bluuebunny/crossref_metadata_2025 huggingface dataset:
UNFCCC: A Feminist Perspective
Authors: Maguire Rowena , Carter George , Mangubhai Sangeeta , Lewis Bridget , Harris Rimmer Susan
Published: November 2023

The United Nations Framework Convention on Climate Change (UNFCCC) was the only multilateral environmental agreement to emerge from the Earth Summit in 1992 which did not include any references to gender. Recognition of gender within the UNFCCC has been exceedingly slow and largely tokenistic with a focus on ensuring ‘gender balance’ within UNFCCC meetings and processes. This article explores the emergence of gender language within the UNFCCC by reflecting upon: where we have come from; where we are now; and where we are going with respect with gender. While there was very little progress in the early days of the UNFCCC, this article shows that from 2001 onwards there have been a series of small gains, which will be explained and critique. Much work remains to be done with this paper suggesting some concrete steps such as hosting a Gender COP, ensuring financing for National Climate Change Gender Focal Points and embedding gender meaningfully within existing climate finance processes. In recommending future actions, the paper draws on insights from the Pacific and Australian experience.
From beginner to over champion
Authors: van den Herik Jaap
Published: November 2023

In the game of chess the notion of beginner has three meanings. In this contribution they are used as a framework for the history of computer chess. The natural line of reasoning will then bring us to main question: Will the game of Chess (soon) be Solved? A positive answer will certainly be seen as a stepping stone for the next question: Can a computer play perfect chess? Of course, this question will have a natural follow-up in the form of an even more challenging question: Is perfect thinking by a computer possible? The audacious answer “yes” will lead to the world-wide prevailing question of all current AI scientists: Will our intelligence be replaced by AI? The article finds its way (not discussed by us) via machine learning and autonomous adaptation to deep learning and thereafter via Explainable AI and Interpretable AI to solving the Game of Chess. Cornerstones of this historical development will be given in the next three articles by Richard Pijl, Dap Hartmann and Jon Edwards.
Recognizing and harnessing the transformational power of persistent identifiers (PIDs) for publicly-engaged scholars
Authors: Burton Kath , Cocks Catherine , Russell Bonnie
Published: November 2023

While more recognizable publishing models continue to be favored across academic research and publishing systems, the diverse forms of knowledge emerging from publicly-engaged projects derived from working directly with and for communities requires novel and more dynamic publishing solutions. This article considers how the appropriate application of metadata and persistent identifiers to the processes and outputs of engaged scholarship are required to support the goals of the publicly-engaged humanities, and potentially lead to faster and more effective forms of impact for the people and places involved.
Sharing, curation and metadata as essential components of the data management plan
Authors: Gibson Jennifer
Published: November 2023

This paper stresses the critical importance that data management plans actually be data management and sharing plans, that encourage data-sharing at the early stages of research; that indicate that data must be made as open as possible (and as closed as necessary); and that specify a minimum level of curation and collection of essential metadata. The author stresses that fact that it is no longer sufficient to post material openly and hope that others will be able to make use of it. The use of metadata and careful data curation of the data are essential to facilitate the discovery and successful re-use of data.
Moving from piecemeal to systematic: Reprioritizing how academic libraries approach research information management
Authors: MacIsaac Olivia , Polley Ted
Published: November 2023

This paper is based on a lightening talk given at the 2023 NISO Plus conference. The authors explore how research information management (RIM) workflows at universities are increasingly intersecting with library workflows, particularly regarding compliance with federal funding and preservation of the institution’s scholarly record.

This paper outlines one academic library’s plan to shift from thinking about library-supported RIM services as a piecemeal approach to a more systematic approach that prioritizes open infrastructure. Though in its early stages of implementation, the authors seek to examine current RIM systems and services at their institution, expand on the current findings of U.S. activities brought forth in reports produced by OCLC and Lyrasis, and to identify local opportunities for library-supported RIM tools/services that are open and transparent. Specifically, this paper emphasizes the implementation and adoption of persistent identifiers, such as ORCID, but discussion will also cover other RIM systems and services.
Sensitivity of Individual and Composite Test Scores from the Cogstate Brief Battery to Mild Cognitive Impairment and Dementia Due to Alzheimer’s Disease
Authors: White Joshua P. , Schembri Adrian , Prenn-Gologranc Carmen , Ondrus Matej , Katina Stanislav , Novak Petr , Lim Yen Ying , Edgar Chris , Maruff Paul
Published: November 2023

