Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential population responses of native and alien rodents to an invasive predator, habitat alteration and plant masting

Invasive species and anthropogenic habitat alteration are major drivers of biodiversity loss. When multiple invasive species occupy different trophic levels, removing an invasive predator might cause unexpected outcomes owing to complex interactions among native and non-native prey. Moreover, external factors such as habitat alteration and resource availability can affect such dynamics. We hypothesized that native and non-native prey respond differently to an invasive predator, habitat alteration and bottom-up effects. To test the hypothesis, we used Bayesian state-space modelling to analyse 8-year data on the spatio-temporal patterns of two endemic rat species and the non-native black rat in response to the continual removal of the invasive small Indian mongoose on Amami Island, Japan. Despite low reproductive potentials, the endemic rats recovered better after mongoose removal than did the black rat. The endemic species appeared to be vulnerable to predation by mongooses, whose eradication increased the abundances of the endemic rats, but not of the black rat. Habitat alteration increased the black rat's carrying capacity, but decreased those of the endemic species. We propose that spatio-temporal monitoring data from eradication programmes will clarify the underlying ecological impacts of land-use change and invasive species, and will be useful for future habitat management.
Beyond the scope of acquisition: A novel perspective on the isomorphism effect from Broca’s aphasia

ABSTRACT Children have been reported to prefer the surface scope or “isomorphic” reading of scopally ambiguous sentences (Musolino 1998, among others). Existing accounts in the literature differ with respect to the proposed source of this isomorphism effect. Some accounts are based on learnability considerations (e.g., Moscati & Crain 2014), while others invoke pragmatic and/or processing factors (e.g., Gualmini et al. 2008; Musolino & Lidz 2006). The present study investigates whether the isomorphism effect is specific to development or rather is observable in other populations with language processing limitations. We investigated the interpretation of ambiguous sentences containing “every” and negation in 4–6-year-old children, individuals with Broca’s aphasia, and neurotypical adult controls. We observed parallel performance in the children and the aphasic group, with both groups accessing more surface scope readings than inverse scope readings. This finding suggests that the preference for isomorphism may not be specific to acquisition and supports accounts that are not specifically based on learnability considerations—for example, processing accounts along the lines of Musolino & Lidz (2006).
An Epstein-Barr Virus Anti-Apoptotic Protein Constitutively Expressed in Transformed Cells and Implicated in Burkitt Lymphomagenesis: The Wp/BHRF1 Link

Two factors contribute to Burkitt lymphoma (BL) pathogenesis, a chromosomal translocation leading to c-myc oncogene deregulation and infection with Epstein-Barr virus (EBV). Although the virus has B cell growth–transforming ability, this may not relate to its role in BL since many of the transforming proteins are not expressed in the tumor. Mounting evidence supports an alternative role, whereby EBV counteracts the high apoptotic sensitivity inherent to the c-myc–driven growth program. In that regard, a subset of BLs carry virus mutants in a novel form of latent infection that provides unusually strong resistance to apoptosis. Uniquely, these virus mutants use Wp (a viral promoter normally activated early in B cell transformation) and express a broader-than-usual range of latent antigens. Here, using an inducible system to express the candidate antigens, we show that this marked apoptosis resistance is mediated not by one of the extended range of EBNAs seen in Wp-restricted latency but by Wp-driven expression of the viral bcl2 homologue, BHRF1, a protein usually associated with the virus lytic cycle. Interestingly, this Wp/BHRF1 connection is not confined to Wp-restricted BLs but appears integral to normal B cell transformation by EBV. We find that the BHRF1 gene expression recently reported in newly infected B cells is temporally linked to Wp activation and the presence of W/BHRF1-spliced transcripts. Furthermore, just as Wp activity is never completely eclipsed in in vitro–transformed lines, low-level BHRF1 transcripts remain detectable in these cells long-term. Most importantly, recognition by BHRF1-specific T cells confirms that such lines continue to express the protein independently of any lytic cycle entry. This work therefore provides the first evidence that BHRF1, the EBV bcl2 homologue, is constitutively expressed as a latent protein in growth-transformed cells in vitro and, in the context of Wp-restricted BL, may contribute to virus-associated lymphomagenesis in vivo.
Dynamic Real-time Task Scheduling on Hypercubes 1

