Reviewerly/exHarmony huggingface dataset:
Corona: A Catalyst of Poetic Justice

Corona has terrified the people and the countries the world over. Safety and security of individuals at individual levels have become more important than at collective levels. No doubt, at collective levels too, people are awakened to take precautionary measures but at the cost of individual levels by being quarantined. In the present paper I’ve tried to throw light on the brighter side of corona. It has emerged as boon for flora and fauna. Corona has frightened man and has made him realize to understand the broader perspectives of Nature. Man, animals, living and non-living creatures are the parts of Nature; good and bad,virtues and vices, healthful life and life with diseases rest in Nature and so it is unfair to curse Corona.
Penerapan Motode Modelling Pada Kasus Intellectual Disability

Children with Down Syndrome experience developmental delays globally in gross and fine motor skills. This motor delay is accompaniedby mild to moderate Intellectual Disability with a majority IQ between 40 and 70.Miller and Chapman (1984) in Paul &amp; Norbury (2012)estimate that nearly 50% of children with non-specific intellectual disabilities have language skills equivalent to their nonverbal abilities. .The rest have language skills that are not commensurate with their nonverbal abilities, namely 25% have a relative expressive languagedeficit. Speech therapist has a role in handling cases of Intellectual Disability in language skills. Therapeutic planning that is set on theclient in the form of a short-term goal is to improve receptive language skills at the level of the family category noun with an accuracy levelof 50% for 3 consecutive sessions and the therapy material given to the client is the exercise of pointing at family photos, namely: nizam,mother, ladies and gentlemen. This study aims to determine the description of the Intellectual Disability case at the Tugurejo HospitalSemarang, to find out the description of therapy planning in the Intellectual Disability case at the Tugurejo Hospital Semarang, todetermine the factors that influence the management of Speech Therapy in the Intellectual Disability case at the Tugurejo HospitalSemarang. The results of therapy on the ability to understand the family category as many as 5 meetings for 5 weeks with an accuracylevel of 80% have increased even though they have not been able to be consistent for 3 consecutive sessions. After 5 sessions of therapy, itcan be seen that the specified short-term goals have not been achieved because they are influenced by several factors, namely the age of theclient who is 6 years old and the client's poor attention
STUDI DESKRIPTIF KEMAMPUAN KOMUNIKASI TULIS DALAM MENYELESAIKAN SOAL PECAHAN CAMPURAN PADA PESERTA DIDIK KELAS VII SMPN 1 LAMPASIO

Communication skills are important for every human being. Communication in this study focused on the written communication skills of students in solving mixed fraction questions. This quantitative descriptive research was conducted at SMPN 1 Lampasio, Tolitoli Regency, Central Sulawesi with the object of research as many as 15 grade VII students in the odd semester of the 2020/2021 school year. The data collection technique used was the test method to obtain data on the written communication skills of mixed fraction material. Based on the results of the study, it shows that 7% of the 15 research objects have written communication skills, including in the low ability category, 86% in the medium ability category, and 7% in the high ability category. The characteristics of the test results show that students who have written communication skills in the low category generally only remember the material or memorize but are weak in the aspect of understanding the material. Meanwhile, students who have written communication skills in the medium category show that the stages are already able to write answers close to perfect where the direction of the answer structure and solving strategies used is visible, but there are still errors in the accuracy and correctness of the answers. And for students who have written communication skills in the high category show the ability to use mathematical language, the solving strategies used, the accuracy and correctness of answers, and the answer structure is perfect
Selection of low-resistant reservoir rocks in geological cross-section of Helvetian deposits at Letnianske field

The main difficulties that arise in the selection of reservoirs in the geological section of the Helvetian deposits at Bilche-Volytska zone are due to the fact that they are characterized by low values of electrical resistivity. Under such conditions, very often, when interpreting the data of electrical and electromagnetic logging, gas-saturated reservoir rocks are characterized by increasing the penetration of filtrate into the formation and are mistakenly referred to as water-saturated rocks. Based on the analysis results of laboratory studies of the core material and data from geophysical well logging (GWL) in the geological section of Helvetian deposits at Letnianske field, two groups of reservoir rocks were identified. The first group of rocks belongs to the low-resistance, and the second - to the typical quartz sandstones. The formation of groups is due to the difference in electrical, radioactive and neutron attributes of reservoir rocks. According to the results of research it is established that the low resistance of Helvetian reservoir layers is caused by the electronic conductivity of pyrite and chlorite grains, which are part of the cementing material in rocks. Low indications of gamma radiation intensity radiation capture of thermal neutrons for low-resistance rocks are associated with high content of bound water in pyrite and chlorite minerals, and increased radioactivity is due to the content of zircon grains and high adsorption attributes of chlorite and clay masses. In order to increase the reliability of electric and electromagnetic logging data interpretation for the separation of reservoir rocks into typical and low-resistance quartz sandstones, it is proposed to use the comparison of the lateral logging curve (LL) with the normalized neutron gamma-ray logging (NGL) curve. The efficiency of proposed method for dividing reservoir rocks into groups was tested on actual material.
Political Philosophy: The Ethics of Globalization and Scenarios Provides Educational Message to the Society

