nils-herrmann/clean_scirepeval huggingface dataset:
Clinical evaluation of a toothpaste containing lysozyme for the treatment of recurrent aphthous stomatitis: A 3 month, double blind, randomized study.
Venue: American journal of dentistry

To assess the efficacy and safety of a toothpaste containing lysozyme for the treatment of minor recurrent aphthous stomatitis (MiRAS) in a 3 month clinical trial.  71 participants with MiRAS were recruited to this randomized, parallel controlled, double blind clinical trial. Participants were allocated randomly to the test group or the control group. Demographic data and pain score (visual analogue scale, VAS) were recorded at baseline. Healing time of MiRAS, recurrence frequency and side effects were recorded at the 1 2 and 3 month follow up visits. All data were analyzed using SAS software version 8.0.  There was no significant difference (P>0.05) in pain score between the treatment group (3.00 1.66) and the control group (2.66 1.51) The average healing time was significantly reduced (P< 0.01) in the treatment group (5.66 2.02) compared with the control group (7.46 2.69) while the recurrence frequency also showed a significant reduction from 4.40 2.89 in the control group to 3.06 1.48 in the treatment group (P< 0.05) No obvious side effects were observed.  The results of this clinical study supported the conclusion that a toothpaste containing lysozyme was effective in promoting healing and reducing recurrence frequency without significant side effects in the treatment of minor recurrent aphthous stomatitis.
Growing up Too Fast: Rural Children Working in Addis Ababa

The study explores the life situation of children who come from rural areas to work in Addis Ababa. It discusses their migration, work, relationships, and their economic contributions using data from 30 children. Findings indicate that poverty is a major push factor for migration, while a strong network of relatives living in Addis Ababa is a pull factor. In Addis Ababa, the children live in a challenging environment, drawing on their personal and social resources to persevere in the face of difficulties. Though they work hard and sometimes manage without basic necessities, they appreciate the opportunities available to help families, and for most to go to school, which reflects agency in action. Interventions need to consider not only vulnerability, but also the agency and resilience of children and the factors behind these.
Treatment of Electroplating Cr(VI) for Reduction Cr(VI) by Electrocoagulation in Continuous Operation

The performance of electrocoagulation, with aluminium sacrificial anode, in the treatment of metal ion Cr(VI) containing wastewater, has been investigated. Several working parameters, such as pH, current density and metal ion concentrations were studied in an attempt to achieve a higher removal capacity. Results obtained with synthetic wastewater revealed that the most effective removal capacities of studied metal could be achieved when the pH was kept between 4 and 8. In addition, the increase of current density, in the range 0.8 4.8Adm 2 enhanced the treatment rate without affecting the charge loading, required to reduce metal ion concentrations under the admissible legal levels. The process was successfully applied to the treatment of an electroplating wastewater where an effective reduction of Cr(VI) concentrations under legal limits was obtained, just after 20 min. The electrode and electricity consumptions were found to be 1 g l 1 and 32 A h l 1 respectively. The method was found to be highly efficient and relatively fast compared to conventional existing techniques
Mining complex hyperspectral ALMA cubes for structure with neural machine learning
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

Astronomy is producing the largest "Big Data" sets today and in the near future, with instruments such as the Atacama Large Millimeter and sub millimeter Array (ALMA) the Large Synoptic Survey Telescope (LSST) and the Square Kilometer Array (SKA) These observations afford a deeper, wider, and more dynamic glimpse into the structure and composition of the universe than ever before. However, in addition to unprecedented volume, the data also exhibit unprecedented complexity, mandating new approaches for extracting and summarizing relevant information. ALMA data, in particular, challenges with very high dimensionality (measurements in a large number of spectral channels) where the dimensions represent both compositional information and velocities, and the high spectral resolution allows detailed interpretation of the kinematic structure of sources such as molecular clouds or protoplanetary disks. Traditional tools like moment maps can no longer fully exploit and visualize the rich information in these data. We present a neural map based clustering approach that can utilize all spectral channels simultaneously and is capable of finding clusters of widely varying statistical properties, which are expected in these complex data sets. Many clustering methods, including modern graph segmentation algorithms, run into limitations when encountering such data. We demonstrate our tools, collectively named "NeuroScope" through structure mining from an ALMA image of the protoplanetary disk HD142527. We highlight the advantages for both the emerging details and visualization. In addition, we explore an augmentation of leading graph segmentation algorithms with NeuroScope products, which can lead to efficient full automation of our clustering process for fast distillation of large data sets on board or in archives.
Optimization and Design for Automation of Brachytherapy Delivery and Learning Robot Assisted Surgical Sub Tasks

