Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic heap sizing: taking real memory into account

Heap size has a huge impact on the performance of garbage collected applications. A heap that barely meets the application's needs causes excessive GC overhead, while a heap that exceeds physical memory induces paging. Choosing the best heap size <i>a priori</i> is impossible in multiprogrammed environments, where physical memory allocations to processes change constantly. We present an automatic heap-sizing algorithm applicable to different garbage collectors with only modest changes. It relies on an analytical model and on detailed information from the virtual memory manager. The model characterizes the relation between collection algorithm, heap size, and footprint. The virtual memory manager tracks recent reference behavior, reporting the current footprint and allocation to the collector. The collector uses those values as inputs to its model to compute a heap size that maximizes throughput while minimizing paging. We show that our adaptive heap sizing algorithm can substantially reduce running time over fixed-sized heaps.
From lecithotrophy to planktotrophy: ontogeny of larval feeding in the Amazon River prawn Macrobrachium amazonicum

During downstream transport from rivers to estuaries, early larval stages of the Amazon River prawn Macrobrachium amazonicum (Heller 1862) are likely exposed to planktonic food limita- tion. In the laboratory, we studied the effects of presence or absence of food on larval survival, moult- ing and biomass (dry mass, and content of carbon, hydrogen and nitrogen). Unfed larvae developed successfully from hatching of the Zoea I (Z I) to the third zoeal stage (Z III). Complete absence of star- vation effects indicated obligatory lecithotrophy in Z I, while significantly delayed moulting and reduced biomass in unfed Z II proved that this stage is facultatively lecithotrophic. Although unfed Z III did not develop any further (obligatory planktotrophy), they still showed a high endotrophic potential, surviving for up to another 10 d (in total 2 wk from hatching), and utilizing about two-thirds of their initial biomass. Dramatically decreasing C:N ratios in unfed larvae suggest an almost com- plete metabolic degradation of internal lipid stores (visible as fat droplets in the hepatopancreas region), but little protein mobilization. Larvae obtained from 2 different females differed significantly in biomass at hatching and, correspondingly, also in maximum survival time, delay of moulting to the Z III and average rates of biomass utilization. In conclusion, the early larval stages of M. amazonicum depend very little on food, shifting from completely non-feeding behaviour (Z I) through facultative lecithotrophy (Z II), to planktotrophy (later stages). This ontogenetic pattern may be an adaptation to initial food limitation associated with larval export from limnic to estuarine environments.
Recommending Emergent Teams

To build successful complex software systems, developers must collaborate with each other to solve issues. To facilitate this collaboration, specialized tools, such as chat and screen sharing, are being integrated into development environments. Currently, these tools require a developer to maintain a list of other developers with whom they may wish to communicate and to determine who within this list has expertise for a specific situation. For large, dynamic projects, like several successful open-source projects, these requirements place an unreasonable burden on the developer. In this paper, we show how the structure of a team emerges from how developers change software artifacts. We introduce the emergent expertise locator (EEL) that uses emergent team information to propose experts to a developer within their development environment as the developer works. We found that EEL produces, on average, results with higher precision and higher recall than an existing heuristic for expertise recommendation.
Risk of Cancer Among Firefighters: A Quantitative Review of Selected Malignancies

