bluuebunny/crossref_metadata_2025_split huggingface dataset:
Managing Economic Uncertainty: Fuzzy Computational Models in International Oil Economy Forecasting
Authors: Zhang Qianqian 
Published: March 2024

Abstract
The use of sophisticated computational models for economic forecasting and decision-making is on the rise. Several studies have compared the Hybridization Adaptive Fuzzy Inference System (HAFIS) which is proposed in this research to traditional approaches; this review looks at them all to show how HAFIS is better in several areas, including precision, flexibility, responsiveness, decision support, and long-term planning. The version's accuracy, responsiveness, flexibility, decision support, and strategic making plans talents are more suitable as the included system evolves in phases. The thorough exam of Economic Uncertainty, which is divided into 3 principal impacts: Geopolitical Events, Market Pressures, and Environmental Factors, is the critical process of HAFIS. All of these items integrate to form the unpredictable surroundings that the oil commercial enterprise works in. Economic facts is notoriously misguided, however that is all treated by means of a mixture of rule bases, fuzzy common sense operations. The complicated Forecasting Model, which includes modern Fuzzy Computational Models, is on the middle of this level and can react dynamically to the various troubles posed by means of economic unpredictability and global marketplace tendencies. The fashions use adaptive procedures and fuzzy logic to decipher complex patterns inside the oil enterprise's complex fabric. The endorsed HAFIS method is portrayed as a complete and flexible technique to the challenges of working inside the unpredictable worldwide oil market. The use of actual-world data within the simulation evaluation proved that HAFIS outperformed extra traditional techniques of predicting. Because of its flexibility and flexibility, HAFIS has the potential to generate accurate projections, making it a doubtlessly beneficial asset for everyone involved inside the oil enterprise. In the end, these studies will be of assistance to professionals working in the oil industry in navigating the complexities of the global oil economic system. This will be accomplished via the development of forecasting methodologies and the demonstration of how to realistically apply such models to actual global situations.
Morphological and molecular characterization of Belondira khorramshahii sp. n. (Dorylaimida: Belondiridae) from Iran
Authors: Naghavi Arezoo , Niknam Gholamreza , Vazifeh Nasir , Mirzaeipour Zahra 
Published: March 2024

Abstract
Belondira khorramshahii sp. n. is described, based on morphological observations and D2-D3 expansion segment of the 28S rRNA analysis, collected from the rhizosphere of Persian oak (Quercus brantii L.) trees in Lorestan province, Iran. The new species is characterized by its medium sized (L = 1.04–1.36 mm) body; lip region width 6.5-8.0 µm, amalgamated, continuous with body counter; presence of distinct labial and post-labial sclerotizations; odontostyle 4.0-5.5 µm long with distinct lumen and aperture, neck 220–260 µm long; pharyngeal expansion 84–107 µm, V = 33–36; female reproductive system mono-opisthodelphic, anterior uterine sac 24.0–38.0 µm, tail cylindrical (2.8.5–33.5 µm, c = 38–46; c′ = 1.2–1.4 in females; 30.5–34.0 µm long; c = 33–39; c´ = 1.3–1.6 in males) with rounded end, spicules 30–34 µm long, three ventromedian supplements and lacking hiatus. The new species morphologically comes most close to B. apitica and B. tarjani.
Impact of Biocontrol Agents on Biochemical Changes of Aquatic Weed Water Hyacinth, Pontederia crassipes (Mart.) Solms-Laubach
Authors: Misra Deblina , Dutta Writuparna , Prieto Jorge Galarza , Ray Puja 
Published: March 2024