Roman Ideal of Republic explained the meaning in this way where Cicero excluded black people (race in society), poor people, but in the modern republic we all are included, which guaranteed the republic for all (a shared moral values). The purpose of the topic is to understanding globalization and the proper implementation of its ethics from the Roman Republic to the 20th century’s democracy, violence, human rights etc. based on the theories like consequential and non-consequential. It is an educational philosophy by learning democracy and its openness, its current violent atmosphere, and learning through the artistic politics for a new set-up of philosophic education in the school curriculum. Methodologies have been constructed by academic journals and books. The outcome of the essay helps to find out the problems of ethics in the present scenario and its connection from the era of Cicero, Socrates, Plato, Bentham, Aristotle, and Immanuel Kant. The feature question is do ethical terms implement from the beginning of the republic to the current globalism? If not, how can it be implemented?
Intelligence Offloading and the Neurosimulation of Developmental Agents

Cognitive offloading occurs when environmental affordances expand cognitive capacity while facilitating spatial and social behaviors. Capacity-related constraints are also important, particularly as embodied agents come online during development. Vast differences in brain size and offloading capacity exist across the tree of life. We take from multiple perspectives to understand the proportional contributions of internal models (brain) and externalized processing (offloading) in developing embodied computational agents. As developing nervous systems scale with body size and/or functional importance, offloading is also driven by neural capacity. Cognitive capacity is ultimately determined by various innate and environmental constraints. We propose a similar model for computationally developing cognitive agents. A regulatory model of cognition is proposed as a means to build cognitive systems that interface with biologically-inspired substrates. Multiple tradeoffs result from energetic, innate, and informational constraints, and determine the proportion of internal to external information processing capacity. As growth of a biologically-inspired substrate accelerates or decelerates over developmental time, it changes the acquisitional capacity of the agent. Our agent’s capacity limitations determine externalization potential, which is characterized by three parameters and two mathematical functions. The neurosimulation approach to intelligence offloading can be applied to a broad range of agent-based models and Artificial Intelligences.
Prospects for Using of Digital Technologies in Jewish Epigraphy (the Results of the Sefer Center School on Digital Epigraphy)

In October 2021, the first school on digital epigraphy was held by the Sefer center. During the school, important questions were raised by the participants: how digital methods can help researchers, where they can be applied, what limitations may arise when applying them. At the seminar part, the participants got acquainted with some techniques for data processing - crowdsourcing, visualization, and data analysis using R programming language, regular expressions. During the lecture sessions at the school, such questions were actively discussed, as in which aspects of epigraphy and for what purpose it is appropriate to use certain digital methods, as well as what are the prospects for this direction. The use of digital methods was considered when working with visual, textual data, mapping. Digital methods can help a researcher both at the stage of data collection and primary processing and during academic analysis. However, the use of digital technologies is only a tool though effective, and the main task of the researcher is to ask proper questions that can (or cannot) be answered using one method or another. These and other issues and considerations are briefly summarized in this paper as a summary.
What's in the R-Stars for Korea?

Korea's stars tell of an economy saddled with a real neutral rate (r-star) that has declined significantly in recent decades and is currently below zero.This reflects a significant decline in trend growth, and two large financial crises that triggered significant shifts in the savinginvestment balance.Larger fiscal deficits and frothy financial conditions since 2012 have helped offset rising demand for safer assets, preventing the neutral rate from falling further.Nonetheless, the fall in the neutral rate, coupled with its effects on asset returns, has complicated the task of monetary policy stabilization.Korea's neutral rate is likely to remain low over the medium-term and could fall further, reflecting a structural savings-investment imbalance owing to declining productivity and a rotation in demographics increasing the demand for precautionary saving and convenience yield, and widening the capital risk premia.The COVID pandemic risks magnifying these trends.
Personalizable Vehicle User Interfaces for Better User Experience

