Miracle-dz/UniFAR-FTUs huggingface dataset:
Customer Shopping Behavior on E-Commerce Effectiveness Using the Information System Success Theory Approach

In addressing the purpose of this research, it seeks to unravel the intricacies of payment systems in e-commerce, particularly focusing on the challenges posed by the indirect nature of transactions. The design and methodology of the study involve a comprehensive examination of customer perceptions and concerns, emphasising payment security and privacy in the digital landscape. This investigation stems from recognising that security is a linchpin for the successful development of Internet-based payment systems. Within the discourse of e-commerce, customer apprehensions regarding the security of their payment and financial information, encompassing details like credit card transaction numbers, are prevalent. As the e-commerce market in Indonesia experiences rapid growth, exemplified by the leadership of Tokopedia, the competition among companies and organisations intensifies. The endeavour to satisfy customers becomes a formidable challenge for many, underscoring the need for nuanced insights into the factors influencing customer satisfaction. Adopting the Information System Success Theory as a theoretical framework, this study posits that customer concerns about the payment system significantly impact the perceived quality of service. In this context, quality serves as a yardstick for measuring effectiveness by delving into the intricate layers of customer satisfaction. The research employs Structural Equation Modelling (SEM) as the chosen methodology, engaging with the perspectives of 100 respondents to derive meaningful conclusions. Despite its contributions, the study acknowledges its limitations, including the inherent subjectivity in customer perceptions. Nevertheless, the implications drawn from this research carry significance for the ongoing refinement and enhancement of e-commerce payment systems, providing valuable insights for practitioners, researchers, and policymakers navigating the dynamic intersection of technology and consumer satisfaction in the digital age.
Bleeding and Perforation Complications after Follow-Up Colonoscopies in Faecal Immunochemical Test-Based Colorectal Cancer Screening: Insights from a Retrospective Case–Control Study

Monitoring complications of colonoscopies after a positive faecal immunochemical test (FIT-colonoscopies) is crucial in FIT-based colorectal cancer (CRC) screening. We investigated the occurrence of bleeding and perforation post FIT-colonoscopies (2013–2019) in Flanders and the contributing factors. A retrospective case–control study was conducted, including bleeding/perforation cases within 14 days after index colonoscopy, and controls without such events. Bleeding rates dropped from 0.9–1.1% (pre-2017) to 0.3% (2017–2018) and further to 0.05% (2019), while perforation rates remained at 0.05–0.11% (2014–2019). Male gender, polypectomy, general anaesthesia, and recent antiplatelet/antithrombotic drug use increased bleeding odds. Incomplete colonoscopy, polypectomy, general anaesthesia, and recent antiplatelet/antithrombotic drug use raised perforation odds. The endoscopists (n = 16) with highest bleeding rates (top 5%) performed only 6% of total FIT-colonoscopies, yet their patients experienced 45.5% of bleeding events. Similarly, for the top 5% of perforation rates, endoscopists conducting only 4.5% of total FIT-colonoscopy had 49.0% of perforation events occur in their patients. This study sheds light on FIT-colonoscopy-related complications in Flanders, their rates and risk factors. These findings can be incorporated into CRC screening materials and guide interventions to mitigate complications. A central colonoscopy register is currently lacking in Belgium, highlighting the need for its establishment to facilitate recurrent monitoring and evaluation.
Paradoxes versus Contradictions in Logic of Sentential Operators

Classical logic, of first or higher order, is extended with sentential operators and quantifiers, interpreted substitutionally over unrestricted substitution class. Operators mark a single layered, consistent metalanguage. Self-reference, arising from substitutional quantification over sentences, allows to express paradoxes which, unlike contradictions, do not lead to explosion. Semantics of the resulting language, using semi-kernels of digraphs, is non-explosive yet two-valued and has classical semantics as a special case for clasically consistent theories. A complete reasoning is obtained by extending LK with two rules for sentential quantifiers. Adding (cut) yields a complete system for the explosive semantics.
Augmented Security Framework using Internet of Things for Tracking Improvised Explosive Devices

