nils-herrmann/clean_scirepeval huggingface dataset:
Ethical issues in using Twitter for population level depression monitoring: a qualitative study
Venue: BMC medical ethics

BackgroundRecently, significant research effort has focused on using Twitter (and other social media) to investigate mental health at the population level. While there has been influential work in developing ethical guidelines for Internet discussion forum based research in public health, there is currently limited work focused on addressing ethical problems in Twitter based public health research, and less still that considers these issues from users' own perspectives. In this work, we aim to investigate public attitudes towards utilizing public domain Twitter data for population level mental health monitoring using a qualitative methodology.MethodsThe study explores user perspectives in a series of five, 2 h focus group interviews. Following a semi structured protocol, 26 Twitter users with and without a diagnosed history of depression discussed general Twitter use, along with privacy expectations, and ethical issues in using social media for health monitoring, with a particular focus on mental health monitoring. Transcripts were then transcribed, redacted, and coded using a constant comparative approach.ResultsWhile participants expressed a wide range of opinions, there was an overall trend towards a relatively positive view of using public domain Twitter data as a resource for population level mental health monitoring, provided that results are appropriately aggregated. Results are divided into five sections: (1) a profile of respondents' Twitter use patterns and use variability; (2) users' privacy expectations, including expectations regarding data reach and permanence; (3) attitudes towards social media based population level health monitoring in general, and attitudes towards mental health monitoring in particular; (4) attitudes towards individual versus population level health monitoring; and (5) users' own recommendations for the appropriate regulation of population level mental health monitoring.ConclusionsFocus group data reveal a wide range of attitudes towards the use of public domain social media "big data" in population health research, from enthusiasm, through acceptance, to opposition. Study results highlight new perspectives in the discussion of ethical use of public data, particularly with respect to consent, privacy, and oversight.
Identifying Depression Related Tweets from Twitter for Public Health Monitoring

We present our work towards automatic monitoring of major depressive disorder at the population level leveraging social media and natural language processing. In this pilot study, we manually annotated Twitter tweets i.e. whether the tweet conveys clinical evidence of depression or not, and if the tweet is depression related, whether it conveys low mood, fatigue or loss of energy, or problems with social environment. Our classifiers trained with simple features can automatically distinguish between tweets with clinical evidence of depression or not with promising results, suggesting complete automation is possible.
Interrelation of Evaluation and Self Evaluation in the Diagnostic Procedures to Assess Teachers' Readiness for Innovation.

The paper solves the problem of the relationship of external diagnosis and self diagnosis of readiness of teachers to innovative activity. It highlights major disadvantages of measurement tools that are used to this process. The author demonstrates an alternative approach to harmonizing the diagnosis, based on a modular diagnostic model, general diagnostic tools, to synchronize the management tasks of the process of readiness for innovation and self innovation. The proposed approach, in the author's opinion, creates the necessary conditions for improving the quality of innovative activity of both teachers and ongoing modernization of education.
Recommendations for the next generation of global freshwater biological monitoring tools

Biological monitoring has a long history in freshwaters, where much of the pioneering work in this field was developed over a 100 years ago but few of the traditional monitoring tools provide the global perspective on biodiversity loss and its consequences for ecosystem functioning that are now needed. Rather than forcing existing monitoring paradigms to respond to questions they were never originally designed to address, we need to take a step back and assess the prospects for novel approaches that could be developed and adopted in the future. To resolve some of the issues with indicators currently used to inform policymakers, we highlight new biological monitoring tools that are being used, or could be developed in the near future, which (1) consider less studied taxonomic groups, (2) are standardised across regions to allow global comparisons, and (3) measure change over multiple time points. The new tools we suggest make use of some of the key technological and logistical advances seen in recent years including remote sensing, molecular tools, and local to global citizen science networks. We recommend that these new indicators should be considered in future assessments of freshwater ecosystem health and contribute to the evidence base for global to regional (and national) assessments of biodiversity and ecosystem services: for example, within the emerging framework of the Intergovernmental Platform on Biodiversity and Ecosystem Services.
A road map for designing and implementing a biological monitoring program
Venue: Environmental Monitoring and Assessment

