Reviewerly/exHarmony huggingface dataset:
LibGuides: Capturing Sound: A Primer: Home

Recording & producing music has a wide variety of equipment, techniques, and concepts that can be daunting to a novice. This guide will explain these facets, and provide background on music recording and how to learn and improve.
Plate tectonics and volatiles: the nanorock connexion

&amp;lt;p&amp;gt;The global geological volatile cycle (H, C, N) plays an important role in the long term self-regulation of the Earth system. However, the complex interaction between its deep, solid Earth component (i.e. crust and mantle), Earth&amp;amp;#8217;s fluid envelope (i.e. atmosphere and hydrosphere) and plate tectonic processes is a subject of ongoing debate. Here, we want to draw attention to how the presence of primary, pristine melt (MI) and fluid (FI) inclusions in high grade metamorphic minerals could help constrain the crustal component of the volatile cycle. We review the distribution of pristine MI and FI throughout Earth&amp;amp;#8217;s history, from the onset of plate tectonics at ca. 3.0 Ga to the present day. Combined with thermodynamic modelling, our compilation indicates that periods of well-established plate tectonics regimes at 0-1.2 Ga and 1.8-2.0 Ga, might be more prone to the reworking of supracrustal lithologies and the storage of volatiles at lower crustal depths. We then argue that the lower crust might constitute an important, although temporary, volatile storage unit, capable to influence the composition of the surface envelopes through the mean of weathering, crustal thickening, partial melting and crustal assimilation during volcanic activity.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Such hypothesis has implication beyond the scope of metamorphic petrology as it potentially links geodynamic mechanisms to habitable surface conditions. MI and FI in metamorphic rocks is a rich but still relatively uncharted realm. In the near future, a concerted research effort should aim to find and characterize new instances of pristine inclusions in periods of the Earth&amp;amp;#8217;s history currently underrepresented in the inclusion database, e.g. the Boring Billion. The merging of the messages of thousands of minuscule droplets of fluids trapped in the deepest roots of the continental plates will then eventually provide a truly comprehensive portrait of how the Earth&amp;amp;#8217;s evolution proceeds through the geological timescale.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;
Development of students’ creative thinking skills by means of traditional art

Traditional art as a guarantee for the preservation of national foundations of the society, opposing its teaching potential to the crises of contemporary society and popular culture which contributes to the targeted person through the "language" of human emotions, the complexity and subtlety of expression, which is directly connected with the development of students’ creative thinking skills. Until now, there has been no holistic view of traditional art as a factor in the development of students’ creative thinking skills. The identification of potential of traditional art in the students’ creative thinking skills development will create preconditions for further development of vocational and personal problems of the teacher's personality, who is able to examine and learn new information and adopt unconventional creative solutions, conceptual and factual understanding of the problem, undoubtedly, enrich pedagogical science with new knowledge of the essential characteristics of forms and methods of using the traditional art as a a major factor in the development of students’ creative thinking skills.
Cheating with (Recursive) Models

To what extent can misspecified models generate false estimated correlations? We focus on models that take the form of a recursive system of linear regression equations. Each equation is fitted to minimize the sum of squared errors against an arbitrarily large sample. We characterize the maximal pairwise correlation that this procedure can predict given a generic objective covariance matrix, subject to the constraint that the estimated model does not distort the mean and variance of individual variables. We show that as the number of variables in the model grows, the false pairwise correlation can become arbitrarily close to one, regardless of the true correlation.
Binocular Stereo Vision and Modified DBSCAN on Point Clouds for Single Leaf Segmentation