Background: The Cogstate Brief Battery (CBB) is a computerized cognitive test battery used commonly to identify cognitive deficits related to Alzheimer’s disease (AD). However, AD and normative samples used to understand the sensitivity of the CBB to AD in the clinic have been limited, as have the outcome measures studied. Objective: This study investigated the sensitivity of CBB outcomes, including potential composite scores, to cognitive impairment in mild cognitive impairment (MCI) and dementia due to AD, in carefully selected samples. Methods: Samples consisted of 4,871 cognitively unimpaired adults and 184 adults who met clinical criteria for MCI (Clinical Dementia Rating (CDR) = 0.5) or dementia (CDR > 0.5) due to AD and CBB naive. Speed and accuracy measures from each test were examined, and theoretically- and statistically-derived composites were created. Sensitivity and specificity of classification of cognitive impairment were compared between outcomes. Results: Individual CBB measures of learning and working memory showed high discriminability for AD-related cognitive impairment for CDR 0.5 (AUCs ∼ 0.79–0.88), and CDR > 0.5 (AUCs ∼ 0.89–0.96) groups. Discrimination ability for theoretically derived CBB composite measures was high, particularly for the Learning and Working Memory (LWM) composite (CDR 0.5 AUC = 0.90, CDR > 0.5 AUC = 0.97). As expected, statistically optimized linear composite measures showed strong discrimination abilities albeit similar to the LWM composite. Conclusions: In older adults, the CBB is effective for discriminating cognitive impairment due to MCI or AD-dementia from unimpaired cognition with the LWM composite providing the strongest sensitivity.
Multifactorial Causation of Alzheimer’s Disease Due to COVID-19
Authors: Monllor Paloma , Kumar Pratyush , Lloret Mari-Ángeles , Ftara Artemis , Leon Jose-Luis , Lopez Begoña , Cervera-Ferri Ana , Lloret Ana
Published: November 2023

There are several implications of the surge in the incidence of pandemics and epidemics in the last decades. COVID-19 being the most remarkable one, showed the vulnerability of patients with neurodegenerative diseases like Alzheimer’s disease (AD). This review studies the pathological interlinks and triggering factors between the two illnesses and proposes a multifactorial pathway of AD causation due to COVID-19. The article evaluates and describes all the postulated hypotheses which explain the etiology and possible pathogenesis of the disease in four domains: Inflammation & Neurobiochemical interactions, Oxidative Stress, Genetic Factors, and Social Isolation. We believe that a probable hypothesis of an underlying cause of AD after COVID-19 infection could be the interplay of all these factors.
Elevated Ghrelin Promotes Hippocampal Ghrelin Receptor Defects in Humanized Amyloid-β Knockin Mice During Aging
Authors: Tian Jing , Du Eric , Jia Kun , Wang Tienju , Guo Lan , Zigman Jeffrey M. , Du Heng
Published: November 2023

Background: Emerging evidence has revealed that dysregulation of the hormone ghrelin and its receptor, growth hormone secretagogue receptor (GHSR), contributes to the pathogenesis of Alzheimer’s disease (AD). Specifically, defective GHSR function and resultant hippocampal ghrelin resistance are linked to hippocampal synaptic injury in AD paradigms. Also, AD patients exhibit elevated ghrelin activation. However, the detailed molecular mechanisms of hippocampal GHSR dysfunction and the relevance of ghrelin elevation to hippocampal ghrelin resistance in AD-relevant pathological settings are not fully understood. Objective: In the current study, we employed a recently established mouse line of AD risk [humanized amyloid beta knockin (hAβ KI mice), also referred to as a mouse model of late-onset AD in previous literature] to further define the role of ghrelin system dysregulation in the development of AD. Methods: We employed multidisciplinary techniques to determine the change of plasma ghrelin and the functional status of GHSR in hAβ KI mice as well as primary neuron cultures. Results: We observed concurrent plasma ghrelin elevation and hippocampal GHSR desensitization with disease progression. Further examination excluded the possibility that ghrelin elevation is a compensatory change in response to GHSR dysfunction. In contrast, further in vitro and in vivo results show that agonist-mediated overstimulation potentiates GHSR desensitization through enhanced GHSR internalization. Conclusions: These findings suggest that circulating ghrelin elevation is a pathological event underlying hippocampal GHSR dysfunction, culminating in hippocampal ghrelin resistance and resultant synaptic injury in late-onset AD-related settings.
Deep learning architecture towards consumer buying behaviour prediction using multitask learning paradigm
Authors: Geetha M.P. , Karthika Renuka D.
Published: November 2023

A recommendation system serves as a distributed information filter, predicting customer preferences in reviews, ratings, and comments. Analysing customer behaviour aids in understanding needs and predicting intentions. E-commerce tracks product usage and sentiment to provide a personalized network based on consumer preference modelling. The challenge lies in optimizing item selection for suitable consumers to enhance performance. To address this, an imperative is the item recommendation approach for modelling future consumer behaviour. However, traditional machine learning methods often overlook dynamic product recommendations due to evolving user interests and changes in preferences reflected in customer ratings, causing cold-start issues. To overcome these challenges, a comprehensive deep learning approach is introduced. This approach incorporates a deep neural network for consumer preference prediction, utilizing a multi-task learning paradigm to accommodate variations in consumer ratings. The research contribution lies in applying this network to predict consumer preference scores based on latent multimodal information and item characteristics. Initially, the architecture manages changing consumer aspects and preferences by extracting features and latent factors from customer review rating data. These latent factors include customer demographic information and other concealed features that signify preferences based on experiences and behaviours. Extracted latent features are processed using a sentiment analysis model to generate embedding latent features. A finely-tuned deep neural network with hyper-parameter adjustments serves as a prediction network, forming a customer performance-oriented recommendation system. It processes embedded latent features along with associated sentiments to achieve high prediction accuracy, reliability, and latency. The deep learning architecture, enriched with consumer-specific discriminative information, generates an objective function for item recommendations with minimal error, significantly enhancing predictive performance. Empirical experiments on Amazon review datasets validate the proposed model’s performance, showcasing its enhanced effectiveness and scalability in handling substantial data volumes.
Grey relational analysis method for multi-attribute group decision making based on cumulative prospect theory under single-value neutrosophic sets
Authors: Li Yue , Cai Qiang , Wei Guiwu
Published: November 2023

