Reviewerly/exHarmony huggingface dataset:
[de]Territorialization, the Role of our Brain in a Technological World.

Since the turn of the 20th century, the act of design has gone through an exercise of problem-solving. It happened in the field of the city, architecture, or objects. Much of this discourse is present in the modernist manifestos. These goals are primarily related to Russian constructivism, in which many modern personalities were engaged. This problem-solving process, oriented toward an economic practice that articulated the available means to the proposed ends, was so necessary to the revolutionary spirit of the time. However, they answered the questions that the post-Russia zeitgeist of the Revolution intended to answer. The articulation of their intended function, coupled with the emergence of their utility, entrusted them with a good and abstract character in the city.However, in its genesis, the project contains much more than that. It cannot be merely the functional resolution of a problem. It must have the instability of that problem in its course, which becomes changeable in the search for the solution. As a result, the merely utilitarian character thus loses its initial grip. As Roger Scruton argues, the definition of a project methodology is complex if a method is indeed the correct word to use in the process. The method, that is, a path composed of specific tools to achieve a purpose, seems to us little convergent with the themes that should flow. To start from this assumption is to invalidate what we previously described as a fundamental part of the process of memory, which should have a high place in the project process. The design process is, in essence, the transit between the identification of a problem until it resolves (one, among many possible ones). To which we allude, it does not refer only to the project in Architecture but to a whole system that involves not only objects but also cities, in what we can understand as relationships with the body. More than a mere technical process, it involves an empirical component based on experience, which we define as physical and intellectual. The act of design, or project, must contain in its origin the state of emptiness, without preconceptions, that gag it. This state, which we wish to bring into discussion, is nothing more than the full potential of the task we want to accomplish.
A Platform for Offline Voice Assistants

Smart speakers provide a convenient way to request information or control the smart home. Commercial devices require central services operated by large companies. As a result, many users are concerned about privacy and security. A solution could be to shift all involved software components to the end-user device. Even though we then cannot access the large variety of functions of commercial smart speakers, they often are sufficient for common applications such as weather forecast, public transportation timetables or to control smart home devices. Even though existing voice interaction platforms already provide basic functions such as wake word detection and speech recognition, a developer still has to put huge efforts to create smart speaker applications. In this paper we present the JabberBrick platform that significantly simplifies such developments.
Design of Rural Public Cultural Activity Space

Rural public cultural activity space is an important space for villagers to communicate with neighbors. It is also the main place for villagers to conduct daily communication and participate in public affairs. However, at the time of rural development and construction, there has been a situation of integration of rural community space construction and urban space construction. Faced with these problems, this article takes Jinxing Village in China as an example. Starting from the cultural needs of community residents, this article conducts a specific investigation, research and analysis of the current situation of the use of public cultural activity space, in order to deeply explore the public cultural activities and community activities of community residents. It also provides reference and ideas for the design and renewal of other rural public cultural spaces.
Progress, open questions and application prospects of analytical techniques for refractory elements and representative radioisotope systems

Pt-Os、Re-Os和Hf-W同位素体系的母体和子体Pt、Os、Re、Hf和W以及其它铂族元素（PGE）化学性质上都是难熔的，我们将这些元素和相关同位素称为难熔元素和难熔元素放射性同位素体系。难熔元素及其放射性同位素体系不仅可以直接测定金属矿床、油气藏和沉积岩系的年龄，而且还可以有效示踪地球深部的核幔反应等过程，这是其它地球化学工具不可替代的。本文评述了当前Pt-Os、Re-Os和Hf-W同位素体系和PGE元素分析技术的研究进展，指出：（1）目前Re-Os同位素定年误差仍较大，迫切需要优化改进分析技术，大幅提高Re-Os同位素定年的准确度和成功率；（2） Pt-Re-Os和W同位素的分析技术需要简化繁琐的化学分离流程和提高仪器分析的效率，同时探索建立新的化学分离和仪器分析方法，进一步提高分析精度，实现对更低Pt、Re、Os和W含量样品的准确分析，才能更有效地示踪地球深部物质循环过程；（3） PGE的元素分析技术尚需改进，分析精度仍需要进一步提升。我们预期随着进一步提升难熔元素和代表性放射性同位素的分析精度，显著降低同位素定年误差，其将在核-幔、幔-幔和壳-幔物质循环过程示踪、金属矿床精细定年和成因机制、复杂含油气系统的定年和示踪以及中元古代环境变化等研究中得到更广泛的应用。
Model Pruning

