Miracle-dz/UniFAR-FTUs huggingface dataset:
Epigallocatechin Gallate Potentiates the Anticancer Effect of AFP-siRNA-Loaded Polymeric Nanoparticles on Hepatocellular Carcinoma Cells

To develop a potential cancer treatment, we formulated a novel drug delivery platform made of poly(lactic-co-glycolic) acid (PLGA) and used a combination of an emerging siRNA technology and an extracted natural substance called catechins. The synthesized materials were characterized to determine their properties, including morphology, hydrodynamic size, charge, particle stability, and drug release profile. The therapeutic effect of AFP-siRNA and epigallocatechin gallate (EGCG) was revealed to have remarkable cytotoxicity towards HepG2 when in soluble formulation. Notably, the killing effect was enhanced by the co-treatment of AFP-siRNA-loaded PLGA and EGCG. Cell viability significantly dropped to 59.73 ± 6.95% after treatment with 12.50 μg/mL of EGCG and AFP-siRNA-PLGA. Meanwhile, 80% of viable cells were observed after treatment with monotherapy. The reduction in the survival of cells is a clear indication of the complementary action of both active EGCG and AFP-siRNA-loaded PLGA. The corresponding cell death was involved in apoptosis, as evidenced by the increased caspase-3/7 activity. The combined treatment exhibited a 2.5-fold increase in caspase-3/7 activity. Moreover, the nanoparticles were internalized by HepG2 in a time-dependent manner, indicating the appropriate use of PLGA as a carrier. Accordingly, a combined system is an effective therapeutic strategy.
Cytokines, Serological, and Histopathological Assessment of Recombinant Vaccination Strategies for Combatting Infectious Bursal Disease in Broiler Chickens

Infectious bursal disease (IBD) represents a greatly transmissible viral disease found worldwide, causing significant health and production challenges in young chickens. The aim of this research was to assess the immune reaction induced by different vaccines targeting IBD. These vaccines included recombinant (Vac1; HVT-IBD vector), immune complex (Vac2; Bursa-Plex®), and intermediate plus (Vac3; Bursine plus) IBD vaccines. Our assessment relied on serological and histopathological analyses, as well as the pattern of immune-related cytokine expression in the bursal tissue. The vaccinated groups, along with a control positive (CP) group, were subjected to a vvIBDV challenge on their 28th day of life, while the control negative (CN) group received a mock vaccination with PBS. Our study revealed that Vac1 resulted in the most favorable growth performance, as well as maintained normal liver and kidney function, mitigating the impact of IBDV infection. Serological analysis using VP2 ELISA kits indicated that Vac1 induced the strongest immunological response among all vaccines. Histopathological examination demonstrated that Vac1 caused minimal lymphoid depletion observed in the lymphoid organs, followed by Vac2. Analysis of cytokine expression profiles showed significant upregulation in all vaccinated groups, particularly Vac1, during the pre-challenge period. Following IBDV infection, Vac1 resulted in a noteworthy increase in the expression of IL2 and IFN-γ, Vac2 showed a significant upregulation in TNF-α and granzyme, and both Vac1 and Vac3 exhibited increased levels of IL1β and IL10. In conclusion, our study suggests that the various vaccines triggered immune responses against IBD through both humoral and cell-mediated immunity. However, recombinant followed by immune complex vaccines appeared to induce more robust immunity while also being safer for broiler chickens in contrast to the intermediate plus vaccine.
The Role of Actors in Blockchain Adoption Decisions - An Innovation Translation Perspective

