Miracle-dz/UniFAR-FTUs huggingface dataset:
Sample-Based Gradient Edge and Angular Prediction for VVC Lossless Intra-Coding

Lossless coding is a compression method in the Versatile Video Coding (VVC) standard, which can compress video without distortion. Lossless coding has great application prospects in fields with high requirements for video quality. Since the current VVC standard is mainly designed for lossy coding, the compression efficiency of VVC lossless coding makes it hard to meet people’s needs. In order to improve the performance of VVC lossless coding, this paper proposes a sample-based intra-gradient edge detection and angular prediction (SGAP) method. SGAP utilizes the characteristics of lossless intra-coding to employ samples adjacent to the current sample as reference samples and performs prediction through sample iteration. SGAP aims to improve the prediction accuracy for edge regions, smooth regions and directional texture regions in images. Experimental results on the VVC Test Model (VTM) 12.3 reveal that SGAP achieves 7.31% bit-rate savings on average in VVC lossless intra-coding, while the encoding time is only increased by 5.4%. Compared with existing advanced sample-based intra-prediction methods, SGAP can provide significantly higher coding performance gain.
A Generative Design Approach to Improving the Environmental Performance of Educational Buildings in Hot Arid Climates. (Assiut National University as a Case Study)

The architectural design process is complex, involving diverse objectives that may be contradictory, and on which orientation exerts significant influence. The artificial intelligence application, Generative Design facilitates solving multi-objective design dilemmas through the creation and evaluation of numerous design alternatives. However, its exploration in educational buildings in hot arid climates remains limited. Given the impact of spaces’ function distribution, this study aims to optimize it in the typical plans of educational buildings. Employing a multi-objective design approach to enhance environmental performance. The study is conducted and evaluated in national universities in Egypt as a case study, specifically in Assiut City. The results revealed that the optimum design for a certain objective has not equated to optimal performance for other goals, highlighting an inherent contradiction between them. Among 26,334 possible alternatives for spaces’ function distribution, the difference between the optimal scenario and the least favourable one is significant for the parameters related to study spaces: natural daylighting, and visual comfort, ranging from 10% to 24%, besides around 1% difference for parameters related to the whole building, including energy consumption, thermal comfort, and carbon emission. This research offers a framework applicable to various building types. Additionally, it encourages decision-makers to adopt a no-cost sustainable design approach.
Coronary Microvascular Function Assessment using the Coronary Angiography-Derived Index of Microcirculatory Resistance in Patients with ST-segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention

Background : Studies reporting the status of coronary microvascular function in the infarct-related artery (IRA) after primary percutaneous coronary intervention (PCI) remain limited. This study utilized the coronary angiography-derived index of microcirculatory resistance (caIMR) to assess coronary microvascular function in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary PCI. Methods : We used the FlashAngio system to measure the caIMR after primary PCI in 157 patients with STEMI. The primary endpoint was the occurrence of a major adverse cardiovascular event (MACE), defined as a composite endpoint encompassing cardiac mortality, target vessel revascularization, and rehospitalization due to congestive heart failure (CHF), myocardial infarction (MI), or angina. Results : Approximately 30% of patients diagnosed with STEMI and who experienced successful primary PCI during the study period had a caIMR in the IRA of > 40. The caIMR in the IRA was significantly higher than in the reference vessel (32.9 ± 15.8 vs. 27.4 ± 11.1, p < 0.001). The caIMR in the reference vessel of the caIMR > 40 group was greater than in the caIMR ≤ 40 group (30.9 ± 11.3 vs. 25.9 ± 10.7, p = 0.009). Moreover, the caIMR > 40 group had higher incidence rates of MACEs at 3 months (25.5% vs. 8.3%, p = 0.009) and 1 year (29.8% vs. 13.9%, p = 0.04), than in the caIMR ≤ 40 group, which were mainly driven by a higher rate of rehospitalization due to CHF, MI, or angina. A caIMR in the IRA of > 40 was an independent predictor of a MACE at 3 months (hazard ratio (HR): 3.459, 95% confidence interval (CI): 1.363–8.779, p = 0.009) and 1 year (HR: 2.384, 95% CI: 1.100–5.166, p = 0.03) in patients with STEMI after primary PCI. Conclusions : Patients with STEMI after primary PCI often have coronary microvascular dysfunction, which is indicated by an increased caIMR in the IRA. An elevated caIMR of > 40 in the IRA was associated with an increased risk of adverse outcomes in STEMI patients undergoing primary PCI.
Analysis of the Performance of mc-Si and CdTe Modules Under Soiling Conditions

