Miracle-dz/UniFAR-FTUs huggingface dataset:
VARIABLE PAY: A CASE STUDY IN WAREHOUSE LOGISTICS

The use of variable pay schemes has been identified as a means of rewarding employees in order to increase their motivation and productivity. However, experiences from post-transition economies show prevalent use of variable pay model in the sales sector. The reason behind that is insufficient interest by top management into other sectors, such as supply chain management. In addition, supply chain management and different types of distribution channels have not yet been recognized as the sources of competitive advantage. Furthermore, when compared to the sales sector, performance is hard to measure within the supply chains suggesting the need for more complex performance indicators. The main aim of this paper is to present the introduction of variable pay schemes in warehouse logistics leading to productivity improvement. In that context, a case study method is used to compare warehouse employees’ fixed and variable pay and their impact on employees’ performance. The results reveal significant differences in warehouse employees’ performance outputs after introducing variable pay schemes. The research is limited by the levels of technology used in the warehouse operations. Consequently, the lack of a precise classification of warehouse employees’ activities can be noted indicating the need to include subjective indicators in the analysis. Finally, performance management in post-transition economies is still rather delicate field with top management still being sceptical about the use of performance pay schemes. In that sense, the efforts should be made to develop efficient solutions to improve employee motivation and performance.
The Development of a Simplified Process Model for Cbsd

This study introduces the MyCL process model, a simplified Component-Based Software Development (CBSD) process model that is clear and easy to be understood and hence, applied. It is motivated by the fact that even though many CBSD process models have been proposed, a clear and step-by-step guidance is still lacking. They vary from one another and some are even complicated and difficult to be applied. The MyCL process model is therefore derived by retaining the strengths and overcoming the impracticality causes of these existing CBSD process models. Evaluation of the model, which was carried out by interviewing the experts in this field has shown that this model has a good potential to be applied by software developers, especially those who are new to CBSD.
Scalable Corpus Annotation by Graph Construction and Label Propagation

The efficient annotation of documents in vast corpora calls for scalable methods of text classification. Representing the documents in the form of graph vertices, rather than in the form of vectors in a bag of words space, allows for the necessary information to be pre-computed and stored. It also fundamentally changes the problem definition, from a content-based to a relation-based classification problem. Efficiently creating a graph where nearby documents are likely to have the same annotation is the central task of this paper. We compare the effectiveness of various approaches to graph construction by building graphs of 800,000 vertices based on the Reuters corpus, showing that relation-based classification is competitive with Support Vector Machines, which can be considered as state of the art. We further show that the combination of our relation-based approach and Support Vector Machines leads to an improvement over the methods individually.
Efficient Latency Guarantees for Mixed-Criticality Networks-on-Chip

Abstract-Networks-on-Chip (NoCs) for future mixedcriticality systems must handle a growing variety of traffic requirements, ranging from safety-critical real-time traffic to bursty latency-sensitive best-effort traffic. Additionally, safety standards (e.g. ISO 26262) require sufficient independence among different criticality levels or a full system certification according to the highest applicable safety level. Hence, a NoC must provide performance isolation for safety-critical traffic, while sustaining low latency for best-effort traffic. This paper presents a run-time configurable NoC design enabling latency guarantees for safety-critical traffic with reduced adverse impact on the performance of best-effort traffic. In contrast to existing approaches, we prioritize best-effort over safety-critical traffic and only switch priorities when required. Doing this, we exploit the latency slack of safety-critical applications, while providing sufficient independence among different criticality levels w.r. t. timing properties. We present a formal analysis and an experimental evaluation, showing that the approach provides performance isolation for safety-critical applications, while reducing the adverse effects through strict prioritization on best-effort applications
cDNA Cloning, Tissue Distribution, and Identification of the Catalytic Triad of Monoglyceride Lipase

Monoglyceride lipase catalyzes the last step in the hydrolysis of stored triglycerides in the adipocyte and presumably also complements the action of lipoprotein lipase in degrading triglycerides from chylomicrons and very low density lipoproteins. Monoglyceride lipase was cloned from a mouse adipocyte cDNA library. The predicted amino acid sequence consisted of 302 amino acids, corresponding to a molecular weight of 33,218. The sequence showed no extensive homology to other known mammalian proteins, but a number of microbial proteins, including two bacterial lysophospholipases and a family of haloperoxidases, were found to be distantly related to this enzyme. By means of multiple sequence alignment and secondary structure prediction, the structural elements in monoglyceride lipase, as well as the putative catalytic triad, were identified. The residues of the proposed triad, Ser-122, in a GXSXG motif, Asp-239, and His-269, were confirmed by site-directed mutagenesis experiments. Northern blot analysis revealed that monoglyceride lipase is ubiquitously expressed among tissues, with a transcript size of about 4 kilobases.
A general theory for positioning and orienting 2D polygonal or curved parts using intelligent motion surfaces

