Miracle-dz/UniFAR-FTUs huggingface dataset:
Cold season Arctic strong cyclones enhance Atlantification of the Arctic Ocean

In recent years, as the Arctic Ocean’s warming trend has accelerated, there has been increasing attention on the process of Atlantification in the Arctic Ocean. This study focused on the Arctic Atlantic inflow zone (AAZ) as its research area. Multi-source reanalysis data and in-situ Argo float data were utilized to detect Arctic strong cyclones (ASCs) in the AAZ and analyze the resulting changes in the upper ocean. The findings reveal that during the cold season (October to March), influenced by ASCs’ intensity, frequency, tracks, and the concurrent weakening of ocean stratification, these cyclones can disrupt the cold halocline layer through mechanisms such as mixing and Ekman pumping. This process facilitates the transport of heat from the deep, warm and saline Atlantic Water within the ocean to the subsurface layers. Concurrently, ASCs during the cold season can enhance the process of Atlantification in the Arctic Ocean by intensifying the intrusion of the Barents Sea Branch. Additionally, the attenuation of oceanic stratification during ASCs is primarily driven by changes in salinity, particularly above the 100 m.
Nonlinear soil response—A reality?

Geotechnical models consistently indicate that the stress-strain relationship of soils is nonlinear and hysteretic, especially at shear strains larger than ∼10−5 to 10−4. Nonlinear effects, such as an increase in damping and reduction in shear-wave velocity as excitation strength increases, are commonly recognized in the dynamic loading of soils. On the other hand, these effects are usually ignored in seismological models of ground-motion prediction because of the lack of compelling corroborative evidence from strong-motion observations. The situation is being changed by recently obtained data. Explicit evidence of strong-motion deamplification, accompanied by changes in resonant frequencies, are found in the data from the 1985 Michoacan, Mexico, and the 1989 Loma Prieta, California, earthquakes, the events recorded by the vertical and surface accelerograph arrays in Taiwan, as well as a number of other events throughout the world. Evidence of nonlinear behavior becomes apparent beyond a threshold acceleration of ∼100 to 200 gal. Nonlinearity is considerable in cohesionless soil but may be negligible in stiff soils. The findings of recent years indicate that nonlinear site effects are more common than previously recognized in strong-motion seismology.
Cross-device target migration intelligent diagnosis method of wind power gearbox faults

The current convolutional neural network (CNN) deep learning algorithm for wind power gearbox fault diagnosis requires a substantial amount of high-quality tagged data from testbeds to achieve accurate results. However, it may not perform well in practical engineering scenarios where there is limited fault tag data and incomplete fault information. To overcome this challenge, a novel approach utilizing cross-device target transfer for intelligent diagnosis of wind turbine gearbox faults is proposed. This method transforms the fault diagnosis of wind turbine gearboxes into an image recognition and classification task. Initially, the source domain gearbox testbed data is subjected to dimension transformation using the Gramian angular difference field technique, resulting in the generation of small sample two-dimensional images. This transformation simulates the limited fault tag data scenario encountered in practical engineering. Once the fault features have been augmented, the small sample source domain gearbox testbed data is fed into the IConvNeXt deep CNNs. These CNNs are interconnected and specifically designed for the field. They aim to extract and recognize fault features, thereby creating a pre-training model. The pre-training model is then transferred to the target domain wind power gearbox data for fault diagnosis experiments. The results of these experiments demonstrate the significant effectiveness of the proposed method in recognizing faults in small sample wind power gearboxes within the target domain. Overall, this method successfully achieves the goal of intelligent fault diagnosis through target transfer. It addresses the challenge of limited fault tag data and incomplete fault information, thereby enhancing the performance of CNNs in practical engineering scenarios.
The Political Economy of Gig Work in the Pandemic: Social Hierarchies and Labour Control of Indian Platform Workers

