LLukas22/scidocs huggingface dataset:
Deep Learning Approach for Brain Machine Interface

of a dissertation at the University of Miami. Dissertation supervised by Professor Abhishek Prasad. No. of pages in text. (82) Objective: Brain machine interface (BMI) or Brain Computer Interface (BCI) provides a direct pathway between the brain and an external device to help people suffering from severely impaired motor function by decoding brain activities and translating human intentions into control signals. Conventionally, the decoding pipeline for BMIs consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes the whole system difficult to be adaptive. Our goal is to create differentiable signal processing modules and plug them together to build an adaptive online system. The system could be trained with a single objective function and a single learning algorithm so that each component can be updated in parallel to increase the performance in a robust manner. We use deep neural networks to address these needs. Main Results: We predicted the finger trajectory using Electrocorticography (ECoG) signals and compared results for the Least Angle Regression (LARS), Convolutional Long Short Term Memory Network (Conv-LSTM), Random Forest (RF), and a pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. We also estimated the source connectivity of the brain signals using a Recurrent Neural Network (RNN) and it correctly estimated the order and sparsity level of the underlying Multivariate Auto-regressive process (MVAR). The time course of the source connectivity was also recovered. Significance: We replace the conventional signal processing pipeline with differentiable modules so that the whole BMI system is adaptive. The study of the decoding system demonstrated a model for BMI that involved a convolutional and recurrent neural network. It integrated the feature extraction pipeline into the convolution and pooling layer and used Long Short Term Memory (LSTM) layer to capture the state transitions. The decoding network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning. The study of the source connectivity estimation demonstrated a generative RNN model that can estimate the un-mixing matrix and the MVAR coefficients of the source activity at the same time. Our method addressed the issue of estimation and inference of the non-stationary MVAR coefficients and the un-mixing matrix in the presence of non-gaussian noise. More importantly, this model can be easily plugged into the BMI decoding system as a differentiable feature extraction module.
Effects of Aerobic Exercise vs. Resistance Training on Endothelial Function in Women with Type 2 Diabetes Mellitus

BACKGROUND
There is controversy over whether aerobic or resistance exercise is more effective for improving endothelial function in type 2 diabetes mellitus (T2DM). This study was aimed to investigate the effects of an aerobic and resistance training program on endothelial function, and the influences of glycemic control, body weight changes, and aerobic capacity in T2DM.


METHODS
Total 40 overweight women with T2DM were assigned into 3 groups: an aerobic exercise group (AEG, n=13), resistance exercise group (REG, n=12), and control group (CG, n=15), and followed either brisk walking for the AEG or resistance band training for the REG, 60 minutes per day, 5 days per week for 12 weeks with monitoring daily activity using accelerometers. We assessed endothelial function by flow-mediated dilation (FMD), and aerobic capacity by oxygen uptake at anaerobic threshold (AT_VO(2)) at baseline and following training program.


RESULTS
The mean participants' age was 57.0±6.8 years, and body mass index (BMI) was 27.0±2.3 kg/m(2). After intervention, FMD increased by 2.2±1.9% in AEG, which differed from REG and CG (P=0.002), despite of decreased body weight (BW) in both AG and RG (2.8±2.5%, P=0.002; 1.6±2.0%, P=0.017, respectively). A significant increased AT_VO(2) and decreased HbA1c were found only in AEG. In all participants, FMD was changed with the significant relations to the AT_VO(2) (r=0.348, P=0.035), but not to HbA1c levels or BW.


