Miracle-dz/UniFAR-FTUs huggingface dataset:
Zedwulf: Power-Performance Tradeoffs of a 32-Node Zynq SoC Cluster

Commodity SoCs with hybrid architectures that combine CPUs with programmable FPGA fabric such as the Xilinx Zynq SoC have become a competitive energy-efficient platform for addressing irregular parallelism in graph problems. In this paper, we prototype a 32-node cluster composed from these Zynq SoC chips to accelerate communication-bound sparse graph-oriented applications such as neural network simulations. We develop specialized MPI routines specifically developed for irregular accelerator-to-accelerator communication of small message traffic. We use the ARM processor for handling the MPI stack while offloading compute-intensive calculations to the FPGA. For graphs with 32M nodes and 32M edges, Zedwulf delivers the highest 94 MTEPS (Million Traversed Edges Per Second)throughput over other x86 multi-threaded platforms in our study by 1.2 -- 1.4×. For this experiment, Zedwulf operates at an efficiency of 0.49 MTEPS/W when using ARM+FPGA which is1.2× better than using ARMv7 CPUs alone, and within 8% of the Intel Core i7-4770k platform.
Investigating the Effects of Exam Length on Performance and Cognitive Fatigue

This study examined the effects of exam length on student performance and cognitive fatigue in an undergraduate biology classroom. Exams tested higher order thinking skills. To test our hypothesis, we administered standard- and extended-length high-level exams to two populations of non-majors biology students. We gathered exam performance data between conditions as well as performance on the first and second half of exams within conditions. We showed that lengthier exams led to better performance on assessment items shared between conditions, possibly lending support to the spreading activation theory. It also led to greater performance on the final exam, lending support to the testing effect in creative problem solving. Lengthier exams did not result in lower performance due to fatiguing conditions, although students perceived subjective fatigue. Implications of these findings are discussed with respect to assessment practices.
Self- regulation of motivation: Contributing to students' learning in middle school

The self-regulation of motivation (SRM) implies that students can regulate their motivation to learn, a process that has a positive impact on academic achievement. SRM regulates students’ behavior through strategies that are influenced by motivational beliefs (e.g., expectations, goals, and values). The self-regulation of motivation allows students to motivate themselves and guides their behavior, and thus, becomes part of the self-regulatory process. In this paper our goal was to identify beliefs regarding motivation to learn, more specifically those that promote
A Ca2+ transport system associated with the plasma membrane of Dictyostelium discoideum is activated by different chemoattractant receptors

Amebae of Dictyostelium exhibit a transient uptake of extracellular Ca2+ approximately 5 s after activation of surface folate or cAMP receptors (Bumann, J., B. Wurster, and D. Malchow. 1984. J. Cell Biol. 98:173-178). To further characterize these Ca2+ entry systems, we analyzed 45Ca2+ uptake by resting and activated amebae. Like the surface chemoreceptors, folate- and cAMP-induced Ca2+ uptake responses were developmentally regulated; the former response was evident in vegetative but not aggregation-competent cells, whereas the latter response displayed the opposite pattern of expression. In contrast, other characteristics of these Ca2(+)-uptake pathways were remarkably similar. Both systems (a) exhibited comparable kinetic properties, (b) displayed a high specificity for Ca2+, and (c) were inhibited effectively by Ruthenium Red, sodium azide, and carbonylcyanide m- chlorophenyl-hydrazone. These results, together with the finding that vegetative cells transformed with a plasmid expressing the surface cAMP receptor exhibit a cAMP-induced Ca2+ uptake, suggest that different chemoreceptors activate a single Ca2+ entry pathway. Additional pharmacological and ion competition studies indicated that receptor- mediated Ca2+ entry probably does not involve a Na+/Ca2+ exchanger or voltage-activated channels. Chemoattractant binding appears to generate intracellular signals that induce activation and adaption of the Ca2(+)- uptake response. Analysis of putative signaling mutants suggests that Ca2+ entry is not regulated by the guanine nucleotide-binding (G) protein subunits G alpha 1 or G alpha 2, or by G protein-mediated changes in intracellular cAMP or guanosine 3,'5'-cyclic monophosphate (cGMP).
A Cell-Regulatory Mechanism Involving Feedback between Contraction and Tissue Formation Guides Wound Healing Progression

