LLukas22/scidocs huggingface dataset:
Investigation of Parameters Affecting Surface Roughness in CNC Routing Operation on Wooden EGP

The aim of this study was to evaluate the effect of CNC routing, using different parameters with the Taguchi experimental design, on the surface quality of various wooden (pine, spruce, and beech) edge-glued panels (EGP). The study evaluated five processing parameters: cutting direction, cutting depth, cutting width, feed rate, and spindle rotation speed, and their effects on surface roughness on pine, spruce, and beech EGP. Based on the results of statistical analysis of the burr surface roughness values, the mentioned parameters affected panels at varying levels. It was seen that the parameters were only responsible for ~34% (Rz) of the roughness on the surface of pine EGP, ~49% (Rz) of spruce EGP, and ~27% (Rq) of beech EGP. Statistically important parameters were as follows: cutting direction for pine, cutting depth (tip diameter) and feed rate for spruce, and cutting direction and feed rate for beech.
Ricochet Robots: A Transverse ASP Benchmark

A distinguishing feature of Answer Set Programming is its versatility. In addition to satisfiability testing, it offers various forms of model enumeration, intersection or unioning, as well as optimization. Moreover, there is an increasing interest in incremental and reactive solving due to their applicability to dynamic domains. However, so far no comparative studies have been conducted, contrasting the respective modeling capacities and their computational impact. To assess the variety of different forms of ASP solving, we propose Alex Randolph’s board game Ricochet Robots as a transverse benchmark problem that allows us to compare various approaches in a uniform setting. To begin with, we consider alternative ways of encoding ASP planning problems and discuss the underlying modeling techniques. In turn, we conduct an empirical analysis contrasting traditional solving, optimization, incremental, and reactive approaches. In addition, we study the impact of some boosting techniques in the realm of our case study.
Developing Web-based assessment strategies for facilitating junior high school students to perform self-regulated learning in an e-Learning environment

This research refers to the self-regulated learning strategies proposed by Pintrich (1999) in developing a multiple-choice Web-based assessment system, the Peer-Driven Assessment Module of the Web-based Assessment and Test Analysis system (PDA-WATA). The major purpose of PDA-WATA is to facilitate learner use of self-regulatory learning behaviors to perform self-regulated learning and in turn improve e-Learning effectiveness. PDA-WATA includes five main strategies: ‘Adding Answer Notes,’ ‘Stating Confidence,’ ‘Reading Peer Answer Notes,’ ‘Recommending Peer Answer Notes’ and ‘Querying Peers’ Recommendation on Personal Answer Notes’. Using these strategies, examinees are allowed to add answer notes to explain why they chose a certain option as the correct answer and state their confidence in their own answer and answer notes, for peers’ reference. In addition to reading peer answer notes, examinees can also recommend peer answer notes as valuable references. The recommendation information can also be queried by all examinees. Quasi-experimental design was adopted to understand the effectiveness of PDA-WATA in facilitating learner use of self-regulatory learning behaviors to perform self-regulated learning and in improving learner e-Learning effectiveness. Participants were 123 seventhgrade junior high school students from four classes. These four classes were randomly divided into the PDA-WATA group (n1⁄4 63) and the N-WBT group (n1⁄4 60). Before e-Learning instruction, all students took the pre-test of the Learning Process Inventory (LPI), used to understand how often learners use selfregulatory learning behaviors in the learning process, and the pre-test of the summative assessment. After a two-week e-Learning instruction, the students all took the post-test of the LPI and the summative assessment. Results indicate that students in the PDA-WATA group appear to be more willing to take the Web-based formative assessment than students in the N-WBT group. In addition, PDA-WATA appears to be significantly more effective than N-WBT in facilitating learner use of self-regulatory learning behaviors to perform self-regulated learning and in improving their e-Learning effectiveness. Moreover, this research also finds that in the PDA-WATA group, there is no significant difference between the learning effectiveness of students with a low level of self-regulated learning and students with a high level of self-regulated learning, but similar result cannot be found in the N-WBT group. 2011 Elsevier Ltd. All rights reserved.
Oral topiramate reduces the consequences of drinking and improves the quality of life of alcohol-dependent individuals: a randomized controlled trial.