This article examines capital–labour relations within location-based gig work in India, with a focus on the COVID-19 pandemic. The crisis of the pandemic exacerbated unemployment and created opportunities for platform services to expand, as consumers relied on digital platforms for their needs. This article assesses conditions across three gig services—food delivery, ride hailing and beauty work—based on interviews with 23 gig workers in the Delhi–National Capital Region in India and five organizers of gig worker collectives. The article discusses how workers’ incomes were cut even as they were exposed to higher risks to health and safety, and was accompanied by higher control exerted over their labour ostensibly for the safety of consumers. This control—both algorithmic and bodily—over workers derived its legitimacy from social hierarchies of caste and class between workers and consumers, and between workers and the platform. The article reveals a remarkable similarity in how workers fared across sectors, despite different classifications as essential or non-essential services. It establishes the significance of the pandemic to amplifying processes of labour commodification and labour control in gig work, ultimately contributing to antagonism between platforms and workers and to an emergent class politics of gig workers.
When enough is not enough: behavioral and motivational paths to compulsive social media consumption

Purpose Compulsive social media use has the potential to reduce well-being. In this study, the authors propose that there are two main paths to compulsive social media consumption. One is behavioral and based on habit; the other is motivational and rooted in the fear of missing out. This study aims to test the antecedents of these two drivers as well as their consequences for the tendency to engage in compulsive social media consumption. Design/methodology/approach The authors applied a quantitative research design and collected data through a survey of 600 respondents from a representative sample. The authors used structural equation modeling to test their conceptual model and hypotheses. Gender and age were included as moderators to investigate the model’s boundary conditions. Findings The authors found support for all the suggested relationships in the conceptual model. The findings indicate two main manifestations of compulsive social media use – always being logged in (i.e. the frequency of social media consumption) and excessive use (the intensity of consumption) – that in turn spurred a reinforcer of compulsivity: disconnection anxiety. The findings also indicate two main paths to compulsive social media consumption. One path is behavioral, based on habit, and the other is motivational, based on fear of missing out. Moreover, the authors identified the key antecedents of both paths. Habit formation was observed to be a function of situational cues (technological nudges in the online sphere) and consumer engagement. Fear of missing out was shaped by both injunctive norms (a consumer norm to be online) and descriptive norms (social proof). Research limitations/implications Although the antecedents of compulsive social media consumption suggested in this study have a strong and significant effect, the explained variance in the dependent variables being always logged in and excessive social media use indicates that there might be other drivers as well. These should be explored along with moderators other than gender and age to identify the potential boundary conditions of the model. Practical implications The main implications of the present work point to the “ease” with which typical or normal social media use may spiral out of control and become compulsive, with adverse implications for consumer health and well-being. Originality/value The behavioral and motivational paths to compulsive social media consumption have been less explored and have not yet been studied in conjunction, nor have their antecedents and consequences. Thus, this is a novel approach to understanding how social media use can potentially lead to reduced control and well-being.
Cuspal Deflection and Marginal Gap of Class II MOD Using Preheating Bulk-Fill Composite with Different Application Techniques

The novel bulk-fill composite to reduces time consumption and overcomes sensitive incremental techniques. Cuspal deflection and marginal gap are the common problems of composite material restoration. This in vitro study was conducted to evaluate the cuspal deflection and marginal gap of CL II MOD cavity restored with preheated One bulk-fill composite resin applied with different application techniques. Methodology: 48 upper 1st premolar teeth were prepared as CL II MOD cavities to be restored with One bulk-fill restorative composite resin without (Group A) or with preheating (Group B). Each group (n=24) was subdivided into three subgroups (n=8): A1 and B1 were restored in one increment, A2 and B2 were restored using two increments, and A3 and B3 were filled using a sublayer of a flowable composite resin. The intercuspal distance of the buccal and palatal cusps was recorded before preparation, after 5 minutes, and 24 hours from the restoration. The cuspal deflection (CD) was calculated by subtracting intercuspal distance after restorat ion (5 minutes or 24 hours) from before preparation for all subgroups. The marginal gaps were recorded from images by scanning electron microscopy (SEM) for both the proximal and gingival margins. The mean values of the data we re analyzed statistically using one-way ANOVA and paired t -test at p<0.05. Preheating of One bulk-fill resin did not pr oduce a significant effect on cuspal deflection compared with the control (p>0.05) however, the incremental layering of One bulk-fill composite recorded significantly lower cuspal deflection with or without preheating. While preheating of bulk-fill produced a significant decrease of both marginal gaps compared with the control subgroups (p≤0.05). Preheating One bulk-fill composite before cu ring did not influence the cuspal deflection while imp roved marginal adaptation in different application techni ques. The incremental technique significantly reduced cuspal deflection and marginal gap.
Weave: Abstraction and Integration Flow for Accelerators of Generated Modules

