Large Set Of Tools Research Articles

THE ROLE OF ARTIFICIAL INTELLIGENCE IN MAKING FOREIGN POLICY DECISIONS IN THE UKRAINIAN-RUSSIAN WAR

The article considers the application of the artificial intelligence systems as a new tool in making foreign policy decision. The content of the concept of artificial intelligence is studied, the scope of the use of artificial intelligence systems in everyday life and in international relations is studied. It can be noted that AI, as a progressive and rapidly developing technology, has a large set of tools that help people make decisions and increase the efficiency of their work, for example, save time and spent resources to achieve a particular result. With the development of technology, more and more machines with artificial intelligence are used in various areas of life. For example, the field of medicine, mechanical engineering, data analysis, public administration and politics - all these fields are actively developing with using of artificial intelligence technologies. Special attention is paid to how artificial intelligence affects in making decision, event forecasting, and automation of data analysis. The use of artificial intelligence systems in international diplomacy was analyzed. Attention is focused on the weak and strong sides and what risks this technology can carry for foreign policy decisions. The given statistical data show how artificial intelligence is treated in Ukraine. Based on the research, it can be concluded that for the widespread use of artificial intelligence, it is necessary to develop convenient and transparent rules and algorithms, norms for the using of technology and its interaction with people. Summarizing the discussed topic, we will come to the conclusion that artificial intelligence will soon become a powerful tool in international relations, diplomacy, and in other areas of our life, which will bring benefit and a real threat. But in order for the benefit to be greater, it is necessary that the people who will use artificial intelligence be trained and knowledgeable in the technology.

Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculum

Augmenting large language models (LLMs) with external tools has emerged as a promising approach to extending the capability of LLMs. Although there are some works that employ open-source LLMs for the tool-learning task, most of them are trained in a controlled environment in which LLMs only learn to execute the human-provided tools. However, selecting proper tools from the large toolset is also a crucial ability for the tool-learning model to be applied in real-world applications. Existing methods usually directly employ self-instruction methods to train the model, which ignores differences in tool complexity. In this paper, we propose the Confucius a novel tool-learning framework to train LLM to use complicated tools in real-world scenarios, which contains two main phases: (1) We first propose a multi-stage learning method to teach the LLM to use various tools from an easy-to-difficult curriculum; (2) thenceforth, we propose the Iterative Self-instruct from Introspective Feedback (ISIF) to dynamically construct the dataset to improve the ability to use the complicated tool. Extensive experiments conducted on both controlled and real-world settings demonstrate the superiority of our tool-learning framework in the real-world application scenario compared to both tuning-free (e.g., ChatGPT, Claude) and tuning-based baselines (e.g., GPT4Tools).

DEVELOPMENT AND ADOPTION OF MANAGEMENT DECISIONS IN CHANGE MANAGEMENT (LITERATURE REVIEW)

Dynamism and aggressive environmental factors leave no chance for organizations of all types of activities, except to follow modern trends and react flexibly by restructuring their activities and the activities of teams.
 Today, managers have a large set of tools and ready-made solutions for implementing changes, but we believe that a list of indicators is needed by which the sequences and methods of transformations will be determined.
 Undoubtedly, the institutional framework for making changes in organizations is important, the work contains a list of global organizations that provide both information and consulting and educational support.
 The process of reactions and adaptation to changes is quite complicated, as it encounters various obstacles in its path, and the decision-making procedure in such conditions is not simple either.
 The article decomposes the process of possible changes, taking into account risk factors and uncertainty, which allows identifying possible barriers and selecting appropriate methods of development and decision-making.
 The gamification method is considered as one of the relevant tools for preparing for changes, thanks to which it is possible to simulate new conditions and work out possible staff mistakes, in addition to reveal and develop the creative abilities of employees.
 Purpose the study of the features of the development and adoption of managerial decisions in change management.
 Methodology the article mainly used the method of theoretical analysis of the available scientific and theoretical base in the field of change management.
 Results: the most informative criteria, the need for changes in organizations and the algorithm of development and decision-making in the conditions of transformation of the organization are obtained.
 Practical implications it is advisable to apply the obtained results to both management theorists and practitioners in order to improve work in the field of change management.