In this work, we study the soiling impact on the performance of two PV technologies installed in the south of Spain. For this purpose, we include electrical measurements as well as spectral aspects such as dust transmittance, quantum efficiency and the local solar spectrum to analyse their response. The studied technologies were multicrystalline silicon (mc-Si) and cadmium telluride (CdTe) PV modules. The solar spectra representative for clear sky, clean glass cover and soiled glass as well as the spectral response of the PV modules were used for the calculation of the photogenerated current density and spectral mismatch factor. Two cloudless days were chosen for analysis. In terms of the solar resource, these days did not exhibit large differences. Nevertheless, soiling was present to a different extent. When comparing the corresponding power output of the technologies on day 1 and day 2, the power losses at 12 UTC were 3 times larger for mc-Si and nearly the same for CdTe. This result shows that the soiling impacts differently on PV modules having different spectral responses.
Research on the pricing and replenishment decision-making problem of vegetable products based on neural networks and grey wolf algorithm

This article deals with the knapsack problem, where, under real-world conditions, the wholesale prices for the day are not known, and the sales of vegetable products exhibit seasonal patterns. Therefore, this article utilizes an LSTM neural network model to predict the daily wholesale prices. Subsequently, the top 60 projects with the highest profits are selected to create a histogram, and available projects are chosen from these 60.Initially, this article identifies five factors that impact profit and transforms them into positive indicators. Weight allocation is done using the entropy weight method and fuzzy comprehensive evaluation method. The TOPSIS method is employed to obtain composite score indicators for the 60 projects. A linear programming objective function is established, and the results are solved using the Grey Wolf Optimization (GWO) algorithm.
Surface Examination of Structure Loss in N-Type Czochralski Silicon Ingots

In principle, growing a dislocation-free Czochralski silicon ingot is possible if the growth process is kept stable and below the critical resolved shear stress value. However, in practice, a considerable proportion of the Si ingots are remelted due to the generation of dislocations or the so-called structure loss. The assessment of the failed ingots is a crucial step toward higher yield. However, the characterization of Si ingots is challenging due to their high brittleness and the high concentration of dislocations related to slip. In this work, we develop a non-destructive method to investigate the ingots that have experienced structure loss and reveal the root causes of this failure. Many characteristic features have been found on the surface of Czochralski silicon ingots. Based on these features, the ingots are classified into seven major groups that could be related to the main causes of the structure loss. Furthermore, the temperature gradient of several ingots is revealed by careful measurements of the growth ridges’ widths of these ingots. The results show that most of the failed ingots experience low-temperature gradients before the dislocation generation which agrees with the previous results. Three ingots have a clear particle hit on the surface, which caused an immediate transition to a multi-crystalline silicon structure. Particles are found on atomically smooth and rough interfaces, growth ridges, and surfaces in between. The surface examination method is a promising, fast, low-cost, and non-destructive technique that can be used to identify the most critical factors of structure loss in industrial ingots.
In Vitro Lactic Acid Bacteria Anti-Hepatitis B Virus (HBV) Effect and Modulation of the Intestinal Microbiota in Fecal Cultures from HBV-Associated Hepatocellular Carcinoma Patients

