Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study into the similarity in generator and discriminator in GAN architecture

One popular generative model that has high-quality results is the Generative Adversarial Networks(GAN). This type of architecture consists of two separate networks that play against each other. The generator creates an output from the input noise that is given to it. The discriminator has the task of determining if the input to it is real or fake. This takes place constantly eventually leads to the generator modeling the target distribution. This paper includes a study into the actual weights learned by the network and a study into the similarity of the discriminator and generator networks. The paper also tries to leverage the similarity between these networks and shows that indeed both the networks may have a similar structure with experimental evidence with a novel shared architecture.
A Noncoherent Multiuser Large-Scale SIMO System Relying on M-Ary DPSK and BICM-ID

A new constellation is designed for the multiuser noncoherent large-scale single-input multiple-output uplink system based on M-ary differential phase-shift keying, which is combined with a bit interleaved coded modulation-iterative decoding scheme for attaining improved performance. We conceive a new approach for constructing EXIT charts parameterized by the number of antennas used for optimizing the design. Finally, the system performance is analyzed and compared to previous work. This evaluation shows an overall improvement of two orders of magnitude demonstrating a dramatic reduction in the required number of antennas.
Inhibition of autophagy inhibits the conversion of cardiac fibroblasts to cardiac myofibroblasts

The incidence of heart failure with concomitant cardiac fibrosis is very high in developed countries. Fibroblast activation in heart is causal to cardiac fibrosis as they convert to hypersynthetic cardiac myofibroblasts. There is no known treatment for cardiac fibrosis. Myofibroblasts contribute to the inappropriate remodeling of the myocardial interstitium, which leads to reduced cardiac function and ultimately heart failure. Elevated levels of autophagy have been linked to stress-induced ventricular remodeling and other cardiac diseases. Previously, we had shown that TGF-β1 treatment of human atrial fibroblasts both induced autophagy and enhanced the fibrogenic response supporting a linkage between the myofibroblast phenotype and autophagy. We now demonstrate that with in vitro culture of primary rat cardiac fibroblasts, inhibition of autophagy represses fibroblast to myofibroblast phenoconversion. Culturing unpassaged cardiac fibroblasts for 72 hours on plastic tissue culture plates is associated with elevated α-smooth muscle actin (α-SMA) expression. This activation parallels increased microtubule-associated protein 1A/1B-light chain 3 (LC-3β II) protein expression. Inhibition of autophagy with bafilomycin-A1 (Baf-A1) and chloroquine (CQ) in cardiac fibroblasts significantly reduces α-SMA and extracellular domain A fibronectin (ED-A FN) protein vs untreated controls. Myofibroblast cell migration and contractility were significantly reduced following inhibition of autophagy. These data support the possibility of a causal link between cardiac fibroblast-to-myofibroblast phenoconversion and autophagy.
Combining SVM classifiers for handwritten digit recognition

We investigate the advantages and weaknesses of various decision fusion schemes using statistical and rule-based reasoning. The cooperation schemes are applied on two SVM (Support Vector Machine) classifiers performing classification tasks on two feature families referenced as structural and statistical features. The obtained results show that it is difficult to exceed the recognition rate of a single classifier applied straightforwardly on both feature families as one set. The rule based cooperation schemes enable an easy and efficient implementation of various rejection criteria. On the other hand, the statistical cooperation schemes provide higher recognition rates and offer possibility for fine-tuning of the recognition versus the reliability tradeoff.
Earing Prediction in Drawing and Ironing Processes Using an Advanced Yield Criterion

