nils-herrmann/clean_scirepeval huggingface dataset:
Combined effects of sleep quality and depression on quality of life in patients with type 2 diabetes

Poor sleep quality and depression negatively impact the health-related quality of life of patients with type 2 diabetes, but the combined effect of the two factors is unknown. This study aimed to assess the interactive effects of poor sleep quality and depression on the quality of life in patients with type 2 diabetes.



Patients with type 2 diabetes (n = 944) completed the Diabetes Specificity Quality of Life scale (DSQL) and questionnaires on sleep quality and depression. The products of poor sleep quality and depression were added to the logistic regression model to evaluate their multiplicative interactions, which were expressed as the relative excess risk of interaction (RERI), the attributable proportion (AP) of interaction, and the synergy index (S).



Poor sleep quality and depressive symptoms both increased DSQL scores. The co-presence of poor sleep quality and depressive symptoms significantly reduced DSQL scores by a factor of 3.96 on biological interaction measures. The relative excess risk of interaction was 1.08. The combined effect of poor sleep quality and depressive symptoms was observed only in women.



Patients with both depressive symptoms and poor sleep quality are at an increased risk of reduction in diabetes-related quality of life, and this risk is particularly high for women due to the interaction effect. Clinicians should screen for and treat sleep difficulties and depressive symptoms in patients with type 2 diabetes.
Why do academics engage with industry ? The entrepreneurial university and individual motivations

The debate on the entrepreneurial university has raised questions about what motivates academics to engage with industry. This paper provides evidence, based on survey data for a comprehensive sample of UK investigators in the physical and engineering sciences. Our results suggest that most academics engage with industry to further their research rather than to commercialize their knowledge. However, there are differences in terms of the channels of engagement. While patenting and spin-off company formation is motivated exclusively by commercialization, joint research, contract research and consulting are strongly informed by research-related motives. We conclude that policy should refrain from focusing on monetary incentives for industry engagement and consider a broader range of incentives for promoting interaction between academia and industry.
Quality care outcomes following transitional care interventions for older people from hospital to home: a systematic review

Provision of high quality transitional care is a challenge for health care providers in many western countries. This systematic review was conducted to (1) identify and synthesise research, using randomised control trial designs, on the quality of transitional care interventions compared with standard hospital discharge for older people with chronic illnesses, and (2) make recommendations for research and practice.



Eight databases were searched; CINAHL, Psychinfo, Medline, Proquest, Academic Search Complete, Masterfile Premier, SocIndex, Humanities and Social Sciences Collection, in addition to the Cochrane Collaboration, Joanna Briggs Institute and Google Scholar. Results were screened to identify peer reviewed journal articles reporting analysis of quality indicator outcomes in relation to a transitional care intervention involving discharge care in hospital and follow-up support in the home. Studies were limited to those published between January 1990 and May 2013. Study participants included people 60 years of age or older living in their own homes who were undergoing care transitions from hospital to home. Data relating to study characteristics and research findings were extracted from the included articles. Two reviewers independently assessed studies for risk of bias.



Twelve articles met the inclusion criteria. Transitional care interventions reported in most studies reduced re-hospitalizations, with the exception of general practitioner and primary care nurse models. All 12 studies included outcome measures of re-hospitalization and length of stay indicating a quality focus on effectiveness, efficiency, and safety/risk. Patient satisfaction was assessed in six of the 12 studies and was mostly found to be high. Other outcomes reflecting person and family centred care were limited including those pertaining to the patient and carer experience, carer burden and support, and emotional support for older people and their carers. Limited outcome measures were reported reflecting timeliness, equity, efficiencies for community providers, and symptom management.



Gaps in the evidence base were apparent in the quality domains of timeliness, equity, efficiencies for community providers, effectiveness/symptom management, and domains of person and family centred care. Further research that involves the person and their family/caregiver in transitional care interventions is needed.
A General Framework for Agglomerative Hierarchical Clustering Algorithms

This paper presents a general framework for agglomerative hierarchical clustering based on graphs. Different hierarchical agglomerative clustering algorithms can be obtained from this framework, by specifying an inter-cluster similarity measure, a subgraph of the 13-similarity graph, and a cover routine. We also describe two methods obtained from this framework called hierarchical compact algorithm and hierarchical star algorithm. These algorithms have been evaluated using standard document collections. The experimental results show that our methods are faster and obtain smaller hierarchies than traditional hierarchical algorithms while achieving a similar clustering quality
Linear Time Euclidean Distance

Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a two-dimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels in the image. The rst algorithm, which is of primarily theoretical interest, constructs the complete Voronoi diagram. The second, more practical, algorithm constructs the Voronoi diagram where it intersects the horizontal lines passing through the image pixel centres. Extensions to higher dimensional images and to other distance functions are also discussed.
Speaker identification using FBCC in Malayalam language

