Miracle-dz/UniFAR-FTUs huggingface dataset:
How Does Information and Communication Technology Capital Affect Productivity in the Energy Sector? New Evidence from 14 Countries, Considering the Transition to Renewable Energy Systems

By focusing on a distributed energy system that has been widely diffused for efficient utilization of renewable energy generation in recent years, this paper investigates the relationship between productivity growth and information and communications technology capital in the energy sector. Information and communications technology is a key factor in operating distributed energy systems in a way that balances energy supply and demand in order to minimize energy loss and to enhance capacity utilization. The objective of this study is to clarify the determining factors that affect productivity growth, focusing on three different information and communications technologies: information technology capital, communication technology capital and software capital. Our estimation sample covers energy sectors in 14 countries from 2000 to 2014. The results show that information technology and software capital contribute to increasing material productivity and capital productivity in the energy sector, respectively. Meanwhile, communication technology capital negatively affects these two productivity indicators.
Coding of depth-maps using piecewise linear functions

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Anthropological Study of Somatic Symptoms in Tattooed Individuals

Tattoos are increasing in size and popularity around the world, especially in the younger generation. Traditionally it is commonly seen in most of the religions having these tattoos; more common in females. Inserting tattoo, into the skin by introducing them through punctures has long posed an intriguing problem; commonly seen as challenging medical practice. The tattoo is expected to alter the new wearer's perception of the individual's identity. For the same reason, tattoos seem to have the ability to have a greater impact on one's self, with minimal variations and majority potentially affected identity. In the recent era, tattoos are even recognized as having autotherapeutical power which is in case of psychological trauma [1]. Tattoo and Body modifications are also considered a healthier alternative to attempts of self-mutilation [2].
Triple Agent Immunosuppressive Therapy in Vogt-Koyanagi-Harada Syndrome

Purpose: To describe the role of triple agent immunosuppression in severe recalcitrant cases of Vogt-Koyanagi-Harada syndrome. Materials and methods: Retrospective chart review of five cases of Vogt-Koyanagi-Harada syndrome. Results: All cases were treated with oral prednisolone, azathioprine, and cyclosporine in combination, and rapid remission was observed in all patients. The synergistic effect of the triple agent immunosuppressives helped in preventing recurrences. Prolonged treatment with steroid sparing immunosuppressives in severe and recalcitrant cases of Vogt-Koyanagi-Harada syndrome maintained disease remission. Conclusion: Severe cases of Vogt-Koyanagi-Harada syndrome can be treated with early use of high-dose triple agent immunosuppressives.
Metagenomic Evaluation of Bacteria from Voles Koskela

Voles (Arvicolinae, Rodentia) are known carriers of zoonotic bacteria such as Bartonella spp. and Francisella tularensis. However, apart from F. tularensis, the bacterial microbiome of voles has not previously been determined in Finland and rarely elsewhere. Therefore, we studied liver samples from 61 voles using 16S ribosomal RNA gene PCR analysis, followed by Sanger sequencing. Twenty-three of these samples were also studied with tag-encoded pyrosequencing. The samples originated from 21 field voles (Microtus agrestis), 37 tundra voles (Microtus oeconomus), and 3 bank voles (Myodes glareolus). With the more conventional 16S rDNA PCR analysis, 90 (33%) of the recovered 269 sequence types could be identified to genus level, including Bartonella, Francisella, Mycoplasma, Anaplasma, and Acinetobacter in 31, 15, 9, 9, and 9 sequences, respectively. Seventy-five (28%) matched best with sequences of uncultured bacteria, of which 40/75 could be classified to the order Clostridiales and, more specifically, to families Lachnospiraceae and Ruminococcaceae. Pyrosequencing from 23 samples revealed comparable and similar results: clinically relevant bacterial families such as Mycoplasmataceae, Bartonellaceae, Anaplasmataceae, and Francisellaceae were recognized. These analyses revealed significant bacterial diversity in vole livers, consisting of distinct and constant sequence patterns reflecting bacteria found in the intestinal gut, but including some known zoonotic pathogens as well. The molecular bacterial sequence types determined with the two different techniques shared major similarities and verified remarkable congruency between the methods.
Chemotactic Activity of Cyclophilin A in the Skin Mucus of Yellow Catfish (Pelteobagrus fulvidraco) and Its Active Site for Chemotaxis

