LLukas22/scidocs huggingface dataset:
Effects of exercise training on circulating high molecular weight adiponectin and adiponectin oligomer composition: a randomized controlled trial.

AIM
To determine the effects of exercise training on total and high molecular weight (HMW) adiponectin and adiponectin oligomeric distribution.


METHODS
A randomized parallel-design study (n=53; 40 women and 13 men; age range, 32?65 years) was conducted at a fitness club between April 2006 and July 2007. Participants were randomly assigned to the exercise (n=26) or control (n=27) group and received exercise training for 70 min 2 times per week for 12 weeks and exercise advice at the baseline, respectively. The primary outcomes were changes in total adiponectin, HMW adiponectin and percentage of HMW adiponectin.


RESULTS
Muscle strength improved in the exercise group but remained stable in the control group. Body weight and BMI were not modified by exercise training. After 12 weeks, there were no differences between groups in total adiponectin levels, HMW adiponectin levels, or percentage of HMW adiponectin.


CONCLUSION
In the absence of weight loss, twice-weekly exercise training does not change HMW adiponectin levels or the adiponectin oligomer composition.
Vascular disrupting therapy-induced mobilization of circulating endothelial progenitor cells.

Vascular disrupting therapy-induced mobilization of circulating endothelial progenitor cells Antivascular therapies are currently intensively studied approaches in clinical oncology. Low molecular weight vascular disrupting agents (VDA) aim to cause rapid and selective shutdown of the established tumor vasculature, leading to massive cancer cell death in the central areas of tumor [1]. However, a common feature of VDA that is poorly understood is the sparing of a relatively intact viable rim at the periphery of the tumor. This viable rim leads to rapid regrowth of tumors and consequently poor responses to VDA when given as a single agent [1]. Combination therapy with chemo-or radiotherapy has produced promising responses in preclinical models and is currently being evaluated in early clinical developments.
Fighting money laundering with technology: A case study of Bank X in the UK

Article history: Received 4 December 2016 Received in revised form 29 October 2017 Accepted 21 November 2017 Available online 2 December 2017 This paper presents a longitudinal interpretive case study of a UK bank's efforts to combat Money Laundering (ML) by expanding the scope of its profiling ofML behaviour. The concept of structural coupling, taken from systems theory, is used to reflect on the bank's approach to theorize about the nature of ML-profiling. The paper offers a practical contribution by laying a path towards the improvement of money laundering detection in an organizational context while a set of evaluation measures is extracted from the case study. Generalizing from the case of the bank, the paper presents a systems-oriented conceptual framework for ML monitoring. © 2017 Elsevier B.V. All rights reserved.
A Topologically Convex Vertex-Ununfoldable Polyhedron

We construct a polyhedron that is topologically convex (i.e., has the graph of a convex polyhedron) yet has no vertex unfolding: no matter how we cut along the edges and keep faces attached at vertices to form a connected (hinged) surface, the surface necessarily unfolds with overlap.
Experience with various surgical options for the treatment of atrial fibrillation.

BACKGROUND
New alternatives exist using various energy sources and lesion lines for the surgical treatment of atrial fibrillation (AF). The efficacy of these options compared to the cut-and-sew maze III procedure is unknown.


METHODS
From August 1996 to August 2003, 79 patients have undergone a procedure for AF, with 70 patients currently more than 3 months postsurgery. The patients (58 continuous, 12 paroxysmal) underwent a surgical procedure for AF, lone AF (12) and with concomitant procedures (58). Techniques included cut and sew (23), bipolar radiofrequency (RF) (28) and unipolar-RF (10), and cryothermy (9). Lesions included maze III (46), pulmonary vein isolation (16), and pulmonary vein isolation plus mitral annular connecting line only (8).