In this paper, the author propose a unique multi-attribute group decision making(MAGDM) method SVN-CPT-GRA. The method takes the single-value neutrosophic environment as the decision-making environment and uses the entropy weighted-grey relational analysis method under cumulative prospect theory. First, based on the evaluation of decision-makers, the single-value neutrosophic decision matrix was obtained. The entropy weight method was used to calculate the attribute weights. Next, according to the distance between each SVNN and the negative ideal value, combining the gray relation analysis and the cumulative prospect theory, the correlation between each solution and the attribute is compared to determine the advantages and disadvantages of each solution. Finally, the extended gray relational analysis method is demonstrated to be effectively applied to the decision-making process through a case study of investment choices in new energy vehicles and a comparison with other methods. The main innovations in this paper can be summarized as follows. Firstly, combining the cumulative prospect theory with the gray relational analysis for decision making can better reflect and represent the psychological changes and risk sensitivity of decision makers. Secondly, the entropy weight method is used to determine the attribute weights according to the distance between SVNN and the negative ideal value, which makes the attribute weights more objective and ensures the scientificity and reasonableness of the attribute weights. Thirdly, applying GRA method to the single-value neutrosophic environment, the original simple and practical GRA method to be more widely applied to the fuzzy environment, expanding the scope of application. Overall, the extended GRA method proposed in this paper can be more efficiently and scientifically adapted to MAGDM in fuzzy environments, providing more choices for decision-makers.
Cascade failure analysis of power-information interdependent network
Authors: Sun Xu , Zou Qingyu
Published: November 2023

Modern information technology has been constantly evolving, transforming the traditional power grid into a network that couples both power and information layers. Understanding the cascade failure behavior of such power communication interdependent networks is essential for effectively controlling catastrophic network failures, preventing system collapse, and ensuring normal network operation. This research can contribute to the development of tools to predict and prevent such failures, and restore normal network functions in a timely manner. This paper focuses on the modeling method and cascading fault analysis of the power-information double-layer coupling network. We construct power information interdependent networks based on IEEE30 system and England39 system, and evaluate the cascade failure results using load distribution cascade failure model and HITS algorithm. The evaluation criteria include network efficiency, residual network size, and residual network load. By analyzing these parameters, we can gain insights into the performance of the power-information interdependent networks during cascade failures. Through simulation results, we demonstrate that the type i attack proposed in this paper renders the network structure unstable and less robust compared to the degree attack, intermediate attack, and random attack. These findings provide valuable references for developing strategies to mitigate the cascading failure of power-information interdependent networks.
A flexible group decision-making method for informationization teaching ability evaluation of university teachers integrating ExpTODIM and GRA under interval neutrosophic environment
Authors: Fu Liping
Published: November 2023

Today, information technology has penetrated into various fields of universities, and the development of information technology in teaching, scientific research, management, and services has become a catalyst for promoting changes in universities. In terms of teaching informatization, the Internet provides a powerful tool for knowledge dissemination and a huge platform for learning and communication between university teachers and students. Knowledge sharing has become easier, and the era of mutual interaction between teachers and students has arrived. University teachers need to quickly face this challenge, adapt to the new teaching and learning environment, improve their own literacy, enhance their information-based teaching ability, change their teaching behavior, and thereby improve the quality of university education and meet the needs of society for talent cultivation. The informationization teaching ability evaluation of university teachers is a classical MAGDM problems. Recently, the Exponential TODIM(ExpTODIM) and (grey relational analysis) GRA method has been used to cope with MAGDM issues. The interval neutrosophic sets (INSs) are used as a tool for characterizing uncertain information during the informationization teaching ability evaluation of university teachers. In this manuscript, the interval neutrosophic number Exponential TODIM-GRA (INN-ExpTODIM-GRA) method is built to solve the MAGDM under INSs. In the end, a numerical case study for informationization teaching ability evaluation of university teachers is given to validate the proposed method.
Optimal weight random forest ensemble with Fuzzy C-means cluster-based subsampling for carbon price forecasting
Authors: Zhang Yuhua , Li Yuerong , Che Jinxing
Published: November 2023

Accurate prediction of carbon price is of great value for production, operation, investment decisions and the establishment of carbon pricing mechanism. However, the large amount of data often limits the application of learning model with good predictive performance in carbon price prediction. Therefore, the development of learning algorithms with low computational complexity has become a research hotspot. Among them, subsampling integration technology is an effective method to reduce the computational complexity. However, lack of data representativeness in subsamples and ignorance of differences among submodels inhibit the prediction performance of the subsampled ensemble model. This project proposes an optimal weight random forest ensemble model with cluster-based subsampling (FCM-OWSRFE) for carbon price forecasting. Firstly, Fuzzy C-means cluster-based subsampling to ensure the data representativeness of subsamples. Secondly, a series of sub-random forest models are built based on subsamples with data representativeness. Finally, an optimal weight ensemble model from these sub-models is derived. To verify the validity of the model, we test FCM-OWSRFE model with the carbon price of Guangzhou Emission Exchange and the carbon price of Hubei Carbon Emission Exchange, respectively. Experimental results show that Fuzzy C-means cluster-based subsampling and the optimal weight scheme can efficiently improve the prediction performance of the subsampled random forest ensemble model.
RETRACTED: Evaluation of machine learning techniques for heart disease prediction using multi-criteria decision making
Authors: Kumar Ajay , Singh Anuj Kumar , Garg Ankit
Published: November 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Exploring and predicting China’s consumer price index with its influence factors via big data analysis
Authors: Cui Qian , Rong Shuai , Zhang Fei , Wang Xiaodan
Published: November 2023