Nowadays, the task of segmenting individual leaves is essential in some specific computer vision applications, for instance the recognition and localization of plant leaves in agricultural robotic applications. Compared with 2D-image-based algorithms, the segmentation algorithms dealing with 3D point clouds of plants always have higher performance in these tasks due to the utilization of depth information, which provides more intuitive but powerful features for distinguishing and separating individual leaves. In this paper, we propose a real-time sparse stereo match algorithm which combines two basic cost functions, sum of absolute differences (SAD) and zero-mean normalized cross-correlation (ZNCC) and generates multiple depth hypotheses. However, the reconstructed sparse point clouds are corrupted by a noticeable amount of noise because of the extremely weak texture of leaves. Then, we denoise the raw point clouds and evaluate the affinities between points using Tensor Voting, which is a well-known algorithm for inferring underlying structure of sparse and noisy data. Finally, a modified density-based spatial clustering of applications with noise (DBSCAN) algorithm based on the above new-defined distance metric is used to cluster the refined point clouds. Individual leaves can be represented by these clusters. Experiments on simulation and real sceneries show that the proposed algorithm could be able to segment individual leaves well. This algorithm is the core algorithm of tea leaves localization of our self-developed tea picking robot.
Optimization of universal quantum gates with higher-dimensional spaces

Minimizing the number of necessary two-qubit gates is an important task in quantum information processing. By introducing non-computational quantum states, we construct effective circuits for the controlled-NOT (CNOT) gate and the n-qubit Toffoli gate with (2n-3) qubit-qudit gates and (2n-4) single-qudit gates. The cost of a three-qubit Toffoli gate is reduced from the minimum limit of five two-qubit gates to three nearest-neighbor qubit-qudit gates. By operating with the spatial-mode degree of freedom, polarization CNOT and Toffoli gates are designed with linear optics. Our optical schemes can be achieved with a higher success probability and no extra auxiliary photons are needed in the scheme.
A STUDY ON STUDENTS’ MOTIVATION TOWARDS LEARNING ENGLISH LANGUAGE: A CASE STUDY OF ONE SENIOR HIGH SCHOOL IN PEKANBARU

Motivation is the main point to determine the students’ desire to learn English. Students’ motivation will be correlated with their performance and achievement during the learning process. The research aimed to find out students’ motivations in learning English and the kinds of motivations they have. The respondents of this study were sixty two third-grader students of senior high school in Pekanbaru. This study used quantitative and descriptive method where the information delivered based on the actual condition. A questionnaire that consists of twenty-five questions and open-enede questions was delivered to the students. The answers of the respondents were analyzed and computed to find out the mean valaue of each kind of motivation. Based on the result of the study, it is found that the students have high motivation to learn English. They want to be able to communicate fluently, to understand reading materials and to get better job in the future. However, the students do not neglect the aim of learning English at school is to pass the examination. The teachers are suggested to encourage students to focus on their improvement, not only grade or examination.
Perbedaan tingkat daya juang dan motivasi berprestasi siswa ditinjau dari pendapatan orang tua saat pembelajaran daring selama pandemi COVID-19

: This study aims to determine the description and differences in fighting power and achieve- ment motivation of Junior High School in terms of their parents' income. This research uses quantitative methods with a comparative study. Data collection was carried out by means of a questionnaire to 164 students of   junior high school. The results of this study indicate that the level of fighting power of stu- dents is mostly at a high level of fighting power of 50.6%. In addition, it was also found that the level of student achievement motivation was mostly at the high achievement motivation level of 45.1%. The re- sults of the unpaired t test show that there is a significant difference in the fighting power of students and the achievement motivation of students whose parents have high income and those who have low income during online learning during the COVID-19 pandemic.
LibGuides: Graphic Novels & Manga: A General Guide: How to Read Graphic Novels & Manga

Final project submission for INFO 287-13 [Ellyssa Valenti] Spring 2020 Easy instructions to read any graphic novel and manga
Towards Unpaired Depth Enhancement and Super-Resolution in the Wild.

