bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does Distrust Matter More than Trust? How Audit Judgment Is Influenced by Inconsistent Evidence
Authors: Hawkins Erin M. , Donnelly Amy M. , Owens Joel 
Published: August 2024

SUMMARY
Prior research considering the influence of trust on auditor judgment and decision making has largely ignored distrust, viewing distrust as one end of a unidimensional measure of trust. Psychology literature, however, suggests that trust and distrust are distinct constructs with fundamental differences. In this study, we argue that auditing research would benefit from embracing this conceptualization of both trust and distrust when examining auditor judgments. We conduct an experiment that examines whether situational trust and distrust mediate the relationship between the receipt of inconsistent evidence from the client and auditor effort. Results suggest that distrust has a greater influence on auditor effort than trust. We also find that the prior receipt of consistent evidence from the client weakens the negative influence that inconsistent evidence has on perceptions of trust and distrust, and violations of trust due to the receipt of inconsistent evidence are quick to repair.
Data Availability: Please contact the first author.
An Exploratory Study of Fraud Examination Education in Preparing Accounting Students to Combat Fraud: Evidence from COVID-19
Authors: Hsiao Daniel , Saeedi Ali , Wang Liz 
Published: August 2024

ABSTRACT
This study aims to assess the ability of accounting students to identify fraud symptoms, analyze prevention and detection controls, and determine legal consequences during the COVID-19 pandemic. The research data were collected from an online discussion forum completed by accounting students in the “Fraud Examination” course at a public university in the United States. Adapting to the framework of experiential learning theory, we assessed students’ performance using a rubric based on five learning objectives over three semesters from Spring 2020 to Spring 2021. The results indicate that most of the students, regardless of the semester, demonstrated proficiency in applying fraud examination concepts and performing fraud analyses in the pandemic setting, meeting the expected learning objectives.
JEL Classifications: K42; I20.
Penerapan Metode EOQ Dalam Pengendalian Persediaan Pakan Ternak Pada Usaha Peternakan Ayam Petelur Skala Mikro
Authors: Fayaqun Reza , Sulistyaningsih Febriani , Numang Irpan 
Published: August 2024

Bisnis di bidang peternakan memiliki prospek yang menjanjikan di Indonesia, salah satunya peternakan ayam petelur. Bukan tanpa alasan karena harga dan permintaan telur yang relatif stabil dan tingkat kematian (mortality rate) lebih rendah dibandingkan ayam pedaging. Kedua hal tersebut tidak serta merta menjadi faktor kesuksesan bisnis di bidang peternakan ayam petelur, tetapi kemampuan dalam mengendalikan faktor-faktor produksi menjadi hal mutlak yang harus diperhatikan, salah satunya dalam pengendalian persediaan pakan ternak. Penelitian ini meggunakan metode Economic Order Quantity (EOQ) sebagai metode pengendalian persediaan pakan ternak dengan tujuan mengetahui jumlah pemesanan pakan ternak yang optimal. Dari observasi lapangan pada peternakan ayam petelur berskala mikro (< 1.000 unggas) didapat pola data pengguanaan pakan ternak 1 tahun terakhir, juga biaya simpan dan biaya pesan yang diperlukan dalam perhitungan EOQ. Hasilnya diketahui bahwa pemesanan pakan ternak yang optimal adalah sebanyak 18 zak dengan frekuensi pemesanan 11 kali pesan dalam setahun dan reorder point pada saat jumlah pakan ternak tersisa 1 zak, hal itu berpengaruh terhadap penurunan biaya persediaan sebesar Rp. 2.037.693.- dari semula sebesar Rp. 2.402.413.- menjadi Rp. 364.720.- per tahun.
Experimental Investigation Into the Tensile Strength Post-Repair on Damaged Aluminium 2024 -T3 Plates Using Hybrid Bonding/Riveting
Authors: Merah Abdelkrim , Houari Amin , Madani Kouider , Belhouari Mohamed , Amroune Salah , Chellil Ahmed , Yahia Cherif Zineelabidine , Campilho Raul D.S.G. 
Published: August 2024

