Technical Tools Research Articles

Super-resolution spectroscopy via spectrum slicing with a Fabry–Perot cavity

Spectroscopy is one of the most powerful technical tools that are widely used in the study of natural sciences and the development of high technologies. To improve the performance of a traditional dispersive spectrometer, there is a competition between its spectral resolution and the geometric volume; a higher resolution is usually accompanied by a higher cost as well. However, a growing body of evidence suggests an urgent demand for miniaturized spectrometers with high spectral resolution and low costs. In this paper, we propose and study super-resolution spectroscopy via spectrum slicing by use of a Fabry–Perot (FP) cavity combined with a traditional spectrometer. The cavity functions as a spectral filter to slice into discrete pieces the continuous spectrum of the input light. For each given cavity length, the cavity outputs a set of sliced spectral pieces that are then analyzed and recorded by the subsequent spectrometer. By scanning the cavity length, one will have multiple sets of sliced spectral pieces that are then finally fused to recover a resolution-enhanced copy of the input spectrum. A theoretical analysis for the super-resolution spectroscopy is provided to prove the feasibility of the proposal, as further confirmed by MATLAB numerical simulation. The studied spectral analysis technique will benefit the research fields in need of high resolution spectrometers with moderate device volumes and low costs.

Folk Omens about the Weather: Specificity of Form and Syntactic-stylistic Peculiarities

The paper analyzes the genre of peasant omens about the weather, which is the least investigated in folklore. The purpose is to explore the specifics of the language of folk poetic style using the example of German folk omens about the weather. The main technical tools and stylistic means that are used when creating this type of text are discussed.

Advanced Magnetocaloric Materials for Energy Conversion: Recent Progress, Opportunities, and Perspective

AbstractSolid‐state caloric effects as intrinsic thermal responses to different physical external stimuli (magnetic‐, uniaxial stress‐, pressure‐, and electric‐fields) can achieve a higher energy efficiency compared with traditional gas compression techniques. Among these effects, magnetocaloric energy conversion is regarded as the best available alternative and has been exploited extensively for promising application scenarios in the last decades. This review systematically introduces the magnetocaloric effect and its applications, and summarizes the corresponding representative magnetocaloric materials, as well as important progress in recent years. Specifically, the review focuses on some key understandings of the magnetocaloric effect by utilizing state‐of‐the‐art technical tools such as synchrotron X‐ray, neutron scattering, muon spin spectroscopy, positron annihilation spectroscopy, high magnetic fields, etc., and highlights their importance toward advanced materials design and development. An overview of the basic principles and applications of these advanced techniques on magnetocaloric materials is provided. Finally, the challenges and perspectives on further developments in this field are discussed. Further in‐depth understanding and manufacturing technology advancement combined with fast‐developed artificial intelligence and machine learning are expected to advance the magnetocaloric energy conversion technology closer to real applications.

Conducting Forensic Multidisciplinary Examinations and Sets of Forensic Examinations Using Specific Expertise in Economics

The quality of forensic examination depends on a forensic expert’s qualification and his/her in-depth and responsible research on objects, the investigation of which arose during pre-trial investigation or trial. Currently, expert methodologies for conducting multidisciplinary forensic economic examinations and sets of forensic examinations require improvement, especial-ly in light of wartime conditions. Multidisciplinary examination reflects contemporary theoretical trends by integrating legal norms into practical application to address urgent tasks in pre-trial investigations and court proceedings. The most efficient approach is to use a set of methods and technical means that give rise to new branches of scientific knowledge, determine the regularities of their practical significance, and establish interdisciplinary links. At the same time, multidisciplinary examination demonstrates high efficiency and broad possibilities through the combined and synthesized application of knowledge from diverse scientific fields and technical tools in addressing tasks assigned to a forensic expert. Sequential conduct of various types of forensic examinations during the resolution of multidisciplinary tasks in some cases ensures the reliability of expert conclusions and optimizes the judicial process. Multidisciplinary examination conclusions have a varied impact on the decisions made by the parties to the dispute. Therefore, improving the methodology of conducting multidisciplinary forensic examinations or sets of forensic examinations during the resolution of complex issues, which often arise in conditions of martial law, is relevant. This allows for the determination of unified approaches to addressing problematic aspects of such research.

