Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Heterogeneity of Bacteria: Evidence from Hot Composts by Culture-independent Analysis

The phylogenetic diversity of the bacteria in hot composting samples collected from three spatial locations was investigated by molecular tools in order to determine the influence of gradient effect on bacterial communities during the thermophilic phase of composting swine manure with rice straw. Total microbial DNA was extracted and bacterial near full-length 16S rRNA genes were subsequently amplified, cloned, restriction fragment length polymorphism-screened and sequenced. The superstratum sample had the highest microbial diversity among the three samples which was possibly related to the surrounding conditions of the sample resulting from the location. The results showed that the sequences related to Bacillus sp. were most common in the composts. In superstratum sample, 45 clones (33%) and 36 clones (27%) were affiliated with the Bacillus sp. and Clostridium sp. , respectively; 74 clones (58%) were affiliated with the Clostridium sp. in the middle-level sample; 52 clones (40%) and 29 clones (23%) were affiliated with the Clostridium sp. and Bacillus sp. in substrate sample, respectively. It indicated that the microbial diversity and community in the samples were different for each sampling site, and different locations of the same pile often contained distinct and different microbial communities.
AGGRO: Boosting STM Replication via Aggressively Optimistic Transaction Processing

Software Transactional Memories (STMs) are emerging as a potentially disruptive programming model. In this paper we are address the issue of how to enhance dependability of STM systems via replication. In particular we present AGGRO, an innovative Optimistic Atomic Broadcast-based (OAB) active replication protocol that aims at maximizing the overlap between communication and processing through a novel AGGRessively Optimistic concurrency control scheme. The key idea underlying AGGRO is to propagate dependencies across uncommitted transactions in a controlled manner, namely according to a serialization order compliant with the optimistic message delivery order provided by the OAB service. Another relevant distinguishing feature of AGGRO is of not requiring a-priori knowledge about read/write sets of transactions, but rather to detect and handle conflicts dynamically, i.e. as soon (and only if) they materialize. Based on a detailed simulation study we show the striking performance gains achievable by AGGRO (up to 6x increase of the maximum sustainable throughput, and 75% response time reduction) compared to literature approaches for active replication of transactional systems.
Science gateways made easy: the In‐VIGO approach

Science gateways require the easy enabling of legacy scientific applications on computing Grids and the generation of user‐friendly interfaces that hide the complexity of the Grid from the user. This paper presents the In‐VIGO approach to the creation and management of science gateways. First, we discuss the virtualization of machines, networks and data to facilitate the dynamic creation of secure execution environments that meet application requirements. Then we discuss the virtualization of applications, i.e. the execution on shared resources of multiple isolated application instances with customized behavior, in the context of In‐VIGO. A Virtual Application Service (VAS) architecture for automatically generating, customizing, deploying, and using virtual applications as Grid services is then described. Starting with a grammar‐based description of the command‐line syntax, the automated process generates the VAS description and the VAS implementation (code for application encapsulation and data binding) that is deployed and made available through a Web interface. A VAS can be customized on a per‐user basis by restricting the capabilities of the original application or by adding to it features such as parameter sweeping. This is a scalable approach to the integration of scientific applications as services into Grids and can be applied to any tool with an arbitrarily complex command‐line syntax. Copyright © 2006 John Wiley & Sons, Ltd.
Integrated Segmentation and Recognition of Hand-Printed Numerals

Neural network algorithms have proven useful for recognition of individual, segmented characters. However, their recognition accuracy has been limited by the accuracy of the underlying segmentation algorithm. Conventional, rule-based segmentation algorithms encounter difficulty if the characters are touching, broken, or noisy. The problem in these situations is that often one cannot properly segment a character until it is recognized yet one cannot properly recognize a character until it is segmented. We present here a neural network algorithm that simultaneously segments and recognizes in an integrated system. This algorithm has several novel features: it uses a supervised learning algorithm (backpropagation), but is able to take position-independent information as targets and self-organize the activities of the units in a competitive fashion to infer the positional information. We demonstrate this ability with overlapping handprinted numerals.
One Gate Diode-Connected Dual-Gate a-IGZO TFT Driven Pixel Circuit for Active Matrix Organic Light-Emitting Diode Displays

A dual-gate (DG) amorphous indium-gallium- zinc-oxide thin-film transistor (TFT)-driven pixel circuit for active-matrix organic light-emitting diode displays is presented. One gate of the DGs serves as a primary gate (PG) and the other as an auxiliary gate (AG). The threshold voltage (V<sub>TH</sub>) of the DG TFT under the PG operation is modulated by the AG bias voltage. The VTH variation (ΔV<sub>TH</sub>) is compensated with the AG and the drain diode-connected structure. The validity of the presented pixel circuit is experimentally verified. The measured current error rates are less than 3.2% at a ΔV<sub>TH</sub> of TFT = ±0.5 V and a ΔV<sub>TH</sub> of OLED = 0.5 V with the emission current ranging from 7 nA to 1.13 μA.
Combining approaches for solving satisfiability problems with qualitative preferences

