nils-herrmann/clean_scirepeval huggingface dataset:
The Bowel Function Index: a new validated scale for assessing opioid-induced constipation.

The management of opioid-induced constipation (OIC) is often complicated by the fact that clinical measures of constipation do not always correlate with patient perception. As the discomfort associated with OIC can lead to poor compliance with the opioid treatment, a shift in focus towards patient assessment is often advocated.



The Bowel Function Index * (BFI) is a new patient-assessment scale that has been developed and validated specifically for OIC. It is a physician-administered, easy-to-use scale made up of three items (ease of defecation, feeling of incomplete bowel evacuation, and personal judgement of constipation). An extensive analysis has been performed in order to validate the BFI as reliable, stable, clinically valid, and responsive to change in patients with OIC, with a 12-point change in score constituting a clinically relevant change in constipation.



The results of the validation analysis were based on major clinical trials and have been further supported by data from a large open-label study and a pharmaco-epidemiological study, in which the BFI was used effectively to assess OIC in a large population of patients treated with opioids. Although other patient self-report scales exist, the BFI offers several unique advantages. First, by being physician-administered, the BFI minimizes reading and comprehension difficulties; second, by offering general and open-ended questions which capture patient perspective, the BFI is likely to detect most patients suffering from OIC; third, by being short and easy-to-use, it places little burden on the patient, thereby increasing the likelihood of gathering accurate information.



Altogether, the available data suggest that the BFI will be useful in clinical trials and in daily practice.
Objective measurement of use of the reciprocating gait orthosis (RGO) and the electrically augmented RGO in adult patients with spinal cord lesions.

The purpose of the study was to measure objectively the home use of the reciprocating gait orthosis (RGO) and the electrically augmented (hybrid) RGO. It was hypothesised that RGO use would increase following provision of functional electrical stimulation (FES). Five adult subjects participated in the study with spinal cord lesions ranging from C2 (incomplete) to T6. Selection criteria included active RGO use and suitability for electrical stimulation. Home RGO use was measured for up to 18 months by determining the mean number of steps taken per week. During this time patients were supplied with the hybrid system. Three alternatives for the measurement of steps taken were investigated: a commercial digital pedometer, a magnetically actuated counter and a heel contact switch linked to an electronic counter. The latter was found to be the most reliable system and was used for all measurements. Additional information on RGO use was acquired using three patient diaries administered throughout the study and before and after the provision of the hybrid system. Testing of the original hypothesis was complicated by problems in finding a reliable measurement tool and difficulties with data collection. However, the results showed that overall use of the RGO, whether with or without stimulation, is low. Statistical analysis of the step counter results was not realistic. No statistically significant change in RGO use was found between the patient diaries. The study suggests that the addition of electrical stimulation does not increase RGO use. The study highlights the problem of objectively measuring orthotic use in the home.
A Base Integer Programming Model and Benchmark Suite for Liner-Shipping Network Design

Maritime transportation is accountable for 2.7% of the worlds CO emissions and the liner shipping industry is committed to a slow steaming policy to provide low cost and environmentally conscious global transport of goods without compromising the level of service. The potential for making cost effective and energy efficient liner shipping networks using operations research is huge and neglected. The implementation of logistic planning tools based upon operations research has enhanced performance of both airlines, railways and general transportation companies, but within the field of liner shipping very little operations research has been done. We believe that access to domain knowledge and data is an entry barrier for researchers to approach the important liner shipping network design problem. This paper presents a thorough description of the liner shipping domain applied to network design along with a rich integer programming model based on the services, that constitute the fixed schedule of a liner shipping company. The model may be relaxed as well as decomposed. The design of a benchmark suite of data instances to reflect the business structure of a global liner shipping network is discussed. The paper is motivated by providing easy access to the domain and the data sources of liner shipping for operations researchers in general. A set of data instances with offset in real world data is presented and made available upon request. Future work is to provide computational results for the instances.
mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials.

mHealth programs offer potential for practical and cost-effective delivery of interventions capable of reaching many individuals.



To (1) compare the effectiveness of mHealth interventions to promote physical activity (PA) and reduce sedentary behavior (SB) in free-living young people and adults with a comparator exposed to usual care/minimal intervention; (2) determine whether, and to what extent, such interventions affect PA and SB levels and (3) use the taxonomy of behavior change techniques (BCTs) to describe intervention characteristics.



A systematic review and meta-analysis following PRISMA guidelines was undertaken to identify randomized controlled trials (RCTs) comparing mHealth interventions with usual or minimal care among individuals free from conditions that could limit PA. Total PA, moderate-to-vigorous intensity physical activity (MVPA), walking and SB outcomes were extracted. Intervention content was independently coded following the 93-item taxonomy of BCTs.



