Reviewerly/exHarmony huggingface dataset:
Modes of Explanation

This chapter first introduces Aristotle’s doctrine of the four causes: material cause, formal cause, efficient cause and final cause. It is followed by the covering law model with its two versions: the deductive-nomological model, which is deterministic, and the inductive-statistical model, which is probabilistic. There are a number of counterexamples revealing the flaws of the covering law model, and the chapter discusses three: the barometer, the birth-control pill and the flagpole. A key defect of the model is that it does not involve the notion of causal mechanism. In contrast, mechanismic explanation traces the causal chain that produces the effect of interest and avoids the problems represented by the three counterexamples. Intentional explanation attempts to explain human behavior by intentional causation that treats reasons as causes. Although the terms teleological explanation and functional explanation are often used interchangeably, teleological explanation deals with conscious intent to achieve goals and is only applicable to human actions whereas functional explanation is concerned with the contribution of an entity to the future maintenance of a system of which the entity is a part. Historical explanation focuses on explaining the occurrence of some particular event by describing how it came to be. Finally, in contrast to variance theorizing that only examines the covariation among independent and dependent variables, process organization studies take time sequencing and ordering of events to be critical in conjuring up an explanation.
The Effect of smart specialisation on the Regional Economy

：Arguably many studies point out that regional innovation capabilities are accepted as a major source of growth for the sustainable regional economy. Recently, a smart specialisation strategy that should reflect regional characteristics in the policy implementation process of the regional innovation system has been proposed, but empirical studies have only presented limited results. This study attempts to overcome limitations by approaching smart specialisation as a supplementary strategy for existing regional innovation research. To this end, smart specialisation was not an alternative strategy for the regional innovation system, but rather the institutional elements of regional innovation capabilities, and the relationship between regional innovation capabilities and the local economy was analyzed to identify the impact of smart specialisation on the local economy. A study was conducted through a panel model consisting of 16 cities and provinces in Korea and 10 years from 2009-2018, and the FGLS model was finally used through the process of searching for an appropriate panel model. As a result of the study, smart specialisation consisting of industry related variety and non-related variety had a positive effect on the local economy. In addition, other regional innovation capabilities measured by dividing them into base and facilitating factors also had a positive effect on the local economy, reaffirming the results of positive research between existing regional innovation and the local economy. This study is meaningful in that smart specialisation lacking in domestic research was viewed as an institutional element of regional innovation capabilities, and it was measured through regional industry-related variety and non-related variety.
The Vulnerability of Differential Object Marking in Three Heritage Languages

This chapter presents the motivation and methodology of a cross-linguistic and cross-generational study of DOM in Spanish, Hindi and Romanian as heritage languages. Innovative aspects of this project are the comparison of the same linguistic phenomenon cross-linguistically and in heritage languages that share the same majority language context and the inclusion of adult first generation immigrants to examine the cross-generational component. By including heritage speakers and first-generation immigrants as well as two generations of native speakers in the homeland, we examine whether changes with DOM are observed in both diaspora and homeland contexts, or only in the diaspora context. The purpose of this study was to elucidate the linguistic and situational factors that contribute to DOM erosion within and across languages. The rest of this chapter presents the research questions, more specific hypotheses and the overall methodology.
Differential Object Marking in Spanish as a Heritage Language

The acquisition of DOM in Spanish monolingual children and Spanish-speaking bilinguals has been intensely investigated in the last two decades. One of the main objectives of the in-depth study of DOM conducted for this project was to confirm and evaluate the strength of previous findings of DOM omission in Spanish-English bilingual children and in young adult heritage speakers. If erosion of DOM in Spanish as a heritage language is indeed a robust phenomenon, it should be documented in other groups of heritage speakers. Although hypotheses about the potential role of the parental generation in contributing to heritage language grammars abound, at the time the Spanish study reported in this book was conceived, there were no studies of potential attrition of DOM in adult immigrants. Therefore, the first-generation immigrant group was included to put the language transmission hypothesis to the test. This chapter presents a brief overview of Spanish in the United States before summarizing the main results of the language background questionnaire, and of the production, comprehension and judgment tasks described in Chapter 5.
Design and implementation of ice and snow tourism based on virtual reality technology

With the development of science and technology, virtual reality technology has gradually matured. The traditional method of promoting tourist attractions with the help of video cannot meet people's needs, so we build an ice and snow tourism system based on virtual reality technology. By software unity3D, build scenes, add characters, animals, snow scenes, etc. the virtual ice and snow world is present perfectly, provide people with a virtual space, strengthen people's perception of the ice and snow world by means of human-computer interaction, and let people experience ice and snow travel.
Obstruction avoidance path planning of unmanned surface vehicle based on Dijkstra self-optimization model