Depth maps captured with commodity sensors are often of low quality and resolution; these maps need to be enhanced to be used in many applications. State-of-the-art data-driven methods of depth map super-resolution rely on registered pairs of low- and high-resolution depth maps of the same scenes. Acquisition of real-world paired data requires specialized setups. Another alternative, generating low-resolution maps from high-resolution maps by subsampling, adding noise and other artificial degradation methods, does not fully capture the characteristics of real-world low-resolution images. As a consequence, supervised learning methods trained on such artificial paired data may not perform well on real-world low-resolution inputs. We consider an approach to depth map enhancement based on learning from unpaired data. While many techniques for unpaired image-to-image translation have been proposed, most are not directly applicable to depth maps. We propose an unpaired learning method for simultaneous depth enhancement and super-resolution, which is based on a learnable degradation model and surface normal estimates as features to produce more accurate depth maps. We demonstrate that our method outperforms existing unpaired methods and performs on par with paired methods on a new benchmark for unpaired learning that we developed.
Intervenções de enfermagem no pós-operatório de revascularização do miocárdio: revisão sistemática da literatura

Introduction: Cardiovascular diseases affect a large part of the world population, and many times, coronary artery bypass grafting becomes necessary. This procedure has risks and possible complications that the nurse must be aware of to prevent and intervene. Objective: To discuss the main nursing interventions in the postoperative period of coronary artery bypass grafting in adult patients evidenced in the literature. Methodology: This is a systematic review, which used PRISMA as a guiding instrument, registered in PROSPEROCRD42020150912. Included are the works that answer the question Which nursing interventions are evidenced in the postoperative of coronary artery bypass grafting in adult patients?, using as a search source the databases PubMed (Search resource provided by the National Center for Biotechnology Information), VHL (Virtual Health Library), Scopus (Database of abstracts and citations of literature with peer review, provided by the company Elsevier), Web of Science (Clarivate Analytics) and CINAHL (Cumulative Index to Nursing and Allied Health Literature). Results: After the analysis and selection process, 06 studies were selected, tabulated and arranged in category. This study identified the main nursing interventions in the postoperative period of coronary artery bypass grafting in adult patients, evidenced in the literature. They were distributed in four categories: (01) Patient orientation/education, (02) Postoperative complications, (03) Pain management and (04) Care protocol. Discussion: This study identified the main nursing interventions in the postoperative period of coronary artery bypass grafting in adult patients, evidenced in the literature. The category 01, orientation/education to the patient undergoing coronary artery bypass grafting, included the studies E2 and E6, which understand the process of patient orientation. Category 02 encompassed the articles E3 and E5, on the complications present in the postoperative period of CABG. On the other hand, in category 03 pain management, the E4 study noted the frequency of pain in the postoperative period of heart surgery and therefore the importance of its identification. Finally, the category 04 Assistential Protocols, comprises the effectiveness of the use of assistential protocols, reinforcing the effectiveness of the implementation of nursing care. Conclusion: Facing the patient in the postoperative period of CABG, the nurse has a possibility of comprehensive action, especially if he takes advantage of the assistential systematization to implement his interventions. Being able to benefit not only the patient's prognosis, but also the effectiveness of the responsible health team.
Student digital SRW-club

Modern conditions for remote communication and learning have entailed the spread of digital technologies, when teachers are actively involved in the process of searching for new knowledge and mastering effective digitalization tools. Responding to modern challenges, the authors propose to create on the basis of KazNPU named after Abai «Student digital SRW-club», the purpose of which is to stimulate research and educational activities of students, cultivate students’ enthusiasm, form critical thinking and leadership skills, skills of creative activity, work in a team. The project «Student digital research club» is based on remote scientific activities and gamification elements that will allow students to instill interest in research work. The novelty of the project is that for the first time at a qualitatively new level, an attempt is made to modernize the process of the research process for university students. The work is promising, since through the creation of innovative methods, the competitiveness of the training of domestic teaching staff is increased.
Mensuração de ansiedade e otimismo em pacientes cardíacos

