Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-Switch Dual-Buck Grid-Connected Inverter with SPWM Control and Single Current Sensor

This paper presents a two-switch dual-buck grid-connected inverter with sinusoidal pulse-width modulation (SPWM) control and single current sensor. The freewheeling current flows through the independent diodes instead of the body diodes of the switches, so reverse recovery losses of the diodes can be reduced. Half of the power devices operate in high frequency at each half line cycle, and the others switch at grid period and can realize zero-current switching (ZCS), thus the efficiency can be increased. Moreover, uniploar modulation is adopted. Therefore, weight and volume of the output filter can be decreased. SPWM control is adopted, so the output filter is easy to design. Only one current sensor is used. The operating principle is illustrated. Finally, simulation results verify the theoretical analysis and satisfy the IEEE Std. 929-2000.
Heterogeneity of Focal Breast Lesions and Surrounding Tissue Assessed by Mammographic Texture Analysis: Preliminary Evidence of an Association with Tumor Invasion and Estrogen Receptor Status

Aim: This pilot study investigates whether heterogeneity in focal breast lesions and surrounding tissue assessed on mammography is potentially related to cancer invasion and hormone receptor status. Materials and Methods: Texture analysis (TA) assessed the heterogeneity of focal lesions and their surrounding tissues in digitized mammograms from 11 patients randomly selected from an imaging archive [ductal carcinoma in situ (DCIS) only, n = 4; invasive carcinoma (IC) with DCIS, n = 3; IC only, n = 4]. TA utilized band-pass image filtration to highlight image features at different spatial frequencies (filter values: 1.0–2.5) from fine to coarse texture. The distribution of features in the derived images was quantified using uniformity. Results: Significant differences in uniformity were observed between patient groups for all filter values. With medium scale filtration (filter value = 1.5) pure DCIS was more uniform (median = 0.281) than either DCIS with IC (median = 0.246, p = 0.0102) or IC (median = 0.249, p = 0.0021). Lesions with high levels of estrogen receptor expression were more uniform, most notably with coarse filtration (filter values 2.0 and 2.5, rs = 0.812, p = 0.002). Comparison of uniformity values in focal lesions and surrounding tissue showed significant differences between DCIS with or without IC versus IC (p = 0.0009). Conclusion: This pilot study shows the potential for computer-based assessments of heterogeneity within focal mammographic lesions and surrounding tissue to identify adverse pathological features in mammographic lesions. The technique warrants further investigation as a possible adjunct to existing computer aided diagnosis systems.
Intercomparison of Clean Air Status and Trends Network Nitrate and Nitric Acid Measurements with Data from Other Monitoring Programs

Abstract The U.S. Environmental Protection Agency Clean Air Status and Trends Network (CASTNET) utilizes an open-face filter pack system to measure concentrations of atmospheric sulfur and nitrogen species. Concentration data for nitrogen species measured with filter pack systems sometimes deviate from data collected by other measurement systems used to measure the same species. The nature of these differences suggests that more than one sampling mechanism or atmospheric process is involved. The study presented here examines these differences by intercomparing CASTNET data with data from other studies, examining the results from earlier intercomparison studies, and conducting a field test to investigate the effect of particle size on filter pack measurement systems. Measurements of nitrogen species from the Maryland Aerosol Research and Characterization (MARCH) monitoring site were compared with nitrogen concentrations at three nearby CASTNET sites. Results indicate that CASTNET measured higher particulate nitrate (NO3 -) and lower gaseous nitric acid (HNO3) concentrations. Comparisons of NO3 - from 34 collocated CASTNET and Inter-agency Monitoring of Protected Visual Environments (IMPROVE) sites show that CASTNET NO3 - measurements were typically higher than the corresponding IM PROVE values. Also, results from the Lake Michigan Air Director’s Consortium Midwest Ammonia Monitoring Project demonstrated NO3 - dissociation on Teflon filters. To investigate the effect of particle size, filter pack measurement systems were operated at three CASTNET sites with and without cyclones during six 7-day measurement periods from March to August 2006. Results indicate the size-selection cyclones had a significant effect on both NO3 - and HNO3 concentrations, but little effect on sulfate (SO4 2-) and ammonium (NH4 +) levels. NO3 - concentrations sampled with the open-face filters were significantly higher than concentrations measured with a 2.5-μm cut point, as were HNO3 concentrations. Although limited in spatial and temporal coverage, the field study showed that the use of an open-face filter pack may allow for the collection of coarse NO3 - particles and for the reaction of HNO3 with metals/salts on the Teflon filter.
The evaluation of hydrogen peroxide bleaching of Gonometa postica silk

