Miracle-dz/UniFAR-FTUs huggingface dataset:
UWaterloo at SemEval-2016 Task 5: Minimally Supervised Approaches to Aspect-Based Sentiment Analysis

This paper describes our system for Aspect-Based Sentiment Analysis (ABSA), task 5 of SemEval 2016. To conduct sentence level ABSA, we employed minimally supervised approaches for each type of extracted information. The system uses Word2Vec to derive word semantic similarities, and relies on ex-ternal review corpora as training data. The re-sults of the 2016 evaluation are discussed and suggestions for improvements are given.
A Predictive Model for Self-reported Computer Criminal Behavior among College Students

Crimmins, Danielle M. M.S., Purdue University, August 2015. A Predictive Model for Self-reported Computer Criminal Behavior among College Students. Major Professor: Dr. Marcus Rogers. Presently, computer crime is rampant and costly. Combating these crimes is not only focused on the technical aspect but also the individual behind the computer. Researchers agree the way to fight computer crime is to gain a better understanding of those behind the keyboard. In an effort to aid investigators in profiling computer criminals, the current study aims to add empirical literature relating to characteristics which predict computer behavior. The current study aims to test the Rogers, Seigfried and Tidke (2006) predictive model and determine if Internet addiction is related to self reported computer deviant behavior. By utilizing a snowball sampling method the current study (n=95) was comprised of 49 self reported computed deviants and 46 non-computer deviants. Over all, Internet addiction was the best predictive variable for computer behavior. Those who scored high on the Internet Addiction Test (IAT) were 1 time more likely to be selfreported computer deviants. Limitation and future research is also discussed.
Prevalence of advance directives and do-not-resuscitate orders in community nursing facilities.

OBJECTIVE To determine the prevalence of advance directives and do-not-resuscitate (DNR) orders in nursing homes and to measure the effect of the Patient Self-Determination Act (PSDA) and patient characteristics on these prevalences. DESIGN Cross-sectional study. SETTING Eight rural community nursing facilities. PARTICIPANTS Six hundred forty-one records of nursing home residents (total census of eight facilities). RESULTS The mean age of the residents was 82.6 years and 75% were women. Thirty-seven percent were judged to have decisional capacity. Less than one third of the records revealed an advance directive (standard living will, 11.5%; other written directive, 11.1%; durable power of attorney for health care, 12%). Thirty-six percent had DNR orders. Residents with advance directives were older than those without them. Those residents with advance directives were more likely to have been admitted to the nursing home after the enactment of the PSDA (25.1% before vs 37.9% after enactment; P < .0001). There was substantial variation among facilities in both prevalences. Written rationales for DNR orders were found in only 40% of records. CONCLUSION Enactment of the PSDA reflects increased interest in documentation of advance directives. However, in many nursing facilities, the prevalence of advance directives and DNR orders is relatively low. A greater commitment will be required by providers, residents, and their proxies if we are to change this reality.
Estimating gasoline demand in Iran using different soft computing techniques

Present study develops two scenarios to analyse gasoline consumption and makes future projections based on the particle swarm optimisation (PSO) and genetic algorithm (GA). The gasoline consumption is estimated based on the basic indicators of the population, gross domestic product (GDP), import, export, gasoline production and number of cars figures. Two different exponential and linear estimation models are developed for each scenario using PSO and GA methods. Developed models are validated with actual data, while future estimation of gasoline demand is projected between 2006 and 2030. For the best result (PSO - PGIE{inexponential), the relative error average was 1.03%.
Non-Rigid Object Detection with Local Interleaved Sequential Alignment (LISA).

This paper shows that the successively evaluated features used in a sliding window detection process to decide about object presence/absence also contain knowledge about object deformation. We exploit these detection features to estimate the object deformation. Estimated deformation is then immediately applied to not yet evaluated features to align them with the observed image data. In our approach, the alignment estimators are jointly learned with the detector. The joint process allows for the learning of each detection stage from less deformed training samples than in the previous stage. For the alignment estimation we propose learnable regressors that approximate non-linear regression functions and compute the alignment parameters extremely fast. Experiments show a significant improvement in speed and detection rates when compared to the state of the art.
Historical data decrease complete blood count reflex blood smear review rates without missing patients with acute leukaemia