Deep learning models have reached significant success in many real-life problems. A lot of devices use neural networks to perform everyday tasks. However, complex neural networks are computationally expensive. And not all devices have GPU processors to run deep learning models. Therefore, it would be helpful to perform model compression methods to reduce the model size and accelerate model performance without losing accuracy significantly. One of the main model compression techniques is model pruning. Pruning optimizes the model by eliminating some model weights. It can eliminate a significant amount of model weights with no negligible damage to model performance. A pruned model is lighter and faster. Pruning is a straightforward approach that can give nice model speedup results.
The Impact of Large Financial Incentives on C-Section Rates: Evidence from Iran

Iran has long had one of the highest Caesarean section (C-section) rate in the world. In 2014, the Iranian Ministry of Health and Medical Education (MHME) created substantial financial incentives discouraging the use of C-sections in public hospitals, by increasing physician payments and eliminating patient co-payments for vaginal deliveries. The MHME subsequently extended a modified version of the physician-level incentives (but not the patient-level incentives) to non-public hospitals. We use difference-in-differences (DiD) regression analysis to examine the impact of these reforms on the rate of C-sections and health outcomes in public and non-public hospitals. We find evidence of statistically and economically significant effects; C-section rates in public hospitals declined by almost 5%, with no evidence of adverse health effects. As expected, we find higher reductions for 1st time mothers, and smaller reductions for mothers with clinical indications of higher-risk pregnancies (e.g., hypertension and diabetes). Physician-level incentives explain roughly two-thirds of the decline, and patient-level incentives explain most of the rest.
The Machine Learning Principles Based at the Quantum Mechanics Postulates

Quantum mechanics is governed by well-defined postulates by the which one can go through either theory or experimental studies in order to perform measurements of microscopic dynamics of elementary particles, atoms and molecules for instance. By knowing the Tom Mitchell criteria inside Machine Learning, then one can wonder about the postulates of Quantum Mechanics in the entire picture of Mitchell criteria. This paper tries to answer this question. In essence it is focused on the role of brackets formalism and how it makes more feasible to project the ground principles of Quantum Mechanics in the arena of Machine Learning and Artificial Intelligence.
Emotion Recognition for Individuals with Autism

Individuals suffering from Autism Spectrum Disorder find it challenging to perceive basic human emotions, which deters their communication capabilities. Given this difficulty, we proposed a Kawaii-engineered framework for Individuals with Autism by developing a Machine Learning pipeline using multilabel classification algorithms to identify the emotions from a video. We experimented on two datasets OMGE and DIAEMO. Both datasets have videos of the duration of approximately one minute. After pre-processing, facial expressions and audio content-based features were extracted. Multilabel Classification algorithm like Instance Based Learning by Logistic Regression for Multi-Label Learning, Multi Label k- Nearest Neighbour, Binary Relevance k- Nearest Neighbour, Random k- Label Sets, and Calibrated Label Ranking were used and for sampling, 5-fold Cross-Validation and Leave One Out Cross Validation were employed for both the datasets. We observed that LOOCV based sampling strategy gave the best results for both the datasets with CLR classifier using Gaussian kernel.
Smartphone Data Distributions and Requirements for Realistic Mobile Device Forensic Corpora