Machine Learning Applications in Electromagnetics and Antenna Array Processing [Book Review

Machine learning (ML) is a field of research with a rapidly growing list of applications.This book takes a unique position in bridging the gap between the ML community, on the one hand, and the electromagnetics community on the other. Classically schooled electrical engineers tend to reduce all problems to the solution of a system of linear equations. This book invites them to consider a much larger set of tools. The book is divided into two parts. Part I introduces the background and algorithms for a number of effective ML methods that lend themselves particularly well for tackling problems in the fields of electromagnetics and array processing. Part II comprises a number of chapters that start from specific problems encountered by the practicing electrical engineer. Applications range from signal analysis over antenna steering to full-wave simulation. The book is most suitable for the researcher and practitioner who wants to learn where to start in the vast domain of ML. Indeed, because of its quick development and its ongoing expansion, it can seem daunting for researchers and engineers not primarily trained in this domain to embark on its exploration. This book is a clear guide to what can be expected from ML, what the prerequisites for tackling the topic are, and what references to turn to for in-depth exposition. Teachers looking to update more traditional courses in electrical engineering will find a good starting point in this book to consider modifications to the curriculum. What is missing to simply use this book as a textbook is a comprehensible set of exercises, especially at undergraduate level.

Платформа MOODLE як інструмент реалізації дистанційного навчання у процесі підготовки майбутніх учителів іноземних мов

Introduction. The training of future foreign language teachers should focus on current advances in the IT field, in particular on the use of elements of distance learning in mastering professional and general competencies. One of the common learning management systems that provide distance education is the Moodle system –Learning Management System(LSM), courses, virtual learning environment, or just a learning platform that provides educational subjects and administrators with a large set of tools for computerized teaching and learning. Purpose. The purpose of the paper is to analyze the features and advantages of distance learning in the information and educational environment of higher education, the structure and principles of working with distance courses in the Moodle system during the training of future teachers of foreign languages, which is used at Mariupol State University, and also to determine the advantages of the Moodle learning management system in the educational process. Results. We believe that the Moodle system, which was developed in the logic of the “pedagogy of social constructionism” (P. Berger and T. Lukman), is able to significantly increase the level of education if the work of students is properly organized in it: it will create a solid base and allow to prepare a specialist who is well trained and possesses competencies at a high level. On the example of our distance course “Methodological workshop” for students of OS Master in specialty 014 Secondary education “Language and Literature (English)”, which organically combines the theoretical principles and practice of teaching English, as well as in-depth study of the courses“Methods of teaching basic foreign language in secondary education”and“Modern technologies for teaching a basic foreign language (English) in high school”, which have practical importance in the professional development of future specialists, we analyzed the productivity of work organization and the effectiveness of students learning in Moodle, using the principle of “constructive coordination” (John Biggs). In its construction, we approached the planning of the entire process of studying the discipline as a set of interconnected types of educational activities of students. The principle of “first content, then technology” works here. This course contains three components that are consistent with each other: 1) expected learning outcomes, consistent with the objectives of the educational program and programmatic learning outcomes; 2) assessment, which verifies certain learning outcomes; 3) all types of activities during the course that are aimed at achieving learning outcomes. Conclusion. According to online surveys and our own experience, the use of distance learning courses created in the Moodle system in the educational process of students allows them to better study a specific academic discipline, helps to improve students’ achievement; complements enriches and makes the learning process convenient for both students and teachers.

PhiC31 integrase for recombination-mediated single-copy insertion and genome manipulation in Caenorhabditis elegans.