Twenty-one RCTs (1701 participants-700 with objectively measured PA) met eligibility criteria. SB decreased more following mHealth interventions than after usual care (standardised mean difference (SMD) -0.26, 95 % confidence interval (CI) -0.53 to -0.00). Summary effects across studies were small to moderate and non-significant for total PA (SMD 0.14, 95 % CI -0.12 to 0.41); MVPA (SMD 0.37, 95 % CI -0.03 to 0.77); and walking (SMD 0.14, 95 % CI -0.01 to 0.29). BCTs were employed more frequently in intervention (mean = 6.9, range 2 to 12) than in comparator conditions (mean = 3.1, range 0 to 10). Of all BCTs, only 31 were employed in intervention conditions.



Current mHealth interventions have small effects on PA/SB. Technological advancements will enable more comprehensive, interactive and responsive intervention delivery. Future mHealth PA studies should ensure that all the active ingredients of the intervention are reported in sufficient detail.
Gastric rupture with necrosis following acute gastric dilatation: report of a case

Gastric rupture with necrosis following acute gastric dilatation (AGD) is a rare and potentially fatal event; usually seen in patients with eating disorders such as anorexia nervosa or bulimia. A 12-year-old lean boy with no remarkable medical history was brought to our Emergency Department suffering acute abdominal symptoms. Emergency laparotomy revealed massive gastric dilatation and partial necrosis, with rupture of the anterior wall of the fundus of the stomach. We performed partial gastrectomy and the patient recovered uneventfully. We report this case to demonstrate that AGD and subsequent gastric rupture can occur in patients without any underlying disorders and that just a low body mass index is a risk factor for this potentially fatal condition.
Lateral Browlift Using Temporal (Pretrichial) Subcutaneous Approach Under Local Anesthesia

Lateral brow ptosis is a common aging phenomenon, contributing to the lateral upper eyelid hooding, in addition to dermatochalasis. Lateral brow lift complements upper blepharoplasty in achieving a youthful periorbital appearance. In this study, the author reports his experience in utilizing a temporal (pretrichial) subcutaneous lateral brow lift technique under local anesthesia. A retrospective analysis of all patients undergoing the proposed technique by one surgeon from 2009 to 2016 was conducted. Additional procedures were recorded. Preoperative and postoperative photographs at the longest follow-up visit were used for analysis. Operation was performed under local anesthesia. The surgical technique included a temporal (pretrichial) incision with subcutaneous dissection toward the lateral brow, with superolateral lift and closure. Total of 45 patients (44 females, 1 male; mean age: 58 years) underwent the temporal (pretrichial) subcutaneous lateral brow lift technique under local anesthesia in office setting. The procedure was unilateral in 4 cases. Additional procedures included upper blepharoplasty (38), ptosis surgery (16), and lower blepharoplasty (24). Average follow-up time was 1 year (range, 6 months to 5 years). All patients were satisfied with the eyebrow contour and scar appearance. One patient required additional brow lift on one side for asymmetry. There were no cases of frontal nerve paralysis. In conclusion, the temporal (pretrichial) subcutaneous approach is an effective, safe technique for lateral brow lift/contouring, which can be performed under local anesthesia. It is ideal for women. Additional advantages include ease of operation, cost, and shortening the hairline (if necessary).
Unemployment , Vacancies , Wages

1045 We have all visited several stores to check prices and/or to find the right item or the right size. Similarly, it can take time and effort for a worker to find a suitable job with suitable pay, and for employers to receive and evaluate applications for job openings. Search theory explores the workings of markets once facts such as these are incorporated into the analysis. Adequate analysis of market frictions needs to consider how reactions to frictions change the overall economic environment: not only do frictions change incentives for buyers and sellers, but the responses to the changed incentives also alter the economic environment for all the participants in the market. Because of these feedback effects, seemingly small frictions can have large effects on outcomes. Equilibrium search theory is the development of basic models to permit analysis of economic outcomes when specific frictions are incorporated into simpler market models. The primary friction addressed by search theory is the need to spend time and effort to learn about opportunities—opportunities to buy or to sell, to hire or to be hired. There are many aspects of a job and of a worker that matter when deciding whether a particular match is worthwhile. Such frictions are naturally analyzed in models that consider a process over time—of workers seeking jobs, firms seeking employees, borrowers seeking lenders, and shoppers buying items that are not part of frequent shopping. Search theory models have altered the way we think about markets, how we interpret market data, and how we think about government policies. The complexity of the economy calls for the use of multiple models that address different aspects of the determinants of unemployment (and other) outcomes. This view was captured so well by Alfred Marshall (1890: 1948 edition, p. 366) that I have quoted this passage repeatedly since coming upon it while doing research for the Churchill Lectures (Diamond 1994b).
Applying proxemics to mediate people's interaction with devices in ubiquitous computing ecologies

