experimental results from two benchmark programs, CG, and Tomcatv. Our results show that: 1) the compiler generated multithreaded code achieves high performance, not previously seen from distributed memory compilers, and 2) the performance of compiler generated code is comparable to the performance of hand-written multithreaded codes.
Accurate and efficient modeling of the detector response in small animal multi-head PET systems

In fully three-dimensional PET imaging, iterative image reconstruction techniques usually outperform analytical algorithms in terms of image quality provided that an appropriate system model is used. In this study we concentrate on the calculation of an accurate system model for the YAP-(S)PET II small animal scanner, with the aim to obtain fully resolution- and contrast-recovered images at low levels of image roughness. For this purpose we calculate the system model by decomposing it into a product of five matrices: (1) a detector response component obtained via Monte Carlo simulations, (2) a geometric component which describes the scanner geometry and which is calculated via a multi-ray method, (3) a detector normalization component derived from the acquisition of a planar source, (4) a photon attenuation component calculated from x-ray computed tomography data, and finally, (5) a positron range component is formally included. This system model factorization allows the optimization of each component in terms of computation time, storage requirements and accuracy. The main contribution of this work is a new, efficient way to calculate the detector response component for rotating, planar detectors, that consists of a GEANT4 based simulation of a subset of lines of flight (LOFs) for a single detector head whereas the missing LOFs are obtained by using intrinsic detector symmetries. Additionally, we introduce and analyze a probability threshold for matrix elements of the detector component to optimize the trade-off between the matrix size in terms of non-zero elements and the resulting quality of the reconstructed images. In order to evaluate our proposed system model we reconstructed various images of objects, acquired according to the NEMA NU 4-2008 standard, and we compared them to the images reconstructed with two other system models: a model that does not include any detector response component and a model that approximates analytically the depth of interaction as detector response component. The comparisons confirm previous research results, showing that the usage of an accurate system model with a realistic detector response leads to reconstructed images with better resolution and contrast recovery at low levels of image roughness.
Information-Based Selection of Abstraction Levels

We model the learning of classifications as a combination of abstraction and class assignment. We discuss the problem of selecting the most suitable of multiple abstractions for this purpose. Weaker abstractions perform better on training sets, but typically do not generalize very well. Stronger abstractions often generalize better, but may fail to include important properties. We introduce the relative information gain as a criterion to determine an optimal balance between precision and generality of abstractions. Experimental results with abstractions used for the classification of terms indicate the success of this approach.
The Limits of Health and Nutrition Education: Evidence from Three Randomized-Controlled Trials in Rural China

This article studies whether or not health education programs targeting childhood anemia are sufficient for changing health behavior and nutrition in rural China. We conducted three different randomized-controlled trials of single and multiple face-to-face education sessions with parents and distributed written health education materials—and compare our results with a simple vitamin distribution program. Across all three studies, we find little evidence of changes in blood hemoglobin concentration or anemia status. In contrast, in our two studies that also examined a multivitamin supplementation intervention, we find meaningful reductions in anemia. (JEL codes: I12, I15, O15)
An Asymmetric Proxy Backbone Architecture for Sensor Nodes

In many environments where communications infrastructure already exists, e.g. factories and hospitals, sensor networks applications are becoming increasingly interesting. We present our ongoing work aimed at developing a network architecture using such existing infrastructure as proxy support for sensor networks. The proposed topology is asymmetric in its communication, i.e. the proxy can reach its sensor nodes in one hop but there is no guarantee that the sensor nodes reach the proxy directly. Thus we propose to divide the topology hierarchically. Too handle sensor nodes with different demands and to save energy at the sensor nodes we propose to schedule the sensor nodes with time-division multiplexed access (TDMA). We outline a proposed network architecture and point out important research issues that must be addressed. One of the main purpose of this paper is to solicit feedback on our proposed network architecture.
Diagonal total variation regularization criterion for fast convergence