Caenorhabditis elegans benefits from a large set of tools for genome manipulation. Yet, the precise single-copy insertion of very large DNA constructs (>10 kb) and the generation of inversions are still challenging. Here, we adapted the phiC31 integrase system for C. elegans. We generated an integrated phiC31 integrase expressing strain flanked by attP sites that serves as a landing pad for integration of transgenes by recombination-mediated cassette exchange (RCME). This strain is unc-119(-) so RMCE integrants can be produced simply by injection of a plasmid carrying attB sites flanking unc-119(+) and the gene(s) of interest. Additionally, phiC31 integrase is removed concomitantly with integration, eliminating the need to outcross away the integrase. Integrations were obtained for insert sizes up to ∼33.4 kb. Taking advantage of this integration method we establish a dual-color fluorescent operon reporter system able to study post-transcriptional regulation of mRNA. Last, we show that large chromosomal segments can be inverted using phiC31 integrase. Thus, the phiC31 integrase system should be a useful addition to the C. elegans toolkit.

Reduced Recombination Losses in Evaporated Perovskite Solar Cells by Postfabrication Treatment

The photovoltaic perovskite research community has now developed a large set of tools and techniques to improve the power conversion efficiency (PCE). One such arcane trick is to allow the finished devices to dwell in time, and the PCE often improves. Herein, a mild postannealing procedure is implemented on coevaporated perovskite solar cells confirming a substantial PCE improvement, mainly attributed to an increased open‐circuit voltage (V OC). From a V OC of around 1.11 V directly after preparation, the voltage improves to more than 1.18 V by temporal and thermal annealing. To clarify the origin of this annealing effect, an in‐depth device experimental and simulation characterization is conducted. A simultaneous reduction of the dark saturation current, the ideality factor (n id), and the leakage current is revealed, signifying a substantial impact of the postannealing procedure on recombination losses. To investigate the carrier dynamics in more detail, a set of transient optoelectrical methods is first evaluated, ascertaining that the bulk carrier lifetime is increased with device annealing. Second, a drift‐diffusion simulation is used, confirming that the beneficial effect of the annealing has its origin in effective bulk trap passivation that accordingly leads to a reduction of Shockley–Read–Hall recombination rates.

Modelling and Differential Quantification of Electric Cell-Substrate Impedance Sensing Growth Curves.

Measurement of cell surface coverage has become a common technique for the assessment of growth behavior of cells. As an indirect measurement method, this can be accomplished by monitoring changes in electrode impedance, which constitutes the basis of electric cell-substrate impedance sensing (ECIS). ECIS typically yields growth curves where impedance is plotted against time, and changes in single cell growth behavior or cell proliferation can be displayed without significantly impacting cell physiology. To provide better comparability of ECIS curves in different experimental settings, we developed a large toolset of R scripts for their transformation and quantification. They allow importing growth curves generated by ECIS systems, edit, transform, graph and analyze them while delivering quantitative data extracted from reference points on the curve. Quantification is implemented through three different curve fit algorithms (smoothing spline, logistic model, segmented regression). From the obtained models, curve reference points such as the first derivative maximum, segmentation knots and area under the curve are then extracted. The scripts were tested for general applicability in real-life cell culture experiments on partly anonymized cell lines, a calibration setup with a cell dilution series of impedance versus seeded cell number and finally IPEC-J2 cells treated with 1% and 5% ethanol.

