Miracle-dz/UniFAR-FTUs huggingface dataset:
Multidimensional Penalized Signal Regression

We propose a general approach to regression on digitized multidimensional signals that can pose severe challenges to standard statistical methods. The main contribution of this work is to build a two-dimensional coefficient surface that allows for interaction across the indexing plane of the regressor array. We aim to use the estimated coefficient surface for reliable (scalar) prediction. We assume that the coefficients are smooth along both indices. We present a rather straightforward and rich extension of penalized signal regression using penalized B-spline tensor products, where appropriate difference penalties are placed on the rows and columns of the tensor product coefficients. Our methods are grounded in standard penalized regression, and thus cross-validation, effective dimension, and other diagnostics are accessible. Further, the model is easily transplanted into the generalized linear model framework. An illustrative example motivates our proposed methodology, and performance comparisons are made to other popular methods.
A comparative study of the reported performance of ab initio protein structure prediction algorithms

Protein structure prediction is one of the major challenges in bioinformatics today. Throughout the past five decades, many different algorithmic approaches have been attempted, and although progress has been made the problem remains unsolvable even for many small proteins. While the general objective is to predict the three-dimensional structure from primary sequence, our current knowledge and computational power are simply insufficient to solve a problem of such high complexity. Some prediction algorithms do, however, appear to perform better than others, although it is not always obvious which ones they are and it is perhaps even less obvious why that is. In this review, the reported performance results from 18 different recently published prediction algorithms are compared. Furthermore, the general algorithmic settings most likely responsible for the difference in the reported performance are identified, and the specific settings of each of the 18 prediction algorithms are also compared. The average normalized r.m.s.d. scores reported range from 11.17 to 3.48. With a performance measure including both r.m.s.d. scores and CPU time, the currently best-performing prediction algorithm is identified to be the I-TASSER algorithm. Two of the algorithmic settings—protein representation and fragment assembly—were found to have definite positive influence on the running time and the predicted structures, respectively. There thus appears to be a clear benefit from incorporating this knowledge in the design of new prediction algorithms.
Evaluation of a psychiatric day hospital program for elderly patients with mood disorders

Background: Very little is known about the utility of psychiatric day hospitals for elderly adults with mood disorders. The objectives of this study were to evaluate a long-standing day-hospital program and to explore whether demographic and non-demographic patient characteristics were associated with treatment outcomes. Method: We used t-tests to compare retrospective admission and discharge data for 708 patients over a 16-year period, and multiple regression to examine predictors of improvement. Results: Depressed patients showed statistically and clinically significant improvements on the Geriatric Depression Scale and the Hamilton Depression Rating Scale. The number and severity of depressive symptoms at admission were strongly related to treatment outcomes. After controlling for initial levels of depression, demographic characteristics did not predict improvement, and axis I and II diagnoses modestly and inconsistently predicted improvement. Conclusions: A biopsychosocially-focused day-hospital treatment program was associated with improvements in depression in a large sample of elderly adults with mood disorders. Except for depression severity at admission, patient characteristics had very little impact on treatment outcomes, suggesting that day hospital programs are beneficial for a wide range of depressed elderly adults.
Improving EA-based design space exploration by utilizing symbolic feasibility tests

This paper will propose a novel approach in combining Evolutionary Algorithms with symbolic techniques in order to improve the convergence of the algorithm in the presence of large search spaces containing only few feasible solutions. Such problems can be encountered in many real-world applications. Here, we will use the example of design space exploration of embedded systems to illustrate the benefits of our approach. The main idea is to integrate symbolic techniques into the Evolutionary Algorithm to guide the search towards the feasible region. We will present experimental results showing the advantages of our novel approach.
Implementing a new instructional design framework in an animated pedagogical agent: Does an animated pedagogical agent enhance student motivation and learning gains?