BACKGROUND
Topiramate, a fructopyranose derivative, was superior to placebo at improving the drinking outcomes of alcohol-dependent individuals.


OBJECTIVES
To determine whether topiramate, compared with placebo, improves psychosocial functioning in alcohol-dependent individuals and to discover how this improvement is related to heavy drinking behavior.


DESIGN
Double-blind, randomized, controlled, 12-week clinical trial comparing topiramate vs placebo for treating alcohol dependence (1998-2001).


PARTICIPANTS
One hundred fifty alcohol-dependent individuals, diagnosed using the DSM-IV.


INTERVENTIONS
Seventy-five participants received topiramate (escalating dose of 25 mg/d to 300 mg/d), and 75 had placebo and weekly standardized medication compliance management.


MAIN OUTCOME MEASURES
Three elements of psychosocial functioning were measured: clinical ratings of overall well-being and alcohol-dependence severity, quality of life, and harmful drinking consequences. Overall well-being and dependence severity and quality of life were analyzed as binary responses with a generalized estimating equation approach; harmful drinking consequences were analyzed as a continuous response using a mixed-effects, repeated-measures model.


RESULTS
Averaged over the course of double-blind treatment, topiramate, compared with placebo, improved the odds of overall well-being (odds ratio [OR] = 2.17; 95% confidence interval [CI], 1.16-2.60; P =.01); reported abstinence and not seeking alcohol (OR = 2.63; 95% CI, 1.52-4.53; P =.001); overall life satisfaction (OR = 2.28; 95% CI, 1.21-4.29; P =.01); and reduced harmful drinking consequences (OR = -0.07; 95% CI, -0.12 to -0.02, P =.01). There was a significant shift from higher to lower drinking quartiles on percentage of heavy drinking days, which was associated with improvements on all measures of psychosocial functioning.


CONCLUSIONS
As an adjunct to medication compliance enhancement treatment, topiramate (up to 300 mg/d) was superior to placebo at not only improving drinking outcomes but increasing overall well-being and quality of life and lessening dependence severity and its harmful consequences.
Phase 2 study of a high dose of 186Re-HEDP for bone pain palliation in patients with widespread skeletal metastases.

UNLABELLED
(186)Re-1-hydroxyethylidene-1,1-diphosphonate (HEDP) is an attractive radiopharmaceutical for the treatment of bone pain arising from skeletal metastatic lesions. Currently, (186)Re-HEDP is most commonly used in European countries. The aim of this study was to investigate the palliative efficacy and adverse effects of (186)Re-HEDP in patients with different types of cancers and skeletal bone pain.


METHODS
Nineteen (8 male, 11 female) patients with various cancers (breast, prostate, renal cell carcinoma, colon, and neuroendocrine tumors) and painful bone metastases were included in the study. A dose of 1,480-3,330 MBq (40-90 mCi) of (186)Re-HEDP was administered intravenously. The patients' level of pain relief was assessed by the Visual Analog Scale for 8 wk after treatment and by a weekly blood cell count to evaluate for hematologic toxicity.


RESULTS
The overall response rate was 89.5%, and the mean pain score assessed by the Visual Analog Scale was reduced from 9.1 to 5.3 after 1 wk (P = 0.003). No adverse effects were reported by patients during intravenous administration or for up to 24 h after administration. A flare reaction was seen in 63.2% of patients, mainly during days 1-3, and lasted for 2-4 d. There was no significant correlation between the response to therapy and the flare reactions (P > 0.05). The nadir of platelet reduction occurred at the fourth or fifth week and led to platelet infusion in only 4 patients with a low baseline platelet count and diffuse skeletal metastases. Bone marrow suppression occurred in patients receiving higher doses, but no clinical problems were seen except in 2 patients who required packed cell transfusion similar to their prior transfusions.


