nils-herrmann/clean_scirepeval huggingface dataset:
Assessing physical therapist students’ self-efficacy: measurement properties of the Physiotherapist Self-Efficacy (PSE) questionnaire

Apart from skills, and knowledge, self-efficacy is an important factor in the students' preparation for clinical work. The Physiotherapist Self-Efficacy (PSE) questionnaire was developed to measure physical therapy (TP) students' self-efficacy in the cardiorespiratory, musculoskeletal, and neurological clinical areas. The aim of this study was to establish the measurement properties of the Dutch PSE questionnaire, and to explore whether self-efficacy beliefs in students are clinical area specific.



Methodological quality of the PSE was studied using COSMIN guidelines. Item analysis, structural validity, and internal consistency of the PSE were determined in 207 students. Test-retest reliability was established in another sample of 60 students completing the PSE twice. Responsiveness of the scales was determined in 80 students completing the PSE at the start and the end of the second year. Hypothesis testing was used to determine construct validity of the PSE.



Exploratory factor analysis resulted in three meaningful components explaining similar proportions of variance (25%, 21%, and 20%), reflecting the three clinical areas. Internal consistency of each of the three subscales was excellent (Cronbach's alpha > .90). Intra Class Correlation Coefficient was good (.80). Hypothesis testing confirmed construct validity of the PSE.



The PSE shows excellent measurement properties. The component structure of the PSE suggests that self-efficacy about physiotherapy in PT students is not generic, but specific for a clinical area. As self-efficacy is considered a predictor of performance in clinical settings, enhancing self-efficacy is an explicit goal of educational interventions. Further research is needed to determine if the scale is specific enough to assess the effect of educational interventions on student self-efficacy.
The clinical atlas of Greig cephalopolysyndactyly syndrome.

Greig cephalopolysyndactyly syndrome (GCPS) is a rare multiple congenital anomaly syndrome that is inherited in an autosomal dominant pattern and is caused by haploinsufficiency of the GLI3 gene. The syndrome typically includes preaxial or mixed pre- and postaxial polydactyly and cutaneous syndactyly, ocular hypertelorism, and macrocephaly in its typical forms, but sometimes includes hydrocephalus, seizures, mental retardation, and developmental delay in more severe cases. Patients with milder forms of GCPS can have subtle craniofacial dysmorphic features that are difficult to distinguish from normal variation. This article presents the spectrum of dysmorphic findings in GCPS highlighting some of its key presenting features to familiarize clinicians with the variable expressivity of the condition.
Advances in Wireless Sensor Networks

With the development of embedded and communication technology, along with the rapid popularization of smart mobile devices in recent years, the communication techniques in ubiquitous networking becomes more and more mature and variety, ranging from wireless communication techniques in long distance such as WiMAX and 3G to wireless communication techniques in moderate distance such as WiFi, as well as wireless communication techniques in short distance such as Bluetooth and ZigBee. Smart mobile devices can take advantages of various communication techniques in ubiquitous networking to connect, discover and communicate to each other, forming into groups to realize cooperation among multiple devices in ubiquitous networking environment. Combined with the application context of cooperation among multiple devices on entertainment in the scene of smart home, ubiquitous networking techniques and smart mobile devices are adopted while a method of group management for multiple devices in ubiquitous networking is put up. And a cooperative platform in ubiquitous networking based on a multi-agent framework, named JADE, is designed and implemented. Last but not least, a prototype system is given to validate the feasibility and the performance.
Extreme broadband waveguide diplexer design for high performance antenna feed systems

A novel broadband waveguide diplexer design serving two frequency bands with up to 20% bandwidth out of an overall frequency band of more than 65% (3.5 to 7.15GHz) is established. Since the overall extreme frequency demands exceed the operating bands of standard rectangular waveguide types with sole fundamental mode propagation, three different waveguides are considered for the interfacing, namely a dual ridge type at the common port and different standard rectangular ones (WR229, WR137) at the ports serving the assigned frequency bands. A conductor loaded H-plane T-junction is used for the common branching facing at one port the common dual ridge waveguide interface of the diplexer. The other ports of the T-junction are directed to ridge waveguide filter types for the separation of the dedicated wide passbands with up to 20% bandwidth. The opposite ports of these filters are directly adapting to the assigned standard waveguide types for the dedicated served frequency band. It is shown that this approach satisfies high performance properties with a very compact implementation. The overall design has been supported with a full wave CAD method. The measured characteristics exhibit good coincidence with the computed ones and thus validate the broadband design approach. The high performance demands qualify this diplexer design for the implementation in modular feed systems for large radio antennas to provide multi access for serving several frequency bands simultaneously.
An integration method combining Rough Set Theory with formal concept analysis for personal investment portfolios