Terrorism and the proliferation of explosives or improvised explosive devices (IEDs) have plagued many parts of the world. This is an issue of serious public and security concern across the world. One of the innovations like the Internet of Things (IoT), with the inherent ability to sense and propagate information about its environment with neighboring nodes in a network, has shown great promise in remotely providing monitoring and tracking information of suspected harmful substances. The integration of Artificial Intelligence (AI), Augmented Reality (AR), Robotics, etc. promises even more deliverables for the future in securing our world. This paper proposes a framework that leverages the IoT for continuous dynamic tracking of IEDs, overlayed with augmented geospatial details for guiding security agencies. The proposed framework would serve as a design and implementation guide.
Differential microRNA editing may drive target pathway switching in human temporal lobe epilepsy

Abstract MicroRNAs have emerged as important regulators of the gene expression landscape in temporal lobe epilepsy. The mechanisms that control microRNA levels and influence target choice remain, however, poorly understood. RNA editing is a post-transcriptional mechanism mediated by the adenosine acting on RNA (ADAR) family of proteins that introduces base modification that diversifies the gene expression landscape. RNA editing has been studied for the mRNA landscape but the extent to which microRNA editing occurs in human temporal lobe epilepsy is unknown. Here, we used small RNA-sequencing data to characterize the identity and extent of microRNA editing in human temporal lobe epilepsy brain samples. This detected low-to-high editing in over 40 of the identified microRNAs. Among microRNA exhibiting the highest editing was miR-376a-3p, which was edited in the seed region and this was predicted to significantly change the target pool. The edited form was expressed at lower levels in human temporal lobe epilepsy samples. We modelled the shift in editing levels of miR-376a-3p in human-induced pluripotent stem cell-derived neurons. Reducing levels of the edited form of miR-376a-3p using antisense oligonucleotides resulted in extensive gene expression changes, including upregulation of mitochondrial and metabolism-associated pathways. Together, these results show that differential editing of microRNAs may re-direct targeting and result in altered functions relevant to the pathophysiology of temporal lobe epilepsy and perhaps other disorders of neuronal hyperexcitability.
Development of Anthocyanin-Rich Gel Beads from Colored Rice for Encapsulation and In Vitro Gastrointestinal Digestion

Colored rice anthocyanins are water-soluble natural pigments that can be used as an active ingredient in healthy food and pharmaceutical products. However, anthocyanin utilization is limited because of its instability. This work produced anthocyanin-rich gel beads from colored rice using a modified ionotropic gelation technique for encapsulation, and their efficacy was studied in vitro in the gastrointestinal tract. In total, 15 colored rice samples of three types (whole grain rice, ground rice, and ground germinated rice) were screened to identify the highest anthocyanin content. The anthocyanin content of the whole grain rice was significantly (p < 0.05) higher than it was in the ground and ground germinated rice. The sample with the highest anthocyanin content (1062.7 µg/g) was the black glutinous rice grain from Phrae, chosen based on its anthocyanin-rich crude extract. A new formula using a modified ionotropic gelation technique was prepared for the inclusion of the extract in gel beads. The results indicated that the incorporation of oil and wax significantly increased the encapsulation efficiency of the gel beads (% EE value of 85.43%) and improved the bioavailability of the active ingredient. Moreover, after simulated digestion, the release of anthocyanin and total phenolic content occurred more than five times. Scanning electron microscopy revealed that the surface of the gel beads was smooth. Furthermore, the presence of polyphenols and polysaccharides in the gel beads was confirmed using FTIR. The oil-wax-incorporated, anthocyanin-rich gel beads could be implemented for antioxidant delivery into the gastrointestinal tract to further improve healthy food and nutraceutical products.
Material-Sparing Feasibility Screening for Hot Melt Extrusion

