bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adsorption of amoxicillin onto breadfruit seed hull biochar modified using ZnONPs: disinfection and decontamination
Authors: Amaku James Friday , Mtunzi Fanyana M. 
Published: November 2024

AbstractBiochar (BHC) and biochar-supported nanocomposite (BZNC) were employed for the removal of amoxicillin (AMX) from simulated and real wastewater. The biochar and nanocomposite were characterized using Fourier transform infrared (FTIR) spectroscopy, powder X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET), and scanning electron microscopy (SEM) spectroscopic techniques. Agitation speed of 120 rpm, solution pH 7, 50 mg dosage, and 120-min agitation time were employed for the optimization of the adsorption capacity of BZNC and BHC. Increases in sorbent dosage, contact time, and initial AMX concentration improved BZNC and BHC’s capacity to sequester AMX. The kinetic best description of the absorption of AMX onto BHC and BZNC was provided by the pseudo-second-order and pseudo-first-order models, respectively. Furthermore, Freundlich and Langmuir isotherm models were observed to best describe the equilibrium data obtained for the uptake of AMX onto BZNC and BHC, respectively. At 318 K, the optimal adsorption capacities of BZNC and BHC were found to be 61.02 mg g−1 and 49.82 mg g−1, respectively. The entropy-driven adsorption of AMX onto the BZNC and BHC was thermodynamically possible. It was observed that BZNC exhibited better antioxidant and antimicrobial potential. Hence, this study shows that BZNC has the ability to efficiently disinfect and cleanse industrial wastewater that contains AMX.
Effects of local gas shielding on induction brazing of stainless steel: an experimental approach
Authors: Weis S. , Grunert R. , Fedorov V. , Brumm S. , Uhlig T. 
Published: November 2024

AbstractNi-based brazing fillers are primarily utilized in vacuum furnaces or continuous furnaces. However, the application of such furnace techniques imposes technical and economic limitations on the size of brazeable components. Induction brazing offers an alternative to overcome these limitations, enabling the brazing of large components by means of localized heating and gas shielding. This study aims to improve the understanding of process control and required gas quality for effective brazing by conducting experiments on tube-to-tube joints using Ni-based brazing alloys. To determine their impact on brazing outcomes, process gases with varying oxygen contents were systematically tested. The microstructure of the brazed joints was analyzed by light microscopy. The influence of process gas quality on corrosion behavior was examined using a capillary microcell. High residual oxygen contents in the process gas led to a shift in the corrosion potentials. Additionally, the mechanical properties of the joints are affected. Therefore, the monotonic mechanical properties were investigated at ambient temperature. The findings of this research offer practical recommendations and present a newly developed shielding gas nozzle for industrial applications. These insights support the optimization of induction brazing processes and highlight the potential for increasing the quality and efficiency of brazing large components.
Advancements and Limitations: A Systematic Review of Remote-Based Deep Learning Predictive Algorithms for Depression
Authors: Haley Fintan , Andrews Jacob , Moghaddam Nima 
Published: November 2024