The consumer price index (CPI) is an important indicator to measure inflation or deflation, which is closely related to residents’ lives and affects the direction of national macroeconomic policy formulation. It is a common method to discuss CPI from the perspective of economic analysis, but the statistical principles and influencing factors related to CPI are often ignored. Thus, the impact of different types of CPI on China’s overall CPI was discussed from three aspects: statistical simulation, machine learning prediction and correlation analysis of various types of influencing factors and CPI in this study. Realistic data from the National Bureau of Statistics from 2010 to 2022 were selected as the analysis object. The Statistical analysis showed that in 2015 and 2020, CPI had a fluctuating trend due to the impact of education and transportation. Four types of statistical models including Gauss, Lorentz, Extreme and Pearson were compared. It was determined that the R2 fitted by Extreme model was higher (R2 = 0.81), and the optimal year of simulation was around 2019, which was close to reality. To accurately predict the CPI, the results of Support Vector Machine, Regression decision tree and Gaussian regression (GPR) were compared, and the GPR was determined to be the optimal model (R2 = 0.99). In addition, Spearman matrix analyzed the correlation between CPI and various influencing factors. Herein, this study provided a new method to determine and predict the changing trend of CPI by using big data analysis.
Synthetical reasoning for hybrid tabular-textual question answering over multitasking model
Authors: Pu Tongzheng , Huang Chongxing , Yang Yifei , Yang Jingjing , Huang Ming
Published: November 2023

Hybrid tabular-textual question answering (QA) is a crucial task in natural language processing that involves reasoning and locating answers from various information sources, primarily through numerical reasoning and span extraction. Cur-rent techniques in numerical reasoning often rely on autoregressive models to decode program sequences. However, these methods suffer from exposure bias and error propagation, which can significantly decrease the accuracy of program generation as the decoding process unfolds. To address these challenges, this paper proposes a novel multitasking hybrid tabular-textual question answering (MHTTQA) framework. Instead of generating operators and operands step by step, this framework can independently generate entire program tuples in parallel. This innovative approach solves the problem of error propagation and greatly improves the speed of program generation. The effectiveness of the method is demonstrated through experiments using the ConvFinQA and MultiHiertt datasets. Our proposed model outperforms the strong FinQANet baselines by 7% and 7.2% Exe/Prog Acc and the MT2Net baselines by 20.9% and 9.4% EM/F1. In addition, the program generation rate of our method far exceeds that of the baseline method. Additionally, our non-autoregressive program generation method exhibits greater resilience to an increasing number of numerical reasoning steps, further highlighting the advantages of our proposed framework in the field of hybrid tabular-textual QA.
Deep-MAD: Deep learning based multiple attack detection for secure device- to-device communication in FOG environment1
Authors: Kumar M. , Kavitha A.
Published: November 2023

An exponential growth of users demands ubiquitous connectivity, which requires the integration of new technology. Therefore, Device to Device (D2D) communication has been considered a promising technology that utilizes effective and efficient communication. Even though numerous studies have been conducted for establishing secure D2D communication, however, existing techniques face challenges like privacy, security threats, and poor generality. To overcome these issues a novel Deep-MAD model is proposed to preserve data privacy along with its access control in the D2D network and multiple attack detection in a fog environment. A Fully Homomorphic Elliptic Curve Cryptography (FHECC) is introduced to transmit data securely in a D2D network. The data owner uses FHECC algorithm to encrypt the plain text into cipher text before storing it on the fog. Whenever the user requests data from the fog, the fog service provider confirm the user’s access control. Furthermore, the deep learning-based Bi-LSTM is used to differentiate the device as an authorized or unauthorized user. If the IP address is genuine then the inverse FHECC is used to decrypt the data for authorized users. Otherwise, the particular device is blocked and it is sent for further verification for classifying the types of attacks. The effectiveness of the proposed strategy is examined using several parameters, such as computational complexity, scalability, accuracy, and Execution time. The proposed technique improves the overall computational overhead of 31.77, 9.34, and 4.67 better than AKA protocol, lightweight cipher, and FHEEP respectively.
Association Between Menopausal Hormone Therapy and Risk for Parkinson’s Disease
Authors: Yuk Jin-Sung , Jeong Seong Ho
Published: November 2023

Background:

The relationship between menopausal hormone therapy (MHT) and risk of Parkinson’s disease (PD) remains controversial.

Objective:

This nationwide population-based cohort study investigated the association between MHT and PD development.

Methods:

Data from the National Health Insurance System of South Korea from 2007 to 2020 were used. The MHT group included women who underwent MHT for the first time between 2011–2014, while the non-MHT group included women who visited a healthcare provider for menopause during the same period but never received hormonal therapy. We used propensity score matching (1 : 1) to adjust for potential confounders, and Cox regression models to assess the association between MHT and PD.