Mobile devices such as smartphones are carried and used constantly by people in their daily lives and, therefore, play important roles in forensic investigations. As a result, digital forensic professionals are confronted with large numbers of devices with data that has to be extracted and analyzed. The education and training of forensic experts and the development and evaluation of smartphone forensic tools require copious amounts of realistic data. Unfortunately, secrecy and privacy considerations limit the availability of real digital forensic data. Smartphone datasets for training and testing are sparse and unrealistic, and knowledge about data distributions in real smartphones is limited. This chapter presents the results of a survey of law enforcement professionals from two countries that sought to understand the typical data residing in smartphones encountered in criminal investigations, with the goal of supporting the creation of publicly-available forensic datasets. The typical data extracted from smartphones using current forensic tools is presented; this data is divided into two forensic classes, relevant and irrelevant. Additionally, the chapter discusses current problems encountered by mobile device forensic professionals and opportunities for future research.
Overview of Data Deduplication

Data deduplication is a lossless data compression technology. Deduplication eliminates redundant data by keeping only one physical copy that could be referenced by other duplicate data (copies), which reduces storage cost and network bandwidth. Section 2.1 presents the principle and methods of data deduplication on different types. Section 2.2 describes the workflow and procedure of data deduplication. Section 2.3 describes some application scenarios of data deduplication. Section 2.4 presents the challenges of data deduplication.
The Impact of Test Positivity on Surveillance with Asymptomatic Carriers

Objectives: Recent studies show that Test Positivity Rate (TPR) gain a better correlation than incidence with the number of hospitalized patients in COVID-19 pandemic. Nevertheless, epidemiologist remain sceptical concerning the widespread use of this metric for surveillance, and indicators based on known cases like incidence are still preferred despite the large number of asymptomatic carriers which remain unknown. Our aim is to compare TPR and incidence, to determine which of the two has the best characteristics to predict the trend of hospitalized patients in COVID-19 pandemic. Methods: We perform a retrospective study considering 60 cases, using global and local data from Italy in different waves of the pandemic, in order to detect peaks in TPR time series, and peaks in incidence, finding which of the two has the best ability to anticipate peaks in patients admitted in hospitals. Results: On average the best TPR based approach anticipates incidence of about 4.6 days (95% CI 2.8, 6.4), more precisely the average distance between TPR peaks and hospitalized peaks is 17.6 days (95% CI 15.0, 20.4) with respect to 13.0 days (95% CI 10.4, 15.8) obtained for incidence. Moreover, the average difference between TPR and incidence increases to more than 6 days in the Delta outbreak during Summer 2021, where presumably the percentage of asymptomatic carriers was larger. Conclusions: We conclude that TPR should be used as primary indicator to enable early intervention and for planning hospitals admissions in infectious diseases with asymptomatic carriers.Funding: None to declare. Declaration of Interest: None to declare.
The Shape Model of Ceramic Products Based on 3D Image Reproduction Technology

With the development of computer technology, three-dimensional spatial data has become a mainstream trend. In industrial design, the use of two-dimensional or four-dimensional projection to simulate and reconstruct the surface of ceramic products can reduce a lot of unnecessary troubles. At the same time, the ceramic industry is China’s pillar industry. With economic globalization and the acceleration of the international trade process, ceramic products play an increasingly important role in the international market. Due to factors such as technical level, production scale, and product quality, most domestic enterprises are still stuck in a simple and extensive business model. In order to increase market share and enhance competitiveness and reduce costs, so that the company can obtain better benefits, it is necessary to continuously innovate and optimize product design and manufacturing processes to meet customer needs. This article uses experimental analysis and data analysis to better understand the performance of the model and the degree of deviation of the angle of the ceramic thin-walled parts through experiments. According to the experimental results, as the diameter of the extrusion head and the height of the extrusion layer change, the angle of the ceramic thin-walled part will also have a certain deviation. When the extruder diameter is 0.6 mm, the formability of the layer height under 0.4 mm is the best, the deviation value is the smallest, and the ceramic product has the highest precision.
Complex Relative Position Encoding for Improving Joint Extraction of Entities and Relations

