LLukas22/scidocs huggingface dataset:
A wait-list randomized controlled trial of loving-kindness meditation programme for self-criticism.

UNLABELLED
Self-criticism is a vulnerability risk factor for a number of psychological disorders, and it predicts poor response to psychological and pharmacological treatments. In the current study, we evaluated the efficacy of a loving-kindness meditation (LKM) programme designed to increase self-compassion in a sample of self-critical individuals. Thirty-eight individuals with high scores on the self-critical perfectionism subscale of the Dysfunctional Attitude Scale were randomized to an LKM condition (n = 19) or a wait-list (WL) condition (n = 19). Measures of self-criticism, self-compassion and psychological distress were administered before and immediately following the intervention (LKM or WL). WL participants received the intervention immediately after the waiting period. Both groups were assessed 3 months post-intervention. Intent-to-treat (n = 38) and per-protocol analyses (n = 32) showed significant reductions in self-criticism and depressive symptoms as well as significant increases in self-compassion and positive emotions in the LKM condition compared with the WL condition. A follow-up per-protocol analysis in both groups together (n = 20) showed that these gains were maintained 3 months after the intervention. These preliminary results suggest that LKM may be efficacious in alleviating self-criticism, increasing self-compassion and improving depressive symptoms among self-critical individuals.


KEY PRACTITIONER MESSAGE
Self-criticism plays a major role in many psychological disorders and predicts poor response to brief psychological and pharmacological treatments for depression. The current study shows that loving-kindness meditation, designed to foster self-compassion, is efficacious in helping self-critical individuals become less self-critical and more self-compassionate. The study also suggests that practising loving-kindness may reduce depressive symptoms and increase positive emotions.
A Survey of Search Methodologies and Automated Approaches for Examination Timetabling

Exam timetabling is one of the most important administrative activities that takes place in academic institutions. In this paper we present a critical discussion of the research on exam timetabling in the last decade or so. This last ten years has seen an increased level of attention on this important topic. There has been a range of significant contributions to the scientific literature both in terms of theoretical and practical aspects. The main aim of this survey is to highlight the new trends and key research achievements that have been carried out in the last decade. We also aim to outline a range of relevant important research issues and challenges that have been generated by this body of work. We first define the problem and review previous survey papers. Algorithmic approaches are then classified and discussed. These include early techniques (e.g. graph heuristics) and state-of-the-art approaches including meta-heuristics, constraint based methods, multi-criteria techniques, hybridisations, and recent new trends concerning neighbourhood structures, which are motivated by raising the generality of the approaches. Summarising tables are presented to provide an overall view of these techniques. We discuss some issues on decomposition techniques, system tools and languages, models and complexity. We also present and discuss some important issues which have come to light concerning the public benchmark exam timetabling data. Different versions of problem datasets with the same name have been circulating in the scientific community in the last ten years which has generated a significant amount of confusion. We clarify the situation and present a re-naming of the widely studied datasets to avoid future confusion. We also highlight which research papers have dealt with which dataset. Finally, we draw upon our discussion of the literature to present a (non-exhaustive) range of potential future research directions and open issues in exam timetabling research.
Mobile experience sampling: Reaching the parts of Facebook other methods cannot reach

Location-aware Social Network Sites (SNS) are now widely used by mobile phone users, enabling users to share their location in real time to their social network. Such locationsharing may introduce privacy concerns depending on the user, the location being shared, and the people to whom they are shared. The study of such privacy concerns is difficult, as a user filling out a questionnaire may forget the exact reasons for sharing. We have explored the Experience Sampling Method (ESM) for in situ capture of users’ experiences. This paper describes our mobile phone ESM testbed and presents preliminary results obtained from a 2-week experiment with 40 students sharing their location in real time on Facebook, a popular SNS.
Analytical methods for estimating equivalent thermal conductivity in impregnated electrical windings formed using Litz wire

This paper discusses two analytical methods used in estimating the equivalent thermal conductivity of impregnated electrical windings constructed with Litz wire. Both methods are based on a double-homogenisation approach consecutively employing the individual winding conductors and wire bundles. The first method is suitable for Litz wire with round-profiled enamel-coated conductors and round-shaped bundles; whereas the second method is tailored for compacted Litz wires with conductors and/or bundles having square or rectangular profiles. The work conducted herein expands upon established methods for cylindrical conductor forms [1], and develops an equivalent lumped-parameter thermal network for rectangular forms. This network derives analytical formulae which represents the winding's equivalent thermal conductivity and directly accounts for any thermal anisotropy. The estimates of equivalent thermal conductivity from theoretical, analytical and finite element (FE) methods have been supplemented with experimental data using impregnated winding samples and are shown to have good correlation.
Business Process Intelligence

workflows, data warehousing, business intelligence Process design and automation technologies are being increasingly used by both traditional and newly-formed, Internet-based enterprises in order to improve the quality and efficiency of their administrative and production processes, to manage e-commerce transactions, and to rapidly and reliably deliver services to businesses and individual customers.
Sources of symmetric potentials