RESULTS
Follow-up was complete in 58 (83%) of 70 patients at a mean time of 595 +/- 750 days (range, 24-2530 days). The operative mortality was 0% in lone AF patients and 7.1% (5/70) in patients undergoing concomitant procedures. Need for perioperative pacemaker was 22.9%. Overall, normal sinus rhythm (NSR) was restored in 82.7% of patients, with success in 83.3% (10/12) lone procedures and 82.6% (38/46) concomitant procedures ( P = NS); the rate of continuous AF was 85.1% (40/47) and SR with paroxysmal fibrillation was 72.7% (8/11) ( P = NS). Traditional maze was successful in 80.6% (29/36) patients, pulmonary vein isolation was successful 93.3% (14/15), and left-sided maze in 71.4% (5/7) ( P = NS). Cut and sew procedures were successful in 88.2% (15/17), RF-bipolar in 84.0% (21/25), RFunipolar in 77.8% (7/9), and cryothermy in 71.4% (5/7) ( P = NS). Energy source, lesion set, AF duration, and lone/concomitant procedure were the factors subjected to logistic regression analysis. No factors were predictive of achieving postoperative NSR.


CONCLUSIONS
Our early experience with newer surgical techniques employing different energy sources and fewer incision lines suggests that the success rate may approach the results obtained with traditional cut-and-sew Cox-maze III procedures.
Exposure assessment of particulate matter air pollution before, during, and after the 2003 Southern California wildfires

Exposure to biomass smoke has been associated with increased respiratory illness and symptoms. The goal of this study was to estimate daily particulate matter (PM; PM10 and PM2.5) concentrations at a zip-code level for southern California before, during and after the 2003 southern California wildfires. On average, heavy smoke from the fires increased PM10 and PM2.5 concentration by 160 and 100 μg m, respectively. Missing PM concentrations from the every 3 or 6 day routine measurements or due to the incapacitation of monitors and/or stations by the fires were estimated based on (1) temporal profiles of continuous TEOM or BAM data at co-located or closely-located sites; and (2) light extinction, meteorological conditions, and smoke information extracted from MODIS satellite images at a 250 m resolution. Light extinction coefficient, smoke, and relatively humidity were the most important factors strongly associated with PM concentrations, especially PM2.5. Spatial interpolations of PM concentrations were performed using inverse distance weighting (IDW), kriging or cokriging methods for the non-fire periods. Kriging was not superior to IDW in many cases due to the small number of monitoring stations. Since the fire and smoke created highly heterogeneous pollution surfaces, typical IDW and kriging could not work during the fires. Polygons were created based on satellite images to represent each smoke-covered area under different smoke densities. Concentrations were assigned to each polygon using measured or valid estimated concentrations at the corresponding monitoring stations, or at other stations under similar smoke conditions. In summary, population-weighted PM10 and PM2.5 concentrations were 190 and 90 μg m, and 125 and 75 μg m under heavy and light smoke conditions, respectively, in contrast to concentrations of 40 and 20 μg m for PM10 and PM2.5, respectively, during the non-fire periods. The methodology we developed in this study is also applicable to other regions to a greater or lesser extent based on the availability of satellite, visibility and air quality data.
Aged garlic extract reduces blood pressure in hypertensives: a dose–response trial

Background/objectives:Hypertension affects about 30% of adults worldwide. Garlic has blood pressure-lowering properties and the mechanism of action is biologically plausible. Our trial assessed the effect, dose–response, tolerability and acceptability of different doses of aged garlic extract as an adjunct treatment to existing antihypertensive medication in patients with uncontrolled hypertension.Subjects/methods:A total of 79 general practice patients with uncontrolled systolic hypertension participated in a double-blind randomised placebo-controlled dose–response trial of 12 weeks. Participants were allocated to one of three garlic groups with either of one, two or four capsules daily of aged garlic extract (240/480/960 mg containing 0.6/1.2/2.4 mg of S-allylcysteine) or placebo. Blood pressure was assessed at 4, 8 and 12 weeks and compared with baseline using a mixed-model approach. Tolerability was monitored throughout the trial and acceptability was assessed at 12 weeks by questionnaire.Results:Mean systolic blood pressure was significantly reduced by 11.8±5.4 mm Hg in the garlic-2-capsule group over 12 weeks compared with placebo (P=0.006), and reached borderline significant reduction in the garlic-4-capsule group at 8 weeks (−7.4±4.1 mm Hg, P=0.07). Changes in systolic blood pressure in the garlic-1-capsule group and diastolic blood pressure were not significantly different to placebo. Tolerability, compliance and acceptability were high in all garlic groups (93%) and highest in the groups taking one or two capsules daily.Conclusions:Our trial suggests aged garlic extract to be an effective and tolerable treatment in uncontrolled hypertension, and may be considered as a safe adjunct treatment to conventional antihypertensive therapy.
Vine-copula GARCH model with dynamic conditional dependence