Designing and implementing natural resource monitoring is a challenging endeavor undertaken by many agencies, NGOs, and citizen groups worldwide. Yet many monitoring programs fail to deliver useful information for a variety of administrative (staffing, documentation, and funding) or technical (sampling design and data analysis) reasons. Programs risk failure if they lack a clear motivating problem or question, explicit objectives linked to this problem or question, and a comprehensive conceptual model of the system under study. Designers must consider what "success" looks like from a resource management perspective, how desired outcomes translate to appropriate attributes to monitor, and how they will be measured. All such efforts should be filtered through the question "Why is this important?" Failing to address these considerations will produce a program that fails to deliver the desired information. We addressed these issues through creation of a "road map" for designing and implementing a monitoring program, synthesizing multiple aspects of a monitoring program into a single, overarching framework. The road map emphasizes linkages among core decisions to ensure alignment of all components, from problem framing through technical details of data collection and analysis, to program administration. Following this framework will help avoid common pitfalls, keep projects on track and budgets realistic, and aid in program evaluations. The road map has proved useful for monitoring by individuals and teams, those planning new monitoring, and those reviewing existing monitoring and for staff with a wide range of technical and scientific skills.
A safe and feasible "clock face" duct to mucosa pancreaticojejunostomy with a very low incidence of anastomotic failure: A single center experience of 248 patients.
Venue: Journal of visceral surgery

Postoperative pancreatic fistula (POPF) is one of the most frequent and serious postoperative complications of pancreatoduodenectomy (PD) We sought to assess the impact of a novel pancreaticojejunostomy (PJ) on the rates of POPF and overall postoperative complications.  Between 01/2010 and 12/2013, a total of 248 consecutive patients who underwent PD with a modified PJ were identified from our database and retrospectively analyzed. POPF cases were divided into three categories (ISGPF international study group guidelines) biochemical fistula without clinical sequelae (grade A) fistula requiring any therapeutic intervention (grade B) and fistula with severe clinical sequelae (grade C) Perioperative outcomes were recorded and analyzed.  The overwhelming majority of patients had no evidence of fistula. Grade A POPF was observed in 9 (3.62% grade B in 1 (0.40% and grade C in 0 patients. There were no postoperative deaths. Overall complications occurred in 61 patients (24.59% of patients after PD.  This modified pancreaticojejunostomy is widely applicable and is associated with very low rates of POPF, low postoperative morbidity and mortality. Overall, it is a feasible and safe novel approach with excellent short term outcomes.
Design space exploration of FPGA based Deep Convolutional Neural Networks
Venue: 2016 21st Asia and South Pacific Design Automation Conference (ASP DAC)

Deep Convolutional Neural Networks (DCNN) have proven to be very effective in many pattern recognition applications, such as image classification and speech recognition. Due to their computational complexity, DCNNs demand implementations that utilize custom hardware accelerators to meet performance and energy efficiency constraints. In this paper we propose an FPGA based accelerator architecture which leverages all sources of parallelism in DCNNs. We develop analytical feasibility and performance estimation models that take into account various design and platform parameters. We also present a design space exploration algorithm for obtaining the implementation with the highest performance on a given platform. Simulation results with a real life DCNN demonstrate that our accelerator outperforms other competing approaches, which disregard some sources of parallelism in the application. Most notably, our accelerator runs 1.9x faster than the state of the art DCNN accelerator on the same FPGA device.
A Holistic Approach for Optimizing DSP Block Utilization of a CNN implementation on FPGA
Venue: ICDSC

Deep Neural Networks are becoming the de facto standard models for image understanding, and more generally for computer vision tasks. As they involve highly parallelizable computations, Convolutional Neural Networks (CNNs) are well suited to current fine grain programmable logic devices. Thus, multiple CNN accelerators have been successfully implemented on Field Programmable Gate Arrays (FPGAs) Unfortunately, FPGA resources such as logic elements or Digital Signal Processing (DSP) units remain limited. This work presents a holistic method relying on approximate computing and design space exploration to optimize the DSP block utilization of a CNN implementation on FPGA. This method was tested when implementing a reconfigurable Optical Character Recognition (OCR) convolutional neural network on an Altera Stratix V device and varying both data representation and CNN topology in order to find the best combination in terms of DSP block utilization and classification accuracy. This exploration generated dataflow architectures of 76 CNN topologies with 5 different fixed point representation. Most efficient implementation performs 883 classifications/sec at 256 x 256 resolution using 8 of the available DSP blocks.
Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text
Venue: ACL