The effect of hydrogen peroxide bleaching on Gonometa postica silk and the influence that temperature, pH and time duration had on hydrogen peroxide release , colour change, breaking load and stiffness were determined. The best bleaching (81 delta E) of the Gonometa postica silk fabric was obtained with 60 minutes exposure to hydrogen peroxide at 90°C and pH 8. Bleaching lowered the strength of the Gonometa postica silk fabric 7, 6% at pH10 but 12, 8% at pH 8. Rigidity of Gonometa postica silk fabric increased as a result of bleaching at 60°C, 70°C and 90°C at pH 8 and pH 10. The bending length was the highest (5.28 cm) after bleaching at 90°C and pH 8. Although acceptable bleaching of Gonometa postica silk fabric is reached with 60 minute exposure to hydrogen peroxide at 90°C and pH 8 or 180 minutes at 70°C at pH 8, bleaching cannot be recommended because the fabric becomes too rigid and requires a lower load to break. Gonometa postica silk fabric should be used in its natural colour or dyed in darker colours until a bleaching practice that would not cause the fabric to be harsh and stiff is developed.
Heating Dispersal for Self-Healing NAND Flash Memory

Substantially reduced lifetimes are becoming a critical issue in NAND flash memory with the advent of multi-level cell and triple-level cell flash memory. Researchers discovered that heating can cause worn-out NAND flash cells to become reusable and greatly extend the lifetime of flash memory cells. However, the heating process consumes a substantial amount of power, and some fundamental changes are required for existing NAND flash management techniques. In particular, all existing wear-leveling techniques are based on the principle of evenly distributing writes and erases. For self-healing NAND flash, this may cause NAND flash cells to be worn out in a short period of time. Moreover, frequently healing these cells may drain the energy quickly in battery-driven mobile devices, which is defined as the concentrated heating problem. In this paper, we propose a novel wear-leveling scheme called DHeating (Dispersed Heating) to address the problem. In DHeating, rather than evenly distributing writes and erases over a time period, write and erase operations are scheduled on a small number of flash memory cells at a time, so that these cells can be worn out and healed much earlier than other cells. In this way, we can avoid quick energy depletion caused by concentrated heating. In addition, the heating process takes several seconds and has become the new performance bottleneck. In order to address this issue, we propose a lazy heating repair scheme. The lazy heating repair scheme can ease the long time delays caused by the heating via delaying the heating operation and using the system idle time to repair. Furthermore, the flash memory's reliability becomes worse with the flash memory cells reaching the excepted worn-out time. We propose an early heating strategy to solve the reliability problem. With the extended lifetime provided by self-healing, we can trade some lifetimes for reliability. The idea is to start the healing process earlier than the expected worn-out time. We evaluate our scheme based on an embedded platform. The experimental results show that the proposed scheme can effectively prolong the consecutive heating time interval, alleviate the long time delays caused by the heating, and enhance the reliability for self-healing flash memory.
CODEA : an agent based multi-objective optimization framework

This work presents CODEA, a COoperative DEcentralized Architecture for Multiobjective Optimization. CODEA is an objectoriented framework that aims at the creation of groups of agents to tackle complex problems by cooperative search. This cooperation is carried out without any individual controlling the cooperation nor the behaviour of the agents. Each agent works on its own to improve itself and collaborates to improve the performance of the group by sharing information.
Web 2.0 and SOA: Converging Concepts Enabling the Internet of Services

