Reviewerly/exHarmony huggingface dataset:
Nonboolean Conditionals

On standard analyses, indicative conditionals behave in a Boolean fashion when interacting with and and or. We test this prediction by investigating probability judgments about sentences of the form "If A, then B {and, or} if C, then D". Our findings are incompatible with a Boolean picture. This is challenging for standard analyses of ICs, as well as for several nonclassical analyses. Some trivalent theories, conversely, may account for the data.
Corpus evidence for the role of world knowledge in ambiguity reduction: Using high positive expectations to inform quantifier scope

Every-negation utterances (e.g., Every vote doesn’t count) are ambiguous between a surface scope interpretation (e.g., No vote counts) and an inverse scope interpretation (e.g., Not all votes count). Investigations into the interpretation of these utterances have found variation: child and adult interpretations diverge (e.g., Musolino 1999) and adult interpretations of specific constructions show considerable disagreement (Carden 1973, Heringer 1970, Attali et al. 2021). Can we concretely identify factors to explain some of this variation and predict tendencies in individual interpretations? Here we show that a type of expectation about the world (which we call a high positive expectation), which can surface in the linguistic contexts of every-negation utterances, predicts experimental preferences for the inverse scope interpretation of different every-negation utterances. These findings suggest that (1) world knowledge, as set up in a linguistic context, helps to effectively reduce the ambiguity of potentiallyambiguous utterances for listeners, and (2) given that high positive expectations are a kind of affirmative context, negation use is felicitous in affirmative contexts (e.g., Wason 1961).
When Transformer models are more compositional than humans: The case of the depth charge illusion

State-of-the-art Transformer-based language models like GPT-3 are very good at generating syntactically well-formed and semantically plausible text. However, it is unclear to what extent these models encode the compositional rules of human language and to what extent their impressive performance is due to the use of relatively shallow heuristics, which have also been argued to be a factor in human language processing. One example is the so-called depth charge illusion, which occurs when a semantically complex, incongruous sentence like No head injury is too trivial to be ignored is assigned a plausible but not compositionally licensed meaning (Don't ignore head injuries, even if they appear to be trivial). I present an experiment that investigated how depth charge sentences are processed by Transformer models, which are free of many human performance bottlenecks. The results are mixed: Transformers do show evidence of non-compositionality in depth charge contexts, but also appear to be more compositional than humans in some respects.
Comparative Evaluation of Oversampling Techniques for Balancing Metabolic Profiles

The problem of imbalanced data is common when applying data analytics paradigms to binary and multiclass data, such as statistical analyses, predictive models, and classification metrics sensitive to imbalanced data, i.e., accuracy. Although there exist some pre-processing, algorithms, and hybrid approaches, none of them has a special focus on balancing metabolic profiles for Metabolic Syndrome analysis. Since the insights and conclusions obtained from data analysis paradigms applied to metabolic data are relevant to the topic, statistical power may be lost due to an imbalance between the Metabolic Syndrome related subclasses. Thus, there is a need to balance metabolic data to improve the insights derived from these types of analyses. In this context, this paper presents a comparative evaluation of six oversampling techniques for balancing metabolic profiles (SMOTE, B-SMOTE, ADASYN, ROS, K-SMOTE, and SVM-SMOTE). An imbalanced dataset with 16 classes from the combinations of 4 binary metabolic conditions is used for this analysis. Additionally, a methodology is defined to objectively evaluate and compare the six oversampling techniques in terms of representativity and variety. The results have shown that ROS and SMOTE have been the best oversampling techniques to balance metabolic data, generating high-quality synthetic profiles that resemble the real ones while balancing all classes equally. This demonstrates that metabolomics studies focused on metabolic syndrome can trust in these oversampling methods to improve their conclusions.
Supplemental Material: Transition from breccia pipe to stratabound mineralization in Mississippi Valley-type hydrothermal systems: The Nayongzhi Zn-Pb deposit, world-class Sichuan–Yunnan–Guizhou triangle, South China

&lt;p&gt;Figure S1: Paragenetic sequence of Nayongzhi Zn-Pb mineralization. Figure S2: Homogenization temperature and salinity histograms for all inclusions of different stages. Figure S3: Sketches of fluid inclusion assemblages from growth-zoned sphalerite crystal. Table S1: Sulfur and lead isotope composition in the Nayongzhi deposit. Table S2: Summary of microthermometric data for fluid inclusion in the Nayongzhi deposit.&lt;/p&gt;
Noise Reduction Through Thresholding Process Over the Space of Orthogonal Polynomials

Generally, noise contamination occurs during the acquisition, transmission, and storage processes. Due to these noisy components, the approximated data suffer from the dynamic synthesis of oscillatory patterns that reduces the overall data quality. In this paper, a new discretization technique is employed over the orthogonal basis functions to suppress noise components from the corrupted signal. Also, the acceleration into the error decay rate is done by including a thresholding function into the spectral methods. The efficiency of proposed method is demonstrated in terms of exponential convergence, signal-to-noise ratio, percentage root mean square difference, mean square error, and maximum error.
THE FUNCTIONAL AND STRUCTURAL FEATURES OF STUDENTS' PSYCHOLOGICAL WELL-BEING.

