Reviewerly/exHarmony huggingface dataset:
Balsa: A Compact Line Notation Based on SMILES

Despite its widespread use, Simplified Molecular Input Line Entry System (SMILES) remains underspecified. The lack of a detailed specification encourages improvisation by software developers, complicates data standardization efforts, and undermines extension development. Balsa, a reformulation of SMILES, addresses these problems. A formal, machine- readable grammar defines Balsa’s syntax. Semantics are described at three levels of resolution: constitution; configuration; and conformation. To estimate the compatibility of Balsa strings with SMILES software, all differences between the two languages were enumerated. To the extent that SMILES documentation is unambiguous, every difference was consistent with Balsa being a language subset.
SKRINING TUMBUH KEMBANG ANAK PADA SISWA KB INTAN PERMATA AISYIYAH MAKAMHAJI

Background: The golden period of growth and development of children occurs at the age of 0 to 6 years. Deviations in child growth and development needs to be detected so that intervention or stimulation can be given. Early detection (screening) of deviations in child development can be done using the DDST II (Denver Development Screening Test) method. KB Terpadu Intan Permata Aisyiah Makamhaji has slowly returned to using the face-to-face learning system. However, efforts to monitor the growth and development of the students have not been implemented yet. Objective: To obtain demographic information about the growth and development of students in KB Terpadu Intan Permata Aisyiah Makamhaji. Methods: Screening for the growth and development of students of KB Terpadu Intan Permata Aisyiah Makamhaji was carried out in 2 stages. The first stage is measuring the child's growth rate through measuring their weight and height to determine their BMI and adjusted for age. The second stage is the measurement of children's developmental achievements using the DDST II form and tool set. Results: Measurement of growth rate obtained 85% of students have very thin nutritional status and only 0.05% are classified as normal nutritional status. Measurement of developmental achievement found that 90% of students had normal development, while others were considered suspicious and unstable. The gross motor aspect is one aspect in which most students are considered advanced.Conclusion: The growth rate of students in KB Terpadu Intan Permata Aisyiah Makamhaji is still not in accordance with the age level, while the achievement of their development is quite good
Visuomotor control of 3D circular tracking movement in a virtual reality space

PurposeThe progress of learning human movements and motor control mechanisms by observing and imitating human movements was based on visuomotor control in three-dimensional (3D) space.However, previous studies of motion control in 3D space have focused on analyzing tracking tasks along 1D lines or 2D planes using single or multi-joint movements.In this study, we propose a visuomotor system for quantitatively evaluating visuomotor control in a 3D space based on virtual reality (VR) (Choi ( 2018)).The proposed system has been designed to analyze 3D circular tracking motions on frontal and sagittal planes of VR space.Furthermore, we analyzed two types of 3D target tracking tasks to verify the effectiveness of our system, the 3D circular tracking movements from the frontal plane to the body and the circular tracking movements from the sagittal plane to the body.In addition, we compared visuomotor control in 3D circular tracking motion between monocular without depth and binocular vision with depth.Method The system allowed users to conduct the 3D visually-guided tracking movement in the 3D VR space (Figure 1).We established the size of the 3D target as 1.5 times larger than the 3D tracer in this research.The 3D target has a red ball with a radius of 1.5 cm.The 3D tracer has a yellow ball with a radius of 1 cm placed at the tip of the 3D stick.Instead of users' own hands in VR space, the hands were shown the 3D stick.Each task was carried out with the 3D target rotating on the frontal plane (ROT0 in Figure 1(A)) and on the sagittal plane (ROT90 in Figure 1(B)).We transformed the data of the X, Y, and Z to "R" displacement, "θ" angular displacement, and "ω" angular velocity on polar coordinates.We analyzed the differences of 3D circular tracking movements based on the parameters of ΔR, Δθ, and Δω in VR space (Choi ( 2020)).Results and Discussion We developed a system that allows users to quantitatively evaluate visuomotor movement based on 3D target tracking in a 3D virtual reality space.It is verified that 3D visuomotor control under monocular and binocular conditions could be analyzed quantitatively.We found that the tracking system is more useful to adopt the parameters of Δθ, and Δω to analyze the circular tracking movement with increasing speed.In addition, we also found that the parameter of ΔR was not suitable for the analysis of low-speed movement.When tracking movement, we also found that the visual dependence was large and had a great influence on the accuracy of the movement.The proposed system can be useful for assessing the severity of the disease and the rehabilitation of people with hemiplegic upper arms.The proposed system can also quantitatively measure the performance of the visuomotor control system of aging adults and create a database of the visuomotor control.This study will contribute to a basic research to analyze the changes of the visuomotor control system that occur with aging and to present an appropriate motor learning model for aging adults.
Controllable Question Generation with Semantic Graphs