CONCLUSION
Aerobic exercise appears to be more beneficial than resistance exercise for improving endothelial function in T2DM. In addition, aerobic capacity could be a better predictor of changes in FMD than BW and glycemic control.
The Deep Structure of Confucianism: A social psychological approach

The deep structure of Confucianism is identi ed through structuralist analysis in order to provide a conceptual framework for conducting social psychological research in Chinese society. Through understanding and imitating the Way of Heaven (tiendao), Confucians constructed the Way of Humanity (rendao), which consists of two aspects; ethics for ordinary people and ethics for scholars. Ethics for ordinary people adopts the principle of Respecting the Superior for procedural justice and the principle of Favouring the Intimate for distributive justice; the person who occupies the superior position should play the role of decision-maker and should allocate resources by favouring intimate relationships. Because Confucian cosmology suggests that the Way of Humanity corresponds to the Way of Heaven, Confucians required individuals to cultivate themselves with the Way of Humanity. Ethics for scholars further endows Confucian disciples with the mission of bene ting the whole society with the Way of Humanity. An understanding of Confucian cultural traditions is crucial to a comprehensive understanding of Chinese social behaviour. The purpose of this paper is to integrate all of my past research analysing the deep structure of Confucianism from the perspective of social psychology in order to further understanding of Chinese social behaviour. The bulk of my analysis of the deep structure of Confucianism has been published in two works, Confucianism and East Asian Modernization and Knowledge and Action. In my article ‘Chinese relationalism: theoretical construction and methodological considerations’,2 I employed the philosophy of realism to construct a theoretical model I call Face and Favour.3 Using this model, I analysed the deep structure of Confucian ideas in terms of structuralism, which led to the construction of a series of theories on Chinese relationalism. As discussed in my article ‘The discontinuity hypothesis of modernity and constructive realism’,4 the Chinese traditional worldview of achieving harmony is achieved through maintaining homeostasis within the human body, between humans and the social system, and between humans and nature.5 Of these three levels, maintenance of homeostasis between humans and the social system draws the most interest from social psychologists studying Chinese social behaviour, and is the focus of this paper. The deep structure of Confucianism is composed of  ve interrelated parts: conceptions of destiny, a model of mind, ethics for ordinary people, practical methods of self-cultivation and ethics for scholars. The Confucian Way of Humanity consists of two aspects: ethics for ordinary people, and ethics for scholars. Because Confucians believe that the Way of Humanity corresponds to the Way of Heaven, every person is obligated to practice ethics for ordinary people through self-cultivation. Confucians ISSN 0955-2367 print/ISSN 1469-2961 online/01/030179-26 Ó 2001 Taylor & Francis Ltd DOI: 10.1080/09552360120116928
Tableau Methods for Modal and Temporal Logics

This document is a complete draft of a chapter by Rajeev Gor e on \Tableau Methods for Modal and Temporal Logics" which is part of the \Handbook of Tableau Methods", edited
Distributed Force-Directed Graph Layout and Visualization

While there exist many interactive tools for the visualization of small graphs and networks, these tools do not address the fundamental problems associated with the visualization of large graphs. In particular, larger graphs require much larger display areas (e.g., display walls) to reduce visual clutter, allowing users to determine the structure of large graphs. Moreover, the layout algorithms employed by these graph visualization tools do not scale to larger graphs, thereby forcing users into a batchoriented process of generating layouts offline and later viewing of static graph images. In this paper, we present a parallel graph layout algorithm based on the Fruchterman-Reingold force-directed layout algorithm and demonstrate its implementation in a distributed rendering environment. The algorithm uses available distributed resources for both compute and rendering tasks, animating the graph as the layout evolves. We evaluate the algorithm for scalability and interactivity and discuss variations that minimize communication for specific types of graphs and applications.
OCR Error Correction Using Character Correction and Feature-Based Word Classification

This paper explores the use of a learned classifier for post-OCR text correction. Experiments with the Arabic language show that this approach, which integrates a weighted confusion matrix and a shallow language model, improves the vast majority of segmentation and recognition errors, the most frequent types of error on our dataset.
Efficacy and safety of luseogliflozin monotherapy in Japanese patients with type 2 diabetes mellitus: a 12-week, randomized, placebo-controlled, phase II study.

OBJECTIVE
Luseogliflozin is a novel sodium glucose cotransporter 2 inhibitor for type 2 diabetes mellitus (T2DM) treatment. An exploratory Phase II study was conducted to assess the efficacy and safety of several doses of luseogliflozin in Japanese T2DM patients.