Multiprocesssor systems have emerged as an important computing means for real-time applications and have received increasing attention than before. However, until now, little research has been done on the problem of on-line scheduling of parallel tasks with deadlines in partitionable multiprocessor systems. Meshes and hypercubes belong to this class of multiprocessors. In this paper, we propose a new on-line scheduling algorithm, called Deferred Earliest Deadline First (DEDF) for hypercube systems. The main idea of the DEDF algorithm is to defer the scheduling as late as possible, so that a set of jobs is scheduled at a time instead of one at a time. For processor allocation using DEDF, we have introduced a new concept-Available Time Window (ATW). By using ATW, the system utilization can be improved and thereby the deadlines of more number of tasks can be met. Simulation results indicate that the DEDF algorithm performs signiicantly better than the earlier proposed Buddy/RT and Stacking algorithms for a wide range of workloads.
BRAF inhibition improves tumor recognition by the immune system

In spite of the fact that they occur at high rates, the clinical responses of BRAFV600 mutant metastatic melanoma to BRAF inhibitors are usually short-lasting, with most cases progressing within less than 8 mo. Immunomodulatory strategies initiated after progression have recently been reported to be poorly efficient. By characterizing the immunological interactions between T cells and cancer cells in clinical material as well as the influence of the FDA-approved BRAF inhibitor vemurafenib on the immune system, we aimed at unraveling new strategies to expand the efficacy of adoptive T-cell transfer, which represents one of the most promising approaches currently in clinical development for the treatment of metastatic melanoma. Here we show that blocking the BRAF-MAPK pathway in BRAF signaling-addicted melanoma cells significantly increases the ability of T cells contained in clinical grade tumor-infiltrating lymphocytes to recognize autologous BRAFV600 mutant melanoma cell lines in vitro. Antitumor reactivity was improved regardless of the class of antigen recognized by tumor-specific CD8+ T cells. Microarray data suggests that improved tumor recognition is associated with modified expression of MHC Class I-associated proteins as well as of heat-shock proteins. In conclusion, our preclinical data suggest that an appropriately timed sequential treatment of BRAFV600 mutant melanoma with vemurafenib and adoptive T-cell transfer might result in synergistic antineoplastic effects owing to an increased immunogenicity of cancer cells.
Perinatal Gene-Gene and Gene-Environment Interactions on IgE Production and Asthma Development

Atopic asthma is a complex disease associated with IgE-mediated immune reactions. Numerous genome-wide studies identified more than 100 genes in 22 chromosomes associated with atopic asthma, and different genetic backgrounds in different environments could modulate susceptibility to atopic asthma. Current knowledge emphasizes the effect of tobacco smoke on the development of childhood asthma. This suggests that asthma, although heritable, is significantly affected by gene-gene and gene-environment interactions. Evidence has recently shown that molecular mechanism of a complex disease may be limited to not only DNA sequence differences, but also gene-environmental interactions for epigenetic difference. This paper reviews and summarizes how gene-gene and gene-environment interactions affect IgE production and the development of atopic asthma in prenatal and childhood stages. Based on the mechanisms responsible for perinatal gene-environment interactions on IgE production and development of asthma, we formulate several potential strategies to prevent the development of asthma in the perinatal stage.
Housing Discrimination and Health: Understanding Potential Linking Pathways Using a Mixed-Methods Approach