Author(s) Garg, Animesh Advisor(s) Goldberg, Ken; Atamturk,  The goal of this dissertation is to enhance automation in healthcare applications, specifically: brachytherapy delivery for cancer treatment and robot assisted surgery, used for over 500,000 procedures annually in US alone. Brachytherapy uses cutting edge computer assisted planning, but assumes a fixed hardware design. On the contrary, Robot Assisted Surgery uses high precision state of the art hardware under complete manual control with little automation. This dissertation is a step towards addressing this gap using a combination of optimization and design. Case studies show that performance of autonomous systems can be improved by leveraging the interaction between optimization based algorithms and the design of hardware systems.For Brachytherapy, this dissertation has developed a new approach for treatment delivery in Intracavitary Brachytherapy using patient specific 3D printed implants and implemented it on a clinical case of oral cancer. I present an algorithm to quantify reachability with straight line needles for a given anatomy in prostate cancer. I integrate optimization based needle and dose planning algorithms in interstitial brachytherapy for prostate cancer using two methods of skew line needle configuration implants: robot assisted procedures and customized needle guides. The procedures are demonstrated on physical phantoms and performance is compared with an expert physician.For Robot Assisted Surgery, this dissertation highlights the interplay between the design ofhardware to reduce uncertainty and optimization based motion planning to enable automated multi throw suturing A novel algorithm, Transition State Clustering (TSC) extracts the latent task structure from task demonstrations by segmenting robot trajectories using hierarchical clustering and fitting Gaussian mixture model to identify transitions. I extend TSC with deep learning to perform trajectory segmentation for multi modal data consisting of kinematics and videos.
An eMERGE Clinical Center at Partners Personalized Medicine
Venue: Journal of personalized medicine

The integration of electronic medical records (EMRs) and genomic research has become a major component of efforts to advance personalized and precision medicine. The Electronic Medical Records and Genomics (eMERGE) network, initiated in 2007, is an NIH funded consortium devoted to genomic discovery and implementation research by leveraging biorepositories linked to EMRs. In its most recent phase, eMERGE III, the network is focused on facilitating implementation of genomic medicine by detecting and disclosing rare pathogenic variants in clinically relevant genes. Partners Personalized Medicine (PPM) is a center dedicated to translating personalized medicine into clinical practice within Partners HealthCare. One component of the PPM is the Partners Healthcare Biobank, a biorepository comprising broadly consented DNA samples linked to the Partners longitudinal EMR. In 2015, PPM joined the eMERGE Phase III network. Here we describe the elements of the eMERGE clinical center at PPM, including plans for genomic discovery using EMR phenotypes, evaluation of rare variant penetrance and pleiotropy, and a novel randomized trial of the impact of returning genetic results to patients and clinicians.
Prenatal Caffeine Exposure and Child IQ at Age 5.5 Years: The EDEN Mother Child Cohort
Venue: Biological Psychiatry

Evidence from animal studies suggests maternal caffeine intake during pregnancy has detrimental effects on subsequent brain development in offspring. However, human data in this area are limited. The aim of this study was to assess whether caffeine intake by women during pregnancy is associated with impaired cognitive development in offspring at age 5.5 years.  Multivariate modeling was conducted using data of 1083 mother child pairs from a population based birth cohort in France followed from pregnancy to age 5.5 years of the children. Measures included an estimate of maternal caffeine intake during pregnancy, children's IQ at age 5.5, and individual and family characteristics.  Prenatal caffeine exposure was common in the sample (91% with 12% displaying an intake =200 mg/day (high) Multivariable modeling showed a significant negative relationship between caffeine intake and children's IQ at 5.5 years .94 [95% confidence interval 1.70, .17] full IQ unit per 100 mg daily caffeine intake) In particular, children of mothers consuming =200 mg/day were more likely to have borderline or lower IQ compared with children of mothers consuming <100 mg/day (13.5% vs. 7.3% odds ratio 2.30, 95% confidence interval 1.13, 4.69) CONCLUSIONS We found an association between caffeine intake during pregnancy and impaired cognitive development in offspring, a result in line with animal data. More epidemiologic and biologically grounded research is needed to determine whether this association is causal. This finding suggests that conservative guidelines regarding the maximum caffeine intake recommended in pregnancy (i.e. 200 mg/day) should be maintained.
Postoperative pain control after arthroscopic rotator cuff repair.
Venue: Journal of shoulder and elbow surgery