The ability to effectively reason in the presence of qualitative preferences on literals or formulas is a central issue in Artificial Intelligence. In the last few years, two procedures have been presented in order to reason with propositional satisfiability SAT problems in the presence of additional, partially ordered qualitative preferences on literals or formulas: the first requires a modification of the branching heuristic of the SAT solver in order to guarantee that the first solution is optimal, while the second computes a sequence of solutions, each guaranteed to be better than the previous one. The two approaches have their own advantages and disadvantages and when compared on specific classes of instances --each having an empty partial order --the second seems to have superior performance.In this paper we show that the above two approaches for reasoning with qualitative preferences can be combined yielding a new effective procedure. In particular, in the new procedure we modify the branching heuristic --as in the first approach --by possibly changing the polarity of the returned literal, and then we continue the search --as in the second approach --looking for better solutions. We extended the experimental analysis conducted in previous papers by considering a wide variety of problems, having both an empty and a non-empty partial order: the results show that the new procedure performs better than the two previous approaches on average, and especially on the “hard” problems. As a preliminary result, we show that the framework of qualitative preferences on literals is more general and expressive than the framework on quantitative preferences.
Does environmental heat stress impact physical and technical match-play characteristics in football?

ABSTRACT Purpose: To examine the impact of environmental heat stress conditions on physical and technical football match-play characteristics. Method: Data from 42 matches of 9 outfields, professional football players were collected in temperatures ranging from 13°C to 37°C and relative humidity ranging from 11% to 83%. Individual player data were only included if a player had played a full match (>90+ min) and had completed at least one full match in each of the four available environmental heat stress risk conditions of low, moderate, high and excessive. Results: Significant effects were observed for run speed (p = .001), high speed run (p = .041), high intensity (p = .023) and explosive (p = .001) distance covered, with run speed and explosive distance significantly decreasing in excessive compared to low environmental heat stress conditions. Similarly, the number of balls lost (p = .002) significantly decreased in excessive compared to low climatic conditions. Total and sprint distances were unaffected. Conclusion: Excessive environmental conditions may impact physical and to some degree technical match-play characteristics. A rational may be due to professional players employing pacing strategies to modulate their physical exertion in an attempt to control thermal strain and physical fatigue.
Towards Automated Reputation and Brand Monitoring on the Web

The ever-increasing growth of the Web as principal provider of news and opinions makes it impossible for individuals to manually spot and analyze all information of particular importance for global large-scale corporations. Hence, automated means, identifying upcoming topics of utter relevance and monitoring the reputation of a brand as well as its competitors, are becoming indispensable. In this paper, we present a platform for analyzing Web data for such purposes, adopting different semantic perspectives and providing the market analyst with a flexible suite of instruments. We focus on two of these tools and outline their particular utility for research and exploration
Unsupervised WSD based on Automatically Retrieved Examples: The Importance of Bias

This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the “WordNet monosemous relatives” method to construct automatically a web corpus that we have used to train disambiguation systems. The corpus-building process has highlighted important factors, such as the distribution of senses (bias). The corpus has been used to train WSD algorithms that include supervised methods (combining automatic and manuallytagged examples), minimally supervised (requiring sense bias information from hand-tagged corpora), and fully unsupervised. These methods were tested on the Senseval-2 lexical sample test set, and compared successfully to other systems with minimum or no supervision.
Simultaneous immunolocalization of desmoglein 3 and IgG4 in oral pemphigus vulgaris: IgG4 predominant autoantibodies in its pathogenesis.

BACKGROUND Oral pemphigus vulgaris (PV), an autoimmune blistering disease, is mainly mediated by autoantibodies against desmoglein (Dsg) 3. However, no attention has been paid to IgG subclasses of the autoantibodies against Dsg3 in the diagnostic procedure for PV. Thus, our aim in this study was to investigate whether Dsg3 and any of IgG subclasses are immunohistochemically colocalized in tissue sections of PV oral mucosa. MATERIALS AND METHODS Serial sections cut from formalin-fixed paraffin blocks of biopsy specimens of 9 PV cases and those of normal buccal mucosa surgically removed for fibro-epithelial polyps were comparatively examined for immunohistochemical localizations for Dsg3, IgG4, and IgG. RESULTS Dsg3 was demonstrated in a dot-like pattern on the cell border and in the cytoplasm of the whole epithelial layer in both normal and PV specimens, while its staining was irregular among floating epithelial sheets of PV. IgG4 was also demonstrated in a punctuated fashion on the cell border among floating epithelial sheets, which was nearly identical to the immunohistochemical profile of Dsg3. In addition to being detected in the epithelial part, IgG4 signals were prominently localized in plasma cells scattered in the granulation tissue, where ratios of IgG4-positive (+) plasma cells to IgG+ cells were extraordinarily higher (mean 28%) than those in normal mucosa. DISCUSSION These findings confirmed for the first time that autoantibodies against Dsg3 are mainly composed of IgG4 in oral PV and that the combined immunohistochemistry for Dsg3 and IgG4 can be a valuable aid in confirming a histopathological diagnosis of PV.
Multi-Channel Features Spatio-Temporal Context Learning for Visual Tracking

