LLukas22/scidocs huggingface dataset:
PCT: Partial Co-Alignment of Social Networks

People nowadays usually participate in multiple online social networks simultaneously to enjoy more social network services. Besides the common users, social networks providing similar services can also share many other kinds of information entities, e.g., locations, videos and products. However, these shared information entities in different networks are mostly isolated without any known corresponding connections. In this paper, we aim at inferring such potential corresponding connections linking multiple kinds of shared entities across networks simultaneously. Formally, the problem is referred to as the network “Partial Co-alignmenT” (PCT) problem. PCT is an important problem and can be the prerequisite for many concrete cross-network applications, like social network fusion, mutual information exchange and transfer. Meanwhile, the PCT problem is also very challenging to address due to various reasons, like (1) the heterogeneity of social networks, (2) lack of training instances to build models, and (3) one-to-one constraint on the correspondence connections. To resolve these challenges, a novel unsupervised network alignment framework, UNICOAT (UNsupervIsed COncurrent AlignmenT)), is introduced in this paper. Based on the heterogeneous information, UNICOAT transforms the PCT problem into a joint optimization problem. To solve the objective function, the one-to-one constraint on the corresponding relationships is relaxed, and the redundant non-existing corresponding connections introduced by such a relaxation will be pruned with a novel network co-matching algorithm proposed in this paper. Extensive experiments conducted on real-world coaligned social network datasets demonstrate the effectiveness of UNICOAT in addressing the PCT problem.
A Course in Probability Theory

In recent years books on probability theory have mushroomed. The two books under review have this in common : they are concerned with probability theory proper, rather than with its foundations (like the recent elegant but austere book by Neveu), and they give a balanced view of the theory rather than dwelling at length on some specialized topics. What is probability theory? Chung's spirited preface at first tells us what it is not: the "specious utterance" that "probability is just a chapter of measure theory" finds no more favor with him than the use of probability "as a front for certain types of analysis such as combinatorial, Fourier, functional and whatnot." Elsewhere he says about the same utterance that it is "not so much false as it is fatuous, as it would be to say that number theory is just a chapter of algebra." Thus over the years Professor Chung continues his disagreement with Professor Doob who in his Stochastic processes writes: "Probability is simply a branch of measure theory, with its own special emphasis and field of application." On the positive side Professor Chung remarks in the preface of his book: "The random walks in Chapter 8 illustrate well the way probability theory transforms other parts of mathematics. I t does so by introducing the trajectories of the process, thereby turning what was static into a dynamic structure." As for Dr. Breiman, without defining probability he tells us about its right and left hand. "On the right is the rigorous foundational work using the tools of measure theory. The left hand i thinks probabilistically/ reduces problems to gambling situations, coin-tossing, motions of a physical particle." Breiman acknowledges M. Loève as his teacher of the first aspect of probability (and D. Blackwell as the teacher of the second) and Professor Loève in his treatise on the subject (p. 170) defines a probabilistic property as one which can be described in terms of distribution functions. Professor Neveu (Preface, op. cit.) strongly disagrees: "Attempts have been made, it is true, to treat convergence problems of probability theory within the restricted framework of the study of distribution functions; but this 1 J. Neveu, Mathematical foundations of the calculus of probability, Holden-Day, San Francisco, Calif., 1965. 2 In the review of A. Rényi's textbook, Bull. Amer. Math. Soc. 70 (1964), 225.
Serum beta2-microglobulin and immunoglobulin levels in young hemodialysis patients