Psychophysiological Research and its Place in the Lithuanian Scientific Discourse

This article gives a brief overview of the development of psycho-physiological research using the polygraph. The main focus is on the legal regulation of these methods and the evaluation of the scientific discourse of Lithuanian specialists on the problems of psychophysiological research and the application of its methods in comparison with analogous processes in Poland. Already in the inter-war period, so-called lie detection attracted considerable interest, not only from the academic world, but also from law enforcement authorities. In interwar Lithuania, considerable attention was paid to the psychology of testimony and the problems of lie detection, including the apeplication of instrumental methods of psychodiagnostics. V. Lazerson, J. Vabalas-Gudaitis, B. Kalvaitis and others have written about it. It should be noted that at that time there were quite heated debates about the permissibility and effectiveness of psychophysiological tests. During the Soviet era, the issue of psychophysiological (poly-graph) examinations was not the subject of an official broad scientific discourse in the jurisdictional process, even though medical and psychological professionals cooperating with special services were interested in this issue. After the restoration of independence in 1990, the Lithuanian media interest in this issue prompted the law enforcement authorities and their specialists and scientists to look deeper into the possibility, reliability, permissibility and effectiveness of the use of these technical diagnostic tools in foreign countries, as well as into their compatibility with the Lithuanian law in the investigation of crimes. In this article, some aspects of psychophysiological tests using the polygraph in Poland have been analysed for comparison purposes, which in the neighbouring country have attracted considerably more attention, both in the academic world as well as among lawyers and representatives of law enforcement agencies.

Big Data Education Landscape for Graduates in Morocco: Insights from 2022 Offerings

The main objective of this research was to analyze graduate programs in Big Data in Morocco in 2022, focusing on the technical skills, tools and technologies, and functional skills taught in the programs. In the digital age, the Big Data revolution has generated massive amounts of data, transforming the way businesses and organizations around the world make decisions and innovate. In this ever-changing context, Training of Big Data professionals in Morocco in 2022 is crucial. The expansion of Big Data has created a growing need for skilled professionals to manage these immense data sets. Higher education programs play a key role in preparing these future experts. This study adopted a content analysis methodology, examining the curricula of 16 public engineering schools, and 21 accredited public schools and science faculties in Morocco. The technical skills, tools and technologies, and functional skills taught were analyzed and compared with existing literature on Big Data skills. The programs focus on technical skills such as programming, machine learning, statistics, and mathematics, with Python as the main tool. However, certain skills, such as predictive analysis, are under-represented. Functional skills in communication and management are essential; however, skills in agile methods and change management vary in coverage. The results offer an insight into the alignment between higher education programs and the needs of the Big Data market. Educational institutions can adjust their programs to better meet emerging needs, focusing on under-represented skills, and ensuring the continued relevance of training.

Agrarian and $$\ell ^2$$-Betti numbers of locally indicable groups, with a twist

AbstractWe prove that twisted $$\ell ^2$$ ℓ 2 -Betti numbers of locally indicable groups are equal to the usual $$\ell ^2$$ ℓ 2 -Betti numbers rescaled by the dimension of the twisting representation; this answers a question of Lück for this class of groups. It also leads to two formulae: given a fibration E with base space B having locally indicable fundamental group, and with a simply-connected fiber F, the first formula bounds $$\ell ^2$$ ℓ 2 -Betti numbers $$b_i^{(2)}(E)$$ b i ( 2 ) ( E ) of E in terms of $$\ell ^2$$ ℓ 2 -Betti numbers of B and usual Betti numbers of F; the second formula computes $$b_i^{(2)}(E)$$ b i ( 2 ) ( E ) exactly in terms of the same data, provided that F is a high-dimensional sphere. We also present an inequality between twisted Alexander and Thurston norms for free-by-cyclic groups and 3-manifolds. The technical tools we use come from the theory of generalised agrarian invariants, whose study we initiate in this paper.