Generating questions from answers and articles is an interesting and difficult task.Recent works have mostly focused on quality of generating a single question from a given article.However, question generation is not only a one-to-one problem that maps an article to one single question, because everyone may focus on different parts of the article and ask different questions accordingly.This makes the diversity of generated questions equally important with the quality.In this paper, we discuss the quality and diversity of question generation, and propose a controllable question generation model to improve these two aspects.Specifically, we associate the article with the dependencies parse tree and merge it with the article by constructing different triples.Secondly, because triples are different, we can generate different questions based on different triples and articles.By selecting different triples, we can control the content of generated questions and improve both the quality and the diversity.Experiment results on the SQuAD dataset show that our proposed method can significantly improve the diversity of generated questions, especially from the perspective of using different question types.Compared with the existing methods, our model achieves a better trade-off between the quality and diversity of generated questions, and we can generate diverse questions in a more controlled way.
Alternatives selection to control the impact of unlicensed sand mining at Batur Global Geopark using Analytical Hierarchy Process

Based on the problem of unlicensed sand mining at the Batur Global Geopark, research is needed on controlling the impact of unlicensed sand mining in terms of environmental, social, and economic dimensions, in the Batur Global Geopark area.This study uses the analytical hierarchy process (AHP) method to choose alternative impact control on illegal sand mining at Batur Global Geopark.This study uses assessments from 12 stakeholders.The five AHP criteria in this study are; Increase people's income; Contribute to regional development tax; Simplify the mining permit process; Increase other job opportunities; Minimize the risk of environmental damage; and Repairing environmental damage; while the three alternatives in this study are; Partnership program; Granting community mining permits with relatively simple concepts and obligations; and Closing and providing sanctions in accordance with law.The highest weight of the overall value of all criteria is the partnership program.
A Comprehensive Analysis of Deep Learning's Impact on Natural Language Processing

The application of deep learning (DL) models has become significantly more widespread in recent years, which has facilitated significant development in the field of natural language processing (NLP).Through the enhancement of verbal interactions between humans and computers, NLP makes intelligent robots possible.The need for data-driven automation of semantic analysis has increased in response to recent advancements in processing capability as well as the appearance of enormous quantities of linguistic data.The enormous advancements made by deep learning techniques in the fields of computer vision, automatic speech recognition, and NLP have contributed to the widespread acceptance of data-driven initiatives.In this paper, NLP applications that can benefit from deep learning are classified.It highlights fundamental NLP tasks and applications, in addition to the ways in which deep learning might improve those jobs and applications.In our analysis, we compare various tactics to various modern models.
An Explainable Deep Network Framework with Case-based Reasoning Strategies for Survival Analysis in Cancer