Wound healing is a process driven by cells. The ability of cells to sense mechanical stimuli from the extracellular matrix that surrounds them is used to regulate the forces that cells exert on the tissue. Stresses exerted by cells play a central role in wound contraction and have been broadly modelled. Traditionally, these stresses are assumed to be dependent on variables such as the extracellular matrix and cell or collagen densities. However, we postulate that cells are able to regulate the healing process through a mechanosensing mechanism regulated by the contraction that they exert. We propose that cells adjust the contraction level to determine the tissue functions regulating all main activities, such as proliferation, differentiation and matrix production. Hence, a closed-regulatory feedback loop is proposed between contraction and tissue formation. The model consists of a system of partial differential equations that simulates the evolution of fibroblasts, myofibroblasts, collagen and a generic growth factor, as well as the deformation of the extracellular matrix. This model is able to predict the wound healing outcome without requiring the addition of phenomenological laws to describe the time-dependent contraction evolution. We have reproduced two in vivo experiments to evaluate the predictive capacity of the model, and we conclude that there is feedback between the level of cell contraction and the tissue regenerated in the wound.
Bayesian frame synchronization using periodic preamble for OFDM-based WLANs

In this letter, the principles of Bayesian changepoint detection are applied to the problem of frame synchronization in wireless systems that use a periodic training signal as part of the packet preamble. An autocorrelation-based metric is used, which allows modeling the synchronization problem as a problem of changepoint detection of a Gaussian process. A MAP estimator for the changepoint is derived that suits the wireless scenario. Examples and comparisons are made using the IEEE 802.11a OFDM standard. It is demonstrated that the proposed method has advantages over some existing synchronization approaches in terms of accuracy, latency, and/or complexity.
Immunohistochemical Expression of Myeloperoxidase in Placental Samples of Systematic Lupus Erythematosus Pregnancies

Objective: Reports of increased level of Myeloperoxidase (MPO) in plasma and placental extracts of Systematic Lupus Erythematosus (SLE) has been proposed that MPO may have an important role in this pregnancy complication. In present study immunohistochemical MPO expression was investigated in placental samples of SLE women compared with normal controls. Materials and methods: Ten patients with SLE were recruited as case group. Control group was selected from mothers with normal uncomplicated pregnancies. A monoclonal antibody specific for MPO was used for immunohistochemical staining and then the staining was quantified and differences between groups were compared using Mann-Whitney U test. Results: There were significant differences in the expression levels of MPO in the syncytiotrophoblast cells and the extravillous trophoblast cells between the control and SLE groups (p < 0.05). There were no significant differences in the expression level of MPO in the vascular endothelium and the relative number of the MPO-positive leukocytes in placental tissue between SLE and control groups (p > 0.05). Conclusion: The present study showed that MPO expression is increased in syncytiotrophoblast cells and the extravillous trophoblast cells of SLE placentas compared to healthy subjects. It seems that these changes are able to impress structure and function of placenta and survival of the fetus.
Decay of Aspen (Populus tremuloides Michx.) Wood in Moist and Dry Boreal, Temperate, and Tropical Forest Fragments