This work aims to contribute to the understanding of the role/influence of advanced yield criteria on the earing profile prediction after drawing and ironing, for a cylindrical cup benchmark proposed at the NUMISHEET 2011 conference [1]. Two typical materials used for can-making were considered and studied: an AA5042 aluminum alloy and an AKDQ steel. The drawing and ironing operations are performed on a special die which allows drawing and ironing in one single punch stroke in order to simplify the real process. The benchmark results report include, for each material: (i) the earing profile after drawing and ironing, presenting the cup height evolution with the angle from the rolling direction, and (ii) the evolution of punch force with punch stroke. This work presents a comparison between experimental and numerical results obtained for the aforesaid benchmark with DD3IMP in-house solver, using two sets of parameters for the Cazacu and Barlat 2001 [2] yield criterion, identified based on uniaxial tensile, equi-biaxial tension and disc compression test results. The first set uses the initial yield stress values while the second one used the flow stress values for an accumulated plastic work of 20 MPa. The results highlight the different impact of the experimental data in the earing prediction for both materials: the results for the second set are slightly improved for the AKDQ steel while for AA5042 the effect is negligible. The improved earing prediction obtained with the second set for the AKDQ steel seems to result from a better description of the stress states that occur in the flange zone.
Triage Scheduling Optimization for Mass Casualty and Disaster Response

This paper discusses casualty and medical group scheduling for disaster response in order to reduce casualities. First, triage levels and their stochastic transition, Markov Chain, are introduced to establish a function from treated time to probability of death. Then, job shop scheduling model and a genetic algorithm are designed. Finally, we performed a simulation experiment, partially using real data of 5.12 Wenchuan earthquakes for reference. The results show that the algorithm reduces number of mortalities stably and efficiently while considering disturbance events.
Development of a biped walking robot compensating for three-axis moment by trunk motion

The authors have been using the ZMP (zero moment point) as a criterion to distinguish the stability of walking for a biped walking robot which has a trunk. The authors introduce a control method of dynamic biped walking for a biped walking robot to compensate for the three-axis (pitch, roll and yaw-axis) moment on an arbitrary planned ZMP by trunk motion. The authors developed a biped walking robot and performed a walking experiment with the robot using the control method. The result was a fast dynamic biped walking at the walking speed of 0.54 s/step with a 0.3 m step on a flat floor. This walking speed is about 50% faster than that with the robot which compensates for only the two-axis (pitch and roll-axis) moment by trunk motion.
Molecular Characterization of Gregarines from Sand Flies (Diptera: Psychodidae) and Description of Psychodiella n. g. (Apicomplexa: Gregarinida)

ABSTRACT. Sand fly and mosquito gregarines have been lumped for a long time in the single genus Ascogregarina and on the basis of their morphological characters and the lack of merogony been placed into the eugregarine family Lecudinidae. Phylogenetic analyses performed in this study clearly demonstrated paraphyly of the current genus Ascogregarina and revealed disparate phylogenetic positions of gregarines parasitizing mosquitoes and gregarines retrieved from sand flies. Therefore, we reclassified the genus Ascogregarina and created a new genus Psychodiella to accommodate gregarines from sand flies. The genus Psychodiella is distinguished from all other related gregarine genera by the characteristic localization of oocysts in accessory glands of female hosts, distinctive nucleotide sequences of the small subunit rDNA, and host specificity to flies belonging to the subfamily Phlebotominae. The genus comprises three described species: the type species for the new genus—Psychodiella chagasi ( Adler and Mayrink 1961 ) n. comb. , Psychodiella mackiei ( Shortt and Swaminath 1927 ) n. comb. , and Psychodiella saraviae ( Ostrovska, Warburg, and Montoya‐Lerma 1990 ) n. comb. Its creation is additionally supported by sequencing data from other gregarine species originating from the sand fly Phlebotomus sergenti. In the evolutionary context, both genera of gregarines from mosquitoes (Ascogregarina) and sand flies (Psychodiella) have a close relationship to neogregarines; the genera represent clades distinct from the other previously sequenced gregarines.
Misspecification in Latent Change Score Models: Consequences for Parameter Estimation, Model Evaluation, and Predicting Change

