nils-herrmann/clean_scirepeval huggingface dataset:
Metamerism Appreciation of Jadeite Jade Green under the Standard Light Sources D65, A and CWF

We tested 288 pieces of the polished cabochon jadeite jade with high quality green and smooth surfaces using the colorimeter Color i5 based on the CIE 1976 L*a*b* uniform color space. The color changes after alternating three CIE standard light sources D65, A and CWF were compared, and the degree of metamerism was evaluated. The results show that the CIE standard light sources D65, A and CWF increase the chroma of green and turn bluish green into vivid green, which are similar or to nearly colorless and transparent glass like samples with fine textures. When the three light sources were individually alternated, the lightness of the jadeite jades showed little change, but the tone changed significantly. Metamerism occurred only in 3 pairs among the 16 samples that were selected by cluster analysis for quality, and the metamerism colors were highly consistent of L*D65(43.47, 46.75) C*D65(65.20, 68.80) and ho*D65(138.10, 140.23) We can conclude that the jadeite jade green gradually turns to blue when the color temperature of the light source increases. But when considering both the light sources and the samples, D65 is more suitable to be the light source of jadeite jade green when compared with the light sources CWF and A. Compared with the CIE standard green and high chroma green, high quality jadeite jade green has a slight yellow tone, low lightness and high chroma. The special metamerism index decreased to 1 when the light source alternated among D65, A and CWF. Therefore, the color of jadeite jade green might be slightly influenced by alternating of the light sources.
Feasibility of a Memory Clinic Based Physical Activity Prescription Program.
Venue: Journal of Alzheimer's disease JAD

Effective programs for promoting physical activity are needed for those with cognitive impairment.  To test the feasibility of mobile Health (mHealth) technology supported physical activity prescription from a tertiary care memory clinic.  This feasibility study was designed as a 16 week randomized, crossover trial of a physical activity prescription: 8 weeks of intervention, 8 weeks of baseline or maintenance phase data collection. We recruited 2 cohorts: 21 individuals with Alzheimer related cognitive impairment (mean age 72.3 (5.2) 9 females) and 9 individuals with normal cognition (mean age 69.6 (5.8) 8 females) We gave each cohort an mHealth accelerometer based physical activity prescription to double number of steps taken. Our primary outcomes were feasibility and safety. Our secondary outcomes were change in weekly steps taken, Dementia Quality of Life Scale, Self efficacy Scale, 6 minute Walk, and mini Physical Performance Test.  Set up and use of the device was not a barrier to participation. However, only 62% of participants with cognitive impairment completed the intervention. The cohort with cognitive impairment did not change their weekly step count above Week 1. All participants in the cohort with normal cognition were able to set up and use their device and increased their weekly step count above Week 1. There were no differences between Week 1 and Week 8 for any secondary measures in either cohort.  Setup and daily use of mHealth technology appears to be feasible for a person with cognitive impairment with the help of a partner, but increasing daily step counts over 8 weeks was not achieved. Future work needs to assess alternative activity prescription goals or additional support for patients and their partners.
Clinical Trials to Gain FDA Approval for Computerized Cognitive Training: What Is the Ideal Control Condition?
Venue: Front. Aging Neurosci.

The explosive growth of mobile technologies combined with the rapid rise of aging populations fearful of their risk for Alzheimer's disease has led to a number of marketed products aimed at enhancing cognitive health. However, an increasing number of product claims that are not substantiated has led regulatory agencies, such as the Federal Trade Commission (FTC) to issue warnings or penalties against some companies. Therefore, it is likely that a number of computerized cognitive training (CCT) companies will conduct clinical trials to prove their efficacy to gain Food and Drug Administration (FDA) clearance as a medical software/device. This raises a number of issues such as optimal trial design for establishing efficacy. The type of control condition is unique issue for CCT, given the variety of non specific known to produce beneficial effects on cognition that are difficult to isolate from the content of the program. These include participant expectancy, engagement, motivation, novelty, and therapist interaction. We herein discuss the types of non specific factors, desirable qualities of an active control condition, and the nuances that exist between previously used control conditions within the context of CCT for mild cognitive impairment.
MHealth for Alzheimer's Disease: Regulation, Consent, and Privacy Concerns