AbstractThis systematic literature review explores the emerging field of remote-based deep learning predictive algorithms for depression, focusing on addressing the limitations of traditional diagnostic methods and examining the current state of research in this novel area. A systematic search was conducted in Embase, Medline, Web of Science Core Collection, CINAHL, and PsycINFO in June 2023. To capture relevant studies, titles and abstracts of the papers were reviewed against predefined inclusion and exclusion criteria using four groups of keywords addressing prediction, depression, validity, and deep learning. Eligible studies were systematically reviewed based on the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist. The risk of bias was assessed using the Prediction Model Risk of Bias Assessment (PROBAST) Tool for methodological quality. The synthesis of data was conducted using the Synthesis Without Meta-Analysis (SWiM) framework. From 286 studies initially identified, 6 studies met all inclusion criteria, published between 2020 and 2023. Performance metrics revealed the potential of deep learning models, with accuracy rates reaching as high as 98.23%. Convolutional neural networks (CNNs) emerged as the predominant model, with applicability across diverse data sources such as speech recordings, body motion data, and facial images. However, issues related to risk of bias were prevalent, with most studies lacking essential reporting details and employing relatively small sample sizes. The review identified limitations in the practical application of these models, including limited demographic representation, absence of external validation, and a notable absence of models capable of anticipating the onset of depression. While the current models focus primarily on identifying existing depression of any duration, there is a need for advancements that enable the anticipation of future depressive episodes. To advance this field, we recommend standardized reporting practices, larger and more diverse datasets, external validation, and the development of predictive models that anticipate depression occurrences in advance. These enhancements will contribute to the credibility and real-world relevance of these models. While remote-based deep learning predictive algorithms hold promise in revolutionizing depression prediction, they require refinement and validation to fulfil their potential in clinical practice. This review underscores the need for further research and development in this area to address the identified limitations and contribute to improved mental health assessment and intervention.
Generalized Poincaré-Dulac Singularities of Holomorphic Foliations
Authors: Fernández-Sánchez Percy , Mozo-Fernández Jorge 
Published: November 2024

AbstractIn this paper, we study the analytic classification of a class of nilpotent singularities of holomorphic foliations in $$({\mathbb {C}}^2,0)$$

(

C

2

,
0
)

, those exhibiting a Poincaré-Dulac type singularity in their reduction process. This analytic classification is based in the holonomy of a certain component of the exceptional divisor. Finally, as a consequence, we show that these singularities exhibit a formal analytic rigidity.
Recent advances and future perspectives in electrochemical sensing of biomarkers by using MOF- based electrode materials
Authors: Arivazhagan Mani , Prabu Samikannu , Elancheziyan Mari , Jakmunee Jaroon 
Published: November 2024

AbstractMetal-organic frameworks (MOF) are an extraordinarily versatile class of porous nanostructured materials that have gained popularity in several scientific fields. Organic ligands are coupled to the inorganic metal centers or clusters to produce MOFs. This frontier review paper critically summarizes the most recent developments in MOF-based materials for electrochemical (EC) detection of key biomarkers, including glucose, dopamine, lactic acid, L-tryptophan, uric and ascorbic acids, H2O2, and nicotine. Various electrochemical techniques, such as cyclic voltammetry (CV), chronoamperometry, and differential pulse voltammetry (DPV) have been employed to enhance detection sensitivity and specificity. MOF-based EC sensing systems hold promise in medical diagnostics, particularly for diseases such as diabetes, neurodegenerative and cardiovascular disorders, and cancer. These sensors offer distinctive features like an extensive specific surface area, tunable pore sizes, exceptional catalytic performance, and abundant active sites, enabling sensitive, rapid, and cost-effective biomarker detection. The construction of different nanostructures, such as nanoparticles, nanorods, nanowires, and three-dimensional networks, has further improved the electro-catalytic efficiency of MOF-based materials. We also critically assess the performance of advanced MOF-derived nanostructured EC sensor platforms, and discuss future challenges and potential improvements, particularly for enzyme-free EC sensors in clinical diagnostics. This work underscores the potential of MOF-based EC sensors as versatile and effective tools for detecting a wide range of compounds and biomolecules relevant to human health.
Graphical abstract
Laser powder bed fusion of porous 304SS samples for use in developing oil impregnated ball bearings
Authors: Mashayamombe Tafadzwa , Matope Stephen 
Published: November 2024

Abstract
The ball bearing market is mature where there is a massive range of products available with new ones being developed all the time due to technological advancements. Additive Manufacturing (AM) provides a promising approach for developing oil-impregnated ball bearings. Oil impregnated bearings are critical for applications requiring smooth and low-friction motion. This study explores the feasibility of utilizing laser powder bed fusion (LPBF) technology to fabricate 304 stainless steel (304SS) samples with open pores, which can then be impregnated with a lubricant. To achieve this, 304SS powder was used, and optimum selective laser melting (SLM) printing parameters were altered to induce intentional pores. Initial screening of samples involved Archimedes density measurements and computed tomography (CT) scanning was conducted on a selected samples to assess their porosity levels. CT scan foam analysis results indicated a correlation between hatch spacing and porosity. Results revealed trends in cell volume and solidified scanning tracks thickness, indicating greater connectedness with larger pores. Synthesis of these findings could help in the development of efficient and reliable open pores that may find use in oil-impregnated self-lubricating ball bearings.
Stable plastid transformation in kiwifruit (Actinidia chinensis)
Authors: Chen Qiqi , Wu Yuyong , Wang Yanchang , Zhang Jiang , Li Shengchun 
Published: November 2024