Fish skin mucus is a dynamic barrier for invading pathogens with a variety of anti-microbial enzymes, including cyclophilin A (CypA), a multi-functional protein with peptidyl-prolyl cis/trans isomerase (PPIase) activity. Beside various other immunological functions, CypA induces leucocytes migration in vitro in teleost. In the current study, we have discovered several novel immune-relevant proteins in yellow catfish skin mucus by mass spectrometry (MS). The CypA present among them was further detected by Western blot. Moreover, the CypA present in the skin mucus displayed strong chemotactic activity for yellow catfish leucocytes. Interestingly, asparagine (like arginine in mammals) at position 69 was the critical site in yellow catfish CypA involved in leucocyte attraction. These novel efforts do not only highlight the enzymatic texture of skin mucus, but signify CypA to be targeted for anti-inflammatory therapeutics.
De-Anonymizing the Bitcoin Blockchain

Bitcoin is the most popular of a collection of cryptocurriences that have risen to prominence in recent years, promising a de-centralized approach to currency. A belief in transaction anonymity has accompanied, and often propelled, this growth, especially among users who desire privacy. In this paper, we investigate whether one method of 'anonymizing' transaction histories in practice namely, utilizing different addresses for every transaction is successful, by attempting to cluster together addresses owned by the same entity. We use a novel approach that involves unsupervised clustering based on structural and attribute similarities in an augmented transaction graph. In doing so, we integrate and build upon past efforts to cluster user addresses using either structural properties of the bitcoin transaction graph or network-level data on user behavior. We ultimately find this methodology to be successful in proof-of-concept tests.
IMPROVING GLOBAL NEIGHBORHOOD STRUCTURE MAP DENOISING APPROACH FOR DIGITAL IMAGES

This paper proposes a new noise reduction model for digital images. In the proposed model, the intensity similarity between the center pixel and its neighboring pixels within a certain window for constructing a Global Neighborhood Structure (GNS) using Dominant Neighborhood Structure (DNS) maps of central pixels has been measured. The intensity similarity was calculated by using the Canberra Distance measurement equation; where the conventional GNS map approach used the Euclidean distance principle. To evaluate the performance of the proposed model, several noise attacks were imposed on two public image datasets and experimental results demonstrated that the proposed model outperforms the conventional GNS map based denoising technique by exhibiting higher PSNR and SNR values.
Cornea Evaluation of Corneal Displacement Using High-Speed Photography at the Early and Late Phases of Noncontact

Citation: Nakakura S, Kiuchi Y, Kaneko M, et al. Evaluation of corneal displacement using high-speed photography at the early and late phases of noncontact tonometry. Invest Ophthalmol Vis Sci. 2013;54:2474–2482. DOI:10.1167/ iovs.12-11424 PURPOSE. We investigated the extent of corneal displacement and factors associated with the measurement of IOP during the early and late phases of noncontact tonometry.
A High-Performance Stochastic Fractal Search Algorithm for Optimal Generation Dispatch Problem

This paper proposes applications of a modified stochastic fractal search algorithm (MSFS) to solve the economic load dispatch problem (ELD) in which valve-point effects, prohibited operating zones, power losses in all conductors, multi-fuel sources and other constraints of power system are taken into consideration. The proposed method is first developed in the study by performing two modifications on two procedures of new solution generation from conventional stochastic fractal search (SFS). The first modification is used to change the strategy of producing new solutions of the first and the second update procedures while the second one is to newly update the worst solutions in the first update process and the best solutions in the second update process. These modifications have major influence on the solution search performance of the proposed method. All improvements of the proposed method can be illustrated by solving and analyzing results from various test systems with different system scales including 3-unit, 6-unit, 10-unit, and 20-unit systems. Comparison of results obtained by MSFS, SFS, and other existing methods indicates that the proposed MSFS method is more effective and robust than compared methods in terms of solution quality, high-quality solution search stability and convergence process. Consequently, the proposed method should be used as a very favorable optimization method for the ELD problem and it should be tried for other optimization problems in electrical engineering.
Critical Power can be Estimated From Nonexhaustive Tests Based on Rating of Perceived Exertion Responses