Using the fixed-effect model, the author quantitatively estimated the risks of cancers of the colon, bladder, kidneys, and brain as well as non-Hodgkin's lymphoma and leukemia among fire-fighters. The risk of these six cancers was not markedly elevated when cohort mortality studies were considered. When all mortality studies were considered, however, there was a mild increase in risk for kidney cancer and non-Hodgkin's lymphoma, with a summary relative risk (sumRR) of 1.22 (95% confidence interval [CI] = 1.02-1.43) and 1.40 (95% CI = 1.20-1.60), respectively. A subcohort analysis based on duration of employment revealed that firefighters with 30 or more years of employment had a significantly increased mortality risk for colon cancer, sumRR of 1.51 (95% CI = 1.05-2.11); kidney cancer, sumRR of 6.25 (95% CI = 1.70-16.00); brain cancer, sumRR of 2.53 (95% CI = 1.27-7.07); and leukemia, sumRR of 2.87 (95% CI = 1.43-5.14). After firefighters had 40 or more years of employment, their risk of mortality was significantly increased for colon cancer, sumRR of 4.71 (95% CI = 2.03-9.27); kidney cancer, sumRR of 36.12 (95% CI = 4.03-120.42); and bladder cancer, sumRR of 5.7 (95% CI = 1.56-14.63). The risk for non-Hodgkin's lymphoma was elevated but not significantly so among firefighters with 20 or more years of employment, with sumRR of 1.72 (95% CI = 0.90-3.31). Kidney cancer risk was significantly elevated as early as the second decade of employment.
How to Set Focal Categories for Brief Implicit Association Test? “Good” Is Good, “Bad” Is Not So Good

Three studies were conducted to examine the validity of the four versions of BIATs that are supposed to measure the same construct but differ in shared focal category. Study 1 investigated the criterion validity of four BIATs measuring attitudes toward flower versus insect. Study 2 examined the experimental sensitivity of four BIATs by considering attitudes toward induced ingroup versus outgroup. Study 3 examined the predictive power of the four BIATs by investigating attitudes toward the commercial beverages Coke versus Sprite. The findings suggested that for the two attributes “good” and “bad,” “good” rather than “bad” proved to be good as a shared focal category; for two targets, so long as they clearly differed in goodness or valence, the “good” rather than “bad” target emerged as good for a shared focal category. Beyond this case, either target worked well. These findings may facilitate the understanding of the BIAT and its future applications.
Adaptation strategies to climate change in marine systems

The world's oceans are highly impacted by climate change and other human pressures, with significant implications for marine ecosystems and the livelihoods that they support. Adaptation for both natural and human systems is increasingly important as a coping strategy due to the rate and scale of ongoing and potential future change. Here, we conduct a review of literature concerning specific case studies of adaptation in marine systems, and discuss associated characteristics and influencing factors, including drivers, strategy, timeline, costs, and limitations. We found ample evidence in the literature that shows that marine species are adapting to climate change through shifting distributions and timing of biological events, while evidence for adaptation through evolutionary processes is limited. For human systems, existing studies focus on frameworks and principles of adaptation planning, but examples of implemented adaptation actions and evaluation of outcomes are scarce. These findings highlight potentially useful strategies given specific social–ecological contexts, as well as key barriers and specific information gaps requiring further research and actions.
Optimal fuzzy control to optimise energy consumption in distillation columns

Abstract Distillation columns constitute a significant fraction of the capital invested in the refineries around the world; their control requires a major part of the total operating cost of chemical processes, if the used strategy is not adequate. This article presents the application of optimal fuzzy control to reduce the energy consumption of a Benzene-Toluene distillation column. This method is based on the determination of the specific values of the fuzzy controller parameters such that certain performance criterion is minimised. Results of a simulation study are presented showing the potential improvement offered by this method.
Topical Categorization of Credible Microblog Content

Microblogs are often considered to be useful sources of information. Increasing popularity of micro blogging sites like twitter, is making them a viable source of real-time news with a huge potential to replace news sites. Credibility of such microblogs is of concern when they are to be considered as sources of news. This paper details on an approach to examine microblogs like tweets, determine their credibility and categorize them under different news topics. This approach builds upon the previous work done in microblog credibility determination and rating. This paper works with twitter as test data source. The proposed novel approach can be extended to any other microblogs also.
Nitrogen to phosphorus ratio of plant biomass versus soil solution in a tropical pioneer tree, Ficus insipida

