Miracle-dz/UniFAR-FTUs huggingface dataset:
Vasohibin‐1 deficiency enhances renal fibrosis and inflammation after unilateral ureteral obstruction

Tubulointerstitial injuries are known to predict the deterioration of renal function in chronic kidney disease (CKD). We recently reported the protective role of Vasohibin‐1(VASH‐1), a negative feedback regulator of angiogenesis, in diabetic nephropathy, but its impact on tubulointerstitial injuries remains to be elucidated. In the present study, we evaluated the role of endogenous VASH‐1 in regulating the tubulointerstitial alterations induced by unilateral ureteral obstruction (UUO), and assessed its role on fibrogenesis and the activation of Smad3 signaling in renal fibroblasts. UUO was induced in female Vasohibin‐1 heterozygous knockout mice (VASH‐1+/−) or wild‐type (WT) (VASH‐1+/+) littermates. Mice were sacrificed on Day 7 after left ureter ligation, and the kidney tissue was obtained. Interstitial fibrosis, the accumulation of type I and type III collagen and monocytes/macrophages infiltration in the obstructed kidneys (OBK) were significantly exacerbated in VASH‐1+/− mice compared with WT mice (Day 7). The increases in the renal levels of TGF‐β1, pSmad3, NF‐κB pp65, CCL2 mRNA, and the number of interstitial fibroblast‐specific protein‐1 (FSP‐1)+ fibroblasts in the OBK were significantly aggravated in VASH‐1+/− mice. In addition, treatment with VASH‐1 siRNA enhanced the TGF‐β1‐induced phosphorylation of Smad3, the transcriptional activation of the Smad3 pathway and the production of type I/type III collagen in fibroblasts, in vitro. Taken together, our findings demonstrate a protective role for endogenous VASH‐1 on tubulointerstitial alterations via its regulation of inflammation and fibrosis and also show the direct anti‐fibrotic effects of VASH‐1 on renal fibroblasts through its modulation of TGF‐β1 signaling.
Variational Bayesian inference for nonlinear acoustic echo cancellation using adaptive cascade modeling

In this contribution, we present a variational Bayesian framework for the acoustic echo cancellation problem in the presence of a memoryless loudspeaker nonlinearity. We pursue a cascade modeling strategy, where first-order Markov models are described over the acoustic echo path and the nonlinear expansion coefficients. An iterative algorithm is then derived that learns the posterior on the echo path and the nonlinear coefficients to fit the evidence distribution. We show that the formulated variational Bayesian state-space frequency-domain adaptive filter is efficiently implementable and performs joint learning of the echo path and the loudspeaker nonlinearity. The algorithm exploits the internal exchange of the reliability information, resulting in effective linear and nonlinear echo cancellation.
Distributed Combinatorial Optimization – Extended Abstract

Approximating integer linear programs by solving a relaxation to a linear program (LP) and afterwards reconstructing an integer solution from the fractional one is a standard technique in a non-distributed scenario. Surprisingly, the method has not often been applied for distributed algorithms. In this paper, we show that LP relaxation is a powerful technique also to obtain fast distributed approximation algorithms. We present a novel deterministic distributed algorithm which computes a constant factor approximates for fractional covering and packing problems in only log rounds, using messages of logarithmic size. If messages are allowed to be larger, we show that a constant approximation can be achieved in a logarithmic number of rounds only. Finally, we show that by combining our LP approximation algorithms with randomized rounding techniques, we obtain efficient distributed approximation algorithms for a number of combinatorial problems.
Effects of social sustainability signaling on neural valuation signals and taste-experience of food products

Value-based decision making occurs when individuals choose between different alternatives and place a value on each alternative and its attributes. Marketing actions frequently manipulate product attributes, by adding, e.g., health claims on the packaging. A previous imaging study found that an emblem for organic products increased willingness to pay (WTP) and activity in the ventral striatum (VS). The current study investigated neural and behavioral processes underlying the influence of Fair Trade (FT) labeling on food valuation and choice. Sustainability is an important product attribute for many consumers, with FT signals being one way to highlight ethically sustainable production. Forty participants valuated products in combination with an FT emblem or no emblem and stated their WTP in a bidding task while in an MRI scanner. After that, participants tasted—objectively identical—chocolates, presented either as “FT” or as “conventionally produced”. In the fMRI task, WTP was significantly higher for FT products. FT labeling increased activity in regions important for reward-processing and salience, that is, in the VS, anterior and posterior cingulate, as well as superior frontal gyrus. Subjective value, that is, WTP was correlated with activity in the ventromedial prefrontal cortex (vmPFC). We find that the anterior cingulate, VS and superior frontal gyrus exhibit task-related increases in functional connectivity to the vmPFC when an FT product was evaluated. Effective connectivity analyses revealed a highly probable directed modulation of the vmPFC by those three regions, suggesting a network which alters valuation processes. We also found a significant taste-placebo effect, with higher experienced taste pleasantness and intensity for FT labeled chocolates. Our results reveal a possible neural mechanism underlying valuation processes of certified food products. The results are important in light of understanding current marketing trends as well as designing future interventions that aim at positively influencing food choice.
International Journal of Emerging Electric Power Systems Multi-Agent Models for Consumer Choice and Retailer Strategies in the Competitive Electricity Market