This study investigated whether an animated pedagogical agent (APA) affected student motivation and learning in a simulation on a science topic. The APA focused on students' perceptions of task-relevance and self-efficacy beliefs. For the construction of the APA a motivational design model was newly developed. This model combined expectancy-value theory (Eccles & Wigfield, 2002), self-efficacy theory (Bandura, 1977) and the ARCS Model (Keller, 1987;2010). In an experiment with 68 high school students, an APA condition was compared with a no-APA control condition. Gender was evenly distributed over conditions. For initial motivation, a gender difference was found with girls scoring lower than boys. After completing two-thirds of the training, students in the control condition gave significantly higher appraisals for self-efficacy than students in the APA condition. In addition, girls expressed higher perceptions of task-relevance than boys effect of gender on task and condition. After training, an interaction effect showed that the self-efficacy of girls had increased most in the APA condition while self-efficacy of boys increased most in the control condition. For task-relevance a main effect of condition was found, in favor of the control condition. For knowledge gains there were main effects for condition and gender. The control condition yielded more learning gains than the APA condition, and girls learned more than boys. The discussion explains the outcomes with reference to gender differences in initial motivation, the possibility of gender-sensitive motivational strategies and the gender-specific visual presentation of the APA (i.e., a girl). In addition, the question is raised how to draw students' attention to their perceptions of task-relevance and self-efficacy beliefs during training without disturbing their learning focus.
Theme: an approach for aspect-oriented analysis and design

Aspects are behaviours that are tangled and scattered across a system. In requirements documentation, aspects manifest themselves as descriptions of behaviours that are intertwined, and woven throughout. Some aspects may be obvious, as specifications of typical crosscutting behaviour. Others may be more subtle, making them hard to identify. In either case, it is difficult to analyse requirements to locate all points in the system where aspects should be applied. These issues lead to problems achieving traceability of aspects throughout the development lifecycle. To identify aspects early in the software lifecycle, and establish sufficient traceability, developers need support for aspect identification and analysis in requirements documentation. To address this, we have devised the Theme approach for viewing the relationships between behaviours in a requirements document, identifying and isolating aspects in the requirements, and modelling those aspects using a design language. This paper describes the approach, and illustrates it with a case study and analysis.
Osmoprotection of Escherichia coli by Peptone Is Mediated by the Uptake and Accumulation of Free Proline but Not of Proline-Containing Peptides

ABSTRACT The effect of meat peptone type I (Sigma) on the growth ofEscherichia coli cells under hyperosmotic stress has been investigated. Peptone is a complex mixture of peptides with a small content of free amino acids, which resembles nutrients found in natural environments. Our data showed that peptone enhances the growth ofE. coli cells in high-osmolarity medium to levels higher than those achieved with the main compatible solute in bacteria, glycine betaine. The mechanism of osmoprotection by peptone comprises the uptake and accumulation of the compatible solute, proline. The main role of the peptides contained in peptone is the provision of nutrients rather than the intracellular accumulation of osmolytes. In contrast toListeria monocytogenes (M. R. Amezaga, I. Davidson, D. McLaggan, A. Verheul, T. Abee, and I. R. Booth, Microbiology 141:41–49, 1995), E. coli does not accumulate exogenous peptides for osmoprotection and peptides containing proline do not lead to the accumulation of proline as a compatible solute. In late-logarithmic-phase cultures of E. coli growing at high osmolarity plus peptone, proline becomes the limiting factor for growth, and the intracellular pools of proline are not maintained. This is a consequence of the low concentration of free proline in peptone, the catabolism of proline by E. coli, and the inability ofE. coli to utilize proline-containing peptides as a source of compatible solutes. Our data highlight the role that natural components in food such as peptides play in undermining food preservation regimes, such as high osmolarity, and also that the specific mechanisms of osmoprotection by these compounds differ according to the organism.
Aboveground Herbivory Shapes the Biomass Distribution and Flux of Soil Invertebrates

Background Living soil invertebrates provide a universal currency for quality that integrates physical and chemical variables with biogeography as the invertebrates reflect their habitat and most ecological changes occurring therein. The specific goal was the identification of “reference” states for soil sustainability and ecosystem functioning in grazed vs. ungrazed sites. Methodology/Principal Findings Bacterial cells were counted by fluorescent staining and combined direct microscopy and automatic image analysis; invertebrates (nematodes, mites, insects, oligochaetes) were sampled and their body size measured individually to allow allometric scaling. Numerical allometry analyses food webs by a direct comparison of weight averages of components and thus might characterize the detrital soil food webs of our 135 sites regardless of taxonomy. Sharp differences in the frequency distributions are shown. Overall higher biomasses of invertebrates occur in grasslands, and all larger soil organisms differed remarkably. Conclusions/Significance Strong statistical evidence supports a hypothesis explaining from an allometric perspective how the faunal biomass distribution and the energetic flux are affected by livestock, nutrient availability and land use. Our aim is to propose faunal biomass flux and biomass distribution as quantitative descriptors of soil community composition and function, and to illustrate the application of these allometric indicators to soil systems.
Tyrosine Phosphorylation Generates Multiple Isoforms of the Mitochondrial Capsule Protein, Phospholipid Hydroperoxide Glutathione Peroxidase (PHGPx), During Hamster Sperm Capacitation1