In order to generate an obstruction avoidance path for unmanned surface vehicle, the Dijkstra self-optimization model is proposed in this paper. First, a Maklink undirected graph is generated according to the starting point, ending point, and obstructions, the Dijkstra algorithm is used to generate an initial path to avoid obstructions. Second, a directed graph is generated based on the initial path, the Dijkstra algorithm is used to generate the optimal path with the shorter length. The experimental results show that the Dijkstra self-optimization model can generate the shortest path to avoid obstructions. Compared with the Maklink+ACO model, this model has smaller time complexity and is the optimal solution.
Wavelet and histogram based mammogram enhancement for abnormality detection

The Ceylon Journal of Science is a peer-reviewed journal published quarterly by the University of Peradeniya, Sri Lanka in March, June, September and December. It is aimed at publishing high quality research articles on topics related to different disciplines in Science. The journal accepts original research articles, book reviews, reviews and mini-reviews, short communications, opinions, research notes, and commentaries and notes. The Journal has its own website https://site.pdn.ac.lk/cjs/. The journal strictly adheres to publication ethics as emphasized by the Committee on Publication Ethics (COPE). It is indexed in Sri Lanka Journals Online (SLJOL), Directory of Open Access Journals (DOAJ), Google Scholar and Zoological Records. According to the Google Scholar;H5-Index: 12H5-Median: 15According to the Exaly (1970 – 2021);Impact Factor: 0.6 (top 19%)Extended IF: 0.6 (top 19%)H-Index: 8 (top 28%)Citations/paper: 1.42
Possible Worlds and Possible Individuals

Abstract While this book endorses an ontological commitment to propositions, properties, and relations, it rejects a commitment to the existence of merely possible worlds or merely possible individuals. The aim of this chapter is to reconcile the rejection of these ontological commitments with a model theory for modal logic that seems to require them. It is argued that a model structure of a Kripke model that is intended to represent some aspect of reality should be regarded as a representational device that may contain artifacts that do not correspond to anything in the reality being modeled. The role of the artifacts is to represent a relational structure that is realized in the domains of entities being modeled. The modeling strategy is a generalized supervaluation strategy that uses refinements of models to facilitate the compositional semantics for domains with relational structure that is not grounded intrinsic properties.
First-Order Modal Logic and a First-Order Theory of Propositions

Abstract This chapter is a technical digression with two aims: The first is to make explicit the proof theory and model theory for the first-order modal logic that has been proposed as a framework for regimented languages. The model theory is a version of possible-worlds semantics that allows the domains of individuals to vary from world to world. The second task is to make explicit a representation of the formal theory of propositions proposed in Chapter 2 in this modal framework. The first task includes giving a completeness theorem for the modal logic. The second task includes an argument that there is no paradox in a theory of propositions with a truth predicate that applies to the propositions expressed in the language of that theory.
Propositions

Abstract A theory of propositions with just two primitive predicates, truth and consistency, is formulated in first-order extensional logic, and it is argued that a theory of this kind should be acceptable to one with Quine’s ontological scruples. But if we accept that there are propositions, we should assume that regimented languages of the kind that Quine aimed to construct should express propositions, and this assumption motivates and helps to justify the use of a language with modal operators in which to formulate our theories. Quine rejected modal logic, and while it is acknowledged that there are good reasons to criticize the foundations for modal logic given by its early developers, it is argued that the theory of propositions provides a different foundation that is not subject to those criticisms. The move to modal logic does raise some new questions that are to be discussed in later chapters.
Combining modified hyper learning binary dragonfly algorithm and deep learning for <scp>BI‐RADS</scp> classification of breast masses in mammograms

Abstract Background It has always been difficult and challenging to quantify the breast imaging reporting and data system (BI‐RADS) criteria into several categories. Automatic quantitation can assist clinicians in the early diagnosis and treatment eventually reducing the mortality rate. As a result, in the recent years, early BC diagnosis methods based on pathological breast images have been in high demand. Method We propose a computer‐aided diagnosis (CAD) system that combines the transfer learning approach with meta‐heuristic optimization, and machine learning to classify BI‐RADS breast masses categories within levels 3 and 4. Transfer learning technique ResNet‐18 is used for high‐level feature extraction. The clinically important features are then chosen using a modified feature selection technique based on the Hyper Learning Binary DragonFly Algorithm (M‐HLBDA). Finally, a Fine K‐nearest neighbour (KNN) is employed for classification. Result A series of mammography breast mass images from the curated breast imaging subset of DDSM (CBIS‐DDSM) are evaluated in order to categorize within BI‐RADS levels 3 and 4. Experimental findings demonstrated M‐HLBDA capability to identify the optimal feature subset, which minimizes the number of selected features and maximizes the classification. Our system attained classification accuracy of 87.5%, Sensitivity of 88.8%, Specificity of 86.5%, and AUC of 0.82 using KNN on selected features using M‐HLBDA. Conclusion Our model can annotate and classify BI‐RADS levels 3 and 4 with better classification accuracy, and it may be used as an automated system to help radiologists.
Time-domain measurement of twin beams produced by fiber amplifiers with an ultra-fast pulse train as a pump