Through vastly increasing availability of digital devices in people’s everyday life, ubiquitous computing (ubicomp) ecologies are emerging. An important challenge here is the design of adequate techniques that facilitate people’s interaction with these ubicomp devices. In my research, I explore how the knowledge of people’s and devices’ spatial relationships – called proxemics – can be applied to interaction design. I introduce concepts of proxemic interactions that consider fine-grained information of proxemics to mediate people’s interactions with digital devices, such as large digital surfaces or portable personal devices. In particular, my work considers four dimensions that are essential to determine basic proxemic relationships of people and devices: position, orientation, movement, and identity. I outline my previous and current work towards a framework of proxemic interaction, the design of adequate development tools, and the implementation and evaluation of applications that illustrate concepts of proxemic interactions.  Input devices and strategies. General terms: Design, Human Factors
Predicting query execution time: Are optimizer cost models really unusable?

Predicting query execution time is useful in many database management issues including admission control, query scheduling, progress monitoring, and system sizing. Recently the research community has been exploring the use of statistical machine learning approaches to build predictive models for this task. An implicit assumption behind this work is that the cost models used by query optimizers are insufficient for query execution time prediction. In this paper we challenge this assumption and show while the simple approach of scaling the optimizer's estimated cost indeed fails, a properly calibrated optimizer cost model is surprisingly effective. However, even a well-tuned optimizer cost model will fail in the presence of errors in cardinality estimates. Accordingly we investigate the novel idea of spending extra resources to refine estimates for the query plan after it has been chosen by the optimizer but before execution. In our experiments we find that a well calibrated query optimizer model along with cardinality estimation refinement provides a low overhead way to provide estimates that are always competitive and often much better than the best reported numbers from the machine learning approaches.
Big Data, Social Media, and Protest: Foundations for a Research Agenda

Following the Arab Spring, a debate broke out among both academics and pundits as to how important social media had been in bringing about what may have been the least anticipated political development of the 21st century. Critics of the importance of social media pointed in particular to two factors: (a) the proportion of social media messages that were transmitted in English; and (b) the proportion of Arab Spring related social media posts that originated from outside the Arab world. In our chapter, we will test whether two important subsequent unanticipated protests Turkey’s 2013 Gezi Park protests and Ukraine’s 2013-14 Euromaidan protest also are susceptible to such criticisms. To do so, we draw on millions of tweets from both protests including millions of geolocated tweets from Turkey to test hypotheses related to the use of Twitter by protest participants and, more generally, in-country supporters of protest movements, effectively refuting the idea that emerged after the Arab Spring that Twitter use during protests only reflects international attention to an event. ∗The authors are all members of the New York University Social Media and Political Participation (SMaPP) laboratory. The writing of this article was supported by the INSPIRE program of the National Science Foundation (Award # SES-1248077) and Dean Thomas Carew and the Research Investment Fund (RIF) of New York University. 1 Online Appendix  Turkish Facebook Activity Over Time
Learning to Play Othello with N-Tuple Systems

This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then evaluated for use with temporal difference learning. Performance is compared with prev iously developed weighted piece counters and multi-layer perceptrons. The n-tuple system is able to defeat the best performing of these after just five hundred ga mes of selfplay learning. The conclusion is that n-tuple networks learn faster and better than the other more conventional approaches.
Targeting renal glucose reabsorption to treat hyperglycaemia: the pleiotropic effects of SGLT2 inhibition

