Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced survival associated with precopulatory mate guarding in male Asellus aquaticus (Isopoda)

Precopulatory mate-guarding in aquatic crustaceans is known to have immediate costs for the guarding male. The extent to which guarding behavior may reduce future reproductive opportunities, however, is less established. We examined the survival and antennae length, suggested to be important in detecting receptive females, in male freshwater isopods (Asellus aquaticus) collected paired or unpaired. Antennae length to body size relationships suggested that large, paired males had broken antennae more commonly than large, unpaired males. Moreover, broken antennae seem to be associated with increased mortality. Males collected paired had lower survival than males collected unpaired, and this reduction in survival was greatest in larger individuals. In pairing trials, males usually attempted pair formation regardless of their size, female size, or previous pairing status. Our results suggest that some costs associated with male guarding behavior may extend beyond the actual guarding episode, though the consequences for mating decisions remain to be determined.
An Acoustic Study of Telephone Speaking Style in Brazilian Portuguese

This paper presents an acoustic analysis of the telephone speaking style in a Brazilian Portuguese corpus. The corpus contains 80 recordings from 20 speakers (10 male and 10 female) in two non-simultaneous conditions: face-to-face (non-mediated speaking style) and via mobile phone (telephone speaking style) and were recorded in silent and noisy environments. The acoustic analysis is divided considering global and local parameters, which are tested with respect to their correlation with condition (face-to-face, mobile phone), environment (silent, noisy) and speakers’ gender (male, female). For global parameters, spectral emphasis and F 0 -peak production rate in noisy environment tend to be higher in comparison with their values in silent environment. For local parameters, the use of mobile phone in noisy environments causes an increase of the F 0 -median. The F 0 standard-deviation is higher in this condition when compared to face-to-face condition. Concerning the differences between genders, F 0 -median of male speakers tends to be higher in mobile condition when in noisy environments. Even though females’ values for F 0 standard-deviation are higher in each recording condition than males’, males’ values for this parameter differ more across face-to-face vs. mobile phone conditions if compared to women’s.
The role of H-2 linked genes in helper T-cell function. IV. Importance of T-cell genotype and host environment in I-region and Ir gene expression

We have studied the properties of helper T cells specific for sheep erythrocytes (SRBC), keyhole limpet hemocyanin (KLH), or poly-L- (Tyr,Glu)-poly-DL-Ala-poly-L-Lys [(T,G)-A--L]. These T cells differentiated and were primed in vivo in irradiation chimeras constructed of various combinations of F1 and parental bone marrow donors and irradiated recipients. Primed T cells were then tested for helper activity in the in vitro response of B cells and macrophages (Mphi) of parental or F1 origin to the hapten trinitrophenol coupled to the priming antigen. When testing either SRBC or KLH-specific T cells of parental H-2 type which had differentiated in F1 hosts, we found that they cooperated equally well with B cells and Mphi of either parental H-2 type. On the other hand, when testing F1 T cells which had differentiated in parental hosts, we found that they cooperated well only with B cells and Mphi which had the K-IA region type of the parental host. In similar experiments we found that (T,G)-A--L-specific T cells of low responder H-2 type which had differentiated in (high responder X low responder) F1 hosts induced high responses in high responder B cells and Mphi (T,G)-A--L-specific F1 T cells which differentiated in high responder but not those which differentiated in low responder hosts induced high responses in high responder B cells and Mphi. Low responder B cells and Mphi yielded low responses in all cases regardless of the source of (T,G)-A--L-specific T cells with what they were tested. Our results support the conclusion that I-region and Ir genes function via their expression in B cells and Mphi and in the host environment during helper T-cell differentiation, but not, at least under the conditions of these experiments, via their expression in the helper T cell itself. These findings place constraints upon models which attempt to explain the apparent dual recognition of antigen and I-region gene products by helper T cells.
Genomics of Actinobacteria: Tracing the Evolutionary History of an Ancient Phylum

SUMMARY Actinobacteria constitute one of the largest phyla among Bacteria and represent gram-positive bacteria with a high G+C content in their DNA. This bacterial group includes microorganisms exhibiting a wide spectrum of morphologies, from coccoid to fragmenting hyphal forms, as well as possessing highly variable physiological and metabolic properties. Furthermore, Actinobacteria members have adopted different lifestyles, and can be pathogens (e.g., Corynebacterium, Mycobacterium, Nocardia, Tropheryma, and Propionibacterium), soil inhabitants (Streptomyces), plant commensals (Leifsonia), or gastrointestinal commensals (Bifidobacterium). The divergence of Actinobacteria from other bacteria is ancient, making it impossible to identify the phylogenetically closest bacterial group to Actinobacteria. Genome sequence analysis has revolutionized every aspect of bacterial biology by enhancing the understanding of the genetics, physiology, and evolutionary development of bacteria. Various actinobacterial genomes have been sequenced, revealing a wide genomic heterogeneity probably as a reflection of their biodiversity. This review provides an account of the recent explosion of actinobacterial genomics data and an attempt to place this in a biological and evolutionary context.
Semi-Supervised Fuzzy Clustering with Feature Discrimination