A pulsed pumped four-wave mixing process via χ (3) nonlinearity in an optical fiber can generate optical pulses with continuous variable quantum correlation. However, pairwise correlation of the generated pulses in this system has not been demonstrated. Here we report a time-domain measurement of an intensity difference squeezed state generated in a fiber. With a fast response differential detection system, we show the generated twin-beam pulses are pairwisely correlated, and −3.8-dB (−8.1 dB after detection losses correction) intensity difference squeezing degree is measured in the time domain. Our result is beneficial for generating multi-mode entangled state by time-division multiplexing in fiber system.
Band-Structure-Engineered Electronic-Photonic Nonlinear Activation Functions

Fast, sensitive, and compact devices that implement nonlinear activation functions are needed to form fully connected photonic neural networks (PNNs). However, even in highly nonlinear media, optical nonlinearities are relatively weak. We propose here a scheme for implementing nonlinear activation functions that relies on band-structure-engineered nanostructures. This scheme realizes the smallest possible hybrid optoelectronic approach, relying on fast electronic processes to implement nonlinearity instead of a true optical nonlinearity. Using well-established simplified density-matrix models, we demonstrate architectures that exhibit a low-intensity threshold of $3.5\phantom{\rule{0.2em}{0ex}}\ensuremath{\mu}\mathrm{W}$ along with a fast optical response of 10 ps in a relatively small linear footprint of $4\phantom{\rule{0.2em}{0ex}}\ensuremath{\mu}\mathrm{m}$. We also show that PNN training performance is improved in handwritten pattern recognition when applying our simulated nonlinear activation function, indicating potential for creating deep fully connected PNNs.
EE92 Economic Evaluation of Isavuconazole Versus Voriconazole for the Treatment of Patients With Possible Invasive Aspergillosis in the Brazilian Private Healthcare System

In 2019, isavuconazole was approved in Brazil by ANVISA for the treatment of invasive aspergillosis (IA) and invasive mucormycosis (IM). The primary objective was to assess the cost-effectiveness of isavuconazole compared to reference voriconazole for suspected IA in the Brazilian Private Healthcare System (PHS). The secondary objective was to assess the price impact in an economic evaluation of generic voriconazole versus isavuconazole without discount on list price, and generic and reference voriconazole with a 60% discount.
Installing Ubuntu

All things considered, installing an operating system should really be difficult and arcane. It controls your computer. After starting everything up, it loads the drivers, runs every program, orchestrates how software and hardware work together, provides the computer-user interface, and determines how you will work with your machine.
Ethics and legal regulation of using large databases in medicine

Use of information technologies in medicine resulted in formation of large databases. Analysis of large databases allows to reveal the patterns between the environmental conditions, a way of life and morbidity, that promote a progressive study of pathogenesis, clinical course, disease prognosis, and accelerate clinical trials of novel treatment options. Large databases are most in demand in bioinformatics and biomedicine. The issues of using large databases are associated with a number of ethical issues such as confidentiality, informed consent, and privacy. Ethical issues of using personal medical data were reflected in international documents. The use of large databases is associated with a dilemma of legislative protection of patients’ rights, on the one hand, and a decrease in analytical capabilities of using the data, on the other hand. Several methods of medical data safety are suggested to prevent identification of patients. Depersonilized data belong to one way of solving the issues. The options of studying secondary medical data are being discussed.
Supplemental Material: Phanerozoic cratonization by plume welding

&lt;p&gt;Geophysical compilation and details for magnetic inversion, lithospheric structure, and seismic-based interpretation. &lt;/p&gt;
A Perceptual Evaluation of the StyleGAN2-ADA Generated Images of Translucent Objects