Hot melt extrusion (HME) offers a high-throughput process to manufacture amorphous solid dispersions. A variety of experimental and model-based approaches exist to predict API solubility in polymer melts, but these methods are typically aimed at determining the thermodynamic solubility and do not take into account kinetics of dissolution or the associated degradation of the API during thermal processing, both of which are critical considerations in generating a successful amorphous solid dispersion by HME. This work aims to develop a material-sparing approach for screening manufacturability of a given pharmaceutical API by HME using physically relevant time, temperature, and shear. Piroxicam, ritonavir, and phenytoin were used as model APIs with PVP VA64 as the dispersion polymer. We present a screening flowchart, aided by a simple custom device, that allows rapid formulation screening to predict both achievable API loadings and expected degradation from an HME process. This method has good correlation to processing with a micro compounder, a common HME screening industry standard, but only requires 200 mg of API or less.
Impacts of forest management practices on forest carbon

Forest management is an important activity that affects the global carbon stock, and therefore needs to be studied to further understand how its different practices can aid in greenhouse gas reduction efforts. Attaining sustainable harvesting potentials without sacrificing forests' ability to store carbon is very complicated. This report examines forest management practices and forest carbon in relation to possible climate change mitigation. Based on the review of scientific literature regarding forest systems' carbon sequestration, we discuss implications of the results of different forest management practices in the world and in Finland, and also touch upon the legislation as a regulatory measure. We conclude that carbon sequestration can be increased by management techniques such as prolonged rotations, increased thinning, continuous forest cover, supporting litter production and natural ecological conditions, keeping the right water level and cleaning the high emission ditches in peatlands. Preservation of large carbon stock of boreal forest soil is crucial, whereas in tropical forests, preventing deforestation is more relevant. In peatlands, forestrydraining can have a negative effect on the soil carbon pool in the long run in fertile sites. Carbon sequestration could be increased by storing carbon in wood products and using it as an alternative to fossil fuels. Forest management usually focuses on increasing the forest productivity and growing stock. However, forest management practices should be optimized for other factors too, such as the ecological quality of the forests and the soil carbon balance.
Enhancing Team Attendance Tracking in TBL Classes: A Comparative Study of LiDAR and Camera-Based Systems

Team-Based Learning (TBL), a pedagogical approach that positively influences classroom attendance, still needs help with student absenteeism. Current attendance tracking tools are designed for something other than TBL environments and require manual interaction from the instructor or students, consuming valuable class time. This paper introduces a novel approach to this problem, proposing an automated attendance tool for TBL classes using fixed sensors, either a camera or a Light Detection and Ranging (LiDAR), combined with a machine learning classification algorithm. The paper delves into a comparative study of using cameras and LiDAR for this purpose, evaluating them based on privacy, accuracy, efficiency, and perceptions of students and instructors. The results indicate that while both methods successfully record attendance, the LiDAR system was more efficient and reliable. Although the camera offered a higher accuracy rate, a better customized LiDAR dataset designed for the classroom environment could enhance the machine learning algorithm's accuracy in identifying students and recording attendance. Finally, the LiDAR system was favored by both students and instructors for its ease of use, non-intrusiveness, and privacy preservation.
Enhancing Industrial Control Network Security Through Vulnerability Detection and Attack Graph Analysis

Insufficient communication attack defense capabilities within industrial control networks is a serious problem that is addressed in this study. The author proposes a methodology that focuses on creating attack graphs to ease security and vulnerability studies in industrial control network systems in order to address this issue. The article provides thorough construction guidance and techniques for attack graphs, which are used for penetration testing and vulnerability analysis of networks for industrial control systems. On the created attack graph, experimental evaluations utilizing the ``earthquake net'' virus were carried out. The findings point to four main attack routes where the ``Zhenwang'' virus is most likely going to attack and cause the most damage. With a loss value of 12.2 and an attack success chance of 0.096, the first path involves cumulative attack stages. The second path consists of cumulative attack steps, with a loss value of 10.2 and an attack success probability of 0.072. The third path encompasses cumulative attack steps, with a loss value of 16.6 and an attack success probability of 0.063. The fourth path comprises cumulative attack steps, with a loss value of 18.6 and an attack success probability of 0.084.
Sedimentary environment evolution and biogenic silica records over 33,000 years in the Liaohe delta, China