An overview of challenges around blockchain adoption has revealed that there is little understanding of the process of blockchain adoption decisions, including who needs to be involved and consulted at various stages. When systems are designed to intentionally protect privacy or to obscure actors, such as blockchain platforms, it can be challenging to identify them and to understand their roles. To do this we used an Innovation Translation approach from Actor-Network Theory (Latour, 2007) which looks at the roles of both human and non-human actors. To understand the interactions among the actors involved, multiple rounds of interviews were conducted with Blockchain experts, utilising the qualitative Delphi method. The findings of this study propose a framework that provides insight into the decision-process by exploring the actors involved and their roles as they implement strategies to adopt blockchain and to convince other actors. The outcomes will assist blockchain practitioners and researchers to have an understanding of pre-adoption decisions and stakeholder involvement. Organisations considering implementing blockchain will benefit from this research as they will know where to start, who to engage, and which stakeholders are needed during the decision-making process.
SPH–FEM Analysis of Effect of Flow Impingement of Ultrasonic Honing Cavitation Microjet on Titanium–Tantalum Alloy Surface

To investigate the machining effect of ultrasonic honing microjets on a titanium–tantalum alloy surface, a cavitation microjet flow impingement model was established using the smoothed particle hydrodynamics–finite element method (SPH–FEM) coupling method including the effects of wall elastic–plastic deformation, the ultrasonic field and the honing pressure field. Simulation analysis was conducted on a single impact with different initial speeds and a continuous impact at a constant initial speed. The results showed that the initial speed of the microjet needed to reach at least 580 to 610 m/s in order to obtain an obvious effect of the single impact. The single impact had almost no effect at low speeds. However, when the microjet continuously impacted the same position, obvious pits were produced via a cumulative effect. These pits were similar to that obtained by the single impact, and they had the maximum depth at the edge rather than the center. With the increase in the microjet’s initial speed, the total number of shocks required to reach the same depth gradually decreases. When the number of impacts is large, with the increase in the number of impacts, the growth rate of the maximum pit depth gradually slows down, and even shows no growth or negative growth at some times. Using the continuous impacts of the microjet by prolonging the processing time can enhance titanium–tantalum alloy machining with ultrasonic honing for material removal.
Growing centralization in China’s farmland protection policy in response to policy failure and related upward-extending unwillingness to protect farmland since 1978

Since 1978, China has experienced a rapid loss of arable land, leading to centralizing of farmland protection policies. To understand the growing centralization, this paper has used the lens of the interactions among (1) unwillingness to protect farmland among diverse actors, (2) policy failure and (3) policy change. The growing centralization is an adaptive response to the unwillingness to protect farmland from local up to provincial government levels, and its associated policy failure. The article suggests that gradual centralization over the last almost 40 years has gone through three phases: centralization to county-level, centralization to provincial-level, and intensifying technical supervision from central government. In the first phase, the unwillingness to preserve farmland appeared at the levels of the rural household, village and township; in the second phase, county- and prefecture-level governments began to lose willingness to preserve farmland; and, in the third phase, provincial governments’ willingness to preserve farmland weakened. The current centralized system has succeeded, for the most part, in addressing the problem of asymmetric information about farmland preservation between central and local governments, but the basic planning problem regarding loss of farmland remains a challenge.
Compendium of Clinical Variant Classification for 2,246 Unique ABCA4 Variants to Clarify Variant Pathogenicity in Stargardt Disease Using a Modified ACMG/AMP Framework

Biallelic variants in ABCA4 cause Stargardt disease (STGD1), the most frequent heritable macular disease. Determination of the pathogenicity of variants in ABCA4 proves to be difficult due to (1) the high number of benign and pathogenic variants in the gene; (2) the presence of many rare ABCA4 variants; (3) the presence of complex alleles for which phasing data are absent; (4) the extensive variable expressivity of this disease and (5) reduced penetrance of hypomorphic variants. Therefore, the classification of many variants in ABCA4 is currently of uncertain significance. Here, we complemented the ABCA4 Leiden Open Variation Database (LOVD) with data from ~11,000 probands with ABCA4-associated inherited retinal diseases from literature up to the end of 2020. We carefully adapted the ACMG/AMP classifications to ABCA4 incorporating ClinGen recommendations and assigned these classifications to all 2,246 unique variants from the ABCA4 LOVD to increase the knowledge of pathogenicity. In total, 1,248 variants were categorized with a likely pathogenic or pathogenic classification, whereas 194 variants were categorized with a likely benign or benign classification. This uniform and improved structured reclassification, incorporating the largest dataset of ABCA4-associated retinopathy cases so far, will improve both the diagnosis as well as genetic counselling for individuals with ABCA4-associated retinopathy.
Salmonella enterica Serovar Gallinarum Biovars Pullorum and Gallinarum in Poultry: Review of Pathogenesis, Antibiotic Resistance, Diagnosis and Control in the Genomic Era