Laboratory experiments on gravitation are usually performed with objects of constant density, so that the analysis of the forces concerns only the geometry of their shape. In an ideal experiment, the shapes of the constituent parts will be optimised to meet certain mathematical criteria, which ensure that the experiment has maximal sensitivity. 
Using this idea, the author suggested an experiment to determine the departure of the gravitational force from Newton's force law [1]. The geometrical problem which has to be solved is to find two shapes which differ significantly, but have the same Newtonian potential. Essentially, the experiment determines whether the two objects are distinguishable by their gravitational force. Here, we consider the case when one of them is a round ball. The result, Theorem 1, establishes a fact which appeared in numerical simulations, that the second object has to have a hole in it.
Symmetry-restrained flexible fitting for symmetric EM maps.

Many large biological macromolecules have inherent structural symmetry, being composed of a few distinct subunits, repeated in a symmetric array. These complexes are often not amenable to traditional high-resolution structural determination methods, but can be imaged in functionally relevant states using cryo-electron microscopy (cryo-EM). A number of methods for fitting atomic-scale structures into cryo-EM maps have been developed, including the molecular dynamics flexible fitting (MDFF) method. However, quality and resolution of the cryo-EM map are the major determinants of a method's success. In order to incorporate knowledge of structural symmetry into the fitting procedure, we developed the symmetry-restrained MDFF method. The new method adds to the cryo-EM map-derived potential further restraints on the allowed conformations of a complex during fitting, thereby improving the quality of the resultant structure. The benefit of using symmetry-based restraints during fitting, particularly for medium to low-resolution data, is demonstrated for three different systems.
Structured programming in assembly language (abstract only)

A continuous sequence of test data for testing LSI devices is provided selectably from one of a number of memory elements, each of which is reloaded, when not busy providing test data, from a higher capacity, lower speed storage element.
Detection and prevention of ARP cache poisoning

Acknowledgements It is a great pleasure to have an opportunity to thanks valuable beings for their continuous support and inspiration throughout the thesis work. I would like to extend my gratitude towards Dr. for all the guidance and great knowledge he shared during our course. The abundance of knowledge he has always satisfied our queries at every point. Thanks to Mr. Sumit Miglani, My guide for his contribution for timely reviews and suggestions in completing the thesis. Every time he provided the needed support and guidance. At last but not the least, a heartiest thanks to all my family and friends for being there every time I needed them. Abstract Address Resolution Protocol (ARP) is a protocol having simple architecture and have been in use since the advent of Open System Interconnection (OSI) network architecture. Its been working at network layer for the important dynamic conversion of network address i.e. Internet Protocol (IP) address to physical address or Media Access Control (MAC) address. Earlier it was sufficiently providing its services but in today " s complex and more sophisticated unreliable network, security being one major issue, standard ARP protocol is vulnerable to many different kinds of attacks. These attacks lead to devastating loss of important information. With certain loopholes it has become easy to be attacked and with not so reliable security mechanism, confidentiality of data is being compromised. Therefore, a strong need is felt to harden the security system. Since, LAN is used in maximum organizations to get the different computer connected. So, an attempt has been made to enhance the working of ARP protocol to work in a more secure way. Any kind of attempts to poison the ARP cache (it maintains the corresponding IP and MAC address associations in the LAN network) for redirecting the data to unreliable host, are prevented beforehand. New modified techniques are proposed which could efficiently guard our ARP from attacker and protect critical data from being sniffed both internally and externally. Efficiency of these methods has been shown mathematically without any major impact on the performance of network. Main idea behind how these methods actually work and proceed to achieve its task has been explained with the help of flow chart and pseudo codes. With the help of different tools ARP cache is being monitored regularly and if any malicious activity is encountered, it is intimidated to the administrator immediately. So, in …
PREDICTING THE SURFACE ROUGHNESS IN THE DRY MACHINING OF DUPLEX STAINLESS STEEL ( DSS )