The purpose of this study was to evaluate a novel procedure, based on the perceived exertion threshold (PET) concept, involving non-exhaustive tests (PET14-17) to estimate critical power (CP), as well as to examine the reproducibility of these indices. Twenty young men performed 2 trials (Trial 1 and Trial 2) of 4 exhaustive predictive tests to estimate CP, PET, and PET14-17. The slope coefficients of the regression lines corresponding to the ratings of perceived exertion (RPE) versus time relationship (y axis) obtained during the predictive tests were plotted against the power outputs (x axis) to estimate PET. PET was calculated as the intersection point of the regression line in the power axis. The 14-17 RPE range of each predictive test was modeled using the same mathematical procedures used to estimate PET14-17. CP was derived from the power-time hyperbolic equation. Analysis of variance revealed no significant differences among CP (189-194 W), PET (190-191 W) and PET14-17, (191-195 W). The correlations between CP and PET (r = 0.87), CP and PET14-17 (r = 0.89), and PET and PET14-17 (r = 0.88) were all strong. Additionally, the bias ± limits of agreement when plotting CP and PET was -2.16 ± 31.60 W, and -5.70 ± 31.21 W when comparing CP and PET14-17. Relatively high reproducibility levels of CP (ICC = 0.96), PET (ICC = 0.85) and PET14-17 (ICC = 0.83) were recorded in the test-retest fashion. It can be concluded that the PET14-17 can be utilized with relatively high accuracy and reproducibility to estimate CP without causing exhaustion in the subjects.
Cornea Generation of Human Corneal Endothelial Cells via In Vitro Ocular Lineage Restriction of Pluripotent Stem Cells

METHODS. Corneal endothelial cell induction was driven by small molecules in a stepwise fashion of lineage specification. During the initial phase, PSC fate was restricted to the eye field-like state and became eye field stem cells (EFSCs). In the second phase, PSC-derived EFSCs were further directed toward either neural crest lineage or retinal lineage. The CECs were directly induced from ocular neural crest stem cells (NCSCs) by suppressing TGF-b and ROCK signaling.
High-temperature charge density wave correlations in La1.875Ba0.125CuO4 without spin–charge locking

Significance Charge correlations have now been identified in the low-temperature phase of essentially all families of underdoped cuprates, but in two apparently distinct types. The first hosts locked charge and spin stripes of which the material La1.875Ba0. 125CuO4 (LBCO 1/8) is a paradigmatic example. In the second type, a charge density wave (CDW) exists without any obviously related spin correlations. Here we report the discovery of high-temperature CDW correlations that exist at temperatures above the CDW transition in the canonical striped cuprate LBCO 1/8. We find that the high-temperature CDW is decoupled from the fluctuating spin density wave, lessening apparent differences in behavior among different materials and setting important constraints for how we understand their electronic states. Although all superconducting cuprates display charge-ordering tendencies, their low-temperature properties are distinct, impeding efforts to understand the phenomena within a single conceptual framework. While some systems exhibit stripes of charge and spin, with a locked periodicity, others host charge density waves (CDWs) without any obviously related spin order. Here we use resonant inelastic X-ray scattering to follow the evolution of charge correlations in the canonical stripe-ordered cuprate La1.875Ba0. 125CuO4 across its ordering transition. We find that high-temperature charge correlations are unlocked from the wavevector of the spin correlations, signaling analogies to CDW phases in various other cuprates. This indicates that stripe order at low temperatures is stabilized by the coupling of otherwise independent charge and spin density waves, with important implications for the relation between charge and spin correlations in the cuprates.
Sundell Helping students remember : catalytic knowledge and knowledge outlines with visual mnemonics