Few studies have examined the impact of housing discrimination on health. This study explores potential pathways linking housing discrimination and health using concept mapping, a mixed-method approach. Participants included employees from twenty Fair Housing Organizations nationwide who participated in two online sessions, brainstorming, and structuring. Responses were generated representing biological, social, economic, and physical connections between housing discrimination and health. Using hierarchical cluster analysis, five clusters were identified: (1) Access and barriers; (2) Opportunities for growth; (3) Neighborhood and communities; (4) Physical effects of housing discrimination; and (5) Mental health. Clusters 1 (4.09) and 2 (4.08) were rated as most important for health, while clusters 2 (3.93) and 3 (3.90) were rated as most frequently occurring. These findings add to the limited evidence connecting housing discrimination to health and highlight the need for studies focusing on the long-term health effects of housing discrimination on individuals and neighborhoods.
An analog VLSI chip with asynchronous interface for auditory feature extraction

We describe the architecture and circuit implementation of an analog VLSI feature extraction chip that has an asynchronous digital interface and is designed to serve as an auditory based front-end for a digit recognition system. The single chip system encodes signal energies and zero crossing time intervals of frequency components in a cochlear filter bank. The chip has been fabricated in a 1.2 /spl mu/m n-well, double polysilicon, double metal CMOS process and it is fully functional. Power consumption when operated from a 5 V supply is only a few milliwatts.
A Hybrid Learning Algorithm Fusing STDP with GA based Explicit Delay Learning for Spiking Neurons

This paper presents a hybrid learning algorithm for spiking neural networks (SNNs), referred to as an evolvable spiking neural network (ESNN) paradigm. The algorithm integrates a supervised and unsupervised learning approach. The unsupervised approach exploits a spike timing dependent plasticity (STDP) mechanism with explicit delay learning for multiple connections between neurons. Supervision of the synaptic delays and the excitatory/inhibitory connections is governed by a genetic algorithm (GA), while the STDP rule is free to operate in its normal unsupervised manner. A spike train encoding/decoding scheme is developed for the algorithm. The approach is validated by application to the Iris classification problem
Body image, peer effects and food disorders: Evidence from a sample of European women

Excessive preoccupation with self-image has been pinpointed as a factor contributing to the proliferation of food disorders, especially among young women. To provide an economic basis for this argument this paper models how ‘self-image’ and ‘other people’s appearance’ influence health-related behaviour. Self-image (identity) is claimed to be biased towards anorexic women by social norms and peer pressure, increasing the probability of women experiencing a food disorder. This paper empirically tests this claim using data from a representative, cross-sectional European survey for 2004. A two-step empirical strategy was used. First, the probability was estimated of a woman ‘being extremely thin’ and at the same time ‘seeing herself as too fat’. The findings revealed robust evidence suggesting that (different definitions of) peer effects average out, and that a larger peer body-mass decreases the likelihood of being anorexic. Second, the two processes were estimated separately, using a recursive system, which suggested that self-image was associated with body weight when unobservable variables explaining both processes were controlled for. (These processes were found to be positively and significantly correlated). As expected, several definitions of peers’ body mass were found to decrease the likelihood of women being thin or extremely thin, when common unobservable variables were controlled for.
Quality Misuse

There are several methods for the derivation and analysis of detailed non-functional requirements. They often are designed for a special application, like misuse cases for top-down derivation of requirements detailing the quality attribute “security”, or ATAM for evaluating given architectural alternatives. In this work, we apply misuse cases to any other quality attribute (e.g. usability, efficiency) to develop a misuse-based method for deriving detailed nonfunctional and functional requirements. Doing so, we find that generalizations must be made to the definitions of the misuse case concepts, and new concepts must be included. With this paper, we want to stimulate a discussion about the general usefulness of our approach and definitions.
The Leadership Orientations of the Students Receiving Sports Education in Turkey