Semi-supervised clustering algorithms are increasingly employed for discovering hidden structure in data with partially labelled patterns. In order to make the clustering approach useful and acceptable to users, the information provided must be simple, natural and limited in number. To improve recognition capability, we apply an effective feature enhancement procedure to the entire data-set to obtain a single set of features or weights by weighting and discriminating the information provided by the user. By taking pairwise constraints into account, we propose a semi-supervised fuzzy clustering algorithm with feature discrimination (SFFD) incorporating a fully adaptive distance function. Experiments on several standard benchmark data sets demonstrate the effectiveness of the proposed method.
An In-memory-Computing DNN Achieving 700 TOPS/W and 6 TOPS/mm2 in 130-nm CMOS

Deep neural networks (DNNs) are increasingly popular in machine learning and have achieved the state-of-the-art performance in a range of tasks. Typically, the best results are achieved using a large amount of training data and large models, which make both training and inference complex. While GPUs are used in many applications for the parallel computing they provide, lower energy platforms have the potential to enable a range of new applications. A trend being observed is the ability to reduce the precision of weights and activations, with previous research showing that in some cases, weights and activations can be binarized [i.e., binarized neural networks (BNNs)], significantly reducing the model size. Exploiting this toward reduced compute energy and reduced data-movement energy, we demonstrate the BNN mapped to a previously presented in-memory-computing architecture, where binarized weights are stored in a standard 6T SRAM bit cell and computations are performed via an analog operation. Using a reduced size BNN, chosen to fit on the CMOS prototype (in 130 nm), MNIST classification is achieved with only 0.4% accuracy degradation (from 94%), but at $26\times $ lower energy compared to a digital approach implementing the same network. The system reaches over 700-TOPS/W energy efficiency and 6-TOPS/mm2 throughput.
The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems

Social bookmarking systems have established themselves as an important part in today’s Web. In such systems, tag recommender systems support users during the posting of a resource by suggesting suitable tags. Tag recommender algorithms have often been evaluated in offline benchmarking experiments. Yet, the particular setup of such experiments has rarely been analyzed. In particular, since the recommendation quality usually suffers from difficulties such as the sparsity of the data or the cold-start problem for new resources or users, datasets have often been pruned to so-called cores (specific subsets of the original datasets), without much consideration of the implications on the benchmarking results. In this article, we generalize the notion of a core by introducing the new notion of a set-core, which is independent of any graph structure, to overcome a structural drawback in the previous constructions of cores on tagging data. We show that problems caused by some types of cores can be eliminated using set-cores. Further, we present a thorough analysis of tag recommender benchmarking setups using cores. To that end, we conduct a large-scale experiment on four real-world datasets, in which we analyze the influence of different cores on the evaluation of recommendation algorithms. We can show that the results of the comparison of different recommendation approaches depends on the selection of core type and level. For the benchmarking of tag recommender algorithms, our results suggest that the evaluation must be set up more carefully and should not be based on one arbitrarily chosen core type and level.
Experimental and finite difference modelling of borehole mach waves

In crosshole tomography, the radiation pattern of the source has a large influence on the observed wavefield. Meredith et al . (1991) showed how the Mach wave, generated by the tube wave in a soft formation when its velocity is high than the shear wave velocity, can produce a large arrival in the receiver borehole and hide the direct shear wave arrival. In this paper we studied the problem of seismic source radiation from a borehole into a soft formation using laboratory scaled borehole models and the finite differente method.
StopIt: Mitigating DoS Flooding Attacks from Multi-Million Botnets Technical Report 08-05

This paper presents the design and implementation of a ﬁlter-based DoS defense system (StopIt) and a comparison study on the effectiveness of ﬁlters and capabilities. Central to the StopIt design is a novel closed-control , open-service architecture: any receiver can use StopIt to block the undesired trafﬁc it receives, yet the design is robust to various strategic attacks from millions of bots, including ﬁlter exhaustion attacks and bandwidth ﬂooding attacks that aim to disrupt the timely installation of ﬁlters. Our evaluation shows that StopIt can block the attack trafﬁc from a few millions of attackers within tens of minutes with bounded router memory. We compare StopIt with existing ﬁlter-based and capability-based DoS defense systems under simulated DoS attacks of various types and scales. Our results show that StopIt outperforms existing ﬁlter-based systems, and can prevent legitimate communications from being disrupted by various DoS ﬂooding attacks. It also out-performs capability-based systems in most attack scenarios, but a capability-based system is more effective in a type of attack that the attack trafﬁc does not reach a victim, but congests a link shared by the victim. These results suggest that both ﬁlters and capabilities are highly effective DoS defense mechanisms, but neither is more effective than the other in all types of DoS attacks.
Text Mining and Natural Language Processing Approaches for Automatic Categorization of Lay Requests to Web-Based Expert Forums

