Reviewerly/exHarmony huggingface dataset:
Soft-Aware Development: Social Emotional Learning as an Agile Process

Industry trends showcase the increasing importance of soft skills, but interpersonal STEM education is not yet well defined [7, 14]. With high technology churn and increasingly higher-level programming practices, the need for effective collaboration remains constant, as "productivity depends on a work force that is socially and emotionally competent" [5]. Social and Emotional Learning promotes engagement in STEM [1, 6], while experiential/makerspace learning increases equity, belonging, and competency [3, 13, 19]. Reflecting on undergraduate Agile [2] Software Development at Knox College, we contend that learning to make Software is less important than learning to work together while attempting to make Software. We define Soft-Aware Development to encompass building Software, building stakeholder relationships, and building up each developer along the way.
A Cut-Free, Sound and Complete Russellian Theory of Definite Descriptions

Abstract We present a sequent calculus for first-order logic with lambda terms and definite descriptions. The theory formalised by this calculus is essentially Russellian, but avoids some of its well known drawbacks and treats definite description as genuine terms. A constructive proof of the cut elimination theorem and a Henkin-style proof of completeness are the main results of this contribution.
Nested Sequents for Quantified Modal Logics

Abstract This paper studies nested sequents for quantified modal logics. In particular, it considers extensions of the propositional modal logics definable by the axioms D , T , B , 4 , and 5 with varying, increasing, decreasing, and constant domains. Each calculus is proved to have good structural properties: weakening and contraction are height-preserving admissible and cut is (syntactically) admissible. Each calculus is shown to be equivalent to the corresponding axiomatic system and, thus, to be sound and complete. Finally, it is argued that the calculi are internal—i.e., each sequent has a formula interpretation—whenever the existence predicate is expressible in the language.
DefTab : A Tableaux System for Sceptical Consequence in Default Modal Logics

Abstract We report on an implementation of a tableaux calculus for sceptical consequence in Default Logic built on Hybrid Modal Logic. In turn, our tool offers support for checking default consequence over formulas from Propositional Logic, Basic Modal Logic and Hybrid Logic. We develop a test suite for assessing the correctness, scalability, and efficiency of our system, and inform on the results. Interestingly, our method can be adapted to generate examples for other default provers.
Absolutely maximally entangled state equivalence and the construction of infinite quantum solutions to the problem of 36 officers of Euler

Ordering and classifying multipartite quantum states by their entanglement content remains an open problem. One class of highly entangled states, useful in quantum information protocols, the absolutely maximally entangled (AME) ones, are especially hard to compare as all their subsystems are maximally random. While it is well known that there is no AME state of four qubits, many analytical examples and numerically generated ensembles of four-qutrit AME states are known. However, we prove the surprising result that there is truly only one AME state of four qutrits up to local unitary equivalence. In contrast, for larger local dimensions, the number of local unitary classes of AME states is shown to be infinite. Of special interest is the case of local dimension 6, where it was established recently that a four-party AME state does exist, providing a quantum solution to the classically impossible Euler problem of 36 officers. Based on this, an infinity of quantum solutions are constructed, and we prove that these are not equivalent. The methods developed can be usefully generalized to multipartite states of any number of particles.
Non-Classical Logics in Satisfiability Modulo Theories

Abstract We show that tableau methods for satisfiability in non-classical logics can be supported naturally in SMT solving via the framework of user-propagators. By way of demonstration, we implement the description logic $$\mathcal {ALC}$$ in the Z3 SMT solver and show that working with user-propagators allows us to significantly outperform encodings to first-order logic with relatively little effort. We promote user-propagators for creating solvers for non-classical logics based on tableau calculi.
Proof Systems for the Modal $$\mu $$-Calculus Obtained by Determinizing Automata