AbstractPlastid transformation offers valuable benefits in plant biotechnology, such as high-level transgene expression and the absence of gene silencing. Here we describe the first protocol of a plastid transformation system for a woody vine (liana) kiwifruit (Actinidia chinensis). The transgenic DNA carries a spectinomycin-resistance gene (aadA) cassette and a green fluorescent protein (GFP) reporter gene cassette, flanked by two adjacent kiwifruit plastid genome sequences, thereby allowing targeted insertion between the trnfM and trnG genes. Six spectinomycin-resistant shoots were obtained out of 12 plates subjected to bombardment, and two were positive events, confirmed through PCR and Southern blot analyses. The GFP was localized to plastids as monitored by confocal laser scanning microscopy and reached 2.5% of leaf total soluble protein. Success in kiwifruit extends transplastomic technology of woody species beyond poplar, and will provide an attractive biosynthetic chassis for molecular farming.
Predicting neonatal mortality in preterm neonates 32 weeks of gestation or less by using the modified NEOMOD score
Authors: Lawtrakulngam Nathakorn , Pomrop Mallika , Manopunya Satit , Kosarat Shanika , Khuwuthyakorn Varangthip 
Published: November 2024

Abstract
Background
Preterm neonates have a significantly higher mortality rate compared to full-term neonates. The Modified NEOMOD Score (mNEOMOD) predicts neonatal mortality in preterm neonates with high sensitivity and specificity.

Objective
This study aimed to evaluate the efficacy of the mNEOMOD in predicting neonatal mortality among preterm neonates and identify associated variables associated with increased neonatal mortality.

Methods
This diagnostic test study included neonates with a gestational age of ≤ 32 weeks admitted to the NICU from 2018 to 2022 at Chiang Mai University Hospital. The mNEOMOD assessed dysfunction across eight organ systems based on the worst cumulative score during the first seven days of life. Predictive accuracy was determined using the Area Under the ROC Curve (AUC). Clinical and demographic variables were compared between survival and death groups.

Results
Among 280 neonates, 277 (98.9%) had multi-organ dysfunction (MOD), with a mortality rate of 10.7%. The mNEOMOD showed higher scores in the mortality group compared to the survival group (median score: 13 vs. 5). The predictive accuracy was highest at a cutoff value of 9, with 100% sensitivity and 91.2% specificity. Significant variables for increased mortality included severe intraventricular hemorrhage (aOR 8.76, p < 0.001) and APGAR score < 7 at 5 min (aOR 3.46, p 0.010).

Conclusion
The mNEOMOD is reliable tool for predicting neonatal mortality in preterm neonates ≤ 32 weeks gestation.
Effort versus accuracy: How well do we understand why others perceive threats?
Authors: Landau-Wells Marika 
Published: November 2024

Abstract
Threat perception provokes a range of behaviour, from cooperation to conflict. Correctly interpreting others’ behaviour, and responding optimally, is thought to be aided by ‘stepping into their shoes’ (i.e. mentalising) to understand the threats they have perceived. But IR scholarship on the effects of attempting this exercise has yielded mixed findings. One missing component in this research is a clear understanding of the link between effort and accuracy. I use a US-based survey experiment (study N = 839; pilot N = 297) and a novel analytic approach to study mentalising accuracy in the domain of threat perception. I find that accurately estimating why someone feels threatened by either climate change or illegal immigration is conditional on sharing a belief in the issue’s overall dangerousness. Similar beliefs about dangerousness are not proxies for shared political identities, and accuracy for those with dissimilar beliefs does not exceed chance. Focusing first on the emotional states of those who felt threatened did not significantly improve accuracy. These findings suggest that: (1) effort does not guarantee accuracy in estimating the threats others see; (2) emotion understanding may not be a solution to threat mis-estimation; and (3) misperception can arise from basic task difficulty, even without information constraints or deception.
Canning cannabis: Consumer preferences for CBD- and THC-infused beverages
Authors: Staples Aaron J. 
Published: November 2024