Abstract In this study, we set up a wood decomposition experiment to i) quantify the percent of mass remaining, decay constant and performance strength of aspen stakes (Populus tremuloides) in dry and moist boreal (Alaska and Minnesota, USA), temperate (Washington and Idaho, USA), and tropical (Puerto Rico) forest types, and ii) determine the effects of fragmentation on wood decomposition rates as related to fragment size, forest age (and/or structure) and climate at the macro- and meso-scales. Fragment sizes represented the landscape variability within a climatic region. Overall, the mean small fragments area ranged from 10–14 ha, medium-sized fragments 33 to 60 ha, and large fragments 100–240 ha. We found that: i) aspen stakes decayed fastest in the tropical sites, and the slowest in the temperate forest fragments, ii) the percent of mass remaining was significantly greater in dry than in moist forests in boreal and temperate fragments, while the opposite was true for the tropical forest fragments, iii) no effect of fragment size on the percent of mass remaining of aspen stakes in the boreal sites, temperate dry, and tropical moist forests, and iv) no significant differences of aspen wood decay between forest edges and interior forest in boreal, temperate and tropical fragments. We conclude that: i) moisture condition is an important control over wood decomposition over broad climate gradients; and that such relationship can be non linear, and ii) the presence of a particular group of organism (termites) can significantly alter the decay rates of wood more than what might be predicted based on climatic factors alone. Biotic controls on wood decay might be more important predictors of wood decay in tropical regions, while abiotic constraints seems to be important determinants of decay in cold forested fragments.
Large system analysis of linear multistage parallel interference cancellation

In this paper, we derive an expression for the signal to interference-plus-noise ratio of a linear multistage parallel interference cancellation receiver. We focus on a linear multistage receiver which converges to the linear minimum mean-squared error receiver as the number of stages increases. The signal to interference-plus-noise ratio is given in terms of the system loading, the partial cancellation factor, the number of stages, and the signal-to. noise ratio. Our expression also allows a simple approximation for the bit error rate at each stage. Finally, we perform a numerical optimization to maximize the signal to interference-plus-noise ratio expression with respect to the partial cancellation factor of the resulting linear multistage receiver.
Dream Recall as a Function of Method of Awakening

&NA; Eleven subjects were awakened from dream periods (defined in terms of Dement and Kleitman's eye‐movement criteria) and asked to describe their dream experience. Subjects more often believed that they were awake and/or thinking when the awakening was gradual than when the awakening was abrupt (P <.05). Reports in which the subject believed that he had been awakened from a dreamless sleep were more frequent for the first several eye‐movement periods of the night than for eye‐movement periods which occurred toward morning (P <.05). Depth of sleep, as defined by the arousal threshold, also became lighter for successive eye‐movement periods during the night (P <.05).
Wireless fading vector channel model for multi-antenna system at mobile terminals

To investigate the performance of smart antenna technology applied in mobile terminals, the simulation of multi-antenna system requires a spatial channel model, which should reasonably characterize the effects of wireless channel, such as time-varying, multipath-fading and Doppler effects, between base station and mobile handsets. This paper presents a space-time vector channel model fit for these demands. Based on the lowpass-equivalent impulse response, the diverse stochastic parameters of the channel, such as DOA/TOA and Rayleigh fading, are discussed at full length. The final simulated channel data produced by this model is consistent with previous theory and measurement, which exhibits its feasibility for the further investigation of different smart antenna algorithms or joint detection techniques.
A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method

Heart disease is one of the most common diseases in the world. The objective of this study is to aid the diagnosis of heart disease using a hybrid classification system based on the ReliefF and Rough Set (RFRS) method. The proposed system contains two subsystems: the RFRS feature selection system and a classification system with an ensemble classifier. The first system includes three stages: (i) data discretization, (ii) feature extraction using the ReliefF algorithm, and (iii) feature reduction using the heuristic Rough Set reduction algorithm that we developed. In the second system, an ensemble classifier is proposed based on the C4.5 classifier. The Statlog (Heart) dataset, obtained from the UCI database, was used for experiments. A maximum classification accuracy of 92.59% was achieved according to a jackknife cross-validation scheme. The results demonstrate that the performance of the proposed system is superior to the performances of previously reported classification techniques.
Sequential and Parallel Experimental Results with Bipartite Matching Algorithms

