nils-herrmann/clean_scirepeval huggingface dataset:
KIKEN YOCHI TRAINING (KYT) IN REDUCING ACCIDENTS AT WORKPLACES: A SYSTEMATIC REVIEW

The aim of this paper is to systematically review the literature in order to explore the usage and efficiency of Kiken Yochi training (KYT) in reducing workplace accidents.  Literature was sought from online database. These database included PubMed, Science Direct, JICOSH, and Google Scholar. Only English full text articles published from 2000 to 2015 were selected. The main keywords used for the search were (Kiken Yochi) OR (hazard prediction) AND (work injury) OR (accident) AND (working site accident) In total, six studies met the inclusion criteria for this review.  Four studies were from Japan, one study was from Thailand, and one study was from the United States of America (USA) These selected studies used different study designs; cross sectional, cohort, experimental, quasi experimental and case study. Respondents involved were factory workers, laboratory workers, students and contractor workers. Implementation of KYT was found to be consistently effective in increasing workers' awareness on occupational hazards, promoting health and safety practice and reducing occupational accident rate. Involvement of all top managements and employees in decision making process is the key factor for the success of KYT implementation.  In summary, KYT is indeed a promising tool to be implemented in various industries to reduce hazard and accidents at the workplace.  Kiken yochi training, accident, workplace, hazards,
KIKEN YOCHI TRAINING (KYT) IN REDUCING ACCIDENTS AT WORKPLACES: A SYSTEMATIC REVIEW

The aim of this paper is to systematically review the literature in order to explore the usage and efficiency of Kiken Yochi training (KYT) in reducing workplace accidents.  Literature was sought from online database. These database included PubMed, Science Direct, JICOSH, and Google Scholar. Only English full text articles published from 2000 to 2015 were selected. The main keywords used for the search were (Kiken Yochi) OR (hazard prediction) AND (work injury) OR (accident) AND (working site accident) In total, six studies met the inclusion criteria for this review.  Four studies were from Japan, one study was from Thailand, and one study was from the United States of America (USA) These selected studies used different study designs; cross sectional, cohort, experimental, quasi experimental and case study. Respondents involved were factory workers, laboratory workers, students and contractor workers. Implementation of KYT was found to be consistently effective in increasing workers' awareness on occupational hazards, promoting health and safety practice and reducing occupational accident rate. Involvement of all top managements and employees in decisionmaking process is the key factor for the success of KYT implementation.  In summary, KYT is indeed a promising tool to be implemented in various industries to reduce hazard and accidents at the workplace.
Quantification of hazard prediction ability at hazard prediction training (Kiken Yochi Training: KYT) by free response receiver operating characteristic (FROC) analysis
Venue: Radiological Physics and Technology

The ability to predict hazards in possible situations in a general X ray examination room created for Kiken Yochi training (KYT) is quantified by use of free response receiver operating characteristics (FROC) analysis for determining whether the total number of years of clinical experience, involvement in general X ray examinations, occupation, and training each have an impact on the hazard prediction ability. Twenty three radiological technologists (RTs) (years of experience: 2 28) four nurses (years of experience: 15 19) and six RT students observed 53 scenes of KYT: 26 scenes with hazardous points (hazardous points are those that might cause injury to patients) and 27 scenes without points. Based on the results of these observations, we calculated the alternative free response receiver operating characteristic (AFROC) curve and the figure of merit (FOM) to quantify the hazard prediction ability. The results showed that the total number of years of clinical experience did not have any impact on hazard prediction ability, whereas recent experience with general X ray examinations greatly influenced this ability. In addition, the hazard prediction ability varied depending on the occupations of the observers while they were observing the same scenes in KYT. The hazard prediction ability of the radiologic technology students was improved after they had undergone patient safety training. This proposed method with FROC observer study enabled the quantification and evaluation of the hazard prediction capability, and the application of this approach to clinical practice may help to ensure the safety of examinations and treatment in the radiology department.
Low temperature plasma enhanced atomic layer deposition of tin oxide electron selective layers for highly efficient planar perovskite solar cells