ABSTRACT Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study investigates the robustness of LCS when invariance over time is incorrectly imposed on key change-related parameters. Monte Carlo simulation methods were used to explore the impact of misspecification on parameter estimation, predicted trajectories of change, and model fit in the dual change score model, the foundational LCS. When constraints were incorrectly applied, several parameters, most notably the slope (i.e., constant change) factor mean and autoproportion coefficient, were severely and consistently biased, as were regression paths to the slope factor when external predictors of change were included. Standard fit indices indicated that the misspecified models fit well, partly because mean level trajectories over time were accurately captured. Loosening constraint improved the accuracy of parameter estimates, but estimates were more unstable, and models frequently failed to converge. Results suggest that potentially common sources of misspecification in LCS can produce distorted impressions of developmental processes, and that identifying and rectifying the situation is a challenge.
Detecting changes in content and posting time distributions in social media

We address a problem of detecting changes in information posted to social media taking both content and posting time distributions into account. To this end, we introduce a generative model consisting of two components, one for a content distribution and the other for a timing distribution, approximating the shape of the parameter change by a series of step functions. We then propose an efficient algorithm to detect change points by maximizing the likelihood of generating the observed sequence data, which has time complexity almost proportional to the length of observed sequence (possible change points). We experimentally evaluate the method on synthetic data streams and demonstrate the importance of considering both distributions to improve the accuracy. We, further, apply our method to real scoring stream data extracted from a Japanese word-of-mouth communication site for cosmetics and show that it can detect change points and the detected parameter change patterns are interpretable through an in-depth investigation of actual reviews.
Mobility analysis and kinematic synthesis of a novel 4-DoF parallel manipulator

SUMMARY This paper proposes a novel parallel manipulator with 1 translational and 3 rotational degrees of freedom, which may be designed as the docking equipment for large-scale component assemblage in the aircraft industry. First, the mobility and kinematic analysis of the novel manipulator is performed using the screw theory and the closed-loop vector method. To evaluate the kinematic performance of the manipulator, its workspace is calculated, and the dimensional homogeneous Jacobian matrix of this manipulator is deduced. Mainly based on a nonlinear programming approach, the kinematic dimensional synthesis is performed to optimise the dimensional parameters of this novel parallel manipulator in a prescribed workspace. The results of this paper may lay a solid foundation for the prototype design and manufacture of the novel parallel manipulator.
ACESO: Analysis of Cervical Cancer: An Evidence-Based Treatments Optimization

Deciding for Cervical Cancer (CxCa) treatment is not a simple task. There are several competing factors that arise from the perspective of survival, treatment, toxicity, quality of patient&#x2019;s life, as well as the geographic location of the patient, which indicates access to specific healthcare resources. All of these factors play a significant role in the ultimate decision to pursue surgery, chemotherapy, and radiation therapy. Our aim is to develop an integrated platform incorporating a big data analytics (BDA) platform, enabling the collection and analysis of heterogeneous data related to the effectiveness of existing interventions and to the discovery of more effective techniques.
On the matching precision of SIFT

Matching precision of scale-invariant feature transform (SIFT) is evaluated and improved in this paper. The aim of the paper is not to invent a new feature detector more invariant than the others. Instead, we focus on SIFT method and evaluate and improve the matching precision, defined as the root mean square error (RMSE) under ground truth geometric trans-form. Matching precision reflects to some extent the average relative localization precision between two images. For scale invariant feature detectors like SIFT, the matching precision decreases with the scale of features due to the sub-sampling in the scale space. We propose to cancel the sub-sampling to improve the matching precision. But in case of scale change, the improvement is marginal due to the coarse scale quanti-zation in the scale space. One more sophisticated method is also proposed to improve the matching precision in case of scale change. These modifications can be easily extended to other scale invariant feature detectors.
Multi-surface sliding control of MIMO autonomous flight systems