CONCLUSION
(186)Re-HEDP is an effective radiopharmaceutical for the palliative treatment of metastatic bone pain and has minimal adverse effects.
Building temperature control with adaptive feedforward

A common approach to the modeling of temperature evolution in a multi-zone building is to use thermal resistance and capacitance to model zone and wall dynamics. The resulting thermal network may be represented as an undirected graph. The thermal capacitances are the nodes in the graph, connected by thermal resistances as links. The temperature measurements and temperature control elements (heating and cooling) in this lumped model are collocated. As a result, the input/output system is strictly passive and any passive output feedback controller may be used to improve the transient and steady state performance without affecting the closed loop stability. The storage functions associated with passive systems may be used to construct a Lyapunov function, to demonstrate closed loop stability and motivate the construction of an adaptive feedforward control to compensate for the variation of the ambient temperature and zone heat loads (due to changing occupancy). The approach lends itself naturally to an inner-outer loop control architecture where the inner loop is designed for stability, while the outer loop balances between temperature specification and power consumption. Energy efficiency consideration may be added by adjusting the target zone temperature based on user preference and energy usage. The initial analysis uses zone heating/cooling as input, but the approach may be extended to more general model where the zonal mass flow rate is the control variable. A four-room example with realistic ambient temperature variation is included to illustrate the performance of the proposed passivity based control strategy.
Is physics-based liveness detection truly possible with a single image?

Face recognition is an increasingly popular method for user authentication. However, face recognition is susceptible to playback attacks. Therefore, a reliable way to detect malicious attacks is crucial to the robustness of the system. We propose and validate a novel physics-based method to detect images recaptured from printed material using only a single image. Micro-textures present in printed paper manifest themselves in the specular component of the image. Features extracted from this component allows a linear SVM classifier to achieve 2.2% False Acceptance Rate and 13% False Rejection Rate (6.7% Equal Error Rate). We also show that the classifier can be generalizable to contrast enhanced recaptured images and LCD screen recaptured images without re-training, demonstrating the robustness of our approach.1
Online Social Networking and Learning: What are the Interesting Research Questions?

This article introduces a youth-initiated practice: online social networking that is transforming our society in important ways and has vast implications for research concerning online behavior, the social and psychological aspects of online learning and the institution of education. In this paper, the author introduces the socio-technical features that characterize social networking systems and outlines results from preliminary research that suggests the informal social and intellectual practices in which participants naturally engage and how these relate to the competencies increasingly valued in formal education. The paper outlines four overlapping categories for research such as activities and outcomes, tool, place, and medium, identity and communication, and network analytics and methods. Within these categories the author outlines interesting research questions to pursue in documenting and interpreting the complexity of ‘learning’ within these spaces. Goals are to catalyze inquiry that bridges informal and formal learning and stimulate interdisciplinary conversation about where such agendas fit within and advance learning research.
Longitudinal screening algorithm that incorporates change over time in CA125 levels identifies ovarian cancer earlier than a single-threshold rule.

PURPOSE
Longitudinal algorithms incorporate change over time in biomarker levels to individualize screening decision rules. Compared with a single-threshold (ST) rule, smaller deviations from baseline biomarker levels are required to signal disease. We demonstrated improvement in ovarian cancer early detection by using a longitudinal algorithm to monitor annual CA125 levels.


PATIENTS AND METHODS
We retrospectively evaluated serial preclinical serum CA125 values measured annually in 44 incident ovarian cancer cases identified from participants in the PLCO (Prostate Lung Colorectal and Ovarian) Cancer Screening Trial to determine how frequently and to what extent the parametric empirical Bayes (PEB) longitudinal screening algorithm identifies ovarian cancer earlier than an ST rule.