Recent progress has shown that low temperature processed tin oxide (SnO2) is an excellent electron selective layer (ESL) material for fabricating highly efficient organic inorganic metal halide perovskite solar cells with a planar cell structure. Low temperature processing and a planar cell structure are desirable characteristics for large scale device manufacturing due to their associated low costs and processing simplicity. Here, we report that plasma enhanced atomic layer deposition (PEALD) is able to lower the deposition temperature of SnO2 ESLs to below 100 degC and still achieve high device performance. With C60 self assembled monolayer passivation, our PEALD SnO2 ESLs deposited at ~100 degC led to average power conversion efficiencies higher than 18% (maximum of 19.03% and 15% (maximum of 16.80% under reverse voltage scan for solar cells fabricated on glass and flexible polymer substrates, respectively. Our results thus demonstrate the potential of the low temperature PEALD process of SnO2 ESLs for large scale manufacturing of efficient perovskite solar cells.
Highly efficient and stable planar perovskite solar cells by solution processed tin oxide

Perovskite solar cells (PSCs) are one of the most promising lab scale technologies to deliver inexpensive solar electricity. Low temperature planar PSCs are particularly suited for large scale manufacturing. Here, we propose a simple, solution processed technological approach for depositing SnO2 layers. The use of these layers in planar PSCs yields a high stabilized power conversion efficiency close to 21% exhibiting stable performance under real operating conditions for over 60 hours. In addition, this method yielded remarkable voltages of 1214 mV at a band gap of 1.62 eV (approaching the thermodynamic limit of 1.32 V) confirming the high selectivity of the solution processed layers. PSCs aged under 1 sun illumination and maximum power point tracking showed a final PCE of 20.7% after ageing and dark storage, which is slightly higher than the original efficiency. This approach represents an advancement in the understanding of the role of electron selective layers on the efficiency and stability of PSCs. Therefore, the newly proposed approach constitutes a simple, scalable method paving the way for industrialization of perovskite solar cells.
Evaluation of the Ocular Tolerance of Three Tacrolimus Topical Pharmaceutical Preparations by Bovine Corneal Opacity and Permeability Test
Venue: Current eye research

Tacrolimus ocular preparations are commonly employed in autoimmune or inflammatory ocular disorders. However, currently there are not yet approved ocular formulations. Tacrolimus ocular side effects have been reported in clinical use, so the evaluation of different pharmaceutical preparations is mandatory. In this study, the local corneal tolerance and safety profile of three common tacrolimus 0.03% pharmaceutical preparations were evaluated.  Corneal irritation and permeability of tacrolimus preparations were evaluated with the bovine corneal opacity and permeability (BCOP) test. Complementary corneal hematoxylin/eosin and immunohistochemistry staining for tight junctions and adherent junctions E cadherin, VE cadherin and zonula occludens 1 were examined and scored to evaluate and to confirm corneal disruption and irritation scores obtained with the BCOP method.  Commercial brand ointment (Protopic(r) topical compounded eye ointment (pharmacy elaboration) and tacrolimus suspension eye drops (elaborated from parenteral prograf(r) were tested as potential ocular preparations to be used in clinics. Tacrolimus preparations hereby studied do not alter the opacity and permeability of the bovine cornea by more than three units, measured by the In Vitro Irritancy Score, neither affected the immunohistochemical parameters, composite score or transepithelial electrical resistance.  Tacrolimus preparations studied can be safely applied as a topical ocular treatment.
Pharmaceutical services cost analysis using time driven activity based costing: A contribution to improve community pharmacies' management.
Venue: Research in social administrative pharmacy RSAP