We present experimental results for four bipartite matching algorithms on 11 classes of graphs. The algorithms are depth-rst search (dfs), breadth-rst search (bfs), the push-relabel algorithm GT88b], and the algorithm by Alt, Blum, Mehlhorn, and Paul (abmp) ABMP91]. dfs was thought to be a good choice for bipartite matching but our results show that, depending on the input graph, it can have very poor performance. bfs on the other hand has generally very good performance. The results also show that the abmp and push-relabel implementations are similar in performance, but abmp was faster in most cases. We did not nd a clear-cut advantage of abmp over bfs or vice-versa, but both the abmp and push-relabel implementations have generally smaller growth rates than bfs, and should thus be preferred if very large problems are to be solved. For small problems bfs is the best choice. We also present experimental results from a parallel implementation of the push-relabel algorithm, showing that it can be up to three times faster than its sequential implementation, on a shared-memory multiprocessor using up to 12 processors.
Need Singapore Fear Floating? A DSGE-VAR Approach

This paper uses a DSGE-VAR model to examine the managed exchange-rate system at work in Singapore and asks if the country has any reason to fear floating the exchange rate with a Taylor rule inflation-targeting mechanism that uses the short term interest rate instead of the exchange rate as the benchmark monetary policy instrument. Our simulation results show that the use of a more flexible exchange rate system will reduce volatility in inflation and investment but consumption volatility will increase. Overall, there are neither signi ficant welfare gains or losses in the regime shift. Given the highly open and trade dependent nature of the Singapore economy where the policy preference is for exchange rate stability, there is no impetus to abandon the present monetary regime.
A S alable Approa h to Balan ed, High-dimensional Clustering of Market-baskets

Abstra t This paper presents Opossum, a novel similarity-based lus-tering approa h based on onstrained, weighted graph-partitioning. Opos-sum is parti ularly attuned to real-life market baskets, hara terized by very high-dimensional, highly sparse ustomer-produ t matri es with positive ordinal attribute values and signi(cid:12) ant amount of outliers. Sin e it is built on top of Metis, a well-known and highly eÆ ient graph-partitioning algorithm, it inherits the s alable and easily parallelizeable attributes of the latter algorithm. Results are presented on a real retail industry data-set of several thousand ustomers and produ ts, with the help of Clusion, a luster visualization tool.
Hypothesis Testing in High-Dimensional Regression Under the Gaussian Random Design Model: Asymptotic Theory

We consider linear regression in the high-dimensional regime where the number of observations n is smaller than the number of parameters p. A very successful approach in this setting uses 11-penalized least squares (also known as the Lasso) to search for a subset of s0 <; n parameters that best explain the data, while setting the other parameters to zero. Considerable amount of work has been devoted to characterizing the estimation and model selection problems within this approach. In this paper, we consider instead the fundamental, but far less understood, question of statistical significance. More precisely, we address the problem of computing p-values for single regression coefficients. On one hand, we develop a general upper bound on the minimax power of tests with a given significance level. We show that rigorous guarantees for earlier methods do not allow to achieve this bound, except in special cases. On the other, we prove that this upper bound is (nearly) achievable through a practical procedure in the case of random design matrices with independent entries. Our approach is based on a debiasing of the Lasso estimator. The analysis builds on a rigorous characterization of the asymptotic distribution of the Lasso estimator and its debiased version. Our result holds for optimal sample size, i.e., when n is at least on the order of s0 log(p/s0). We generalize our approach to random design matrices with independent identically distributed Gaussian rows xi ~ N(0, Σ). In this case, we prove that a similar distributional characterization (termed standard distributional limit) holds for n much larger than s0(log p)2.Our analysis assumes Σ is known. To cope with unknown Σ, we suggest a plug-in estimator for sparse covariances Σ and validate the method through numerical simulations. Finally, we show that for optimal sample size, n being at least of order s0 log(p/s0), the standard distributional limit for general Gaussian designs can be derived from the replica heuristics in statistical physics. This derivation suggests a stronger conjecture than the result we prove, and near-optimality of the statistical power for a large class of Gaussian designs.
Quantitative Vascular Pathology and Phenotyping Familial and Sporadic Cerebral Small Vessel Diseases