The goal of investigation - the content and functional components of the psychological well-being of students have been studied. Questionnaire and testing methods were applied. The gender, the age, the profession, the university, the average annual income in the family, availability of the COVID-19 vaccination, and the degree of involvement in the IT sector were determined through the questionnaire. In the frames of the testing M. Rosenberg's "Trust Scale", K. Riff's "Psychological well-being scale", subjective well-being scale and A. Batrashev's "Job Satisfaction" tests were used. The obtained results underwent quantitative and qualitative analysis. 108 students from universities of different regions of the RA took part in the study. Statically significant positive relationships between the psychological well-being and job satisfaction and its components, trust, self-assessment of health, as well as subjective well-being and its components was revealed. Meanwhile, there have been no links between subjective well-being and trust, job satisfaction, as well as some components of psychological well-being. There are also no reliable links between psychological well-being and the degree of IT involvement, average annual income, as well as vaccination rates from COVID. One-way analysis showed that the formation of psychological well-being is significantly influenced by such variables as satisfaction of professional activity, life, professional achievements, relationships with management and health assessment. It was shown that the person's orientation to the discovery and improvement of one's own resources as necessary determinants of psychological well-being effect a person's trust, attitude towards life, and the level of subjective well-being.
Teaching of Reading in the Midst of Uncertainties: The Narrative of Elementary School Teachers in Digos City

This descriptive-phenomenological study divulged the context of teaching reading during the health crisis brought by COVID-19 among elementary pupils. This study involved ten (10) informants which, composed of one (1) full- time faculty of Rizal Central Elementary School (RCES), two (2) teaching the English subjects, and three (3) employed in the institution since the beginning of the pandemic. Through purposive sampling, ten (10) teachers qualified from the inclusion criteria set were approached to request their voluntary involvement as participants through focus-group interviews. Hence, Colaizzi’s Data Analysis Approach was also employed in this study. Results indicated that Elementary teachers have a variety of experiences in teaching reading to their students with some difficulties and challenges but still have a positive outlook on the students. The study’s results also revealed that the teacher cope up with those challenges by having constant follow-ups with their parents reading progress. The different pedagogical techniques in promoting students’ reading were evident. However, the appropriate pedagogical techniques in teaching reading to students should be considered at all times. Hence, the result of the study also revealed that teachers use PHIL IRI to categorize the students reading progress.
Public Libraries of China: Basic Principles of Modernization

The purpose of this paper is to determine the basic principles of modernization of the People’s Republic of China.&#x0D; The methodology. The article uses the method of systematization. Based on the scientific literature, a brief but comprehensive description of the features of modern Chinese libraries is given, in particular, special attention is paid to the measures of library modernization, and thoughtful actions aimed at meeting the needs of each client.&#x0D; The results. The activity of public libraries in China is aimed at the formation of traditional regional culture, preservation of book cultural heritage, and promotion of social and economic development and is based on the principles of a client-oriented approach and openness of information space. These basic principles of modernization of public libraries in China are implemented in the active development of forms and methods of meeting the information needs of users of national information resources.&#x0D; The scientific novelty. This article joins the new array of scientific research, which focuses on the basic principles of transformation of library activities, which can be considered vectors of the development of public libraries.&#x0D; The practical significance. The article will be useful for scientists who are interested in the principles of library modernization (not only Chinese — the principles identified in the study can be applied to the development of all libraries, especially Ukrainian ones), as well as for library managers and ordinary employees who want to make their institution as comfortable as possible for visitors, advanced, attractive in all aspects.
Dynamic 3D face acquisition based on feature points matching and active binocular vision