Visual tracking is a challenging issue in surveillance, human–computer Interaction, and intelligent robotics, among others. Managing appearance changes of the target object, illumination changes, rotations, non-rigid deformations, partial or full occlusions, background clutter, fast motion, and so forth is generally difficult. Among the numerous existing trackers, the correlation-filter-based tracker can achieve appealing performance with a fast speed for fast Fourier transform. Motivated by this property, the spatio-temporal context (STC) learning algorithm was proposed with the consideration of the information from the context around the target, and this algorithm achieved good results. However, STC only utilizes the overall intensity information. In this paper, we propose a multi-channel features STC learning algorithm with an improved scale-adaptive scheme. Our algorithm integrates powerful features, including Histogram of Oriented Gradients and color naming, using kernel methods on the basis of the STC algorithm to further enhance the overall tracking performance. Extensive experimental results obtained from various benchmark data sets demonstrate that the proposed tracker is promising for various challenging scenarios and maintains real-time performance at an average speed of 78 frames/s. According to the test results, our algorithm outperforms the STC algorithm and achieves performance that is competitive with the state-of-the-art algorithms.
A migration-oriented partial adaptation architecture for IoT-empowered city platform as a service

Evolution of IoT-empowered city-scale platform leads to migration requirements. All successful IoT systems need to address migration of existing or external systems. The author discusses the challenges of phased migration of heterogeneous IoT systems. Then, the author presents approaches of migratable architecture. Finally, the author proposes a partial adaptation migration architecture to cope with the challenges. The mapping architecture can provide a framework of accommodating evolution of heterogeneous IoT systems.
Individual Variability and Test-Retest Reliability Revealed by Ten Repeated Resting-State Brain Scans over One Month

Individual differences in mind and behavior are believed to reflect the functional variability of the human brain. Due to the lack of a large-scale longitudinal dataset, the full landscape of variability within and between individual functional connectomes is largely unknown. We collected 300 resting-state functional magnetic resonance imaging (rfMRI) datasets from 30 healthy participants who were scanned every three days for one month. With these data, both intra- and inter-individual variability of six common rfMRI metrics, as well as their test-retest reliability, were estimated across multiple spatial scales. Global metrics were more dynamic than local regional metrics. Cognitive components involving working memory, inhibition, attention, language and related neural networks exhibited high intra-individual variability. In contrast, inter-individual variability demonstrated a more complex picture across the multiple scales of metrics. Limbic, default, frontoparietal and visual networks and their related cognitive components were more differentiable than somatomotor and attention networks across the participants. Analyzing both intra- and inter-individual variability revealed a set of high-resolution maps on test-retest reliability of the multi-scale connectomic metrics. These findings represent the first collection of individual differences in multi-scale and multi-metric characterization of the human functional connectomes in-vivo, serving as normal references for the field to guide the use of common functional metrics in rfMRI-based applications.
Feasting at Poverty Point with Poverty Point Objects

ABSTRACT Attempts to account for the impressive and unusual archaeological record of the World Heritage site of Poverty Point have often faltered. The vast and diverse set of artifacts, the spectacular and well-designed earthworks, and the millions of baked-clay objects known as Poverty Point Objects are all distinctive and anomalous features of the site. This paper argues that the archaeological record of Poverty Point can best be explained as the product of periodic, ritualized feasting events. Drawing on diverse archaeological and anthropological studies of feasting I demonstrate that it is a useful research framework for understanding the site’s content because many of the archaeological signatures of feasting are present at Poverty Point. I argue furthermore that Poverty Point Objects were an integral component of this culture of feasting and offer hypotheses on their role in the feasts.
Is Generalized Maternal Optimism or Pessimism During Pregnancy Associated with Unplanned Cesarean Section Deliveries in China?