Abstract Automata operating on infinite objects feature prominently in the theory of the modal $$\mu $$ -calculus. One such application concerns the tableau games introduced by Niwiński &amp; Walukiewicz, of which the winning condition for infinite plays can be naturally checked by a nondeterministic parity stream automaton. Inspired by work of Jungteerapanich and Stirling we show how determinization constructions of this automaton may be used to directly obtain proof systems for the $$\mu $$ -calculus. More concretely, we introduce a binary tree construction for determinizing nondeterministic parity stream automata. Using this construction we define the annotated cyclic proof system $$\textsf{BT}$$ , where formulas are annotated by tuples of binary strings. Soundness and Completeness of this system follow almost immediately from the correctness of the determinization method.
CoNP Complexity for Combinations of Non-normal Modal Logics

Abstract We study the complexity of the validity/derivability problem for combinations of non-normal modal logics in the form of logic fusions, possibly extended with simple interaction axioms. We first present cut-free sequent calculi for these logic combinations. Then, we introduce hypersequent calculi with invertible rules, and show that they allow for a coNP proof search procedure. In the last part of the paper, we consider the case of combinations of logics sharing a universal modality. Using the hypersequent calculi, we show that these logics remain coNP-complete, and also provide an equivalent axiomatisation for them.
IMPLEMENTASI ALGORITMA VIGENERE CIPHER UNTUK ENKRIPSI DAN DEKRIPSI PADA PERESEPAN DATA OBAT DI PUSKESMAS MERTOYUDAN 1 KABUPATEN MAGELANG

Puskesmas is a place to provide health and medical services for the community. Every patient who seeks treatment at a doctor at the health center always gets a message containing a prescription for the drug. The problem that often occurs is the large number of drug prescribing processes that occur without being based on a system, can cause errors in drug prescribing and can be fatal for patients. The purpose of this research is to make an electronic encrypted prescription application using the Vigener Cipher method. The implementation of this system uses the Vigener Cipher Algorithm in securing prescription drug data. The Vigener Cipher algorithm can perform encryption and decryption processes. System Design with Context Diagram. The result of this study is that the application of drug prescribing data using the Vigener Cipher Algorithm has been able to secure drug prescribing properly. In the PARASETAMOL Drug Data Test, key: CXWDFHHJYVW, result: RXNDXLAJKJH. Functional Testing Results obtained results that are accepted in all test scenarios and Validity Test Results obtained 100% valid results
Resolution Calculi for Non-normal Modal Logics

Abstract We present resolution calculi for the cube of classical non-normal modal logics. The calculi are based on a simple clausal form that comprises both local and global clauses. Any formula can be efficiently transformed into a small set of clauses. The calculi contain uniform rules and provide a decision procedure for all logics. Their completeness is based on a new and crucial notion of inconsistency predicate, needed to ensure the usual closure properties of maximal consistent sets. As far as we know the calculi presented here are the first resolution calculi for this class of logics.
Extensions of $$\textsf{K5}$$: Proof Theory and Uniform Lyndon Interpolation

Abstract We introduce a Gentzen-style framework, called layered sequent calculi , for modal logic $$\textsf{K5}$$ and its extensions $$\textsf{KD5}$$ , $$\textsf{K45}$$ , $$\textsf{KD45}$$ , $$\textsf{KB5}$$ , and $$\textsf{S5}$$ with the goal to investigate the uniform Lyndon interpolation property (ULIP), which implies both the uniform interpolation property and the Lyndon interpolation property. We obtain complexity-optimal decision procedures for all logics and present a constructive proof of the ULIP for $$\textsf{K5}$$ , which to the best of our knowledge, is the first such syntactic proof. To prove that the interpolant is correct, we use model-theoretic methods, especially bisimulation modulo literals.
On Intuitionistic Diamonds (and Lack Thereof)