Abstract Relative position encoding (RPE) is important for transformer based pretrained language model to capture sequence ordering of input tokens. Transformer based model can detect entity pairs along with their relation for joint extraction of entities and relations. However, prior works suffer from the redundant entity pairs, or ignore the important inner structure in the process of extracting entities and relations. To address these limitations, in this paper, we first use BERT with complex relative position encoding (cRPE) to encode the input text information, then decompose the joint extraction task into two interrelated subtasks, namely head entity extraction and tail entity relation extraction. Owing to the excellent feature representation and reasonable decomposition strategy, our model can fully capture the semantic interdependence between different steps, as well as reduce noise from irrelevant entity pairs. Experimental results show that the F1 score of our method outperforms previous baseline work, achieving a better result on NYT-multi dataset with F1 score of 0.935.
THE FIRST DATA FROM UYTENBOGAАRDITE IN THE ORE OF THE TASEYEVSKOYE GOLD-SILVER DEPOSIT IN EASTERN TRANSBAIKALIA (RUSSIA)

The relevance lies in the need to have complete data on the features of the mineralogy of the unique in terms of gold and silver content ores of shallow gold-silver formation deposits, one example of which is the Taseevskoye deposit in the Baleisky ore field in Eastern Transbaikalia. The purpose of the study is to determine the mineral composition of the rich gold-silver ores of the Taseevsky deposit. The object of the study is a hessite-uytenbogaardite-electrum-chalcopyrite-calcite-quartz mineral association. The subject of the study is the chemical composition and forms of isolation of uytenbogaardite. Method and methodology used are optical and electron microscopy with the determination of forms of precipitation and variations in the chemical composition of uytenbogaardite. The results are the following: for the first time, the rare Au and Ag sulfide uytenbogaardite was identified in the gold-silver ore of the Taseevskoye deposit, its chemical composition was determined, and it was found that it is in association with electrum, chalcopyrite, sphalerite, hessite, quartz, acanthite, cervelite, and petzite. Subspherical forms of aggregates predominate, less often lenticular and veinlets. The size of its crystals and their intergrowths is 0.005 - 0.5 mm. All crystals are nonstoichiometric. The content of the main chemical elements varies within (wt.%): Ag 52.43 - 64.76; Au 22.57 - 37.35; S 7.32 - 12.84. Among the studied individuals of uytenbogardite, three contain from 2.98 to 5.18% Te. Low grade Au, which is associated with uytenbogardite, contains from 43.32 to 56.42% Ag and is electrum by their ratio. Uytenbogaardite was found only in the upper part of the ore zone of the Taseevskoe deposit. This may be a typomorphic feature for determining whether the chalcedony-like quartz containing it belongs to the supra-ore zone of a deposit of a shallow gold-silver formation
Deeper into R Programming

In this chapter, we leave data analysis and return to programming and software development, topics that are the focus of the remaining chapters of the book. In the first chapter, you took a tutorial introduction to R programming, but we left out a lot of details. This chapter will cover many of those details, while the next two chapters will cover more advanced aspects of R programming: functional programming and object-oriented programming.
A Comparative Study of Various Traditional and Hybrid Cryptography Algorithm Models for Data Security

Information security involves various services like availability, cryptography, and integrity which help to protect data. Nowadays everyone store his/her important data on various cloud environments for easy access without much thinking of data privacy. Still most individual or many companies prefer to store their business or individual level information in computer but connected to Internet. There are well-known algorithms available which help to secure data by using some secret key. Hackers are simply capable to interrupt the key with the assistance of recent high end computing machines. Hence information needs to be secured in more powerful way that no longer to be abused by folks that aren't entitled to. The security of data can be increased by hybridization of these well-known algorithms. The paper provides the generic models of various hybrid cryptographic models which improves the security of data. The paper also provides the comparative study of various traditional and hybrid models used heavily for providing security to data. The hybrid model can provide enhanced security than AES and should be selected if extreme security is required.
An Improved Image Authentication Method Using QR Code Watermarking Approach