ynamic 3D face acquisition has been widely used in the fields of real-time expression capture, face recognition, plastic surgery and film entertainment. High-precision 3D shape can be obtained by fringe projection 3D measurement technology. However, the phase ambiguity is one of the key issues must be solved. According to the features of human face, a method based on feature point matching and active binocular vision is proposed to address this problem. The specific method is as follows: 1) Project three sinusoidal fringes with a phase difference of 2π/3. Capture the deformed fringes by the left and right cameras simultaneously. 2) According to the phase shift method, calculate the corresponding intensity images and the wrapping phase maps from the deformed fringes captured by the left and right cameras respectively. 3) Detect the face feature points in the left and right intensity images respectively. 4) Create the rough face disparity map by matching the feature points of human face in the left and right intensity images. 5) On the basis of rough disparity map, obtain the dense and high-precision disparity map by directly matching the wrapping phase of the left and right images. And then reconstruct the 3D face. Compared with the traditional method, the proposed method does not need the spatial phase unwrapping, nor does it need the projection of additional patterns to assist the phase unwrapping, which shortens the acquisition time while ensuring the measurement reliability. A DLP projector and two cameras with resolution of 1.3 megapixels and speed of 210fps were used to build an experimental system to verify the proposed method. The experimental results show that the proposed method is robust and the 3D face acquisition speed reaches 70fps.
An energy-efficient quantized inference framework for electro-photonic computing system

Deep Learning is developing rapidly and has made breakthroughs in various fields. As a result, the number of parameters in deep neural networks (DNNs) is scaling about 5× rate of Moore’s Law. To meet the computing power needs of DNNs, new computing architectures have been proposed, and the electro-photonic computing system is one of them. With the physical characteristics of photons, the electro-photonic computing system has demonstrated great potential in improving the efficiency of convolution calculation. However, there are still much space for improvement in the energy efficiency of the electro-photonic computing system. And the high energy consumption led by the high-precision analog-to-digital converters (ADCs) is an important factor hindering the energy efficiency. ADCs dominate about 50% energy consumption of the entire system, and they will increase exponentially with the precision. But if the low-precision ADCs are used directly, they will destroy the computing accuracy in the convolution calculation and reduce the inference performance of DNNs. In this paper, we propose an energy-efficient quantized inference framework for electro-photonic computing system to balance the energy consumption of ADCs and the DNNs inference performance, which includes a multi-scale quantization scheme based on per-slice granularity and width variable optical matrix. The proposed framework can reduce the energy consumption of the system by using low-precision ADCs, and ensure the inference performance of the DNNs at the same time. The experiments are carried out in MobileNet-v2, ResNet50 and Vgg16 respectively. The experimental results show that the proposed quantized inference framework can reduce the precision of ADCs by 7 bits and compared with using the low-precision ADCs directly, it improves the model accuracy of 40.5%, 70.2% and 65.4% respectively, which is close to the full precision model.
Influence of projector pixel arrangement on 3D measurement error under different defocusing degree

In the fringe projection 3D measurement system in which the camera pixel size is much smaller than the projector pixel size, the pixel arrangement of projector will have a significant impact on the measurement results. The main reason for this problem is that the sinusoidal property of the fringes captured by the camera deteriorates. This can be improved by defocusing the projector. In this paper, the influence of projector pixel arrangement on 3D measurement error under different defocusing degree is studied by experiments. According to the actual pixel structure of DMD projector, sinusoidal fringes with zigzag and linear pixel arrangement are designed for experiments. The fringes with a period of 8 pixels are adopted for experiment, and the phase of the fringe is calculated by four-step phase-shifting algorithm. Experimental results demonstrated that the measurement error is a tendency which increases first and then decreases with increasing projector defocusing degree. When the degree of defocus is small, the phase measurement error of linear pixel array is significantly smaller than that of zigzag array. And when the degree of projector defocus increases to a certain extent, the phase measurement error of zigzag pixel array is smaller than that of linear pixel array. The experimental results are valuable for the design of high-resolution 3D measurement system.
Unified Design Using Monte Carlo Tree Search and Hybridized Topology-Parameter Optimization

This paper presents a novel total design method using Monte Carlo tree search and hybridized topology-parameter optimization. In this method, the global structure of an electrical machine is represented by nodes in a tree structure. Monte Carlo tree search is used to select a path in the tree structure, which corresponds to a machine structure. After that, detailed machine shape is optimized by the hybridized method considering both of flexibility and manufacturability. By repeating the above procedure, the global structure and detailed shape are simultaneously optimized. This method is applied to the design of a permanent magnet motor to enhance torque characteristics.
RANCANG BANGUN MEDIA PEMBELAJARAN BERBASIS ANDROID (SMART APP CREATOR) PADA MATA PELAJARAN SISTEM ADMINISTRASI JARINGAN DI SMK ULIL ALBAB