Соціальні мережі як культурно‑просвітницький ресурс

Автором статті виявлені сутність і потенціал віртуальних соціальних мереж як культурно-просвітницького ресурсу. Методологія дослідження ґрунтується на застосуванні загальнонаукових методів системного аналізу (аналіз, синтез, проблематизація, абстрагування), теорії соціальних мереж; метод логічної реконструкції використовувався при з’ясуванні сутності основних властивостей соціальних мереж та їх функціонування в сучасності.Наукова новизна дослідження полягає в осмисленні соціальних мереж в новому контексті: не лише як інформаційного поля, на якому здійснюються процеси самопрезентації та самоідентифікації користувача і формується його Я-Образ, а й як культурно-просвітницького ресурсу, дієвого інструменту для виховання студентської молоді, коригування її ціннісних орієнтацій, розвитку самосвідомості і професійного самовдосконалення.Звернено увагу на специфічні культуру та активність у віртуальних соціальних мережах, які впливають на людину не менше, ніж соціальні мережі в житті. Наголошено, що, крім виконання комунікативної функції і володіння великим набором інструментів для самопрезентації особистості, отримання визнання і поваги, віртуальні соціальні мережі придатні й для реалізації культурних і культурно-просвітницьких проєктів. Успіх останніх залежить від глибокого й якісного моніторингу запитів і цінностей студентів, їхнього внутрішнього світу, кола інтересів, світоглядної позиції тощо.Впровадження у виховну роботу культурно-просвітницьких ресурсів, збагачених духовно-моральним змістом, покликані орієнтувати студентство на користування ресурсами мережі, що відповідають потребам і запитам високоосвіченої шляхетної людини. Це має стати початковим етапом у відмові від ресурсів, які пропагують шкідливі звички, жорстокість, несмак і нівелюють загальнолюдські духовні цінності. Висловлене сподівання, що надалі розвиток віртуальних соціальних мереж піде шляхом зростання інтенсивності інтелектуальної взаємодії, з’являться нові соціальні та культурні якості спільнот і вони стануть універсальною формою для одночасного вирішення всіх напрямків виховної та культурно-просвітницької роботи.

Computational Saturation Screen Reveals the Landscape of Mutations in Human Fumarate Hydratase.

Single amino acid substitutions within protein structures often manifest with clinical conditions in humans. The mutation of a single amino can significantly alter protein folding and stability, or change protein dynamics to influence function. The chemical engineering field has developed a large toolset for predicting the influence of point mutations with the aim of guiding the design of improved and more stable proteins. Here, we reverse this general protocol and adapt these tools for the prediction of damaging mutations within proteins. Mutations to fumarate hydratase (FH), an enzyme of the citric acid cycle, can lead to human diseases. The inactivation of FH by mutation causes leiomyomas and renal cell carcinoma by subsequent fumarate buildup and reduction in available malate. We present a scheme for accurately predicting the clinical effects of every possible mutation in FH by adaptation to a database of characterized damaging and benign mutations. Using energy prediction tools Rosetta and FoldX coupled with molecular dynamics simulations, we accurately predict individual mutations as well as mutational hotspots with a high disruptive capability in FH. Furthermore, through dynamic analysis, we find that hinge regions of the protein can be stabilized or destabilized by mutations, with mechanistic implications for the functional ability of the enzyme. Finally, we categorize all potential mutations in FH into functional groups, predicting which known mutations in the human population are loss of function, therefore having clinical implications, and validate our findings through metabolomics data of characterized human cell lines.

A holistic approach is key to protect water quality and monitor, assess and manage chemical pollution of European surface waters

Chemical pollution of surface waters is a societal concern around the globe. Key problems in current water quality protection, assessment and management are the narrow focus on a small fraction of the chemicals in commerce, concerns for increasingly diverse chemical emissions, and lack of effective diagnosis and management approaches. In reply, three key concepts to address these challenges were developed and tested. The approaches were developed in the context of the European Union Water Framework Directive, based on principles such as the DPSIR-causal framework (Drivers, Pressure, Status, Impact and Response) and the basic feature that water protection and management should be based on a water-system level approach. Collaborative actions of researchers and stakeholders resulted in: (1) an operationalization and implementation of the solution-focused risk assessment paradigm as proposed in 2009, to improve the utility of risk assessments, (2) the provision of a large set of tools and services to prevent, monitor, assess and manage complex mixture pollution problems, and (3) a strategy and a database on intervention options. These three elements were recognized as core elements to help protecting and improving water quality. Although the methods were developed in the context of water quality problems in Europe, the three elements can be applied globally in water quality protection and management.

Why do organizations discontinue Lean Six Sigma initiatives?