Results:

We selected 303,260 female participants ( n = 151,630 per MHT and non-MHT groups). The median age of the participants was 50 (48–54) years, and the follow-up period lasted 7.9 (6.9–8.9) years. Cox regression analysis revealed an increased risk of PD with MHT (hazard ratio [HR] 1.377, 95% confidence interval [CI] 1.184–1.602), particularly with tibolone (HR 1.554, 95% CI 1.297–1.861) and estrogen alone (HR 1.465, 95% CI 1.054–2.036). Tibolone and estrogen alone were linked to PD within three years; however, no association was observed after three years. In contrast, the use of combined estrogen-progesterone was linked to a higher risk of PD, which increased with the duration of MHT (HR 1.885, 95% CI 1.218–2.918 for over five years).

Conclusions:

This study demonstrated that the MHT is closely associated with the risk of PD in a regimen- and duration-specific manner.
Clinical assessment, treatment, and referral trends for adolescent runners seeking care at an injured runners’ clinic
Authors: DeJong Lempke Alexandra F. , Stracciolini Andrea , Willwerth Sarah B. , Ackerman Kathryn E. , d’Hemecourt Pierre A. , Meehan William P. , Whitney Kristin E.
Published: November 2023

PURPOSE: Over a 10-year time frame, this study aimed to evaluate diagnosis, treatment, and referral trends for adolescent runners seeking care for running-related injuries (RRIs) at a clinic that specializes in running medicine. METHODS: This study was a retrospective chart review of 392 adolescent runners (2,326 encounters) who sought care for RRIs between the years 2011 and 2021. Descriptive statistics were used to summarize clinical assessments, referrals, assistive devices, and medications prescribed or administered overall and by injury type. Chi-square analyses were used to compare proportions of services rendered across the 10-year time frame. RESULTS: Patients most frequently received manual evaluations or special tests during clinic visits. Most visits resulted in at least one referral (91%), primarily for physical therapy or gait-training. Assistive devices and medications/supplements were offered at only 18% of patient visits. The majority of assessments (X2 = 69.7, p = 0.002), treatments (X2: 23.6–43.8, p: <  0.001–0.003), and referrals (X2 = 132, p <  0.001) were for shin injuries. Larger proportions of nutrition assessments (X2 = 40.7, p <  0.001), interventions (X2 = 26.8, p = 0.003), and referrals (X2 = 27.5, p = 0.002) were performed in or after the year 2015. CONCLUSION: Clinic visits for shin injuries required the most clinical resources per episode of care. There were observed shifts in clinical assessment and treatment approaches to include more expanded nutritional and physiologic considerations.
Transformational leadership and organizational learning culture in the health sector: The mediating and moderating role of intrinsic work motivation
Authors: Udin Udin
Published: November 2023

BACKGROUND: Transformational leadership and organizational learning culture have become exciting topics to be explored over the last few decades. However, several previous studies have shown certain inconclusive findings regarding the link between transformational leadership and organizational learning culture. OBJECTIVE: This study fills this gap by developing a clear model and aims to examine the extent of the impact of (1) transformational leadership on organizational learning culture and intrinsic work motivation, (2) intrinsic work motivation on organizational learning culture, (3) intrinsic work motivation in mediating and moderating the relationship between transformational leadership and organizational learning culture. METHODS: The data of this study are collected from employees working at the community health center in Indonesia. A partial least squares (PLS) based structural equation modeling (SEM) technique is used to analyze the data by utilizing the SmartPLS 3.0 software package. RESULTS: First, the results concluded that transformational leadership has a significant impact on organizational learning culture and intrinsic work motivation. Second, intrinsic work motivation has a significant impact on organizational learning culture. Third, intrinsic work motivation fully mediates the relationship between transformational leadership and organizational learning culture. Also, intrinsic work motivation moderates these variables’ relationships. CONCLUSION: The theoretical model of previous research on the relationship between transformational leadership and organizational learning culture with intrinsic work motivation as a mediator and moderator variable has yet to be fully developed both in public and private organizations, particularly in the health sector.
Prediction of the dependence of the indoor air temperature on the change in the working characteristics of the water heating system
Authors: Petrenko V. , Petrenko A. , Holiakova I. , Petrenko V.
Published: November 2023

This article was devoted to the theoretical determination of the predicted indoor air temperature based on the basic equations of hydraulics and heat exchange with variable operating characteristics of the water heating system network. Derive a relationship that will predict the indoor air temperature setting of the room that is being heated as a result of changes in the operating characteristics of the water heating systems. In basis the solution to the problem of determining the temperature in the room by changing the performance characteristics of the water heating system is based on the basic equations of hydraulics and heat transfer such as Darcy-Weisbach equation to determine the hydraulic losses in the network; flow continuity equation; equation to determine the heat flux from the coolant to the walls of the heater; equation for determining the heat transfer of the heater. The resulting dependence makes it possible to predict the setting of the indoor air temperature in the room heated as a result of changes in the operating characteristics of the water heating systems. This dependence will allow at the design stage and in the process of operation of water heating systems to predict changes in the indoor air temperature in order to take measures to stabilize it. The predicted indoor air temperature is theoretically determined based on basic equations of hydraulics and heat exchange with variable operational characteristics of the water heating system network. The obtained results of indoor air temperature prediction calculations show that the parameters of the indoor microclimate change due to changes in the operational characteristics of water heating systems (changes in coolant consumption, hydraulic characteristics of pipelines). This approach will allow you to make decisions to improve the reliability of water heating systems in the process of ensuring the parameters of the microclimate in the room.
Model of target situation for building lexical competence in English professionally oriented oral communication of prospective ecologists
Authors: Mykytenko Nataliia , Shymanska Vira
Published: November 2023