Salmonella enterica subsp. enterica serovar Gallinarum (SG) has two distinct biovars, Pullorum and Gallinarum. They are bacterial pathogens that exhibit host specificity for poultry and aquatic birds, causing severe systemic diseases known as fowl typhoid (FT) and Pullorum disease (PD), respectively. The virulence mechanisms of biovars Gallinarum and Pullorum are multifactorial, involving a variety of genes and pathways that contribute to their pathogenicity. In addition, these serovars have developed resistance to various antimicrobial agents, leading to the emergence of multidrug-resistant strains. Due to their economic and public health significance, rapid and accurate diagnosis is crucial for effective control and prevention of these diseases. Conventional methods, such as bacterial culture and serological tests, have been used for screening and diagnosis. However, molecular-based methods are becoming increasingly important due to their rapidity, high sensitivity, and specificity, opening new horizons for the development of innovative approaches to control FT and PD. The aim of this review is to highlight the current state of knowledge on biovars Gallinarum and Pullorum, emphasizing the importance of continued research into their pathogenesis, drug resistance and diagnosis to better understand and control these pathogens in poultry farms.
A recommender system-using novel deep network collaborative filtering

The recommendation model aims to predict the user’s preferred items among million through analyzing the user-item relations; furthermore, Collaborative Filtering has been utilized as one of the successful recommendation approaches in last few years; however, it has the issue of sparsity. This research work develops a deep network collaborative filtering (DeepNCF), which incorporates graph neural network (GNN), and novel network collaborative filtering (NCF) for performance enhancement. At first user-item dual network is constructed, thereafter-custom weighted dual mode modularity is developed for edge clustering. Furthermore, GNN is utilized for capturing the complex relation between user and item. DeepNCF is evaluated considering the two distinctive. The experimental analysis is carried out on two datasets for Amazon and movielens dataset for recall@20 and recall@50 and the normalized discounted cumulative gain (NDCG) metric is evaluated for Amazon Dataset for NDCG@20 and NDCG@50. The proposed method outperforms the most relevant research and is accurate enough to give personalized recommendations and diversity.
A Scalable Random Forest-Based Scheme to Detect and Locate Partial Shading in Photovoltaic Systems

Photovoltaic (PV) systems are prone to partial shading (PS) due to the environmental factors that they function in such as vegetation, nearby structures, and clouds. All types of PS scenarios can lead to power loss and hot spots in the PV system due to module mismatch and heating of shaded cells. To mitigate the power loss that occurs due to PS, it is imperative to detect PS and its characteristics, such as the number of shaded modules and the associated shading factor (SF), in a reliable manner. This paper proposes a three-step framework to detect and locate PS, the number of shaded modules, and the SF in the PV system using a random forest (RF)-based approach. The proposed approach utilizes independent string current and voltage measurements to distinguish different PS scenarios. This approach allows for a scalable data acquisition through an uncoupled modeling scheme. PS, the number of shaded modules and the SF are deduced with accuracies of 99.5%, 92.3%, 90.2%, respectively. Further, the proposed approach is validated through two testing tiers, and its ability to detect multiple PS scenarios in a PV system has been highlighted. The results observed through different PS scenarios confirm the high reliability and demonstrate the effectiveness and scalability of the proposed RF-based approach.
Predictive maintenance framework for assessing health state of centrifugal pumps