In earlier research it has been shown that a personalizable product, one that is flexible and can be tailored to suit the users’ needs, can offer a closer, more emotional and personal attachment to the product that affects the way the product is used and experienced. The possibility to personalize a product can increase both user experience of the product and usability, since unwanted functions and appearance related features can be removed and other features more usable and relevant to the user can be chosen. The objective of this paper is to show that the possibility to personalize a product is beneficial for users emotional responses towards the product. In this paper data from a study that used experience prototyping to study what happens if computerized interface personalization features are brought into the vehicle context. Twenty participants participated in a study, where a personalizable vehicle driver interface prototype was evaluated with a number of methods, for example interviews and Microsoft product reaction cards. The interface prototype was integrated in a high fidelity driving simulator and the participants interacted with the system both while driving the simulator and while standing still in order to be in the right context for increased ecological validity. All of the participants would, to some extent, like to use a system like this in their own cars. The possibility to make a product ones’ own with a personal touch was important for many participants. This makes the users feel better and the product funnier and more entertaining to use. The usefulness and flexibility of the system was the most salient features and about 22% of the words best describing the users experience with the interface were related to their emotional experiences. It can be concluded that personalizable vehicle interfaces can increase both the usefulness and the user experience with the product.
How to Design Great Emotional Experience for Mobile User Interface?

Emotion is easily recognized but difficult to define. For example, emotion has been a famous topic for a long time in user experience (UX) design. However, it has been a question of long standing how to systematically evaluate and design emotion, while maintaining qualitative aspects of emotion (e.g., not-measurable aspects). We developed the systematic tool for emotional UX design, while leaving some room for designer’s creativity. To develop the tool, participants performed various tasks using smartphone, generating both positive and negative emotions. Once people’s emotions were identified, ideal emotional journey, consisting emotional solutions, were created. In order to create ideal emotions, general design principles were proposed. Finally, more specific UX solutions were developed based on general design principles. Some of our UX solutions were applied to design new messenger for smartphone, emotionally augmenting communicating experiences.
Hydrogeological analysis of sulfide tailings at a uranium mine using geophysical and hydrochemical methods

A hydrogeological analysis was conducted of aquifer systems within a sulfide-rich tailings pile and underlying rocks at a uranium mine to understand the generation and transport of AMD.A geophysical investigation was carried out along seven transects spaced 30 m apart using electrical resistivity tomography and a Wenner-Schlumberger array.The results were used as input to 2D and pseudo-3D models of resistivity and chargeability parameters.The geophysical results and models contrasted unaffected saturated zones and zones impacted by AMD, in addition to three areas within the tailings with a high ulfide content.The tailings and underlying fractured bedrock aquifer are hydrologicall connected, which promotes the exchange of mineinfluenced water into the regional aquifer.Releases from the site's tailings and other wastes can severely affect regional groundwater.
Gamma-ray spectrometry signatures of alkaline rocks from the Ponta Grossa Arch, southern Brazil

We present airborne gamma-ray spectrometry signatures of some igneous suites from the Ponta Grossa Arch Alkaline Province (southern Brazil), namely: Bairro da Cruz, Banhadão, Itapirapuã Nepheline syenite, Barra do Itapirapuã Carbonatite, Barra do Teixeira Phonolite, and Mato Preto and Tunas complexes.Gamma-ray spectrometric methods involved analyses of basic, ternary, and ratio maps, thorium-normalized parameters, and sampled data points radioelement concentrations.The results allowed us to verify that all complexes were mainly enriched in eTh.Carbonatite bodies showed the highest contents of eTh and eU.Our findings were consistent with radiometric responses of alkaline bodies and impact the understanding of alkaline provinces in Brazil.
Geophysical analysis of the Curral Homocline and Moeda Syncline junction, Quadrilátero Ferrífero, MG

The Quadrilátero Ferrífero (QFe) has been intensively studied over the last few decades, given its structural complexity and economic importance.For the study, an analysis of geophysical data (magnetometry) of the northwest portion of the QFe was carried out.The study area has an intense structural complexity and is considered a key to better understanding the various and controversial tectonic models proposed for the QFe region.The magnetometry aerial survey databases were compiled and processed for the production of several thematic geophysical maps which were treated in a qualiquantitative analysis, allowing extracting relevant information from subsurface rocks, through 2D inverted profiles and 3D in-depth views of the selected area.Euler deconvolution was performed in a regular grid of profiles in NW-SE direction and profiles coincident with the mapped geological ones.The inverted magnetometric profiles characterized very well the planar structures at the investigated depths and allowed the 3D view of the main fault zones (Curral and Mário Campos faults) that outcrop in the area.The comparison of the results obtained with the adopted model of tectonic development for the region of the junction between the Curral Homocline and the Moeda Syncline is consistent with the structures observed in this study.
The Relevance of Bitcoin to the Regression Theorem: Reply to Pickering