The classical Rough Set Theory (RST) always generates too many rules, making it difficult for decision makers to choose a suitable rule. In this study, we use two processes (pre process and post process) to select suitable rules and to explore the relationship among attributes. In pre process, we propose a pruning process to select suitable rules by setting up a threshold on the support object of decision rules, to thereby solve the problem of too many rules. The post process used the formal concept analysis from these suitable rules to explore the attribute relationship and the most important factors affecting decision making for choosing behaviours of personal investment portfolios. In this study, we explored the main concepts (characteristics) for the conservative portfolio: the stable job, less than 4 working years, and the gender is male; the moderate portfolio: high school education, the monthly salary between NT$30,001 (US$1000) and NT$80,000 (US$2667), the gender is male; and the aggressive portfolio: the monthly salary between NT$30,001 (US$1000) and NT$80,000 (US$2667), less than 4 working years, and a stable job. The study result successfully explored the most important factors affecting the personal investment portfolios and the suitable rules that can help decision makers.
Using Link Features for Entity Clustering in Knowledge Graphs

Knowledge graphs holistically integrate information about entities from multiple sources. A key step in the construction and maintenance of knowledge graphs is the clustering of equivalent entities from different sources. Previous approaches for such an entity clustering suffer from several problems, e.g., the creation of overlapping clusters or the inclusion of several entities from the same source within clusters. We therefore propose a new entity clustering algorithm CLIP that can be applied both to create entity clusters and to repair entity clusters determined with another clustering scheme. In contrast to previous approaches, CLIP not only uses the similarity between entities for clustering but also further features of entity links such as the so-called link strength. To achieve a good scalability we provide a parallel implementation of CLIP based on Apache Flink. Our evaluation for different datasets shows that the new approach can achieve substantially higher cluster quality than previous approaches.
Modular Generative Adversarial Networks

Existing methods for multi-domain image-to-image translation (or generation) attempt to directly map an input image (or a random vector) to an image in one of the output domains. However, most existing methods have limited scalability and robustness, since they require building independent models for each pair of domains in question. This leads to two significant shortcomings: (1) the need to train exponential number of pairwise models, and (2) the inability to leverage data from other domains when training a particular pairwise mapping. Inspired by recent work on module networks [2], this paper proposes ModularGAN for multi-domain image generation and image-to-image translation. ModularGAN consists of several reusable and composable modules that carry on different functions (e.g., encoding, decoding, transformations). These modules can be trained simultaneously, leveraging data from all domains, and then combined to construct specific GAN networks at test time, according to the specific image translation task. This leads to ModularGAN’s superior flexibility of generating (or translating to) an image in any desired domain. Experimental results demonstrate that our model not only presents compelling perceptual results but also outperforms state-of-the-art methods on multi-domain facial attribute transfer.
Improved Low Reflection Transition From Microstrip Line to Empty Substrate-Integrated Waveguide

Substrate-integrated waveguides (SIWs) maintain the advantages of planar circuits (low loss, low profile, easy manufacturing, and integration in a planar circuit board) and improve the quality factor of filter resonators. Empty substrate-integrated waveguides (ESIWs) substantially reduce the insertion losses, because waves propagate through air instead of a lossy dielectric. The first ESIW used a simple tapering transition that cannot be used for thin substrates. A new transition has recently been proposed, which includes a taper also in the microstrip line, not only inside the ESIW, and so it can be used for all substrates, although measured return losses are only 13 dB. In this letter, the cited transition is improved by placing via holes that prevent undesired radiation, as well as two holes that help to ensure good accuracy in the mechanization of the input iris, thus allowing very good return losses (over 20 dB) in the measured results. A design procedure that allows the successful design of the proposed new transition is also provided. A back-to-back configuration of the improved new transition has been successfully manufactured and measured.
Ambulation training with and without partial weightbearing after traumatic brain injury: results of a randomized, controlled trial.

To test the hypothesis that 8 wks of partial weight-bearing gait retraining improves functional ambulation to a greater extent than traditional physical therapy in individuals after traumatic brain injury.



A randomized, open-label, controlled, cohort study was conducted at two inpatient university-based rehabilitation hospitals. A total of 38 adults with a primary diagnosis of traumatic brain injury and significant gait abnormalities received either 8 wks of standard physical therapy or physical therapy supplemented with partial weight-bearing gait training twice weekly.



Significant (P < 0.05) improvements were detected in both groups on Functional Ambulation Category, Standing Balance Scale, Rivermead Mobility Index, and FIM. However, no differences were found between the treatment groups.