Recently, the relationship between Web 2.0 and service-oriented architectures (SOAs) has received an enormous amount of coverage because of the notion of complexity-hiding and reuse, along with the concept of loosely coupling services. Some argue that Web 2.0 and SOAs have significantly different elements and thus cannot be regarded as parallel philosophies. Others, however, consider the two concepts as complementary and regard Web 2.0 as the global SOA. This paper investigate these two philosophies and their respective applications from both a technological and business perspective
Low-complexity compressive sensing detection for multi-user spatial modulation systems

In this work we present a low-complexity detection scheme for spatial modulation (SM) systems in the large-scale multiple access channel (MAC). The proposed strategy is based on compressive sensing (CS) and it exploits the sparsity and structure of the transmitted SM signals in the MAC to enhance the detection performance. The analytical and simulation results presented in this paper show that the proposed technique outperforms conventional CS and linear detectors with a reduced signal processing complexity.
Inferring project-specific bug patterns for detecting sibling bugs

Lightweight static bug-detection tools such as FindBugs, PMD, Jlint, and Lint4j detect bugs with the knowledge of generic bug patterns (e.g., objects of java.io.InputStream are not closed in time after used). Besides generic bug patterns, different projects under analysis may have some project-specific bug patterns. For example, in a revision of the Xerces project, the class field "fDTDHandler" is dereferenced without proper null-checks, while it could actually be null at runtime. We name such bug patterns directly related to objects instantiated in specific projects as Project-Specific Bug Patterns (PSBPs). Due to lack of such PSBP knowledge, existing tools usually fail in effectively detecting most of this kind of bugs. We name bugs belonging to the same project and sharing the same PSBP as sibling bugs. If some sibling bugs are fixed in a fix revision but some others remain, we treat such fix as an incomplete fix. To address such incomplete fixes, we propose a PSBP-based approach for detecting sibling bugs and implement a tool called Sibling-Bug Detector (SBD). Given a fix revision, SBD first infers the PSBPs implied by the fix revision. Then, based on the inferred PSBPs, SBD detects their related sibling bugs in the same project. To evaluate SBD, we apply it to seven popular open-source projects. Among the 108 warnings reported by SBD, 63 of them have been confirmed as real bugs by the project developers, while two existing popular static detectors (FindBugs and PMD) cannot report most of them.
Deep Reinforcement Learning for Flappy Bird

Reinforcement learning is essential for applications where there is no single correct way to solve a problem. In this project, we show that deep reinforcement learning is very effective at learning how to play the game Flappy Bird, despite the high-dimensional sensory input. The agent is not given information about what the bird or pipes look like it must learn these representations and directly use the input and score to develop an optimal strategy. Our agent uses a convolutional neural network to evaluate the Q-function for a variant of Q-learning, and we show that it is able to achieve super-human performance. Furthermore, we discuss difficulties and potential improvements with deep reinforcement learning.
Fast Computation of Lexical Affinity Models

We present a framework for the fast computation of lexical affinity models. The framework is composed of a novel algorithm to efficiently compute the co-occurrence distribution between pairs of terms, an independence model, and a parametric affinity model. In comparison with previous models, which either use arbitrary windows to compute similarity between words or use lexical affinity to create sequential models, in this paper we focus on models intended to capture the co-occurrence patterns of any pair of words or phrases at any distance in the corpus. The framework is flexible, allowing fast adaptation to applications and it is scalable. We apply it in combination with a terabyte corpus to answer natural language tests, achieving encouraging results.
Psychophysiological and Cortisol Responses to Psychological Stress in Depressed and Nondepressed Older Men and Women With Elevated Cardiovascular Disease Risk