Translucent materials have a wide variety of appearances due to variability of scattering, geometry, and lighting condition. Most previous studies used rendered images as stimuli. However, it is challenging to acquire accurate physical parameters to render materials with realistic appearance. Here, we investigate to what extent Generative Adversarial Networks (GANs) trained on unlabeled photographs of translucent materials can produce perceptually realistic images and achieve diverse appearances, without knowing about the physical parameters. We created a dataset of 3000 photographs of soaps with a variety of translucent appearances. The images were trained with StyleGAN2-ADA, a generative network that is trained on limited data with data-augmentation. We then conducted human psychophysical experiments to measure the perceived quality of the model’s output. In Experiment 1, we sampled 250 images from the real photographs and another 250 from the generated images, and asked observers to judge whether the soap in the image is real or fake after a brief 300ms presentation. In Experiment 2, observers rated the level of translucency of the material for the same 500 images on a 5-point-scale. Ten observers sequentially completed both experiments. We find observers can correctly judge the vast majority of real photographs (73% of the real images are correctly judged by at least 9 observers) but they make substantial mistakes for the generated images (60% fake images are falsely judged to be real by at least 2 observers and 7% fake images are falsely judged by more than 5 observers). Second, observers can discriminate a range of translucency from the generated images from opaque to transparent, similar to that of the real photographs. Our results suggest StyleGAN2-ADA has the potential to learn a representation of translucent appearances similar to that of humans, and it is useful to explore its latent space to disentangle the material-related features.
Automatic generation of semantic feature norms of objects using GPT-3

Semantic features are an essential part in the study of human knowledge about objects and have been playing an important role in understanding the role of semantics in object representations. Existing semantic feature norms have been produced by human participants and require extensive manual curation by experimenters. This process is not only time consuming and costly - humans are also known to omit important features. Recent advances in Natural Language Processing have led to large language prediction models that yield impressive performance in various language tasks. Here we asked to what degree recent language models can be used to automatically produce feature norms for arbitrary object concepts. To test this, we probed GPT-3 to generate semantic features for 1,854 objects from the THINGS database, using three human-generated examples as training data. Mirroring experimental approaches that merge data across human participants, we collected 30 runs, each finetuned with different example sentences. For better comparability to humans, we automatically preprocessed and normalized generated features. In comparison to existing norms, GPT-3 generated a broader set of features than humans, yet showed strong representational similarities with existing norms, highlighting their overall external validity. When predicting independent human similarity judgments and superordinate object categories, GPT-3 was competitive with human judgments. Explained variance in similarity judgments was mostly shared between human ratings and GPT-3, demonstrating that both humans and GPT-3 rely on similar conceptual information for producing object features. Together, our results demonstrate that semantic feature norms can be generated automatically using GPT-3 with comparable quality to human judgments. Further, we provide a new broad feature norm of 1,854 objects which may help improve our understanding of object knowledge and object representations. Finally, these results offer a new approach for comparing knowledge learned by humans to knowledge in language models.
Omit Needless Words: Sentence Length Perception

Introduction: Most measures of text readability quantify sentence length. Short sentences typically promote readability, and therefore inclusiveness. Omitting needless words from one’s own writing entails skimming the text for long sentences (targets) among short sentences (distractors) -a visual search task followed by a numerosity task. Do these tasks depend on perceptually learned global text orientation? Method: Before collecting data I pre-registered the hypotheses, predictions, methods, and statistical power analysis on the Open Science Framework ( https://osf.io/3k5cn ). Subsequently, the web-participant service “Prolific” recruited 88 adults who reported English as their first language and completed the experiment online using the pavlovia.org platform. Each trial began with a 2-second presentation of a text page containing one bolded sentence among numerous non-bolded sentences. Across trials, the text appeared either in standard orientation (like the page you are reading now) or flipped (upside down or mirror reversed). Participants judged whether the bolded sentence contained more or fewer than 17 words. Results & Conclusion. The experiment generated four findings. First, naive participants showed excellent precision in judging sentence length: thresholds approximated 1.3-word fluctuations around a 17-word mean sentence length (Weber Fraction = ~7.4%). Second, the precision and speed of sentence length judgments remained virtually unchanged after flipping standard-orientation-text either vertically or horizontally. Third, error patterns indicated that participants estimated sentence length by counting the lines of text rather than by counting individual words. This "chunking" strategy has the advantage of bringing sentence-length estimates into the subitizing range: 1 to 3 lines versus 10 to 24 words. Fourth, interleaving standard text and upside down text had no effect on response biases. However, interleaving standard text and mirror-reversed text significantly biased participants toward underestimating sentence length in both conditions. The specificity of this underestimate provides evidence for a laterally anchored scene syntax in visual search (Wolfe, 2021).