We present a new approach to compute quasi-static and dynamic equilibrium positions and orientations (if any) of 2D polygonal or curved parts placed on general shaped 2D force field configurations. On the theoretical side, the novelty of our approach is that it puts into practice a fundamental result of piecewise-linear topology-the simplicial approximation theorem-and suggests an implementation using tools and techniques borrowed from modern computational geometry.
Energy Efficient Online Routing Algorithm for QoS-Sensitive Sensor Networks

In this letter, we propose a new energy efficient online routing algorithm for QoS-sensitive sensor networks. An important design principle underlying our algorithm is online decision making based on real time network estimation. This on-line approach gives adaptability and flexibility to solve a wide range of control tasks for efficient network performance. In addition, our distributed control paradigm is practical for real sensor network management. Simulation results indicate the superior performance of our algorithm between energy efficiency and QoS provisioning.
A novel autoantibody to a 155-kd protein is associated with dermatomyositis.

OBJECTIVE In polymyositis and dermatomyositis (DM), identified autoantibodies occur in <50% of adult patients and in a smaller proportion of children. This study was undertaken as part of a larger effort to define novel autoantibodies that assist in the clinical evaluation of myositis. METHODS Sera from children and adults satisfying criteria for idiopathic inflammatory myopathies and from patients with other connective tissue diseases (CTDs), patients with noninflammatory myopathies, and healthy individuals were tested for autoantibodies by immunoprecipitation (IP). A previously unrecognized autoantibody that immunoprecipitated a 155-kd protein along with a weaker 140-kd protein was seen. When the presence of this anti-p155 autoantibody in test sera was suggested based on IP results, it was confirmed by immunoblotting of immunoprecipitates. RESULTS Sera from 51 of 244 myositis patients (21%), including 30 with juvenile DM (29%), 5 with juvenile CTD-associated myositis (33%), 8 with adult DM (21%), 6 with cancer-associated DM (75%), and 2 with adult CTD-associated myositis (15%), were found to have anti-p155 autoantibody. One of 49 patients with lupus, and none of 89 others without myositis, had anti-p155. Caucasian patients with anti-p155 had a unique HLA risk factor, DQA1*0301 (odds ratio 5.4, corrected P = 0.004). In adults with anti-p155, of several clinical features assessed only the frequency of V-sign rash was increased, but patients with this antibody were clinically distinct from those with autoantibodies to aminoacyl-transfer RNA synthetases. CONCLUSION A newly recognized autoantibody, anti-p155, is associated with DM and cancer-associated DM, and is one of the most common autoantibodies in this condition, occurring as frequently in children as in adults. The clinical features and immunogenetics associated with anti-p155 differ from those associated with antisynthetases.
ECC based Fault Tolerant and Secured E-Payment Protocol *

A digital system is very vulnerable to the faultsmay be natural or injected. Fault tolerance is a very important feature of a highly critical or secured system. Efficient detection of errors & verification of the correctness of computations may be a sufficient countermeasure for many security applications to provide a system which can resist fault based attacks. In this paper we consider hashed elliptic curve based payment protocol. Different error detection schemes & fault tolerant schemes have been considered in this paper. Point validation (PV) in elliptic curve cryptography is considered as a scheme against fault-analysis attack. Though, PV alone is not sufficient against all attacks, we consider recomputation along with PV. These structures provide a high probability of detecting errors due to faults. Additionally, we show that using N-modular redundancy, the fault –tolerability of the system can be increased.
intériorisés et l'anxiété chez les enfants d'âge préscolaire