Objective: The objective of this study was to compare psychophysiological and cortisol reactions to psychological stress in older depressed and nondepressed patients at risk for cardiovascular disease (CVD). Methods: Forty-eight depressed participants and 20 controls with elevated cardiovascular risk factors underwent a psychological stress test during which cardiovascular variables were measured. Salivary cortisol was collected after each test segment. Traditional (e.g., lipids) and atypical (e.g., C-reactive protein) CVD risk factors were also obtained. Results: At baseline, the groups did not differ on lipid levels, flow-mediated vasodilation, body mass index, or asymmetric dimethylarginine. However, the depressed patients had significantly higher C-reactive protein levels. Contrary to our hypothesis, there were no differences in baseline cortisol levels or diurnal cortisol slopes, but depressed patients showed significantly lower cortisol levels during the stress test (p = .03) and less cortisol response to stress. Compared with nondepressed subjects, depressed subjects also showed lower levels of respiratory sinus arrhythmia (RSATF) during the stress test (p = .02). Conclusions: In this sample, older depressed subjects with elevated risk for CVD exhibited a hypocortisol response to acute stress. This impaired cortisol response might contribute to chronic inflammation (as reflected in the elevated C-reactive proteins in depressed patients) and in other ways increase CVD risk. The reduced RSATF activity may also increase CVD risk in depressed patients through impaired autonomic nervous system response to cardiophysiological demands. ACTH = adrenocorticotropic hormone; ADH = antidiuretic hormone; ADMA = asymmetric dimethylarginine; ANS = autonomic nervous system; BMI = body mass index; BP = blood pressure; BRC = baroreflex control; CAD = coronary artery disease; CBT = cognitive behavioral therapy; CHD = coronary heart disease; CO = cardiac output; CON = nondepressed control; CPM = cycles per minute; CVD = cardiovascular disease; DBP = diastolic blood pressure; DISH = Depression Interview and Structured Hamilton; ECG = electrocardiogram; FMVD = flow-mediated vasodilation; HDL = high-density lipoprotein; HPA = hypothalamic–pituitary–adrenal axis; HR = heart rate; HRSD = Hamilton Rating Scale of Depression; HRV = heart rate variability; LDL = low-density lipoprotein; MDD = major depressive disorder; MI = myocardial infarction; NO = nitric oxide; PANAS = Positive and Negative Affect Schedule; pCO2 = partial pressure of carbon dioxide; PEP = preejection period; PSS = Perceived Stress Scale; RSA = respiratory sinus arrhythmia; RSATF = transfer function respiratory sinus arrhythmia; SBP = systolic blood pressure; SVR = systemic vascular resistance; TSST = Trier Social Stress Test; VLDL = very-low-density lipoprotein.
Systemic Injection of Kainic Acid Differently Affects LTP Magnitude Depending on its Epileptogenic Efficiency

Seizures have profound impact on synaptic function and plasticity. While kainic acid is a popular method to induce seizures and to potentially affect synaptic plasticity, it can also produce physiological-like oscillations and trigger some forms of long-term potentiation (LTP). Here, we examine whether induction of LTP is altered in hippocampal slices prepared from rats with different sensitivity to develop status epilepticus (SE) by systemic injection of kainic acid. Rats were treated with multiple low doses of kainic acid (5 mg/kg; i.p.) to develop SE in a majority of animals (72–85% rats). A group of rats were resistant to develop SE (15–28%) after several accumulated doses. Animals were subsequently tested using chronic recordings and object recognition tasks before brain slices were prepared for histological studies and to examine basic features of hippocampal synaptic function and plasticity, including input/output curves, paired-pulse facilitation and theta-burst induced LTP. Consistent with previous reports in kindling and pilocapine models, LTP was reduced in rats that developed SE after kainic acid injection. These animals exhibited signs of hippocampal sclerosis and developed spontaneous seizures. In contrast, resistant rats did not become epileptic and had no signs of cell loss and mossy fiber sprouting. In slices from resistant rats, theta-burst stimulation induced LTP of higher magnitude when compared with control and epileptic rats. Variations on LTP magnitude correlate with animals’ performance in a hippocampal-dependent spatial memory task. Our results suggest dissociable long-term effects of treatment with kainic acid on synaptic function and plasticity depending on its epileptogenic efficiency.
Load balancing and dynamic scaling of cache storage against zipfian workloads