 Amyloidosis is a complication of long-term hemodialysis treatment. The major histological feature of hemodialysis-associated amyloidosis (HAA) is the deposition of amyloid fibrils in the affected lesions, due, in part, to elevated serum β2-microglobulin (β2M) levels. In vitro studies reveal that serum immunoglobulin light and heavy chains co-deposit with β2M in tissues affected by HAA. Only one study of HAA has been performed in young dialysis patients. We therefore assessed risk factors for HAA in a group (n=30) of young (18.7±0.9 years) patients receiving chronic, uninterrupted hemodialysis using cellulose acetate membranes. All patients initiated dialysis before reaching 18 years of age. The pre-dialysis serum β2M level was 49.7±3.9 mg/l (normal 0–2.4 mg/l). Since serum albumin was normal (4.3±0.1 mg/dl) and serum protein/albumin was elevated (1.7±0.0, normal 1.2–1.5), indicating increased circulating protein, we assayed immunoglobulins in the same patients. The serum immunoglobulin levels (expressed as a percentage of the total level of serum proteins) were elevated (21.3±0.9%, normal 11.1%–21.0%). The Kt/v was 1.37±0.03, suggesting that the high levels of serum β2M and immunoglobulins were not due to inadequate dialysis in these patients. Patients with residual renal function (Kr) did display significantly lower serum levels of β2M (33.2±2.3, P=0.03). Furthermore, improved clearance of β2M correlated with higher values of Kr (r=0.914). In contrast, serum levels of immunoglobulin (22.6±3.7, P=0.5) were unaffected by Kr. In addition, there was no correlation between older age at onset of dialysis and serum levels of either β2M (r=0.107) or immunoglobulins (r=0.321). Finally, the length of time on dialysis had no effect on serum levels of either β2M (r=0.105) or immunoglobulins (r=0.092). Taken together, these results indicate that young hemodialysis patients may be at risk for HAA.
Intelligent simulation-based lot scheduling of photolithography toolsets in a wafer fabrication facility

Scheduling of a semiconductor manufacturing facility is one of the most complex tasks encountered. Confronted with a high technology product market, semiconductor manufacturing is increasingly more dynamic and competitive in the introduction of new products in shorter time intervals. Photolithography, being one of the processes repeated often, is a fabrication bottleneck. Lot scheduling within photolithography is a challenging activity where substantial improvements in factory performance can be made. The proposed scheduling methodology integrates two common approaches, simulation and artificial intelligence. Using detailed simulation modeling within a structured modeling method, a comprehensive model to characterize the photolithography process was developed. An artificial intelligence scheduler was then developed and integrated with the model with the goal of reducing Work-In-Process (WIP), setup time, and throughput time. The results have shown a significant improvement in lot cycle time as well as tool utilization, improved the throughput time by an average of 15% and is currently in use for scheduling the photolithography process.
The Eval That Men Do - A Large-Scale Study of the Use of Eval in JavaScript Applications

Transforming text into executable code with a function such as JavaScript’s eval endows programmers with the ability to extend applications, at any time, and in almost any way they choose. But, this expressive power comes at a price: reasoning about the dynamic behavior of programs that use this feature becomes challenging. Any ahead-of-time analysis, to remain sound, is forced to make pessimistic assumptions about the impact of dynamically created code. This pessimism affects the optimizations that can be applied to programs and significantly limits the kinds of errors that can be caught statically and the security guarantees that can be enforced. A better understanding of how eval is used could lead to increased performance and security. This paper presents a large-scale study of the use of eval in JavaScript-based web applications. We have recorded the behavior of 337 MB of strings given as arguments to 550,358 calls to the eval function exercised in over 10,000 web sites. We provide statistics on the nature and content of strings used in eval expressions, as well as their provenance and data obtained by observing their dynamic behavior. eval is evil. Avoid it. eval has aliases. Don’t use them. —Douglas Crockford
Real-time ocular artifact suppression using recurrent neural network for electro-encephalogram based brain-computer interface