Results did not support the hypothesis that 8 wks of partial weight-bearing gait retraining improves functional ambulation to a greater extent than traditional physical therapy in individuals after traumatic brain injury based on common clinical measures.
A Double-Stage Kalman Filter for Orientation Tracking With an Integrated Processor in 9-D IMU

This paper presents an application-specific integrated processor for an angular estimation system that works with 9-D inertial measurement units. The application-specific instruction-set processor (ASIP) was implemented on field-programmable gate array and interfaced with a gyro-plus-accelerometer 6-D sensor and with a magnetic compass. Output data were recorded on a personal computer and also used to perform a live demo. During system modeling and design, it was chosen to represent angular position data with a quaternion and to use an extended Kalman filter as sensor fusion algorithm. For this purpose, a novel two-stage filter was designed: The first stage uses accelerometer data, and the second one uses magnetic compass data for angular position correction. This allows flexibility, less computational requirements, and robustness to magnetic field anomalies. The final goal of this work is to realize an upgraded application-specified integrated circuit that controls the microelectromechanical systems (MEMS) sensor and integrates the ASIP. This will allow the MEMS sensor gyro plus accelerometer and the angular estimation system to be contained in a single package; this system might optionally work with an external magnetic compass.
Towards an Efficient Method of Modeling "Next Best Action" for Digital Buyer's Journey in B2B

The rise of Digital B2B Marketing has presented us with new opportunities and challenges as compared to traditional e-commerce. B2B setup is different from B2C setup in many ways. Along with the contrasting buying entity (company vs. individual), there are dissimilarities in order size (few dollars in e-commerce vs. up to several thousands of dollars in B2B), buying cycle (few days in B2C vs. 6–18 months in B2B) and most importantly a presence of multiple decision makers (individual or family vs. an entire company). Due to easy availability of the data and bargained complexities, most of the existing literature has been set in the B2C framework and there are not many examples in the B2B context. We present a unique approach to model next likely action of B2B customers by observing a sequence of digital actions. In this paper, we propose a unique two-step approach to model next likely action using a novel ensemble method that aims to predict the best digital asset to target customers as a next action. The paper provides a unique approach to translate the propensity model at an email address level into a segment that can target a group of email addresses. In the first step, we identify the high propensity customers for a given asset using traditional and advanced multinomial classification techniques and use non-negative least squares to stack rank different assets based on the output for ensemble model. In the second step, we perform a penalized regression to reduce the number of coefficients and obtain the satisfactory segment variables. Using real world digital marketing campaign data, we further show that the proposed method outperforms the traditional classification methods.
PaperLens: advanced magic lens interaction above the tabletop

In order to improve the three-dimensional (3D) exploration of virtual spaces above a tabletop, we developed a set of navigation techniques using a handheld magic lens. These techniques allow for an intuitive interaction with two-dimensional and 3D information spaces, for which we contribute a classification into volumetric, layered, zoomable, and temporal spaces. The proposed PaperLens system uses a tracked sheet of paper to navigate these spaces with regard to the Z-dimension (height above the tabletop). A formative user study provided valuable feedback for the improvement of the PaperLens system with respect to layer interaction and navigation. In particular, the problem of keeping the focus on selected layers was addressed. We also propose additional vertical displays in order to provide further contextual clues.
Nextgen ATS Communications, Navigation, And Surveillance Test Bed

Following an approximate 12 month planning and definition period, implementation of the Next Generation Air Transportation System (NextGen) Communication, Navigation and Surveillance (CNS) Test Bed began in earnest during mid-year 2006. This Test Bed, focused on the evaluation of promising CNS technologies and systems, presently encompasses three airports in the Cleveland, Ohio region and a Test and Demonstration Center located at NASA Glenn Research Center (GRC).The Test Bed coverage will be extended before the end of 2007 to include a 200 mile radius around the Cleveland metropolitan area thus creating a wide area air-ground test and demonstration capability. The three included airports (Hopkins International, Burke Lakefront, and Lorain County Regional) are representative of various classes of airports across the country close to population centers that will be central to accommodating forecasted air travel growth over the next 20 years. Sensis, in partnership with the Cleveland Airport System, the Lorain County Regional Airport Authority, and the FAA, has installed an advanced version multilateration surveillance system and wireless communications infrastructure at each of these airports. Implemented as well is a prototype of a Remote Tower System (a.k.a., a Staffed Virtual Tower) that "shadow controls" operations at Burke Lakefront Airport from the Test and Demonstration Center some 13 miles away. The Test Bed is integrated as a system via a prototype of a regional information sharing and management system. Sensis Corporation, GRC, and their Test Bed partners are collaborating to define and test possible solutions for some of the most significant challenges to the success of NextGen. In addition to remote monitoring and control of airports, the issues under investigation by this team include validating the promised efficiencies of negotiated 4-D arrival and departure trajectories, assessing advanced integrated surveillance capabilities, helping solve the continuing safely problem of runway incursions, and improving the efficiency of airport and airline surface operations. GRC is planning to explore the potential for an IEEE 802.16e standard-based wireless airport surface communications network operating in the 5.1 GHz band, soon to be allocated for safety critical air-ground communications services. This paper summarizes the mid-2007 status of this Test Bed and shares plans for the next twelve months.
The bipolarity of light and dark: A review on Bipolar Disorder and circadian cycles.