PATIENTS AND METHODS
Japanese T2DM patients aged 20-74 years with hemoglobin A1c (HbA1c) of 6.9-10.5%, fasting plasma glucose (FPG) ≥126 mg/dL and on diet therapy were randomized in a double-blind manner to receive luseogliflozin (0.5, 2.5, or 5 mg) or placebo once daily for 12 weeks (n = 61, 61, 61, and 56, respectively). The primary endpoint was the change in HbA1c from baseline to end of treatment. Other endpoints included FPG, 2 h postprandial plasma glucose (PPG) in a meal tolerance test (MTT), and body weight. Drug safety was also assessed.


TRIAL REGISTRATION
Japan Pharmaceutical Information Center (identifier: JapicCTI-090908).


RESULTS
Changes in HbA1c from baseline to end of treatment were -0.36, -0.62, and -0.75% in the 0.5, 2.5, and 5 mg luseogliflozin groups, respectively, versus +0.06% in the placebo group (all P < 0.001). The reductions in FPG and 2 h-PPG in the MTT were also significantly greater in the luseogliflozin groups (all P < 0.01) without increases in insulin levels from baseline. Luseogliflozin reduced body weight at all doses. There were no significant differences in the incidences of adverse events among groups. Most adverse events were mild in severity. There were no serious adverse events.


CONCLUSIONS
Although this was a small-scale study with a short duration, all tested doses of luseogliflozin significantly improved glycemic control, reduced body weight, and were well tolerated in Japanese T2DM patients over the 12-week treatment period.
Case Based Reasoning: Case Representation Methodologies

Case Based Reasoning (CBR) is an important technique in artificial intelligence, which has been applied to various kinds of problems in a wide range of domains. Selecting case representation formalism is critical for the proper operation of the overall CBR system. In this paper, we survey and evaluate all of the existing case representation methodologies. Moreover, the case retrieval and future challenges for effective CBR are explained. Case representation methods are grouped in to knowledge-intensive approaches and traditional approaches. The first group overweight the second one. The first methods depend on ontology and enhance all CBR processes including case representation, retrieval, storage, and adaptation. By using a proposed set of qualitative metrics, the existing methods based on ontology for case representation are studied and evaluated in details. All these systems have limitations. No approach exceeds 53% of the specified metrics. The results of the survey explain the current limitations of CBR systems. It shows that ontology usage in case representation needs improvements to achieve semantic representation and semantic retrieval in CBR system. Keywords—Case based reasoning; Ontological case representation; Case retrieval; Clinical decision support system; Knowledge management
Straight Talk on Anti-Spoofing Securing the Future of PNT Disruption

GPS spoofing has become a hot topic. At the 2011 Institute of Navigation (ION) GNSS conference, 18 papers discussed spoofing, compared with the same number over the past decade. ION-GNSS also featured its first panel session on anti-spoofing, called “Improving Security of GNSS Receivers,” which offered six security experts a forum to debate the most promising anti-spoofing technologies. The spoofing threat has also drawn renewed U.S. government scrutiny since the initial findings of the 2001 Volpe Report. In November 2010, the U.S. Position Navigation and Timing National Executive Committee requested that the U.S. Department of Homeland Security (DHS) conduct a comprehensive risk assessment on the use of civil GPS. In February 2011, the DHS Homeland Infrastructure Threat and Risk Analysis Center began its investigation in conjunction with subject-matter experts in academia, finance, power, and telecommunications, among others. Their findings will be summarized in two forthcoming reports, one on the spoofing and jamming threat and the other on possible mitigation techniques. The reports are anticipated to show that GPS disruption due to spoofing or jamming could have serious economic consequences. Effective techniques exist to defend receivers against spoofing attacks. This article summarizes state-of-the-art anti-spoofing techniques and suggests a path forward to equip civil GPS receivers with these defenses. We start with an analysis of a typical civil GPS receiver’s response to our laboratory’s powerful spoofing device. This will Straight Talk on Anti-Spoofing Securing the Future of PNT
Aspirin versus heparin to prevent myocardial infarction during the acute phase of unstable angina.