The article deals with an analysis of target situation for building lexical competence in English professionally oriented oral communication of prospective ecologists. Purpose of the article is to elaborate a model of target situation for building lexical competence in English professionally oriented oral communication of prospective ecologists, to select and analyze the data and find out the factors of effectiveness of this process. Methods: theoretical ones (analysis of research sources, content of syllabuses for disciplines of professional prospective ecologists’ training in order to reveal the essence of concept “analysis of target situation” and outline its components of building lexical competence in English professionally oriented oral communication of prospective ecologists); empirical ones (survey, questionnaire, quantitative and qualitative analysis of the data). Results. It has been proved that an analysis of target situation provides the factors of effectiveness of this process and achievement of objectives and outcomes of the teaching. Conclusion. The model of target situation for building lexical competence in English professionally oriented oral communication of prospective ecologists has been designed that includes: the objectives of teaching (development of the system of lexical knowledge, skills and awareness, speaking and listening skills), learning interests (in topics and organization of instruction), learning needs (acquisition of basic glossary in ecology and speech clichés, selection of learning material), teaching methods (projects, presentations, cases, role-plays), teaching tools (a need for developing course books, workbooks and manuals for building lexical competence in English professionally oriented oral communication), content of teaching (topics, issues, typical and topical situations of English professionally oriented oral communication) and outcomes (high level of target competence).
ОСОБЛИВОСТІ СТРАТЕГІЧНОЇ ДІАГНОСТИКИ СФЕРИ HORECA У ВІЙСЬКОВИЙ ПЕРІОД
Authors: Сидорук Світлана , Матвійчук Людмила , Лепкий Михайло
Published: November 2023

У статті розкрито змістовну характеристику поняття HoReCa у сфері обслуговування, фактори розвитку сфери HoReCa у військовий період, проведено аналітичне дослідження сфери HoReCa, розкрито характеристику діяльності сфери HoReCa у сучасний період, запропоновано шляхи розвитку сфери HoReCa в Україні у воєнний період. Основною метою проведеного дослідження є визначення особливостей стратегічної діагностики сфери HoReCa у військовий період. Проведений аналіз наукових джерел по напряму розвитку сфери HoReCa свідчить, в публікаціях висвітлені недостатні елементи, що характеризують діяльність готелів, ресторанів, кафе у військовий період. Систематизація літературних джерел та підходів до вирішення проблеми стратегічної діагностики сфери HoReCa у військовий період передбачає наявність широкого спектру питань, що пов’язані з послугами аутсортингу, дослідженні недостатньо. Актуальність висвітлення проблеми є важливим у сфері HoReCa з точки зору сфери обслуговування, і передбачає 70% завантаженості під корпоративні замовлення. Дослідження сфери HоReCa у військовий період більш спрямований на кейтеринг. У процесі дослідження використовувалися економіко-статистичні дані, порівняння, узагальнення, конкретизація, синтезу та аналізу. Періодом дослідження обрано реальний час, напрямок розвитку якого передбачає вищий рівень послуг, зацікавлені особи, які інвестували гроші в цю галузь, можуть готуватися до зростання доходів. Ринок української їжі поза місцем проживання прямує до перспективного розвитку. Сфера HoReCa займає лідерські позиції та є показником розвитку, в ресторані/кафе на одне місце припадає 30 мешканців, це характерне для України, у Європі ця черга сягає вісім гостей за стіл. Об’єктом дослідження обрано діяльність сфери HoReCa. Дослідження підтверджує та теоретично доводить, що сфера HoReCa має свої переваги та недоліки. Результати проведеного дослідження можуть бути актуальними для гравців ринку, котрі позиціонують себе директорами різних закладів, що по’вязані з харчуванням різних форматів, громадськості, для тих, хто тільки збирається виходити на даний ринок, або шукають перспективний бізнес-план, так і для прямих споживачів сфери послуг,що шукають тренди у сфері HoReCa.
ЕКОНОМІКА ІНДУСТРІЇ ГОСТИННОСТІ В СУЧАСНИХ УМОВАХ: МІЖНАРОДНІ ТА ВІТЧИЗНЯНІ ТРЕНДИ
Authors: Несторишен Ігор , Прокопець Ярослав
Published: November 2023