Abstract
Since the implementation of repair processes by composite patch bonding, this process has consistently demonstrated high performance across various industrial sectors, especially in the fields of aeronautics, aerospace and civil engineering. Consequently, there are situations in which the riveting process becomes the sole solution, particularly when the structure is subjected to severe mechanical or thermo-mechanical stresses, since adhesives have low mechanical strength after aging. Each method has its own set of advantages and disadvantages. The current trend is to combine these two processes to minimise their drawbacks as much as possible. The objective of this work is to present an experimental study on the repair of an aluminium plate AL2024-T3 with a central circular notch using a patch of different nature (metal or composite), under tensile loading conditions. The repair composite considered is a carbon/epoxide. The results of the tensile tests showed that the repair by the combination of the two processes improves the mechanical strength of the damaged structure. A comparison of the results of the experimental curves obtained on riveted, bonded and hybrid assemblies has been taken into consideration.
Rate of Sodium Correction and Osmotic Demyelination Syndrome in Severe Hyponatremia: A Meta-Analysis
Authors: See Xin Ya , Chang Yu-Cheng , Peng Chun-Yu , Wang Shih-Syuan , Chi Kuan-Yu , Chiang Cho-Hung , Chiang Cho-Han 
Published: August 2024

Abstract

Introduction
Current guidelines recommend limiting the rate of correction in patients with severe hyponatremia to avoid severe neurologic complications such as osmotic demyelination syndrome (ODS). However, published data have been conflicting. We aimed to evaluate the association between rapid sodium correction and ODS in patients with severe hyponatremia.

Materials and methods
We searched PubMed, Embase, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials from inception to November 2023. The primary outcome was ODS and the secondary outcomes were in-hospital mortality and length of hospital stay.

Results
We identified 7 cohort studies involving 6,032 adult patients with severe hyponatremia. Twenty-nine patients developed ODS, resulting in an incidence rate of 0.48%. Seventeen patients (61%) had a rapid correction of serum sodium in the first or any 24-hour period of admission. Compared with a limited rate of sodium correction, a rapid rate of sodium correction was associated with an increased risk of ODS (RR, 3.91 [95% CI, 1.17 to 13.04]; I2 = 44.47%; p = 0.03). However, a rapid rate of sodium correction reduced the risk of in-hospital mortality by approximately 50% (RR, 0.51 [95% CI, 0.39 to 0.66]; I2 = 0.11%; p < 0.001) and the length of stay by 1.3 days (Mean difference, −1.32 [95% CI, −2.54 to −0.10]; I2 = 71.47%; p = 0.03).

Conclusions
Rapid correction of serum sodium may increase the risk of ODS among patients hospitalized with severe hyponatremia. However, ODS may occur in patients regardless of the rate of serum sodium correction.
Data-enhanced revealing of trends in Geoscience
Authors: Zhao Yu , Wang Meng , Ding Jiaxin , Qi Jiexing , Wu Lyuwen , Zhang Sibo , Fu Luoyi , Wang Xinbing , Cheng Li 
Published: August 2024

Abstract

Purpose
This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences①.

Design/methodology/approach
The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database. To map relationships between articles, citation networks were constructed, and spectral clustering algorithms were then employed to identify groups of related research, resulting in 407 clusters. Relevant research terms were extracted using the Log-Likelihood Ratio (LLR) algorithm, followed by statistical analyses on the volume of papers, average publication year, and average citation count within each cluster. Additionally, expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation, relevance, and impact within Geosciences, and finalize naming of these top trends with consideration of the content and implications of the associated research. This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists.

Findings
Thirty significant trends were identified in the field of Geosciences, spanning five domains: deep space, deep time, deep Earth, habitable Earth, and big data. These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society, science, and technology.

Research limitations
The analyzed data of this study only contain those were included in the Web of Science.

Practical implications
This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science, especially on solid earth. The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study.