Abstract
Invasive weeds are rapidly adapting to evolutionary changes, brought about by exposure to the plethora of plant-antagonist’s interactions, which eventually leave an effect on the biological control of the weed. These interactions create an array of biochemical responses in the plant, which induce a range of defensive mechanisms to reduce the threat of injury. The present investigation reports the role of plant secondary metabolites in plant defense that may involve deterrence of antifeedant activity associated with the application of biocontrol agents against Pontederia crassipes. Generally, an infestation is preferred on non-challenged plants, as increased content of alkaloid, phenol, or tannin, which Pontederia crassipes produces when infested by its agents, deters the latter by providing a toxic unpleasant atmosphere. Variation in flavonoid level also brings about some physiochemical changes in the weed which impede the entry of phytopathogens. When a few metabolites are used to dissuade the agents, some, like glycosides, attract feeders to lay eggs and allow their population to flourish. This study concentrates on the signals that enable P. crassipes to recognize and respond to the attack and measure the effect in biochemical terms. Through this has, an overall outlook of the fitness costs of attack not only for the weed but over the range of trophic levels has been enlightened with more scope to understand the underlying mechanisms, before the multi-agent release of agents.
Early progressive disease in IDH-mutant grade 2 and 3 astrocytoma without CDKN2A/B homozygous deletions may indicate radiation necrosis
Authors: Ozeki Yukie , Narita Yoshitaka , Honda-Kitahara Mai , Yanagisawa Shunsuke , Takahashi Masamichi , Ohno Makoto , Miyakita Yasuji , Kikuchi Miu , Nakano Tomoyuki , Hosoya Tomohiro , Sugino Hirokazu , Satomi Kaishi , Yoshida Akihiko , Igaki Hiroshi , Kubo Yuko , Ichimura Koichi , Suzuki Hiromichi , Masutomi Kenkichi , Kondo Akihide 
Published: March 2024

Abstract

Purpose
Isocitrate dehydrogenase (IDH)-mutant astrocytoma without cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion (HD) typically follows a slow clinical course. However, some cases show early progression on MRI, and these characteristics have not been fully reported. This study aimed to elucidate the characteristics of those cases.
Methods
This retrospective study included 52 primary cases with astrocytoma, IDH-mutant, CNS WHO grade 2–3, reclassified from the original diagnosis based on WHO2021 classification. Patients underwent surgery followed by radiation therapy or/and chemotherapy at our institution from 2006 to 2019. Progression-free survival (PFS) and overall survival (OS) was analyzed.
Results
The grade 2 and 3 astrocytomas were 24 and 28, respectively; the median age was 38 years. Forty-three patients underwent radiotherapy, with or without chemotherapy. Progression was diagnosed in 28 patients through MRI, and early progression within 2 years of initial radiotherapy occurred in 11 cases (21.2%). Histologically, radiation necrosis was confirmed in four out of these 11 patients (36.4%). Two patients with telomerase reverse transcriptase (TERT) promoter mutations experienced recurrence within three years of the initial surgery. The 2-year true progression-free, except radiation necrosis, at 2 years after surgery in astrocytoma grades 2 and 3 was 91.3% in grade 2 and 88.5% in grade 3 astrocytoma.
Conclusion
The possibility of radiation necrosis exists in the early progression of grade 2–3 astrocytoma. A second surgery should be performed to confirm true recurrence or radiation necrosis. Astrocytomas with TERT promoter mutations may relapse relatively early and should be followed up with caution.
Reliability analysis of complete cubic networks based on extra conditional fault
Authors: Lv Mengjie , Liu Xuanli , Dong Hui , Fan Weibei 
Published: March 2024

Abstract

The reliability of multiprocessor systems is now a crucial concern in parallel computing. In fact, thanks to rapid and consistent technological advances in networking hardware and software, multiprocessor (core) systems have been successfully implemented. Consequently, there is a notable importance in examining the structures of interprocess communication, with a particular focus on investigating the fault tolerance and fault diagnosability of these structures to build a functionally efficient system. This paper investigates the $s$-extra connectivity ($s$-EC) and $s$-extra diagnosability ($s$-ED) of the complete cubic network $CCN(n)$. Specifically, we initially demonstrate that the $s$-EC of $CCN(n)$ is $\kappa_s(CCN(n))=(s+1)(n+1)-\frac{s(s+3)}{2}$ for $n\geq 3$ and $0\leq s\leq n-2$. Subsequently, we demonstrate that the $s$-ED under the PMC model is $t_s(CCN(n))=(s+1)(n+1)-\frac{s(s+3)}{2}+s$ for $n\geq 3$ and $1\leq s\leq n-2$. Similarly, under the MM* model, the $s$-ED is $t_s(CCN(n))=(s+1)(n+1)-\frac{s(s+3)}{2}+s$ for $n\geq 6$ and $1\leq s\leq \frac{n-2}{4}$. Finally, we conduct simulation experiments, and the results indicate that the $s$-EC consistently surpasses other known connectivities, including classical connectivity and $s$-component connectivity. Additionally, the $s$-ED consistently outperforms classical diagnosability and $s$-component diagnosability of $CCN(n)$.
Venezuelan equine encephalitis virus non-structural protein 3 dictates superinfection exclusion in mammalian cells
Authors: Hick Tessy , Zotler Taja , Bosveld Davita , Geertsema Corinne , Oers Monique van , Pijlman Gorben 
Published: March 2024