Constructingmultivariate conditional distributions for non-Gaussian return series has been amajor research agenda recently. CopulaGARCHmodels combine the use ofGARCHmodels and a copula function to allow flexibility on the choice of marginal distributions and dependence structures. However, it is non-trivial to define multivariate copula densities that allow dynamic dependent structures in returns. The vine-copula method has been gaining attention recently in that a multi-dimensional density can be decomposed into a product of conditional bivariate copulas andmarginal densities. The dependence structure is interpreted individually in each copula pair. Yet, most studies have only focused on time varying correlation. A vine-copula GARCH model with dynamic conditional dependence is proposed. A generic approach to specifying dynamic conditional dependence using any dependence measures is developed. The characterization also induces multivariate conditional dependence dynamically through vine decomposition. The main idea is to incorporate dynamic conditional dependence, such as Kendall’s tau and rank correlation, not tomention linear correlation, in each bivariate copula pair. The estimation is conducted through a sequential approach. Simulation experiments are performed and five Hong Kong blue chip stock data from January 2004 to December 2011 are studied. Using t and two Archimedean copulas, it is revealed that Kendall’s tau and linear correlation of the stock returns vary over time, indicating the presence of time varying properties in dependence. © 2013 Elsevier B.V. All rights reserved.
A fast multi-scale covariance descriptor for object re-identification

In many surveillance systems, there is a need to determine if a given object (person, group of persons, vehicle, . . .) has already been observed over a network of cameras. It is the object re-identification problem. Solving this problem involves matching observation of objects across disjoint camera views. Uncalibrated fixed or mobile cameras with non-overlapping field of view generate uncontrolled variation in view point, background and lighting. In such situations, a robust and invariant image description is required. A multi-scale covariance image descriptor and a quadtree based scheme are proposed to describe any object of interest. We describe a fast method for computation of multi-scale covariance descriptor. The descriptor is evaluated in person re-identification application using the VIPeR dataset. We show that the proposed multi-scale approach outperforms existing mono-scale image description methods. 2011 Elsevier B.V. All rights reserved.
Using Social Media to Enhance Emergency Situation Awareness

The described system uses natural language processing and data mining techniques to extract situation awareness information from Twitter messages generated during various disasters and crises.
Advances in Research on Mental Accounting and Reason-Based Choice

Research extending over twenty years in behavioral decision theory has led to the development of two important research streams -mental accounting and reason-based choice. This paper explores recent research on the role of mental accounting and reason-based choice in the construction of consumer preferences. Evidence suggests that the principles of mental accounting often regulate the purchase and consumption of luxuries and that reasons may play an important part in this process. In particular, buying and consuming luxury goods tends to call for reasons and justification and can evoke intrapersonal conflict that might be resolved with the aid of mental accounting. Moreover, reasons can serve as important building blocks in the formation and grouping of mental accounts. The current paper also discusses the construction of preferences as a process where, in certain cases, consumers choose reasons rather than options. Among other things, focusing on reasons can lead to discrepancies between decisions and consumption experiences, preference intransitivity, and unconventional choices. Directions for future research are discussed.
Impact of caregiver group psychoeducation on the course and outcome of bipolar patients in remission: a randomized controlled trial.

OBJECTIVE
Although there are some randomized controlled trials that highlight the positive role of family-focused treatment added to pharmacotherapy in bipolar disorder, no trials using contemporary methodologies have analyzed the specific effect of working with caregiver-only groups. The aim of this study was to assess the efficacy of a psychoeducational group intervention focused on caregivers of euthymic bipolar patients.