Originality/value
This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.
Problematising “World Class” public education policy in South Australia: Insights for education policy makers
Authors: Bills Andrew , Howard Nigel , Hattam Sarah 
Published: August 2024

Abstract
This policy-interested South Australian public education case study problematises how the Chief Executive (CE) and members of the Education Department’s Senior Executive Group (SEG) understood system and school improvement from 2018 to 2022. We applied Carol Bacchi’s, “What’s the Problem Represented to be?”(WPR) policy analysis framework to unearth the policy assumptions underlying the Department’s overarching policy ensemble called “World Class,” initiated across South Australia’s public primary and secondary schools. WPR reveals heightened centralised technologies of command and control directed at teacher and leader work to achieve McKinsey defined World Class status by 2028.
We find school improvement policy solutions were engineered through “managerially enforced complexity reduction” techniques within the paradigm of the Global Education Reform Movement (GERM). These techniques impacted policy prescriptions, performance management technologies, school improvement plans, curriculum materials for schools, and promoted NAPLAN as the ultimate measure of the good school, the good teacher, and the good principal. NAPLAN is the National Assessment Program—Literacy and Numeracy used in Australia and takes the form of an annual standardised assessment for students in Years 3, 5, 7 and 9.
Most concerningly, we find the policy logics of World Class worked to incentivise inequality across public schools through diminishing the purposes of public education and the professionalism of educators. We conclude arguing for the democratisation of existing departmental structures within iterative inquiry-based approaches to policy formation and practice to better attend to public education purposes.
How does adulteration of wax foundation affect phenoloxidase and lysozyme activities as selected parameters of immunity in Apis mellifera?
Authors: Strachecka Aneta , Chęć Magdalena , Olszewski Krzysztof , Staniszewska Patrycja , Dziechciarz Piotr , Gagoś Mariusz 
Published: August 2024

Abstract

Introduction
The adulteration of wax foundation is, for many reasons, a growing problem of modern beekeeping not only in Europe but also around the world. Wax foundation contaminated with stearin addition leads to a brood die-off, while paraffin addition negatively affects the strength of combs. It is tenable that such adulterated wax foundation reduces bees’ immunity. The aim of the study was to determine the activities of two bee immune enzymes, lysozyme and phenoloxidase, in the haemolymph of worker bees which had emerged from combs with wax foundations contaminated with stearin or paraffin.

Material and Methods
Combs built with stearin- or paraffin-adulterated wax (both adulterants at concentrations of 10%, 30% or 50%) or pure wax (0% adulterated) foundations were placed in the colonies, one for each adulterant and percentage. The workers were marked upon emergence from these combs and those bees were introduced into one strong colony per adulterant and percentage. Phenoloxidase and lysozyme activities were determined in the haemolymph of 1-, 7- and 14-day-old workers.

Results
The higher the concentrations of stearin and paraffin in the wax foundation, the lower the phenoloxidase activities were. These activities increased with the bee age. In contrast, the trends in lysozymes were opposite. Paraffin seems to be less toxic than stearin.

Conclusion
Adulteration of wax foundation with even a small amount of stearin or paraffin has negative effects on the functioning of the bee.
A Novel Method to Obtain Reverse Bias I–V Curves for Single Cells Integrated in Photovoltaic Modules
Authors: Drif Mahmoud , Bouchelaghem Ahmed , Guemache Abderezak , Benhamadouche Djoubair Abdelouahab , Saigaa Djamel 
Published: August 2024