The paper presents an adaptive noise canceller (ANC) filter using an artificial neural network for real-time removal of electro-oculogram (EOG) interference from electro-encephalogram (EEG) signals. Conventional ANC filters are based on linear models of interference. Such linear models provide poorer prediction for biomedical signals. In this work, a recurrent neural network was employed for modelling the interference signals. The eye movement and eye blink artifacts were recorded by the placing of an electrode on the forehead above the left eye and an electrode on the left temple. The reference signal was then generated by the data collected from the forehead electrode being added to data recorded from the temple electrode. The reference signal was also contaminated by the EEG. To reduce the EEG interference, the reference signal was first low-pass filtered by a moving averaged filter and then applied to the ANC. Matlab Simulink was used for real-time data acquisition, filtering and ocular artifact suppression. Simulation results show the validity and effectiveness of the technique with different signal-to-noise ratios (SNRs) of the primary signal. On average, a significant improvement in SNR up to 27 dB was achieved with the recurrent neural network. The results from real data demonstrate that the proposed scheme removes ocular artifacts from contaminated EEG signals and is suitable for real-time and short-time EEG recordings.
Effect of virtual reality training on laparoscopic surgery: randomised
controlled trial

OBJECTIVE
To assess the effect of virtual reality training on an actual laparoscopic operation.


DESIGN
Prospective randomised controlled and blinded trial.


SETTING
Seven gynaecological departments in the Zeeland region of Denmark.


PARTICIPANTS
24 first and second year registrars specialising in gynaecology and obstetrics.


INTERVENTIONS
Proficiency based virtual reality simulator training in laparoscopic salpingectomy and standard clinical education (controls).


MAIN OUTCOME MEASURE
The main outcome measure was technical performance assessed by two independent observers blinded to trainee and training status using a previously validated general and task specific rating scale. The secondary outcome measure was operation time in minutes.


RESULTS
The simulator trained group (n=11) reached a median total score of 33 points (interquartile range 32-36 points), equivalent to the experience gained after 20-50 laparoscopic procedures, whereas the control group (n=10) reached a median total score of 23 (22-27) points, equivalent to the experience gained from fewer than five procedures (P<0.001). The median total operation time in the simulator trained group was 12 minutes (interquartile range 10-14 minutes) and in the control group was 24 (20-29) minutes (P<0.001). The observers' inter-rater agreement was 0.79.


CONCLUSION
Skills in laparoscopic surgery can be increased in a clinically relevant manner using proficiency based virtual reality simulator training. The performance level of novices was increased to that of intermediately experienced laparoscopists and operation time was halved. Simulator training should be considered before trainees carry out laparoscopic procedures.


TRIAL REGISTRATION
ClinicalTrials.gov NCT00311792.
Clinical validation of the watershed sign as a marker for neuropsychiatric systemic lupus erythematosus.

OBJECTIVE
To study the relationship between single-photon-emission computed tomography (SPECT) brain imaging and neuropsychiatric signs/symptoms in a cohort of patients with systemic lupus erythematosus (SLE), analyzed using a stereotactic surface projection (SSP) technique.


METHODS
Thirty-seven SLE patients were referred for 99mTc-ethyl cysteinate dimer SPECT brain imaging because of neuropsychiatric signs/symptoms. Nineteen normal controls were studied with the identical protocol. Reconstructed images were computed and Z scores were calculated using the SSP technique with the 2-sample t-tests comparing normal controls with SLE patients, and patients with mild cognitive dysfunction with those with severe cognitive dysfunction. The clinical characteristics of SLE patients were collected by retrospective chart review and categorized according to American College of Rheumatology case definitions for neuropsychiatric SLE. Cognitive dysfunction was rated by the treating physician on a scale of 0-3.


RESULTS
Thirty of 37 SLE patients had abnormal SPECT results. SLE patients had reduced perfusion in the watershed areas of the frontal lobes bilaterally compared with controls. Additionally, SLE patients with severe cognitive dysfunction had more severe perfusion deficits than those with mild cognitive dysfunction. In some patients with severe cognitive dysfunction, the watershed areas had Z scores > or =4 SDs below controls.