METHOD
A total of 113 medicated euthymic bipolar outpatients who lived with their caregivers were randomized into an experimental and a control group. Caregivers in the experimental group received twelve 90-min group psychoeducation sessions focused on knowledge of bipolar disorder and training in coping skills. The patients did not attend the groups. Caregivers assigned to the control group did not receive any specific intervention. Patients were assessed monthly during both the intervention and the 12 months of follow-up. The primary outcome was time to any mood recurrence.


RESULTS
Psychoeducation group intervention focused on the caregivers of bipolar patients carried a reduction of the percentage of patients with any mood recurrence (chi2 = 6.53; p = 0.011) and longer relapse-free intervals (log-rank chi(2) = 4.04; p = 0.044). When different types of episodes were analyzed separately, the effect was significant for both the number of patients who experienced a hypomanic/manic recurrence (chi2 = 5.65; p = 0.017) and the time to such an episode (log-rank chi2 = 5.84; p = 0.015). The differences in preventing depressive and mixed episodes were not significant.


CONCLUSIONS
A psychoeducation group intervention for the caregivers of bipolar patients is a useful adjunct to usual treatment for the patients in reducing the risk of recurrences, particularly mania and hypomania, in bipolar disorder.
Predicting a Business Star in Yelp from Its Reviews Text Alone

Yelp online reviews are invaluable source of information for users to choose where to visit or what to eat among numerous available options. But due to overwhelming number of reviews, it is almost impossible for users to go through all reviews and find the information they are looking for. To provide a business’ overview, one solution is to give the business a 1-5 star(s). This rating can be subjective and biased toward users’ personality. In this paper, we predict a business’ rating based on user-generated reviews’ texts alone. This not only provides an overview of plentiful long review texts but also cancels out subjectivity. Selecting the restaurant category from Yelp Dataset Challenge [1], we use a combination of three feature generation methods as well as four machine learning models to find the best prediction result. Our approach is to create bag of words from the top frequent words in all raw text reviews, or top frequent words/adjectives from results of Part-of-Speech analysis. Our results show Root Mean Square Error (RMSE) of 0.6 for the combination of Linear Regression with either of the top frequent words from raw data or top frequent adjectives after Part-of-Speech (POS). Keywords—Yelp; predicting star; linear regression; review
Coating two-dimensional nanomaterials with metal-organic frameworks.

We demonstrate the coating of various 2D nanomaterials including MoS2 nanosheets, graphene oxide (GO), and reduced graphene oxide (rGO) with zeolitic imidazolate frameworks (i.e., ZIF-8) via a facile procedure. Additionally, ternary core-shell structures like Pt-MoS2@ZIF-8, Pt-GO@ZIF-8, and Pt-rGO@ZIF-8 have also been prepared. As a proof-of-concept application, a memory device based on MoS2@ZIF-8 hybrid was fabricated and it exhibited write-once-read-many-times (WORM) memory effect with high ON/OFF ratio and long operating lifetime. It is expected that MOF coated 2D nanomaterials may find wide applications in energy storage and conversion, catalysis, sensing, and information storage devices.
Workspace Analysis of a Cable Driven Leg Exoskeleton

Robotic systems are being used for gait rehabilitation of patients with neurological disorders. These are externally powered devices that can apply external forces on human limbs to assist the limb motion. Human walking pattern involves repetitive and well coordinated lower limb movements. A cable driven leg exoskeleton (CDLE) uses actuated cables to apply external torques at anatomical hip and knee joints. However, a cable can apply only pulling force on a body which limits a cable driven system functionality compared to a conventional robotic manipulator. Noting that a CDLE is proposed to assist in complex lower limb motion during walking We present workspace analysis of CDLE considering planar and spatial leg model. Human walking data were used for the analysis and to study the feasibility of CDLE architecture for human gait rehabilitation.1
MAXIMAL FUNCTIONS IN VARIABLE EXPONENT SPACES: LIMITING CASES OF THE EXPONENT

In this paper we study the Hardy–Littlewood maximal operator in variable exponent spaces when the exponent is not assumed to be bounded away from 1 and ∞. Within the framework of Orlicz–Musielak spaces, we characterize the function space X with the property that Mf ∈ Lp(·) if and only if f ∈ X, under the assumptions that p is log-Hölder continuous and 1 6 p− 6 p 6 ∞.
The prize collecting Steiner tree problem: theory and practice