AbstractCannabis regulatory reform has opened areas for product innovation and entrepreneurship. One dimension that has so far been understudied is the potential for cannabidiol (CBD) and tetrahydrocannabinol (THC) beverages. This study uses double-bounded contingent valuation techniques and parametric and nonparametric estimation procedures to assess consumer demand and willingness to pay (WTP) for various cannabis-infused beverages. By targeting a nationally representative sample of U.S. adults, the study finds that roughly half of consumers are willing to try cannabis-infused beverages. Among these respondents, cannabis-infused juices and sweetened iced tea elicit the highest mean WTP, though the WTP for other beverage options varies across demographics and consumer preferences. On average, the mean WTP for THC-infused beverages is 12.5% higher per 12 oz can than its CBD-infused counterpart, and younger consumers are willing to pay more for each of these products. These results have important implications for entrepreneurial decision-making, product development, and marketing strategies.
Unraveling the economic impact of wine counterfeiting: An analysis of the Sassicaia 2015 scandal and its consequences
Authors: Kuang Yuyan , Tolhurst Tor N. , Alston Julian M. 
Published: November 2024

AbstractThis paper examines the economic impact of wine counterfeiting, with a focus on the Sassicaia scandal, publicized in 2020, regarding counterfeit 2015 vintage bottles of the iconic Super Tuscan wine. Wine fraud, documented since ancient Rome, has evolved alongside the industry, with key developments such as the Appellation d'Origine Contrôlée system aiming to curb it. The paper briefly reviews three other significant modern cases of wine counterfeiting: the Hardy Rodenstock “Jefferson bottles” affair, the Brunello di Montalcino scandal, and Rudy Kurniawan’s counterfeit operation. It then shifts to a detailed analysis of the case of Sassicaia. We combine informal analysis using data plots and a formal difference-in-differences analysis to assess the market impact of the 2015 Sassicaia scandal. We find that, surprisingly, the scandal led to an increase in the price of authentic 2015 Sassicaia, perhaps driven by perceived rarity and media attention.
How Ideas and Strategic Learning Fostered the 2022 Agreement Between the Liberal Party of Canada and the New Democratic Party
Authors: Massé Louis , Béland Daniel 
Published: November 2024

AbstractWhy did the Liberal Party of Canada (LPC) and the New Democratic Party (NDP) enter into a supply-and-confidence agreement in March 2022? Interparty cooperation among federal parties is rare during minority governments, and yet the agreement created a formal alliance in the House of Commons. In this article, we argue that ideational factors led to the 2022 agreement. We examine the role of programmatic beliefs and strategic learning during the COVID-19 crisis and the 2019-2021 election sequence to shed light on changes in federal parliamentary strategies in Canada. From ad-hoc voting coalitions to extended cooperation on social policymaking, the LPC and the NDP learned how to work together in the House of Commons while using the agreement as a tool to compete with each other in anticipation of the next federal election.
A refined robotic grasp detection network based on coarse-to-fine feature and residual attention
Authors: Zhu Zhenwei , Huang Saike , Xie Jialong , Meng Yue , Wang Chaoqun , Zhou Fengyu 
Published: November 2024