G. Krolczyk, M. Gajek, Opole University of Technology, Department of Technology and Work Environment Engineering, Opole, Poland, S. Legutko, Poznan University of Technology, Institute of Mechanical Technology, Poznan, Poland This paper examines the infl uence of cutting parameters, namely cutting speed, feed and depth of cut onto surface roughness after DSS turning process. The study included developing a mathematical model t o determine the surface roughness. Verifi cation research has been carried out on CNC lathe; henc e the test plan has been adjust ed to the possibility of programmable machines controlling GE Fanuc Series 0-T. The comparison of results obtained by given experimental plan was performed in industrial company.
Improved supply chain management based on hybrid demand forecasts

E D P R Demand forecasts play a crucial role for supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Several forecasting techniques have been developed, each one with its particular advantages and disadvantages compared to other approaches. This motivates the development of hybrid systems combining different techniques and their respective strengths. In this paper, we present a hybrid intelligent system combining Autoregressive Integrated Moving Average (ARIMA) models and neural networks for demand forecasting. We show improvements in forecasting accuracy and propose a replenishment system for a Chilean supermarket, which leads simultaneously to fewer sales failures and lower inventory levels than the previous solution. # 2005 Published by Elsevier B.V.
Late recurrence of aggressive angiomyxoma of the vulva.

OBJECTIVE
Aggressive angiomyxoma (AA) is found mainly in the pelvis and perineum, with a female-to-male ratio of approximately 6:1. Although it is a slow growing tumor, AA has a marked tendency to local recurrence with a low metastasis capacity. The study aimed to describe a case of vulvar angiomyxoma recurred almost 20 years after its initial surgery.


MATERIALS AND METHODS
We report the case of a 57-year-old gravida 5 para 4 woman with vulvar AA arising from the left labium majus, which recurred 20 years after initial surgery. There was a nontender, solid, mobile mass on the left vulva, which was 25 x 30 cm on physical examination. A pelvic computed tomographic scan showed a mass measuring 26 x 10 x 14 cm originating from left vulvar region, which has a fatty tissue density.


RESULT
Under general anesthesia, total excision of the tumor was performed. Macroscopically, the tumor weighed 723 g and measured 33 x 20 x 10 cm. The histopathological examination of the specimen revealed a myxoid tumor with sparse infiltrates of spindle-shaped to stellate cells and vessels of varying sizes. The final histopathological diagnosis was AA.


CONCLUSIONS
Aggressive angiomyxoma may form extremely large tumors, and recurrence is not rare even many years after primary surgery.
Second-Order Discrete-Time Sliding Mode Observer for State of Charge Determination Based on a Dynamic Resistance Li-Ion Battery Model

A second-order discrete-time sliding mode observer (DSMO)-based method is proposed to estimate the state of charge (SOC) of a Li-ion battery. Unlike the first-order sliding mode approach, the proposed method eliminates the chattering phenomenon in SOC estimation. Further, a battery model with a dynamic resistance is also proposed to improve the accuracy of the battery model. Similar to actual battery behavior, the resistance parameters in this model are changed by both the magnitude of the discharge current and the SOC level. Validation of the dynamic resistance model is performed through pulse current discharge tests at two different SOC levels. Our experimental results show that the proposed estimation method not only enhances the estimation accuracy but also eliminates the chattering phenomenon. The SOC estimation performance of the second-order DSMO is compared with that of the first-order DSMO.
Automated classification of Pap smear images to detect cervical dysplasia

BACKGROUND AND OBJECTIVES
The present study proposes an intelligent system for automatic categorization of Pap smear images to detect cervical dysplasia, which has been an open problem ongoing for last five decades.


METHODS
The classification technique is based on shape, texture and color features. It classifies the cervical dysplasia into two-level (normal and abnormal) and three-level (Negative for Intraepithelial Lesion or Malignancy, Low-grade Squamous Intraepithelial Lesion and High-grade Squamous Intraepithelial Lesion) classes reflecting the established Bethesda system of classification used for diagnosis of cancerous or precancerous lesion of cervix. The system is evaluated on two generated databases obtained from two diagnostic centers, one containing 1610 single cervical cells and the other 1320 complete smear level images. The main objective of this database generation is to categorize the images according to the Bethesda system of classification both of which require lots of training and expertise. The system is also trained and tested on the benchmark Herlev University database which is publicly available. In this contribution a new segmentation technique has also been proposed for extracting shape features. Ripplet Type I transform, Histogram first order statistics and Gray Level Co-occurrence Matrix have been used for color and texture features respectively. To improve classification results, ensemble method is used, which integrates the decision of three classifiers. Assessments are performed using 5 fold cross validation.