Despite the progress in digital watermarking technology by optimizing the embedding method and enhancing the robustness of watermarking, the performance can still be improved using the Quick Response (QR) code technology. This paper proposes an improved QR code image watermarking approach by embedding texture-based QR code watermarking into the digital image. In contrast to the existing methods, an improved perceptual hash algorithm is used to extract image texture features, and therefore enhance the relevance of watermarking with image content, especially in light color images. In addition, the QR code method is combined with the reversible watermark algorithm in order to handle the problem that the original image is irreversibly modified. The experiments demonstrate that the proposed method can efficiently enhance the watermarking robustness, and resists common attacks.
EDUCATING BOYS FOR STARTING AN INDEPENDENT FAMILY AS A PEDAGOGICAL NECESSITY

The article is devoted to one of the urgent problems of family pedagogy – the preparation of boys for family life on the basis of national traditions and their orientation in the profession. The methods of preparation taking into account the requirements of family education, as well as ways to achieve the correct organization of vocational training to prepare children for family life in educational institutions are clearly shown.
Increasing Listening Quality of Indonesian Language Lesson on 5<sup>th</sup> grade of SD N 1 Jelobo by Using <i>Quantum Learning</i> Methods

This research was motivated by the author in observing listening learning activities in class V SD NEGERI 1 JELOBO, the thing that attracted the author's attention was the use of learning methods used in listening to a text.The use of the method that the teacher uses according to the author does not make students focus on learning.In addition, the authors also found students who were less confident with the results of their respective work.This study aims to (1) describe the use of the quantum learning method in listening activities in Indonesian language learning in class V SD NEGERI 1 JELOBO, (2) describe the efforts made to improve the quality of listening learning for class 5 students at SD NEGERI 1 JELOBO KLATEN, (3) Identify the impact of using the quantum learning method in learning Indonesian.Data collection was carried out by observing and observing notes.This study is included in the study of classroom activities.This study uses an experimental method to investigate classroom activities.The results of this study are (1) applying the quantum learning method for listening in Indonesian research, (2) making an effort to improve the quality of learning, and (3) applying the effect on listening using the quantum learning method.
Developing the system of interrelated classifications: Comparing State Rubricator of Sci-tech Information to Web of Sciences domain classifiers

Building the single network of subject matches of the most popular classification systems is essential for information support of scientific research. The comparative analysis of the State Rubricator of Sci-tech Information (GRNTI) subject headings and Web of Sciences (WoS) Research Areas and Web of Science Categories was accomplished. The lists of subject research areas and categories are the most detailed and popular classifiers used by Clarivate for systematization. For today, GRNTI sections in social, natural sciences and STEM are analyzed and compared to WoS classifiers. Logical nesting and extension overlappitng represent the semantic links between classification headings.
Enhancing Decision Combination in Classifier Committee via Positional Voting

In this work, we propose an approach for aggregating classifiers using positional voting techniques. We extend the positional voting by optimizing weights of the preferences to better aggregate the committee classifiers. Staring from initial weights determined by a voting algorithm the aggregating weights are optimized by a differential evolution algorithm. The algorithm has been evaluated on a human action dataset. We demonstrate experimentally that on SYSU 3DHOI dataset the proposed algorithm achieves superior results against recent algorithms including skeleton-based ones.
Sentence Alignment of Bilingual Survey Texts Applying a Metadata-Aware Strategy

Sentence alignment is a crucial task in the process of building parallel corpora. Off-the-shelf tools for sentence alignment generally perform well to this end. However in certain cases, depending on factors such as the sentence structure and the amount of contextual information, the sentence alignment task can be challenging and require further resources that may be difficult to find, such as domain-specific bilingual dictionaries. Although investing in creating additional linguistic resources is frequently the chosen option in these circumstances, leveraging extra-linguistic information such as sentence-level metadata can be an easier alternative to narrow the alignment search space. This paper presents a method designed for the alignment of bilingual survey questionnaires’ texts, which leverages sentence-level metadata annotations. We build eight gold standards in four distinct languages to measure our sentence aligner performance, namely Catalan, French, Portuguese, and Spanish.