In modern times, domain-specific accelerators require numerous functional components to execute complex applications in a particular domain. To ensure efficient development, the conventional approach involves decomposing, implementing, and integrating modules. Over the past decade, the generator-based method has proven to enhance the productivity of module implementation. However, current abstractions pose challenges for integrating modules implemented by generators, due to implicit interface definitions, nonunified performance modeling, and fragmented memory management. These limitations result in a lower productivity of the integration process and decreased performance of the integrated accelerators. To overcome these drawbacks, we propose Weave, an abstraction for integrating generated modules and an agile design flow for domain-specific accelerators. The Weave abstraction guides module implementation and integration with a unified performance model and memory management. Furthermore, the Weave integration flow, consisting of generation, selection, and integration phrases, enables optimization of the performance of the integrated accelerator with a design space exploration algorithm and hierarchical memory management. In the experiments, the accelerator developed by Weave achieves $1.93\times $ higher performance in the deep learning domain compared to an open-source accelerator, and the integrated accelerator maintains performance for various applications with different memory access patterns.
Fake news during the Dutch elections: automatic classification and government strategies

This thesis explores the current policy strategies regarding combatting fake news and to what extend automated methods can help in detecting fake news on Twitter. This all with the focus on election times where fake news threatens the basic functioning of the democratic state. A small-scale machine learning study is conducted involving tweets related to the 2021 Dutch elections. To implement the text classification experiment, a collection of tweets was selected and annotated according to pre-defined categories. The aim is to get an understanding to what extent text features can help determine whether a Dutch tweet is true or false. The results show that it is a difficult task to determine whether a tweet is true or false based on the content. Yet, the European approach and their policy strategy describe the importance to invest in new technologies and further research the ways to detect fake news. It is a promising field of study as even with a small dataset, the Support Vector Machine was able to correctly classify 58% of the tweets. Data mining techniques are a useful tool in the detection of fake news on social media and can, with further research and improvements, increasingly play a role in protecting democratic states from the spread of misinformation.
Exploring the Potential of Hesperidin in Preventing Hypertrophic Scars: Insights from a Rabbit Ear Model

Background Hypertrophic scars, commonly occurring after trauma or surgery in critical areas like the head and joints, pose significant challenges to both physical and mental health due to their impact on skin function and aesthetics. While the complex pathogenesis involves fibroblast activation and collagen deposition, effective treatments are lacking, underscoring the importance of exploring pathogenesis and targeted therapies. Hesperidin, a bioactive compound in citrus fruits with diverse health benefits, including anti-fibrotic and anti-angiogenic effects, is the focus of this study with the aim of investigating its impact on hypertrophic scar formation, given its potential to promote blood flow and improve skin microcirculation. Objective This study aimed to observe the inhibitory effect of topical hesperidin on hypertrophic scars in rabbits. Methods A total of 8 healthy adult New Zealand white rabbits were used to establish a rabbit hypertrophic scarring animal model. Five wounds were created on each rabbit’s two ears, with three wounds on the left ear (groups A, B, and C) and two wounds on the right ear (groups D and E). After six days of wound drying postoperatively, the wounds were locally treated with medication as followed: group A, 0.1% hesperidin; group B, 1% hesperidin; group C, 1% triamcinolone acetonide; group D, Vaseline; and group E, blank control without any medication. After 28 days, the scar tissue samples were collected for histological examination. Results The results showed that the scar texture of groups B and C was softer and lighter in color, and the number of fibroblasts, capillaries, and inflammatory cells in the tissue was significantly less than those in the other three groups. The hypertrophic scar indices of groups B and C were significantly smaller than those of groups A, D, and E, and the difference was statistically significant (P < 0.05). There were no significant difference between groups B and C. Conclusion Topical application of hesperidin demonstrated promising potential for reducing hypertrophic scar formation in rabbits.
Visualization of Industrial Production Processes using 3D Simulation Software for Enhanced Decision-Making

