nils-herrmann/clean_scirepeval huggingface dataset:
Evaluation of safety and efficacy of 980 nm diode laser assisted lipolysis versus traditional liposuction for submental rejuvenation: A randomized clinical trial
Venue: Journal of cosmetic and laser therapy official publication of the European Society for Laser Dermatology

Submental fat accumulation and skin laxity is a frequent concern of cosmetic patients.  The aim of this randomized prospective controlled clinical trial was to compare the efficacy and safety of laser assisted lipolysis and liposuction in the submental rejuvenation.  Thirty six female adults were enrolled in this clinical trial and were categorized into two groups: group 1 underwent 980 nm diode laser with the power of 6 8 W and group 2 underwent traditional liposuction. Patients were evaluated with ultrasonography 2 weeks and 2 months after the procedures.  Ultrasonographic evaluation reported the significant reduction of fat thickness in each group compared with the baseline (p value 0.001) At the 2 weeks and 2 months follow up visit, fat thickness reduction was significantly higher in the lipolysis group (p value 0.05) Overall patients' satisfaction in lipolysis group was higher than liposuction with 11 (61% of lipolysis patients being very satisfied in contrast to 10 (55.5% of liposuction patients reporting "dissatisfied or neutral" results.  Laser assisted lipolysis using 980 nm diode is approved to be safe and effective for skin tightening and rejuvenation of the submental area and seems to be a better option than traditional techniques for treatment of this cosmetic problem.
Cognitive Abilities, Monitoring Confidence, and Control Thresholds Explain Individual Differences in Heuristics and Biases
Venue: Front. Psychol.

In this paper, we investigate whether individual differences in performance on heuristic and biases tasks can be explained by cognitive abilities, monitoring confidence, and control thresholds. Current theories explain individual differences in these tasks by the ability to detect errors and override automatic but biased judgments, and deliberative cognitive abilities that help to construct the correct response. Here we retain cognitive abilities but disentangle error detection, proposing that lower monitoring confidence and higher control thresholds promote error checking. Participants (N 250) completed tasks assessing their fluid reasoning abilities, stable monitoring confidence levels, and the control threshold they impose on their decisions. They also completed seven typical heuristic and biases tasks such as the cognitive reflection test and Resistance to Framing. Using structural equation modeling, we found that individuals with higher reasoning abilities, lower monitoring confidence, and higher control threshold performed significantly and, at times, substantially better on the heuristic and biases tasks. Individuals with higher control thresholds also showed lower preferences for risky alternatives in a gambling task. Furthermore, residual correlations among the heuristic and biases tasks were reduced to null, indicating that cognitive abilities, monitoring confidence, and control thresholds accounted for their shared variance. Implications include the proposal that the capacity to detect errors does not differ between individuals. Rather, individuals might adopt varied strategies that promote error checking to different degrees, regardless of whether they have made a mistake or not. The results support growing evidence that decision making involves cognitive abilities that construct actions and monitoring and control processes that manage their initiation.
Decision pattern analysis as a general framework for studying individual differences in decision making

This paper investigated decision pattern analysis (DPA) as a general and standard framework for studying individuals' consistent decision making behavior within and between contexts. DPA classifies decisions on the basis of judgement accuracy and the goal orientation of the decided upon action. Over repeated decisions, patterns of individuals' decision behavior are described by five variables: competence, optimality, recklessness, hesitancy and decisiveness. A fictitious medical decision making test and three standard cognitive ability tests (extended with confidence ratings and a 'submit answer for marking' decision) were used to investigate the psychometric properties of these DPA variables. Internal consistency of the decision patterns ranged from good to excellent. Convergent validity was assessed via cognitive abilities, metacognitive confidence and a control criterion imposed on confidence that determines the decision to be made: the point of sufficient certainty. Personality variables were included to assess discriminant validity. As hypothesised, cognitive abilities showed positive correlations with competence and optimality. High confidence, low points of sufficient certainty and a greater discrepancy between them were associated with higher decisiveness and recklessness, and lower hesitancy. Personality measures showed mixed and generally weak correlations with the DPA variables. These convergent and discriminant results also held after controlling for all variables in regression. The results provide preliminary psychometric support for DPA as a general framework of behavioral decision making. DPA has the potential to be exploited in many contexts for uses that, to date, have been unachievable in a psychometrically valid manner.
Increasing physical activity among young children from disadvantaged communities: study protocol of a group randomised controlled effectiveness trial
Venue: BMC Public Health