The benefit to end-users of electricity, mainly in terms of low prices, is strictly related to the interaction among the consumers themselves and retailers. The literature on retail competition has highlighted possible distortions in market outcomes due to unresponsive demand and boundedly rational consumers. Hence, a model appropriate to represent this aspect of the market is needed. The paper proposes a general model of the interaction among retailers and consumers in the electricity market based on the theory of multi-agent systems. The model incorporates different assumptions concerning the behavior of the players that corresponds to different levels of interaction in determining the market outcomes. The model is validated interpretively by the results provided in terms of Game Theory equilibrium. The results of an extensive set of simulations on a population of 1,000 consumers is presented and discussed.
Modeling and design of a three-phase grid connected PV system based on PWM current source inverter and P-I curve slope MPPT technique

This paper describes a sensorless photovoltaic grid connected system using a MPPT technique based on optimal slope of P-I curve of power load. This system is composed of only one stage: SPWM current source inverter. This system operates without sensor and without tuning. Modeling is presented and a multi-objectives design is performed. The results are validated by simulation in the Matlab-Simulink environment.
Does Consolidation of Visuospatial Sequence Knowledge Depend on Eye Movements?

In the current study, we assessed whether visuospatial sequence knowledge is retained over 24 hours and whether this retention is dependent on the occurrence of eye movements. Participants performed two sessions of a serial reaction time (SRT) task in which they had to manually react to the identity of a target letter pair presented in one of four locations around a fixation cross. When the letter pair ‘XO’ was presented, a left response had to be given, when the letter pair ‘OX’ was presented, a right response was required. In the Eye Movements (EM) condition, eye movements were necessary to perform the task since the fixation cross and the target were separated by at least 9° visual angle. In the No Eye Movements (NEM) condition, on the other hand, eye movements were minimized by keeping the distance from the fixation cross to the target below 1° visual angle and by limiting the stimulus presentation to 100 ms. Since the target identity changed randomly in both conditions, no manual response sequence was present in the task. However, target location was structured according to a deterministic sequence in both the EM and NEM condition. Learning of the target location sequence was determined at the end of the first session and 24 hours after initial learning. Results indicated that the sequence learning effect in the SRT task diminished, yet remained significant, over the 24 hour interval in both conditions. Importantly, the difference in eye movements had no impact on the transfer of sequence knowledge. These results suggest that the retention of visuospatial sequence knowledge occurs alike, irrespective of whether this knowledge is supported by eye movements or not.
Explaining prejudice toward the mentally ill: A test of sociopolitical, demographic, and socioeconomic factors

People with mental disorders often face prejudices that can further deteriorate their condition. We tested whether Social Dominance Orientation (SDO), Right-Wing Authoritarianism (RWA), and Belief in a Just World (BJW), and characteristics of the mentally ill predict such prejudices. Both in a general population sample and a sample of health professionals and trainees, SDO, but not RWA and BJW, predicted more prejudice, although this pattern was less pronounced among health professionals/trainees. BJW interacted with the targets' gender in Study 1, predicting less empathy toward a male but not toward a female mentally ill person. In Study 2, depressed individuals were blamed more for their illness than those with schizophrenia or cancer. Implications for future research and clinical practice are discussed.
How valid is the tallquist method in screening pregnant women with anemia in poor rural settings of southwestern Nigeria?