This paper explores the use of 3D simulation software for visualizing industrial production processes and its potential to enhance decision-making for improved production efficiency, quality, and profitability. Industrial production processes are complex and involve many variables and factors that can interact in unpredictable ways. Visualization helps to simplify these complex interactions, identify patterns and relationships, and enable more informed decision-making.The research question that guides this paper is: How can the use of 3D simulation software for visualization of industrial production processes improve decision-making and optimize production efficiency, quality, and profitability? This paper will investigate the benefits and challenges of using 3D simulation software for visualizing industrial production processes, including the ability to identify bottlenecks, and optimize the production process. Further, the paper examines the role of visualization in enabling more informed decision-making, including the ability to analyze production data and make data-driven decisions. To illustrate this, an industrial automation case study consisting of a manufacturing industry modelled in a 3D simulation software has been presented.The results of this 3D-simulation model provide insights into the advantages and disadvantages of utilizing 3D simulation software to visualize industrial manufacturing processes. The article further presents the significance of these findings for production managers, engineers, and decision-makers. Thus, the purpose of this study is to help readers understand how using 3D simulation software for visualization of industrial production processes can improve decision-making and optimize production efficiency, quality, and profitability.
Whole-Genome Resequencing Reveals Selection Signatures of Abigar Cattle for Local Adaptation

Simple Summary Abigar cattle, native to southwestern Ethiopia’s hot and humid environment, are recognized for their adaptability and vital contribution to local livelihoods and the livestock value chain. Investigating their genetic basis for adaptive traits is crucial for sustainable use. However, there is a paucity of studies on genomic diversity, population structure, and selection signatures of Abigar cattle. This study introduces the first whole-genome sequencing of Abigar cattle, revealing genes linked to heat tolerance, immune response, and stress resilience in tropical conditions. These findings offer essential genomic insights for future Abigar cattle breeding. Abstract Over time, indigenous cattle breeds have developed disease resistance, heat tolerance, and adaptability to harsh environments. Deciphering the genetic mechanisms underlying adaptive traits is crucial for their improvement and sustainable utilization. For the first time, we performed whole-genome sequencing to unveil the genomic diversity, population structure, and selection signatures of Abigar cattle living in a tropical environment. The population structure analysis revealed that Abigar cattle exhibit high nucleotide diversity and heterozygosity, with low runs of homozygosity and linkage disequilibrium, suggesting a genetic landscape less constrained by inbreeding and enriched by diversity. Using nucleotide diversity (Pi) and population differentiation (FST) selection scan methods, we identified 83 shared genes that are likely associated with tropical adaption. The functional annotation analysis revealed that some of these genes are potentially linked to heat tolerance (HOXC13, DNAJC18, and RXFP2), immune response (IRAK3, MZB1, and STING1), and oxidative stress response (SLC23A1). Given the wider spreading impacts of climate change on cattle production, understanding the genetic mechanisms of adaptation of local breeds becomes crucial to better respond to climate and environmental changes. In this context, our finding establishes a foundation for further research into the mechanisms underpinning cattle adaptation to tropical environments.
Concordant GRADE-3 Truncal Ataxia and Ocular Laterodeviation in Acute Medullary Stroke