The total variation (TV) regularization method is very attractive for various image processing applications. In order to apply the TV approach to motion pictures, it is required to reduce the computational time of the iterative signal processing of the TV regularization. In this paper, we propose the diagonal TV criterion instead of conventional isotropic or anisotropic TV criteria. The experimental results show that we can obtain almost half of the iteration number both in the steepest descent algorithm and Chambolle's algorithm by utilizing the diagonal TV compared with the conventional TV criteria.
LASIGE: using Conditional Random Fields and ChEBI ontology

For participating in the SemEval 2013 challenge of recognition and classification of drug names, we adapted our chemical entity recognition approach consisting in Conditional Random Fields for recognizing chemical terms and lexical similarity for entity resolution to the ChEBI ontology. We obtained promising results, with a best F-measure of 0.81 for the partial matching task when using post-processing. Using only Conditional Random Fields the results are slightly lower, achieving still a good result in terms of Fmeasure. Using the ChEBI ontology allowed a significant improvement in precision (best precision of 0.93 in partial matching task), which indicates that taking advantage of an ontology can be extremely useful for enhancing chemical entity recognition.
Ensemble learning approach in improved K Nearest Neighbor algorithm for Text categorization

Due to the tremendous growth of digital content in World Wide Web (WWW), Text categorization has become an important tool to manage and organize text related data. This paper proposes an Ensemble Learning approach in Improved K Nearest Neighbor algorithm for Text Categorization (EINNTC), which consists of single pass clustering, Ensemble learning and KNN algorithm. The EINNTC method provides solution to traditional KNN classifier issues, by reducing the huge text similarity computation complexity, avoids an impact of noisy training sample, and expediting the process of finding K nearest neighbors. The experiments were carried out with standard benchmark Reuters dataset, and their empirical results shows that the proposed method outperforms the SVM and KNN classifiers.
Finding Experts in Unstructured Communities through Relationships and Topics

The problem of expert finding has been explored for many structured question and answer-based social networks. Less explored is the problem of finding trusted individuals in an unstructured social setting. We explore the issue of finding experts in Reddit’s /r/programming, /r/CFB and /r/cars Subreddit – each of which is either unstructured or semi-structured – using a machine learning approach based on prior research in classifying user roles. To target the problem, we assumed that "experts" is a role similar to "answer-person" in previous research in that they have a common pattern of communication quantitatively recognizable through analysis of social network features. Using a combination of inferred topic distributions and social network structure, we trained a supervised classifer to find the topical-network "fingerprint" of experts. Among features examined for a given user include neighbor topical similarity, topical entropy, and depth 2-egocentric network properties. We compare our results with previously considered techniques for evaluating expertise: namely, ExpertiseRank (Social Network Page Rank), HITS and a simple z-score metric introduced by Zhang, Ackerman and Adamic (2007). Using our role-based algorithm, average f1 and recall scores during validation demonstrate comparable or better performance than prior social network analysis-based algorithms. We conclude by describing future metrics that can be explored in the problem of expert classifying in pure discussion communities.
Distributed under Creative Commons Cc-by 4.0 a Candidate Multimodal Functional Genetic Network for Thermal Adaptation