Mobile Health (mHealth) that is, the provision of health care or wellness services through smartphones or tablets, has the potential to improve the quality, access, and affordability of health care services, including mental health. In the last decades, multiple mHealth smartphone applications have been developed to treat and monitor the behavior of first stage Alzheimer's disease patients. Common applications consist of informational reminders (for example, the names of loved ones or medication schedules) and tracking services designed to minimize the risk of patients' wandering. These applications might delay patients' disease progression, improve their quality of life, and empower them as well as their caregivers. However, mHealth apps for Alzheimer's are both a source of opportunities and risks. This paper provides an overview of the promises made by this type of eHealth. Despite these promises, users and app developers currently have little clarity regarding the fragmented legislative and regulatory framework of mHealth. This paper analyzes the privacy and security challenges of mHealth and explains why these concerns are particularly exacerbated in the case of mHealth apps for Alzheimer's patients. Contrary to other users of health and well being apps, these patients often cannot provide their informed consent, may lose their devices easily, and might not always be aware that their location is being tracked and their data collected. Since existing legislation and regulation on medical devices is to a great extent inapplicable to mHealth apps, many of these risks and concerns remain unanswered at the time of the writing.
On the Development of a Robotic Hummingbird

This paper describes the design, development and flight testing of a 62 gram hummingbird inspired flapping wing micro air vehicle with hovering capability. There were several design challenges encountered and innovative techniques were implemented to overcome them. To achieve the required large flap stroke amplitudes necessary to generate lift for hover at moderate flap frequencies ~25Hz) a novel "5 bar" mechanical linkage system was developed which amplifies the output of a standard 4 bar crank rocker mechanism. Utilizing aeroelastic tailoring techniques, lightweight ~0.8 grams) flexible wings were designed which produce the required lift for hover and their performance was optimized for a specific operational frequency range. Insect based wing kinematic modulation mechanisms were developed for control and stabilization by varying two parameters: the tilt of the flapping planes relative to the vehicle, and the flapping amplitude, both of which alter the magnitude and direction of the lift vector of each wing to achieve motion or trim in a particular direction. These mechanisms are controlled via a kinematic autopilot, which senses the vehicle attitude and, using an on board closed loop proportionalderivative controller, transmits corrective signals to the modulation mechanism actuators which stabilize the vehicle. A systematic approach to tuning the vehicle trim and controller gain values has been implemented, leading to several stable controlled flight experiments. One such flight test lasted ~5.0 seconds in which the vehicle ascended and sustained an altitude of ~1 meter with minimal drift. The final vehicle weighs 62 grams and flaps at about 22Hz during hover.
Highly b Selective Cyclopolymerization of 1,6 Heptadiynes and Ring Closing Enyne Metathesis Reaction Using Grubbs Z Selective Catalyst: Unprecedented Regioselectivity for Ru Based Catalysts.
Venue: Journal of the American Chemical Society

