nils-herrmann/clean_scirepeval huggingface dataset:
Searching Trajectories by Regions of Interest

With the increasing availability of moving-object tracking data, trajectory search is increasingly important. We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in many popular applications such as trip planning and recommendation, and location based services in general. TSR query processing faces three challenges: how to model the spatial-density correlation between query regions and data trajectories, how to effectively prune the search space, and how to effectively schedule multiple so-called query sources. To tackle these challenges, a series of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.
20 Fouling of Heat Transfer Surfaces

Fouling is generally defined as the accumulation and formation of unwanted materials on the surfaces of processing equipment, which can seriously deteriorate the capacity of the surface to transfer heat under the temperature difference conditions for which it was designed. Fouling of heat transfer surfaces is one of the most important problems in heat transfer equipment. Fouling is an extremely complex phenomenon. Fundamentally, fouling may be characterized as a combined, unsteady state, momentum, mass and heat transfer problem with chemical, solubility, corrosion and biological processes may also taking place. It has been described as the major unresolved problem in heat transfer1. According to many [1-3], fouling can occur on any fluid-solid surface and have other adverse effects besides reduction of heat transfer. It has been recognized as a nearly universal problem in design and operation, and it affects the operation of equipment in two ways: Firstly, the fouling layer has a low thermal conductivity. This increases the resistance to heat transfer and reduces the effectiveness of heat exchangers. Secondly, as deposition occurs, the cross sectional area is reduced, which causes an increase in pressure drop across the apparatus. In industry, fouling of heat transfer surfaces has always been a recognized phenomenon, although poorly understood. Fouling of heat transfer surfaces occurs in most chemical and process industries, including oil refineries, pulp and paper manufacturing, polymer and fiber production, desalination, food processing, dairy industries, power generation and energy recovery. By many, fouling is considered the single most unknown factor in the design of heat exchangers. This situation exists despite the wealth of operating experience accumulated over the years and accumulation of the fouling literature. This lake of understanding almost reflects the complex nature of the phenomena by which fouling occurs in industrial equipment. The wide range of the process streams and operating conditions present in industry tends to make most fouling situations unique, thus rendering a general analysis of the problem difficult. In general, the ability to transfer heat efficiently remains a central feature of many industrial processes. As a consequence much attention has been paid to improving the understanding of heat transfer mechanisms and the development of suitable correlations and techniques that may be applied to the design of heat exchangers. On the other hand relatively little consideration has been given to the problem of surface fouling in heat exchangers.
Genetics of coronary artery disease: discovery, biology and clinical translation

Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked approximately 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forwards, genetic testing could enable precision medicine approaches by identifying subgroups of patients at increased risk of coronary artery disease or those with a specific driving pathophysiology in whom a therapeutic or preventive approach would be most useful.
A Game-Theoretic Analysis of Adversarial Classification

Attack detection is usually approached as a classification problem. However, standard classification tools often perform poorly, because an adaptive attacker can shape his attacks in response to the algorithm. This has led to the recent interest in developing methods for adversarial classification, but to the best of our knowledge, there have been a very few prior studies that take into account the attacker’s tradeoff between adapting to the classifier being used against him with his desire to maintain the efficacy of his attack. Including this effect is a key to derive solutions that perform well in practice. In this investigation, we model the interaction as a game between a defender who chooses a classifier to distinguish between attacks and normal behavior based on a set of observed features and an attacker who chooses his attack features (class 1 data). Normal behavior (class 0 data) is random and exogenous. The attacker’s objective balances the benefit from attacks and the cost of being detected while the defender’s objective balances the benefit of a correct attack detection and the cost of false alarm. We provide an efficient algorithm to compute all Nash equilibria and a compact characterization of the possible forms of a Nash equilibrium that reveals intuitive messages on how to perform classification in the presence of an attacker. We also explore qualitatively and quantitatively the impact of the non-attacker and underlying parameters on the equilibrium strategies.
Factors that influence young people's mental health help-seeking behaviour: a study based on the Health Belief Model.

To identify key predictors and moderators of mental health 'help-seeking behavior' in adolescents.



Mental illness is highly prevalent in adolescents and young adults; however, individuals in this demographic group are among the least likely to seek help for such illnesses. Very little quantitative research has examined predictors of help-seeking behaviour in this demographic group.