The burial efficiency of biogenic silica (BSi) in deltaic sediments is associated both with the nutrient balance in estuarine ecosystems and with the carbon cycle and climate change. To explore these relationships, foraminifera data, physical and chemical parameters, and ages determined by accelerator mass spectrometry 14C and optically stimulated luminescence from a core drilled at the southwestern edge of the Lower Liaohe Plain in May 2012 were presented. The sedimentary environments since 33,000 cal yr BP were divided into four depositional units, namely, a fluvial deposit (U1), lacustrine deposit (U2), marine‐related deposit (U3), and upper delta plain deposit (U4). Environmentally mediated differences in apparent mass accumulation rates (AMARs) of BSi and organic carbon (Corg) were significant. The BSi‐AMAR in the later parts of U1 and U2 occurred mainly in the Pleistocene and averaged 11.34 ± 0.22 and 16.69 ± 0.91 g m−2 yr−1, which is lower than the analogues for U3 (23.59 ± 2.89–41.74 ± 6.37 g m−2 yr−1) and U4 (37.25 ± 9.96 g m−2 yr−1) that occurred during the Holocene. The BSi record responded more coherently and was more sensitive than Corg to Northern Hemisphere paleoclimatic variations on a long timescale and to abrupt/periodic winter monsoon winds or warming forcings on a short timescale. There was a negative correlation between the concentration of bioavailable Fe2O3 and the ratio of BSi/Corg, the implication being that Fe availability may have modulated silicic acid uptake on a very short timescale and in turn impacted the dynamics of carbon burial.
2-D Attention Based Convolutional Recurrent Neural Network for Speech Emotion Recognition

Recognizing speech emotions is a formidable challenge due to the complexity of emotions. The function of Speech Emotion Recognition(SER) is significantly impacted by the effects of emotional signals retrieved from speech. The majority of emotional traits, on the other hand, are sensitive to emotionally neutral elements like the speaker, speaking manner, and gender. In this work, we postulate that computing deltas for individual features maintain useful information which is mainly relevant to emotional traits while it minimizes the loss of emotionally irrelevant components, thus leading to fewer misclassifications. Additionally, Speech Emotion Recognition(SER) commonly experiences silent and emotionally unrelated frames. The proposed technique is quite good at picking up important feature representations for emotion relevant features. So here is a two dimensional convolutional recurrent neural network that is attention-based to learn distinguishing characteristics and predict the emotions. The Mel-spectrogram is used for feature extraction. The suggested technique is conducted on IEMOCAP dataset and it has better performance, with 68% accuracy value.
The Integration and Utilization of Artificial Intelligence (AI) in Supporting Older/Senior Lecturers to Adapt to the Changing Landscape in Translation Pedagogy

The incorporation of Artificial Intelligence (AI) in translation pedagogy has continued to change the intricacies of the field in such a way that translation educators are expected to frequently update themselves with current Artificial Intelligence (AI) translation tools. In the context of this dynamic pedagogical landscape, translation educators; especially, older/senior lecturers might find it difficult in adjusting to the changing requirements of instructional methods and educational processes. In the light of this identified challenge, the current research aims to explore the opinions of some selected translation lecturers to share their views on how AI can be utilized to support older/senior lecturers and aid them to adapt to the changing landscape of the domain of translation pedagogy. Using the Technology acceptability Model (TAM), this research strives to apply its fundamental principles and variables to understand the acceptability and adoption of artificial intelligence (AI)-driven tools among elderly educators within the framework of evolving translation pedagogy. In addition to this model, the research adopted a quantitative research methodology in gathering and analyzing the research data. An online survey item was used in collating the data. This online survey was conducted on seventy-nine (79) older/senior lecturers, who are also teaching translation courses in various universities. On the other hand, notable findings were made from the analysis conducted by the research. One among them is that these older lecturers find the utilization of AI tools in translation pedagogy is useful; as in these tools aid in effective teaching and learning of translation. Beyond the effectiveness of these tools, the research revealed that majority of older/senior lecturers affirmed that some of these tools are not easy to operate. Based on this finding, the research recommends training of translation educators on the use of these tools, and that the translation educators should adopt tools that are user friendly.
The Impact of Intestinal Microbiota and Toll-like Receptor 2 Signaling on α-Synuclein Pathology in Nontransgenic Mice Injected with α-Synuclein Preformed Fibrils