In this paper, a multi-surface sliding control (MSSC) is proposed for trajectory tracking of 6 degrees of freedom (6-DOF) inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an iterative MSSC design can be carried out to control flight. Using MSSC on MIMO autonomous flight systems creates confluent control that can account for model mismatches, system uncertainties, system disturbances and excitation in internal dynamics. We prove that the MSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the system. Simulation results are presented to validate the analysis.
Effect of contact and no-contact small-sided games on elite handball players

ABSTRACT This study aimed to investigate the effect of contact (C-SSG) and no-contact (NC-SSG) handball small-sided games (SSGs) on motion patterns and physiological responses of elite handball players. Twelve male handball players performed 10 C-SSG and 10 NC-SSG while being monitored through the heart rate (HR) and rate of perceived exertion (RPE) as physiological responses and time-motion activities profile using video-match analysis. Both game conditions resulted in similar HR responses (P > 0.05), but the NC-SSG led to a higher RPE scores. The time-motion activity analysis featured NC-SSG with a greater amount of walking (855.6 ± 25.1 vs. 690.6 ± 35.2 m) and backward movements (187.5 ± 12.3 vs. 142.5 ± 8.7 m) combined with fast running (232.3 ± 8.5 vs. 159.7 ± 5.7 m) and sprinting (79.5 ± 4.7 vs. 39.7 ± 3.7 m) activities (P < 0.001). Conversely, C-SSG had a higher percentage of jogging and sideway movements associated with greater frequency of jumping (0.87 ± 0.09 vs. 0.31 ± 0.06 nr) and physical contact (1.82 ± 0.55 vs. 0.25 ± 0.03 nr) events (P < 0.001). No between-regimen differences were found for the number of throws (P = 0.745). In addition, the RPE was significantly correlated with fast running relative distances (r = 0.909, P < 0.001) and sprinting relative distances (r = 0.939, P < 0.001). In conclusion, this investigation showed that both C-SSG and NC-SSG in team handball can effectively represent specifically oriented exercises, according to the sport-task and the performance demands.
Signal Transducer and Activator of  Transcription (STAT)5 Activation by BCR/ABL Is Dependent on Intact Src Homology (SH)3 and SH2 Domains of BCR/ABL and Is Required for Leukemogenesis

Signal transducer and activator of transcription (STAT)5 is constitutively activated in BCR/ ABL-expressing cells, but the mechanisms and functional consequences of such activation are unknown. We show here that BCR/ABL induces phosphorylation and activation of STAT5 by a mechanism that requires the BCR/ABL Src homology (SH)2 domain and the proline-rich binding site of the SH3 domain. Upon expression in 32Dcl3 growth factor–dependent myeloid precursor cells, STAT5 activation–deficient BCR/ABL SH3+SH2 domain mutants functioned as tyrosine kinase and activated Ras, but failed to protect from apoptosis induced by withdrawal of interleukin 3 and/or serum and did not induce leukemia in severe combined immunodeficiency mice. In complementation assays, expression of a dominant-active STAT5B mutant (STAT5B-DAM), but not wild-type STAT5B (STAT5B-WT), in 32Dcl3 cells transfected with STAT5 activation–deficient BCR/ABL SH3+SH2 mutants restored protection from apoptosis, stimulated growth factor–independent cell cycle progression, and rescued the leukemogenic potential in mice. Moreover, expression of a dominant-negative STAT5B mutant (STAT5B-DNM) in 32Dcl3 cells transfected with wild-type BCR/ABL inhibited apoptosis resistance, growth factor–independent proliferation, and the leukemogenic potential of these cells. In retrovirally infected mouse bone marrow cells, expression of STAT5B-DNM inhibited BCR/ABL-dependent transformation. Moreover, STAT5B-DAM, but not STAT5B-WT, markedly enhanced the ability of STAT5 activation–defective BCR/ABL SH3+SH2 mutants to induce growth factor–independent colony formation of primary mouse bone marrow progenitor cells. However, STAT5B-DAM did not rescue the growth factor–independent colony formation of kinase-deficient K1172R BCR/ABL or the triple mutant Y177F+R522L+ Y793F BCR/ABL, both of which also fail to activate STAT5. Together, these data demonstrate that STAT5 activation by BCR/ABL is dependent on signaling from more than one domain and document the important role of STAT5-regulated pathways in BCR/ABL leukemogenesis.
Incidence and Functional Outcomes of Scapholunate Diastases Associated Distal Radius Fractures: A 2-year Follow-Up Scapholunate Dissociation

