nils-herrmann/clean_scirepeval huggingface dataset:
Broad-side crosstalk mitigation in dual-stripline designs

Dual-striplines are gaining popularity in the high-density computer system designs to save printed circuit board (PCB) cost and achieve smaller form factor. However, broad-side near-end/far-end crosstalk (NEXT/FEXT) between dualstriplines is a major concern that potentially has a significant impact to the signal integrity. In this paper, the broadside coupling between two differential pairs, and a differential pair and a single-ended trace in a dual-stripline design, is investigated and characterized. An innovative design methodology and routing strategy are proposed to effectively mitigate the broad-side coupling without additional routing space.
Building measure-based prediction models for UML class diagram maintainability

The usefulness of measures for the analysis and design of object oriented (OO) software is increasingly being recognized in the field of software engineering research. In particular, recognition of the need for early indicators of external quality attributes is increasing. We investigate through experimentation whether a collection of UML class diagram measures could be good predictors of two main subcharacteristics of the maintainability of class diagrams: understandability and modifiability. Results obtained from a controlled experiment and a replica support the idea that useful prediction models for class diagrams understandability and modifiability can be built on the basis of early measures, in particular, measures that capture structural complexity through associations and generalizations. Moreover, these measures seem to be correlated with the subjective perception of the subjects about the complexity of the diagrams. This fact shows, to some extent, that the objective measures capture the same aspects as the subjective ones. However, despite our encouraging findings, further empirical studies, especially using data taken from real projects performed in industrial settings, are needed. Such further study will yield a comprehensive body of knowledge and experience about building prediction models for understandability and modifiability.
High Range-Resolution Monopulse Tracking Radar

High range-resolution monopulse (HRRM) tracking radar which maintains wide instantaneous bandwidth through both range and angle error sensing channels provides range, azimuth, elevation, and amplitude for each resolved part of the target. The three-dimensional target detail can be used to improve and extend radar performance in several ways: for improved precision of target location, for target classification and recognition, to counter repeater-type ECM, to improve low-angle multipath tracking, to resolve multiple targets, as a miss-distance measurement capability, and for improved tracking in chaff and clutter. These have been demonstrated qualitatively except for the ECCM to repeater ECM and low-altitude tracking improvement. Initial results from an experimental HRRM radar with 3-ns pulse length show resolution of aircraft into its major parts and precise location of each resolved part accurately in range and angle. Realtime closed-loop tracking is performed on aircraft in flight using high-speed sampled, digitized, and processed HRRM range and angle video data. Clutter rejection capability is also demonstrated.
Pouch of Douglas pelvic hernia: a rare entity managed laparoscopically

Pouch of Douglas hernias are uncommon forms of pelvic hernia. They are most commonly seen in multiparous, elderly women and those having undergone previous pelvic surgery (Stamatiou et al.  2010). Herein, we present a case of a 77-year-old female presenting with groin pain due to a Pouch of Douglas hernia. She had no previous abdominal or pelvic surgery. This was repaired via a trans-abdominal pre-peritoneal approach and the patient’s symptoms resolved. To our knowledge, this is the first case report in the literature of an idiopathic Pouch of Douglas hernia managed laparoscopically.
Towards a multi-DOF passive balancing mechanism for upper limbs

Gravity balancing has great significance in many rehabilitation applications and one example is in minimizing the resistance of lifting a patient's upper limb due to its own weight. As compared to commonly used active method in exoskeleton, passive weight compensation offers many other advantages such as elimination of motors which reduces the overall load acting on the patient. However, the torque about each joint due to the weight of the upper and fore arm is dependent on the orientation and location of each other, which makes it a challenge to compensate. Hence, this paper proposes and develop a passive method to compensate the torques on each joint. The proposed design includes a decoupling mechanism for isolating the torsional effect between various linkages and a realizable torsional compliant beam which can provide a specific torsional stiffness function to compensate the torque due to the arm's weight. In place of the usual expensive zero-length spring as the solution, an algorithm that generates the appropriate compliant beam design is also presented in this paper. The end result of the manipulator arm is a reduced required joint torque for gravity compensation using only passive means. A two-DOF prototype, with easy possible extension of additional DOF, has been built, and experiments are performed to illustrate, verify and quantify the effectiveness of the proposed method.
Face recognition techniques, their advantages, disadvantages and performance evaluation