PurposeLean Six Sigma (LSS) has been one of the most widely used quality improvement initiatives over the last decade. However, the success rate of LSS is dismally poor, and most organizations discontinue LSS initiatives prematurely. The purpose of this paper is to answer the question why do organizations discontinue LSS initiatives?Design/methodology/approachTo understand the discontinuance mechanism of LSS initiatives, the authors selected two companies. One from the manufacturing and one from service sector in India. The companies were selected as they had initially implemented LSS, and later within six years had discontinued the initiatives. Four projects from each company were studied using case study methodology.FindingsThis study finds 11 factors due to which the organizations discontinue LSS initiatives. The factors are poor success rate, unrealistic expectations from LSS, unsustainable results, misuse of statistics, large tool set, unsupportive and uncommitted top management, lack of training and development, lack of synergy of LSS and business strategy, lack of link between LSS and customer needs, wrong projects selection and premature discontinuation of LSS experts. The study further discusses the discontinuance mechanisms of LSS using propositions.Practical implicationsLSS is one of the most widely used initiatives in the organizations. Such initiatives involve costs. Earlier studies have reported that many organizations discontinue the LSS initiatives resulting in a loss or not meeting the intended goals. This paper will help the practitioners as well as organizations to understand why organizations discontinue LSS and take prompt actions for its success.Originality/valueEarlier studies on LSS address the critical success factors, and this paper addresses those about failures by studying organizations that have discontinued LSS. The present study finds 11 factors that are responsible for discontinuing LSS in organizations. In addition, propositions are developed for future research and empirical testing. This study also offers further insights into the discontinuance mechanisms involved in LSS.

A Method to Translate Order-Sorted Algebras to Many-Sorted Algebras

Order-sorted algebras and many sorted algebras exist in a long history with many different implementations and applications. A lot of language specifications have been defined in order-sorted algebra frameworks such as the language specifications in K (an order-sorted algebra framework). The biggest problem in a lot of the order-sorted algebra frameworks is that even if they might allow developers to write programs and language specifications easily, but they do not have a large set of tools to provide reasoning infrastructures to reason about the specifications built on the frameworks, which are very common in some many-sorted algebra framework such as Isabelle/HOL, Coq and FDR. This fact brings us the necessity to marry the worlds of order-sorted algebras and many sorted algebras. In this paper, we propose an algorithm to translate a strictly sensible order-sorted algebra to a many-sorted one in a restricted domain by requiring the order-sorted algebra to be strictly sensible. The key idea of the translation is to add an equivalence relation called core equality to the translated many-sorted algebras. By defining this relation, we reduce the complexity of translating a strictly sensible order-sorted algebra to a many-sorted one, make the translated many-sorted algebra equations only increasing by a very small amount of new equations, and keep the number of rewrite rules in the algebra in the same amount. We then prove the order-sorted algebra and its translated many-sorted algebra are bisimilar. To the best of our knowledge, our translation and bisimilar proof is the first attempt in translating and relating an order-sorted algebra with a many-sorted one in a way that keeps the size of the translated many-sorted algebra relatively small.

Nested graphs: A model to efficiently distribute multi‐agent systems on HPC clusters

SummaryComputational simulation is becoming increasingly important in numerous research fields. Depending on the modeled system, several methods such as differential equations or Monte‐Carlo simulations may be used to represent the system behavior. The amount of computation and memory needed to run a simulation depends on its size and precision, and large simulations usually lead to long runs, thus requiring to adapt the model to a parallel system. Complex systems are often simulated using multi‐agent systems (MASs). While linear system based models benefit from a large set of tools to take advantage of parallel resources, multi‐agent systems suffer from a lack of platforms that ease the use of such resources. In this paper, we propose the use of Nested Graphs for a new modeling approach that allows the design of large, complex, and multi‐scale multi‐agent models, which can efficiently be distributed on parallel resources. Nested Graphs are formally defined and are illustrated on the well‐known predator‐prey model. We also introduce PDMAS (parallel and distributed multi‐agent system): a platform that implements the Nested Graph modeling approach to ease the distribution of multi‐agent models on High Performance Computing clusters. Performance results are presented to validate the efficiency of the resulting models.

