Miracle-dz/UniFAR-FTUs huggingface dataset:
Dealing With Inefficiencies of Electricity Markets by Internalization of Negative Externalities of the Operational Restrictions of Generating Units

Economic efficiency is the main goal of all markets, including the electricity market. Technical and pecuniary restrictions, known as externalities, caused by the technical limits of generation units are inherent in electricity markets and can significantly affect their economic efficiency. In this article, an efficient service-based method is proposed aimed at internalizing negative externalities in the electricity markets. The method employs services procured by energy storage systems and responsive demand to internalize the generation sector's technical externalities. For the optimal capacity and price of the proposed service, bi-level optimization and an innovative discriminatory pricing scheme are applied. In this way, the first-best optimal market solution can be reached by internalizing the negative externalities in the sub-optimal second-best solution due to the generators' operational constraints. Numerical case studies verify the effectiveness of the proposed scheme, where considering nearly 5% responsive demand and storage capacity around 5% of peak load, it is possible to achieve economic efficiency by reducing the total cost. In real power systems, this cost reduction can result in millions of dollars in annual operational cost savings.
An Intelligent, User‐Inclusive Pipeline for Organic Semiconductor Design

Data‐guided methodologies for designing new materials are developing apace, yet advances for organic crystals have been infrequent. For the case of organic crystals, data‐guided design platforms involve two problems: the need to construct regression models that can predict solid‐state properties from molecular structures alone and the vast number of molecular structures that satisfy a targeted solid‐state property. In this paper, a new pipeline is presented for designing molecules with targeted solid‐state electronic properties. Here, the first problem is overcome by means of a novel visualization method for band structure data, which allows the user to specify their design preferences and simplify the creation of the required regression models. The second problem is overcome by allowing for user intervention in the selection of the final molecule for subsequent synthesis. The effectiveness of this pipeline is demonstrated by using it to design a simple new molecule with a targeted bandgap and impressive band dispersion. This pipeline is the first data‐guided method that can design new molecules on the basis of genuine solid‐state electronic properties, and with its emphasis on user‐inclusivity, it can easily be applied in collaborative or industry settings.
#capuchinmonkeys on Social Media: A Threat for Species Conservation

ABSTRACT There remains a debate as to whether the display of wild animals in popular media, such as the Internet, contributes toward or erodes conservation behavior. A good model to assess these impacts are capuchin monkeys (genera Cebus and Sapajus), given that they have historically been traded as pets internationally and are among Hollywood’s most famous primate actors. We used crowdsourcing tools to survey social media posts (YouTube and Instagram) and news/reports (on Google) to investigate how these primates are currently portrayed on the Internet. We found 1138 capuchin-related videos on YouTube, and the ones with more than 1 million views mainly (71%) portrayed these animals as pets. Searches on Instagram identified that #capuchinmonkey had 39,000 more posts than #Cebus or #Sapajus, of which the top results (those that generated the most engagement) were posts of individuals in anthropogenic environments and/or close to humans. Our Google search identified an exponential growth of news related to the legal and illegal pet trade of capuchin monkeys since 2017, which could be related to the increase on the reach and engagement of social media posts with these primates as pets. Poor scientific knowledge or interest, along with engagement with exotic pet trade content among Internet users, may lead to negative consequences for species conservation. Given the threats facing both capuchin monkeys and other animals, including increasing habitat fragmentation and loss, it is essential to establish clear policies surrounding wildlife content management on social media.
Correlated Target Search by Vaccinia Virus Uracil–DNA Glycosylase, a DNA Repair Enzyme and a Processivity Factor of Viral Replication Machinery

The protein encoded by the vaccinia virus D4R gene has base excision repair uracil–DNA N-glycosylase (vvUNG) activity and also acts as a processivity factor in the viral replication complex. The use of a protein unlike PolN/PCNA sliding clamps is a unique feature of orthopoxviral replication, providing an attractive target for drug design. However, the intrinsic processivity of vvUNG has never been estimated, leaving open the question whether it is sufficient to impart processivity to the viral polymerase. Here, we use the correlated cleavage assay to characterize the translocation of vvUNG along DNA between two uracil residues. The salt dependence of the correlated cleavage, together with the similar affinity of vvUNG for damaged and undamaged DNA, support the one-dimensional diffusion mechanism of lesion search. Unlike short gaps, covalent adducts partly block vvUNG translocation. Kinetic experiments show that once a lesion is found it is excised with a probability ~0.76. Varying the distance between two uracils, we use a random walk model to estimate the mean number of steps per association with DNA at ~4200, which is consistent with vvUNG playing a role as a processivity factor. Finally, we show that inhibitors carrying a tetrahydro-2,4,6-trioxopyrimidinylidene moiety can suppress the processivity of vvUNG.
Empirical Mode Multi-Scale Image Decomposition