RESULTS
The PEB algorithm detected ovarian cancer earlier than an ST rule in a substantial proportion of cases. At 99% specificity, which corresponded to the ST-rule CA125 cutoff ≥ 35 U/mL that was used in the PLCO trial, 20% of cases were identified earlier by using the PEB algorithm. Among these cases, the PEB signaled abnormal CA125 values, on average, 10 months earlier and at a CA125 concentration 42% lower (20 U/mL) than the ST-rule cutoff. The proportion of cases detected earlier by the PEB algorithm and the earliness of detection increased as the specificity of the screening rule was reduced.


CONCLUSION
The PEB longitudinal algorithm identifies ovarian cancer earlier and at lower biomarker concentrations than an ST screening algorithm adjusted to the same specificity. Longitudinal biomarker assessment by using the PEB algorithm may have application for screening other solid tumors in which biomarkers are available.
Evaluation of the performance of a novel system for continuous glucose monitoring.

BACKGROUND
The performance of a continuous glucose monitoring (CGM) system in the early stage of development was assessed in an inpatient setting that simulates daily life conditions of people with diabetes. Performance was evaluated at low glycemic, euglycemic, and high glycemic ranges as well as during phases with rapid glucose excursions.


METHODS
Each of the 30 participants with type 1 diabetes (15 female, age 47 ± 12 years, hemoglobin A1c 7.7% ± 1.3%) wore two sensors of the prototype system in parallel for 7 days. Capillary blood samples were measured at least 16 times per day (at least 15 times per daytime and at least once per night). On two subsequent study days, glucose excursions were induced. For performance evaluation, the mean absolute relative difference (MARD) between CGM readings and paired capillary blood glucose readings and precision absolute relative difference (PARD), i.e., differences between paired CGM readings were calculated.


RESULTS
Overall aggregated MARD was 9.2% and overall aggregated PARD was 7.5%. During induced glucose excursions, MARD was 10.9% and PARD was 7.8%. Lowest MARD (8.5%) and lowest PARD (6.4%) were observed in the high glycemic range (euglycemic range, MARD 9.1% and PARD 7.4%; low glycemic range, MARD 12.3% and PARD 12.4%).


CONCLUSIONS
The performance of this prototype CGM system was, particularly in the hypoglycemic range and during phases with rapid glucose fluctuations, better than performance data reported for other commercially available systems. In addition, performance of this prototype sensor was noticeably constant over the whole study period. This prototype system is not yet approved, and performance of this CGM system needs to be further assessed in clinical studies.
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains

We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Football. We model the problem as a Bayesian reinforcement learning one, where the action space is exponential in the number of players and where the decision maker’s beliefs are over multiple characteristics of each footballer. We then exploit domain knowledge to construct computationally tractable solution techniques in order to build a competitive automated Fantasy Football manager. Thus, we are able to establish the baseline performance in this domain, even without complete information on footballers’ performances (accessible to human managers), showing that our agent is able to rank at around the top percentile when pitched against 2.5M
Outlooks and Insights on Group Decision and Negotiation

Community governance needs a small group discussion among community people to identify their concerns, to share them each other and to generate better alternatives for solving problems. A planner should manage the discussion to achieve these objectives. This study analyzed the small group discussion in the community disaster risk management by using text mining. Correspondence analysis was applied to the text data of the discussion. Analytical results revealed the characteristics and effects of small group discussion.
Designing content-centric multi-hop networking over Wi-Fi Direct on smartphones

The peer-to-peer and ad-hoc networking allows content dissemination and sharing among mobile devices without depending on any infrastructure. However, mobile devices still encounter content sharing issues in highly dense networks. Therefore, we develop a new architecture which creates self-organizing ad-hoc network with content centric networking over Wi-Fi Direct on smartphones. It enables nodes to build multiple groups using different channels for providing Wi-Fi Direct based multi-hop communications. The proposed architecture can achieve not only power efficiency for energy constrained devices but content sharing efficiency from content-centric networking properties. Our simulation study using NS-3 with CCNx shows significantly improved performance of the proposed solution.
Singing speaker clustering based on subspace learning in the GMM mean supervector space