This research has been planned to identify the factors related to the assessment of “The Leadership Orientations” of the students receiving sports education (physical education and sports teacher, sports management, recreation, trainer education departments) in the universities in Turkey. This descriptive study has a population consisting of the students receiving sports education in the universities in Turkey and a sample of totally 1032 students (N: 1032) (who attend physical education and sports teacher, sports management, recreation, trainer education departments). The data has been collected using The Student Information Form and the Leadership Orientation Survey. According to the means of sub-scales of “Leadership Orientations by Sexes” obtained by the students receiving sports education, a significant difference has been identified between the frames of “Transformational Leadership” and “Charismatic Leadership”. This difference can be explained by the fact that male students consider themselves more competent compared to the female students in these two sub-scales. Consequently, when the mean points of the sub-scales of the Leadership Orientation Survey [Self] obtained by the students receiving sports education in Turkey are compared, it has been observed that the direction and strength of relation between sex, class, department and school is “positive” and “moderate” and also those students have “people-oriented leadership” characteristics among the sub-scales of the leadership orientation frames.
Learning Models of Unknown Events

Agents with incomplete models of their environment are likely to be surprised by it. For agents in immense environments that defy complete modeling, this represents an opportunity to learn. We investigate approaches for situated agents to detect surprise, discriminate among different forms of surprise, and ultimately hypothesize new models for the unknown events that surprised them. We instantiate these approaches in a new goal reasoning agent, FOOLMETWICE, and investigate how that agent performs in a simulated environment. In this case study, we found that FOOLMETWICE learn models that substantially improve its performance.
Geometric Bounds: A Noniterative Analysis Technique for Closed Queueing Networks

We propose the Geometric Bounds (GBs), a new family of fast and accurate noniterative bounds on closed queueing network performance metrics that can be used in the online optimization of distributed applications. Compared to state-of-the-art techniques such as the Balanced Job Bounds (BJBs), GB achieves higher accuracy at similar computational costs, limiting the worst- case bounding error typically within 5-13 percent when, for the BJB, it is usually in the range of 15-35 percent. Optimization problems that are solved with GBs return solutions that are much closer to the global optimum than with existing bounds. We also show that the GB technique generalizes as an accurate approximation to closed fork-join networks commonly used in disk, parallel, and database models, thus extending the applicability of the method beyond the optimization of basic product-form networks.
ANALISIS SELF EFFICACY, EMPLOYEE ENGAGEMENT, SERVANT LEADERSHIP, ORGANIZATIONAL CITIZENSHIP BEHAVIOR DAN KINERJA TENAGA KEPENDIDIKAN PERGURUAN TINGGI SWASTA DI PURWOKERTO

Tujuan penelitian ini adalah untuk menganalisis tingkat s elf efficacy, employee engagement , servant leadership , O rganizational Citizenship B ehavior dan kinerja tenaga kependidikan di Perguruan Tinggi Swasta di Purwokerto. Penelitian dilakukan pada bulan April sampai dengan Mei 2018. Penelitian ini menggunakan metode survey menggunakan analisis deskriptif kuantitatif. Sampel dalam penelitian ini berjumlah 150 tenaga kependidikan, teknik pengambilan sampel yang digunakan adalah cluster random sampling . Data diperoleh dengan mendistribusikan kuisioner. Hasil penelitian menunjukkan bahwa tingkat self efficacy, employee engagement, servant leadership, organizational citizenship behavior dan kinerja tenaga kependidikan di Purwokerto dalam kategori tinggi dengan nilai rata-rata masing-masing berturut-turut 4,16; 4,02; 3,88; 3,92 dan 4,03.
XQ2P: Efficient XQuery P2P Time Series Processing

In this demonstration, we propose a model for the management of XML time series (TS), using the new XQuery 1.1 window operator. We argue that centralized computation is slow, and demonstrate XQ2P, our prototype of efficient XQuery P2P TS computation in the context of financial analysis of large data sets (>1M values).
Tracking Functional Guilds: “Dehalococcoides” spp. in European River Basins Contaminated with Hexachlorobenzene