Abstract Survival analysis has currently become an essential statistical research hotspot that models the time-to-event information with data censorship handling. Such technique yields extensive applications in carcinoma treatment and prediction. Deep neural networks (DNNs) also exhibit unusual appeal for survival analysis because of their non-linear nature. However, DNNs are often described as “black box” models. A black box model is a model that is extremely hard or practically impossible to explain. In this study, we propose an explainable deep network framework for survival prediction in cancer. We utilize the strategy of the nearest distance retrieval in case-based reasoning (CBR) to provide useful insights into the inner workings of the deep network. First, we use an autoencoder network to reconstruct the features of a training input. We create a prototype layer, which can store the weight vector following the encoded input and to receive the output from the encoder. In this deep survival model network, the total loss function consists of four terms: the negative log partial likelihood function of the Cox model, the autoencoder loss, and two interpretability prototype distance terms. We use an adaptive weights approach to combine the four loss terms. The network that the prototype layer learns during training naturally comes with an explanation for each prediction. We also introduce Shapley Additive Explanation (SHAP) values to explain each feature importance that significantly contributes to the model’ predictions. This study employs cross-validation and the concordance index for assessing the predicting effect. Stringent cross-verification testing processes on two cancer methylation data sets demonstrate that the developed approach is effective.
A Study on Various Common Denoising Methods on Chest X-ray Images

Image 'denoising' is an important pre-processing step as noise affects the image quality. The behaviors of denoising algorithms have been examined on a set of 2D Chest X-ray (CXR) images. Both the 'Linear' and 'non-Linear' denoising methods are considered, each having two techniques, such as (i) Moving average and (ii) Gaussian under the Linear method, and (iii) Median and (iv) Bilateral under the non-Linear method, respectively. Noise variance and Signal-to-Noise Ratio (SNR) are computed on the raw images. The study finds that, Median filter is the best of the lot with the PSNR mean = 34.5213; PSNR σ = 0.9618; MSE mean = 12.2337; MSE σ = 1.5491; and Big(O) = 0.02873 milliseconds. Finally, a comparative study has been made among these denoising methods to predict five hundred Tubercular CXRs, which shows that, using the Median filter, 92% CXRs can be accurately diagnosed, followed by Gaussian, Bilateral, and Moving average type filters with the respective accuracies of 80%, 72%, and 60%, respectively. This work could be a ready-reckoner to the researchers in choosing the best filtering technique when working on Medical X-ray images.
Two-stage low-light image enhancement method based on generating saturation-corrected reference images

Abstract The saturation information of the image is given less consideration by the existing low-light enhancement methods, which causes color distortion throughout the improvement process. We propose a two-stage low-light image enhancement method based on generating saturation-corrected reference images to address the issues of inadequate illumination improvement of existing low-light images and distortion of color information during illumination enhancement and obtain well-illuminated, clear, and color information-rich enhancement results. In our proposed method, the illumination component in the HSV color space is enhanced using the SVD decomposition after the original color image is first converted into the HSV color space. To improve the saturation component in the saturation channel in HSV color space, a saturation correction is used. In order to get our saturation-corrected photos, we then merge the original hue channel with the modified value channel and saturation channel. The original low-light image is then optimized via gradient descent using the saturation-corrected image as the reference image. It is important to note that each pixel point's gradient descent step size is determined by the luminance weights. The method can better express details, boost brightness, and return more natural colors in various situations and tones, according to qualitative and quantitative test findings
Knowledge-Based Green’s Kernel for Support Vector Regression

&lt;p&gt; This paper presents a novel prior knowledge-based Green's kernel for support vector regression (SVR). After reviewing the correspondence between support vector kernels used in support vector machines (SVMs) and regularization operators used in regularization networks and the use of Green's function of their corresponding regularization operators to construct support vector kernels, a mathematical framework is presented to obtain the domain knowledge about magnitude of the Fourier transform of the function to be predicted and design a prior knowledge-based Green's kernel that exhibits optimal regularization properties by using the concept of matched filters. The matched filter behavior of the proposed kernel function makes it suitable for signals corrupted with noise that includes many real world systems. We conduct several experiments mostly using benchmark datasets to compare the performance of our proposed technique with the results already published in literature for other existing support vector kernel over a variety of settings including different noise levels, noise models, loss functions, and SVM variations. Experimental results indicate that knowledge-based Green's kernel could be seen as a good choice among the other candidate kernel functions. &lt;/p&gt;
Adaptive Update Handling for Graph HTAP