Speaker identification attempts to determine the best possible match from a group of certain speakers, for any given input speech signal. The text-independent speaker identification system does the task to identify the person who speaks regardless of what is said. The first step in speaker identification is the extraction of features. In this proposed method, the Bessel features are used as an alternative to the popular techniques like MFCC and LPCC. The quasi-stationary nature of speech signal is more efficiently represented by damped sinusoidal basis function that is more natural for the voiced speech signal. Since Bessel functions have damped sinusoidal as basis function, it is more natural choice for the representation of speech signals. Here, Bessel features derived from the speech signal is used for creating the Gaussian mixture models for text independent speaker identification. A set of ten speakers is used for modelling using Gaussian mixtures. The proposed system is made to test over the Malayalam database obtaining an efficiency of 98% which is promising.
The Inside is the Outside : The Relational as the ( Feminine ) Space of the Radical

It may seem precursory to begin my essay with an image that has been haunting me since September 11, but in a concise way it prefigures many issues I will write about. It is an image of a work by the Chilean artist and poet, Cecilia Vicuna, who has been living in New York for many years. The work dates from 1981 and shows a word drawn in three colors of pigment (white, blue, and red—also the colors of the American flag) on the pavement of the West Side Highway with the World Trade Center on the horizon. It reads in Spanish: Parti si passion (Participation), which Vicuna unravels as “to say yes in passion, or to partake of suffering.” Revealing aspects of connectivity and compassion, the word spelled out on the road was as ephemeral as its meaning remained for the art world. Unnoticed and unacknowledged, it disappeared in dust, but becomes intelligible in the present. This precarious work tells us how certain art practices, in their continuous effort to press forward a different perception of the world, have a visionary content that is marginalized because of fixed conventional readings of art, but nevertheless is bound to be recognized. My essay will seek to uncover the latency of this kind of work in the second half of the twentieth century, which is slowly coming into being today and can be understood because of feminist practice, but also perhaps because of an abruptly changed reality. Focusing on the work of two SouthAmerican artists—Lygia Clark (1920-1988) and Anna Maria Maiolino (born in 1942), both from Brazil—I will address the topic of “the relational as the radical.”
Reliability of Solid-State Drives Based on NAND Flash Memory

This paper reviews the reliability of solid-state drives (SSDs) based on NAND Flash memory from the perspectives of failure mechanisms, design mitigations, qualification methods, and field failure rates. NAND reliability is dominated by gradual memory-cell degradation in late life and defects such as interconnect shorts earlier in life. Design mitigations exist for these mechanisms. Qualification methods standardized in JEDEC JESD218 are designed to evaluate the mechanisms and mitigations, over a full drive lifetime, in the laboratory. Full-lifetime qualification provides confidence in the long-term reliability of SSDs that cannot be achieved by the early-life qualifications performed on hard disk drives. If NAND mechanisms are sufficiently suppressed, field reliability will be dominated by non-NAND mechanisms such as firmware bugs, power-loss events, radiation-induced soft errors, and failures in non-NAND components. A wide range of design validation and qualification tests are necessary to evaluate these non-NAND mechanisms. Published field reliability statistics indicate that SSDs are more reliable on average than HDDs, but they are not immune to failure, and there is wide variation among models. The NAND and non-NAND mechanisms are illustrated through new case studies of SSD internal qualification and field reliability data.
Involvement of obliquus capitis inferior muscle in dystonic head tremor.

Head tremor is a common feature in cervical dystonia (CD) and often less responsive to botulinum neurotoxin (BoNT) treatment than dystonic posturing. Ultrasound allows accurate targeting of deeper neck muscles.



In 35 CD patients with dystonic head tremor the depth and thickness of the splenius capitis (SPL), semispinalis capitis and obliquus capitis inferior muscles (OCI) were assessed using ultrasound. Ultrasound guided EMG recordings were performed from the SPL and OCI.



Burst-like tremor activity was present in both OCI in 25 and in one in 10 patients. In 18 patients, tremor activity was present in one SPL and in 2 in both SPL. Depth and thickness of OCI, SPL and semispinalis capitis muscles were very variable.



Muscular activity underlying tremulous CD is most commonly present in OCI. Due to the variability of muscle thickness, we suggest ultrasound guided BoNT injections into OCI.
Anterior Decompression and Shortening Reconstruction with a Titanium Mesh Cage through a Posterior Approach Alone for the Treatment of Lumbar Burst Fractures

A retrospective study.



To examine the efficacy and safety for a posterior-approach circumferential decompression and shortening reconstruction with a titanium mesh cage for lumbar burst fractures.