Abstract Sperm capacitation is a maturation process, occurring in the female reproductive tract, that produces fertilization-competent spermatozoa. Protein tyrosine phosphorylation represents an important event in capacitation. The present study demonstrates the capacitation-dependent tyrosine-phosphorylation of phospholipid hydroperoxide glutathione peroxidase (PHGPx), the disulfide cross-linked, major structural protein of the sperm mitochondrial capsule. Immunofluorescence microscopy using an antiphosphotyrosine monoclonal antibody (anti-pY20) demonstrated the presence of capacitation-associated tyrosine phosphorylated proteins in the flagellum of hamster spermatozoa. Among the tyrosine-phosphorylated polypeptides (Mr 19 000– 99 000), a 19-kDa polypeptide was the only one that can be solubilized completely by Triton X-100-dithiothreitol (DTT). The 19-kDa polypeptide was purified by anion-exchange chromatography and by immunoaffinity chromatography. Proteomic identification of the 19-kDa polypeptide by nano-electrospray tandem mass spectrometry yielded six peptides that matched the National Center for Biotechnology Information (NCBI) database sequences of bovine PHGPx. Indirect immunofluorescence localized PHGPx to the midpiece of the flagellum and the immunoblot analysis demonstrated its DTT-dependent release from purified flagella. DTT extracts of noncapacitated spermatozoa exhibited a charge train of four major PHGPx isoforms (pIs 7.5– 9.0) by two-dimensional PAGE, whereas capacitated spermatozoa revealed the generation of new acidic PHGPx isoforms with isoelectric points ranging between pH 6.0–7.0 and 4.0–5.0, indicating that it is posttranslationally modified during capacitation. These data suggest that the tyrosine-phosphorylation of PHGPx may represent an important event in the signaling pathway(s) associated with capacitation and could potentially affect mitochondrial function.
Mitigating Cyber Identity Fraud using Advanced Multi Anti-Phishing Technique

Developing Countries are gradually transiting from cash to an electronic based economy by virtue of cashless policy implementation. With this development, cyber criminals and hackers who hitherto attacked businesses and individuals across the Atlantic now see this development as a new venture for their criminal acts and are thus re-directing their energies towards exploiting possible loopholes in the electronic payment system in order to perpetuate fraud. In this paper, we proposed an enhanced approach to detecting phishing attempts and preventing unauthorized online banking withdrawal and transfer. We employed the use of Semantics Content Analysis, Earth Mover Distance and Biometric Authentication with finger print to construct a model. We demonstrated the efficacy of the implemented model with the experiments conducted, a good and considerable result was achieved.
A Template-Based Approach to Summarize XML Collections

Existing summarization approaches for XML concentrate on extracting common structure and compressing the data, to optimize storage and speed up queries. Neither compression, nor structure extraction suffices for advanced, content-based summarization tasks. We present a set of tools for semi-automatic summarization of XML collections, where the user can specify semantically relevant features for an XML collection in a template, and define rules for summarization. The system assists the user in generating one or several such templates, selects applicable templates for a given collection, and applies them for automatic summarization. In experiments on the INEX collection (among others), we investigate the merits and limitations of our approach.
Simulation and experimental qualification of the response of microstrip detectors to ion beams

In the framework of the construction of a novel Femtoscope Array for Correlation and Spectroscopy, named FARCOS, aiming at the identification in charge and mass even of particles stopping in the first detection layer, we are performing a thorough characterization of the silicon detector layers in terms of the collection properties as a function of the point of incidence. We have experimental evidence - as previously observed also in the literature for other strip detectors - that interstrip incidence alters the signal shape not only for the trivial effect of charge sharing but also because of induction effects on neighbor strips. In order to clarify this issue we developed a custom simulation suite of the electron-hole transport and signal formation able to properly describe 3-D Coulomb interaction and thermal diffusion in semiconductor detectors. We ran a batch of significant and representative simulations presenting the qualitative correct interpretation and the quantitative validation as proved by the comparison of the simulation results with the experimental data.
Multiphase Pickups for Large Lateral Tolerance Contactless Power-Transfer Systems