Background: Diagnosis of anemia is challenging in resource-poor settings due to inadequate laboratory resources. This study assessed the validity of the Tallquist haemoglobinometer in assessing anemia among pregnant women in Osogbo, Southwestern Nigeria. Methods: This was a cross - sectional study, in which 200 pregnant women of reproductive age were selected using multistage sapling method. A checklist was used to collect socio-demographic data and the results of the screening test. Blood collection and analysis were carried out using standardized referenced methods. Results: Mean±SD age of the respondents was 28.9+3.9 yrs. ; and 62 (62.6%) had up to primary level education. When Tallquist and Haematocrit methods were compared, there was 68.4%, 83.5% and 100% likelihood of Tallquist method (TM) diagnosing severe, moderate and mild anemia, respectively. The validity indices of the TM versus Haematocrit method as the gold standard revealed the sensitivity of 97.9%, specificity of 92.1%, positive predictive value of 92.4%, and negative predictive value of 97.9% and diagnostic accuracy of 95.0%. When compared to the Haemoglobin Cyanide method, the Tallquist method showed a calculated sensitivity of 96.6%, specificity of 87.4%, positive predictive value of 86.0%, and negative predictive value of 97.0% and diagnostic accuracy of 91.5%. Conclusion: The TM is a valid tool in screening anemia among pregnant women in resource- poor settings and rural primary health care centers in Southwestern Nigeria; therefore, its use should be encouraged, particularly to assess mild to moderate anemia.
Isolation of nuclear envelopes with polyanions

Optimal conditions for the isolation of nuclear envelopes by the action of heparin on nuclei are established and a morphological and biochemical study of such isolated envelopes is presented. An almost 100% yield of pure nuclear envelopes can be obtained by a single sedimentation step after incubation of nuclei with heparin for 40 min at 4 degrees C. The nuclear membrane pellet obtained in this way contains whole envelopes with a preserved perinuclear space and with ribosomes present on the outher leaflet. A single band with an apparent buoyant density of 1.18 is obtained by sucrose density gradient analysis. The chemical composition of the pellet is similar to that of the purified membranes and corresponds to 62% proteins, 34% phospholipids, 3% RNA, and 0.5% DNA. The presence of low concentrations of sodium phosphate (2-10 mM) is critical for a complete solubilization of the chromatin. A less rapid and complete solubilization is obtained with the potassium salt. Low concentrations of Mg++ (1-3 mM) counteract chromatin solubilization by heparin mainly at the level of chromatin- nuclear membrane association. The presence of EDTA in the medium leads to isolated nuclear envelopes on which neither ribosomes nor nuclear pores are visible, indicating the pore structure is dependent on the presence of Ca++ or Mg++. A comparison with other polyanions indicates a decisive advantage of heparin. However, pure nuclear envelopes can also be obtained by the action of dextran sulfate (mol wt 500,000) on nuclei incubated for 5 min at 37 degrees C, in the presence of phosphate ions.
Non-linear dimensionality reduction techniques for classification and visualization

In this paper we address the issue of using local embeddings for data visualization in two and three dimensions, and for classification. We advocate their use on the basis that they provide an efficient mapping procedure from the original dimension of the data, to a lower intrinsic dimension. We depict how they can accurately capture the user's perception of similarity in high-dimensional data for visualization purposes. Moreover, we exploit the low-dimensional mapping provided by these embeddings, to develop new classification techniques, and we show experimentally that the classification accuracy is comparable (albeit using fewer dimensions) to a number of other classification procedures.
On the Power of Isolation in Planar Graphs

We study (deterministic) isolation for certain structures in directed and undirected planar graphs. The motivation for undertaking such a study comes from recent positive results on this topic. For example: Bourke et al. [2009] isolate a directed path in planar graphs and subsequently Datta et al. [2010b] isolate a perfect matching in bipartite planar graphs. Our first observation is that sufficiently strong (and plausible) isolations for certain structures in planar graphs would have strong consequences such as: NL ⊆ ⊕L, Bipartite-Matching ∈ NC, and NP ⊆ ⊕P. Our second observation is that although we do not yet have such strong isolations for arbitrary planar graphs, we do have them for bipartite planar graphs, that is, non-bipartiteness is the main bottleneck.
Ontology-based reinterpretation of the SNOMED CT context model

SNOMED CT includes concepts that encode complex expressions in its context model under Situation with explicit context, which blends characteristics of information models with characteristics of ontolo-­‐ gies. In order to improve interoperability of isosemantic expressions that are constituted by different information model / ontology combi-­‐ nations, we propose an ontology-­‐based reinterpretation of four of the most representative patterns found in the SNOMED CT context model. The formalizations provided require the use of negation and universal quantification, thus requiring a shift from OWL-­‐EL to OWL-­‐DL. After a thorough analysis of the meaning of the SNOMED CT con-­‐ cepts that instantiate these patterns as well as ontological errors in the current OWL-­‐EL of SNOMED CT rendering we transformed a module of SNOMED CT according to these patterns. The classification perfor-­‐ mance of the resulting ontology was benchmarked for several trans-­‐ formation steps. Classification times remained under 1s for FaCT++ and under 3s for HermiT. Although the SNOMED CT module comprised only those concepts which are needed for expressing the content of the context model (about 5% of the complete context model), the results are encouraging as they suggest that the limited inclusion of OWL-­‐DL expressiveness does not lead to inacceptable performance results.
Tools and Structures for Modelling Domain/User Knowledge in Virtual Learning