RESULTS
Extended experiments reveal that the proposed system can successfully classify Pap smear images performing significantly better when compared with other existing methods.


CONCLUSION
This type of automated cancer classifier will be of particular help in early detection of cancer.
Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations.

BACKGROUND
Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.


OBJECTIVES
The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.


METHODS
Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.


RESULTS
The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.


CONCLUSION
This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.


PROSPERO REGISTRATION NUMBER
CRD42016039991.
Clinical Natural Language Processing with Deep Learning

The emergence and proliferation of electronic health record (EHR) systems has incrementally resulted in large volumes of clinical free text documents available across healthcare networks. The huge amount of data inspires research and development focused on novel clinical natural language processing (NLP) solutions to optimize clinical care and improve patient outcomes. In recent years, deep learning techniques have demonstrated superior performance over traditional machine learning (ML) techniques for various general-domain NLP tasks e.g. language modeling, parts-of-speech (POS) tagging, named entity recognition, paraphrase identification, sentiment analysis etc. Clinical documents pose unique challenges compared to general-domain text due to widespread use of acronyms and non-standard clinical jargons by healthcare providers, inconsistent document structure and organization, and requirement for rigorous de-identification and anonymization to ensure patient data privacy. This tutorial chapter will present an overview of how deep learning techniques can be applied to solve NLP tasks in general, followed by a literature survey of existing deep learning algorithms applied to clinical NLP problems. Finally, we include a description of various deep learning-driven clinical NLP applications developed at the Artificial Intelligence (AI) lab in Philips Research in recent years such as diagnostic inferencing from unstructured clinical narratives, relevant biomedical article retrieval based on clinical case scenarios, clinical paraphrase generation, adverse drug event (ADE) detection from social media, and medical image caption generation. Sadid A. Hasan Artificial Intelligence Lab, Philips Research North America, Cambridge, MA, USA. e-mail: sadid.hasan@philips.com Oladimeji Farri Artificial Intelligence Lab, Philips Research North America, Cambridge, MA, USA. e-mail: dimeji.farri@philips.com
The impact of a carbon tax on international tourism

A simulation model of international tourist flows is used to estimate the impact of a carbon tax on aviation fuel. The effect of the tax on travel behaviour is small: A global $1000/tC would change travel behaviour to reduce carbon dioxide emissions from international aviation by 0.8%. This is because the imposed tax is probably small relative to the air fare. A $1000/tC tax would less than double air fares, and have a smaller impact on the total cost of the holiday. In addition, the price elasticity is low. A carbon tax on aviation fuel would particularly affect long-haul flights, because of high emissions, and short-haul flights, because of the emission during take-off and landing. Medium distance flights would be affected least. This implies that tourist destinations that rely heavily on short-haul flights (that is, islands near continents, such as Ireland) or on intercontinental flights (e.g., Africa) will see a decline in international tourism numbers, while other destinations may see international arrivals rise. If the tax is only applied to the European Union, EU tourists would stay closer to home so that EU tourism would grow at the expense of other destinations. Sensitivity analyses reveal that the qualitative insights are robust. A carbon tax on aviation fuel would have little effect on international tourism, and little effect on emissions.
Sexual activity and prostate cancer risk in men diagnosed at a younger age.

OBJECTIVE
To examine, in a case-control study, the association between the frequency of sexual activity (intercourse, masturbation, overall) and prostate cancer risk in younger men diagnosed at < or = 60 years old.


PATIENTS, SUBJECTS AND METHODS
In all, 431 prostate cancer cases and 409 controls participated and provided information on their sexual activity. In particular, the frequencies of intercourse and masturbation during the participants' different age decades (20s, 30s, 40s, 50s) were collected.


RESULTS
Whereas frequent overall sexual activity in younger life (20s) increased the disease risk, it appeared to be protective against the disease when older (50s). Alone, frequent masturbation activity was a marker for increased risk in the 20s and 30s but appeared to be associated with a decreased risk in the 50s, while intercourse activity alone was not associated with the disease.


CONCLUSION
These findings could imply different mechanisms by which sexual activity is involved in the aetiology of prostate cancer at different ages. Alternatively, there is a possibility of reverse causation in explaining part of the protective effect seen for men in their 50s.