Hepatocellular carcinoma (HCC), being ranked as the top fifth most prevalent cancer globally, poses a significant health challenge, with a considerable mortality rate. Hepatitis B virus (HBV) infection stands as the primary factor contributing to HCC, presenting substantial challenges in its treatment. This study aimed to identify lactic acid bacteria (LAB) with anti-HBV properties and evaluate their impact on the intestinal flora in HBV-associated HCC. Initially, two LAB strains, Levilactobacillus brevis SR52-2 (L. brevis SR52-2) and LeviLactobacillus delbrueckii subsp. bulgaicus Q80 (L. delbrueckii Q80), exhibiting anti-HBV effects, were screened in vitro from a pool of 498 LAB strains through cell experiments, with extracellular expression levels of 0.58 ± 0.05 and 0.65 ± 0.03, respectively. These strains exhibited the capability of inhibiting the expression of HBeAg and HBsAg. Subsequent in vitro fermentation, conducted under simulated anaerobic conditions mimicking the colon environment, revealed a decrease in pH levels in both the health control (HC) and HCC groups influenced by LAB, with a more pronounced effect observed in the HC group. Additionally, the density of total short-chain fatty acids (SCFAs) significantly increased (p < 0.05) in the HCC group. Analysis of 16S rRNA highlighted differences in the gut microbiota (GM) community structure in cultures treated with L. brevis SR52-2 and L. delbrueckii Q80. Fecal microflora in normal samples exhibited greater diversity compared to HBV-HCC samples. The HCC group treated with LAB showed a significant increase in the abundance of the phyla Firmicutes, Bacteroidetes and Actinobacteria, while Proteobacteria significantly decreased compared to the untreated HCC group after 48 h. In conclusion, the findings indicate that LAB, specifically L. brevis SR52-2 and L. delbrueckii Q80, possessing antiviral properties, contribute to an improvement in gastrointestinal health.
Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.
A DEEP LEARNING MODEL IMPLEMENTATION OF TABNET FOR PREDICTING PEPTIDE-PROTEIN INTERACTION IN CANCER

Cancer has become one of the deadliest diseases in the world, mainly caused by the accumulation of somatic and inherited mutations. However, this phenomenon can be traced back to the molecular level, specifically, to proteins. Proteins are molecules responsible for various bioprocesses in the human body through their interactions with other molecules. Abnormalities in these interactions can lead to various undesirable outcomes, including disease and cancer. Peptides have the potential to serve as molecules that can be used in protein interactions to treat cancer. However, identification of peptides corresponding to target proteins in the laboratory is time-consuming and expensive. Therefore, there is a need for computational methods to aid identification. TabNet, a deep learning-based computational method was used in this study. For comparison purposes, we selected techniques from ensemble learning, including Random Forest and Extreme Gradient Boosting, along with methods from deep learning such as Convolutional Neural Network and Stacked Autoencoder-Deep Neural Network. Predictions are performed on a multi-feature peptide-protein interaction dataset, and the features include position-specific scoring matrices, intrinsic disorder, amino acid sequence, and physicochemical properties. Among our selected metrics, we found that TabNet achieved a better score in AUC of 0.7 and lower false negatives compared to other models.
Prevalence, multidrug resistance, and biofilm formation of Vibrio parahaemolyticus isolated from fish mariculture environments in Cat Ba Island, Vietnam.