It is commonly assumed that the nitrogen to phosphorus (N:P) ratio of a terrestrial plant reflects the relative availability of N and P in the soil in which the plant grows. Here, this was assessed for a tropical pioneer tree, Ficus insipida. Seedlings were grown in sand and irrigated with nutrient solutions containing N:P ratios ranging from <1 to >100. The experimental design further allowed investigation of physiological responses to N and P availability. Homeostatic control over N:P ratios was stronger in leaves than in stems or roots, suggesting that N:P ratios of stems and roots are more sensitive indicators of the relative availability of N and P at a site than N:P ratios of leaves. The leaf N:P ratio at which the largest plant dry mass and highest photosynthetic rates were achieved was ∼11, whereas the corresponding whole-plant N:P ratio was ∼6. Plant P concentration varied as a function of transpiration rate at constant nutrient solution P concentration, possibly due to transpiration-induced variation in the mass flow of P to root surfaces. The transpiration rate varied in response to nutrient solution N concentration, but not to nutrient solution P concentration, demonstrating nutritional control over transpiration by N but not P. Water-use efficiency varied as a function of N availability, but not as a function of P availability.
Spread Spectrum Ultrasonic Positioning System

Many mobile applications can be greatly enhanced when provided with the locations of people and devices. Indoor ultrasonic positioning system provide fine-grained position data for such applications. This paper describes an ultrasonic tagging system developed for monitoring the location of a moving target. Use of spread spectrum in ultrasonic location system allows the system to work at a noisy environment. In the same time it solves the problem of signal collisions when more than one transmitter transmit at the same time. Test results demonstrate that the system is able to locate the position of a moving target with high accuracy.
Dynamic Item Recommendation by Topic Modeling for Social Networks

The need to identify an approach that recommends items that match users' preferences within social networks has grown in tandem with the increasing number of items appearing within these networks. This research presents a novel technique for item recommendation within social networks that matches user and group interests over time. Users often tag items in social networks with words and phrases that reflect their preferred "vocabulary. " As such, these tags provide succinct descriptions of the resource, implicitly reveal user preferences, and, as the tag vocabulary of users tends to change over time, reflect the dynamics of user preferences. Based on evaluation of user and group interests over time, we present a recommendation system employing a modified latent Dirichlet allocation (LDA) model in which users and tags associated with an item are represented and clustered by topics, and the topic-based representation is combined with the item's timestamp to show time-based topic distribution. By representing users via topics, the model can cluster users to reveal the group interests. Based on this model, we developed a recommendation system that reflects user as well as group interests in a dynamic manner that accounts for time, allowing it to perform in a manner superior to that of static recommendation systems in terms of precision rate.
catena-Poly[[diaquadibromidomanganese(III)]-μ-pyridine-2-carboxylato]

The asymmetric unit of the title compound, [MnBr2(C6H4NO2)(H2O)2]n, contains one monomeric unit of the neutral linear coordination polymer. The Mn3+ ions are bridged by anionic pyridine-2-carboxylate (pic) ligands, thereby forming a chain-like structure along the c axis, and are six-coordinated in a distorted octahedral environment by two O atoms of the two different carboxylate groups, two O atoms of two water molecules and two Br atoms. The complex displays intermolecular O—H⋯Br, O—H⋯N, O—H⋯O, C—H⋯O and C—H⋯Br hydrogen bonding. There may also be intermolecular π–π interactions between adjacent pyridine rings, with a centroid–centroid distance of 3.993 (8) Å.
MODELING ROBOT BEHAVIORS WITH HYBRID AUTOMATA

The problem of designing behaviours for mobile ro bots employed in an active surveillance system is considered. The mobile robots are mo delled using differential inclusions and the behaviors are synthesised from viability sets . A basic hybrid automaton is proposed for the control of all designed behaviors. A compositi n rule is presented for the mixing of different behaviors. The main advantage of the presented approach is that behaviors are obtained by specifying regions in the environment. This is u sef l in surveillance, where the location of intruders is not known precisely. Another advan tage is that the same framework is used to control each of the available behaviors. Conseque ntly, the behaviors can be used as basic building blocks in general robot control architectur es. A set of experimental simulations where conducted to evaluate the proposed design approach an d t e results are also presented.
A Medium-Grained Algorithm for Sparse Tensor Factorization