A cross-sectional design was used.



A group of 180 volunteers between the ages of 17-25 completed a survey designed to measure hypothesized predictors and moderators of help-seeking behaviour. Predictors included a range of health beliefs, personality traits and attitudes. Data were collected in August 2010 and were analysed using two standard and three hierarchical multiple regression analyses.



The standard multiple regression analyses revealed that extraversion, perceived benefits of seeking help, perceived barriers to seeking help and social support were direct predictors of help-seeking behaviour. Tests of moderated relationships (using hierarchical multiple regression analyses) indicated that perceived benefits were more important than barriers in predicting help-seeking behaviour. In addition, perceived susceptibility did not predict help-seeking behaviour unless individuals were health conscious to begin with or they believed that they would benefit from help.



A range of personality traits, attitudes and health beliefs can predict help-seeking behaviour for mental health problems in adolescents. The variable 'Perceived Benefits' is of particular importance as it is: (1) a strong and robust predictor of help-seeking behaviour; and (2) a factor that can theoretically be modified based on health promotion programmes.
Big data open platform for water resources management

Nowadays Big Data are becoming a popular topic and a comparatively new technological concept focused on many different disciplines like environmental science, social media and networks, industry and healthcare. Data volumes are on an upward trajectory associated with increased data velocity, and variety. Furthermore, they are needed to develop effective solutions to support intelligent, proactive and predictive processes. In this paper we exploit Big Data concepts for environmental sciences and water resources. The aim of this article is to present the concept and architecture of our Big Data Open Platform used for supporting Water Resources Management. This Platform has been designed to provide effective tools that allow water system managers to solve complex water resources systems, water modeling issues and help in decision making. The Platform brings a variety of information technology tools including stochastic aspects, high performance computing, simulation models, hydraulic and hydrological models, grid computing, decision tools, Big Data analysis system, communication and diffusion system, database management, geographic information system (GIS) and Knowledge based expert system. The operators' objectives of this Big Data Open Platform are to solve and discuss water resources problems that are featured by a huge volume of collected, analyzed and visualized data, to analyze the heterogeneity of data resulting from various sources including structured, unstructured and semi-structured data, also to prevent and/or avoid a catastrophic event related to floods and/or droughts, through hydraulic infrastructures designed for such purposes or strategic planning. This first paper will focus on the first part developed and based on J2EE platform and specifically the hypsometrical approach considered as a decision tool allowing users to compare the effects of different current and future management scenarios and make choice to preserve the environment and natural resources.
To Isolate, or to Share?: That is a Question for Intel SGX

One cornerstone of computer security is hardware-based isolation mechanisms, among which an emerging technology named Intel Software Guard Extensions (SGX) offers arguably the strongest security on x86 architecture. Intel SGX enables user-level code to create trusted memory regions named enclaves, which are isolated from the rest of the system, including privileged system software. This strong isolation of SGX, however, forbids sharing any trusted memory between enclaves, making it difficult to implement any features or techniques that must share code or data between enclaves. This dilemma between isolation and sharing is especially challenging to system software for SGX (e.g., library OSes), to which both properties are highly desirable.
 To resolve the tension between isolation and sharing in system software for SGX, especially library OSes, we propose a single-address-space approach, which runs all (user-level) processes and the library OS in a single enclave. This single-enclave architecture enables various memory-sharing features or techniques, thus improving both performance and usability. To enforce inter-process isolation and user-privilege isolation inside the enclave, we design a multi-domain software fault isolation (SFI) scheme, which is unique in its support for two types of domains: 1) data domains, which enable process isolation, and 2) code domains, which enable shared libraries. Our SFI is implemented efficiently by leveraging Intel Memory Protection Extensions (MPX). Experimental results show an average overhead of 10%, thus demonstrating the practicality of our approach.
Effectiveness of partial hospitalization in the treatment of borderline personality disorder: a randomized controlled trial.

This study compared the effectiveness of psychoanalytically oriented partial hospitalization with standard psychiatric care for patients with borderline personality disorder.