Background Both healthy and sick people increasingly use electronic media to obtain medical information and advice. For example, Internet users may send requests to Web-based expert forums, or so-called “ask the doctor” services. Objective To automatically classify lay requests to an Internet medical expert forum using a combination of different text-mining strategies. Methods We first manually classified a sample of 988 requests directed to a involuntary childlessness forum on the German website “Rund ums Baby” (“Everything about Babies”) into one or more of 38 categories belonging to two dimensions (“subject matter” and “expectations”). After creating start and synonym lists, we calculated the average Cramer’s V statistic for the association of each word with each category. We also used principle component analysis and singular value decomposition as further text-mining strategies. With these measures we trained regression models and determined, on the basis of best regression models, for any request the probability of belonging to each of the 38 different categories, with a cutoff of 50%. Recall and precision of a test sample were calculated as a measure of quality for the automatic classification. Results According to the manual classification of 988 documents, 102 (10%) documents fell into the category “in vitro fertilization (IVF),” 81 (8%) into the category “ovulation,” 79 (8%) into “cycle,” and 57 (6%) into “semen analysis. ” These were the four most frequent categories in the subject matter dimension (consisting of 32 categories). The expectation dimension comprised six categories; we classified 533 documents (54%) as “general information” and 351 (36%) as a wish for “treatment recommendations. ” The generation of indicator variables based on the chi-square analysis and Cramer’s V proved to be the best approach for automatic classification in about half of the categories. In combination with the two other approaches, 100% precision and 100% recall were realized in 18 (47%) out of the 38 categories in the test sample. For 35 (92%) categories, precision and recall were better than 80%. For some categories, the input variables (ie, “words”) also included variables from other categories, most often with a negative sign. For example, absence of words predictive for “menstruation” was a strong indicator for the category “pregnancy test. ” Conclusions Our approach suggests a way of automatically classifying and analyzing unstructured information in Internet expert forums. The technique can perform a preliminary categorization of new requests and help Internet medical experts to better handle the mass of information and to give professional feedback.
Robust Kalman filtering for discrete time-varying uncertain systems with multiplicative noises

In this paper, a robust finite-horizon Kalman filter is designed for discrete time-varying uncertain systems with both additive and multiplicative noises. The system under consideration is subject to both deterministic and stochastic uncertainties. Sufficient conditions for the filter to guarantee an optimized upper bound on the state estimation error variance for admissible uncertainties are established in terms of two discrete Riccati difference equations. A numerical example is given to show the applicability of the presented method.
The Centre for Market and Public Organisation the Result of 11+ Selection: an Investigation into Opportunities and Outcomes for Pupils in Selective Leas the Result of 11 plus Selection: an Investigation into Opportunities and Outcomes for Pupils in Selective Leas

The Centre for Market and Public Organisation (CMPO) is a leading research centre, combining expertise in economics, geography and law. Our objective is to study the intersection between the public and private sectors of the economy, and in particular to understand the right way to organise and deliver public services. The Centre aims to develop research, contribute to the public debate and inform policy-making. CMPO, now an ESRC Research Centre was established in 1998 with two large grants from The Leverhulme Trust. In 2004 we were awarded ESRC Research Centre status, and CMPO now combines core funding from both the ESRC and the Trust. Abstract This paper assesses the impact of academic selection at age 11 on children in the minority of areas that still operate such a system. The answers are very clear. Overall there is little or no impact on attainment, but those educated in grammar schools do substantially better (around four grade points more than pupils with the same Key Stage 2 (KS2) points in similar, but non-selective, areas). This is equivalent to raising four GCSEs from a grade 'C' to a 'B'. Other children within selective areas who do not gain a place in a grammar school are disadvantaged by a little under one grade point. In part these effects stem from the substantive under representation of poorer and special needs children in grammar schools. Only 32% of high ability children eligible for free school meals (FSM) attend grammar schools compared with 60% of non-FSM pupils. So whilst the net effect of selection is not substantive it does result in gains for those attending the grammar schools and a slight disadvantage for the rest. The paradox is that grammar schools bestow greater advantages to poor children than more affluent children, but very few make the cut.
Profile-Based Mood Extraction from a Social Network