Abstract A variety of intuitionistic versions of modal logic $$ K $$ have been proposed in the literature. An apparent misconception is that all these logics coincide on their $$\Box $$ -only (or $$\Diamond $$ -free) fragment, suggesting some robustness of ‘ $$\Box $$ -only intuitionistic modal logic’. However in this work we show that this is not true, by consideration of negative translations from classical modal logic: Fischer Servi’s $$ IK $$ proves strictly more $$\Diamond $$ -free theorems than Fitch’s $$ CK $$ , and indeed $$i K $$ , the minimal $$\Box $$ -normal intuitionistic modal logic. On the other hand we show that the smallest extension of $$i K $$ by a normal $$\Diamond $$ is in fact conservative over $$i K $$ (over $$\Diamond $$ -free formulas). To this end, we develop a novel proof calculus based on nested sequents for intuitionistic propositional logic due to Fitting. Along the way we establish a number of new metalogical results.
A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion

Images captured in low-brightness environments typically have low brightness, low contrast, and high noise levels, which significantly affect the overall image quality. To improve the image quality, a low-brightness image enhancement algorithm based on multi-scale fusion is proposed. First, a novel brightness transformation function is used for the generation of two images with different brightnesses. Then, the illumination estimation technique is used to construct a weight matrix, which facilitates the extraction of advantageous features from each image. Finally, the enhanced image is obtained by the fusion of two images using the weight matrix and the pyramid reconstruction algorithm. The proposed method has a better enhancement effect as shown by the experimental results. Compared to other image enhancement algorithms, it has lower evaluation values in the natural image quality evaluator (NIQE) and lightness order error (LOE) indices. The lowest average NIQE value of the proposed algorithm in each dataset is 2.836. This further demonstrates its superior performance.
Sentiment Analysis of the Use of Digital Banking Service Applications On Google Play Store Reviews Using Naïve Bayes Method

The development of the financial system is characterized by the emergence of digital banking service applications that are widely circulated and can be accessed for free. With so many applications, users often feel confused in choosing which applications are safe to use. Before downloading an application on the Google Play Store, users will usually look at ratings and reviews first. However, the title of the best application cannot be pinned if only seen from the rating and number of downloads. This research was conducted to analyze sentiment on user reviews of digital banking service applications on the Google Play Store using the NBC (Naïve Bayes Classifier) method. Research using the NBC algorithm produced an accuracy value of 81% on the classification of Allo Bank reviews and 78% on the classification of Line Bank reviews
Canonicity of Proofs in Constructive Modal Logic

Abstract In this paper we investigate the Curry-Howard correspondence for constructive modal logic in light of the gap between the proof equivalences enforced by the lambda calculi from the literature and by the recently defined winning strategies for this logic. We define a new lambda-calculus for a minimal constructive modal logic by enriching the calculus from the literature with additional reduction rules and we prove normalization and confluence for our calculus. We then provide a typing system in the style of focused proof systems allowing us to provide a unique proof for each term in normal form, and we use this result to show a one-to-one correspondence between terms in normal form and winning innocent strategies.
A Linear Perspective on Cut-Elimination for Non-wellfounded Sequent Calculi with Least and Greatest Fixed-Points

Abstract This paper establishes cut-elimination for $$\mathsf {\mu LL^\infty }$$ , $$\mathsf {\mu LK^\infty }$$ and $$\mathsf {\mu LJ^\infty }$$ , that are non-wellfounded sequent calculi with least and greatest fixed-points, by expanding on prior works by Santocanale and Fortier [20] as well as Baelde et al. [3, 4]. The paper studies a fixed-point encoding of $$\textsf{LL}$$ exponentials in order to deduce those cut-elimination results from that of $$\mathsf {\mu MALL^\infty }$$ . Cut-elimination for $$\mathsf {\mu LK^\infty }$$ and $$\mathsf {\mu LJ^\infty }$$ is obtained by developing appropriate linear decorations for those logics.
MODEL OF FORMING STUDENTS’ RESEARCH COMPETENCIES IN TEACHING A FOREIGN LANGUAGE AT TECHNICAL UNIVERSITY