Combined with advances in sensing technologies and big data analytics, critical information can be extracted from continuous production processes for predicting the health state of equipment and safeguarding upcoming failures. This research presents a methodology for applying predictive maintenance (PdM) solutions and showcases a PdM application for health state prediction and condition monitoring, increasing the safety and productivity of centrifugal pumps for a sustainable and resilient PdM ecosystem. Measurements depicting the healthy and maintenance-prone stages of two centrifugal pumps were collected on the university campus. The dataset consists of 5,118 records and includes both running and standstill values. Additionally, Spearman statistical analysis was conducted to measure the correlation of collected measurements with the predicted output of machine conditions and select the most appropriate features for model optimization. Several machine learning (ML) algorithms, namely random forest (RF), Naïve Bayes, support vector machines (SVM), and extreme gradient boosting (XGBoost) were analyzed and evaluated during the data mining process. The results indicated the effectiveness and efficiency of XGBoost for the health state prediction of centrifugal pumps. The contribution of this research is to propose an effective framework collectong multistage health data for PdM applications and showcase its effectiveness in a real-world use case.
SEDIMENTARY CHARACTERISTICS, MACROINFAUNA AND TYPES AND ABUNDANCES OF BIVALVES IN A TIDAL FLAT OF THE NORD-PATAGONIC ARCHIPELAGO, CHILE

The physico-chemical characteristics of the sediment, the nutritional value and the biochemical composition of the sedimentary organic matter and the structure of macroinfaunal assemblages were studied in three sites of the low intertidal of Pelluco, a tidal flat located on the inland coast of the Nord-Patagonic archipelago, southern Chile. The Site 1 was dominated by the razor clam Tagelus dombeii; Site 2 was dominated by the razor clam Tagelus dombeii and the bivalves Diplodonta inconspicua and Semele solida; while Site 3 had no bivalves at all. The site without bivalves showed a stronger decrease in depth of the redox potential than the sites with bivalves. This result was probably related to the process of bivalve reworking which redistributes reduced compounds from deeper layers to the sediment surface. Sedimentological differences and differences in the macroinfauna structure among sites were noticed. Thus the sediment characteristics of deeper strata were more different at the site without bivalves as compared to deeper strata of sites 1 and 2. The total number and the total abundance of the macroinfauna were higher at site 1 and 2. The results of BIO-ENV routine showed that the highest fit between the macroinfauna structure and sedimentological variables, was reached with two and four variables (total carbon and redox, p w = 0.391 and carbohydrates, total nitrogen, total carbon and redox, p w = 0.385, respectively), suggesting that that pattern was closely related to the presence of bivalves which would promote macroinfaunal assemblages throughout biogenic reworking of sediments.
Compressed Spectrum Reconstruction Method Based on Coding Feature Vector Enhancement

Compressive spectral imaging (CSI) is a snapshot spectral imaging technique that rapidly captures the spectral information of a target in a single exposure and effectively reconstructs high spectral data using reconstruction algorithms. However, due to the presence of a large number of identical pixels in the measured image, which map to different prior spectral information, existing algorithms struggle to establish an accurate pixel separation representation model. To improve the separation effect between pixels and enhance the representation capability of the measured image pixels, we propose a compressed spectral reconstruction method with enhanced encoding feature vectors. By designing encoding information calculation rules based on a combination of linear and nonlinear functions, encoding features are calculated according to the spatial coordinate position information and wavelength information of the pixels, effectively enhancing the separation representation characteristics between channels and neighboring pixels through the addition of encoding features. Furthermore, by utilizing the semantic similarity between the predicted results of the prior model and the prior spectral image, the reconstruction problem is transformed into a total variation (TV) minimization problem between the predicted results of the prior model and the reconstruction results, combined with the alternating direction method of multipliers (ADMMs) to achieve accurate pixel reconstruction. The experimental setup utilizes a dual-camera compressed spectral imaging (DCCHI) system, consisting of a dual-dispersion coded aperture compressed spectral imaging (DD-CASSI) system and a grayscale imaging system. Various experiments have shown that the proposed method outperforms in reconstructing quality and displays superior algorithmic performance.
From Communal to Individual: Shifting Authorities of Family Dispute Resolution in Minangkabau Society