Recent Advancements in Inverse Reinforcement Learning

Inverse reinforcement learning (IRL) has seen significant advancements in recent years. This class of approaches aims to efficiently learn the underlying reward function that rationalizes the behavior exhibited by expert agents, often represented by humans. In contrast to mere behavioral cloning, the reconstruction of a reward function yields appealing implications, as it allows for more effective interpretability of the expert’s decisions and provides a transferable specification of the expert’s objectives for application in even different environments. Unlike the well-understood field of reinforcement learning (RL) from a theoretical perspective, IRL still grapples with limited understanding, significantly constraining its applicability. A fundamental challenge in IRL is the inherent ambiguity in selecting a reward function, given the existence of multiple candidate functions, all explaining the expert’s behavior. In this talk, I will survey three of my papers that have made notable contributions to the IRL field: “Provably Efficient Learning of Transferable Rewards”, “Towards Theoretical Understanding of Inverse Reinforcement Learning”, and “Inverse Reinforcement Learning with Sub-optimal Experts". The central innovation introduced by the first paper is a novel formulation of the IRL problem that overcomes the issue of ambiguity. IRL is reframed as the problem of learning the feasible reward set, which is the set of all rewards that can explain the expert’s behavior. This approach postpones the selection of the reward function, thereby circumventing the ambiguity issues. Furthermore, the feasible reward set exhibits convenient geometric properties that enable the development of efficient algorithms for its computation. Building on this novel formulation of IRL, the second paper addresses the problem of efficiently learning the feasible reward set when the environment and the expert’s policy are not known in advance. It introduces a novel way to assess the dissimilarity between feasible reward sets based on the Hausdorff distance and presents a new PAC (probabilistic approximately correct) framework. The most significant contribution of this paper is the introduction of the first sample complexity lower bound, which highlights the challenges inherent in the IRL problem. Deriving this lower bound necessitated the development of novel technical tools. The paper also demonstrates that when a generative model of the environment is available, a uniform sampling strategy achieves a sample complexity that matches the lower bound, up to logarithmic factors. Finally, in the third paper, the IRL problem in the presence of sub-optimal experts is investigated. Specifically, the paper assumes the availability of multiple sub-optimal experts, in addition to the expert agent, which provides additional demonstrations, associated with a known quantification of the maximum amount of sub-optimality. The paper shows that this richer information mitigates the ambiguity problem, significantly reducing the size of the feasible reward set while retaining its favorable geometric properties. Furthermore, the paper explores the associated statistical problem and derives novel lower bounds for sample complexity, along with almost matching algorithms. These selected papers represent notable advancements in IRL, contributing to the establishment of a solid theoretical foundation for IRL and extending the framework to accommodate scenarios with sub-optimal experts.

QUESTIONS IN HISTORIOGRAPHY FROM THE NINETEENTH CENTURY TO THE AGE OF GENERATIVE AI

ABSTRACTHistory theory does not have a mature theory of questions. This reflects both historical and philosophical assumptions. As Holly Case has argued in The Age of Questions (2018), the big questions of the nineteenth century and their proposed final solutions arguably primed the murderous logic of genocide in the first half of the twentieth century. On her account, questions have become tamed as technical tools in historical monographs and reviews like this one. This picture of the twentieth century, though, runs up against R. G. Collingwood's historiographical logic of questions and the rise of erotetic logics in computer science. Computational erotetic logics have shaped the creation of large language models such as the GPT series and focused our attention on expressivity, effectivity, and classification in the relation of questions and answers. Collingwood's logic is different, using the relation of questions to questions to point to presuppositions. This metaphysical view of erotetic logic is timely, for it reminds why it might be so hard for historians to cut through with true propositions in an age of AI. Collingwood reminds us that a focus on truth‐evaluable answers to questions does not explain why those questions were asked in the first place. Chasing chains of questions back to presuppositions, Collingwood argues that tackling what is assumed and what is lived with can help historians to change an unthinking world. In our age, this includes the idea of a shift from historians being the users of large language models to historians being the designers of new forms of relationship between people and information.