An image generally includes a great deal of different-scale information, and that the image application research sometimes limits to the phenomenon of one scale or some scales. So, it is necessary to decompose an image according to the different-scale. It can eliminate the influence of other scales to the result of the image processing, and also simplify the difficulty and complexity of the image processing. This paper uses Empirical Mode Decomposition method to decompose image from small-scale to large-scale. The small-scale information contains the detail of the image, and the remained large-scale information expresses the prime tendency and structure of the image. This method is an efficient way in image preprocessing.
Salimenaea and Troncosoa (Verbenaceae, Lantaneae), Two New Monotypic Genera from Southern South America

Abstract. Salimenaea N. O'Leary & P. Moroni and Troncosoa N. O'Leary & P. Moroni (Verbenaceae), two new monotypic genera containing species historically treated under Lippia L. and Acantholippia Griseb. , respectively, are described here. These new genera reconcile the taxonomy of tribe Lantaneae with the evidence so far reached by morphological studies and molecular phylogenetics. Consequently, the combinations S. integrifolia (Griseb.) N. O'Leary & P. Moroni and T. seriphioides (A. Gray) N. O'Leary & P. Moroni are here proposed for two species endemic to Argentina–Bolivia and to Argentina, respectively. Complete generic and species descriptions are included, plus a geographic distribution map, photographs, and line art illustrations. Additionally, the morphological features distinguishing the new genera from other closely related taxa are discussed, and a key to currently recognized genera of Lantaneae is presented.
Eye Movements as Proxy for Visual Working Memory Usage: Increased Reliance on the External World in Korsakoff Syndrome

In the assessment of visual working memory, estimating the maximum capacity is currently the gold standard. However, traditional tasks disregard that information generally remains available in the external world. Only when to-be-used information is not readily accessible, memory is taxed. Otherwise, people sample information from the environment as a form of cognitive offloading. To investigate how memory deficits impact the trade-off between sampling externally or storing internally, we compared gaze behaviour of individuals with Korsakoff amnesia (n = 24, age range 47–74 years) and healthy controls (n = 27, age range 40–81 years) on a copy task that provoked different strategies by having information freely accessible (facilitating sampling) or introducing a gaze-contingent waiting time (provoking storing). Indeed, patients sampled more often and longer, compared to controls. When sampling became time-consuming, controls reduced sampling and memorised more. Patients also showed reduced and longer sampling in this condition, suggesting an attempt at memorisation. Importantly, however, patients sampled disproportionately more often than controls, whilst accuracy dropped. This finding suggests that amnesia patients sample frequently and do not fully compensate for increased sampling costs by memorising more at once. In other words, Korsakoff amnesia resulted in a heavy reliance on the world as ‘external memory’.
Wave telescope technique for MMS magnetometer

Multipoint measurements are a powerful method in studying wavefields in space plasmas. The wave telescope technique is tested against magnetic field fluctuations in the terrestrial magnetosheath measured by the four Magnetospheric Multiscale (MMS) spacecraft on a spatial scale of about 20 km. The dispersion relation diagram and the wave vector distribution are determined for the first time in the ion‐kinetic range. Moreover, the dispersion relation diagram is determined in a proxy plasma rest frame by regarding the low‐frequency dispersion relation as a Doppler relation and compensating for the apparent phase velocity. Fluctuations are highly compressible, and the wave vectors have an angle of about 60° from the mean magnetic field. We interpret that the measured fluctuations represent a kinetic‐drift mirror mode in the magnetosheath which is dispersive and in a turbulent state accompanied by a sideband formation.
A novel collaborative filtering algorithm by making recommendations from curious users

Social curiosity indicates that a user is interested in what other peoples viewed and selected. The idea of UserCF fits matches the social curiosity concept by generating the recommendation from the similar users. However, many studies indicate that UserCF tends to recommend the item similar to what the user has chosen and the user may be bored with such kind of recommendation. To address the issue of UserCF, we propose a novel scheme called CuriCF, which makes recommendation from the curious users who are more active to try the new and different items. And then recommendations with high relevance and high difference are generated from the curious users. Experimental results demonstrate that our CuriCF recommends the items not only fitting the user’s preference but also different from what the user has chosen.
TV Symbol Recognition Based on Shape ang Color Features

As a sign of a TV station, its symbol often implies semantics about its name and program tendency and it is one of the important semantic sources for video analysis, comprehension and retrieval. According to spatio--temporal visual feature, TV station symbol is firstly segmented by the detection of spatio--temporal invariant region, then described by combining space--distribution histogram and color histogram in HSV space, and recognized by support vector machine (SVM) finally. The algorithm is experimentally satisfied.
Mean Velocity Characteristics behind a Forward-Swept Axial-Flow Fan