Vertebrate ectotherms such as reptiles provide ideal organisms for the study of adaptation to environmental thermal change. Comparative genomic and exomic studies can recover markers that diverge between warm and cold adapted lineages, but the genes that are functionally related to thermal adaptation may be difficult to identify. We here used a bioinformatics genome-mining approach to predict and identify functions for suitable candidate markers for thermal adaptation in the chicken. We first established a framework of candidate functions for such markers, and then compiled the literature on genes known to adapt to the thermal environment in different lineages of vertebrates. We then identified them in the genomes of human, chicken, and the lizard Anolis carolinensis, and established a functional genetic interaction network in the chicken. Surprisingly, markers initially identified from diverse lineages of vertebrates such as human and fish were all in close functional relationship with each other and more associated than expected by chance. This indicates that the general genetic functional network for thermoregulation and/or thermal adaptation to the environment might be regulated via similar evolu-tionarily conserved pathways in different vertebrate lineages. We were able to identify seven functions that were statistically overrepresented in this network, corresponding to four of our originally predicted functions plus three unpredicted functions. We describe this network as multimodal: central regulator genes with the function of relaying thermal signal (1), affect genes with different cellular functions, namely (2) lipoprotein metabolism, (3) membrane channels, (4) stress response, (5) response to oxidative stress, (6) muscle contraction and relaxation, and (7) vasodilation, vasoconstriction and regulation of blood pressure. This network constitutes a novel resource for the study of thermal adaptation in the closely related nonavian reptiles and other vertebrate ectotherms.
Behavioural Trajectories of Adaptive Mobile Robot for Animal Behaviour Studies

Modelling animal behaviour using adaptive mobile robots is a well stabilised methodology that permits to test, in an extremely controlled setting, hypnotises, constrains and assumptions about how organisms orient themselves. We apply this methodology to simulate experiments with rats in open field box. Animal psychologists have used open field box settings in order to empirically show the formal structure of cognitive maps used by rats in navigation tasks. In these experiments, rats that have been shown the location of hidden food in a rectangular box are able to navigate towards and dig at that location (or at the rotational equivalent location) in a second identical box. These results lead researchers to state that (a) rats use a cognitive map of the environmental shape, and (b) the cognitive maps can be described in terms of Euclidean geometry. We studied an adaptive mobile robot in a similar experimental setting. Our robot had no capability of constructing internal maps. The robot, despite its sensory-motor limitations, learnt the same behavioural indexes as rats in the open field box experiments. The results show that the open field box experiments are not sufficient to conclude that the rats construct cognitive maps. Other task solutions based on no explicit knowledge of the environment are theoretically possible. The results show that the geometrical properties of the environment can be assimilated in the sensory-motor schema of the robot behaviour without any explicit representation.
Selective Thoracic Fusion for Adolescent Idiopathic Scoliosis with C Modifier Lumbar Curves: 2- to 16-Year Radiographic and Clinical Results

Study Design. Retrospective clinical and radiographic review with functional outcome assessment. Objectives. To evaluate outcome of selective thoracic fusion for adolescent idiopathic scoliosis in the presence of widely deviated compensatory lumbar curves. Summary of Background Data. Previous reports on the results of selective thoracic scoliosis fusion have not specifically focused on deformities with widely deviated lumbar curves. Whether these challenging deformities are best treated with selective thoracic fusion or fusion of both curves remains unclear. Methods. Forty-four consecutive patients with adolescent idiopathic scoliosis with main thoracic, compensatory minor lumbar “C” modifier curves underwent selective thoracic fusion at a single institution (1987–2000). Radiographs were analyzed before surgery, at 1 week, 2 years, and latest follow-up (2–16 years; mean 5.0 years). Results. A mean 36% thoracic correction was closely matched by a 34% lumbar correction at latest follow-up. A majority of spontaneous lumbar correction occurred at its cephalad segments (P = 0.001). Spontaneous correction of lumbar apical translation occurred in a majority of patients (prognostic factors identified). Global coronal imbalance (2–5 cm) was common before surgery and was a significant risk factor (P = 0.04) for global imbalance at latest follow-up. Postoperative bracing was not utilized, and there were no reoperations. Patients with coronal imbalance (2–5 cm) at latest follow-up had slightly inferior SRS-24 results. Conclusions. Satisfactory results are achieved with selective thoracic fusion of properly selected C modifier lumbar curves. Correction of the lumbar curve results principally from a decrease in the tilt of its upper vertebrae, but not necessarily improved apical translation. Mild coronal imbalance was well tolerated and has not necessitated distal extension of the fusion.