Background: The Scapholunate Interosseous Ligament (SLIL) is the first intrinsic carpal ligament to be injured in wrist trauma, present in up to 64% of the distal radius fractures. However, it remains unclear what patients develop symptoms, making primary treatment of these injuries accompanying distal radius fractures remains questionable. Objective: The aim of this study was to evaluate the functional outcomes of patients with scapholunate diastasis associated with distal radius fractures. Methods: We evaluated 391 patients with a distal radius fracture. Using Computer Tomography (CT) scans the scapholunate interval was measured. We identified 14 patients with an SLD (>3mm) of the injured wrist, which underwent a CT-scan of the contralateral wrist. To evaluate the functional outcomes at a mean follow up of 136±90 weeks, we used the Quick Disabilities of the Arm, Shoulder and Hand (qDASH) Score. Results: There were 8 patients with bilateral SLD and 6 patients with unilateral SLD. Five patients had a qDASH score of 0 and one patient showed a qDASH score of 18.2. The patient with a poor score had bilateral preexisting osteoarthritis of the wrist. No patient had additional surgery of the SLIL. Conclusion: In patients with distal radius fractures, more than half of the 14 patients with an SL gap on CT had widening on the contralateral side. It is therefore worthwhile to image the contralateral wrist before diagnosing a SLD. The patients with unilateral SLD should not be surgically treated at initial presentation because they may have good functional outcomes after a follow up of 2 years.
The influence of fluid and crystallized intelligence on the development of knowledge and skills.

BACKGROUND Cattell's Gf-Gc distinction is quite generally recognized. However, the developmental part of the Gf-Gc theory of intelligence has not gained the same recognition. Results are inconsistent, but recent discussions emphasize the importance of homogeneity of samples with regard to education and language when investigating the developmental Investment theory. AIMS The aim of this study was to investigate the influence of Gf and Gc on the development of knowledge and skills in a sample of children in compulsory school who are homogenous with regard to level of education, age, and cultural background. SAMPLE Totally, 9,002 individuals from the evaluation through follow-up database born in 1972 and who left compulsory school in 1988 were included. These individuals were followed up in Grades 3, 6, and 9. METHODS Structural equation modelling was used, and autoregressive path models were fitted. All modelling was performed using Mplus version 6.1. RESULTS In the first step, a path model with a simplex structure was defined. However, a second model with direct relations of Gf on Gc in Grades 6 and 9 had better model fit, suggesting a continuous influence of Gf on Gc. However, no direct influence of Gf was found for the subject grades. CONCLUSION Due to the continuous influence of Gf on the measures of Gc throughout compulsory school, support for Cattell's (1987) Investment theory was found.
A Markov chain representation of the multiple testing problem

The problem of multiple hypothesis testing can be represented as a Markov process where a new alternative hypothesis is accepted in accordance with its relative evidence to the currently accepted one. This virtual and not formally observed process provides the most probable set of non null hypotheses given the data; it plays the same role as Markov Chain Monte Carlo in approximating a posterior distribution. To apply this representation and obtain the posterior probabilities over all alternative hypotheses, it is enough to have, for each test, barely defined Bayes Factors, e.g. Bayes Factors obtained up to an unknown constant. Such Bayes Factors may either arise from using default and improper priors or from calibrating p-values with respect to their corresponding Bayes Factor lower bound. Both sources of evidence are used to form a Markov transition kernel on the space of hypotheses. The approach leads to easy interpretable results and involves very simple formulas suitable to analyze large datasets as those arising from gene expression data (microarray or RNA-seq experiments).