A human brain can store and remember thousands of faces in a person's life time, however it is very difficult for an automated system to reproduce the same results. Faces are complex and multidimensional which makes extraction of facial features to be very challenging, yet it is imperative for our face recognition systems to be better than our brain's capabilities. The face like many physiological biometrics that include fingerprint, hand geometry, retina, iris and ear uniquely identifies each individual. In this paper we focus mainly on the face recognition techniques. This review looks at three types of recognition approaches namely holistic, feature based (geometric) and the hybrid approach. We also look at the challenges that are face by the approaches.
FooTweets: A Bilingual Parallel Corpus of World Cup Tweets

The way information spreads through society has changed significantly over the past decade with the advent of online social networking. Twitter, one of the most widely used social networking websites, is known as the real-time, public microblogging network where news breaks first. Most users love it for its iconic 140-character limitation and unfiltered feed that show them news and opinions in the form of tweets. Tweets are usually multilingual in nature and of varying quality. However, machine translation (MT) of twitter data is a challenging task especially due to the following two reasons: (i) tweets are informal in nature (i.e., violates linguistic norms), and (ii) parallel resource for twitter data is scarcely available on the Internet. In this paper, we develop FooTweets, a first parallel corpus of tweets for English–German language pair. We extract 4, 000 English tweets from the FIFA 2014 world cup and manually translate them into German with a special focus on the informal nature of the tweets. In addition to this, we also annotate sentiment scores between 0 and 1 to all the tweets depending upon the degree of sentiment associated with them. This data has recently been used to build sentiment translation engines and an extensive evaluation revealed that such a resource is very useful in machine translation of user generated content.
NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning

Distributed data management systems often operate on "elastic'' clusters that can scale up or down on demand. These systems face numerous challenges, including data fragmentation, replication, and cluster sizing. Unfortunately, these challenges have traditionally been treated independently, leaving administrators with little insight on how the interplay of these decisions affects query performance. This paper introduces NashDB, an adaptive data distribution framework that relies on an economic model to automatically balance the supply and demand of data fragments, replicas, and cluster nodes. NashDB adapts its decisions to query priorities and shifting workloads, while avoiding underutilized cluster nodes and redundant replicas. This paper introduces and evaluates NashDB's model, as well as a suite of optimization techniques designed to efficiently identify data distribution schemes that match workload demands and transition the system to this new scheme with minimum data transfer overhead. Experimentally, we show that NashDB is often Pareto dominant compared to other solutions.
Corporate Social Responsibility in Emerging Markets: the Chilean Experience

Little is known about corporate social responsibility (CSR) in lesser developed countries. To address this knowledge gap, we used Chile as a test case, and conducted 44 in-depth interviews with informants who are leading CSR initiatives. Using institutional theory as a lens, we outline the state of CSR practice in Chile, describe the factors that have led to the emergence of CSR, and note the barriers to wider adoption of these initiatives.
Transgender people: health at the margins of society

In this paper we examine the social and legal conditions in which many transgender people (often called trans people) live, and the medical perspectives that frame the provision of health care for transgender people across much of the world. Modern research shows much higher numbers of transgender people than were apparent in earlier clinic-based studies, as well as biological factors associated with gender incongruence. We examine research showing that many transgender people live on the margins of society, facing stigma, discrimination, exclusion, violence, and poor health. They often experience difficulties accessing appropriate health care, whether specific to their gender needs or more general in nature. Some governments are taking steps to address human rights issues and provide better legal protection for transgender people, but this action is by no means universal. The mental illness perspective that currently frames health-care provision for transgender people across much of the world is under scrutiny. The WHO diagnostic manual may soon abandon its current classification of transgender people as mentally disordered. Debate exists as to whether there should be a diagnosis of any sort for transgender children below the age of puberty.
Evaluating the past to improve the future - A qualitative study of ICU patients' experiences.

The recovery period for patients who have been in an intensive care unitis often prolonged and suboptimal. Anxiety, depression and post-traumatic stress disorder are common psychological problems. Intensive care staff offer various types of intensive aftercare. Intensive care follow-up aftercare services are not standard clinical practice in Norway.