Bipolar Disorder is characterized by episodes running the full mood spectrum, from mania to depression. Between mood episodes, residual symptoms remain, as sleep alterations, circadian cycle disturbances, emotional deregulation, cognitive impairment and increased risk for comorbidities. The present review intends to reflect about the most recent and relevant information concerning the biunivocal relation between bipolar disorder and circadian cycles.



It was conducted a literature search on PubMed database using the search terms "bipolar", "circadian", "melatonin", "cortisol", "body temperature", "Clock gene", "Bmal1 gene", "Per gene", "Cry gene", "GSK3β", "chronotype", "light therapy", "dark therapy", "sleep deprivation", "lithum" and "agomelatine". Search results were manually reviewed, and pertinent studies were selected for inclusion as appropriate.



Several studies support the relationship between bipolar disorder and circadian cycles, discussing alterations in melatonin, body temperature and cortisol rhythms; disruption of sleep/wake cycle; variations of clock genes; and chronotype. Some therapeutics for bipolar disorder directed to the circadian cycles disturbances are also discussed, including lithium carbonate, agomelatine, light therapy, dark therapy, sleep deprivation and interpersonal and social rhythm therapy.



This review provides a summary of an extensive research for the relevant literature on this theme, not a patient-wise meta-analysis.



In the future, it is essential to achieve a better understanding of the relation between bipolar disorder and the circadian system. It is required to establish new treatment protocols, combining psychotherapy, therapies targeting the circadian rhythms and the latest drugs, in order to reduce the risk of relapse and improve affective behaviour.
Real fuzzy PID control of the UAV AR.Drone 2.0 for hovering under disturbances in known environments

The Indoor flights of UAV (Unmanned Aerial Vehicle) are susceptible to impacts of multiples obstacles and walls. The most basic controller that a drone requires in order to achieve indoor flight, is a controller that can maintain the drone flying in the same site, this is called hovering control. This paper presents a fuzzy PID controller for hovering. The control system to modify the gains of the parameters of the PID controllers in the x and y axes as a function of position and error in each axis, of a known environment. Flight tests were performed over an AR.Drone 2.0, comparing RMSE errors of hovering with classical PID and fuzzy PID under disturbances. The fuzzy PID controller reduced the average error from 11 cm to 8 cm in a 3 minutes test. This result is an improvement over previously published works.
Stability analysis of a grid connected DFIG based WECS with two-mass shaft modeling

In this paper, the dynamic modeling of a doubly-fed induction generator-based wind turbine connected to infinite bus (SMIB) system, is carried out in detail. In most of the analysis, the DFIG stator transients and network transients are neglected. In this paper the interfacing problems while considering stator transients and network transients in the modeling of SMIB system are resolved by connecting a resistor across the DFIG terminals. The effect of simplification of shaft system on the controller gains is also discussed. In addition, case studies are presented to demonstrate the effect of mechanical parameters and controller gains on system stability when accounting the two-mass shaft model for the drive train system.
A decade’s perspective on DNA sequencing technology

The decade since the Human Genome Project ended has witnessed a remarkable sequencing technology explosion that has permitted a multitude of questions about the genome to be asked and answered, at unprecedented speed and resolution. Here I present examples of how the resulting information has both enhanced our knowledge and expanded the impact of the genome on biomedical research. New sequencing technologies have also introduced exciting new areas of biological endeavour. The continuing upward trajectory of sequencing technology development is enabling clinical applications that are aimed at improving medical diagnosis and treatment.
A Field-Based Representation of Surrounding Vehicle Motion from a Monocular Camera

Sensing and presenting on-road information of moving vehicles is essential for fully and semi-automated driving. It is challenging to track vehicles from affordable on-board cameras in crowded scenes. The mismatch or missing data are unavoidable and it is ineffective to directly present uncertain cues to support the decision-making. In this paper, we propose a physical model based on incompressible fluid dynamics to represent the vehicle’s motion, which provides hints of possible collision as a continuous scalar riskmap. We estimate the position and velocity of other vehicles from a monocular on-board camera located in front of the ego-vehicle. The noisy trajectories are then modeled as the boundary conditions in the simulation of advection and diffusion process. We then interactively display the animating distribution of substances, and show that the continuous scalar riskmap well matches the perception of vehicles even in presence of the tracking failures. We test our method on real-world scenes and discuss about its application for driving assistance and autonomous vehicle in the future.