Modeling relation paths has offered significant gains in embedding models for knowledge base (KB) completion. However, enumerating paths between two entities is very expensive, and existing approaches typically resort to approximation with a sampled subset. This problem is particularly acute when text is jointly modeled with KB relations and used to provide direct evidence for facts mentioned in it. In this paper, we propose the first exact dynamic programming algorithm which enables efficient incorporation of all relation paths of bounded length, while modeling both relation types and intermediate nodes in the compositional path representations. We conduct a theoretical analysis of the efficiency gain from the approach. Experiments on two datasets show that it addresses representational limitations in prior approaches and improves accuracy in KB completion.
Caching and Prefetching Images in a Web Based DICOM Viewer
Venue: 2016 IEEE 29th International Symposium on Computer Based Medical Systems (CBMS)

The general trend of information access anywhere and anytime is also leading to the emergence of innovative medical imaging systems, adapted to this new reality. The HTML5 standard led Web applications to another software level, providing a set of features that allows developing professional Web based medical imaging applications. However, despite the visualization quality that is already possible in HTML5 browsers, the performance is still an issue, due to the typical size of image studies. In this paper, we present a caching and prefetching solution that enriches the end user experience in a Web based DICOM viewer, by reducing data access latency of examinations under revision. We deployed the system in a radiology center for mammography screening, at a national level, and the results show that this technique significantly reduces the average examination access latency, during the reviewing process.
Transformational leadership in nursing and medication safety education: a discussion paper.
Venue: Journal of nursing management

This paper discusses the application of transformational leadership to the teaching and learning of safe medication management.  The prevalence of adverse drug events (ADEs) and medication related hospitalisations (one hundred thousand each year in the USA) are of concern.  This discussion is based on a narrative literature review and scrutiny of international nursing research to synthesise pedagogical strategies for the application of transformational leadership to teaching medication safety.  The four elements relating transformational leadership to medication safety education are: 'Idealised influence' or role modelling, both actual and exemplary, 'Inspirational motivation' providing students with commitment to medication safety, 'Intellectual stimulation' encouraging students to value improvement and change, and 'Individualised consideration' of individual students' educational goals, practice development and patient outcomes. The model lends itself to experiential learning and a case study approach to teaching, offering an opportunity to reduce nursing's theory practice gap.  Transformational leadership for medication safety education is characterised by a focus on the role of nurse educators and mentors in the development of students' abilities, creation of a supportive culture, and enhancement of students' creativity, motivation and ethical behaviour. This will prepare nursing graduates with the competencies necessary to be diligent about medication safety and the prevention of errors.  Teaching medication safety through transformational leadership requires the close collaboration of educators, managers and policy makers. Investigation of strategies to reduced medication errors and consequent patient harm should include exploration of the application of transformational leadership to education and its impact on the number and severity of medication errors.
Benefits of Transformational Leadership in the Context of Education

Following expansive changes in the management of schools and the methods of organizing the teaching as well as the changes in the styles of leadership as the function of management, contemporary approaches to leadership: transactional, charismatic, transformational and interactive become more often the focus of research interest. Each of these theoretical approaches has far reaching impacts and values not only in time but also in a certain context. However, in this paper we give priority to transformational leadership taking into consideration the claim that transformational leadership style is the most suitable for guiding the students within the school conditions. This type of claim has its stronghold in these three points: 1) the ethical dimension of transformational leadership, that is, the moral basis; 2) the validity of previous researches supported by evidence, and 3) evidences of the leaders' practice in the field of education.
Optimization of CRISPR/Cas9 genome editing to modify abiotic stress responses in plants
Venue: Scientific reports

Genome editing using the CRISPR/Cas9 system can be used to modify plant genomes, however, improvements in specificity and applicability are still needed in order for the editing technique to be useful in various plant species. Here, using genome editing mediated by a truncated gRNA (tru gRNA)/Cas9 combination, we generated new alleles for OST2, a proton pump in Arabidopsis, with no off target effects. By following expression of Cas9 and the tru gRNAs, newly generated mutations in CRIPSR/Cas9 transgenic plants were detected with high average mutation rates of up to 32.8% and no off target effects using constitutive promoter. Reducing nuclear localization signals in Cas9 decreased the mutation rate. In contrast, tru gRNA Cas9 cassettes driven by meristematic and reproductive tissue specific promoters increased the heritable mutation rate in Arabidopsis, showing that high expression in the germ line can produce bi allelic mutations. Finally, the new mutant alleles obtained for OST2 exhibited altered stomatal closing in response to environmental conditions. These results suggest further applications in molecular breeding to improve plant function using optimized plant CRISPR/Cas9 systems.
Toward a Reduced Reliance on Conventional Pesticides in European Agriculture.
Venue: Plant disease