The overall aim of this study is to investigate how adult patients experience theirintensive care stay their recovery period, and the usefulness of an information pamphlet.



A qualitative, exploratory research with semi-structured interviews of 29 survivors after discharge from intensive care and three months after discharge from the hospital.



Two main themes emerged: "Being on an unreal, strange journey" and "Balancing between who I was and who I am" Patients' recollection of their intensive care stay differed greatly. Continuity of care and the nurse's ability to see and value individual differences was highlighted. The information pamphlet helped intensive care survivors understand that what they went through was normal.



Continuity of care and an individual approach is crucial to meet patients' uniqueness and different coping mechanisms. Intensive care survivors and their families must be included when information material and rehabilitation programs are designed and evaluated.
AADS: Augmented Autonomous Driving Simulation using Data-driven Algorithms

Simulation systems have become an essential component in the development and validation of autonomous driving technologies. The prevailing state-of-the-art approach for simulation is to use game engines or high-fidelity computer graphics (CG) models to create driving scenarios. However, creating CG models and vehicle movements (e.g., the assets for simulation) remains a manual task that can be costly and time-consuming. In addition, the fidelity of CG images still lacks the richness and authenticity of real-world images and using these images for training leads to degraded performance. In this paper we present a novel approach to address these issues: Augmented Autonomous Driving Simulation (AADS). Our formulation augments real-world pictures with a simulated traffic flow to create photo-realistic simulation images and renderings. More specifically, we use LiDAR and cameras to scan street scenes. From the acquired trajectory data, we generate highly plausible traffic flows for cars and pedestrians and compose them into the background. The composite images can be re-synthesized with different viewpoints and sensor models (camera or LiDAR). The resulting images are photo-realistic, fully annotated, and ready for end-to-end training and testing of autonomous driving systems from perception to planning. We explain our system design and validate our algorithms with a number of autonomous driving tasks from detection to segmentation and predictions. Compared to traditional approaches, our method offers unmatched scalability and realism. Scalability is particularly important for AD simulation and we believe the complexity and diversity of the real world cannot be realistically captured in a virtual environment. Our augmented approach combines the flexibility in a virtual environment (e.g., vehicle movements) with the richness of the real world to allow effective simulation of anywhere on earth.
Stress, coping and satisfaction in nursing students.

This article is a report of a study conducted to explore the relationship between sources of stress and psychological well-being and to consider how different sources of stress and coping resources might function as moderators and mediators on well-being.



In most research exploring sources of stress and coping in nursing students, stress has been construed as psychological distress. Sources of stress likely to enhance well-being and, by implication, learning have not been considered.



A questionnaire was administered to 171 final year nursing students in 2008. Questions were asked to measure sources of stress when rated as likely to contribute to distress (a hassle) and rated as likely to help one achieve (an uplift). Support, control, self-efficacy and coping style were also measured, along with their potential moderating and mediating effects on well-being, operationalized using the General Health Questionnaire and measures of course and career satisfaction.



Sources of stress likely to lead to distress were more often predictors of well-being than were sources of stress likely to lead to positive, eustress states, with the exception of clinical placement demands. Self-efficacy, dispositional control and support were important predictors, and avoidance coping was the strongest predictor of adverse well-being. Approach coping was not a predictor of well-being. The mere presence of support appeared beneficial as well as the utility of that support to help a student cope.



Initiatives to promote support and self-efficacy are likely to have immediate benefits for student well-being. In course reviews, nurse educators need to consider how students' experiences might contribute not just to potential distress, but to eustress as well.
Policy-Based Adaptation of Byzantine Fault Tolerant Systems

Malicious attacks, hardware failures or even operator mistakes may cause a system to behave in an arbitrary, and hard to predict manner. Byzantine fault tolerance (BFT) encompasses a number of techniques to make a system robust in face of arbitrary faults. Several BFT algorithms have been proposed in the literature, each optimized for different operational conditions. For that reason, adaptive systems able to adapt BFT systems to the current operational conditions have been proposed but unfortunately all lack expressive mechanisms to specify adaptation policies. Other systems provide expressive mechanisms to specify those policies but lack important abstractions for BFT systems’ adaptation. Considering this context, in this thesis we present an adaptation policy specification language that targets Byzantine fault tolerant systems. In addition, we present a robust engine that, given a policy written in the proposed language, is able to decide the best adaptations to guide a managed system in a path of accordance with its business goals.
Management Accounting Software and Accounting Practices : Empirical Study on SME Enterprises