This research examines whether maternal optimism/pessimism is associated with unplanned Cesarean section deliveries in China. If so, does the association remain after controlling for clinical factors associated with C-sections? A sample of 227 mostly primiparous women in the third trimester of pregnancy was surveyed in a large tertiary care hospital in Beijing, China. Post-delivery data were collected from medical records. In bivariate analysis, both optimism and pessimism were related to unplanned c-section. However, when optimism and pessimism were entered into a regression model together, optimism was no longer statistically significant. Pessimism remained significant, even when adjusting for clinical factors such as previous abortion, previous miscarriage, pregnancy complications, infant gestational age, infant birthweight, labor duration, birth complications, and self-rated difficulty of the pregnancy. This research suggests that maternal mindset during pregnancy has a role in mode of delivery. However, more research is needed to elucidate potential causal pathways and test potential interventions.
Inter‐annual and multi‐decadal variability of monsoon season rainfall in central Thailand during the period 1804–1999, as inferred from tree ring oxygen isotopes

Long‐term records of precipitation in Thailand are necessary to evaluate the robustness of the relationship between El Niño–Southern Oscillation (ENSO) and rainfall. This study presents a tree ring‐cellulose oxygen isotope (δ18O) record, based on Pinus merkusii, for the period 1804–1999 in Thailand. Response and spatial correlation analyses reveal that tree ring δ18O is significantly correlated with regional monsoon season (May–October) precipitation. Tree ring δ18O, which explains 50.1% of the variability in regional precipitation, was employed to reconstruct monsoon season rainfall back to 1804. Relatively wet periods occurred in 1809–1821, 1876–1882, 1897–1908, and 1944–1975, while the periods 1825–1850, 1913–1925, and 1979–1997 were relatively dry. During the periods 1854–1930 and 1970–1999, inter‐annual variability of precipitation was modulated by the ENSO. In contrast, the absence of this relationship between 1930 and 1970 might relate to the reduced variance of ENSO.
Soft Margin Consistency Based Scalable Multi-View Maximum Entropy Discrimination

Multi-view learning receives increasing interest in recent years to analyze complex data. Lately, multiview maximum entropy discrimination (MVMED) and alternative MVMED (AMVMED) were proposed as extensions of maximum entropy discrimination (MED) to the multi-view learning setting, which use the hard margin consistency principle that enforces two view margins to be the same. In this paper, we propose soft margin consistency based multi-view MED (SMVMED) achieving margin consistency in a less strict way, which minimizes the relative entropy between the posteriors of two view margins. With a trade-off parameter balancing large margin and margin consistency, SMVMED is more flexible. We also propose a sequential minimal optimization (SMO) algorithm to efficiently train SMVMED and make it scalable to large datasets. We evaluate the performance of SMVMED on multiple real-world datasets and get encouraging results.
ColdBus: A Near-Optimal Power Efficient Optical Bus

High static power dissipation is one of the largest hurdles in the widespread adoption of on-chip optical networks. There are numerous proposals in literature for the reduction of static power by predicting the activity in future time intervals, and then powering off the laser, and also by sharing optical bandwidth. We propose a novel scheme called ColdBus in this paper that introduces a new method of predicting the optical NoC traffic using program counter addresses, moreover, we then propose novel structures and predictors for handling mispredictions. These units allow optical transmitters to share bandwidth between them while simultaneously minimizing static power. We show that ColdBus consumes 4.1X less optical power than other state of the art proposals. It additionally has a speedup of 3.1%, and improves ED2 by 18% for a suite of Splash, Parsec, and Parboil benchmarks.
Decreased Erythrocyte NA+,K+-ATPase Activity and Increased Plasma TBARS in Prehypertensive Patients

The essential hypertension has been associated with membrane cell damage. The aim of the present study is investigate the relationship between erythrocyte Na+,K+-ATPase and lipoperoxidation in prehypertensive patients compared to normotensive status. The present study involved the prehypertensive patients (systolic: 136 ± 7 mmHg; diastolic: 86.8 ± 6.3 mmHg; n = 8) and healthy men with normal blood pressure (systolic: 110 ± 6.4 mmHg; diastolic: 76.1 ± 4.2 mmHg; n = 8) who were matched for age (35 ± 4 years old). The venous blood samples of antecubital vein (5 mL) were collected into a tube containing sodium heparin as anticoagulant (1000 UI), and erythrocyte ghosts were prepared for quantifying Na+,K+-ATPase activity. The extent of the thiobarbituric acid reactive substances (TBARS) was determined in plasma. The statistical analysis was carried out by Student's t-test and Pearson's correlation coefficient. A P < 0.05 was considered significant. The Na+,K+-ATPase activity was lower in prehypertensive patients compared with normotensive subjects (4.9 versus 8.0 nmol Pi/mg protein/min; P < 0.05). The Na+,K+-ATPase activity correlated negatively with TBARS content (r = −0.6; P < 0.05) and diastolic blood pressure (r = −0.84; P < 0.05). The present study suggests that Na+,K+-ATPase activity reduction and elevation of the TBARS content may underlie the pathophysiological aspects linked to the prehypertensive status.