CONCLUSION
A convenience sample of patients with SLE and neuropsychiatric signs/symptoms demonstrated reduced perfusion in the watershed areas of the frontal lobes on SPECT scanning analyzed by the SSP technique. The severity of findings correlated with severity of cognitive dysfunction. The area of the brain affected is one that is susceptible to ischemia.
Dose Escalation Study of Intravenous Estramustine Phosphate in Combination with Paclitaxel and Carboplatin in Patients with Advanced Prostate Cancer 1

Purpose: The purpose is to determine a safe weekly dose of i.v. estramustine phosphate (EMP) to combine with weekly paclitaxel and monthly carboplatin in patients with advanced prostate cancer. Experimental Design: Patients with advanced prostate cancer (castrate and noncastrate) were administered escalating doses of weekly 1-h infusion of i.v. EMP (500–10001500 mg/m) in combination with weekly paclitaxel (100 mg/m over 1 h) and i.v. carboplatin (area under the curve 6 mg/ml-min every 4 weeks). Four weeks of therapy were considered one cycle. In the first three cohorts, EMP was given i.v. 3 h before paclitaxel. Cohorts 4 and 5 reversed the administration order: EMP (doses 1000–1500 mg/m) was given immediately after the end of paclitaxel infusion. Plasma levels of EMP and its metabolites, estramustine and estromustine, were monitored at time 0, at 120 min, and approximately at 20, 21, and 168 h from the start of EMP infusion. Paclitaxel concentrations were determined at basal (0), 30, 60, 90, and 120 min and 18 h after the start of paclitaxel infusion, and a concentration-time curve was estimated. Pharmacokinetic evaluation was performed in cycles 1 and 2 during the first week of therapy. Results: Nineteen patients were entered on the initial three dose levels (cohorts 1–3). Dose-limiting transient hepatic toxicity was encountered in cohort 3 (EMP 1500 mg/m). An additional 13 patients were treated with paclitaxel (100 mg/m) first, followed by i.v. EMP at 1000 mg/m (cohort 4), and 1500 mg/m (cohort 5). No dose-limiting toxicities were seen, and cohort 5 was determined safe for Phase II studies. Thromboembolic events were observed in 9% of patients (no prophylactic coumadin was used). Plasma concentrations of EMP and metabolites increased proportionally with dose. In all cohorts, there was a slight decrease in EMP and estramustine plasma concentrations between cycles 1 and 2. Although not significant, higher levels of estromustine at cycle 2 were observed in comparison to cycle 1. Decreased clearance of paclitaxel leading to higher than expected paclitaxel plasma concentrations was observed during the first cycle of therapy. Paclitaxel plasma concentrations were lower during cycle 2. In 17 patients with androgen-independent disease, 59% had >50% posttherapy decline in PSA and 22% showed measurable disease regression. Conclusions: The regimen of weekly i.v. EMP in combination with paclitaxel and carboplatin can be safely administered with hepatic toxicity being transient and reversible. Pharmacokinetic results suggest that EMP competitively inhibits the biotransformation of paclitaxel after the first administration. This effect is counterbalanced, after repeated administrations, by a possible induction of the metabolic system caused by EMP. Phase II testing is ongoing to evaluate the efficacy of this combination.
A Spectral Algorithm for Latent Junction Trees

Latent variable models are an elegant framework for capturing rich probabilistic dependencies in many applications. However, current approaches typically parametrize these models using conditional probability tables, and learning relies predominantly on local search heuristics such as Expectation Maximization. Using tensor algebra, we propose an alternative parameterization of latent variable models (where the model structures are junction trees) that still allows for computation of marginals among observed variables. While this novel representation leads to a moderate increase in the number of parameters for junction trees of low treewidth, it lets us design a local-minimum-free algorithm for learning this parameterization. The main computation of the algorithm involves only tensor operations and SVDs which can be orders of magnitude faster than EM algorithms for large datasets. To our knowledge, this is the first provably consistent parameter learning technique for a large class of low-treewidth latent graphical models beyond trees. We demonstrate the advantages of our method on synthetic and real datasets.
Issues Associated With the Use of Semantic Web Technology in Knowledge Acquisition for Clinical Decision Support Systems: Systematic Review of the Literature

BACKGROUND
Knowledge-based clinical decision support system (KB-CDSS) can be used to help practitioners make diagnostic decisions. KB-CDSS may use clinical knowledge obtained from a wide variety of sources to make decisions. However, knowledge acquisition is one of the well-known bottlenecks in KB-CDSSs, partly because of the enormous growth in health-related knowledge available and the difficulty in assessing the quality of this knowledge as well as identifying the "best" knowledge to use. This bottleneck not only means that lower-quality knowledge is being used, but also that KB-CDSSs are difficult to develop for areas where expert knowledge may be limited or unavailable. Recent methods have been developed by utilizing Semantic Web (SW) technologies in order to automatically discover relevant knowledge from knowledge sources.