This paper presents a work in progress whose purpose is to model the handled, acquired, correct and erroneous knowledge of individual learners engaged in learning activities through virtual learning environments. This knowledge is represented according to a cognitive-computational model which also serves to represent the domain knowledge via authoring tools. The latter generates structures that allow the tutor to provide an effective feedback to improve significantly the cognitive level of the learner.
The relationship among self-efficacy, perfectionism and academic burnout in medical school students

Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.
A Low Energy Electron Diffraction Study of Surface Structures

From the low-energy electron diffraction (LEED) analysis of the (110) surface of palladium we have determined an oscillatory relaxation with respect to the bulk interlayer spacing in the two topmost layers. We used R-factors for quantitative comparison of theoretical I-V curves with the experimental data. The oscillatory relaxation of the surface Pd(110) - d12 = (1.33 ± 0.05) u d23 = (1.44 ± 0.06) u d34 at its bulk value 1.38 u To get a minimum Pendry R-factor we had to consider atoms vibrations in the first layer in the direction parallel to the surface.
Online motion selection for semi-optimal stabilization using reverse-time tree

This paper presents a general method for creating an approximately optimal online stabilization system. An optimal stabilization system is an ideal online system that can calculate each optimal motion leading to a stable mechanical goal state depending on the current state. We propose a system that selects each semi-optimal motion according to the current state from a reverse-time tree. To create the reverse-time tree, we applied rapid semi-optimal motion planning method (RASMO) to a reverse-time search from a stable state. We also developed an online motion selection technique. To validate the proposed method, we simulated the stabilization of a double inverted pendulum. When we used an optimization criteria, time optimal, the system quickly stabilized the pendulum's posture and velocity. When we used higher resolution RASMO, the time approached the optimal time. The general framework proposed here is applicable to a variety of machines.
Modeling Far-field Acoustical Nonlinearity from F-35 Aircraft during Ground Run-up

The high noise levels associated with full-scale military aircraft result in nonlinear propagation, which results in acoustic shock formation and can alter noise perception. This propagation has been modeled for other aircraft but previous studies have been limited in scope, showing results for only select engine conditions and angles. Recent data measured near an F-35B allow for a more complete analysis of nonlinear propagation. Visual inspection of waveforms shows shock formation and persistence out to distances of up to 1220 m. Using an algorithm based on the Burgers equation, modified to include weak shock theory and an empirical correction for meteorological and ground effects, nonlinear and linear predictions are compared to measurements over a broad range of angles at 305 m. These analyses show that nonlinear effects become important in the maximum radiation direction at 75% thrust and increase with engine condition. At high engine powers, evidence of nonlinear propagation is found in the forward direction.
An Item-based collaborative filtering method using Item-based hybrid similarity

Item-based collaborative filtering is a preferred technique on recommender system. It uses a value of item rating similarity to predict user's preference. In this paper, we include values of item attribute similarity to adjust the predicted rating equation for target item. The results of Item-based collaborative filtering that hybrid item rating similarity and item attribute similarity techniques have Mean Absolute Error (MAE) less than a traditional Item-based collaborative filtering technique and others. The proposed algorithm is efficient to predict better than traditional algorithm as shown in our experiments.
Statechart simulator for modeling architectural dynamics

Software development is a constant endeavor to optimize qualities like performance and robustness while ensuring functional correctness. Architecture Description Languages (ADLs) form a foundation for modeling and analyzing functional and non-functional properties of software systems, but, short of programming, only the simulation of those models can ensure certain desired qualities and functionalities. The paper presents an adaptation to statechart simulation, as pioneered by D. Harel (1987). This extension supports architectural dynamism: the creation, replacement, and destruction of components. We distinguish between design-time dynamism, where system dynamics are statically proscribed (e.g., creation of a predefined component class in response to a trigger), and run-time dynamism, where the system is modified while it is running (e.g., replacement of a faulty component without shutting down the system). Our enhanced simulation language, with over 100 commands, is tool-supported.
A framework for dependability driven software integration

The integration of system and SW functions for efficiency, performance and especially dependability is of interest from a research and system design perspective. We propose a framework for directing the process of integration of SW functions, with the objective of designing and maintaining desired dependability attributes of the system over the integration process. Rules of composition for integrated functions, and measures to quantify the goodness of dependable system integration are also addressed.