The current financial crisis is pressing health systems to reduce costs while looking to improve service standards. In this context, the necessity to optimize health care systems management has become an imperative. However, little research has been conducted on health care and pharmaceutical services cost management.  Pharmaceutical services optimization requires a comprehensive understanding of resources usage and its costs. This study explores the development of a time driven activity based costing (TDABC) model, with the objective of calculating the cost of pharmaceutical services to help inform policy making.  Pharmaceutical services supply patterns were studied in three pharmacies during a weekday through an observational study. Details of each activity's execution were recorded, including time spent per activity performed by pharmacists. Data on pharmacy costs was obtained through pharmacies' accounting records.  The calculated cost of a dispensing service in these pharmacies ranged from EUR3.16 to EUR4.29. The cost of a counseling service when no medicine was supplied ranged from EUR1.24 to EUR1.46. The cost of health screening services ranged from EUR2.86 to EUR4.55.  The presented TDABC model gives us new insights on management and costs of community pharmacies. This study shows the importance of cost analysis for health care services, specifically on pharmaceutical services, in order to better inform pharmacies' management and the elaboration of pharmaceutical policies.
Aplikasi Penentuan Tingkat Kesegaran Ikan Selar Berbasis Citra Digital Dengan Metode Kuadrat Terkecil

Ikan banyak mengandung nutrisi yang sangat bermanfaat bagi tubuh, namun seringkali ikan diperdagangkan dalam keadaan sudah mati juga dalam keadaan masih hidup. Untuk mengamati kesegaran ikan selar dilakukan dengan pengenalan perubahan warna yang tampak pada citra digital dengn menggunakan metode kuadrat terkecil. Tujuan dari penelitian ini adalah membangun sistem aplikasi pengelolahan citra untuk mendeteksi tingkat kesegaran ikan selar. Data yang gunakan adalah 10 sampel citra ikan selar yang di photo setiap 1 jam selama 15 jam dan diperoleh 150 data gambar kemudian diolah dan dilakukan analisis dengan metode kuadrat terkecil. Proses pertama diawali dengan pengolahan citra dengan melakukan pemtotongan cropping pada bagian tepi mata citra original kemudian dilanjutkan dengan penyamaan ukuran resize menjadi 1000 x 1000 pixel dan pergantian format citra menjadi png. setelah gambar sudah diolah kemudian dilakukan perhitungan nilai rata rata grayscale menggunakakn sistem aplikasi 'Rata_rataGambar' dan diperoleh persamaan yang disimpan sebagai data training pada sistem aplikasi. Setelah citra sudah diolah selanjutnya citra tersebut di input pada sistem maka citra akan dikonversi kedalam bentuk grayscale dan ditampilkan pada tempat yang telah ditentukan bersamaan dengan histogram rgb dan grayscale kemudian dilakukan perhitungan dengan metode kuadrat terkecil. Proses terakhir kita lakukan pencocokan citra uji dengan citra yang disimpan sebagai data training dan diperoleh kesimpulan apakah citra itu (sangat segar, segar cukup segar, tidak segar, atau sangat tidak segar persentase ketidaksegaran ikan selar, dan lama waktu ikan selar mati. Penelitian ini menggunakan 150 sampel citra ikan selar dari ikan masih sangat segar sampai ikan sangat tidak segar (busuk) hasilnya menunjukan 125 citra sesuai dan 25 tidak sesuai dengan persentase akurasi sistem sebesar 83.333 Kata kunci Mata Ikan Selar, Pengolahan Citra Digital, Metode Kuadrat Terkecil.
PERBANDINGAN METODE DETEKSI TEPI MENGGUNAKAN METODE CANNY, PREWITT DAN SOBEL PADA IMAGE IKAN

Pengolahan citra digital merupakan perbaikan kualitas gambar yang optimal untuk tujuan analisis sebuah citra dengan bantuan komputer. Tahapan awal untuk mendapatkan citra dengan proses akuisisi citra yang bertujuan menentukan data yang diperlukan dan memilih metode perekaman citra digital. Hasil akuisisi citra dapat dilakukan proses deteksi tepi Teknik deteksi tepi (Edge Detection) dalam pengolahan citra digital digunakan untuk menentukan lokasi di titik tepi obyek. Obyek yang digunakan pada penelitian ini menggunakan image ikan. Pada image ikan proses image filter menggunakan anisotropic diffusion dan median filter dengan mengatur iterasi dan konstanta sebagai flow constan. Hasil filter image ikan dilakukan proses deteksi tepi. Metode yang digunakan untuk pendeteksian tepi yaitu metode canny, prewitt dan sobel. Berdasarkan ketelitian content based image retrieval pada nilai distance query bahwa hasil deteksi tepi canny memperoleh deteksi tepi lebih baik 75.39% dibandingkan prewitt 76.09% dan sobel 74.67%
The credibility of CSR (corporate social responsibility) reports in Europe. Evidence from a quantitative content analysis in 11 countries