Purpose. The article examines the process of forming students’ research competency in the process of teaching a foreign language at technical university as the way of improving professional education and students’ self-organization.&#x0D; Materials and methods. The basis of the research is the theoretical methods (methods of analysis and synthesis, generalization and systematization, projecting). The leading method of research is the method of projecting, and the main humanistic principle is multimodality to ensure students’ integrity, autonomy and subjectivity.&#x0D; Results. The model of forming students’ research competency has been developed in the context of personal oriented, competent oriented approaches and synergistic methodology. The article determines the main conditions for the formation of students’ research competency. The project model is revealed and the basis of forming research competency is the activity of students’ personal structures. Therefore, they are indicators of increasing the levels of research competencies in the process of teaching a foreign language. The obtained results convincingly testify to the increase in motivation to learn a foreign language, the development of the experience of research competence of students, the motivation to participate in real research projects in the research educational and cultural environment of a technical university. Students’ project activities increase the effectiveness of teaching foreign language communication, the development of research skills, the flexibility of cognitive functions, subjectivity, the formation of research experience, the formation of professional values and meanings.
Human Activity Recognition with Smartwatch Data by using Mahalanobis Distance-Based Outlier Detection and Ensemble Learning Methods

Recognition of human activities is part of smart healthcare applications. In this context, the detection of human actions with high accuracy has been a field that has been working for many years. With the increase in the usage of smart devices, smartphones and smartwatches have become the constant equipment of these studies thanks to their internal sensors. Sometimes abnormal data are included in data sets due to the way the data were collected and for reasons arising from the sensors. For this reason, it becomes important to detect outlier data. In this study, step counter and heart rate sensors were used in addition to an accelerometer and gyroscope in order to detect human activities. Afterward, the outliers were detected and cleared with a Mahalanobis distance-based approach. With the aim of achieving a better classification performance, machine learning methods were used by strengthening them with ensemble learning methods. The obtained results showed that step counter, heart rate sensors, and ensemble learning methods positively affect the success of the classification. In addition, it was found that the Mahalanobis distance-based outlier detection method increased the classification accuracy significantly.
Supergene Hydrous Sulfates in the Tuolugou Co-Au Deposit, Northern Qinghai–Tibet Plateau: Implications for Genetic Mechanism and Exploration

Supergene hydrous sulfate minerals form through the oxygenation and weathering of primary sulfides. In the Qinghai–Tibet Plateau region, with an alpine and dry environment, hydrous sulfate minerals oxidized from pyrite-bearing ore bodies provide important clues regarding the mineralization and environment. The Tuolugou sedimentary-exhalative (SEDEX) Co-Au deposit is located in the East Kunlun metallogenic belt of the northern Qinghai–Tibet Plateau in China. In the mining district, pyrite is the prevalent Co-hosting sulfide mineral, and is partially exposed on the surface to weathering and oxidation. Herein, we document the mineral assemblages in the supergene oxidation zone in the Tuolugou deposit, probe the genesis of supergene assemblage, and explore the implications for exploration. Three zones can be recognized in the oxidation zone of the Tuolugou deposit, including the outer zone (natrojarosite), intermediate zone (rozenite and aplowite), and inner zone (roemerite and melanterite). The mechanism of oxidation under aerobic and anaerobic conditions, as well as zoning with different oxidation degrees, are described in detail. Hydrous sulfates such as natrojarosite can be used as possible indicators of the exploration of albitite-related SEDEX deposit in this region.
On Evaluating IoT Data Trust via Machine Learning