It is well known that Ru based Grubbs catalysts undergo a highly selective a addition to alkynes to promote exo cyclization during ring closing enyne metathesis (RCEYM) or to produce conjugated polyenes containing five membered rings during the cyclopolymerization (CP) of 1,6 heptadiynes. There are a few reports of b selective addition to alkynes using Schrock catalysts based on Mo but none for readily accessible and easy to use Ru based catalysts. We report the first example of b selective addition to alkynes using Grubbs Z selective catalyst, which produces only endo products during the RCEYM reaction of terminal enynes and promotes the CP of 1,6 heptadiyne derivatives to give conjugated polyenes containing a six membered ring as a major repeat unit. This unique preference for b selectivity originated from the side bound approach of alkynes to the catalyst, where the steric hindrance between the chelating N heterocyclic carbene ligand of the catalyst and the alkynes disfavored a addition. To enhance the b selectivity for CP further, one could increase the size of the substrates on the monomers and lower the reaction temperature to obtain conjugated polyenes containing up to 95% six membered rings. Moreover, the physical properties of the resulting polymer were analyzed in detail and compared with those of the conjugated polyenes containing only five membered rings prepared from the same monomer but with a conventional Grubbs catalyst.
Automatic determination of EMG contaminated components and validation of independent component analysis using EEG during pharmacologic paralysis
Venue: Clinical Neurophysiology

Validate independent component analysis (ICA) for removal of EMG contamination from EEG, and demonstrate a heuristic, based on the gradient of EEG spectra (slope of graph of log EEG power vs log frequency, 7 70 Hz) from paralysed awake humans, to automatically identify and remove components that are predominantly EMG.  We studied the gradient of EMG free EEG spectra to quantitatively inform the choice of threshold. Then, pre existing EEG from 3 disparate experimental groups was examined before and after applying the heuristic to validate that the heuristic preserved neurogenic activity (Berger effect, auditory odd ball, visual and auditory steady state responses) RESULTS (1) ICA based EMG removal diminished EMG contamination up to approximately 50 Hz, (2) residual EMG contamination using automatic selection was similar to manual selection, and (3) task induced cortical activity remained, was enhanced, or was revealed using the ICA based methodology.  This study further validates ICA as a powerful technique for separating and removing myogenic signals from EEG. Automatic processing based on spectral gradients to exclude EMG containing components is a conceptually simple and valid technique.  This study strengthens ICA as a technique to remove EMG contamination from EEG whilst preserving neurogenic activity to 50 Hz.
DBPs in a chlorinated indoor swimming pool: occurrences and modeling

Swimming pool water contains higher chlorine residual and is maintained at a higher temperature than tap water. It constitutes environments with high levels of disinfection byproducts (DBPs) in water and air due to continuous disinfection and constant organic loading from the bathers. Exposure to DBPs is inevitable for any bather or trainer while such exposure can have cancer and non cancer risks to humans. In this study, DBPs in tap water (S1) and water and air from a chlorinated indoor swimming pool before (S2) and after swimming (S3) were measured. Trihalomethanes (THMs) in S2 and S3 were 3.0 6.8 and 4.0 10.3 times the THMs in S1, respectively; and haloacetic acids (HAAs) in S2 and S3 were 2.3 4.3 and 2.5 5.5 times the HAAs in S1, respectively. THMs in air before swimming (S2 A) and after swimming (S3 A) were 60.4 and 77.5 mg/m 3 respectively. Models were developed for predicting dissolved organic carbon, THMs and HAAs in swimming pool. The models showed good to excellent performance (R 2 0.70 0.87) The model validation studies showed moderate to good performance r 0.73 0.83) The models might be useful in predicting DBPs9 exposure in swimming pools.
Efficient discovery of longest lasting correlation in sequence databases
Venue: The VLDB Journal

The search for similar subsequences is a core module for various analytical tasks in sequence databases. Typically, the similarity computations require users to set a length. However, there is no robust means by which to define the proper length for different application needs. In this study, we examine a new query that is capable of returning the longest lasting highly correlated subsequences in a sequence database, which is particularly helpful to analyses without prior knowledge regarding the query length. A baseline, yet expensive, solution is to calculate the correlations for every possible subsequence length. To boost performance, we study a space constrained index that provides a tight correlation bound for subsequences of similar lengths and offset by intraobject and interobject grouping techniques. To the best of our knowledge, this is the first index to support a normalized distance metric of arbitrary length subsequences. In addition, we study the use of a smart cache for disk resident data (e.g. millions of sequence objects) and a graph processing unit based parallel processing technique for frequently updated data (e.g. nonindexable streaming sequences) to compute the longest lasting highly correlated subsequences. Extensive experimental evaluation on both real and synthetic sequence datasets verifies the efficiency and effectiveness of our proposed methods.
Applications of egg shell and egg shell membrane as adsorbents: A review