Thirty-eight patients with borderline personality disorder, diagnosed according to standardized criteria, were allocated either to a partially hospitalized group or to a standard psychiatric care (control) group in a randomized controlled design. Treatment, which included individual and group psychoanalytic psychotherapy, was for a maximum of 18 months. Outcome measures included the frequency of suicide attempts and acts of self-harm, the number and duration of inpatient admissions, the use of psychotropic medication, and self-report measures of depression, anxiety, general symptom distress, interpersonal function, and social adjustment. Data analysis used repeated measures analysis of covariance and nonparametric tests of trend.



Patients who were partially hospitalized showed a statistically significant decrease on all measures in contrast to the control group, which showed limited change or deterioration over the same period. An improvement in depressive symptoms, a decrease in suicidal and self-mutilatory acts, reduced inpatient days, and better social and interpersonal function began at 6 months and continued until the end of treatment at 18 months.



Psychoanalytically oriented partial hospitalization is superior to standard psychiatric care for patients with borderline personality disorder. Replication is needed with larger groups, but these results suggest that partial hospitalization may offer an alternative to inpatient treatment.
Single Camera Calibration using Partially Visible Calibration Objects Based on Random Dots Marker Tracking Algorithm

Camera calibration is one of the long existing research issues in computer vision domain. Typical calibration methods take two steps for the procedure: control points localization and camera parameters computation. In practical situation, control points localization is a time-consuming task because the localization puts severe assumption that the calibration object should be visible in all images. To satisfy the assumption, users may avoid moving the calibration object near the image boundary. As a result, we estimate poor quality parameters. In this paper, we aim to solve this partial occlusion problem of the calibration object. To solve the problem, we integrate a planar marker tracking algorithm that can track its target marker even with partial occlusion. Specifically, we localize control points by a RANdom DOts Markers (RANDOM) tracking algorithm that uses markers with randomly distributed circle dots. Once the control points are localized, they are used to estimate the camera parameters. The proposed method is validated with both synthetic and real world experiments. The experimental results show that the proposed method realizes camera calibration from image on which part of the calibration object is visible.
Active object recognition by view integration and reinforcement learning

A mobile agent with the task to classify its sensor pattern has to cope with ambiguous information. Active recognition of three-dimensional objects involves the observer in a search for discriminative evidence, e.g., by change of its viewpoint. This paper defines the recognition process as a sequential decision problem with the objective to disambiguate initial object hypotheses. Reinforcement learning provides then an efficient method to autonomously develop near-optimal decision strategies in terms of sensorimotor mappings. The proposed system learns object models from visual appearance and uses a radial basis function (RBF) network for a probabilistic interpretation of the two-dimensional views. The information gain in fusing successive object hypotheses provides a utility measure to reinforce actions leading to discriminative viewpoints. The system is verified in experiments with 16 objects and two degrees of freedom in sensor motion. Crucial improvements in performance are gained using the learned in contrast to random camera placements.
Automating Disk Forensic Processing with SleuthKit, XML and Python

We have developed a program called |fiwalk| which produces detailedXML describing all of the partitions and files on a hard drive or diskimage, as well as any extractable metadata from the document filesthemselves. We show how it is relatively simple to create automateddisk forensic applications using a Python module we have written thatreads |fiwalk|'s XML files. Finally, we present threeapplications using this system: a program to generate maps ofdisk images; an image redaction program; and a data transfer kioskwhich uses forensic tools to allow the migration of data from portablestorage devices without risk of infection from hostile software thatthe portable device may contain.
Surgical Correction of Hallermann-Streiff Syndrome: A Case Report of Esotropia, Entropion, and Blepharoptosis

We report a case of surgical treatment for Hallermann-Streiff syndrome in a patient with ocular manifestations of esotropia, entropion, and blepharoptosis. A 54-year-old man visited Yeouido St. Mary's Hospital complaining of ocular discomfort due to cilia touching the corneas of both eyes for several years. He had a bird-like face, pinched nose, hypotrichosis of the scalp, mandibular hypoplasia with forward displacement of the temporomandibular joints, a small mouth, and proportional short stature. His ophthalmic features included sparse eyelashes and eyebrows, microphthalmia, nystagmus, lower lid entropion in the right eye, and upper lid entropion with blepharoptosis in both eyes. There was esodeviation of the eyeball of more than 100 prism diopters at near and distance, and there were limitations in ocular movement on lateral gaze. The capsulopalpebral fascia was repaired to treat the right lower lid entropion, but an additional Quickert suture was required to prevent recurrence. Blepharoplasty and levator palpebrae repair were performed for blepharoptosis and dermatochalasis. Three months after lid surgery, the right medial rectus muscle was recessed 7.5 mm, the left medial rectus was recessed 7.25 mm, and the left lateral rectus muscle was resected 8.0 mm.
Critical assumptions: thinking critically about critical thinking.