This study aims to explain the shift of authority in resolving family disputes in Minangkabau society. At least three authorities are involved in resolving family issues in Minangkabau: religious authority, represented by leaders with religious knowledge; customary authority, held by leaders with their own laws; and state authority, enforced by judges in court based on laws and regulations. This research is a field study with a socio-legal approach. The study examined Minangkabau households in both rural and urban areas, utilizing questionnaires and in-depth interviews to collect data from individuals involved in household disputes. The data were then reduced, presented and verified. This study found that in addition to using the three long-standing authorities in Minangkabau society, disputants are more likely to use individual authority in resolving their family disputes. The disputants are more likely to resolve their family problems independently without involving religious leaders, customary leaders, or religious court judges. The tendency towards individual authority is more prevalent in urban communities. The strengthening of individual authority coincides with the weakening of the formal institutions of the three authorities in Minangkabau society. The factors contributing to the diminishment of these authorities include modernisation, technological advancements, and digitalisation which incentivises the involved parties to logically settle their disputes for their individual gains and aspirations. Based on the research findings, the current study confirms that the shift in family dispute resolution authority indicates that there has been a shift from extended to core family patterns in Minangkabau society
Face and liveness detection with criminal identification using machine learning and image processing techniques for security system

In the past, real-world photos have been used to train classifiers for face liveness identification since the related face presentation attacks (PA) and real-world images have a high degree of overlap. The use of deep convolutional neural networks (CNN) and real-world face photos together to identify the liveness of a face, however, has received very little study. A face recognition system should be able to identify real faces as well as efforts at faking utilizing printed or digital presentations. A true spoofing avoidance method involves observing facial liveness, such as eye blinking and lip movement. However, this strategy is rendered useless when defending against replay assaults that use video. The anti-spoofing technique consists of two modules: the ConvNet classifier module and the blinking eye module, which measure lip and eye movement. The results of the testing demonstrate that the developed module is capable of identifying various face spoof assaults, including those made with the use of posters, masks, or smartphones. To assess the convolutional features in this study adaptively fused from deep CNN produced face pictures and convolutional layers learned from real-world identification. Extensive tests using intra-database and cross-database scenarios on cutting-edge face anti-spoofing databases including CASIA, OULU, NUAA and replay-attack dataset demonstrate that the proposed solution methods for face liveness detection. The algorithm has a 94.30% accuracy rate.
Travel Blogs as a Reflection of Thai Perspectives on Myanmar

ABSTRACT This paper aims to analyze perspectives on Myanmar in the discourse of travel blogs. The researchers consider linguistic strategies used by the bloggers under the framework proposed by van Dijk (2006, 2009). The data were drawn from travel blogs in the blue planet section of Pantip.com posted during January 2014 December 2015. Four linguistic strategies were found: lexicon, expressions, rhetorical figures, and indirect speech. The linguistic strategies used in travel blogs on Myanmar reveal both positive and negative points of view from the bloggers. Those points of view deal with issues of way of life, occupation, geography, religion, food, accommodations and buildings, transportation, fashion, security, technology, and sanitation. Since ancient times, Myanmar has been portrayed as an enemy of Thailand by the media (textbooks, films, and TV plays). However, this study reveals that Thai travelers to Myanmar have opened their minds and changed their points of view towards their neighbor. Myanmar is no longer our enemy but a beautiful country with deep roots of Buddhism and many beautiful tourist attractions.