Introduction The availability of historical data decreases the rate of blood smear review rates in outpatients, but we are unaware of studies done at referral centres. In the following study, we determined the effect of historical data on the rates of peripheral blood smears over a 3-month period and then the detection rate of patients with acute leukaemia. Methods All results of complete blood counts (CBCs) tested on three ADVIA 120 analyzers at the regional Rabin Medical Centre, Beilinson Campus over a 3-month period were accessed on a computerised laboratory information system. Over a 3-month period, we determined the proportion of total CBC and patients with criteria for a manual differential count and the actual number of peripheral blood smears done. Finally, we determined the proportion of 100 consecutive patients with acute leukaemia detected using our criteria that included limiting reflex testing according to historical data. Results Over the 3-month period, there were 34 827 tests done in 12 785 patients. Without historical data, our smear rate would have been 24.5%, but with the availability of historical data, the blood smear review rate was 5.6%. The detection rate for cases of acute leukaemia was 100%. Conclusions We conclude that the availability of previous test results significantly reduces the need for blood smear review without missing any patients with acute leukaemia.
GPS analysis of multiple sessions with applications to admission control

We introduce a statistical method to analyze multiplexing of multiple sessions sharing link bandwidth using generalized processor sharing (GPS) scheduling. Our method is shown to substantially improve previous upper bounds for GPS scheduling of Markov modulated fluid processes (MMFP) sessions, especially as the number of sessions increases. Application of analytical results to admission control indicate that by sharing bandwidth using GPS among traffic classes there are significant gains over systems that statically segregate the link bandwidth. This effect is quantified in several experiments where various combinations of source types are used. The gains are pronounced when bursty sources with stricter QoS requirements are used.
IMPRoVIng MeMoRy ReLIAbILITy , PoWeR AnD PeRfoRMAnCe UsIng MIxeD-CeLL DesIgns

In this article, we show that mixed-cell memory designs could play a key role in achieving the right balance between performance, power, and reliability for single-core and multi-core systems. In such designs, part of the memory structure is built with cells that are more robust and failure-resistant, while the rest is designed using traditional cells. Robust cells ensure resiliency under low-voltage conditions to protect the most vulnerable data, while the rest of the memory structure could be used to store redundant data to improve performance. We demonstrate this concept using two specific examples: (1) A cache system that only turns on the robust portion at low-voltage, achieving good reliability and power savings while providing high-voltage performance improvements; (2) A cache system that uses the whole cache (including the non-robust portion) at low voltage, achieving good performance and reliability while not exceeding power limits. While the specific examples we explore in this article are cache-related, the same concept could be used throughout the entire memory hierarchy to improve memory resiliency without sacrificing performance or energy efficiency.
Psychosocial Stress, Internalized Symptoms, and the Academic Achievement of Hispanic Adolescents

This study examined the relationship between stressful life events, internalized symptoms of stress, and academic achievement among a sample of Hispanic students in a large urban high school. Using a paper-and-pencil questionnaire, students were administered the Hispanic Children’s Stress Inventory and two measures of internalized symptoms (Revised Children’s Manifest Anxiety Scale and the Children’s Depression Inventory). Perceived competence was measured using the Harter Perceived Competence Scale. A series of hierarchical multiple regressions revealed main effects for stressful life events and perceived competence on grades, anxiety, and depressive symptomatology. In addition, interaction terms were entered into the regression equations to determine if perceived competence was a moderator of stressful life events. Direct effects of stressful life events and perceived competence on school grades and internalized symptoms were found. Multiplicative interactions for perceived competence were not significant moderators of psychosocial stress on grades or internalized symptoms.
TCP Window-Based Flow-Oriented Dynamic Assembly Algorithm for OBS Networks

In transport control protocol (TCP) over optical burst switching (OBS) networks, TCP window size and OBS parameters, including assembly period and burst dropping probability, will impact the network performance. In this paper, a parameter window data dropping probability(WDDP), is defined to analyze the impact of the assembly and the burst loss on the network performance in terms of the round trip time and the throughput. To reduce the WDDP without introducing the extra assembly delay penalty, we propose a novel TCP window based flow-oriented assembly algorithm dynamic assembly period (DAP). In the traditional OBS assembly algorithms, the packets with the same destination and class of service (CoS) are assembled into the same burst, i.e., the packets from different sources will be assembled into one burst. In that case, one burst loss will influence multiple TCP sources. In DAP, the packets from one TCP connection are assembled into bursts, which can avoid the above situation. Through comparing the two consecutive burst lengths, DAP can track the variation of TCP window dynamically and update the assembly period for the next assembly. In addition, the ingress node architecture for the flow-oriented assembly is designed. The performance of DAP is evaluated and compared with that of fixed assembly period (FAP) over a single TCP connection and multiple TCP connections. The results show that DAP performs better than FAP at almost the whole range of burst dropping probability.
A Research Metasynthesis on Digital Video Composing in Classrooms