To recall educational content from a lecture or textbook is an efficient way to learn (Karpicke & Blunt, 2011), which is referred to as retrieval practice (Karpicke & Roediger, 2008). It is currently seldom used among students (Karpicke, Butler, & Roediger, 2009), even though it provides benefits such as reducing test anxiety (Agarwal, D’Antonio, Roediger III, McDermott, & McDaniel, 2014), longer lasting memories (Karpicke & Blunt, 2011), and also benefit future learning (Pastötter & Bäuml, 2014). But, in order for retrieval practice to work efficiently, the students must not fail to recall too much of the educational content (Kornell, Bjork, & Garcia, 2011). So in order to help students use retrieval practice, I suggest they are provided with an outlining of the educational content, as this probably helps them remember and recall more of it. In this thesis, I conclude with an experimental approach that it is possible to help students remember such knowledge outlines, and how it can be done. Furthermore, since knowledge such as knowledge about the human anatomy, can be catalytic in the sense that it can enhance future learning (Hattie, 2009; Van Overschelde & Healy, 2001), I also suggest that catalytic knowledge should be identified and made memorable by educators using similar techniques as in this study.
Neural Heterogeneous Scheduler

Access to parallel and distributed computation has enabled researchers and developers to improve algorithms and performance in many applications. Recent research has focused on next generation special purpose systems with multiple kinds of coprocessors, known as heterogeneous system-on-chips (SoC). In this paper, we introduce a method to intelligently schedule--and learn to schedule--a stream of tasks to available processing elements in such a system. We use deep reinforcement learning enabling complex sequential decision making and empirically show that our reinforcement learning system provides for a viable, better alternative to conventional scheduling heuristics with respect to minimizing execution time.
3 D-LMNet : Latent Embedding Matching for Accurate and Diverse 3 D Point Cloud Reconstruction from a Single Image : Supplementary Material

1 Training Dataset Details We train all our networks on synthetic models from the ShapeNet [1] dataset. We use the same 80%-20% train/test split provided by [2] consisting of models from 13 different categories, so as to be comparable with the previous works. We use the input images provided by [2], where each model is pre-rendered from 24 different azimuth angles. We crop the images to 128× 128 resolution before passing it through our network. For generating the ground truth point cloud, we uniformly sample 16384 points on the mesh surface using farthest point sampling.
Transfer approach for the detection of missed task-relevant events in P300-based brain-computer interfaces

Detection of human cognitive states using biosig-nals such as the electroencephalogram (EEG) is gaining relevance in different application areas, e.g., teleoperation, human-robot collaboration, and rehabilitation. Especially, the P300, which is evoked as an event-related potential (ERP), when humans perceive task-relevant infrequent events among task-irrelevant frequent events, is widely used in brain-computer interfaces (BCIs). P300 detection has been used as an indicator that a human perceives task-relevant events or detects the occurrence of task-relevant or important events. In this paper, we focus on not only perceived task-relevant events but also not-perceived task-relevant events (i.e., missed events). In fact, a human can miss task-relevant events for different reasons, e.g., reduced attention level or increased workload level during parallel task-processing situations among others. Moreover, a human can also intentionally ignore task-relevant events to manage several simultaneous tasks. However, such missed events do not often occur in real-world applications. In this paper, we propose a transfer approach to handle insufficient number of events for training a classifier. For example, task-irrelevant infrequent events are used for training of classifier to detect missed task-relevant events. We evaluated our approach in different settings of training and testing a classifier with and without classifier transfer.
Salinity Evaluation for Watermelon ( Citrullus lanatus ) Grafted with Different Rootstocks