In this study, we propose algorithms based on subspace learning in the GMM mean supervector space to improve performance of speaker clustering with speech from both reading and singing. As a speaking style, singing introduces changes in the time-frequency structure of a speaker’s voice. The purpose of this study is to introduce advancements for speech systems such as speech indexing and retrieval which improve robustness to intrinsic variations in speech production. Speaker clustering techniques such as k-means and hierarchical are explored for analysis of acoustic space differences of a corpus consisting of reading and singing of lyrics for each speaker. Furthermore, a distance based on fuzzy c-means membership degrees is proposed to more accurately measure clustering difficulty or speaker confusability. Two categories of subspace learning methods are studied: unsupervised based on LPP, and supervised based on PLDA. Our proposed clustering method based on PLDA is a two stage algorithm: where first, initial clusters are obtained using full dimension supervectors, and next, each cluster is refined in a PLDA subspace resulting in a more speaker dependent representation that is less sensitive to speaking style. It is shown that LPP improves average clustering accuracy by 5.1% absolute versus a hierarchical baseline for a mixture of reading and singing, and PLDA based clustering increases accuracy by 9.6% absolute versus a k-means baseline. The advancements offer novel techniques to improve model formulation for speech applications including speaker ID, audio search, and audio content analysis. 2012 Elsevier B.V. All rights reserved.
Intuitionistic fuzzy hypergraphs with applications

Article history: Received 27 October 2011 Received in revised form 26 February 2012 Accepted 23 June 2012 Available online 6 July 2012
High Flow Nasal Oxygen Therapy: From Physiology to Clinic

INTRODUCTION Oxygen support therapy should be given to the patients with acute hypoxic respiratory insufficiency in order to provide oxygenation of the tissues until the underlying pathology improves. The inspiratory flow rate requirement of patients with respiratory insufficiency varies between 30 and 120 L/min. Low flow and high flow conventional oxygen support systems produce a maximum flow rate of 15 L/min, and FiO2 changes depending on the patient’s peak inspiratory flow rate, respiratory pattern, the mask that is used, or the characteristics of the cannula. The inability to provide adequate airflow leads to discomfort in tachypneic patients. With high-flow nasal oxygen (HFNO) cannulas, warmed and humidified air matching the body temperature can be regulated at flow rates of 5–60 L/min, and oxygen delivery varies between 21% and 100%. When HFNO, first used in infants, was reported to increase the risk of infection, its long-term use was stopped. This problem was later eliminated with the use of sterile water, and its use has become a current issue in critical adult patients as well. Studies show that HFNO treatment improves physiological parameters when compared to conventional oxygen systems. Although there are studies indicating successful applications in different patient groups, there are also studies indicating that it does not create any difference in clinical parameters, but patient comfort is better in HFNO when compared with standard oxygen therapy and noninvasive mechanical ventilation (NIMV) (1-6). In this compilation, the physiological effect mechanisms of HFNO treatment and its use in various clinical situations are discussed in the light of current studies.
Microprogrammed significance arithmetic: a perspective and feasibility study

This study is an attempt to evaluate the feasibility of microprogrammed routines for monitoring significant digits in the numerical result of digital computers in real time. The first part is tutorial and, in the second part, microprograms for two methods of significance arithmetic are designed and evaluated.
ICDAR 2015 competition on Robust Reading

Results of the ICDAR 2015 Robust Reading Competition are presented. A new Challenge 4 on Incidental Scene Text has been added to the Challenges on Born-Digital Images, Focused Scene Images and Video Text. Challenge 4 is run on a newly acquired dataset of 1,670 images evaluating Text Localisation, Word Recognition and End-to-End pipelines. In addition, the dataset for Challenge 3 on Video Text has been substantially updated with more video sequences and more accurate ground truth data. Finally, tasks assessing End-to-End system performance have been introduced to all Challenges. The competition took place in the first quarter of 2015, and received a total of 44 submissions. Only the tasks newly introduced in 2015 are reported on. The datasets, the ground truth specification and the evaluation protocols are presented together with the results and a brief summary of the participating methods.