Calls for research documenting outcomes of new literacy practices in school (e.g., Moje, 2009) focus on the need for understanding adolescents’ experiences, what they learn about content, about literacy practices, and about their identities and positions in the world. This metasynthesis of findings from 27 qualitative studies of digital video (DV) composing in secondary schools involved 97 teachers and 135 students as focal participants in ethnographic, case, and grounded theory studies. The focus was on the body of research completed in a mature DV composing project based in sociocultural learning theories, including New Literacies and social semiotics. Following teachers out of professional development on using DV composing as a curricular learning tool into their classrooms and then analyzing across the studies provided trends in contexts for student learning. Following the analytic processes of extracting, categorizing, and translating outlined by Sandelowski and Barroso (2007), six themes were revealed, the components of DV composing pedagogy that led to student engagement in embodied learning: (a) Teacher change toward a New Literacies stance led to development of (b) classroom social spaces for mediating multimodal composing in which participants (c) co-constructed authentic communicative purpose for representing meaning, in part by (d) opening meaning-making to student lifeworlds and cultural resources, and (e) explicitly attending to multimodal design for representing meaning, leading to students’ (f) transmediating or translating in symbolic modes. These components working synergistically in classrooms provide an evidence base for a pedagogical framework for students’ embodied learning through multimodal composing.
IMAGER-A Low-Cost Scalable Multi-channel MRI Front-End

MR. IMAGER is a novel multi-channel Magnetic Resonance Imaging (MRI) front-end. It connects to an MRI scanner and digitally processes raw magnetic field measurements into images of the body. Innovative data acquisition techniques are used, with all digital functions integrated onto a single Field-Programmable Gate Array (FPGA). The result is a device that is an order-ofmagnitude cheaper and much more scalable than existing solutions, making it ideal for academic MRI research. A four-channel prototype has been designed, implemented and tested successfully. COOPER UNION EE TECH. REPORT CU/EE/S-TR06M01
The nature of personality disorder

The lack of a medically grounded approach to personality disorder and its management has led to its comparative neglect as a topic by many clinicians in the UK. In this article we present evidence that personality disorders are, like other mental disorders, the social manifestations of a pathological process. This process presents with characteristic clinical features that are developmental in nature. These cause disturbances in arousal, affect and reality testing that have an impact on interpersonal social functioning. Personality disorder may therefore be conceived of primarily as a socioemotional disability, not dissimilar to Axis I conditions.
A First-in-Human Phase I Study of the ATP-Competitive AKT Inhibitor Ipatasertib Demonstrates Robust and Safe Targeting of AKT in Patients with Solid Tumors.

Activation of AKT signaling by PTEN loss or PIK3CA mutations occurs frequently in human cancers, but targeting AKT has been difficult due to the mechanism-based toxicities of inhibitors that target the inactive conformation of AKT. Ipatasertib (GDC-0068) is a novel selective ATP-competitive small-molecule inhibitor of AKT that preferentially targets active phosphorylated AKT (pAKT) and is potent in cell lines with evidence of AKT activation. In this phase I study, ipatasertib was well tolerated; most adverse events were gastrointestinal and grade 1-2 in severity. The exposures of ipatasertib ≥200 mg daily in patients correlated with preclinical TGI90, and pharmacodynamic studies confirmed that multiple targets (i.e., PRAS40, GSK3β, and mTOR) were inhibited in paired on-treatment biopsies. Preliminary antitumor activity was observed; 16 of 52 patients (30%), with diverse solid tumors and who progressed on prior therapies, had radiographic stable disease, and many of their tumors had activation of AKT. SIGNIFICANCE Potent inhibition of AKT signaling with ipatasertib was associated with a tolerable safety profile and meaningful disease control in a subgroup of patients. Targeting pAKT with an ATP-competitive inhibitor provides a greater therapeutic window than allosteric inhibitors. Further investigation with ipatasertib is ongoing in phase II studies. Cancer Discov; 7(1); 102-13. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 1.
Seasonal changes in phosphorus competition and allelopathy of a benthic microbial assembly facilitate prevention of cyanobacterial blooms

Summary Interactions among microbes determine the prevalence of harmful algal blooms that threaten water quality. These interactions can be indirectly mediated by shared resources or consumers, or through interference by the production of allelochemicals. Allelopathic interactions and resource competition have been shown to occur among algae and associated microbes. However, little work has considered seasonal influences on ecosystem structure and function. Here, we report results of our investigations on seasonal changes in the interactions between benthic microbial assemblies and the bloom forming cyanobacterium Microcystis aeruginosa. We show that phosphorus (P) competition and allelopathy by the microbial assembly vary seasonally and inhibit growth of M. aeruginosa. The interactions per unit biomass of the microbial assembly are stronger under winter than summer conditions and inhibit the recruitment of the cyanobacteria, thereby preventing the reoccurrence of cyanobacterial blooms in the following summer. The seasonality of these interactions correlates with changes in composition, metabolic activity and functional diversity of the microbial assembly. Our findings highlight the importance of competitive and allelopathic interactions in regulating the occurrence of harmful algal blooms. Our results also imply that seasonal variation of competition and allelopathy of the microbial assembly might be beneficial to adjust aquatic ecosystem structure and function.
Targeted lipid nanoparticle delivery of calcitriol to human monocyte-derived macrophages in vitro and in vivo: investigation of the anti-inflammatory effects of calcitriol