OBJECTIVE
The two main objectives of this study were to (1) identify and categorize knowledge acquisition issues that have been addressed through using SW technologies and (2) highlight the role of SW for acquiring knowledge used in the KB-CDSS.


METHODS
We conducted a systematic review of the recent work related to knowledge acquisition MeM for clinical decision support systems published in scientific journals. In this regard, we used the keyword search technique to extract relevant papers.


RESULTS
The retrieved papers were categorized based on two main issues: (1) format and data heterogeneity and (2) lack of semantic analysis. Most existing approaches will be discussed under these categories. A total of 27 papers were reviewed in this study.


CONCLUSIONS
The potential for using SW technology in KB-CDSS has only been considered to a minor extent so far despite its promise. This review identifies some questions and issues regarding use of SW technology for extracting relevant knowledge for a KB-CDSS.
Ankle injuries and ankle strength, flexibility, and proprioception in college basketball players.

OBJECTIVE
To determine if ankle muscular strength, flexibility and proprioception can predict ankle injury in college basketball players and to compare ankle injury rates in female and male players.


DESIGN AND SETTING
In this prospective, correlational study, subjects were tested at the start of the competitive season for ankle joint muscle strength, flexibility, and proprioception. The first ankle injury for each subject was recorded on an injury report form, and the data were analyzed to determine if any of these preseason measurements predicted future injury. The setting was a competitive 9-week season for four women's and four men's college basketball teams.


SUBJECTS
A convenience sample of 31 female and 11 male college basketball players.


MEASUREMENTS
Subjects were tested for ankle dorsiflexion range of motion, various measures of ankle proprioception, and isokinetic peak torque of ankle dorsiflexion-plantar flexion and eversion-inversion at 30 degrees /sec and 180 degrees /sec before the start of the conference basketball seasons. Data were analyzed using a series of multiple regression equations to determine the variance in ankle injury attributed to each variable.


RESULTS
Various measures of proprioception predicted left ankle injury in all subjects (p < .05), while ankle strength and flexibility measures failed to account for additional variance. There was no statistically significant difference in ankle injury rate between women and men.


CONCLUSIONS
Ankle joint proprioceptive deficits can be used to predict ankle injury, but further research is needed to identify other sources of variance. In our study, ankle injury rate was similar in female and male college basketball players.
Face recognition: face in video, age invariance, and facial marks

Face Recognition: face in video, age invariance, and facial marks By Unsang Park Automatic face recognition has been extensively studied over the past decades in various domains (e.g., 2D, 3D, and video) resulting in a dramatic improvement. However, face recognition performance severely degrades under pose, lighting and expression variations, occlusion, and aging. Pose and lighting variations along with low image resolutions are major sources of degradation of face recognition performance in surveillance video. We propose a video-based face recognition framework using 3D face modeling and Pan-Tilt-Zoom (PTZ) cameras to overcome the pose/lighting variations and low resolution problems. We propose a 3D aging modeling technique and show how it can be used to compensate for age variations to improve face recognition performance. The aging modeling technique adapts view invariant 3D face models to the given 2D face aging database. We also propose an automatic facial mark detection method and a fusion scheme that combines the facial mark matching with a commercial face recognition matcher. The proposed approach can be used i) as an indexing scheme for a face image retrieval system and ii) to augment global facial features to improve the recognition performance. Experimental results show i) high recognition accuracy (>99%) on a large scale video data (>200 subjects), ii) ∼10% improvement in recognition accuracy using the proposed aging model, and iii) ∼0.94% improvement in the recognition accuracy by utilizing facial marks. Dedicated to my sweet heart, son, and parents.