Genetic diversity of grain yield traits and identification of a grain weight gene SiTGW6 in foxtail millet.

Agronomic traits were evaluated in 1250 foxtail millet accessions, and a crucial gene SiTGW6 governing grain yield was identified. Elite haplotypes and dCAPS markers developed for SiTGW6 facilitate molecular breeding. A comprehensive evaluation of phenotypic characteristics and genetic diversity in germplasm resources are important for gene discovery and breeding improvements. In this study, we conducted a comprehensive evaluation of 1250 foxtail millet varieties, assessing seven grain yield-related traits and fourteen common agronomic traits over two years. Principal component analysis, correlation analysis, and cluster analysis revealed a strong positive correlation between 1000-grain weight and grain width with grain yield, emphasizing their importance in foxtail millet breeding. Additionally, we found that panicle weight positively correlated with 1000-grain weight but negatively correlated with branch and tiller numbers, indicating selection factors during domestication and breeding. Using this information, we identified 27 germplasm resources suitable for high-yield foxtail millet breeding. Furthermore, through an integration of haplotype variations and phenotype association analysis, we pinpointed a crucial gene, SiTGW6, responsible for governing grain yield in foxtail millet. SiTGW6 encodes an IAA-glucose hydrolase, primarily localized in the cytoplasm and predominantly expressed in flowering panicles. Employing RNAseq analysis, we identified 1439 differentially expressed genes across various SiTGW6 haplotypes. Functional enrichment analysis indicating that SiTGW6 regulates grain yield through the orchestration of auxin and glucan metabolism, as well as plant hormone signaling pathways. Additionally, we have identified elite haplotypes and developed dCAPS markers for SiTGW6, providing valuable technical tools to facilitate molecular breeding efforts in foxtail millet.

Особенности проведения осмотра места происшествия при расследовании преступлений, связанных с применением запрещенных средств и методов ведения войны

The article deals with organizational issues of conducting an inspection of the scene of the incident in the investigation of crimes related to the use of prohibited means and methods of warfare. Based on the analysis of forensic investigative practice and own practical experience, an algorithm for conducting an inspection of the scene of the incident is proposed, its tactical and forensic aspects are disclosed, a list of necessary technical and forensic tools is outlined, and recommendations are given for detecting, fixing, removing and packing traces and objects found during an inspection of the scene of the incident during the investigation of these crimes.

Социальный спрос на уголовно-правовую охрану исторического и культурного наследия как фактор, оказывающий влияние на уголовно-правовую политику в указанной сфере

The article is devoted to the social demand for criminal law protection of historical and cultural heritage, which, in systemic unity with other factors listed in the publication, has had and continues to have a direct impact on criminal law policy in this area. When revealing the content side of social demand, the author suggests using the term historical and cultural complementarity. Thanks to him, a social assessment of existing criminal law prohibitions can be given, the contradictory attitude of the law enforcement officer to the protection of historical and cultural monuments and cultural values can be explained. Using the example of criminalization of illegal search and seizure of archaeological objects from places of occurrence (art. 2432 of the Criminal code), attention is drawn to the lack of social demand for legal regulation of the activities of persons using special technical search tools (metal detectors) and engaged in illegal search for archaeological objects.

Educational and Technical Tools for Developing Students' Creativity in Computer Lessons

In the modern post-industrial society, the problem of developing creative abilities of students using information technologies is especially relevant. At the moment, society needs specialists who can think differently, find creative solutions to problems, and skillfully work with information. The problem of studying the phenomenon of creativity is not new. Many researchers have presented this problem in different interpretations.