Modeling multi-way data can be accomplished using tensors, which are data structures indexed along three or more dimensions. Tensors are increasingly used to analyze extremely large and sparse multi-way datasets in life sciences, engineering, and business. The canonical polyadic decomposition (CPD) is a popular tensor factorization for discovering latent features and is most commonly found via the method of alternating least squares (CPD-ALS). The computational time and memory required to compute CPD limits the size and dimensionality of the tensors that can be solved on a typical workstation, making distributed solution approaches the only viable option. Most methods for distributed-memory systems have focused on distributing the tensor in a coarse-grained, one-dimensional fashion that prohibitively requires the dense matrix factors to be fully replicated on each node. Recent work overcomes this limitation by using a fine-grained decomposition of the tensor nonzeros, at the cost of computationally expensive hypergraph partitioning. To that effect, we present a medium-grained decomposition that avoids complete factor replication and communication, while eliminating the need for expensive pre-processing steps. We use a hybrid MPI+OpenMP implementation that exploits multi-core architectures with a low memory footprint. We theoretically analyze the scalability of the coarse-, medium-, and fine-grained decompositions and experimentally compare them across a variety of datasets. Experiments show that the medium-grained decomposition reduces communication volume by 36-90% compared to the coarse-grained decomposition, is 41-76x faster than a state-of-the-art MPI code, and is 1.5-5.0x faster than the fine-grained decomposition with 1024 cores.
A Phonemic Corpus of Polish Child-Directed Speech

Recent advances in modeling early language acquisition are due not only to the development of machine-learning techniques, but also to the increasing availability of data on child language and child-adult interaction. In the absence of recordings of child-directed speech, or when models explicitly require such a representation for training data, phonemic transcriptions are commonly used as input data. We present a novel (and to our knowledge, the first) phonemic corpus of Polish child-directed speech. It is derived from the Weist corpus of Polish, freely available from the seminal CHILDES database. For the sake of reproducibility, and to exemplify the typical trade-off between ecological validity and sample size, we report all preprocessing operations and transcription guidelines. Contributed linguistic resources include updated CHAT-formatted transcripts with phonemic transcriptions in a novel phonology tier, as well as by-product data, such as a phonemic lexicon of Polish. All resources are distributed under the LGPL-LR license.
Grain Growth Simulation Using Cellular Automata

It is well known that controlling the microstructure of most industrial materials is the key to control its mechanical and physical properties. In particular grain growth is very important phenomenon in material science. However, it is very difficult to examine the dynamic solidification microstructure evolution at high temperatures or during deformation processes. Computer simulations have been used as an effective solution for that difficulty. Cellular Automaton (CA) is one of the techniques that have been used to simulate the evolution of grain growth. In this study 2D grain growth simulations of Al-1%Mg alloy was simulated using CA model based on different transition principles. The first is based on low energy principle. In this method the changes of boundary energy value is compared for each cell and then choosing the one that can minimize the energy system to the largest extent. The second method is based on changes of thermal energy that is computed for each grain boundary. The transition only occurs at the highest energy value. The third method is based on starting with a number of random distributed nucleuses within the simulation area with different orientations. At each CA steps these nucleuses will grow into a grain without effecting in the other grains. The morphology and grain kinetics are studied and discussed for each case.
Automatic summarization of broadcast news using structural features

We present a method for summarizing broadcast news that is not affected by word errors in an automatic speech recognition transcription, using information about the structure of the news program. We construct a directed graphical model to represent the probability distribution and dependencies among the structural features which we train by ﬁnding the values of parameters of the conditional probability tables. We then rank segments of the test set and extract the highest ranked ones as a summary. We present the procedure and preliminary test results.
Candida glabrata drug:H+ antiporter CgTpo3 (ORF CAGL0I10384g): role in azole drug resistance and polyamine homeostasis.