The majority of commercial contactless power-transfer systems used in manufacturing applications can only tolerate limited movement of the power pickup relative to the track to which it is magnetically coupled. This paper describes a new multiphase (quadrature) pickup that significantly improves the tolerance of the power receiver to such relative movement, enabling expanded applications such as continuously powered automatic guided vehicles, robots, and other vehicles to be considered. The advantage gained is largely independent of the track type, so that single-phase or multiphase tracks can be used as desired to improve both the power transfer and lateral tolerance as required. The improvement is achieved by capturing both vertical and horizontal components of magnetic flux around any track.
Dynamic reusability-based replication with network address mapping in CMPs

In a Chip MultiProcessor(CMP) with shared caches, the last level cache is distributed across all the cores. This increases the on-chip communication delay and thus influence the processor's performance. Replication can be provided in shared caches to reduce the on-chip communication delay. However, current proposals do not take into account replicating blocks's access characteristics and how to make the best of replicas, which have limited performance benefit. In this paper, we observe that reusability of cache blocks influences the availability of replication scheme severely. Based on this observation, we propose Dynamic Reusability-based Replication (DRR), a novel cache design to exploit efficient replicas management using blocks's reuse pattern. DRR monitors the recent referenced cache blocks' access pattern, and replicates the blocks with high reusability to appropriate L2 slices, and the replicated copies can be shared by their nearby cores. We evaluate DRR for 16-core system using splash-2 and parsec benchmarks. DRR improves performance by 30% on average over conventional shared cache design, 16% over Victim Replication(VR), 8% over Adaptive Selected Replication (ASR), and 25% over R-NUCA.
A 0.27mm2 13.5dBm 2.4GHz all-digital polar transmitter using 34%-efficiency Class-D DPA in 40nm CMOS

An all-digital polar transmit (TX) architecture exhibits advantages of low cost, low power, as well as reconfigurability with full usage of digital computational power. The design challenge is the need for continuous innovation to further enhance power efficiency and minimize silicon area while achieving the best-in-class RF performance. The design must also meet the increasing demand of concurrent operation for multi-radio SoC integration. The presented Bluetooth TX demonstrates advancements in this direction with over 30% power and 66% area reduction.
Sclerostin and Insulin Resistance in Prediabetes: Evidence of a Cross Talk Between Bone and Glucose Metabolism

OBJECTIVE A gene mutation of the Wnt/β-catenin signaling cascade is present in rare patients with the insulin resistance syndrome. Sclerostin is a circulating peptide inhibiting Wnt/β-catenin signaling. Our aims were to evaluate serum sclerostin in subjects with prediabetes and to analyze its relationship with insulin resistance and β-cell function. RESEARCH DESIGN AND METHODS We performed a cross-sectional study including 43 healthy normal glucose-tolerant (NGT) individuals and 79 individuals with impaired glucose regulation (IGR), which included subjects with impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and combined IFG-IGT, undergoing oral glucose tolerance test (OGTT) and dual-energy X-ray absorptiometry. A subgroup of 18 with NGT and 30 with IGR also underwent a euglycemic–hyperinsulinemic clamp with tracer. RESULTS Sclerostin levels were higher in IGR compared with NGT (50.8 ± 2.4 vs. 38.7 ± 2.3 pmol/L; P = 0.01), positively correlated with HOMA-insulin resistance (IR) (r = 0.62; P < 0.001), and negatively correlated with insulin-mediated total body glucose disposal (r = −0.40; P < 0.001). Fasting endogenous glucose production (EGP) and hepatic and adipose tissue insulin resistance indexes were positively correlated with sclerostin levels (r = 0.48, r = 0.62, and r = 0.61, respectively; P < 0.001). Fasting and OGTT insulin clearance were inversely correlated with sclerostin serum levels (r = −0.52 and r = −0.44, respectively; both P < 0.001). Sclerostin levels were not correlated with β-cell function parameters. In multiple linear regression analysis, the addition of sclerostin levels to the traditional risk factors for insulin resistance improved the r2 associated with HOMA-IR (r2 change: 0.055; F change: 28.893; P = 0.001) and insulin-mediated total body glucose disposal (r2 change: 0.059; F change: 4.938; P = 0.033). CONCLUSIONS Sclerostin levels are increased in individuals with prediabetes and correlated with insulin resistance in skeletal muscle, liver, and adipose tissue. The correlation between sclerostin and insulin clearance at fasting state and during OGTT is novel; thus, studies are needed to explore the potential causal relationship.
A Neural Learning Classifier System with Self-Adaptive Constructivism for Mobile Robot Control

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.