Abstract Hybrid transactional/analytical processing (HTAP) workloads on graph data can significantly benefit from GPU accelerators. However, to exploit the full potential of GPU processing, dedicated graph representations are necessary, which mostly make in-place updates difficult. In this paper, we discuss an approach for adaptive handling of updates in a graph database system for HTAP workloads. We discuss and evaluate strategies for propagating transactional updates from an update-friendly table storage to a GPU-optimized sparse matrix format for analytics.
Heavy Metal Contamination Index, Metal Index and Polycyclic Aromatic Hydrocarbon Content of Ochani River in Ogoni, Rivers State, Nigeria

The Heavy metal Pollution Index (HPI), Metal Index (MI) and the Polycyclic Aromatic Hydrocarbon (PAH) contents of crude oil-polluted Ochani River in Ejamah-Ebubu community were investigated using physicochemical properties, Heavy Metal Analytic Method (AAS), GC-MS method and heavy metal pollution model. The results showed that Ochani River sampling station 2 (ORPS 2) had highest values of temperature, conductivity, turbidity, total solid (TS), total dissolved solid (TDS), Total Suspended Solid (TSS), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and nitrates with values as (32oC, 260 µScm-1, 42NTU, 460 mg/L, 526 mg/L, 400 mg/L, 15 mg/L, 10 mg/L, 25 mg/L and 7.5 mg/L respectively) compared to Ochani River sampling station 1 (ORPS 1) with values as (30oC, 200 µScm-1, 38NTU, 400 mg/L, 500 mg/L, 380 mg/L, 13 mg/L, 9.0 mg/L, 22 mg/L and 6.8mg/L respectively). However, these values of ORPS 1and 2 were higher than the unpolluted water sample (UWS) and WHO standard limits. Heavy metals obtained in Ochani River were rankedas Fe &gt; Cu &gt;Pb&gt; Zn &gt; Cr &gt; Cd &gt;As. The values obtained from crude oil polluted water samples were highest when compared with the values obtained of the UWS and WHO standard limit. The heavy metal pollution index of Ochani River was calculated as 402.32 mg/L which was higher compared with the critical pollution index value of 100. The metal index obtained was 49.88mg/L showing that the water quality classified to be seriously polluted. The Polycyclic Aromatic Hydrocarbon (PAH) components present in Ochani River include fluorene, naphthalene, dibenzyl(a,h)anthracene, benzo(k)fluoranthene and benzo(a)pyrene. However, these values of PAH components obtained were highest in ORPS 2 compared to ORPS 1. No PAH content was detected in UWS. However, the values of PAH obtained in both ORPS 1 and 2 were higher compared with WHO standard limit. In conclusion, Ochani River which is an important river used for irrigation and domestic activities by the populace in that community, is highly polluted with heavy metals and carcinogenic PAHs. We therefore recommend that Ochani River is unsafe for drinking, domestic and agricultural activities of the community where it is sited.
PENYUSUNAN LAPORAN KEUANGAN BERBASIS SYSTEM MELALUI PEMANFAATAN SOFTWARE ACCURATE V5 BAGI SISWA SMK SATRIA DI WILAYAH SRENGSENG JAKARTA BARAT

The increasingly rapid development of Technology and Communication (ICT) in the era of the industrial revolution 4.0 brought changes in all lines of activity. This development changed the social order which initially used the old (conventional) method into new, more technology-based methods. Information technology has changed the accounting process from traditional accounting to information technology accounting. One of the technological and communication developments that occur in the learning process is the preparation of financial reports that previously used manuals to become system-based, namely by using accounting software. Accurate V5 accounting software training can provide benefits for Satria Vocational School students in improving learning and competence in compiling financial reports for service, trading and manufacturing companies using Accurate V5 software. The aim of this training is for Satria Vocational High School students to understand and use Accurate V5 accounting software well. After this activity students are expected to be able to improve learning and competence in the field of accounting in compiling financial reports quickly and accurately using Accurate v5 accounting software so that they can compete with graduates from other schools in the world of work. Overall, the trainees understand the material presented and can use accounting software (Accurate v5) well in preparing financial reports. The activity went well and the participants were actively discussing&#x0D; Keywords: accurate v5 training, SMK Satria, Srengseng
Exploring the Role of Language Families for Building Indic Speech Synthesisers