We consider variants on the Prize Collecting Steiner Tree problem and on the primal-dual 2-approximation algorithm devised for it by Goemans and Williamson. We introduce an improved pruning rule for the algorithm that is slightly faster and provides solutions that are at least as good and typically significantly better. On a selection of real-world instances whose underlying graphs are county street maps, the improvement in the standard objective function ranges from 1.7% to 9.2%. Substantially better improvements are obtained for the complementary "net worth" objective function and for randomly generated instances. We also show that modifying the growth phase of the GoemansWilliamson algorithm to make it independent of the choice of root vertex does not significantly affect the algorithm's worst-case guarantee or behavior in practice. The resulting algorithm can be fttrther modified so that, without an increase in running time, it becomes a 2-approximation algorithm for finding the best subtree over all choices of root. In the second part of the paper, we consider quota and budget versions of the problem. In the first, one is looking for the tree with minimum edge cost that contains vertices whose total prize is at least a given quota; in the second one is looking for the tree with maximum prize, given that the total edge cost is within a given budget. The quota problem is a generalization of the k-MST problem, and we observe how constant-factor approximation algorithms for that problem can be extended to it. We also show how a (5 ÷ e)approximation algorithm for the (unrooted) budget problem can be derived from Gaxg's 3-approximation algorithm for the k-MST. None of these algorithms are likely to be used in ~ ractice, but we show how the general approach behind them which involves performing multiple runs of the GoemansWiUiamson algorithm using an increasing sequence of prizemultipliers) can be incorporated into a practical heuristic. We also uncover some surprising properties of the cost/prize tradeoff curves generated (and used) by this approach. 1 Prob lem Def in i t ions In the Prize Collecting Steiner Tree" (PCST) problem, one is given a graph G = (V, E) , a non-negative edge cost c(e) for each edge e 6 E , a non-negative vertex prize p(v) for each vertex v 6 V, and a specified root vertex vo 6 V. In this paper we shall consider four different optimization problems based on this scenario, the first being the one initially studied in [6, 7]: " ¢ / ~ T Labs, Room C239, 180 Park Avenue, Florham Park, NJ 07932. Email: dsj@research.att.com ?MIT Lab. for Computer Science, 545 Tech Square, Cambridge, MA 02139. Emaih mariam@theory.lcs.mit.edu SAT&T Labs, Room A003, 180 Park Avenue, Florham Park, NJ 07932. Emaih phillips@reseoxch.att.com Steven Phillips 1. The Goemans-WiUiamson Minimization problem: Find a subtree T ' = (V',E') of G tha t minimizes the cost of the edges in the tree plus the prizes of the vertices not in the tree, i.e., tha t minimizes GW(T') = Z c(e) + Z p(v)
DENDRAL: A Case Study of the First Expert System for Scientific Hypothesis Formation

Lindsay, R.K., B.G. Buchanan, E.A. Feigenbaum and J. Lederberg, DENDRAL: a case study of the first expert system for scientific hypothesis formation, Artificial Intelligence 61 (1993) 209-261. The DENDRAL Project was one of the first large-scale programs to embody the strategy of using detailed, task-specific knowledge about a problem domain as a source of heuristics, and to seek generality through automating the acquisition of such knowledge. This paper summarizes the major conceptual contributions and accomplishments of that project. It is an attempt to distill from this research the lessons that are of importance to artificial intelligence research and to provide a record of the final status of two decades of work. Correspondence to: R.K. Lindsay, University of Michigan, 205 Zina Pitcher Place, Ann Arbor, MI 48109, USA. Telephone: (313) 764-4227. Fax: (313) 747.4130. E-mail: lindsay@umich.edu. *This research was supported by the National Aeronautics and Space Administrations, the Advanced Research Projects Agency of the Department of Defense, and the National Institutes of Health. This paper draws upon [37], expanding and updating that account in light of subsequent developments and the benefit of hindsight. Large portions of descriptive material are taken nearly verbatim to make the present paper self-contained since the book itself is no longer in print. OOO4-3702/93/$06.00