In a recent article, George Pickering (2019) has taken issue with my work regarding the two potential ways one might deal with the regression theorem in light of bitcoin. Specifically, he argues that I misinterpret 'the purpose and requirements of the regression theorem' (p. 608). His critical assessment falls short on both counts.
ImitAL: Learned Active Learning Strategy on Synthetic Data

Active Learning (AL) is a well-known standard method for efficiently obtaining annotated data by first labeling the samples that contain the most information based on a query strategy. In the past, a large variety of such query strategies has been proposed, with each generation of new strategies increasing the runtime and adding more complexity. However, to the best of our our knowledge, none of these strategies excels consistently over a large number of datasets from different application domains. Basically, most of the the existing AL strategies are a combination of the two simple heuristics informativeness and representativeness, and the big differences lie in the combination of the often conflicting heuristics. Within this paper, we propose ImitAL, a domain-independent novel query strategy, which encodes AL as a learning-to-rank problem and learns an optimal combination between both heuristics. We train ImitAL on large-scale simulated AL runs on purely synthetic datasets. To show that ImitAL was successfully trained, we perform an extensive evaluation comparing our strategy on 13 different datasets, from a wide range of domains, with 7 other query strategies.
Rate-Distortion Theory for Mixed States

In this paper we consider the compression of asymptotically many i.i.d. copies of ensembles of mixed quantum states where the encoder has access to a side information system. The figure of merit is per-copy or local error criterion. Rate-distortion theory studies the trade-off between the compression rate and the per-copy error. The optimal trade-off can be characterized by the rate-distortion function, which is the best rate given a certain distortion. In this paper, we derive the rate-distortion function of mixed-state compression. The rate-distortion functions in the entanglement-assisted and unassisted scenarios are in terms of a single-letter mutual information quantity and the regularized entanglement of purification, respectively. For the general setting where the consumption of both communication and entanglement are considered, we present the full qubit-entanglement rate region. Our compression scheme covers both blind and visible compression models (and other models in between) depending on the structure of the side information system.
Statistical exploration of the Manifold Hypothesis

The Manifold Hypothesis is a widely accepted tenet of Machine Learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold, embedded in high-dimensional space. This phenomenon is observed empirically in many real world situations, has led to development of a wide range of statistical methods in the last few decades, and has been suggested as a key factor in the success of modern AI technologies. We show that rich and sometimes intricate manifold structure in data can emerge from a generic and remarkably simple statistical model -- the Latent Metric Model -- via elementary concepts such as latent variables, correlation and stationarity. This establishes a general statistical explanation for why the Manifold Hypothesis seems to hold in so many situations. Informed by the Latent Metric Model we derive procedures to discover and interpret the geometry of high-dimensional data, and explore hypotheses about the data generating mechanism. These procedures operate under minimal assumptions and make use of well known, scaleable graph-analytic algorithms.
Measure Term Similarity Using a Semantic Network Approach

Computing semantic similarity between two words comes with variety of approaches. This is mainly essential for the applications such as text analysis, text understanding. In traditional system search engines are used to compute the similarity between words. In that search engines are keyword based. There is one drawback that user should know what exactly they are looking for. There are mainly two main approaches for computation namely knowledge based and corpus based approaches. But there is one drawback that these two approaches are not suitable for computing similarity between multi-word expressions. This system provides efficient and effective approach for computing term similarity using semantic network approach. A clustering approach is used in order to improve the accuracy of the semantic similarity. This approach is more efficient than other computing algorithms. This technique can also apply to large scale dataset to compute term similarity.
Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution

Deep learning-based single image super-resolution (SISR) approaches have drawn much attention and achieved remarkable success on modern advanced GPUs. However, most state-of-the-art methods require a huge number of parameters, memories, and computational resources, which usually show inferior inference times when applying them to current mobile device CPUs/NPUs. In this paper, we propose a simple plain convolution network with a fast nearest convolution module (NCNet), which is NPU-friendly and can perform a reliable super-resolution in real-time. The proposed nearest convolution has the same performance as the nearest upsampling but is much faster and more suitable for Android NNAPI. Our model can be easily deployed on mobile devices with 8-bit quantization and is fully compatible with all major mobile AI accelerators. Moreover, we conduct comprehensive experiments on different tensor operations on a mobile device to illustrate the efficiency of our network architecture. Our NCNet is trained and validated on the DIV2K 3x dataset, and the comparison with other efficient SR methods demonstrated that the NCNet can achieve high fidelity SR results while using fewer inference times. Our codes and pretrained models are publicly available at \url{https://github.com/Algolzw/NCNet}.