Within the realm of social networks, users have personal profiles that can be used to notify contacts about various events and information. Users can use messages to communicate privately with friends, upload photos, publish notes and links, as well as view and comment on friend updates. In this paper, Facebook, a very prominent social network, is used to detect user mood. Being able to detect mood from social network sites is a very vital piece of contextual information, especially in the domain of mobile pervasive applications, where cameras cannot be typically used to detect user mood without explicit user intervention. We hereby propose a method for detecting the profile owner's mood by extracting and analyzing the aforementioned information. Using such context, many applications can be made context aware, including but not limited to, the personalization of devices in reaction to user mood changes, and the personalization of the results of mobile user queries to search engines. Our mood detection classifier was able to closely match the classification made by human subjects asked to take part in our experimentation. We demonstrate our results as we vary the social networking features used in classification.
A study of mining algorithms for finding accurate results and marking irregularities in software fault prediction

In the paper we are showing a comparative study of some of the classification and the clustering algorithms so that we can find the alternatives for the datasets depending upon the requirement. These prediction systems can be used for the software fault prediction as various algorithms in this paper have been categorized and simulation results shown. Prevalence informs the total case load at a given time. Incidence yields a pointer to extent of attention required and choice of measures. Different classification algorithms are trained on the result set to build the final classifier model based on K-fold cross validation method. The best accuracy for the given dataset is achieved in rotation forest algorithm compared to other classifiers. The proposed approach helps high level managers in their management decisions and also in their resource planning procedures for different categorical products.
Gender Comparison of Communication Skills of Nursing Students: Video Analysis of Standardized Patient Interview

The purpose of this study was to investigate gender differences in communication skills of nursing students. The subjects of this study were 99 nursing students in a university. Data were collected by recording the interview process conducted by nursing students with the standardized patients and transcripts were made from the recorded video. To evaluate student’s communication skills, researchers analyzed video and transcripts objectively. Female students scored significantly higher than male students in listening skills (p=.002). Among the items assessing poor interview attitudes, too much focus on writing records (61%) was the most frequent. Therefore, the findings suggest an importance to find ways to improve the listening skills among the communication skills under the situation in increasing number of male nursing students.
BEHAVIORALLY MEDIATED INDIRECT INTERACTIONS IN MARINE COMMUNITIES AND THEIR CONSERVATION IMPLICATIONS

The importance of density-mediated indirect effects (e.g., keystone predators) in marine communities has been widely recognized. Behaviorally mediated indirect interactions (BMIIs) may be equally important in marine systems, but have received relatively little attention. BMIIs occur when a change in an “initiator” species causes a behavioral shift in a “transmitter” species that, in turn, affects a “receiver” species. BMIIs between initiator and receiver species can be described by the ecological relationships between initiator and transmitter, and between transmitter and receiver (i.e., predator and prey, competitors, or no relationship), and the nature of the indirect effect on the receiver (i.e., positive or negative). We review published examples of BMIIs in marine communities, showing that BMIIs may create, enhance, ameliorate, or even reverse the sign of the direct interactions between species. Models that only include direct interactions or density-mediated indirect ones cannot predict some of thes.
MODELS FOR RECURRENT EVENTS IN RELIABILITY AND SURVIVAL ANALYSIS

Existingmodelsforrecurrentphenomenaoccurringinpublichealth,biomedicine, reliability,engineering,economics,andsociologyarereviewed. Anewandgen­ eralclassofmodelsforrecurrenteventsisproposed. Thisclasssimultaneously takesintoaccountinterventioneffects,effectsofaccumulatingeventoccurrences, andeffectsofconcomitantvariables. Itsubsumesasspecialcasesexistingmod­ elsforrecurrentphenomena.Thestatisticalidentifiabilityissuefortheproposed classofmodelsisaddressed.
Xputer Lab Figure 8. Image Processing Example Distributed on Different Xputer Modules 5. Conclusions Strip Mining 4. Example: Image Processing Algorithm Figure 7. Transforming For-loop by Using Strip Mining with Block Size 1000

This paper presents the parallelizing programming environment CoDe-X introducing hardware/software co-design strategies on two levels for Xputer-based accelerators. Xputers are based on field-programmable logic providing high level of parallelism for the computation of data and on hardwired data sequencers providing accessing-sequences for fast address computation. CoDe-X accepts a C dialect, also including a data-procedural extension, and carries out both, the profiling-driven host/accelerator partitioning, and (2nd level) the resource-parameterdriven sequential/structural partitioning of the accelerator source code to optimize the utilization of its reconfigurable datapath resources.