O presente trabalho e fruto de relatorio de pesquisa desenvolvida durante o Programa Institucional de Bolsas de Iniciacao Cientifica (PIBIC) no ano de 2016/2017 sobre a pesquisa para investigar a relacao existente entre a ansiedade e o otimismo em pacientes com diagnostico de Doenca Arterial Coronariana (DAC) e pacientes sem DAC obstrutiva. Para tal pesquisa utilizamos a aplicacao dos testes Inventario de Ansiedade de Greenberger e Padesky (1995) e o Teste de Orientacao da Vida-R (TOV –R, 2002) em pacientes do Hospital Universitario Francisca Mendes, Manaus – AM. Os sujeitos da pesquisa foram divididos em grupo controle e grupo teste; buscando observar os indices de sentimentos positivos nos grupos participantes, como tambem ansiedade elevada. A pesquisa demonstrou que os pacientes ambulatoriais (grupo controle) apresentavam niveis graves de ansiedade em apenas 6% da amostra, enquanto na enfermaria essa mesma classificacao representava 15% da populacao. Os niveis de otimismo mostraram-se altos nas duas populacoes. Enquanto no ambulatorio 75% dos pacientes consideraram-se otimistas, na enfermaria 56% classificou-se da mesma forma. Palavras – Chave: Psicologia Positiva; Ansiedade; Otimismo; Cardiacos. Abstract – This existing paper is the result of an research report conducted during the Institutional Program of Cientific Iniciation Schoolarships (PIBIC) over 2016/2017 about a study to investigate the connexion between anxiety and optimism in patients diagnosed with Coronary Artery Disease (DAC) and without DAC. For said reseach we applied Greenberger and Padesky’s Anxiety Inventory (1995) and the Life-R’s Orientation Test (TOV –R, 2002) in patients from the University Hospital Francisca Mendes, Manaus – AM. The subjects were split in control group and test group; seeking to observe positive feelings rates among the participants , and also high anxiety levels. The study demonstrated that just 6% of ambulatory patients (control group) showed severe levels of anxiety, while infirmary patients from this same category represented 15% of their peers. Optmism levels displayed themselves higher in both populations. Whilst in the ambulatory 75% patients considered themselves optimistic, in the infirmary 56% thinks the same. Keywords: Positive Psychology; Anxiety; Optimism; Heart.
TRACE: A Differentiable Approach to Line-level Stroke Recovery for Offline Handwritten Text

Stroke order and velocity are helpful features in the fields of signature verification, handwriting recognition, and handwriting synthesis. Recovering these features from offline handwritten text is a challenging and well-studied problem. We propose a new model called TRACE (Trajectory Recovery by an Adaptively-trained Convolutional Encoder). TRACE is a differentiable approach that uses a convolutional recurrent neural network (CRNN) to infer temporal stroke information from long lines of offline handwritten text with many characters and dynamic time warping (DTW) to align predictions and ground truth points. TRACE is perhaps the first system to be trained end-to-end on entire lines of text of arbitrary width and does not require the use of dynamic exemplars. Moreover, the system does not require images to undergo any pre-processing, nor do the predictions require any post-processing. Consequently, the recovered trajectory is differentiable and can be used as a loss function for other tasks, including synthesizing offline handwritten text. We demonstrate that temporal stroke information recovered by TRACE from offline data can be used for handwriting synthesis and establish the first benchmarks for a stroke trajectory recovery system trained on the IAM online handwriting dataset.
The structure of signal space: &amp;#160;a case study of direct mapping between seismic waveforms and event distribution

&amp;lt;p&amp;gt;Under special circumstances, waveform observations of seismic events related by a common, spatially-distributed source process exhibit a geometric architecture that is a distorted image of event distribution in the source region.&amp;amp;#160; We describe a prescription for visualizing this signal space image and use a machine-learning algorithm, Isomap, and an algorithm due to Menke to invert collections of waveforms directly for relative event location.&amp;amp;#160; We illustrate concepts and methods with well-characterized induced seismicity at a coal mine in the U.S. state of Utah observed by two local seismic instruments, and with synthetics.&amp;amp;#160; We anticipate application of these methods to repetitive volcanic seismicity, icequakes and induced seismicity.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This is Lawrence Livermore National Laboratory contribution LLNL-ABS-818445.&amp;lt;/p&amp;gt;
Phishing Website Detection Using Hybrid Multi-Feature Classification