There appears to be a paradox between the methods of product valuation considered theoretically most suitable and those effectively used by enterprises according to empirical studies already made. This research strives to clarify which factors explain enterprises continued use of theoretically inadequate methods. The study aims to identify the methods used by Portuguese small and medium size enterprises to value products and to analyze if the management accounting software influences the methods used. Accounting managers from 58 enterprises in 11 Portuguese districts were interviewed. The interviewees stated that the management accounting software influences the method of indirect cost distribution, and the association of these two variables is statistically significant. However, the individual analysis of the interviews led to the detection of a third variable, namely the way in which the product valuation was conceived, and this influences the previous two variables simultaneously. This evidence suggests that the conditioning that accounting managers believed was exerted by the management accounting software on indirect cost distribution was in fact the result of the direct influence of a third variable on the first two, namely the way in which the method was conceived.  management, accounting, software, SME, Portugal
A New Design of Monopole Antenna with 3 . 5 / 5 . 5 GHz Dual Band-Stop Function Using Protruded Strip Resonators

In this paper, a different method for designing an ultra-wideband (UWB) microstrip monopole antenna with dual band-notched characteristic has been presented. The main novelty of the proposed structure is the using of protruded strips as resonators to design an UWB antenna with dual band-stop property. In the proposed design, by cutting the rectangular slot with a pair of protruded T-shaped strips in the ground plane, additional resonance is excited and much wider impedance bandwidth can be produced. To generate a single band-notched function, we convert the square radiating patch to the square-ring structure with a pair of protruded step-shaped strips. By cutting a rectangular slot with the protruded Γ-shaped strip at the feed line, a dual band-notched function is achieved. The measured results reveal that the presented dual band-notched antenna offers a very wide bandwidth from 2.8 to 11.6 GHz, with two notched bands, around of 3.3-3.7 GHz and 5-6 GHz covering all WiMAX and WLAN bands.
Towards Dynamic Computation Graphs via Sparse Latent Structure

Deep NLP models benefit from underlying structures in the data—e.g., parse trees— typically extracted using off-the-shelf parsers. Recent attempts to jointly learn the latent structure encounter a tradeoff: either make factorization assumptions that limit expressiveness, or sacrifice end-to-end differentiability. Using the recently proposed SparseMAP inference, which retrieves a sparse distribution over latent structures, we propose a novel approach for end-to-end learning of latent structure predictors jointly with a downstream predictor. To the best of our knowledge, our method is the first to enable unrestricted dynamic computation graph construction from the global latent structure, while maintaining differentiability.
Visual Question Answering With a Hybrid Convolution Recurrent Model

Visual Question Answering (VQA) is a relatively new task, which tries to infer answer sentences for an input image coupled with a corresponding question. Instead of dynamically generating answers, they are usually inferred by finding the most probable answer from a fixed set of possible answers. Previous work did not address the problem of finding all possible answers, but only modeled the answering part of VQA as a classification task. To tackle this problem, we infer answer sentences by using a Long Short-Term Memory (LSTM) network that allows us to dynamically generate answers for (image, question) pairs. In a series of experiments, we discover an end-to-end Deep Neural Network structure, which allows us to dynamically answer questions referring to a given input image by using an LSTM decoder network. With this approach, we are able to generate both less common answers, which are not considered by classification models, and more complex answers with the appearance of datasets containing answers that consist of more than three words.
Polarization Reconfigurable Slot Antenna With a Novel Compact CPW-to-Slotline Transition for WLAN Application

A polarization reconfigurable slot antenna with a novel coplanar waveguide (CPW)-to-slotline transition for wireless local area networks (WLANs) is proposed and tested. The antenna consists of a square slot, a reconfigurable CPW-to-slotline transition, and two p-i-n diodes. No extra matching structure is needed for modes transiting, which makes it much more compact than all reference designs. The -10 dB bandwidths of an antenna with an implemented bias circuit are 610 (25.4%) and 680 MHz (28.3%) for vertical and horizontal polarizations, respectively. The radiation pattern and gain of the proposed antenna are also tested, and the radiation pattern data were compared to simulation results.