Abstract
Superinfection exclusion (SIE) is a well-known phenomenon induced by a broad spectrum of viruses to hinder a virus from the same virus family to establish a secondary infection in an already infected cell. Despite many years of study, the molecular mechanism(s) of alphavirus SIE remain enigmatic. Alphaviruses are arthropod-borne viruses that cause arthritogenic or encephalitic diseases in vertebrates, depending on the viral species. Several arthritogenic alphaviruses are known to block RNA replication of a superinfecting alphavirus via early proteolytic cleavage by non-structural protein 2 (nsP2). Here, we explore for the first time the SIE mechanism of an encephalitic alphavirus, Venezuelan equine encephalitis virus (VEEV). Using single-cell imaging techniques and encapsidated VEEV replicons encoding green or red fluorescent proteins, we observed immediate onset of VEEV interference, which increases to nearly full SIE capacity in three hours. In a series of experiments, we observed that transient expression of VEEV nsP3, but not nsP2, reduced alphavirus replication in the same mammalian cell, suggesting a key role for VEEV nsP3 in the mechanism of SIE. In particular, the VEEV nsP3 C-terminal hypervariable domain (HVD) was found to be required and sufficient for SIE of VEEV and the more distantly related Sindbis virus. As the nsP3 HVD is known to bind multiple host proteins to form RNA replication complexes and modulate the cellular stress response, we propose that sequestering of essential host protein(s) by VEEV nsP3 interferes with RNA replication of the superinfecting alphavirus.
DEAR: A Novel Deep-Level Semantics Feature Reinforce Framework for Infrared Small Object Segmentation
Authors: Ni Yihe , Zhao Xingbo , Li Yongxiang , Lu Qianwen , Tao Qingchuan , Yu Yanmei 
Published: March 2024

Abstract

Infrared Small Object Segmentation (ISOS) faces challenges in isolating small and faint objects from infrared images due to their limited texture details and small spatial presence. Existing deep learning methods have shown promise but often assume that these networks can effectively map small objects to deep semantic features. This mapping, however, may not be accurately learned by the model due to the excessive downsampling, which may cause the loss of high-level semantic representations essential for accurately identifying small objects in infrared images. To address this issue, this study introduces a novel learning paradigm, DEAR, designed to reinforce deep-level features of infrared small objects from three perspectives. Specifically, the Multi-Scale Nested (MSN) module merges shallow object features with deep semantic features through iterative interactions. The Central Difference Convolution (CDC) module enhances semantic contrast between small objects and their backgrounds, minimizing information loss during downsampling. Additionally, the Orthogonal Dynamic Fusion (ODF) module boosts the representation of deep object features through self-supervised learning. Experimental evaluations on the NUAA-SIRST and NUDT-SIRST datasets show that DEAR significantly outperforms 16 state-of-the-art methods in ISOS, demonstrating its effectiveness. The code is publicly available online at \href{https://github.com/nieyihe888/DEFER}{https://github.com/nieyihe888/DEAR}.
Experimental Study of the Effect of Different Winglet Configurations on The Lift and Drag Characteristics of BWB Aircraft
Authors: Ishrak Md. Shah , Shuvo Md. Adnan Nur Bhuiyan , Tasnim Faria , Patnaik Sidharth Sankar 
Published: March 2024

Abstract

Sustainable aviation is currently a major concern since people are constantly relying on aircraft for transport over long distances in a short amount of time. Newer technologies are constantly being developed to enhance the aerodynamic efficiency of existing aircraft and improve fuel conservation. Winglets are one such technology. Our research focuses on how different winglet designs affect the lift and drag characteristics of blended-wing body aircrafts; the concept of these designs is currently being researched and compared to that of the base model with no winglet. The models were subjected to both computational and experimental analyses at three different velocities and six angles of attack to determine the lift and drag values resulting from various winglet configurations. The results showed that Split Fence had the best performance in both computational and experimental analyses, with an L/D of 10.608 at a 5° angle of attack during the CFD analysis compared to 5.52 for the base model. The Spikelet and the Spike Scimitar Winglet also showed high aerodynamic efficiency. The C-Winglet, however, showed poorer performance than did the other winglets. The insights from this research can help optimize winglet designs and explore the design of BWB aircraft, leading to substantial reductions in fuel consumption and carbon emissions in the aviation industry.
Corporate governance parties effect on private banks’ profitability: Panel fixed effect regression analysis
Authors: Mebratu Agumas Alamirew 
Published: March 2024