BackgroundParticipation in regular physical activity (PA) during the early years helps children achieve healthy body weight and can substantially improve motor development, bone health, psychosocial health and cognitive development. Despite common assumptions that young children are naturally active, evidence shows that they are insufficiently active for health and developmental benefits. Exploring strategies to increase physical activity in young children is a public health and research priority.MethodsJump Start is a multi component, multi setting PA and gross motor skill intervention for young children aged 3 5 years in disadvantaged areas of New South Wales, Australia. The intervention will be evaluated using a two arm, parallel group, randomised cluster trial. The Jump Start protocol was based on Social Cognitive Theory and includes five components: a structured gross motor skill lesson (Jump In) unstructured outdoor PA and gross motor skill time (Jump Out) energy breaks (Jump Up) activities connecting movement to learning experiences (Jump Through) and a home based family component to promote PA and gross motor skill (Jump Home) Early childhood education and care centres will be demographically matched and randomised to Jump Start (intervention) or usual practice (comparison) group. The intervention group receive Jump Start professional development, program resources, monthly newsletters and ongoing intervention support. Outcomes include change in total PA (accelerometers) within centre hours, gross motor skill development (Test of Gross Motor Development 2) weight status (body mass index) bone strength (Sunlight MiniOmni Ultrasound Bone Sonometer) self regulation (Heads Toes Knees Shoulders, executive function tasks, and proxy report Temperament and Approaches to learning scales) and educator and parent self efficacy. Extensive quantitative and qualitative process evaluation and a cost effectiveness evaluation will be conducted.DiscussionThe Jump Start intervention is a unique program to address low levels of PA and gross motor skill proficiency, and support healthy lifestyle behaviours among young children in disadvantaged communities. If shown to be efficacious, the Jump Start approach can be expected to have implications for early childhood education and care policies and practices, and ultimately a positive effect on the health and development across the life course.Trial registrationAustralian and New Zealand Clinical Trials Registry No: ACTRN12614000597695, first received: June 5, 2014.
From smart to deep: Robust activity recognition on smartwatches using deep learning
Venue: 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)

The use of deep learning for the activity recognition performed by wearables, such as smartwatches, is an understudied problem. To advance current understanding in this area, we perform a smartwatch centric investigation of activity recognition under one of the most popular deep learning methods Restricted Boltzmann Machines (RBM) This study includes a variety of typical behavior and context recognition tasks related to smartwatches (such as transportation mode, physical activities and indoor/outdoor detection) to which RBMs have previously never been applied. Our findings indicate that even a relatively simple RBM based activity recognition pipeline is able to outperform a wide range of common modeling alternatives for all tested activity classes. However, usage of deep models is also often accompanied by resource consumption that is unacceptably high for constrained devices like watches. Therefore, we complement this result with a study of the overhead of specifically RBM based activity models on representative smartwatch hardware (the Snapdragon 400 SoC, present in many commercial smartwatches) These results show, contrary to expectation, RBM models for activity recognition have acceptable levels of resource use for smartwatch class hardware already on the market. Collectively, these two experimental results make a strong case for more widespread adoption of deep learning techniques within smartwatch designs moving forward.
Perceptions and Attitudes of Medical Sales Representatives (MSRs) and Prescribers Regarding Pharmaceutical Sales Promotion and Prescribing Practices in Pakistan

Pakistan is the 6 th most populous country in the world and has an enormous potential for an ever increasing drug market. The health care system is highly prone to unethical drug prescribing practices. In addition, there is a huge tendency of pharmaceutical firms to indulge in unethical drug promotional practices by means of inducements and other benefits through their medical sales representatives (MSRs) On the other hand, the prescribers are also reported to be demanding inducements from these companies in return to write higher number of prescription. This study investigated the ground realities of drug promotion and prescribing practices in Pakistan.  A cross sectional study was conducted for a period of 6 months in which 472 physicians and 609 medical sales representatives of Pakistan selected through prospective sampling were interviewed on a validated, structured questionnaire. The responses of the target groups were then analyzed for association between variables by Chi square test (p and cross tabulation through SPSS, version 20.  Majority of practitioners (83.2% expected both, good communication skills and knowledge from MSRs and at the same time nearly 53% of prescribers demanded CME and almost 36% demanded gifts, incentives and inducements from MSRs. Replying to same question, MSRs disagreed with prescribers and believed that ~70 of prescribers ask for inducements with a whopping ~64 among them demanding unethical inducements like excessive free samples, gifts, leisure trips and even cars. Majority of physicians have consensus that the multinational pharmaceutical firms (92 have defined promotional practices while the national pharmaceutical companies ~73 are mainly involved in unethical practices of drug marketing.  Majority of national pharmaceuticals as well as prescribers were involved in unethical drug promotion and prescribing respectively. There is a need of curbing the unethical drug promotion and prescribing and formidable policies governing this issue are required to be implemented by the concerned regulatory authorities to avoid unnecessary harm to the patient's life and pocket. Strength and weakness of study: The study explored the drug promotion and prescribing practices for the first time in a developing country however, due to sensitivity of the topic a number of respondents hesitated to participate.  Drug, Drug detailing, CME, Medical sales representative, Physicians, Pakistan.
The effects of lucky draw sales promotion on brand loyalty in mobile telecommunication industry