Healthy kidneys filter ∼160 g/day of glucose (∼30% of daily energy intake) under euglycaemic conditions. To prevent valuable energy from being lost in the urine, the proximal tubule avidly reabsorbs filtered glucose up to a limit of ∼450 g/day. When blood glucose levels increase to the point that the filtered load exceeds this limit, the surplus is excreted in the urine. Thus, the kidney provides a safety valve that can prevent extreme hyperglycaemia as long as glomerular filtration is maintained. Most of the capacity for renal glucose reabsorption is provided by sodium glucose cotransporter (SGLT) 2 in the early proximal tubule. In the absence or with inhibition of SGLT2, the renal reabsorptive capacity for glucose declines to ∼80 g/day (the residual capacity of SGLT1), i.e. the safety valve opens at a lower threshold, which makes it relevant to glucose homeostasis from day-to-day. Several SGLT2 inhibitors are now approved glucose lowering agents for individuals with type 2 diabetes and preserved kidney function. By inducing glucosuria, these drugs improve glycaemic control in all stages of type 2 diabetes, while their risk of causing hypoglycaemia is low because they naturally stop working when the filtered glucose load falls below ∼80 g/day and they do not otherwise interfere with metabolic counterregulation. Through glucosuria, SGLT2 inhibitors reduce body weight and body fat, and shift substrate utilisation from carbohydrates to lipids and, possibly, ketone bodies. Because SGLT2 reabsorbs sodium along with glucose, SGLT2 blockers are natriuretic and antihypertensive. Also, because they work in the proximal tubule, SGLT2 inhibitors increase delivery of fluid and electrolytes to the macula densa, thereby activating tubuloglomerular feedback and increasing tubular back pressure. This mitigates glomerular hyperfiltration, reduces the kidney’s demand for oxygen and lessens albuminuria. For reasons that are less well understood, SGLT2 inhibitors are also uricosuric. These pleiotropic effects of SGLT2 inhibitors are likely to have contributed to the results of the EMPA-REG OUTCOME trial in which the SGLT2 inhibitor, empagliflozin, slowed the progression of chronic kidney disease and reduced major adverse cardiovascular events in high-risk individuals with type 2 diabetes. This review discusses the role of SGLT2 in the physiology and pathophysiology of renal glucose reabsorption and outlines the unexpected logic of inhibiting SGLT2 in the diabetic kidney.
Employer branding in IT/ITES units - an empirical study

Researchers believe that Employer branding may be the most powerful tool a business can use to emotionally engage employees, maintain and retain the talented. It is essential to accurately measure whether the organization's values, systems, policies and behaviors work towards the objectives of attracting, motivating and retaining current and potential employees. This paper envisages examining empirically the Employer brand status in the IT/ITES (Information Technology / Information Technology Enabled Services) units under study and determining, if any, the differences in the Employer brand and its components /elements among the IT students and IT professionals. This study is limited to analyzing the Employer brand in terms of the perceived Employer brand image and the Employer brand expectations in the selected units of the IT industry in India. The findings would help to picturize the Employer brand image and expectations and provide policy makers and HR consultants a starting point to look individually into the various labor segments and evaluate their Employer brands.
Social Media and Collective Intelligence—Ongoing and Future Research Streams

The tremendous growth in the use of Social Media has led to radical paradigm shifts in the ways we communicate, collaborate, consume, and create information. Our focus in this special issue is on the reciprocal interplay of Social Media and Collective Intelligence. We therefore discuss constituting attributes of Social Media and Collective Intelligence, and we structure the rapidly growing body of literature including adjacent research streams such as social network analysis, Web Science, and computational social science. We conclude by making propositions for future research where in particular the disciplines of artificial intelligence, computer science, and information systems can substantially contribute to the interdisciplinary academic discourse.
Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment

Multilingual knowledge graph (KG) embeddings provide latent semantic representations of entities and structured knowledge with cross-lingual inferences, which benefit various knowledge-driven cross-lingual NLP tasks. However, precisely learning such cross-lingual inferences is usually hindered by the low coverage of entity alignment in many KGs. Since many multilingual KGs also provide literal descriptions of entities, in this paper, we introduce an embedding-based approach which leverages a weakly aligned multilingual KG for semi-supervised cross-lingual learning using entity descriptions. Our approach performs co-training of two embedding models, i.e. a multilingual KG embedding model and a multilingual literal description embedding model. The models are trained on a large Wikipedia-based trilingual dataset where most entity alignment is unknown to training. Experimental results show that the performance of the proposed approach on the entity alignment task improves at each iteration of co-training, and eventually reaches a stage at which it significantly surpasses previous approaches. We also show that our approach has promising abilities for zero-shot entity alignment, and cross-lingual KG completion.
An unusual case of smothering secondary to ingesting raw pet cat.

Smothering is defined as an obstruction of the air passages above the level of the epiglottis, including the nose, mouth, and pharynx. This is in contrast to choking, which is considered to be due to an obstruction of the air passages below the epiglottis. The manner of death in smothering can be homicidal, suicidal, or an accident. Accidental smothering is considered to be a rare event among middle-aged adults, yet many cases still occur. Presented here is the case of a 39-year-old woman with a history of bipolar disease who was found dead on her living room floor by her neighbors. Her hands were covered in scratches and her pet cat was found disemboweled in the kitchen with its tail hacked off. On autopsy her stomach was found to be full of cat intestines, adipose tissue, and strips of fur-covered skin. An intact left kidney and adipose tissue were found lodged in her throat just above her epiglottis. After a complete investigation, the cause of death was determined to be asphyxia by smothering due to animal tissue.