Abstract
The banking disaster affects the monetary mechanism and economic system of a country. The aim of this article is to quantitatively examine the factors that affect the profitability of Ethiopian private commercial banks. In this study, the quantitative research approach, descriptive research design, and secondary data sources collected from the National Bank of Ethiopia for the period 2013 to 2022. The population of this study included all private commercial banks operating in Ethiopia. The findings of the panel fixed-effect regression analysis revealed that the profitability of the selected bank, as measured by return on assets, was significantly influenced by various factors including the size and capital adequacy ratio of the financial institution, control performance, legal reserve ratio, and liquidity ratio. The implications of these findings highlight the combined impact of macro and micro factors on the overall profitability of private commercial banks in Ethiopia.
Validation of the Arabic Version of the Brief Emotional Intelligence Scale (BEIS-10)
Authors: Kanj Gaelle , Obeid Sahar , Malaeb Diana , Azzi Vanessa , Hallit Rabih , Hallit Souheil , Fekih-Romdhane Feten 
Published: March 2024

Abstract

Background Emotional Intelligence (EI) has been a widespread topic of scientific research and discussion among individuals and institutions over the last years, giving room for debate concerning its measurement and applications. One of the shortest, simplest, most economical and increasingly used self-report measures is the Brief Emotional Intelligence Scale (BIES-10), whose validity and reliability have been demonstrated in a sample of individuals from various samples and contexts. The present study contributed to the literature by examining the psychometric properties of an Arabic translation of the BEIS-10 in a native Arabic-speaking population from Lebanon. Method This cross-sectional study was carried out between December 2020 and January 2021; 449 non-clinical adults were included (mean age = 24.34 years; 70.6% females). The forward-backward translation approach was adopted to develop an Arabic version of the BEIS-10. Results CFA provided evidence for a unidimensional solution of the BEIS-10 in its Arabic translation, thus allowing a total score to be obtained that reflects the overall EI construct. Excellent internal consistency was evidenced by a McDonald’s ω of .94 and a Cronbach α of .94. The Arabic BEIS-10 showed significant invariance across gender at the scalar, metric, and configural levels. Furthermore, greater scores on EI have been shown to significantly correlate with higher positive and negative affect, thus attesting to the convergent validity of the Arabic BEIS-10. Conclusion Findings suggest that the Arabic BIES-10 is a valid and reliable self-administered measuring tool for the assessment of EI in Arab settings. Considering its simple and brief administration, this version of the scale might be of better convenience in Arab settings beset by shortage of resources and financial turmoil.
Interpreting mineral deposit genesis classification with decision maps: A case study using pyrite trace elements
Authors: Wang Yu , Qiu Kun-Feng , Telea Alexandru C. , Hou Zhao-Liang , Zhou Tong , Cai Yi-Wei , Ding Zheng-Jiang , Yu Hao-Cheng , Deng Jun 
Published: March 2024

Abstract
Machine learning improves geochemistry discriminant diagrams in classifying mineral deposit genetic types. However, the increasingly recognized “black box” property of machine learning has been hampering the transparency of complex data analysis, leading to challenges in deep geochemical interpretation. To address the issue, we revisited pyrite trace elements and proposed the use of the “Decision Map,” a cutting-edge visualization technique for machine learning. This technique reveals mineral deposit classifications by visualizing the “decision boundaries” of high-dimensional data, a concept crucial for model interpretation, active learning, and domain adaptation. In the context of geochemical data classification, it enables geologists to understand the relationship between geo-data and decision boundaries, assess prediction certainty, and observe data distribution trends. This bridges the gap between the insightful properties of traditional discriminant diagrams and the high-dimensional efficiency of modern machine learning. Using pyrite trace element data, we construct a decision map for mineral deposit type classification, which maintains the accuracy of machine learning while adding valuable visualization insight. Additionally, we demonstrate two applications of decision maps. First, we show how decision maps can help resolve a dispute concerning the genetic type of a deposit whose data were not used in training the models. Second, we demonstrate how the decision maps can help understand the model, which further helps find indicator elements of pyrite. The recommended indicator elements by decision maps are consistent with geologists’ knowledge. This study confirms the decision map’s effectiveness in interpreting mineral genetic type classification problems. In geochemical classification, decision maps mark a shift from conventional machine learning to a visually insightful approach, thereby enhancing the geological understanding derived from the model. Furthermore, our work implies that decision maps could be applicable to diverse classification challenges in geosciences.
Quality Assessment of Young Sparkling Wines of Crimean Indigenous Grape Varieties
Authors: Lutkov Igor , Makarov Alexander , Shmigelskaya Natalia 
Published: March 2024