Student learning outcomes are influenced by two factors, namely internal factors and external factors. Internal factors come from within students and external factors that come from outside students. Internal factors such as students' abilities, interests and motivation to learn, while external factors such as environmental conditions, schools and learning quality. The use of media in learning can help the limitations of educators in conveying information as well as the limitations of class hours. The media serves as a source of information on learning materials and as a source of practice questions. The quality of learning is also influenced by individual differences of students, both differences in learning styles, differences in cognitive abilities, differences in learning speed, and differences in background. This research and development aims to develop learning media for Android-based network server administration on basic network server administration materials, knowing the process of designing learning media developed, and making learning media developed using smart apps creators. There is no android-based learning media in the subject of network server administration. From the results of the preliminary study, it can be illustrated that the learning media used in the learning process still use paper and print media. Student learning outcomes are still far from expectations (KKM). Software development uses the waterfall model development method. In the waterfall there are several main stages that describe software development activities. The reason for using the waterfall method is because the stages in system development in the waterfall model are clearly structured.
CLUSTERING DATA NILAI UJIAN AKHIR SEMESTER MENGGUNAKAN ALGORITMA DATA MINING K-MEANS

Analyzing student performance in education is an active and fairly new area of educational research. Mapping student performance is useful for both teachers and students. However, the factors that affect student performance need to be identified first to build the initial predictive model. The clustering of UAS scores acts as an indicator of whether the spread of knowledge from teachers to students is evenly distributed or not. This is very relevant to the state of the covid pandemic that is happening in Indonesia and the world, we can know which clusters of students are truly self-study or not. K-Means can be used to map students' academic abilities, in order to optimize student learning and understanding.
Early numeracy skills in early childhood: the effect of numbered heads together cooperative learning methods

This study aims to determine the effect of the cooperative learning method with the Numbered Heads Together type on numeracy skills in early childhood. This study used the pre-experimental method with a one group pretest-posttest design. The research sample for children aged 5-6 years was 16 children. Data collection was in the form of a checklist of child development data with value categories from not yet developed to very well developed. Data analysis used the t-test by fulfilling normality and homogeneity first. The results showed that the t-count value is greater than the t-table value (t-count t-table). So, it can be concluded that the cooperative learning method with the Numbered Heads Together type has an influence on the development of early childhood numeracy skills. Thus, the teacher can apply various types of cooperative learning methods in the classroom to improve other aspects of development.
Apply mathematical modeling in steam education at high schools

In mathematics instruction, mathematical models are one of the powerful tools for promoting effective learning. However, it must be used properly. Teachers need to use mathematical models as part of their teaching methods. STEAM education represents a paradigm shift from a traditional education based on standardized test scores to modern ideas that focus on the valuation of learning process. In essence, we allow our students to be wrong, try many ideas, listen to alternative ideas and create a knowledge base that can be applied to real life. In this paper, the researcher studied the application of modeling in STEAM education projects.
Blockchain based Trust System for Counterfeit Product Detection

Counterfeit products have been a significant factor in the manufacturing of goods in recent years.This has an impact on a company's brand, sales, and bottom line.Blockchain technology is used to identify genuine goods and identify counterfeit goods.The distributed, decentralized, and digital ledger that houses transactional data is called blockchain technology.Many databases store information in the form of blocks that are linked together via chains.Blockchain innovation is secure technology, therefore no block can be altered or compromised.Blockchain technology allows for Customers or users do not have to rely on other users to vouch for the security of the product.Quick Response (QR) codes, a developing trend in wireless and mobile technologies, were used in this project a strong strategy to combat the problem of product counterfeiting.A QR code scanner is used to identify fake goods because each product's QR code is connected to a Blockchain.Therefore, this system may be utilized to store product information and its produced unique code as database blocks.It requests the user's unique code, then checks it against entries in the Blockchain database.If the code matches, the customer will receive notification; if not, the consumer will receive notification that the product is a fake.
100 Babasahin Para kay Fino: Intervention in the Development of Reading Comprehension

This study aimed to assess the effectiveness of 100 Babasahin Para kay Fino as an intervention to improve the reading comprehension level of students. Through the intervention of reading and developing the level of understanding of what the students read. The Quasi-Experimental, a group (one group) design pre-test, and post-test (pre-reading assessment and post-reading assessment) was used. The researchers have innovated from a simple reading method to the development of self-made reading materials containing to develop the level of understanding of what the students read. This study has proven that 100 Babasahin Para kay Fino is beneficial at developing students' reading comprehension.