The purpose of this paper is to empirically examine the relationship between lucky draw sales promotion (LDSP) and the four phases of brand loyalty in the telecommunication industry.  A self administered structure questionnaire was used to collect primary data from conveniently sampled 338 lucky draw winners in the Ghanaian telecommunication industry. A response rate of 67.1 percent was obtained for data analysis using structural equation modeling approach.  It was found that LDSP positively relate to cognitive brand loyalty, and to behavioral brand loyalty through affective and conative brand loyalty. All hypothesized relationships among the sequential four stage loyalty were confirmed, except the direct relationship between LDSP and behavioral brand loyalty.  The findings are limited to lucky draw winners in the telecommunication industry.  Marketers can increase brand loyalty and profit more from their customers through targeted programs with hedonic benefits to build strong commitment level (conative brand loyalty) strong favoritism (affective brand loyalty) and strong beliefs about the superiority (cognitive brand loyalty) of a brand.  Theoretically, this study fills the void of empirical studies on non price sales promotion techniques of lucky draw and customer brand loyalty in the telecommunication sector in developing economy context, and contributes to the body of knowledge in the area of customer brand loyalty and LDSP.
Modeling of product sales promotion and price discounting strategy using fuzzy logic in a retail organization
Venue: Ind. Manag. Data Syst.

The purpose of this paper is to capture the dynamic variations in sales of a product based upon the dynamic estimation of the time series data and propose a model that imitates the price discounting and promotion strategy for a product category in a retail organization.,Time series data relating to sales has been used to model the sales estimates using moving average and proportional and derivative control; thereafter a sales forecast is generated to estimate the sales of a particular product category. This provides valuable inputs for taking lot sizing decisions regarding procurement of the products and selection of suppliers. A hybrid model has been proposed and explained with a hypothetical case, which considerably impacts the sales promotion and intelligent pricing decisions.,A conceptual framework is developed for modeling the dynamic price discounting strategy in retail using fuzzy logic. The model imitates sales promotion and price discounting strategy. This has helped minimize the inventory cost thereby keeping the profitability of the retail organization intact.,There is no appropriate empirical data to verify the models. In light of the research approach (modeling based upon historical time series data of a particular product category) that was undertaken, there is a possibility that the research results may be valid for the product category that was selected. Therefore, the researchers are advised to test the proposed propositions further for other product categories.,The study provides valuable insight on how to use the real time sales data for designing a dynamic automated model for product sales promotion and price discounting strategy using fuzzy logic for a retail organization.
Sales Promotion Effectiveness: The Impact of Culture on Demographic Level

Sales promotion is an essential tool which leads to real increase in sales and profit. According to previous studies, sales promotions are effective at a cross cultural level when they provide benefits that go hand in hand with those of the promoted product. However, there is no literature state about the different sales promotion consumer benefits influences on its effectiveness at the demographic level (urban verses rural) To address this concern, this paper seeks to explore the congruence framework by analyzing how culture at a demographic group level impacts sales promotion. The objective is to investigate whether cultural differences at this level will have an impact at the effectiveness of sales promotion. This conceptual paper sheds light on the influence of culture in demographic group level in determining the response of consumers to sales promotions. The findings will contribute to the understanding of products and promotion types in the Vietnam retailers. It will also allow manufacturing companies to focus better on their strategies for marketing their products towards the Vietnamese consumer.
Predicting online product sales via online reviews, sentiments, and promotion strategies

The purpose of this paper is to investigate if online reviews (e.g. valence and volume) online promotional strategies (e.g. free delivery and discounts) and sentiments from user reviews can help predict product sales.  The authors designed a big data architecture and deployed Node.js agents for scraping the Amazon.com pages using asynchronous input/output calls. The completed web crawling and scraping data sets were then preprocessed for sentimental and neural network analysis. The neural network was employed to examine which variables in the study are important predictors of product sales.  This study found that although online reviews, online promotional strategies and online sentiments can all predict product sales, some variables are more important predictors than others. The authors found that the interplay effects of these variables become more important variables than the individual variables themselves. For example, online volume interactions with
Approaching solutions or avoiding problems? The differential effects of approach and avoidance goals with solution focused and problem focused coaching questions