We investigate near-optimal load balancing and auto-scaling solutions that can get the best delay performance while attaining high utilization in two-tier cloud storage systems. The first tier consists of a distributed cache composed of leased resources from a computing cloud (e.g., Amazon EC2) and the second tier consists of a persistent distributed storage (e.g., Amazon S3). At any point in time our solutions dynamically determine how many cache servers should be active as the incoming load, object popularities, and service rate of persistent storage are subject to change. We first present a load balancing solution for a given set of cache servers that can evenly distribute the load against workloads with an unknown Zipf distribution while keeping the overall cache hit ratios close to the maximum. Building on this load balancer, we then present our auto-scaling solution that uses the request backlogs in the caching tier to determine the number of active cache servers to be used in the next epoch. Via simulations, we show that the end-to-end design is quite effective in converging to the right amount of service capacity against the system dynamics.
Reality of auditory verbal hallucinations

Distortion of the sense of reality, actualized in delusions and hallucinations, is the key feature of psychosis but the underlying neuronal correlates remain largely unknown. We studied 11 highly functioning subjects with schizophrenia or schizoaffective disorder while they rated the reality of auditory verbal hallucinations (AVH) during functional magnetic resonance imaging (fMRI). The subjective reality of AVH correlated strongly and specifically with the hallucination-related activation strength of the inferior frontal gyri (IFG), including the Broca's language region. Furthermore, how real the hallucination that subjects experienced was depended on the hallucination-related coupling between the IFG, the ventral striatum, the auditory cortex, the right posterior temporal lobe, and the cingulate cortex. Our findings suggest that the subjective reality of AVH is related to motor mechanisms of speech comprehension, with contributions from sensory and salience-detection-related brain regions as well as circuitries related to self-monitoring and the experience of agency.
Structure vs. Language: Investigating the Multi-factors of Asymmetric Opinions on Online Social Interrelationship with a Case Study

Though current researches often study the properties of online social relationship from an objective view, we also need to understand individuals' subjective opinions on their interrelationships in social computing studies. Inspired by the theories from sociolinguistics, the latest work indicates that interactive language can reveal individuals' asymmetric opinions on their interrelationship. In this work, in order to explain the opinions' asymmetry on interrelationship with more latent factors, we extend the investigation from single relationship to the structural context in online social network. We analyze the correlation between interactive language features and the structural context of interrelationships. The structural context of vertex, edges and triangles in social network are considered. With statistical analysis on Enron email dataset, we find that individuals' opinions (measured by interactive language features) on their interrelationship are related to some of their important structural context in social network. This result can help us to understand and measure the individuals' opinions on their interrelationship with more intrinsic information.
The evolution of intrinsic reproductive isolation in the genus Cakile (Brassicaceae)

In theory, adaptive divergence can increase intrinsic post‐zygotic reproductive isolation (RI), either directly via selection on loci associated with RI, or indirectly via linkage of incompatibility loci with loci under selection. To test this hypothesis, we measured RI at five intrinsic post‐zygotic reproductive barriers between 18 taxa from the genera Cakile and Erucaria (Brassicaceae). Using a comparative framework, we tested whether the magnitude of RI was associated with genetic distance, geographic distance, ecological divergence and parental mating system. Early stages of post‐zygotic RI related to F1 viability (i.e. initial seed set) tended to be stronger than later stages related to F1 fecundity (i.e. flower number, fruit number). Mating system significantly influenced early stages of RI, such that RI was lowest when the mother was selfing and father was outcrossing, consistent with an imbalance between sink strength and resistance to provisioning. We found little evidence that adaptive divergence accelerates the evolution of intrinsic post‐zygotic RI, consistent with a nonecological model of evolution that predicts the nonlinear accumulation of RI and RI asymmetry with time (i.e. genetic distance), irrespective of adaptive divergence. Thus, although certain aspects of ecological divergence do not appear to have contributed strongly to the evolution of RI in this system, divergence in mating system actually reduced RI, suggesting that mating system evolution may play a significant role in speciation dynamics.