OVERVIEW OF LITERATURE
Surgical decompression and reconstruction for severely unstable lumbar burst fractures requires an anterior or combined anteroposterior approach. Furthermore, anterior instrumentation for the lower lumbar is restricted through the presence of major vessels.



Three patients with an L1 burst fracture, one with an L3 and three with an L4 (5 men, 2 women; mean age, 65.0 years) who underwent circumferential decompression and shortening reconstruction with a titanium mesh cage through a posterior approach alone and a 4-year follow-up were evaluated regarding the clinical and radiological course.



Mean operative time was 277 minutes. Mean blood loss was 471 ml. In 6 patients, the Frankel score improved more than one grade after surgery, and the remaining patient was at Frankel E both before and after surgery. Mean preoperative visual analogue scale was 7.0, improving to 0.7 postoperatively. Local kyphosis improved from 15.7° before surgery to -11.0° after surgery. In 3 cases regarding the mid to lower lumbar patients, local kyphosis increased more than 10° by 3 months following surgery, due to subsidence of the cages. One patient developed severe tilting and subsidence of the cage, requiring additional surgery.



The results concerning this small series suggest the feasibility, efficacy, and safety of this treatment for unstable lumbar burst fractures. This technique from a posterior approach alone offers several advantages over traditional anterior or combined anteroposterior approaches.
Low Awareness of Breast Cancer and Considerable Barriers to Early Presentation Among Saudi Women at a Primary Care Setting

In Saudi Arabia, breast cancer is diagnosed at advanced stage compared to Western countries. Nevertheless, the perceived barriers to delayed presentation have been poorly examined. Additionally, available breast cancer awareness data are lacking validated measurement tool. The aim of this study is to evaluate the level of breast cancer awareness and perceived barriers to seeking medical care among Saudi women, using internationally validated tool. A cross-sectional study was conducted among adult Saudi women attending a primary care center in Riyadh during February 2014. Data were collected using self-administered questionnaire based on the Breast Cancer Awareness Measure (CAM-breast). Out of 290 women included, 30 % recognized five or more (out of nine) non-lump symptoms of breast cancer, 31 % correctly identified the risky age of breast cancer (set as 50 or 70 years), 28 % reported frequent (at least once a month) breast checking. Considering the three items of the CAM-breast, only 5 % were completely aware while 41 % were completely unaware of breast cancer. The majority (94 %) reported one or more barriers. The most frequently reported barrier was the difficulty of getting a doctor appointment (39 %) followed by worries about the possibility of being diagnosed with breast cancer (31 %) and being too busy to seek medical help (26 %). We are reporting a major gap in breast cancer awareness and several logistic and emotional barriers to seeking medical care among adult Saudi women. The current findings emphasized the critical need for an effective national breast cancer education program to increase public awareness and early diagnosis.
Range of Motion Requirements for Upper-Limb Activities of Daily Living.

We quantified the range of motion (ROM) required for eight upper-extremity activities of daily living (ADLs) in healthy participants.



Fifteen right-handed participants completed several bimanual and unilateral basic ADLs while joint kinematics were monitored using a motion capture system. Peak motions of the pelvis, trunk, shoulder, elbow, and wrist were quantified for each task.



To complete all activities tested, participants needed a minimum ROM of -65°/0°/105° for humeral plane angle (horizontal abduction-adduction), 0°-108° for humeral elevation, -55°/0°/79° for humeral rotation, 0°-121° for elbow flexion, -53°/0°/13° for forearm rotation, -40°/0°/38° for wrist flexion-extension, and -28°/0°/38° for wrist ulnar-radial deviation. Peak trunk ROM was 23° lean, 32° axial rotation, and 59° flexion-extension.



Full upper-limb kinematics were calculated for several ADLs. This methodology can be used in future studies as a basis for developing normative databases of upper-extremity motions and evaluating pathology in populations.
Fully Homomorphic Encryption for Classification in Machine Learning

Using fully homomorphic encryption scheme, we construct fully homomorphic encryption scheme FHE4GT that can homomorphically compute an encryption of the greater-than bit that indicates x > x' or not, given two ciphertexts c and c' of x and x', respectively, without knowing the secret key. Then, we construct homomorphic classifier homClassify that can homomorphically classify a given encrypted data without decrypting it, using machine learned parameters.
Proposed application of big data analytics in healthcare at Maharaja Yeshwantrao Hospital