Abstract
Despite the existence of accurate mathematical models facilitating the analysis of photovoltaic (PV) sources’ behaviour under diverse conditions, including normal operation and situations involving mismatch phenomena such as partial shadowing and various faults (i.e., PV cells operating in forward bias and reverse bias quadrants), an important issue still persists. Crucial parameters essential for adjusting these models, particularly those related to reverse-biased characteristics such as breakdown voltage, are often absent in manufacturers’ datasheets. This omission presents a substantial challenge, as it restricts the ability to acquire comprehensive and accurate information required for a thorough analysis of devices in the second quadrant. To address this issue, our research introduces a novel method for measuring the reverse-biased I–V characteristics of individual PV cells within a module without having to dissociate them from the PV module encapsulants. The process involves measuring the forward-bias I–V curves of both the fully illuminated PV module and a partially shaded PV module with only one completely shaded cell. This can be achieved outdoors and by utilising commercially available I–V tracers. Thus, the reverse I–V curve can easily be derived from these forward bias I–V curves. Finally, the proposed method serves as a nondestructive technique for characterising solar cells in the second quadrant. This innovative approach offers a promising solution for assessing the performance and health of PV modules without causing damage and may result in significant cost savings.
Regional Export Strategies and Programs: Development Algorithm (the Example of the Tomsk Region)
Authors: Shpakova R. N. , Gorodetskiy D. I. 
Published: August 2024

Introduction. The article analyzes the problems that arise in the development of regional export strategies and programs. The regional export strategy of the Tomsk region, a region with average export characteristics and, at the same time, which has recently encountered a complex of problems typical for a significant number of regions in export activities, has been selected as an object for analysis. The algorithm of strategy development is proposed. It is considered advisable to adopt a special methodological document containing optimal analytical procedures necessary for the development of export strategies and programs, as well as a mechanism for evaluating the effectiveness of their implementation.Materials and methods. The research materials used the provisions of federal projects and regulations related to the support of export and investment activities, regional strategic planning documents of the Tomsk region, statistical data on export dynamics. The methodological basis of the study was the following general scientific methods: statistical, analysis, synthesis, method of interpretation of normative acts and others.The results of the study. The study found that in the absence of methodological development of the main provisions defining the specialization of the regional export strategy, this document can only play the role of a formal duplication of the provisions of regional socio-economic development strategies.First of all, within the framework of a special methodological recommendation document, it isnecessary to prescribe the analytical component of the development of an export strategy and regional programs adopted in accordance with it. In particular, there is a need for methodological foundations for conducting an export audit, which is provided for by the Regional Export Standard.Discussion and conclusion. An algorithm of actions is proposed for the development of a regional export strategy and program, which allows structurally ordering a set of measures to support exports.In addition, when developing export support measures, it is advisable to divide existing and potential exporters into groups regarding their readiness to expand export activities, followed by differentiation of support measures and effectiveness assessment in relation to each of the groups.
Assessment of the Effectiveness of Innovation Activities in the Current Context
Authors: Shapovalov V. V. 
Published: August 2024

Introduction. Innovations play crucial role in modern economic development. Over the past decades, research in this area has significantly expanded, covering not only the industrial sector but also services. A comprehensive approach is required to assess innovative activities, which includes analysis of economic indicators and applying new concepts, covering consumer value creation. This article studies various models and approaches to assessing innovative activities. Modern requirements for technological innovations continue to evolve, reflecting the increased role of consumers in evaluating products and services quality. Therefore, there is a need to develop new approaches in order to assess economic value of companies' innovative projects.Materials and methods. This paper utilized methods of comparative analysis, generalization, and optimization.Research results. Results of the study are based on various numerical indicators and methods of assessing the innovative activities of companies.Discussion and conclusion. The results of the research can help to improve innovative activities of Russian companies and enhance their competitiveness in a rapidly changing socio-economic environment.
Klasifikasi Citra Generasi Artificial Intellegence menggunakan Metodde Fine Tuning pada Residual Network
Authors: Hakim Sulthan Abiyyu , Ubaidillah Muhammad , Ramadhan Aditya Rizky , Hawari Rahmada Zulvia Azzahra , Rizky Audhinata Bebytama , Lutfi Raniyah , Hermanto Putri Tsania Maulidia , Yudistira Novanto 
Published: August 2024