Abstract Background: Severe truncal ataxia associated with an inability to sit up without assistance (STA grade 3) is frequent in patients with central acute vestibular syndrome (AVS) involving the brainstem or cerebellum. When these patients have nystagmus, central HINTS excludes peripheral lesions; however, additional localization and lateralization signs are helpful, not only to resolve the peripheral versus central vestibular lesion dilemma, but to zero in on a precise lesion localization/lateralization to the lateral medulla, the most common ischemic lesion localization associated with an initially false-negative stroke MRI. Methods: This is a study of AVS patients with additional inclusion criteria: grades 2 or 3 ataxia with an eventual diagnosis of medullary stroke (MS), either involving the lateral medulla (LMS) or the medial medulla (MMS), and horizontal (h) gaze paralysis was the main exclusion criteria. All patients sat on the side of the bed or stretcher, with assistance if needed. A general neurologic examination followed in the sitting position, the testing protocol included the head impulse, spontaneous nystagmus, and skew deviation (HINTS) tests, followed by observation of the effect of brief 3–5 sec eyelid closure on ocular position, and saccade and pursuit eye movement tests. If they could sit, the protocol included the ability to stand with a wide base, then a narrow base, the Romberg test, and tandem gait. Radiographic lesion localization and horizontal gaze deviation concluded the protocol. Results: A total of 34 patients met the entry criteria, 34 MS (13 in the lateral medulla, 12 previously described, and 1 new patient), and 1 new MMS. Among them, n = 10/12 had grade 3 ataxia, and 3 (1 new patient) had grade 2 ataxia. In addition, overt ocular laterodeviation (OLD) was present in thirteen of them (35.3%). All OLD patients had gaze deviation and ipsilateral saccade and truncal lateropulsion, 1 medial medulla stroke patient had grade 3 truncal contrapulsion and contralateral hemiparesis without OLD, n = 20/21 patients with LMS without OLD had grade 3 truncal ataxia, and 1 had grade 2 truncal ataxia. Discussion: AVS patients with severe truncal ataxia (inability to sit without assistance) potentially have brainstem, cerebellum, or subcortical lesions. All patients had central HINTS; however, simultaneous direction-concordant STA 3 and OLD provided greater lateral medulla localization specificity, affecting the ipsilateral medulla. Future work to explore a practical posterior circulation stroke scale that includes HINTS, STA, and OLD will potentially select cases for thrombolysis even in the event of initially false-negative imaging.
Management of mixed forest in Cambodia : A case study in Sandan district , Kampong Thom

Exploitation of forests without utilizing information on harvest potential has resulted in mismanagement and deforestation worldwide, particularly in Southeast Asia. The purpose of this report is to provide the comprehensive information on harvest potential of Cambodia's mixed forest, which can be used as a strong foundation for sound forest management in Cambodia. Analysis of 20 inventoried clusters showed that, on average, the stocking of Sandan's mixed forest was 695 trees/ha and 168 m 3 /ha for stand density and stand volume, respectively. Of 168 m 3 , dipterocarp, non-dipterocarp and unknowns shared 37%, 37% and 26%, respectively. On a selective felling of 30 years, Sandan's mixed forest can potentially provide 28 m 3 /ha or 8 trees/ha, of which dipterocarp species represents 40% of the trees to be harvested. This figure is more or less the same to those in Thailand and Vietnam. Sound forest management requires the proper zoning of the forest area to be harvested and to be set aside from harvesting. Research on vegetation and wood utilization of non-dipterocarp and unknown trees should be encouraged since the majority of local people still depend mainly on them for cooking energy, food, medicine and other customary uses. Strong and long-term political commitment to research is always required to ensure the long-term sustainability of natural resources as whole for the benefit of future generations.