This study aimed to give insights into the dynamics underpinning different types of coaching questions by exploring the interactions between solution focused (SF) and problem focused (PF) coaching questions and approach/avoidance goals. Past research has found that SF coaching questions lead to more positive outcomes than PF questions. Another body of research has explored the differential effects of approach and avoidance goals. These two separate theoretical frameworks have significantly influenced the coaching practitioner literature, but no research has explored their conjoint effects. We combine these by randomly allocating 140 participants (university students) in a 2 x 2 (coaching question: SF vs. PF) (goal type: approach vs. avoidance) study. SF questions led to a greater increase in positive affect, self efficacy and goal progress and a greater decrease in negative affect than PF questions. Contrary to expectations, there were no differences between approach and avoidance goals on any outcomes. Findings provide further support for SF approaches and insight into the multifaceted nature of goal setting in coaching.
Sales Analysis of E Commerce Websites using Data Mining Techniques

the emerging global economy, E commerce is a strong catalyst for economic development. The rapid growth in usage of Internet and Web based applications is decreasing operational costs of large enterprises, extending trading opportunities and lowering the financial barriers for active ecommerce participation. Many companies are restructuring their business strategies to attain maximum value in terms of profits as well as customer's satisfaction. Business tycoons around the globe are realizing that e commerce is not just trading of products and information over Internet, rather it provides an opportunity to compete with other giants in the market. Data mining (DM) is used to attain knowledge from available information in order to help companies make weighted decisions. An organization needs to invest only on the group of products which are frequently purchased by its customers as well as price them appropriately in order to attain maximum customer satisfaction. The objective of this paper is to evaluate, propose and improve traditional pricing strategies by using web mining techniques to collect information from e commerce websites and apply data mining methods to induce and extract useful information out of it. The proposed strategy can be generated by optimizing decision trees in an iterative process and exploit information about historical buying behavior of a customer.  Commerce, Data Mining, ID3 Algorithm
Levels of Business to Business E Commerce Adoption and Competitive Advantage in Small and Medium Sized Enterprises: A Comparison Study Between Egypt and the United States

Business to business e commerce adoption has become increasingly important for small and medium sized enterprises, allowing them to gain and sustain competitive advantage. Business to business adopted at different levels based on different resource endowments leads to competitive advantage being gained and sustained in proportion to that level of adoption. This study uses structural equation modeling to investigate how levels of business to business e commerce adoption affects and contributes to gaining and sustaining competitive advantage in both U.S. and Egyptian manufacturing small and medium sized enterprises. The key finding is that small and medium sized enterprises can achieve growth in market share and sales that helps them to improve their position in the global market through higher levels of business to business e commerce adoption. Implications of the study, its limitations and directions for future research, are also discussed.
Design of a Novel Reversible ALU using an Enhanced Carry Look Ahead Adder

Reversible logic is gaining significant consideration as the potential logic design style for implementation in modern nanotechnology and quantum computing with minimal impact on physical entropy. Recent advances in reversible logic allow schemes for computer architectures using improved quantum computer algorithms. Significant contributions have been made in the literature towards the design of reversible logic gate structures and arithmetic units, however, there are not many efforts directed towards the design of reversible ALUs. In this work, a novel programmable reversible logic gate is presented and verified, and its implementation in the design of a reversible Arithmetic Logic Unit is demonstrated. Then, reversible implementations of ripple carry, carry select and Kogge Stone carry look ahead adders are analyzed and compared. Next, implementations of the Kogge Stone adder with sparsity 4, 8 and 16 were designed, verified and compared. The enhanced sparsity 4 Kogge Stone adder with ripple carry adders was selected as the best design, and its implemented in the design of a 32 bit arithmetic logic unit is demonstrated. Index Terms Arithmetic Logic Unit; Carry Look Ahead Adder; Carry Select Adder; Emerging Technologies; Low Power; Nanotechnology; Reversible Logic; Ripple Carry Adder;
Down the hole unbalance vibration exciter for seismic treatment of bottom hole zone
Venue: Journal of Mining Science

The down the hole unbalance vibration exciter with the pneumatic drive is designed to treat face zone in the seismic frequency range. The modular type source consists of a vibration generator with the automated stepped static moment variation, a hold down unit and an in built pneumatic percussive device to advance the facility in uncased holes. The article gives pilot test data on R&D model of the vibration exciter, and amplitude frequency characteristic and spectral content of the excited signal.