&lt;p&gt;Building end-to-end speech synthesisers for Indian languages is challenging, given the lack of adequate clean training data and multiple grapheme representations across languages. This work explores the importance of training multilingual and multi-speaker text-to-speech (TTS) systems based on language families. Such a study is crucial not only from a low resource perspective but also to reduce the overall consumption of computing power. &lt;/p&gt; &lt;p&gt;TTS systems are trained separately for Indo-Aryan and Dravidian language families, and their performance is compared to that of a combined Indo-Aryan+Dravidian voice. We also investigate the amount of training data required for a language in a multilingual setting. We want to see if we can do more with less data without compromising the quality and intelligibility of the synthesised speech. The voices are easily extendable to new languages with limited data. Same-family and cross-family synthesis and adaptation to new languages are analysed. The analyses show that language family-wise training of Indic systems is the way forward for the Indian subcontinent, where a large number of languages are spoken.&lt;/p&gt; &lt;p&gt;&lt;br&gt;&lt;/p&gt;
Human-as-a-Robot Performance in Augmented Reality Teleultrasound

&lt;p&gt; &lt;strong&gt;Purpose:&lt;/strong&gt; In “human teleoperation” [1], augmented reality (AR) and haptics are used to tightly couple an expert leader to a human follower. To determine the feasibility of human teleoperation, we quantify the abil- ity of humans to track a position and/or force trajectory via AR cues. The human response time, precision, frequency response, and step response were characterized, and several rendering methods were compared. &lt;/p&gt; &lt;p&gt;&lt;strong&gt;Methods:&lt;/strong&gt; Volunteers (n=11) performed a series of tasks as the fol- lower in our human teleoperation system. The tasks involved tracking pre-recorded series of motions and forces, each time with a different rendering method. The order of tasks and rendering methods was ran- domized to avoid learning effects and bias. The volunteers then performed a series of frequency response tests and filled out a questionnaire. &lt;/p&gt; &lt;p&gt;&lt;strong&gt;Results:&lt;/strong&gt; Rendering the full ultrasound probe as a position target with an error bar displaying force led to the best position and force tracking. Following force and pose simultaneously was more difficult but did not lead to significant performance degradation versus following one at a time. On average, subjects tracked positions, orientations, and forces with rms tracking errors of 6.2 ± 1.9 mm, 5.9 ± 1.9˚, 1.0 ± 0.3 N, steady-state errors of 2.8 ± 2.1 mm, 0.26 ± 0.2 N, and lags of 345.5 ± 87.6 ms respectively. Performance decreased with input frequency, until the person could no longer follow, depending on the input amplitude. &lt;/p&gt; &lt;p&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; This paper characterizes human tracking ability in aug- mented reality human teleoperation, which shows the system’s feasi- bility and good performance, and is important for designing future human computer interfaces using augmented and virtual reality. &lt;/p&gt;
The Discourse Power of Anti-corruption in the Internet Age

The practice of anti-corruption discourse in the Internet age has broken through the philosophical proposition of Foucault's "Power is saying", and the right interpretation paradigm of discourse has sprung up.The openness of the Internet has given the two discourse systems of anti-corruption power and rights an opportunity to be present, but both present a binary deviation of seriousness and entertainment, and at the same time they are separated from institutional evaluation.Based on structural balance, discourse power should be given more specific institutional arrangements and greater space for speech, while discourse power should be reduced accordingly.The effectiveness of anti-corruption in the Internet age depends on the negotiation rationality of the two voices and the institutional transformation on this basis.