The father-child activation relationship is a new theorization of a child’s attachment to the father, which emphasizes the «exploration» pole. This relation begins during the second year of life and especially develops through physical play. The activation relationship primarily focuses on the child’s openness to the world, and enables the father to respond specifically to the child’s need to be stimulated and to overcome personal limits, in turn satisfying the child’s need for emotional security. The main goal of this thesis is to study the links between the activation to the father and the socioaffective development of the child at preschool age, more specifically in terms of internalising disorders (IDs) and anxiety. This thesis is made up of two empirical articles. The first one used a convenience sample of 51 fatherchild dyads. Analyses demonstrated the existence of the anticipated link between underactivation and IDs: underactivated children had significantly more IDs than activated children. Furthermore, the association between activation scores and IDs was significant after controlling for variables such as the child’s gender and temperament, as well as parental behaviour. The more positively activated children were in their relationship with their father, the fewer internalising disorders they displayed. The exploration of links between the activation relationship and ID subscales revealed a unique connection to anxiety. The second article was based on a sample of 49 families from a clinical population (i.e. child psychiatry department). This study is the first to explore the relationship between activation to the father, attachment to the mother and child anxiety at preschool age. Analyses
Adverse Biological Effect of TiO2 and Hydroxyapatite Nanoparticles Used in Bone Repair and Replacement

The adverse biological effect of nanoparticles is an unavoidable scientific problem because of their small size and high surface activity. In this review, we focus on nano-hydroxyapatite and TiO2 nanoparticles (NPs) to clarify the potential systemic toxicological effect and cytotoxic response of wear nanoparticles because they are attractive materials for bone implants and are widely investigated to promote the repair and reconstruction of bone. The wear nanoparticles would be prone to binding with proteins to form protein-particle complexes, to interacting with visible components in the blood including erythrocytes, leukocytes, and platelets, and to being phagocytosed by macrophages or fibroblasts to deposit in the local tissue, leading to the formation of fibrous local pseudocapsules. These particles would also be translocated to and disseminated into the main organs such as the lung, liver and spleen via blood circulation. The inflammatory response, oxidative stress, and signaling pathway are elaborated to analyze the potential toxicological mechanism. Inhibition of the oxidative stress response and signaling transduction may be a new therapeutic strategy for wear debris–mediated osteolysis. Developing biomimetic materials with better biocompatibility is our goal for orthopedic implants.
Curvature-based face surface recognition using spherical correlation. Principal directions for curved object recognition

Surface curvatures such as Gaussian, mean and principal curvatures are intrinsic surface properties and have played important roles in curved surface analysis. In this paper, we present a correlation-based face recognition approach based on the analysis of maximum and minimum principal curvatures and their directions. We treat face recognition problem as a 3D shape recognition problem of free-form curved surfaces. Our approach is based on a 3D vector sets correlation method which does not require either face feature extraction or surface segmentation. Each face in both input images and the model database, is represented as an Extended Gaussian Image (EGI), constructed by mapping principal curvatures and their directions at each surface points, onto two unit spheres, each of which represents ridge and valley lines respectively. Individual face is then recognized by evaluating the similarities among others by using Fisher's spherical correlation on EGI's effaces. The method is tested for its simplicity and robustness and successively implemented for each of face range images from NRCC (National Research Council Canada) 3D image data files. Results show that shape information from surface curvatures provides vital cues in distinguishing and identifying such fine surface structure as human faces.
Flexible ureteroscopy and laser lithotripsy for stones >2 cm: a systematic review and meta-analysis.

BACKGROUND AND PURPOSE Urinary stones >2 cm are traditionally managed with percutaneous nephrolithotomy (PCNL). Recently, flexible ureteroscopy and laser lithotripsy) (FURSL) has been used to manage them with comparable results. In a comparative study of renal stones between 2 and 3 cm, FURSL was reported to need less second-stage procedures and be just as effective as PCNL. Our purpose was to review the literature for renal stones >2 cm managed by ureteroscopy and holmium lasertripsy. MATERIALS AND METHODS A systematic review and quantitative meta-analysis was performed using studies identified by a literature search from 1990s (the first reported large renal stones treated ureteroscopically) to August 2011. All English language articles reporting on a minimum of 10 patients treated with FURSL for renal stones >2 cm were included. Two reviewers independently extracted the data from each study. The data of studies with comparable results were included into a meta-analysis. RESULTS In nine studies, 445 patients (460 renal units) were reportedly treated with FURSL. The mean operative time was 82.5 minutes (28-215 min). The mean stone-free rate was 93.7% (77%-96.7%), with an average of 1.6 procedures per patient. The mean stone size was 2.5 cm. An overall complication rate was 10.1%. Major complications developed in 21 (5.3%) patients and minor complications developed in 19 (4.8%) patients. A subgroup analysis shows that FURSL has a 95.7% stone-free rate with stones 2-3 cm and 84.6% in those >3 cm (P=0.01), with a minor complication rate of 14.3% and 15.4%, respectively, and a major complication rate of 0% and 11.5%, respectively. CONCLUSION In experienced hands, FURSL can successfully treat patients with stones >2 cm with a high stone-free rate and a low complication rate. Although the studies are from high-volume experienced centers and may not be sufficient to alter everyday routine practice, this review has shown that the efficacy of FURSL allows an alternative to PCNL.
Adapting an Educational Game for Spanish Orthography to make it Adaptive and Accessible