Detailed measurements in the flow behind a highly forward-swept axial-flow fan at three operating conditions were performed using three-dimensional LDV system. Various phenomena related to the leakage flow, leakage vortex, hub vortex and wake were investigated. At the design condition, where no distinct leakage vortex appears behind trailing edge, the leakage flow interacts with the boundary layer of the pressure side inside the blade passage, which directly influence the wake characteristics behind the trailing edge. At the low loading condition, the leakage vortex has the characteristics of the velocity defect and this vortex induces radially inward flows at both the suction and pressure sides in the wake near the tip region. As the loading increases, radially-outward velocity component increases and the position of the maximum value in the wake is closer to the tip region. At the design and high loading condition, hub vortex induces radially inward flow at the pressure side and wakes near the hub region decays very quickly due to the interaction with the large hub vortex.
A Minimum Mean Squared Error Semiparametric Combining Estimator

In the context of competing theoretical economic–econometric models and corresponding estimators, we demonstrate a semiparametric combining estimator that, under quadratic loss, has superior risk performance. The method eliminates the need for pretesting to decide between members of the relevant family of econometric models and demonstrates, under quadratic loss, the nonoptimality of the conventional pretest estimator. First-order asymptotic properties of the combined estimator are demonstrated. A sampling study is used to illustrate finite sample performance over a range of econometric model sampling designs that includes performance relative to a Hausman-type model selection pretest estimator. An important empirical problem from the causal effects literature is analyzed to indicate the applicability and econometric implications of the methodology. This combining estimation and inference framework can be extended to a range of models and corresponding estimators. The combining estimator is novel in that it provides directly minimum quadratic loss solutions.
Analysis of Food Industry Waste Management Based-On the Food Recovery Hierarchy and 3R Concept – A Case Study in Padang City, West Sumatra, Indonesia

This research goal was to analyze food industry waste in Padang City based on Food Recovery Hierarchy and 3R concept. Waste sampling refers to SNI 19-3964-1994 with 35 sampling points spread across 6 types of food industries. According to the sampling result which includes waste generation, composition, and characteristics, the management of the food industry in Padang City was studied based on the principles of Food Recovery Hierarchy and 3R Concept. The result of the study showed that waste generated is 27.44 tons/day or equivalent to 250.31 m 3 / day with the organic waste as the largest contributor having percentage of 85.06%. On the basis of the chemical and biological characteristics, such as water content, C/N ratio, and biodegradability fraction, the waste shows that the most compatible treatment for the waste is biological treatment with composting. First step in the principles of Food Recovery Hierarchy is applying the concept of waste reduction to the waste resulted from each industry in as many as 2.19% or 4.83 kg/day. In the second step, 44.295 or 99.92 kg/day of the waste were given to livestock. The third step involved composting 39.27% or 86.72% of the waste. The fourth step was to do landfilling with 1.77% or 3.90 kg/day of the waste. The fifth step was selling 12.48% or 25.40 kg/day of the waste that has a recycling potential to collectors based on the 3R concept. If these concepts are applied, the waste taken to the dumpsite will decrease from 16.24 tons/day to 0.49 tons/day.
Analysis and Comparison of Methods for Real-time Solid Deformation

The powerful computing capacity of computer has made physically based deformation widely studied. In this paper, we describe a general framework to deal with real-time solid deformation simulation. Based on Newton’s Laws of Motion and discrete analysis methods, this frame system couples several explicit and implicit numerical integrators and elastic material models under initial and boundary constraint conditions. The simulator models solid deformable object as a tetrahedral mesh with internal elastic forces and damping forces derived dependent on material models and equilibrium equations properly time-stepped forward using specific integrators. In order to give a detailed and persuasive description and provide necessary support to potential animators, different material models and integrators are analyzed theoretically and corresponding combinations are compared in respects of time performance and system stability with practical model simulation. In particular, the solution of implicit Newmark integrator in combination with Saint-Venant Kirchhoff model is demonstrated superior performance while taking a comprehensive consideration of complexity, stability and plausibility.
Motion Artifact Reduction Algorithm for Wearable Electrocardiogram Monitoring Systems

An electrocardiogram (ECG) test is usually performed through measurement with Ag/AgCl electrodes. However, this method has disadvantages, such as skin irritation, short shelf life, and conductance variation in gels over time, which limit the usability for long-term monitoring. One of the alternatives is adopting conductive fabric-based electrodes, but this method involves a problem in which a motion artifact (MA) becomes more severe because no gel and adhesive are available to provide a stable interface between the electrodes and the skin. To address this problem, this study presents a conductive fabric-based ECG monitoring system and an MA reduction algorithm. The system can simultaneously measure the ECG and the electrode–tissue impedance (ETI) with the proposed shirt. The MA reduction algorithm aims to reduce MA with ETI information. The MAs in Lead I, II, and III ECG measurement are generated by lifting arms, walking, and jogging. Results of the MA reduction are quantified by the correlation coefficient (CORR) and mean squared error (MSE). The quantitative analysis shows that the MA can be suppressed by the proposed algorithm. Moreover, compared with a reproduced existing approach, the proposed algorithm performs better in most cases.
Whiteboarding: A Tool for Moving Classroom Discourse from Answer-Making to Sense-Making.