ABSTRACT Hexachlorobenzene (HCB) has been widely used in chemical manufacturing processes and as a pesticide. Due to its resistance to biological degradation, HCB has mainly accumulated in freshwater bodies and agricultural soils. “Dehalococcoides” spp. , anaerobic dechlorinating bacteria that are capable of degrading HCB, were previously isolated from river sediments. Yet there is limited knowledge about the abundance, diversity, and activity of this genus in the environment. This study focused on the molecular analysis of the composition and abundance of active Dehalococcoides spp. in HCB-contaminated European river basins. 16S rRNA-based real-time quantitative PCR and denaturing gradient gel electrophoresis in combination with multivariate statistics were applied. Moreover, a functional gene array was used to determine reductive dehalogenase (rdh) gene diversity. Spatial and temporal fluctuations were observed not only in the abundance of Dehalococcoides spp. but also in the composition of the populations and rdh gene diversity. Multivariate statistics revealed that Dehalococcoides sp. abundance is primarily affected by spatial differences, whereas species composition is under the influence of several environmental parameters, such as seasonal changes, total organic carbon and/or nitrogen content, and HCB contamination. This study provides new insight into the natural occurrence and dynamics of active Dehalococcoides spp. in HCB-contaminated river basins.
A Hybrid Approach to Finding Phenotype Candidates in Genetic Texts

Named entity recognition (NER) has been extensively studied for the names of genes and gene products but there are few proposed solutions for phenotypes. Phenotype terms are expected to play a key role in inferring gene function in complex heritable diseases but are intrinsically difficult to analyse due to their complex semantics and scale. In contrast to previous approaches we evaluate state-of-the-art techniques involving the fusion of machine learning on a rich feature set with evidence from extant domain knowledge-sources. The techniques are validated on two gold standard collections including a novel annotated collection of 112 abstracts derived from a systematic search of the Online Mendelian Inheritance of Man database for auto-immune diseases. Encouragingly the hybrid model outperforms a HMM, a CRF and a pure knowledge-based method to achieve an F1 of 77.07. Disagreement analysis points to further improvements on this emerging NE task. The annotated corpus and guidelines are available on request.
Method to determine CPI for ubiquitous radar

Ubiquitous radio: is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in "pop-up" targets in clutter to long-range targets impacts selection of waveform parameters. The CPI (Coherent Processing Interval) must be long enough to achieve a certain signal-to-noise ratio (SNR) that insures the efficiency of detection. This paper analyzes the condition of detection in the case of low SNR, discusses three different cases that would occur during integration and presents a method to determine the CPI. The simulation results show that it is available to determine the CPI for targets detection with SNR as low as −26dB in the experimental system.
Load balancing non-uniform parallel computations

Dynamic load balancing is critical in achieving high performance in parallel systems, especially for applications with unpredictable workloads. Traditional load balancing approaches -- such as work-sharing and work-stealing -- often assume that the computations can be divided into smaller computations based on some granularity. These approaches do not scale when the computations are not dividable and their sizes are highly variant. In this paper, we present a novel approach -- founded in the Actor model known for its programmability -- for dynamically load-balancing non-uniform parallel computations. Specifically, our approach is to explicitly reason about resource requirements and commitments at run-time in order to make fine-grained scheduling decisions. We prototype our approach by extending an efficient Java implementation of Actors, ActorFoundry. We have also implemented a tuner which dynamically balances the resources used by the computations vs. those used by the reasoning mechanism, essentially balancing the quality of scheduling against the resources needed for achieving it. We propose a new benchmark -- the Unbalanced Cobwebbed Tree (UCT) -- to fairly compare our approach to existing approaches, which captures the non-uniform nature of computations. Experimental results show that despite the higher overhead of providing Actors' programmability features, for a diverse enough set of computations, our approach outperforms both work-sharing and work-stealing approaches, and shows better scalability.