This paper explains SAMO, an educational game for Spanish orthography. The game is an evolution of MITO, which was evaluated with real students. Using information obtained from this evaluation, which highlighted some shortcomings from the pedagogical and access point of view, a new game has been developed, using a new architecture, with a new teaching methodology and accessibility features.
Layer, Column and Cell-Type Specific Genetic Manipulation in Mouse Barrel Cortex

Sensory information is processed in distributed neuronal networks connected by intricate synaptic circuits. Studies of the rodent brain can provide insight into synaptic mechanisms of sensory perception and associative learning. In particular, the mouse whisker sensorimotor system has recently begun to be investigated through combinations of imaging and electrophysiology, providing data correlating neural activity with behaviour. In order to go beyond such correlative studies and to pinpoint the contributions of individual genes to brain function, it is critical to make highly controlled and specific manipulations. Here, we review recent progress towards genetic manipulation of targeted genes in specific neuronal cell types located in a selected cortical layer of a well-defined cortical column of mouse barrel cortex. The unprecedented precision of such genetic manipulation within highly specific neural circuits may contribute significantly to progress in understanding the molecular and synaptic determinants of simple forms of sensory perception and associative learning.
Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.
Resolved COG viscoelasticity control of a humanoid

This paper proposes the concept of the center of gravity (COG) viscoelasticity to associate joint viscoelasticity with the COG-zero moment point (ZMP) model of humanoid dynamics. Although COG viscoelasticity is based on the well-known kinematic relationship between joint stiffness and end-effector stiffness, it provides practical advantages for humanoid motion control. Once the feedback gain in the COG-ZMP model is designed using the control theory, COG viscoelasticity can be applied to directly transform it to joint viscoelasticity. The author names this method as resolved COG viscoelasticity control (RCVC). In particular, this paper proposes RCVC in which the null-space of the COG Jacobian is employed. The validity of the RCVC is verified by simulating whole-body dynamics.
Vehicle dynamic analysis using neuronal network algorithms

Theoretical developments of certain engineering areas, the emergence of new investigation tools, which are better and more precise and their implementation on-board the everyday vehicles, all these represent main influence factors that impact the theoretical and experimental study of vehicle’s dynamic behavior. Once the implementation of these new technologies onto the vehicle’s construction had been achieved, it had led to more and more complex systems. Some of the most important, such as the electronic control of engine, transmission, suspension, steering, braking and traction had a positive impact onto the vehicle’s dynamic behavior. The existence of CPU on-board vehicles allows data acquisition and storage and it leads to a more accurate and better experimental and theoretical study of vehicle dynamics. It uses the information offered directly by the already on-board built-in elements of electronic control systems. The technical literature that studies vehicle dynamics is entirely focused onto parametric analysis. This kind of approach adopts two simplifying assumptions. Functional parameters obey certain distribution laws, which are known in classical statistics theory. The second assumption states that the mathematical models are previously known and have coefficients that are not time-dependent. Both the mentioned assumptions are not confirmed in real situations: the functional parameters do not follow any known statistical repartition laws and the mathematical laws aren’t previously known and contain families of parameters and are mostly time-dependent. The purpose of the paper is to present a more accurate analysis methodology that can be applied when studying vehicle’s dynamic behavior.A method that provides the setting of non-parametrical mathematical models for vehicle’s dynamic behavior is relying on neuronal networks. This method contains coefficients that are time-dependent. Neuronal networks are mostly used in various types’ system controls, thus being a non-linear process identification algorithm. The common use of neuronal networks for non-linear processes is justified by the fact that both have the ability to organize by themselves. That is why the neuronal networks best define intelligent systems, thus the word ‘neuronal’ is sending one’s mind to the biological neuron cell. The paper presents how to better interpret data fed from the on-board computer and a new way of processing that data to better model the real life dynamic behavior of the vehicle.