Citra generasi AI memiliki beragam manfaat yang signifikan, baik dalam bidang penelitian maupun industri. Namun, penggunaan citra generasi AI juga memiliki dampak negatif dalam konteks hukum, politik dan berbagai aspek lain dalam kehidupan. Penelitian ini menitik beratkan klasifikasi citra generasi AI yang dapat mendeteksi keaslian dari suatu citra. Metode yang diusulkan adalah menggunakan model residual network yang telah dilakukan fine tuning. Teknik fine tuning yang dilakukan meliputi penggunaan learning rate scheduler berbasis warm up yang diikuti dengan linear scheduler, akumulasi gradien, dan augmentasi citra. Penelitian menunjukkan bahwa model residual network 152 menghasilkan performa terbaik dengan f1 score 0.963 dan loss 0.08.

Abstract

AI-generated images have various significant benefits, both in the realm of research and industry. However, the use of AI-generated images also has negative impacts in legal, political, and various other aspects of life. This research focuses on the classification of AI-generated images that can detect the authenticity of an image. The proposed method involves using a fine-tuned residual network model. The fine-tuning techniques applied include the use of a warm-up-based learning rate scheduler that followed by linear scheduler, gradient accumulation, and image augmentation. The research demonstrates that the Residual Network 152 model achieves the best performance with a f1 score of 0.963 and a loss of 0.08.
Model Deep Learning Untuk Klasifikasi Objek Pada Gambar Fisheye
Authors: Putri Riza Ayu , Suryadi Satyawan Arief , Prihantono Johanes Adi , Linggi Rinda Safana , Paramita I Gusti Ayu Putri Surya , Iswarawati Ni Kadek Emy , Akbar Fabian , Utomo Prio Adjie 
Published: August 2024

Pengenalan suatu objek secara otomatis adalah suatu pekerjaan yang sangat penting seperti halnya untuk mengidentifikasi sebuah objek tertentu. Jika hal ini dilakukan oleh manusia maka akan sulit untuk mendapatkan hasil yang baik dengan konsisten, oleh sebab itu digunakan komputer. Komputer dapat mengenali objek selayaknya kemampuan manusia dalam mengenali objek, dengan cara mengamati gambar yang diperoleh dari kamera, dan menerapkan metode pengenalan pada gambar tersebut. Pada penelitian ini metode pengenalan objek akan dikembangkan dengan menggunakan kamera fisheye yang memiliki luas tangkap empat kali kamera konvensional. Metode pengenalan objek yang digunakan yaitu deep learning dengan arsitektur CNN (Convolution Neural Network). CNN memiliki kemampuan untuk mengenali objek dalam gambar. Model CNN yang digunakan terdiri dari 1 layer, 2 layer, 3 layer, dan 7 layer. Sedangkan untuk melatih dan memvalidasi model tersebut digunakan 900 gambar dataset. Hasil pengujian pada penelitian ini menunjukan bahwa pada 7 layer CNN menghasilkan nilai presisi, recall dan akurasi tertinggi dengan komposisi nilai presisi 98,56%, recall 98,5% dan akurasi 98,59%. Nilai tersebut menunjukan bahwa hasil klasifikasi terhadap ketiga klasifikasi objek gambar manusia pada gambar fisheye dapat dilakukan dengan sangat baik.

Abstract

Object recognition is an important method of identifying object in an image. If this method is carried out by the humans, it is difficult to work continuously, therefore, it can be done by a computer. The computer can recognize an object on an image taken from a camera as if a human if it is trained whit a certain dataset of be object. In this research, a method a recognizing object is developed by using images captured from a fisheye camera. This camera provides better field of view four times then confessional camera. The object recognition method relies on convolutional neural network architecture that has capability to recognize object on an image. The CNN model is developed in four types of models. The first model consists of 1 layer, while the second model consist of 2 layers. The thread model consists of 3 layers, while the last consist of 7 layers. The number of datasets used for training and testing each model is 900 images. The experiment results showed that the four model which consist of 7 layers provide the best result. This is confirmed by the number of precisions, recall, and accuracy, which reach 98,56%, 98,5%, and 98,59% respectively. This result means that can classify three different objects of human on fisheye images well.