Background Vitamin D3 possesses anti-inflammatory and modulatory properties in addition to its role in calcium and phosphate homeostasis. Upon activation, macrophages (M) can initiate and sustain pro-inflammatory cytokine production in inflammatory disorders and play a pathogenic role in certain cancers. Purpose The main purpose of this study was to encapsulate and specifically target calcitriol to macrophages and investigate the anti-inflammatory properties of calcitriol in vitro and in vivo. Methods In this study we have designed and developed near-infrared calcitriol PEGylated nanoparticles (PEG-LNP(Cal)) using a microfluidic mixing technique and modified lipid nanoparticles (LNPs) to target the M specific endocytic receptor CD163. We have investigated LNP cellular uptake and anti-inflammatory effect in LPS-induced M in vitro by flow cytometry, confocal microscopy and gene expression analyses. LNP pharmacodynamics, bio-distribution and organ specific LNP accumulation was also investigated in mice in vivo. Results In vitro, we observed the specific uptake of PEG-LNP(Cal)-hCD163 in human M, which was significantly higher than the non-specific uptake of control PEG-LNP(Cal)-IgG(h) in M. Pretreatment with encapsulated calcitriol was able to attenuate intracellular TNF-expression, and M surface marker HLA-DR expression more efficiently than free calcitriol in LPS-induced M in vitro. Encapsulated calcitriol diminished mRNA gene levels of TNF-, NF-B, MCP-1 and IL-6, while upregulating IL-10. TNF- and IL-6 protein secretion also decreased. In mice, an in vivo pharmacodynamic study of PEG-LNP(Cal) showed a rapid clearance of IgG and CD163 modified LNPs compared to PEG-LNP(Cal). Antibody modified PEG-LNP(Cal) accumulated in the liver, spleen and kidney, whereas unmodified PEG-LNP(Cal) accumulation was only observed in the liver. Conclusion Our results show that calcitriol can be effectively targeted to M. Our data confirms the anti-inflammatory properties of calcitriol and this may be a potential way to deliver high dose bioactive calcitriol to M during inflammation in vivo.
Yeast Transcriptional Module Identification Based on Line Manifold

A living cell can carry out complex biological functions dependent on its transcriptional regulatory modules. Therefore, identifying transcriptional regulatory modules is very important for understanding cell function and its transcription mechanism. In this paper, a novel algorithm based on line manifold clusters and a linear mixture framework is presented for transcriptional regulatory module identification. A combined dissimilarity is constructed by combining gene expression and Chip-chip data with the linear mixture framework. Then the combined dissimilarity is introduced into a line manifold cluster searching algorithm. The application of this novel algorithm for two yeast gene expression datasets identified many transcriptional regulatory modules with significant biological meanings. The analysis of the identified transcriptional modules is helpful for a further understanding of yeast transcription mechanism.
Audiometer-earphone mounting to improve intersubject and cushion-fit reliability.

The range of combined intersubject and cushion‐fit variation in the response of the TDH‐39 audiometer earphone in an MX41/AR cushion, reported in the literature and confirmed in these measurements, is of the order of 25 dB at 100 Hz, 6 dB at 1 kHz, and 15 dB at 5 kHz. The performance of this earphone system is further impaired by cushion‐induced physiological noise that masks low‐frequency thresholds, typically by 6 dB in normal‐hearing subjects. An experimental mounting for the TDH‐39 is described and analyzed; it is a circumaural device designed to keep the earphone‐ear acoustical system as near constant as possible with successive fittings and different subjects, and to reduce physiological noise. The performance of the TDH‐39 in this mounting, compared to performance in an MX41/AR cushion, showed a substantial reduction in cushion‐fit and intersubject response variation, and masking by physiological noise was largely eliminated in the subjects tested. The mounting has an optional cup for reducing the .
Software Components Behavioral Adaptation Based on LTS

Compatibility is the precondition to ensure the correct interaction among components in composition process, how to make the mismatch components coordinate correctly is a vital problem in component composition. This paper first modeled component behavior by LTS and expressed action mapping as synchronous vector then defined the sequential relationship among synchronous vectors as adaptation contract. Thirdly we analyzed the different mismatch situations and corresponding adaptation strategies. At last designed adaptation algorithm to produce adaptor specification automatically and ensured the mismatch components can correct interaction under the mediation of adaptor and verified the validity of proposed method through an application system.