When it comes to corporate social responsibility (CSR) reports, skepticism and mistrust toward companies often prevail among both stakeholders and scholars. However, the overall content quality of CSR reports has only sparsely evoked researchers' attention. Therefore, this paper focuses on the credibility of CSR reports, based on both human and software enhanced quantitative content analysis of 237 CSR reports from 11 European countries. Credibility is conceptualized as a multilayered construct along CSR and communication theories, filling the theory void in the field. The influence of contextual (e.g. industry) format, and firm level (e.g. size) factors on reporting credibility is also investigated. The results show that European CSR reports do not score high on credibility, leaving much room for improvement. The study finds that it is standardization and content that matter most for reporting credibility; external influences are secondary, at best. To be considered credible, CSR reports must first be understandable to their readers; in addition, credibility involves truth, sincerity, and stakeholder specificity. Voluntary standardization affects CSR reporting credibility positively, whereas regulation does not yet have the same positive effect. Based on the empirical results of the content analysis, we present a new two phase model of reporting credibility. For practice, we suggest that companies focus on the contents of their reports to render them more credible. To raise credibility levels consistently, policy makers can create a level playing field in CSR reporting regulation, as already initiated by several countries.
Automated content analysis for construction safety: A natural language processing system to extract precursors and outcomes from unstructured injury reports

In the United States like in many other countries throughout the globe, construction workers are more likely to be injured on the job than workers in any other industry. This poor safety performance is responsible for huge human and financial losses and has motivated extensive research. Unfortunately, safety improvement in construction has decelerated in the last decade and traditional safety programs have reached saturation. Yet major construction companies and federal agencies possess a wealth of empirical knowledge in the form of huge databases of digital construction injury reports. This knowledge could be used to better understand, predict, and prevent the occurrence of construction accidents. Unfortunately, due to the lack of a clear methodology and the high costs of manual large scale content analysis, these valuable data have yet to be extracted and leveraged. Recently, researchers have proposed a framework allowing meaningful empirical data to be extracted from accident reports. However, the resource limitations inherent to manual content analysis still remain. The present study tested the proposition that manual content analysis of injury reports can be eliminated using natural language processing (NLP) This paper describes (1) the overall strategy and methodology used in developing the system, and specifically how key challenges with decoding unstructured reports were overcome; (2) how the system was built through an iterative process of coding and testing against manual content analysis results from a team of seven independent analysts; and (3) the implications and potential uses of the data extracted. The results indicate that the NLP system is capable of quickly and automatically scanning unstructured injury reports for 101 attributes and outcomes with over 95% accuracy. The main contribution of this research is to empower any organization to quickly obtain a large and highly reliable structured attribute and outcome data set from their databases of unstructured accident reports. Such structured data are a necessary prerequisite to the application of statistical modeling techniques, allowing the extraction of new safety knowledge and finally the amelioration of safety management.
Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis
Venue: J. Biomed. Semant.