The concept of critical thinking has been featured in nursing literature for the past 20 years. It has been described but not defined by both the American Association of Colleges of Nursing and the National League for Nursing, although their corresponding accreditation bodies require that critical thinking be included in nursing curricula. In addition, there is no reliable or valid measurement tool for critical thinking ability in nursing. As a result, there is a lack of research support for the assumptions that critical thinking can be learned and that critical thinking ability improves clinical competence. Brookfield suggested that commitments should be made only after a period of critically reflective analysis, during which the congruence between perceptions and reality are examined. In an evidence-based practice profession, we, as nurse educators, need to ask ourselves how we can defend our assumptions that critical thinking can be learned and that critical thinking improves the quality of nursing practice, especially when there is virtually no consensus on a definition.
Improving trilateration for indoors localization using BLE beacons

While the Global Positioning System (GPS) tends to be not useful anymore in terms of precise localization once one gets into a building, Low Energy beacons might come in handy instead. Navigating free of signal reception problems throughout a building when one has never visited that place before is a challenge tackled with indoors localization. Using Bluetooth Low Energy1 (BLE) beacons (either iBeacon or Eddystone formats) is the medium to accomplish that. Indeed, different purpose oriented applications can be designed, developed and shaped towards the needs of any person in the context of a certain building. This work presents a series of post-processing filters to enhance the outcome of the estimated position applying trilateration as the main and straightforward technique to locate someone within a building. A later evaluation tries to give enough evidence around the feasibility of this indoor localization technique. A mobile app should be everything a user would need to have within a building in order to navigate inside.
Pad porosity , compressibility and slurry delivery effects in chemical-mechanical planarization : modeling and experiments

A chemical-mechanical planarization (CMP) model based on lubrication theory is developed which accounts for pad compressibility, pad porosity and means of slurry delivery. Slurry ®lm thickness and velocity distributions between the pad and the wafer are predicted using the model. Two regimes of CMP operation are described: the lubrication regime (for ,40±70 mm slurry ®lm thickness) and the contact regime (for thinner ®lms). These regimes are identi®ed for two different pads using experimental copper CMP data and the predictions of the model. The removal rate correlation based on lubrication and mass transport theory agrees well with our experimental data in the lubrication regime.
An unusual case of suicidal asphyxia by smothering.

A case is presented of a 30-year-old man suffering from borderline personality disorder who committed suicide by means of smothering. He was hospitalized at the psychiatric department of a public hospital for several months and was found dead in the seclusion room. The death resulted from an obstruction of the upper aerodigestive tract after ingurgitation of pellets of toilet paper. A literature review revealed several cases of suicidal asphyxia by smothering of patients with a history of psychiatric illness. Our patient's operating process had not been reported before to our knowledge.
Data centre temperature monitoring with ESP8266 based Wireless Sensor Network and cloud based dashboard with real time alert system

The Internet of Things (IoT) system proposed in this paper is an advanced solution for monitoring the temperature at different points of location in a data centre, making this temperature data visible over internet through cloud based dashboard and sending SMS and email alerts to predefined recipients when temperature rises above the safe operating zone and reaches certain high values. This helps the datacenter management team to take immediate action to rectify this temperature deviation. Also this can be monitored from anywhere anytime over online dashboard by the senior level professionals who are not present in the data centre at any point in time. This Wireless Sensor Network (WSN) based monitoring system consists of temperature sensors, ESP8266 and Wi-Fi router. ESP8266 is a low power, highly integrated Wi-Fi solution from Espress if. The ESP8266 here, in this prototype, connects to ‘Ubidots’ cloud through its API for posting temperature data to the cloud dashboard on real time and the cloud event management system generates alerts whenever the high temperature alert event is fired. Cloud events need to be configured for different alerts beforehand through the user friendly user interface of the platform. It's to be noted that the sensor used here can be leveraged to monitor the relative humidity of the data center environment as well along with the temperature of the data center. But for this prototype solution focus is kept entirely on the temperature monitoring.