Salinity is a common stress in arid and semi-arid environments and can affect quality and production of sensitive crops such as watermelon (Citrullus lanatus). Grafting vegetable crops has been shown to improve fruit quality as well as impart tolerance to abiotic and biotic stresses. To evaluate potential rootstocks that will minimize the impact of salinity on watermelons, a preliminary study was conducted to study the performance of watermelons grafted to experimental and commercial rootstocks. Mini watermelons (Citrullus lanatus ‘TAMU mini’) were grafted on four rootstocks: Strong Tosa, CTPI RS, NIZ 54-07, and smell melon. These grafted plants and ungrafted ‘TAMU mini’ controls were subjected to three levels of salinity (0, 1.5, and 3 dS·m irrigation water). Grafted watermelons exposed to 1.5 dS·m had increased dry vine biomass, flesh firmness, and soluble solids compared to plants irrigated with 0 and 3 dS·m. Exposure to the 3 dS·m treatment increased brix but did not significantly change other measured variables. Increasing salinity did not reduce biomass or fruit size, and ‘TAMU mini’ watermelon grafted to ‘Strong Tosa’ rootstock was the best performer amongst the four rootstocks tested. Additional Index Words: Watermelon, grafting, salinity, Citrullus lanatus, rootstocks As of 2012, approximately 55 million acres of farmland in the U.S. were irrigated (United States Department of Commerce, 2012). Irrigated agriculture is predicted to increase in the next few decades as population and subsequent demand for food production increases (Ghassemi et al., 1995; Howell, 2001). As irrigated acreage increases, so does soil salinization, especially in areas affected by drought (Ghassemi et al., 1995; Munns, 2002). Selecting crops for tolerance to salinity stress is vital for the future of agriculture in order to meet the food needs of future populations. Most breeding programs select cultivars or rootstocks for their tolerance to abiotic stresses such as salinity, heat and cold, as well as disease resistance. However, traits related to stress tolerance may lead to reduced fruit quality or yield (Davis et al., 2008). One common method to induce stress tolerance by physical means is grafting of a productive scion on a stress tolerant rootstock. Large scale production of grafted watermelons began in Korea and Japan in the 1920’s to allow for continuous cropping in areas prone to soilborne diseases (Davis et al., 2008). Grafting to vigorous rootstocks can enhance disease resistance, yield, nutrient acquisition, drought and cold tolerance, growth, fruit quality, and salt tolerance as reported for different crops such as watermelon, tobacco and tomato (Colla et al., 2006; Edelstein et al., 2004; Ruiz et al., 2006; Santa-Cruz et al., 2002; Uygur and Yetisir, 2009). Grafted cucumber plants have higher photosynthesis rates and stomatal conductance in saline conditions than non-grafted plants (Yang et al., 2006). Several studies have also shown that grafting led to in-
A Collaboration Maturity Model: Development and Exploratory Application

This paper presents a Collaboration Maturity Model (Col-MM) to assess an organization's team collaboration quality. The Col-MM is intended to be sufficiently generic to be applied to any type of collaboration and useable by practitioners for con-ducting self-assessments. The Col-MM was developed during a series of Focus Group meetings with professional collaboration experts. The model was piloted and subsequently applied in the automotive industry. This paper reports on the development and first field application of the Col-MM. The paper further serves as a starting point for future research in this area.
Novel Approach to Fashion Design using Artificial Intelligence

: The task of fashion designing now days is becoming more and more difficult due to increasing expectations of the consumers. For this, Artificial Intelligence is going to aid the growing need for variety of designs and their faster production which will also minimize the huge loss in production. Recent approaches include use of deep neural networks and here we are extending their use to generate the apparel designs. A class of deep neural networks known as Generative Adversarial Networks (GANs) which are comprised of two networks namely generative and discriminative. Specifically, we are using Deep Convolutional Generative Adversarial Networks (DCGANs) have certain constraints on their architecture which help them to be a good prospect for unsupervised learning. Additionally, we show that the proposed model functions generatively i.e., according to the user preferences, it can generate new images of clothing items similar to the user taste.
Ozone fl ux measurements over a Scots pine forest using eddy covariance method : performance evaluation and comparison with fl ux-profi le method

1) University of Helsinki, Department of Physical Sciences, P.O. Box 64, FIN-00014 University of Helsinki, Finland 2) University of Helsinki, Department of Chemistry, P.O. Box 55, FIN-00014 University of Helsinki, Finland 3) Finnish Meteorological Institute, Air Quality Research, Sahaajankatu 22 E, FIN-00880 Helsinki, Finland 4) University of Helsinki, Department of Forest Ecology, P.O. Box 27, FIN-00014 University of Helsinki, Finland