Arthroscopic rotator cuff repair (ARCR) can provide excellent clinical results for patients who fail to respond to conservative management of symptomatic rotator cuff tears. ARCR, however, can be associated with severe postoperative pain and discomfort that requires adequate analgesia. As ARCR continues to shift toward being performed as an outpatient procedure, it is incumbent on physicians and ambulatory surgical centers to provide appropriate pain relief with minimal side effects to ensure rapid recovery and safe discharge. Although intravenous and oral opioids are the cornerstone of pain management after orthopedic procedures, they are associated with drowsiness, nausea, vomiting, and increased length of hospital stay. As health care reimbursements continue to become more intimately focused on quality, patient satisfaction, and minimizing of complications, the need for adequate pain control with minimal complications will continue to be a principal focus for providers and institutions alike. We present a review of alternative modalities for pain relief after ARCR, including cryotherapy, intralesional anesthesia, nerve blockade, indwelling continuous nerve block catheters, and multimodal anesthesia. In choosing among these modalities, physicians should consider patient and system based factors to allow the efficient delivery of analgesia that optimizes recovery and improves patient satisfaction.
Multi objective assisted inversion of chemical EOR corefloods for improving the predictive capacity of numerical models

Reservoir modeling is a powerful tool to thoroughly assess chemical EOR performances and to design the economically optimal injection sequence (chemicals concentration, slugs size) However, while building a model requires a large amount of data, laboratory experiments allow assessing a non exhaustive number of parameters only. Some essential data besides remain costly or time consuming to acquire. The calibration process is thus not straightforward and typically results in under constrained models that may not provide meaningful results. To increase the model robustness, we propose to carry out a multiobjective assisted calibration, further tested on an additional differentiating experiment. The multi objective aspect refers to the calibration of various production data acquired from a consistent series of recovery experiments. The methodology is applied to five surfactantpolymer displacements performed on sandstone cores, differing from the surfactant slug concentration, its size and the brine salinity. The experiments set is chosen to provide a wide range of tertiary recoveries, from 52% to 86% of residual oil in place. The oil recovery and the differential pressure are history matched with a limited number of adjustable parameters among which the surfactant adsorption, the wateroil interfacial tension and the extrapolation of Corey exponents along flooding history. The sensitivity to adjustable parameters is thoroughly explored by more than 1000 simulations to finally get a model that successfully reproduces the main features of the experiments. Calibration on a few experiments then gives more confidence in the model than when done on a single experiment. Its ability to reproduce the processes occurring in the core and to further predict the optimal chemical injection sequence is reinforced by the additional differentiating experiment which segregates different consistent models. This additional experiment specifically better constrains the surfactant adsorption.
Myocardial Fibrosis in Athletes.
Venue: Mayo Clinic proceedings

Myocardial fibrosis (MF) is a common phenomenon in the late stages of diverse cardiac diseases and is a predictive factor for sudden cardiac death. Myocardial fibrosis detected by magnetic resonance imaging has also been reported in athletes. Regular exercise improves cardiovascular health, but there may be a limit of benefit in the exercise dose response relationship. Intense exercise training could induce pathologic cardiac remodeling, ultimately leading to MF, but the clinical implications of MF in athletes are unknown. For this comprehensive review, we performed a systematic search of the PubMed and MEDLINE databases up to June 2016.  Headings terms and keywords pertaining to MF and exercise (training) were included. Articles were included if they represented primary MF data in athletes. We identified 65 athletes with MF from 19 case studies/series and 14 athletic population studies. Myocardial fibrosis in athletes was predominantly identified in the intraventricular septum and where the right ventricle joins the septum. Although the underlying mechanisms are unknown, we summarize the evidence for genetic predisposition, silent myocarditis, pulmonary artery pressure overload, and prolonged exercise induced repetitive micro injury as contributors to the development of MF in athletes. We also discuss the clinical implications and potential treatment strategies of MF in athletes.
The training injury prevention paradox: should athletes be training smarter and harder?
Venue: British Journal of Sports Medicine