Worldwide consumption of hen eggs is quite high, which results into availability of large amount of discarded egg wastes, particularly egg shell (ES) and egg shell membrane (ESM) Disposal of ES and ESM is always a problem particularly to the authorities of food, bakery and poultry units. In recent years, attempts have been made to utilize ES and ESM for the production of biodiesel and collagen but results are not much economically viable. In the hunt of waste materials as potential scavenger of hazardous chemicals, ES and ESM have emerged as non toxic, versatile and efficient adsorbents. Last 10 years have witnessed a systematic growth in the use of ES and ESM as adsorbents for the removal of variety of organic as well as inorganic hazardous chemicals, particularly from wastewater. Literature survey reveals that ES and ESM in their natural as well as chemically modified forms have provided excellent results for the removal of various classes of dyes, oxalic acid, phenol, pesticides, humic acid, pharmaceutics, surfactants, PAHs, heavy precious and light metals, actinides, fluorides, etc. In recent years powdered ESM have been modified to nano particles and used as adsorbent in various interesting applications. Reports are also available on the use of nanostructured material CHAP, derived from ES, for the removal of cadmium and lead ions from waste water. Present review article is an attempt to summarize the research carried out on the above mentioned applications of ES and ESM. Overall 108 research articles have been included in this review, which describe a methodical growth in the subject matter.
Transgene Free Disease Specific iPSC Generation from Fibroblasts and Peripheral Blood Mononuclear Cells.
Venue: Methods in molecular biology

Induced pluripotent stem cells (iPSCs) offer great promise as tools for basic biomedical research, disease modeling, and drug screening. In this chapter, we describe the generation of patient specific, transgene free iPSCs from skin biopsies and peripheral blood mononuclear cells through electroporation of episomal vectors and growth under two different culture conditions. The resulting iPSC lines are characterized with respect to pluripotency marker expression through immunostaining, tested for transgene integration by PCR, and assayed for differentiation capacity via teratoma formation.
DeepNNNER: Applying BLSTM CNNs and Extended Lexicons to Named Entity Recognition in Tweets
Venue: NUT@COLING

In this paper, we describe the DeepNNNER entry to The 2nd Workshop on Noisy User generated Text (WNUT) Shared Task #2: Named Entity Recognition in Twitter. Our shared task submission adopts the bidirectional LSTM CNN model of Chiu and Nichols (2016) as it has been shown to perform well on both newswire and Web texts. It uses word embeddings trained on large scale Web text collections together with text normalization to cope with the diversity in Web texts, and lexicons for target named entity classes constructed from publicly available sources. Extended evaluation comparing the effectiveness of various word embeddings, text normalization, and lexicon settings shows that our system achieves a maximum F1 score of 47.24, performance surpassing that of the shared task's second ranked system.
Factors Affecting the Business Performance of the Micro Small and Medium Enterprises in Creative Economic Sector in Makassar Indonesia

This study aims at determining the effects of (i) the venture capital on growth strategies, (ii) the characteristics of entrepreneurs on business growth strategy, (iii) business growth strategy on business performance, and (iv) the competence of entrepreneurship on the performance of the business. The number of sample collected in this study using Slovin formula was 296. This sample was collected based on the business category of the creative economic sector. The results of this study showed that there was significant effect of the venture capital business growth strategy and business performance. Variables that were significantly affecting the entrepreneurial characteristics of business growth strategy, entrepreneurial competence and business performance. Competence entrepreneurship significant effect on business performance. Entrepreneurial characteristics Significantly influence business performance. However, growth strategies have no significant effect on business performance. Whilst venture capital has a significant influence on business performance through business growth strategy. Finally, entrepreneurial characteristics have significant influence on business performance through business growth strategy and entrepreneurial competence.
Effect of Core Competence on Sustainable Competitive Advantages of Batik Banyumas Small and Medium Enterprises