Whether modern agriculture without conventional pesticides will be possible or not is a matter of debate. The debate is meaningful within the context of rising health and environmental awareness on one hand, and the global challenge of feeding a steadily growing human population on the other. Conventional pesticide use has come under pressure in many countries, and some European Union (EU) Member States have adopted policies for risk reduction following Directive 2009/128/EC, the sustainable use of pesticides. Highly diverse crop production systems across Europe, having varied geographic and climatic conditions, increase the complexity of European crop protection. The economic competitiveness of European agriculture is challenged by the current legislation, which banned the use of many previously authorized pesticides that are still available and applied in other parts of the world. This challenge could place EU agricultural production at a disadvantage, so EU farmers are seeking help from the research community to foster and support integrated pest management (IPM) Ensuring stable crop yields and quality while reducing the reliance on pesticides is a challenge facing the farming community is today. Considering this, we focus on several diverse situations in European agriculture in general and in European crop protection in particular. We emphasize that the marked biophysical and socio economic differences across Europe have led to a situation where a meaningful reduction in pesticide use can hardly be achieved. Nevertheless, improvements and/or adoption of the knowledge and technologies of IPM can still achieve large gains in pesticide reduction. In this overview, the current pest problems and their integrated management are discussed in the context of specific geographic regions of Europe, with a particular emphasis on reduced pesticide use. We conclude that there are opportunities for reduction in many parts of Europe without significant losses in crop yields.
SQUAD: a spectrum based quality adaptation for dynamic adaptive streaming over HTTP
Venue: MMSys

The application layer based control loops of dynamic adaptive streaming over HTTP (DASH) make video bitrate selection a complex problem. In this work, we review and present new insights into the challenges of DASH rate adaptation. We identify several critical issues that contribute to the degradation of DASH performance with respect to the rate control loops of DASH and TCP. We then introduce a novel DASH quality adaptation algorithm SQUAD, which is specifically designed to ensure high quality of experience (QoE) We implement and test our algorithm together with a number of state of the art quality adaptation algorithms. Through extensive experiments on both testbed and cross Atlantic Internet scenarios, we show that by sacrificing little to none in average quality bitrate, SQUAD provides significantly better QoE in terms of number and magnitude of quality switches.
Decorin alleviated chronic hydrocephalus via inhibiting TGF b1/Smad/CTGF pathway after subarachnoid hemorrhage in rats
Venue: Brain Research

Chronic hydrocephalus is one of the severe complications after subarachnoid hemorrhage (SAH) However, there is no efficient treatment for the prevention of chronic hydrocephalus, partially due to poor understanding of underlying pathogenesis, subarachnoid fibrosis. Transforming growth factor b1(TGF b1) is a potent fibrogenic factor implicated in wide range of fibrotic diseases. To investigate whether decorin, a natural antagonist for TGF b1, protects against subarachnoid fibrosis and chronic hydrocephalus after SAH, two hemorrhage injection SAH model was conducted in 6 week old rats. Recombinant human decorin(rhDecorin) (30ug/2ul) was administered before blood injection and on the 10th day after SAH. TGF b1, p Smad2/3, connective tissue growth factor (CTGF) collagen I and pro collagen I c terminal propeptide were assessed via western blotting, enzyme linked immunosorbent assay, radioimmunoassay and immunofluorescence. And neurobehavioral tests and Morris water maze were employed to evaluate long term neurological functions after SAH. We found that SAH induced heightened activation of TGF b1/Smad/CTGF axis, presenting as a two peak response of TGF b1 in cerebrospinal fluid, elevation of TGF b1, p Smad2/3, CTGF, collagen I in brain parenchyma and pro collagen I c terminal propeptide in cerebrospinal fluid, and increased lateral ventricle index. rhDecorin treatment effectively inhibited up regulation of TGF b1, p Smad2/3, CTGF, collagen I and pro collagen I c terminal propeptide after SAH. Moreover, rhDecorin treatment significantly reduced lateral ventricular index and incidence of chronic hydrocephalus after SAH. Importantly, rhDecorin improved neurocognitive deficits after SAH. In conclusion, rhDecorin suppresses extracellular matrix accumulation and following subarachnoid fibrosis via inhibiting TGF b1/Smad/CTGF pathway, preventing development of hydrocephalus and attenuating long term neurocognitive defects after SAH.