There is dogma that higher training load causes higher injury rates. However, there is also evidence that training has a protective effect against injury. For example, team sport athletes who performed more than 18 weeks of training before sustaining their initial injuries were at reduced risk of sustaining a subsequent injury, while high chronic workloads have been shown to decrease the risk of injury. Second, across a wide range of sports, well developed physical qualities are associated with a reduced risk of injury. Clearly, for athletes to develop the physical capacities required to provide a protective effect against injury, they must be prepared to train hard. Finally, there is also evidence that under training may increase injury risk. Collectively, these results emphasise that reductions in workloads may not always be the best approach to protect against injury.  This paper describes the 'Training Injury Prevention Paradox' model; a phenomenon whereby athletes accustomed to high training loads have fewer injuries than athletes training at lower workloads. The Model is based on evidence that non contact injuries are not caused by training per se, but more likely by an inappropriate training programme. Excessive and rapid increases in training loads are likely responsible for a large proportion of non contact, soft tissue injuries. If training load is an important determinant of injury, it must be accurately measured up to twice daily and over periods of weeks and months (a season) This paper outlines ways of monitoring training load 'internal' and 'external' loads) and suggests capturing both recent 'acute' training loads and more medium term 'chronic' training loads to best capture the player's training burden. I describe the critical variable acute:chronic workload ratio as a best practice predictor of training related injuries. This provides the foundation for interventions to reduce players risk, and thus, time loss injuries.  The appropriately graded prescription of high training loads should improve players' fitness, which in turn may protect against injury, ultimately leading to (1) greater physical outputs and resilience in competition, and (2) a greater proportion of the squad available for selection each week.
The Mental Health of Elite Athletes: A Narrative Systematic Review
Venue: Sports Medicine

BackgroundThe physical impacts of elite sport participation have been well documented; however, there is comparatively less research on the mental health and psychological wellbeing of elite athletes.ObjectiveThis review appraises the evidence base regarding the mental health and wellbeing of elite level athletes, including the incidence and/or nature of mental ill health and substance use.MethodsA systematic search of the PubMed, EMBASE, SPORTDiscus, PsycINFO, Cochrane and Google Scholar databases, up to and including May 2015, was conducted.ResultsThe search yielded a total of 2279 records. Following double screening, 60 studies were included. The findings suggested that elite athletes experience a broadly comparable risk of high prevalence mental disorders (i.e. anxiety, depression) relative to the general population. Evidence regarding other mental health domains (i.e. eating disorders, substance use, stress and coping) is less consistent. These results are prefaced, however, by the outcome of the quality assessment of the included studies, which demonstrated that relatively few studies (25 were well reported or methodologically rigorous. Furthermore, there is a lack of intervention based research on this topic.ConclusionThe evidence base regarding the mental health and wellbeing of elite athletes is limited by a paucity of high quality, systematic studies. Nonetheless, the research demonstrates that this population is vulnerable to a range of mental health problems (including substance misuse) which may be related to both sporting factors (e.g. injury, overtraining and burnout) and non sporting factors. More high quality epidemiological and intervention studies are needed to inform optimal strategies to identify and respond to player mental health needs.
Safety Training, Company Policy and Communication for Effective Accident Management

The construction industry in Malaysia is currently characterised by an accident prone culture on construction sites. There have been several fatal incidents, incidents causing physical disability and near miss incidents. With effective accident management, it is expected that accidents could be reduced and existing knowledge and awareness of safety and health could be improved. The objective of this study is to determine the relationship between safety training, company policy and communication in the context of effective accident management. The research design of this study is descriptive and cross sectional. Quantitative research method using questionnaire survey is utilised to collect data at a selected Mass Rapid Transit project in the Klang Valley. The respondents consists of the main contractor, client and consultants employee. A total of 150 questionnaires were distributed to the respondents in which simple random sampling was performed in selecting the respondents for this study. Out of the total questionnaires distributed, only 136 (90.6% valid and usable questionnaires were returned. Descriptive and Pearson Correlation analyses were used to analyse the data collected from respondents. The results revealed a significant strong positive relationship between safety training, company policy, communication with effective accident management. These findings indicate that effective accident management is not likely to succeed without full commitment from both employees and their organization.
Algae as nutritional and functional food sources: revisiting our understanding
Venue: Journal of Applied Phycology

Global demand for macroalgal and microalgal foods is growing, and algae are increasingly being consumed for functional benefits beyond the traditional considerations of nutrition and health. There is substantial evidence for the health benefits of algal derived food products, but there remain considerable challenges in quantifying these benefits, as well as possible adverse effects. First, there is a limited understanding of nutritional composition across algal species, geographical regions, and seasons, all of which can substantially affect their dietary value. The second issue is quantifying which fractions of algal foods are bioavailable to humans, and which factors influence how food constituents are released, ranging from food preparation through genetic differentiation in the gut microbiome. Third is understanding how algal nutritional and functional constituents interact in human metabolism. Superimposed considerations are the effects of harvesting, storage, and food processing techniques that can dramatically influence the potential nutritive value of algal derived foods. We highlight this rapidly advancing area of algal science with a particular focus on the key research required to assess better the health benefits of an alga or algal product. There are rich opportunities for phycologists in this emerging field, requiring exciting new experimental and collaborative approaches.