Most domestic sparkling wines are made of traditional champagne grape varieties. However, indigenous Crimean cultivars could increase the output of high-quality original beverages if a proper technology was introduced.
This research featured young sparkling wines from Crimean grape varieties, i.e., Soldaya, Shabash, Kokur Beliy, Sary Pandas, Kefesiya, Dzhevat Kara, and Ekim Kara. Organic acids, sugars, glycerin, phenolic substances, and ethanol were determined by high performance liquid chromatography; the content of amine nitrogen was measured by formalin titration. The optical profile of the wine samples was subjected to the colorimetric method while their foamy properties were studied by bubbling the samples in a measuring cylinder. The sparkling properties depended on the rate of CO2 desorption; the volumetric method made it possible to define the CO2 content; the viscosity was measured using a viscometer. The sensory assessment followed State Standard 32051-2013, ISO 5492:2008, and ISO 11035:1994.
The samples of Kokur Beliy, Sary Pandas, and Soldaya received high tasting ratings (≥ 9.0 points), as did the red variety of Kefesiya (8.95 points). They demonstrated a clear typical aroma and a harmonious taste, as well as good foamy and sparkling properties. The maximal foam volume correlated with amine nitrogen (r = 0.762) while the sparkling properties correlated with the mass fraction of bound CO2 (r = 0.977). The red sparkling wine from the Kefesiya variety had a dark garnet color due to its high anthocyanins. It also contained quercetin and glycoside, which are known for their biological (P-vitamin) activity and powerful antioxidant properties. The early low-sugar (< 18 g/100 cm3) varieties of Dzhevat Kara and Ekim Kara had the same acidity but demonstrated a less diverse phenolic profile and were paler in color.
In this research, the indigenous Crimean grape cultivars of Kokur Beliy, Sary Pandas, Soldaya, and Kefesia showed good prospects for young sparkling wines. Other varieties needed special technologies to preserve their typical properties and the aroma/taste balance. The new technology makes it possible to obtain unique high-quality products right in the harvest year, thus increasing the range and volume of sparkling wine production.
Quails of Stavropol Region: Autumn Food Habits
Authors: Kaledin Anatoly , Malovichko Lyubov΄ , Rezanov Alexander , Drozdova Lyudmila , Serikbayeva Andiya 
Published: March 2024

Quails (Coturnix coturnix (Linnaeus, 1758)) are the only migratory Galliformes species. Quails are nestling ground-dwelling birds, feeding on seeds and crawling insects. Wild quails inhabit many parts of Russia. Quail farming is quite popular because quail meat is low in calories and possesses a number of beneficial properties, e.g., it is rich in proteins, contains little fat and virtually no carbohydrates, etc. As a rule, quails winter in Transcaucasia and Southern Europe; however, they sometimes prefer to stay in southern regions for the winter. This article introduces the autumn food habits of quails in the Central Ciscaucasia.
The research relied on the analysis of stomach contents of 156 birds killed by hunters or hit by vehicles in several districts of the Stavropol Region. The material was collected in the autumn in 2008–2021.
In the Central Ciscaucasia, quails are mesophiles and inhabit abandoned wheat and pea fields. The population fluctuates from year to year, depending on spring weather conditions. Their optimal nestling grounds include irrigated fields and areas near canals and ponds. In the steppe regions, they prefer agricultural areas, e.g., orchards, vineyards, holiday villages, sheep sheds, green belts along fields, roads, and railways, etc. Being phytophages, they rely on plant and, to a lesser extent, animal forage.
In the autumn, they feeding on green plants, wheat grain, seeds of cultivated and wild plants, and insect larvae.