BackgroundIn the United States, 795,000 people suffer strokes each year; 10 15 of these strokes can be attributed to stenosis caused by plaque in the carotid artery, a major stroke phenotype risk factor. Studies comparing treatments for the management of asymptomatic carotid stenosis are challenging for at least two reasons: 1) administrative billing codes (i.e. Current Procedural Terminology (CPT) codes) that identify carotid images do not denote which neurovascular arteries are affected and 2) the majority of the image reports are negative for carotid stenosis. Studies that rely on manual chart abstraction can be labor intensive, expensive, and time consuming. Natural Language Processing (NLP) can expedite the process of manual chart abstraction by automatically filtering reports with no/insignificant carotid stenosis findings and flagging reports with significant carotid stenosis findings; thus, potentially reducing effort, costs, and time.MethodsIn this pilot study, we conducted an information content analysis of carotid stenosis mentions in terms of their report location (Sections) report formats (structures) and linguistic descriptions (expressions) from Veteran Health Administration free text reports. We assessed an NLP algorithm, pyConText's, ability to discern reports with significant carotid stenosis findings from reports with no/insignificant carotid stenosis findings given these three document composition factors for two report types: radiology (RAD) and text integration utility (TIU) notes.ResultsWe observed that most carotid mentions are recorded in prose using categorical expressions, within the Findings and Impression sections for RAD reports and within neither of these designated sections for TIU notes. For RAD reports, pyConText performed with high sensitivity (88 specificity (84 and negative predictive value (95 and reasonable positive predictive value (70 For TIU notes, pyConText performed with high specificity (87 and negative predictive value (92 reasonable sensitivity (73 and moderate positive predictive value (58 pyConText performed with the highest sensitivity processing the full report rather than the Findings or Impressions independently.ConclusionWe conclude that pyConText can reduce chart review efforts by filtering reports with no/insignificant carotid stenosis findings and flagging reports with significant carotid stenosis findings from the Veteran Health Administration electronic health record, and hence has utility for expediting a comparative effectiveness study of treatment strategies for stroke prevention.
SAR Image Segmentation Based on Hierarchical Visual Semantic and Adaptive Neighborhood Multinomial Latent Model
Venue: IEEE Transactions on Geoscience and Remote Sensing

A synthetic aperture radar (SAR) imaging system usually produces pairs of bright area and dark area when depicting the ground objects, such as a building or tree and its shadow. Many buildings (trees) are aggregated together to form urban areas (forests) It means that the pairs of bright and dark areas often exist in the aggregated scenes. Conventional unsupervised segmentation approaches usually segment the scenes (e.g. urban areas and forests) into different regions simply according to the gray values of the image. However, a more convincing way is to regard them as the consistent regions. In this paper, we aim at addressing this issue and propose a new SAR image segmentation approach via a hierarchical visual semantic and adaptive neighborhood multinomial latent model. In this approach, the hierarchical visual semantic of SAR images is proposed, which divides SAR images into aggregated, structural, and homogeneous regions. Based on the division, different segmentation methods are chosen for these regions with different characteristics. For the aggregated region, locality constrained linear coding based hierarchical clustering is used for segmentation. For the structural region, visual semantic rules are designed for line object location, and a geometric structure window based multinomial latent model is proposed for segmentation. For the homogeneous region, a multinomial latent model with adaptive window selection is proposed for segmentation. Finally, these results are integrated together to obtain the final segmentation. Experiments on both synthetic and real SAR images indicate that the proposed method achieves promising performances in terms of the consistencies of the regions and the preservations of the edges and line objects.
The suffix priming effect: Further evidence for an early morpho orthographic segmentation process independent of its semantic content
Venue: Quarterly journal of experimental psychology

This work presents the results of a masked lexical decision experiment in which we explore the morphological parsing of Spanish suffixed or pseudosuffixed words through the suffix priming effect. Priming the bases or pseudobases with their suffixed or pseudosuffixed forms is the standard process in experiments aimed at understanding the processes underlying morphological parsing in visual word recognition with masked priming lexical decision (e.g. darkness DARK; corner CORN) We, however, compare the effect of suffix priming on the lexical decision of suffixed (ero JORNALERO) and pseudosuffixed words (ero CORDERO) as well as the effect of orthographic priming on nonsuffixed words (eba PRUEBA) The results show that in the case of suffixed and pseudosuffixed words, related primes (ero JORNALERO; ero CORDERO) significantly accelerated response latencies in comparison to unrelated primes (ista JORNALERO; ura CORDERO) while for simple words there was no facilitation from the orthographically related prime in comparison to the unrelated prime (eba PRUEBA; afo PRUEBA) These results are consistent with the so called morpho orthographic segmentation process in the course of visual word recognition, which might also be independent of orthographic and purely semantic factors. Our results also support the view that morphological parsing takes place regardless of whether a stem is present in a word. These results complement findings from studies dealing with CORNER and BROTHEL like stimuli.