Data trust in IoT is crucial for safeguarding privacy, security, reliable decision-making, user acceptance, and complying with regulations. Various approaches based on supervised or unsupervised machine learning (ML) have recently been proposed for evaluating IoT data trust. However, assessing their real-world efficacy is hard mainly due to the lack of related publicly available datasets that can be used for benchmarking. Since obtaining such datasets is challenging, we propose a data synthesis method, called random walk infilling (RWI), to augment IoT time-series datasets by synthesizing untrustworthy data from existing trustworthy data. Thus, RWI enables us to create labeled datasets that can be used to develop and validate ML models for IoT data trust evaluation. We also extract new features from IoT time-series sensor data that effectively capture its autocorrelation as well as its cross-correlation with the data of the neighboring (peer) sensors. These features can be used to learn ML models for recognizing the trustworthiness of IoT sensor data. Equipped with our synthesized ground-truth-labeled datasets and informative correlation-based features, we conduct extensive experiments to critically examine various approaches to evaluating IoT data trust via ML. The results reveal that commonly used ML-based approaches to IoT data trust evaluation, which rely on unsupervised cluster analysis to assign trust labels to unlabeled data, perform poorly. This poor performance is due to the underlying assumption that clustering provides reliable labels for data trust, which is found to be untenable. The results also indicate that ML models, when trained on datasets augmented via RWI and using the proposed features, generalize well to unseen data and surpass existing related approaches. Moreover, we observe that a semi-supervised ML approach that requires only about 10% of the data labeled offers competitive performance while being practically more appealing compared to the fully supervised approaches. The related Python code and data are available online.
Proposed DeepFake Detection Method Using Multiwavelet Transform

Videos made by artificial intelligence (A.I.) seem real, but they are not. When making DeepFake videos, face-swapping methods are frequently employed. The misuse of technology when using fakes, even though it was fun at first, these videos were somewhat recognizable to human eyes. However, as machine learning advanced, it became simpler to produce profound fake videos. It's practically impossible to tell it apart from actual videos now. Using GANs (Generative Adversarial Networks) and other deep learning techniques, DeepFake videos are output technology that may mislead people into thinking something is real when it is not. This study used a MultiWavelet transform to analyze the type of edge and its sharpness to develop a blur inconsistency detecting system. With this capability, it can assess whether or not the facial area is obscured in the video. As a result, it will detect fake videos. This paper reviews DeepFake detection techniques and discusses how they might be combined or altered to get more accurate results. A detection rate of more than 93.5% was obtained, which is quite successful.
Standardizing HER2 immunohistochemistry assessment: calibration of color and intensity variation in whole slide imaging caused by staining and scanning

Abstract In the evaluation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) — one of the standard biomarkers for breast cancer— visual assessment is laborious and subjective. Image analysis using whole slide image (WSI) could produce more consistent results; however, color variability in WSIs due to the choice of stain and scanning processes may impact image analysis. We therefore developed a calibration protocol to diminish the staining and scanning variations of WSI using two calibrator slides. The IHC calibrator slide (IHC-CS) contains peptide-coated microbeads with different concentrations. The color distribution obtained from the WSI of stained IHC-CS reflects the staining process and scanner characteristics. A color chart slide (CCS) is also useful for calibrating the color variation due to the scanner. The results of the automated HER2 assessment were compared to confirm the effectiveness of two calibration slides. The IHC-CS and HER2 breast cancer cases were stained on different days. All stained slides and CCS were digitized by two different WSI scanners. Results revealed 100% concordance between automated evaluation and the pathologist’s assessment with both the scanner and staining calibration. The proposed method may enable consistent evaluation of HER2.
Creating Custom Immersive 360-Degree Videos for Use in Clinical and Nonclinical Settings: Tutorial

The use of virtual reality (VR) stimulation in clinical settings has increased in recent years. In particular, there has been increasing interest in the use of VR stimulation for a variety of purposes, including medical training, pain therapy, and relaxation. Unfortunately, there is still a limited amount of real-world 360-degree content that is both available and suitable for these applications. Therefore, this tutorial paper describes a pipeline for the creation of custom VR content. It covers the planning and designing of content; the selection of appropriate equipment; the creation and processing of footage; and the deployment, visualization, and evaluation of the VR experience. This paper aims to provide a set of guidelines, based on first-hand experience, that readers can use to help create their own 360-degree videos. By discussing and elaborating upon the challenges associated with making 360-degree content, this tutorial can help researchers and health care professionals anticipate and avoid common pitfalls during their own content creation process.