A Survey of WEC Reliability, Survival and Design Practices

A wave energy converter must be designed to survive and function efficiently, often in highly energetic ocean environments. This represents a challenging engineering problem, comprising systematic failure mode analysis, environmental characterization, modeling, experimental testing, fatigue and extreme response analysis. While, when compared with other ocean systems such as ships and offshore platforms, there is relatively little experience in wave energy converter design, a great deal of recent work has been done within these various areas. This paper summarizes the general stages and workflow for wave energy converter design, relying on supporting articles to provide insight. By surveying published work on wave energy converter survival and design response analyses, this paper seeks to provide the reader with an understanding of the different components of this process and the range of methodologies that can be brought to bear. In this way, the reader is provided with a large set of tools to perform design response analyses on wave energy converters.

Sustainable computational science: the ReScience initiative.

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results; however, computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested and are hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests.

Novel Bio-imaging Tools Based on the Precise Design of Functional Fluorescence Probes.

Fluorescence imaging is one of the most powerful techniques currently available for continuous observation of intracellular processes in living cells and tissues, and so it would be useful to have a large toolset of fluorescence probes suitable for visualizing bioactive molecules or biological phenomena. However, design strategies for small molecule-based fluorescence probes have been limited. Therefore, we are interested in establishing novel rational design strategies for developing functional fluorescence probes. For this purpose, we have focused on the intramolecular spirocyclization reaction of rhodamine derivatives bearing intramolecular nucleophiles as a fluorescence switching mechanism; these derivatives exist in thermal equilibrium between a fluorescent open form and a non-fluorescent spirocyclic form. By utilizing this reaction, we have successfully developed various kinds of fluorescence probes. This review first describes the design of our recently developed fluorescence probes, and then introduces their applications for visualizing the activities of reporter enzymes, for in vivo cancer imaging, and for super-resolution imaging. We believe these probes can serve as key tools to provide unprecedented insights into a wide range of biological phenomena.

Flexible System Solutions for Innovative Laser Welding Processes

AbstractThe new platform WeldMaster by Precitec provides a large toolset for modern laser welding applications. Sensors and actuators for the pre‐, in‐ and post‐process monitoring and control are implemented, offering the most advanced all‐in‐one system‐solution for laser welding tasks. The customer's benefits are especially valuable in automotive applications, where robustness, efficiency and reliability are highly demanded. The combination with an intelligent welding head allows to improve known applications and to develop trend‐setting joining processes.

NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference.

BackgroundIn the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods.ResultsOur open-source and freely available Bioconductor package aggregates a large set of tools to assess the robustness of network inference algorithms against different simulators, topologies, sample sizes and noise intensities.ConclusionsThe benchmarking framework that uses various datasets highlights the specialization of some methods toward network types and data. As a result, it is possible to identify the techniques that have broad overall performances.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0728-4) contains supplementary material, which is available to authorized users.

Approaches to integrating germline and tumor genomic data in cancer research.

Cancer is characterized by a diversity of genetic and epigenetic alterations occurring in both the germline and somatic (tumor) genomes. Hundreds of germline variants associated with cancer risk have been identified, and large amounts of data identifying mutations in the tumor genome that participate in tumorigenesis have been generated. Increasingly, these two genomes are being explored jointly to better understand how cancer risk alleles contribute to carcinogenesis and whether they influence development of specific tumor types or mutation profiles. To understand how data from germline risk studies and tumor genome profiling is being integrated, we reviewed 160 articles describing research that incorporated data from both genomes, published between January 2009 and December 2012, and summarized the current state of the field. We identified three principle types of research questions being addressed using these data: (i) use of tumor data to determine the putative function of germline risk variants; (ii) identification and analysis of relationships between host genetic background and particular tumor mutations or types; and (iii) use of tumor molecular profiling data to reduce genetic heterogeneity or refine phenotypes for germline association studies. We also found descriptive studies that compared germline and tumor genomic variation in a gene or gene family, and papers describing research methods, data sources, or analytical tools. We identified a large set of tools and data resources that can be used to analyze and integrate data from both genomes. Finally, we discuss opportunities and challenges for cancer research that integrates germline and tumor genomics data.