Індустрія туризму є однією з важливих складових світової економіки, на яку припадає близько 7% міжнародної торгівлі. За даними Всесвітньої туристичної організації, кожне десяте робоче місце у світі опосередковано створюється туризмом. Метою дослідження є систематизація сучасних тенденцій розвитку вітчизняної та зарубіжної індустрії гостинності в контексті виявлення відповідних чинників, які негативно впливають на цю галузь, а також вироблення рекомендацій щодо напрямів реалізації вітчизняної програми «постконфліктного туризму». Аналіз сучасних тенденцій розвитку індустрії туризму показує, що, починаючи з 2020 року, підприємства туристичної сфери постійно перебували під негативним тиском факторів зовнішнього середовища. Таким чином, суттєвої шкоди розвитку туристичного бізнесу у світі завдали заходи, спрямовані на подолання наслідків пандемії COVID-2019, які нині ускладнили процеси переміщення громадян як усередині країни, так і можливості міжнародного туризму. через запровадження значних «ковідних» обмежень на пересування громадян між країнами. Так, внаслідок політики обмеження можливого пересування до країн Європейського Союзу, США, Близького та Далекого Сходу протягом 2020-2022 років туристична сфера багатьох туристичних регіонів зазнала значних втрат. За оцінками UNWTO, заходи з подолання пандемії COVID-2019 у 2020-2021 роках призвели до значного зниження масштабів міжнародного туризму (до 80 %), а також падіння надходжень від експорту туристичних послуг склало більше 900 мільярдів доларів США. В досліджені запропоновано актуальні заходи щодо відновлення туристичної галузі з урахуванням досвіду країн, де відбувалися військові конфлікти, та розроблено відповідні заходи щодо відновлення туризму в постконфліктний період. Систематизовано міжнародний досвід функціонування туристичної галузі у постконфліктний період та запропоновано заходи щодо відновлення вітчизняної сфери туризму у післявоєнний період.
ІННОВАЦІЙНІ МАРКЕТИНГОВІ ТЕХНОЛОГІЇ У СФЕРІ ТУРИЗМУ
Authors: Мокрий Андрій
Published: November 2023

Стаття присвячена дослідженню впливу інновацій на розвиток маркетингових технологій у галузі туризму. Досліджено, що маркетинг є невід’ємною складовою успішного функціонування туристичного підприємства. Здійснено аналіз останніх досліджень і публікацій, які стосуються маркетингових інновацій у туристичній сфері. Визначено найпопулярніші на сьогоднішній день новітні технології маркетингу: аналітика з використанням штучного інтелекту; використання чат-ботів; маркетинг у соціальних мережах; технології на основі визначення місцезнаходження. Визначено, що маркетингові інновації в туризмі впливають на перспективні напрями розвитку туризму, удосконалення існуючих туристичних продуктів, підвищення іміджу і конкурентоздатності підприємств туристичної індустрії. При дослідженні новітніх маркетингових технологій було виявлено, що невирішеною залишається проблема оцінки актуальності певної маркетингової технології для конкретного туристичного підприємства. Простіше кажучи, відсутні оцінки потенційних переваг для підприємства від впровадження певної маркетингової технології порівняно з іншими. Основною метою дослідження була розробка оцінки актуальності сучасних маркетингових технологій у сфері туризму, що дозволило б туристичним підприємствам першочергово впроваджувати найактуальніші новітні маркетингові технології. Наведено класифікацію видів туризму залежно від мети поїздки. Проведений аналіз показав, що актуальність певних маркетингових технологій для клієнта може відрізнятися залежно від мети поїздки. Для вирішення проблеми було запропоновано метод бальної оцінки актуальності існуючих маркетингових технологій залежно від основної мети візиту клієнтів. Даний метод дозволяє туристичним підприємствам оцінювати пріоритет різних новітніх технологій маркетингу та першочергово впроваджувати найактуальніші з них. Результати проведеного дослідження можуть бути корисними для працівників сфери туристичного та готельно-ресторанного бізнесу, науковців, викладачів, студентів вищих навчальних закладів тощо.
ФІНАНСОВА ПОЛІТИКА ДЕРЖАВИ В УМОВАХ ЦИФРОВІЗАЦІЇ ЕКОНОМІКИ
Authors: Мільман Л.М. , Кучмійова Т.С.
Published: November 2023

У статті висвітлено особливості фінансової політики держави в умовах цифровізації економіки. Виявлено, що ефективна реформа системи управління державними фінансами є основою для реалізації національної політики та досягнення стратегічних цілей розвитку за допомогою підтримки загальної фіскальної дисципліни, стратегічного розподілу бюджетних ресурсів та ефективного надання послуг. Розглянуто особливості реалізації Стратегії здійснення цифрового розвитку, цифрових трансформацій і цифровізації Системи управління державними фінансами до 2025 року. Охарактеризовано Стратегію розвитку фінансового сектору України та встановлено, що, незважаючи на війну, цей документ визначає необхідність продовження технологічного розвитку фінансових послуг як важливої передумови для подальшого розширення фінансової доступності та забезпечення кібербезпеки. Розглянуто особливості модернізації законодавства про регулювання фінансового ринку.
Beyond reliability in first impressions research: Considering validity and the need to “Mix it up with folks”
Authors: Satchell Liam , Jaeger Bastian , Jones Alex , López Beatriz , Schild Christoph
Published: November 2023