Phishing is stealing sensitive information from users like, passwords, usernames, & debit/credit card details in a fraudulent way. Detection and Classification of such Phishing Websites are generally inefficient due to Low Accuracy rate and High False Positive rate with Novel Phishing Techniques. Hence, the need for development of Hybrid Multi-Feature based Prediction and Classification System plays a vital role in Preventing and Safeguarding users from online theft, fraud, and espionage. The Proposed System consists of Hybrid Prediction model using Random Forest and Logistic Regression Algorithms which are used in the Prediction of Phishing URLs more efficiently. A Decision Algorithm Module is used to check for URL/Domain feature-based detection which is incorporated with an URL Feature Classification model which uses XGBoost for classifying the Phishing URL based on the Domain based Features, HTML & Javascript based Features and Address Bar based Features of the URLs. The Hybrid system would detect phishing URLs more efficiently.
Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification

In recent years, the availability of digitized Whole Slide Images (WSIs) has enabled the use of deep learning-based computer vision techniques for automated disease diagnosis. However, WSIs present unique computational and algorithmic challenges. WSIs are gigapixel-sized ($\sim$100K pixels), making them infeasible to be used directly for training deep neural networks. Also, often only slide-level labels are available for training as detailed annotations are tedious and can be time-consuming for experts. Approaches using multiple-instance learning (MIL) frameworks have been shown to overcome these challenges. Current state-of-the-art approaches divide the learning framework into two decoupled parts: a convolutional neural network (CNN) for encoding the patches followed by an independent aggregation approach for slide-level prediction. In this approach, the aggregation step has no bearing on the representations learned by the CNN encoder. We have proposed an end-to-end framework that clusters the patches from a WSI into ${k}$-groups, samples ${k}'$ patches from each group for training, and uses an adaptive attention mechanism for slide level prediction; Cluster-to-Conquer (C2C). We have demonstrated that dividing a WSI into clusters can improve the model training by exposing it to diverse discriminative features extracted from the patches. We regularized the clustering mechanism by introducing a KL-divergence loss between the attention weights of patches in a cluster and the uniform distribution. The framework is optimized end-to-end on slide-level cross-entropy, patch-level cross-entropy, and KL-divergence loss (Implementation: this https URL).
Using fuzzy c-means algorithm to cluster human development index

Human Development Index (HDI) plays an important role in the development of a modern economy, in line with proper human development will enable the production factors to be maximized. The Human Development Index (HDI) which consists of three components, consists of life expectancy, the level of education measured by a combination of the adult literacy rate and the average length of schooling and an adequate standard of living is measured by the adjusted per-capita expenditure. Long story short, this paper will examine HDI in Aceh Province, Indonesia and create clusters using fuzzy C means Manhattan distance. The results obtained are this method can form 4 clusters with an accuracy of 82.75%.
Verification and communication of the scientific quality of operational oceanography products of the Copernicus Marine Service

&amp;lt;p&amp;gt;The &amp;lt;strong&amp;gt;Copernicus Marine Environment Monitoring Service (CMEMS)&amp;lt;/strong&amp;gt; is delivering ocean satellite observations, in situ observations, together with ocean model reanalyzes, analyzes and forecasts from a unique web portal (Le Traon et al, 2019, https://doi.org/10.3389/fmars.2019.00234). Each one of these products is evaluated before its entry into service, and its quality is documented in a Quality Information Document (QUID). This information is complemented by regular quality metrics updates on the CMEMS website. Due to a relatively sparse observation network, in particular in subsurface, it is still a challenge to propose meaningful uncertainty estimates and forecast skills to the operational oceanography user&amp;amp;#8217;s community. In order to improve, and better target the scientific quality information provided to the various types of CMEMS users, several developments are ongoing which will be described in this presentation.&amp;lt;/p&amp;gt;