Intestinal microbiota and Toll-like receptor 2 (TLR2), which can bind lipoteichoic acid produced by microbiota, might contribute to the pathogenesis of Parkinson’s disease (PD), which is characterized by α-synuclein accumulation. Although the contribution of intestinal microbiota and TLR2 to PD pathology was validated in genetic PD models, evidence suggests that the effects of TLR2 signaling on proteinopathy might depend on the presence of a genetic etiology. We examined the impact of intestinal microbiota and TLR2 signaling on α-synuclein pathology in a nontransgenic mouse model of sporadic PD. While an α-synuclein preformed fibrils injection successfully reproduced PD pathology by inducing accumulation of α-synuclein aggregates, microglial activation and increased TLR2 expression in the brains of nontransgenic mice, antibiotic-induced reduction in the density of intestinal microbiota and TLR2 knockout had small impact on these changes. These findings, which are in contrast to those reported in transgenic mice harboring transgene encoding α-synuclein, indicate that the contribution of intestinal microbiota and TLR2 signaling to α-synuclein pathogenesis might be influenced by the presence of a genetic etiology. Additionally, these findings suggest that integrating insights from this experimental model and genetic models would further advance our understanding of the molecular mechanisms underlying sporadic PD.
The Sedimentary Rock Record of Mars: Distribution, Origins, and Global Stratigraphy

The last decade of Mars exploration produced a series of discoveries that provide compelling evidence for the existence of sedimentary rocks on Mars. Previously, Mars was regarded principally as a volcanic planet, the dominant surface processes of which were eruption of lavas and pyroclastic deposits, although early studies did recognize valley networks, enormous outflow channels, and the required transport of sedimentary materials to the northern plains of Mars. In contrast, our new view of Mars shows a rich history of interactions between water and the surface, with weathering, transport, and deposition of sediments by water as well as eolian processes. Surprisingly thick accumulations of stratified rocks extend back into the Noachian Era—the oldest of which were likely formed over 4 billion years ago, making these rocks much older than any sedimentary rocks preserved on Earth. Some sedimentary rocks were formed and deposited locally, whereas others accumulated as vast sheets that can be correlated for hundreds of kilometers or farther. Local deposits were formed in alluvial fan, deltaic, sublacustrine fan, and lacustrine environments in addition to deposits that fill canyons and valleys possibly carved during catastrophic floods. These former deposits indicate more gradual erosion and sedimentation, perhaps even involving meteoric precipitation, and they provide support for the notion of clement conditions on early Mars. In contrast, rapid erosion and sedimentation may have occurred within large, regional outflow channels thought to have resulted from outbursts of groundwater. Regionally extensive sedimentary deposits have less obvious origins, but the presence of hydrated sulfate minerals indicates that some of these deposits may have formed as lacustrine evaporites, particularly in the Valles Marineris network of open and closed basins. Others may have involved eolian reworking of previously deposited sulfates, or perhaps aqueous (groundwater) alteration of previously deposited basaltic sediments. Another major type of regionally extensive sedimentary deposit occurs as meter-scale stratification with highly rhythmic organization. These deposits occur in several places in the Arabia Terra region of Mars and are also observed at the top of a 5-km-thick stratigraphic section in Gale Crater. The significant lateral continuity of relatively thin beds, their distribution over broadly defined highs as well as lows, and the lack of strong spectral absorption features indicate that these rocks may be duststones, formed by weak lithification of fine particles that settled from the Martian atmosphere. The most ancient sedimentary deposits on Mars may be dominated by stacked, impact-generated debris sheets, similar to those seen on the Moon, and may include