This paper gives an insight of how we can store healthcare data digitally like patient's records as an Electronic Health Record (EHR) and how we can generate useful information from these records by using analytics techniques and tools which will help in saving time and money of patients as well as the doctors. This paper is fully focused towards the Maharaja Yeshwantrao Hospital (M.Y.) located in Indore, Madhya Pradesh, India. M.Y hospital is the central India's largest government hospital. It generates large amount of heterogeneous data from different sources like patients health records, laboratory test result, electronic medical equipment, health insurance data, social media, drug research, genome research, clinical outcome, transaction and from Mahatma Gandhi Memorial medical college which is under MY hospital. To manage this data, data analytics may be used to make it useful for retrieval. Hence the concept of "big data" can be applied. Big data is characterized as extremely large data sets that can be analysed computationally to find patterns, trends, and associations, visualization, querying, information privacy and predictive analytics on large wide spread collection of data. Big data analytics can be done using Hadoop which plays an effective role in performing meaningful real-time analysis on the large volume of this data to predict the emergency situations before it happens. This paper also discusses about the EHR and the big data usage and its analytics at M.Y. hospital.
A relativistic extension of Hopfield neural networks via the mechanical analogy

We propose a modification of the cost function of the Hopfield model whose salient features shine in its Taylor expansion and result in more than pairwise interactions with alternate signs, suggesting a unified framework for handling both with deep learning and network pruning. In our analysis, we heavily rely on the Hamilton-Jacobi correspondence relating the statistical model with a mechanical system. In this picture, our model is nothing but the relativistic extension of the original Hopfield model (whose cost function is a quadratic form in the Mattis magnetization which mimics the non-relativistic Hamiltonian for a free particle). We focus on the low-storage regime and solve the model analytically by taking advantage of the mechanical analogy, thus obtaining a complete characterization of the free energy and the associated self-consistency equations in the thermodynamic limit. On the numerical side, we test the performances of our proposal with MC simulations, showing that the stability of spurious states (limiting the capabilities of the standard Hebbian construction) is sensibly reduced due to presence of unlearning contributions in this extended framework.
Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder

Accurate segmentation of anatomical structures in chest radiographs is essential for many computer-aided diagnosis tasks. In this paper we investigate the latest fully-convolutional architectures for the task of multi-class segmentation of the lungs field, heart and clavicles in a chest radiograph. In addition, we explore the influence of using different loss functions in the training process of a neural network for semantic segmentation. We evaluate all models on a common benchmark of 247 X-ray images from the JSRT database and ground-truth segmentation masks from the SCR dataset. Our best performing architecture, is a modified U-Net that benefits from pre-trained encoder weights. This model outperformed the current state-of-the-art methods tested on the same benchmark, with Jaccard overlap scores of 96.1% for lung fields, 90.6% for heart and 85.5% for clavicles.
The impact of mindfulness-based interventions on brain activity: A systematic review of functional magnetic resonance imaging studies

Mindfulness-based interventions are increasingly used in the treatment and prevention of mental health conditions. Despite this, the mechanisms of change for such interventions are only beginning to be understood, with a number of recent studies assessing changes in brain activity. The aim of this systematic review was to assess changes in brain functioning associated with manualised 8-session mindfulness interventions. Searches of PubMed and Scopus databases resulted in 39 papers, 7 of which were eligible for inclusion. The most consistent longitudinal effect observed was increased insular cortex activity following mindfulness-based interventions. In contrast to previous reviews, we did not find robust evidence for increased activity in specific prefrontal cortex sub-regions. These findings suggest that mindfulness interventions are associated with changes in functioning of the insula, plausibly impacting awareness of internal reactions 'in-the-moment'. The studies reviewed here demonstrated a variety of effects across populations and tasks, pointing to the need for greater consistency in future study design.
Sensing and coverage for a network of heterogeneous robots

We address the problem of covering an environment with robots equipped with sensors. The robots are heterogeneous in that the sensor footprints are different. Our work uses the location optimization framework in with three significant extensions. First, we consider robots with different sensor footprints, allowing, for example, aerial and ground vehicles to collaborate. We allow for finite size robots which enables implementation on real robotic systems. Lastly, we extend the previous work allowing for deployment in non convex environments.
A Survey of the Application of Machine Learning in Decision Support Systems

Machine learning is a useful technology for decision support systems and assumes greater importance in research and practice. Whilst much of the work focuses technical implementations and the adaption of machine learning algorithms to application domains, the factors of machine learning design affecting the usefulness of decision support are still understudied. To enhance the understanding of machine learning and its use in decision support systems, we report the results of our content analysis of design-oriented research published between 1994 and 2013 in major Information Systems outlets. The findings suggest that the usefulness of machine learning for supporting decision-makers is dependent on the task, the phase of decision-making, and the applied technologies. We also report about the advantages and limitations of prior research, the applied evaluation methods and implications for future decision support research. Our findings suggest that future decision support research should shed more light on organizational and people-related evaluation criteria.