In 1998 I had been teaching science for 13 years. I was a good teacher: I had the plaques and certificates to prove it. But often I felt like an impostor (which I have since learned is not unusual—70% of all people feel like a fake at one time or another). While my students could solve problems and ace tests, every June when I sat down to look at their Force Concept Inventory (FCI) results, I was confronted by how little they had actually learned in my physics classes. It was this annual reality check that drove me to pursue my first Modeling Workshop in summer of 1998. For four weeks I was a physics student again—every day, for six to eight hours a day. I (re)learned to think aloud, to “speak physics” and to listen to how I and others (students) spoke physics. That summer changed everything. When I returned to my high school physics classroom equipped with a new way of teaching in September of 1998, I was excited. I felt like I had the key to the perfect year—I wouldn't be an impostor anymore.
The Management of Diabetes Mellitus Using Medicinal Plants and Vitamins

Diabetes mellitus (DM) is a serious chronic metabolic disease that is associated with hyperglycemia and several complications including cardiovascular disease and chronic kidney disease. DM is caused by high levels of blood sugar in the body associated with the disruption of insulin metabolism and homeostasis. Over time, DM can induce life-threatening health problems such as blindness, heart disease, kidney damage, and stroke. Although the cure of DM has improved over the past decades, its morbidity and mortality rates remain high. Hence, new therapeutic strategies are needed to overcome the burden of this disease. One such prevention and treatment strategy that is easily accessible to diabetic patients at low cost is the use of medicinal plants, vitamins, and essential elements. The research objective of this review article is to study DM and explore its treatment modalities based on medicinal plants and vitamins. To achieve our objective, we searched scientific databases of ongoing trials in PubMed Central, Medline databases, and Google Scholar websites. We also searched databases on World Health Organization International Clinical Trials Registry Platform to collect relevant papers. Results of numerous scientific investigations revealed that phytochemicals present in medicinal plants (Allium sativum, Momordica charantia, Hibiscus sabdariffa L., and Zingiber officinale) possess anti-hypoglycemic activities and show promise for the prevention and/or control of DM. Results also revealed that intake of vitamins C, D, E, or their combination improves the health of diabetes patients by reducing blood glucose, inflammation, lipid peroxidation, and blood pressure levels. However, very limited studies have addressed the health benefits of medicinal plants and vitamins as chemo-therapeutic/preventive agents for the management of DM. This review paper aims at addressing this knowledge gap by studying DM and highlighting the biomedical significance of the most potent medicinal plants and vitamins with hypoglycemic properties that show a great potential to prevent and/or treat DM.
To Ski or Not to Ski: Estimating Transition Matrices to Predict Tomorrow's Snowfall Using Real Data

Using historical data from the Global Historical Climatology Network (GHCN)-Daily database, the use of Markov chain models is presented to predict a ‘Snow Day’ at eight national weather stations. This serves as a variation of the classic Markov chain precipitation example, predicting a significant snow depth tomorrow from today's snow depth conditions. Stations near Seattle WA, Denver CO, Milwaukee WI, Chicago IL, New York NY and Boston MA, were included as they represent major urban centers, while stations in Montana and North Dakota were added to improve geographical coverage. Estimates of the appropriate transition matrices (ˆi) are provided, as well as a sample of code in the R statistical programming language to enable construction of similar examples for other geographical areas.
New 5-Hydroxycoumarin-Based Tyrosyl-DNA Phosphodiesterase I Inhibitors Sensitize Tumor Cell Line to Topotecan

Tyrosyl-DNA-phosphodiesterase 1 (TDP1) is an important enzyme in the DNA repair system. The ability of the enzyme to repair DNA damage induced by a topoisomerase 1 poison such as the anticancer drug topotecan makes TDP1 a promising target for complex antitumor therapy. In this work, a set of new 5-hydroxycoumarin derivatives containing monoterpene moieties was synthesized. It was shown that most of the conjugates synthesized demonstrated high inhibitory properties against TDP1 with an IC50 in low micromolar or nanomolar ranges. Geraniol derivative 33a was the most potent inhibitor with IC50 130 nM. Docking the ligands to TDP1 predicted a good fit with the catalytic pocket blocking access to it. The conjugates used in non-toxic concentration increased cytotoxicity of topotecan against HeLa cancer cell line but not against conditionally normal HEK 293A cells. Thus, a new structural series of TDP1 inhibitors, which are able to sensitize cancer cells to the topotecan cytotoxic effect has been discovered.