Low-altitude remote sensing-based global 3D path planning for precision navigation of agriculture vehicles - beyond crop row detection

Field path planning provides the basis for the autonomous navigation of agricultural vehicles. Existing path planning approaches are constrained to a 2D plane, disregarding the impact of terrain factors on navigation tasks. Furthermore, these methods generate non-global paths, as evidenced by their inability to accommodate the headland turning area while performing path planning based on the actual crop growth in the farmland. Low-altitude remote sensing technology, characterized by its high spatial resolution, timely data acquisition, and strong terrain perception, holds great potential for application in autonomous navigation. This study aims to integrate low-altitude remote sensing technology with path-planning tasks for agricultural vehicles by constructing oblique photography models of fields. The objective is to achieve global 3D path planning leveraging advanced methodologies rooted in deep learning and image processing. Four main steps were included in the proposed method. Low-altitude remote sensing models of field blocks were constructed first. Secondly, the models were converted to image patches for dataset establishment. Thirdly, primary crop row identification was conducted by semantic segmentation. Finally, global 3D paths covering the farmland and headland areas were generated. Tea fields in hilly areas were used to test the algorithm. Experiments revealed that the proposed method could be adapted to different field shapes, row numbers, row spacing, and vehicle turning radii. The proposed method uses deep learning and image processing as the primary technical tools but goes beyond traditional crop row detection to form a global path-planning strategy. In addition, the elevation information enabled by the 3D detection manner allows agricultural vehicles to gain a comprehensive understanding of both their own position and that of their destination. The dataset and the code are available at: https://github.com/ZeroHeading/Global-3D-path-generation.git.

Relazioni familiari e migrazioni tra diritto, religioni e culture


 
 
 Family relationships and migrations between law, religions and culture
 ABSTRACT: In recent years, the social and multi-religious evolution of the family has contributed to redefined its morphology, varying its traits through a continuous work of cultural, ethnic and religious relocation. It frequently clashes with resistance typical of an institution that is in some ways still linked to traditional legal paradigms. It is consequently increasingly necessary to acquire technical tools that allow people to govern family relationships in the current “multicolor” context. The essay investigates the possibility of leaving ample space for private autonomy in the regulation of family relationships in the belief that in this way families are provided with flexible tools that conform to their own cultural and religious identity.
 SOMMARIO: 1. Dalla famiglia alle famiglie - 2. Le relazioni familiari multicolor - 3. La famiglia e i modelli cultural-religiosi - 4. I diritti religiosi come “argine” alla derivazione di alcuni modelli di famiglia - 5. La famiglia: dal totale dirigismo all’autonomia parziale.
 
 

Catalysis in action via elementary thermal operations

We investigate catalysis in the framework of elementary thermal operations (ETOs), leveraging the distinct features of such operations to illuminate catalytic dynamics. As groundwork, we establish new technical tools that enhance the computability of state transition rules for ETOs. Specifically, we provide a complete characterisation of state transitions for a qutrit system and special classes of initial states of arbitrary dimension. By employing these tools in conjunction with numerical methods, we find that by adopting a small catalyst, including just a qubit catalyst, one can significantly enlarge the set of state transitions for a qutrit system. This advancement notably narrows the gap of reachable states between ETOs and generic thermal operations. Furthermore, we decompose catalytic transitions into time-resolved evolution, which critically enables the tracking of nonequilibrium free energy exchanges between the system and bath. Our results provide evidence for the existence of simple and practicable catalytic advantage in thermodynamics while offering insight into analysing the mechanism of catalytic processes.