‘First impressions’ are a popular topic in social psychology. They are researched because the initial judgments of others are consequential in everyday life (such as job interviews, first dates, justice outcomes). In the context of broader concerns about the credibility of psychological science, first impressions research has developed commendable initiatives for improving reliability (open stimulus databases, international collaborations, replication studies and reanalyses). However, these initiatives can impact the validity of studying how people form first impressions. There is a long history of critiquing the usefulness of passive-observer judgments of controlled, reduced, presentations of people—and these concerns are still relevant today. Here, we highlight the praiseworthy practices improving reliability in first impressions research, before moving on to identify persistent methodological concerns in the field. This includes inadequate stimulus sampling and diversity, constrained participant response options, limited consideration of study context, and limitations of atomised presentations of target people. We identify how these methodological limitations impact theory development, how we might be over/underestimating everyday experience, and even misunderstanding social differences in autism and mental health. Finally, we identify opportunities for methodological reform, focusing on codifying instead of controlling interactions, promoting inductive, participant-led, methodologies, and asking for stronger theory development and clarity on ‘can’ vs. ‘do’ research questions. Overall, we praise reforms for improving the reliability of first impressions research, but improvements to making scientific predictions about first impressions require renewed consideration of validity.
In Contemplation of Hyewon Sin Yun-bok’s Hyewonhawcheop(蕙園畫帖)
Authors:   Korea Association of World History and Culture, Im Mi-Hyun
Published: November 2023

Hyewonhawcheop(蕙園畫帖) by Hyewon Sin Yun-bok(申潤福, 1758?-1817 or later) is a collection of paintings in a literary artist’s style mainly focusing on landscape painting with figures. This collection of paintings contains two pages of HaengSeo(a semi-cursive style of writing) and six pages of paintings with a variety of genres, including letters, Sagunja(Four Gracious Plant Painting), landscape painting with figures, and paintings of Taoist immortals and Buddhist Saints and Arhats. These works of art help enhance insight also on his preference for literary arts that had not received much attention due to genre paintings.
As Hyewonhawcheop carries a government seal recording “Hyewon, lunar July of the year Mu Jin” and other variety of seals, including “yu-eo-yeah”, “sin-ga-gwon-in”, it can be inferred that this was produced when Sin Yun-bok was 50 years old. Since his other works’ production dates are unknown, this can be a reference work for timepoint. This paper focuses on this significance, analyzing and contemplating on each work in Hyewonhawcheop to understand Sin Yun-bok and his works.
Profesor Alicja Jaruga jako twórca łódzkiej szkoły rachunkowości
Authors: Walińska Ewa
Published: November 2023

Celem artykułu jest przedstawienie sylwetki Profesor Alicji Jarugi, twórcy łódzkiej szkoły rachunkowości, badacza o uznanym dorobku naukowym i dydaktycznym. Profesor Jaruga była prawdziwą pasjonatką nauki rachunkowości, której poświęciła 60 lat życia zawodowego. Inspirowała swoich podwładnych i współpracowników do podejmowania nowatorskich i trudnych wyzwań badawczych.
Artykuł składa się z trzech części oraz podsumowania. W pierwszej części przedstawiono istotę systemu informacyjnego rachunkowości organizacji, będącego przedmiotem badań Profesor Alicji Jarugi. Druga zawiera rys biograficzny Pani Profesor, natomiast w trzeciej przedstawiono Jej różne oblicza – w szczególności jako wybitnego badacza, dydaktyka, wychowawcy kadr naukowych i ambasadora nauki polskiej za granicą.
Niniejsze opracowanie jest rezultatem analizy literatury przedmiotu, w tym materiałów archiwalnych, z zastosowaniem metody biograficznej.
Przedstawione w artykule fakty i opinie potwierdzają fenomen osobowości Pani Profesor – Jej ogromny wkład w rozwój nauki i praktyki polskiej rachunkowości, utworzenie szkoły naukowej, promowanie kadr naukowych i doskonalenie procesu kształcenia akademickiego w Polsce.
Badania dotyczące robotyzacji procesów biznesowych w naukach o zarządzaniu – systematyczny przegląd literatury
Authors: Pypłacz Paula
Published: November 2023

Celem artykułu jest przedstawienie i porównanie badań naukowych dotyczących wykorzystania RPA w obszarze nauk o zarządzaniu. Tym samym postawiono pytanie badawcze: jakie główne trendy można zidentyfikować w badaniach naukowych nad RPA w obszarze nauk o zarządzaniu? Przeprowadzono systematyczny przegląd literatury, w którym jednym z etapów było badanie bibliometryczne przeprowadzone wg następujących parametrów: chronologia, źródło, kraj, treść, cytowanie, uniwersytet. Ostateczny zbiór publikacji składał się z 1193 artykułów podzielonych na zestaw ogólny (970 sztuk) oraz zestaw specjalny (223 sztuki). Analiza pozwala stwierdzić, iż obszar badań nad RPA w naukach o zarządzaniu jest młody, rozwijający się. Nauki inżynieryjne i techniczne mają zdecydowanie większą bazę publikacji dotyczących RPA. W naukach o zarządzaniu nie rozwinęła się mocna sieć współpracy i cytowań, co jest zdecydowanie rozwojowym obszarem. Badacze winni korzystać z dotychczasowego dorobku oraz tworzyć tematyczne sieci współpracy, szczególnie, że w zakresie zarządzania występuje wiele luk badawczych, które mogą być eksplorowane. Badania mogą być wykorzystane przez innych badaczy, którzy zainteresowani są różnymi aspektami RPA.