BACKGROUND
Antiplatelet therapy with aspirin and antithrombotic therapy with heparin both prevent the complications of unstable angina; however, no definitive data exist on the relative clinical efficacy of the two drugs.


METHODS AND RESULTS
Aspirin (325 mg bid) or heparin (5000-U intravenous bolus followed by a perfusion titrated to the APTT) were compared in a double-blind randomized trial of 484 patients in two cohorts enrolled sequentially. The study was initiated at admission to hospital at a mean of 8.3 +/- 7.8 hours after the last episode of pain. End points were assessed 5.7 +/- 3.3 days later, when the decision for long-term management was made. Myocardial infarction occurred in 2 (0.8%) of the 240 patients randomized to heparin and in 9 (3.7%) of the 244 randomized to aspirin (P = .035), an odds ratio of 0.22 and a risk difference of 2.9% (95% confidence limits, 0.3% to 5.6%) with heparin. The only death resulted from a myocardial infarction in an aspirin patient. Survival curves with Cox logistic regression analysis showed that the improvement in survival without myocardial infarction with heparin (P = .035) was independent of other baseline characteristics.


CONCLUSIONS
This study documents that heparin prevents myocardial infarction better than aspirin during the acute phase of unstable angina.
THE IMPORTANCE OF PAY IN EMPLOYEE MOTIVATION : DISCREPANCIES BETWEEN WHAT PEOPLE SAY AND WHAT THEY DO

Rynes, Colbert, and Brown (2002) presented the following statement to 959 members of the Society for Human Resource Management (SHRM): “Surveys that directly ask employees how important pay is to them are likely to overestimate pay’s true importance in actual decisions” (p. 158). If our interpretation (and that of Rynes et al.) of the research literature is accurate, then the correct true-false answer to the above statement is “false.” In other words, people are more likely to underreport than to overreport the importance of pay as a motivational factor in most situations. Put another way, research suggests that pay is much more important in people’s actual choices and behaviors than it is in their self-reports of what motivates them, much like the cartoon viewers mentioned in the quote above. Yet, only 35% of the respondents in the Rynes et al. study answered in a way consistent with research findings (i.e., chose “false”). Our objective in this article is to show that employee surveys regarding the importance of various factors in motivation generally produce results that are inconsistent with studies of actual employee behavior. In particular, we focus on well-documented findings that employees tend to say that pay THE IMPORTANCE OF PAY IN EMPLOYEE MOTIVATION: DISCREPANCIES BETWEEN WHAT PEOPLE SAY AND WHAT THEY DO
Redefining the therapeutic objective in psoriatic patients candidates for biological therapy.

The advances in psoriasis management currently allow achieving a good control of the disease. In particular, with the latest developed molecules, available evidence suggests that it is possible to pose an ambitious therapeutic goal, such as a Dermatology Life Quality Index 0/1, a Physician Global Assessment 0/1, or a Psoriasis Area and Severity Index 90/100 response. However, patients often fail to achieve the complete clearance of their cutaneous lesions or the improvement of disease factors that impair their quality of life. To optimize the treatment of psoriasis, it is not enough to define precisely the therapeutic objective, but also to adapt the therapeutic strategy to make the necessary modifications in case of not achieving it at the time point (at the end of the induction phase, or every 3-6 months) to be agreed with the patient (the so-called treat-to-target approach). In the present report, based on the Delphi methodology, 11 dermatologists from the Spanish Psoriasis Group addressed key issues that could be involved in the achievement and maintenance of the therapeutic goals of patients with moderate to severe psoriasis. The document provides 27 consensus statements intended to support clinical decision-making by healthcare professionals for patients who might be candidates to receive biologic therapy.
Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation

Recently, there has been a dramatic proliferation in the number of blogs; however, little is published about what motivates people to participate in blog activities. Based on the theory of reasoned action, we developed a model involving technology acceptance, knowledge sharing and social influences. A survey of 212 blog participants found strong support for the model. The results indicated that ease of use and enjoyment, and knowledge sharing (altruism and reputation) were positively related to attitude toward blogging, and accounted for 78% of the variance. On the other hand, social factors (community identification) and attitude toward blogging significantly influenced a blog participant’s intention to continue to use blogs. Together they explain 83% of the variance of intention to blog. # 2007 Elsevier B.V. All rights reserved. www.elsevier.com/locate/im Available online at www.sciencedirect.com Information & Management 45 (2008) 65–74
Mixture contrast limited adaptive histogram equalization for underwater image enhancement

Within the last decades, improving the quality of an underwater image has received considerable attention due to poor visibility of the image which is caused by physical properties of the water medium. This paper presents a new method called mixture Contrast Limited Adaptive Histogram Equalization (CLAHE) color models that specifically developed for underwater image enhancement. The method operates CLAHE on RGB and HSV color models and both results are combined together using Euclidean norm. The underwater images used in this study were taken from Redang Island and Bidong Island in Terengganu, Malaysia. Experimental results show that the proposed approach significantly improves the visual quality of underwater images by enhancing contrast, as well as reducing noise and artifacts.
The Intuition Behind Black-Litterman Model Portfolios

■ To do this, we use examples to show the difference between the traditional meanvariance optimization process and the Black-Litterman process. We show that the mean-variance optimization process, while academically sound, can produce results that are extreme and not particularly intuitive. In contrast, we show that the optimal portfolios generated by the Black-Litterman process have a simple, intuitive property:
A High-Precision Dual-Servo Stage Using Halbach Linear Active Magnetic Bearings

In this paper, a high-precision dual-servo stage with a magnetically levitated fine stage is described. For magnetic levitation, a Halbach linear active magnetic bearing (HLAMB) is used. The HLAMB has two functions: gravity compensation and actively control of vertical motion. To implement these functions, the HLAMB utilizes permanent magnet arrays and Lorentz coils. The fine stage has positioning capabilities with 6 DOF due to four HLAMBs and four voice coil motors (VCM). The HLAMBs control out-of-plane motions, and the VCM control in-plane motions. The fine stage achieves high-precision position feedback using laser interferometers and capacitive sensors. The coarse stage has an H-type structure that can carry the fine stage 300 mm by 300 mm along the x - and y-axes. Positioning and scanning performances are verified by the experimental results. It has ±10 and ±15 nm in-position stability in the x- and y-axes, respectively. At the scan with 10 mm/s constant velocity, ±1 nm mean tracking error and 4.7 nm jitter were obtained.
Religious affiliation and suicide attempt.

OBJECTIVE
Few studies have investigated the association between religion and suicide either in terms of Durkheim's social integration hypothesis or the hypothesis of the regulative benefits of religion. The relationship between religion and suicide attempts has received even less attention.


METHOD
Depressed inpatients (N=371) who reported belonging to one specific religion or described themselves as having no religious affiliation were compared in terms of their demographic and clinical characteristics.


RESULTS
Religiously unaffiliated subjects had significantly more lifetime suicide attempts and more first-degree relatives who committed suicide than subjects who endorsed a religious affiliation. Unaffiliated subjects were younger, less often married, less often had children, and had less contact with family members. Furthermore, subjects with no religious affiliation perceived fewer reasons for living, particularly fewer moral objections to suicide. In terms of clinical characteristics, religiously unaffiliated subjects had more lifetime impulsivity, aggression, and past substance use disorder. No differences in the level of subjective and objective depression, hopelessness, or stressful life events were found.


CONCLUSIONS
Religious affiliation is associated with less suicidal behavior in depressed inpatients. After other factors were controlled, it was found that greater moral objections to suicide and lower aggression level in religiously affiliated subjects may function as protective factors against suicide attempts. Further study about the influence of religious affiliation on aggressive behavior and how moral objections can reduce the probability of acting on suicidal thoughts may offer new therapeutic strategies in suicide prevention.