Materials and Climate Change: A Set of Indices as the Benchmark for Climate Vulnerability and Risk Assessment for Tangible Cultural Heritage in Europe

Among the issues most related to climate change, the built environment is also subjected to short- and long-term risks. Referring to tangible cultural heritage, materials and buildings are subjected to different types of damage that require adaptive risk prevention and containment strategies, currently missing from conventional risk assessments. Thus, there is an increasingly urgent need for scientific and technical knowledge, tools, and solutions aimed at solving critical issues in cultural heritage due to climate change. In this context, the aim of this study is to study the mechanisms of impacts brought about by climate change and the formulation of a possible set of indices as benchmarks to measure climate change’s effect on cultural heritage buildings. The study is structured on a methodology that identifies three sections: the first and second parts systematize and critically interpret data on impact mechanisms and indices for climate vulnerability and risk assessment; the third part, data processing, reports the perspective findings. The main intermediate indices, contributing to a comprehensive damage index, were identified, and a procedural protocol was developed. Finally, through the correlation of indices, a potential case study could be analyzed, and benchmarks made effective. The study reports partial results of one of the “Ecosystems of Innovation” pilot projects funded by the National Recovery and Resilience Plan. The study is still a work in progress and needs advancement and deepening to verify case study indices.

Navigating the technical analysis in stock markets: Insights from bibliometric and topic modeling approaches

In stock markets, technical analysis plays a vital role by offering valuable insights into price trends, patterns, and anticipated market movements, aiding investors in making well-informed decisions. This study employs bibliometric and topic modelling approaches on 589 English-language journal articles indexed in Scopus in the last two decades (from 2003 to 2023), exclusively focusing on technical analysis in stock markets. The keyword co-occurrence analysis identifies five topic clusters. The application of structural topic modelling also unravels five prominent thematic clusters, namely pattern-based forecasting, rule-based trading, algorithmic trading, techno-fundamental trading, and machine learning & sentiment analysis. The topic of pattern-based forecasting involves researching the application of various patterns or models to predict stock prices. Rule-based trading concentrates on utilizing technical analysis tools to generate buy and sell signals, aiming for profitability. The algorithmic trading cluster explores the use of algorithms to systematically execute buy and sell actions, especially in high-frequency trading scenarios. Techno-fundamental trading investigates the integration of both fundamental and technical analysis in trading and investment decisions. Lastly, machine learning & sentiment analysis focus on applying advanced machine learning techniques and sentiment analysis for predicting stock prices, highlighting the use of sophisticated methods in this domain. The three predominant topics in the dataset are "rule-based trading," "machine learning & sentiment analysis," and "algorithmic trading" constituting 26.79%, 23.52%, and 21.11% of the dataset, respectively. These findings underscore the prominence and significance of these themes within the context of the research domain.

Directions for improving the concept of technology for the purpose of financial support for their transfer within the European Union

The object of this study is the essence and directions of improvement of the normative construction of the concept of technology, which is used within the framework of legal regulation of financial support of the innovation process and technology transfer within the framework of the law of the European Union. In the course of summarizing and studying the existing regulations, it was established that they are not unified and differ significantly. This does not meet the needs of participants in the innovation process and subjects of technology transfer. It has been proven that the most negative impact of the disparity of legal regulation occurs during the implementation of means of financial support for innovative processes. The expediency of improving the existing concept of technology definition by fixing its single generalized definition has been substantiated. Authentic definition of technology is proposed as information of an organizational and technical nature about the sequence of production operations, which can be expressed in the form of the results of scientific research, research and design works, a system of objects of intellectual property rights, information of an organizational and technical nature, technological documentation, equipment, tools, machines, and mechanisms. It was substantiated that this definition makes it possible to eliminate most of the identified problems and is formed on the basis of the existing needs of the participants of technology transfer. The study is aimed at the formation of general theoretical foundations for improving the essence of technology for the purposes of legal support for financial support of innovation processes and technology transfer in the European Union. The research results could be used in the formation of international normative acts, acts of national legislation, and serve as a basis for further scientific research on these issues

Towards ultra-low-cost smartphone microscopy.

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here, we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ∼9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ∼5 𝜇m, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we used an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We used the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. RESEARCH HIGHLIGHTS: We propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of ∼5 𝜇m. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.