Abstract
Precise and efficient grasping detection is vital for robotic arms to execute stable grasping tasks in industrial and household applications. However, existing methods fail to consider refining different scale features and detecting critical regions, resulting in coarse grasping rectangles. To address these issues, we propose a real-time coarse and fine granularity residual attention (CFRA) grasping detection network. First, to enable the network to detect different sizes of objects, we extract and fuse the coarse and fine granularity features. Then, we refine these fused features by introducing a feature refinement module, which enables the network to distinguish between object and background features effectively. Finally, we introduce a residual attention module that handles different shapes of objects adaptively, achieving refined grasping detection. We complete training and testing on both Cornell and Jacquard datasets, achieving detection accuracy of 98.7% and 94.2%, respectively. Moreover, the grasping success rate on the real-world UR3e robot achieves 98%. These results demonstrate the effectiveness and superiority of CFRA.
Imagery-based cognitive therapy to reduce emotional dysregulation and mood instability in bipolar disorder: a case-series study
Authors: Paulet Thomas , Weiner Luisa 
Published: November 2024

Abstract

Introduction:
Bipolar disorder (BD) has a significant impact on functioning in the absence of acute mood episodes. This has been associated with subsyndromal symptoms, co-morbidities, and emotional dysregulation. The present study aims to evaluate the acceptability and preliminary efficacy of imagery-based cognitive therapy (ImCT) in a French community setting. We were particularly interested in the link between mental imagery and emotional dysregulation as this may clarify the mechanisms involved in the potential efficacy of the therapy and ultimately improve its relevance.

Method:
Ten participants underwent ImCT, with weekly assessments of mood fluctuations, anxiety, and emotional dysregulation conducted over 1 month (i.e. pre-therapy, post-therapy and 1-month follow-up). Recovery, post-traumatic stress symptoms and self-compassion were measured at baseline and post-therapy. Attrition rates and satisfaction were measured.

Results:
All participants who completed therapy (n=8) reported high levels of satisfaction. Five of them showed reliable individual improvement on emotion dysregulation scores. At the group level, a significant decrease in mood fluctuation with a large effect size was found post-therapy.

Conclusion:
ImCT showed good acceptability among participants who completed the study. Importantly, our study is the first to provide an indication that ImCT may alleviate subsyndromal mood symptoms but also emotional dysregulation in individuals with BD. This latter finding is particularly relevant given the scarcity of validated psychosocial interventions targeting emotional dysregulation in BD.
Supplementation of diet with Astaxanthin and DHA prevents gestational and lactational undernourishment-induced metabolic derangements in dams: a metabolomic approach
Authors: Hegde Pramukh Subrahmanya , Agni Megha Bhat , Rai Praveen , Upadhyay Shubham Sukerndeo , Aravind Anjana , Keshava Prasad Thottethodi Subrahmanya , Gowda K.M. Damodara 
Published: November 2024

Abstract
Nutrition is the critical nongenetic factor that has a major influence on the health status of an organism. The nutritional status of the mother during gestation and lactation plays a vital role in defining the offspring’s health. Undernutrition during these critical periods may induce chronic metabolic disorders like obesity and cardiovascular diseases in mothers as well as in offspring. The present study aims to evaluate the impact of undernutrition during gestational and lactational periods on the plasma metabolic profile of dams. Additionally, we investigated the potential synergistic mitigating effects of astaxanthin and docosahexaenoic acid (DHA) on dysregulated plasma metabolic profiles. Evaluation of plasma lipid profile revealed that undernourishment resulted in elevated levels of total cholesterol, triglycerides, low density and very low-density lipoproteins in dams. Liquid chromatography-tandem mass spectrometry (LC–MS/MS) based untargeted metabolomics illustrated that pathways related to lipid metabolism, such as cholesterol metabolism, steroid biosynthesis and metabolism of amine-derived hormones, were dysregulated by undernourishment. Additionally, pathway enrichment analysis predicted that there is a high incidence of development of desmosterolosis, hypercholesterolaemia, lysosomal acid lipase deficiency and Smith–Lemli–Opitz syndrome in the offspring, reflecting predisposition in mothers. However, synergistic supplementation of astaxanthin and DHA ameliorated these adverse effects by regulating a separate set of metabolic pathways associated with lipid metabolism. They included branched chain amino acid degradation such as valine, leucine and isoleucine, metabolism of alpha-linolenic acid, lipoic acid, lysine degradation, biosynthesis, elongation and degradation of fatty acids.