OBJECTIVES The ability of opportunistic pathogenic Candida species to persist and invade specific niches in the human host depends on their resistance to natural growth inhibitors and antifungal therapy. This work describes the role of the Candida glabrata drug:H(+) antiporter CgTpo3 (ORF CAGL0I10384g) in this context. METHODS Deletion and cloning of CgTPO3 was achieved using molecular biology tools. C. glabrata strain susceptibility was assayed based on growth in liquid and solid media and through MIC determination. Radiolabelled compound accumulation or HPLC were used for the assessment of the role of CgTpo3 as a drug or polyamine transporter. Quantitative RT-PCR was used for expression analysis. RESULTS CgTpo3 was found to confer resistance to azole drugs in C. glabrata. This protein was found to be localized to the plasma membrane and to decrease the intracellular accumulation of [(3)H]clotrimazole, playing a direct role in its extrusion from pre-loaded C. glabrata cells. CgTPO3 was further found to confer resistance to spermine, complementing the susceptibility phenotypes exhibited by the deletion of its Saccharomyces cerevisiae homologue, TPO3. In spermine-stressed C. glabrata cells, CgTPO3 is transcriptionally activated in a CgPdr1-dependent manner, contributing to a decrease in the intracellular concentration of this polyamine. Clotrimazole exposure was found to lead to the intracellular accumulation of spermine, and pre-exposure to this polyamine was found consistently to lead to increased clotrimazole resistance. CONCLUSIONS Altogether, these results point to a significant role for CgTpo3 in azole drug resistance and in the tolerance to high polyamine concentrations, such as those found in the urogenital tract.
Use of the MagNA Pure LC Automated Nucleic Acid Extraction System followed by Real-Time Reverse Transcription-PCR for Ultrasensitive Quantitation of Hepatitis C Virus RNA

ABSTRACT Hepatitis C virus (HCV) infection is an increasing health problem worldwide. Quantitative assays for HCV viral load are valuable in predicting response to therapy and for following treatment efficacy. Unfortunately, most quantitative tests for HCV RNA are limited by poor sensitivity. We have developed a convenient, highly sensitive real-time reverse transcription-PCR assay for HCV RNA. The assay amplifies a portion of the 5′ untranslated region of HCV, which is then quantitated using the TaqMan 7700 detection system. Extraction of viral RNA for our assay is fully automated with the MagNA Pure LC extraction system (Roche). Our assay has a 100% detection rate for samples containing 50 IU of HCV RNA/ml and is linear up to viral loads of at least 109 IU/ml. The assay detects genotypes 1a, 2a, and 3a with equal efficiency. Quantitative results by our assay correlate well with HCV viral load as determined by the Bayer VERSANT HCV RNA 3.0 bDNA assay. In clinical use, our assay is highly reproducible, with high and low control specimens showing a coefficient of variation for the logarithmic result of 2.8 and 7.0%, respectively. The combination of reproducibility, extreme sensitivity, and ease of performance makes this assay an attractive option for routine HCV viral load testing.
A co-training approach to automatic face recognition

Semi-supervised face recognition using both labelled and unlabelled data has received considerable interest in recent years. Co-training is one of the most well-known semi-supervised learning methods, but its application in face recognition almost remains unexplored because its assumption of conditional independence can be rarely satisfied between two facial features. However, even if two facial features are not completely independent, their different characteristics produce a so-called “classification margin” between two classifiers based on them, and hence there is the possibility of mutual training. In this paper, we report a semi-supervised face recognition algorithm which applies co-training on two classifiers based on Linear Discriminant Analysis (LDA) and Local Binary Patterns (LBP) features respectively. Experimental results show not only that the proposed co-training algorithm significantly improves the recognition accuracy over supervised methods using only labelled training data, but also demonstrates the superiority of co-training over self-training methods which only use one facial feature.