We quantified vascular changes in the frontal lobe and basal ganglia of four inherited small vessel diseases (SVDs) including cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), pontine autosomal dominant microangiopathy and leukoencephalopathy (PADMAL), hereditary multi‐infarct dementia of Swedish type (Swedish hMID), and hereditary endotheliopathy with retinopathy, nephropathy, and stroke (HERNS). Vascular pathology was most severe in CADASIL, and varied with marginally greater severity in the basal ganglia compared to the frontal lobe. The overall sclerotic index values in frontal lobe were in the order CADASIL ≥ HERNS > PADMAL > Swedish hMID > sporadic SVD, and in basal ganglia CADASIL > HERNS > Swedish hMID > PADMAL> sporadic SVD. The subcortical white matter was almost always more affected than any gray matter. We observed glucose transporter‐1 (GLUT‐1) protein immunoreactivities were most affected in the white matter indicating capillary degeneration whereas collagen IV (COL4) immunostaining was increased in PADMAL cases in all regions and tissue types. Overall, GLUT‐1 : COL4 ratios were higher in the basal ganglia indicating modifications in capillary density compared to the frontal lobe. Our study shows that the extent of microvascular degeneration varies in these genetic disorders exhibiting common end‐stage pathologies but is the most aggressive in CADASIL.
Relationship between IL-17 serum level and ambulatory blood pressure in women with polycystic ovary syndrome

Background Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders with an inflammatory basis. It is associated with hyperandrogenism in women and can be also associated with increased activity of the renin-angiotensin system (RAS). Approximately 5% to 10% of women of reproductive age are affected by this disease. This syndrome is the main cause of infertility. Blood pressure may be one of the complications of the syndrome. Objectives In this study, we sought to assess the role of the IL-17 inflammatory cytokine in increasing blood pressure in patients with PCOS. Patients and Methods In this cross-sectional study, after obtaining informed consent, we evaluated 85 patients with PCOS. IL-17 serum level was measured after separating the serum via ELISA method. The results obtained for the two groups of patients with high blood pressure and normal blood pressure were compared with each other. Results The daytime blood pressure was abnormal in eight patients, while it was normal in 72 patients. The blood pressure during the day had a direct correlation with the IL-17serum level; as a result, the mean IL-17 serum level in patients with high blood pressure was 77.10 ± 17.94 ρ g/ml while in those with normal blood pressure it was 55.20 ± 13.71 ρ g/ml (P = 0.001). High blood pressure during the night also showed a direct relation with theIL-17 serum level (P = 0.001). In addition, increasing of ambulatory 24-hourblood pressure was significantly related with IL-17 serum level, in such a way that the IL-17 serum level of people with high blood pressure rose by almost 22 ρg/ml during 24 hours (P = 0.001). Conclusions Our results showed an association between PCO syndrome and inflammatory factors. The IL-17 serum level was directly associated with the increase in blood pressure.
Blockade of NMDA receptors in the dorsomedial striatum prevents action–outcome learning in instrumental conditioning

Although there is consensus that instrumental conditioning depends on the encoding of action–outcome associations, it is not known where this learning process is localized in the brain. Recent research suggests that the posterior dorsomedial striatum (pDMS) may be the critical locus of these associations. We tested this hypothesis by examining the contribution of N‐methyl‐d‐aspartate receptors (NMDARs) in the pDMS to action–outcome learning. Rats with bilateral cannulae in the pDMS were first trained to perform two actions (left and right lever presses), for sucrose solution. After the pre‐training phase, they were given an infusion of the NMDA antagonist 2‐amino‐5‐phosphonopentanoic acid (APV, 1 mg/mL) or artificial cerebral spinal fluid (ACSF) before a 30‐min session in which pressing one lever delivered food pellets and pressing the other delivered fruit punch. Learning during this session was tested the next day by sating the animals on either the pellets or fruit punch before assessing their performance on the two levers in extinction. The ACSF group selectively reduced responding on the lever that, in training, had earned the now devalued outcome, whereas the APV group did not. Experiment 2 replicated the effect of APV during the critical training session but found no effect of APV given after acquisition and before test. Furthermore, Experiment 3 showed that the effect of APV on instrumental learning was restricted to the pDMS; infusion into the dorsolateral striatum did not prevent learning. These experiments provide the first direct evidence that, in instrumental conditioning, NMDARs in the dorsomedial striatum are involved in encoding action–outcome associations.