This study seeks to determine the relationship between firm core competence, competitive advantage and performance of small and medium enterprises based on analysis of data from a survey conducted on 58 owner and manager of small firms of Banyumas batik in Banyumas Region, Central Java, Indonesia. Data was analysed using multiple regression analysis. The results showed that competence in relationship, adaptation and innovation has significantly effect on firms innovativeness. The ability of entrepreneurs to build business network has eased information exchange leading to social relatedness, and thereby contributing to improve the competitive advantage. The results of the study provide new empirical evidence supporting the resources based view (RBV) theory.
Policy analytics and accountability mechanisms: judging the 'value for money' of policy implementation
Venue: Ann. Oper. Res.

Many applications of analytical methods in public policy relate to aspects of ex ante decision support, such as assisting policy makers assess projected costs and benefits of potential approaches to implementing policy objectives. This paper sets out some issues in a less widely discussed area of policy analytics, namely their application to holding government bodies to account, ex post, for the 'value for money' with which they have used public funds. It shows how the task of arriving at a judgment on value for money can be modelled as the construction of a partial order relation on an 'outcome space' of possible outcomes with 'value' and 'money' dimensions, and uses this framework to present case examples from the work of the UK National Audit Office. It shows how analytical methods are used to provide evidence to support such judgments. It concludes that there is scope for exploring the application of new techniques, such as big data analytics, to developing the 'observed' and 'possible' elements of value for money conclusions. There is also scope for applying decision analytic techniques, such as multi criteria decision analysis, to develop the 'value for money criteria' against which actual performance can be judged in fair, balanced, transparent, consistent, and technically rigorous manner.
Big Data Applied to Tax Evasion Detection: A Systematic Review
Venue: 2016 International Conference on Computational Science and Computational Intelligence (CSCI)

Tax evasion fraud is an issue faced by all governments in the world and one way to improve its detection is the application of big data technologies. This work performs a systematic literature review with the objective of identifying primary studies that address the fraud tax detection by the use of big data. This review resulted in the finding of 56 works of which 5 were identified as primary study. An overview of the results is presented categorized by the studies that address the problem by the use of pattern recognition methodologies, natural language processing and data analytics in auditing. The results also present algorithms and models used in each solution.
Burst photography for high dynamic range and low light imaging on mobile cameras
Venue: ACM Trans. Graph.

Cell phone cameras have small apertures, which limits the number of photons they can gather, leading to noisy images in low light. They also have small sensor pixels, which limits the number of electrons each pixel can store, leading to limited dynamic range. We describe a computational photography pipeline that captures, aligns, and merges a burst of frames to reduce noise and increase dynamic range. Our system has several key features that help make it robust and efficient. First, we do not use bracketed exposures. Instead, we capture frames of constant exposure, which makes alignment more robust, and we set this exposure low enough to avoid blowing out highlights. The resulting merged image has clean shadows and high bit depth, allowing us to apply standard HDR tone mapping methods. Second, we begin from Bayer raw frames rather than the demosaicked RGB (or YUV) frames produced by hardware Image Signal Processors (ISPs) common on mobile platforms. This gives us more bits per pixel and allows us to circumvent the ISP's unwanted tone mapping and spatial denoising. Third, we use a novel FFT based alignment algorithm and a hybrid 2D/3D Wiener filter to denoise and merge the frames in a burst. Our implementation is built atop Android's Camera2 API, which provides per frame camera control and access to raw imagery, and is written in the Halide domain specific language (DSL) It runs in 4 seconds on device (for a 12 Mpix image) requires no user intervention, and ships on several mass produced cell phones.