BACKGROUND Vibrio parahaemolyticus is a major foodborne pathogen in aquatic animals and a threat to human health worldwide. This study investigated the prevalence, antimicrobial resistance, antimicrobial resistance genes (ARGs), and biofilm formation of V. parahaemolyticus strains isolated from fish mariculture environments in Cat Ba Island, Vietnam. METHODS In total, 150 rearing water samples were collected from 10 fish mariculture farms in winter and summer. A polymerase chain reaction assay was used to identify V. parahaemolyticus, its virulence factors, and ARGs. The antimicrobial resistance patterns and biofilm formation ability of V. parahaemolyticus strains were investigated using the disk diffusion test and a microtiter plate-based crystal violet method, respectively. RESULTS Thirty-seven V. parahaemolyticus isolates were recovered from 150 samples. The frequencies of the tdh and trh genes among V. parahaemolyticus isolates were 8.1% and 21.6%, respectively. More than 90% of isolates were susceptible to ceftazidime, cefotaxime, and chloramphenicol, but over 72% were resistant to ampicillin, tetracycline, and erythromycin. Furthermore, 67.57% of isolates exhibited multidrug resistance. The presence of ARGs related to gentamicin (aac(3)-IV), tetracycline (tetA) and ciprofloxacin (qnrA) in V. parahaemolyticus isolates was identified. Conversely, no ARGs related to ampicillin or erythromycin resistance were detected. Biofilm formation capacity was detected in significantly more multidrug-resistant isolates (64.9%) than non-multidrug-resistant isolates (18.9%). CONCLUSION Mariculture environments are a potential source of antibiotic-resistant V. parahaemolyticus and a hotspot for virulence genes and ARGs diffusing to aquatic environments. Thus, the prevention of antibiotic-resistant foodborne vibriosis in aquatic animals and humans requires continuous monitoring.
Evaluating Dendrolimus superans (Lepidoptera: Lasiocampidae) Occurrence and Density Modeling with Habitat Conditions

Dendrolimus superans, a prominent forest pest in northeast China, exerts detrimental effects on tree growth and development, disrupts the ecological functioning of forests, and even alters the trajectory of succession. The objective of this study was to investigate the influence of habitat conditions on the occurrence probability and density of overwintering D. superans, aiming to provide scientific insights for the effective prevention of and control measures against this pest infestation. The investigation encompassed 142 plots (20 m × 20 m) in various forest types within the primary distribution area of D. superans in the Great Xing’ an Mountains, focusing on factors such as topography, forest vegetation, and larval density. Binary logistic regression was employed to establish models for predicting the occurrence probability of D. superans, while generalized linear models (GLMs) and categorical regression (CATREG) were utilized to develop models for estimating its population size. Subsequently, an evaluation was conducted to assess the performance of these models. The occurrence probability model showed high accuracy (AUC = 0.826) in predicting infestation. The slope aspect and herb cover were the key factors affecting the occurrence of D. superans. The occurrence probability was the lowest on shady slopes and the highest on sunny slopes. The occurrence probability of D. superans increased with the increase in herb cover. The model of quantification showed that the density of D. superans was the least on shady slopes and the highest on sunny slopes. As the slope gradient increased, the density decreased. D. superans occurred most frequently on ridges. Similarly, with the increase in canopy cover or the decrease in diameter at breast height (DBH) and stand density, the density of D. superans increased. The influence of the topography factors surpassed that of the forest vegetation factors in shaping the population dynamics of D. superans, despite both being significant contributors. The study revealed that D. superans is prone to occur on sunny slopes, flat slopes, and ridges, which should be the focus of prevention and control in forest management practices, such as replanting, thinning, and regular weeding, to help restrain the growth of the population of this pest.
Revitalisation as a Method of Planning Sustainable Development of Old Town Complexes in Historic Towns

Old towns in spatial structures of historic towns are the areas which – same as centuries before – serve as the town centres. This is almost invariably true about small towns especially, as the inner town district is more frequently the site where a town was originally located and is often the manifestation of its historic identity. However, functional and spatial problems of many small historic towns arise from the above trend, mostly because of the frequently high density of buildings in the oldest part of a town. The intricate nature of elements creating the structure of a town’s historic centre often calls for certain steps to be taken, which will ensure better exposure of an old town complex against the backdrop of the town’s other areas. Numerous problems need to be solved, not only spatial but also economic and social ones. A town is a living organism, inhabited by people. The key to tackling these issues successfully lies in the creation of such revitalisation programmes that will improve the quality of space and help achieve the sustainable development of inner-town areas in historic towns. The historic centres in the medieval towns of Warmia, a region rich in history and situated in north-eastern Poland, can serve as an example and has been investigated in the following study. All the towns in Warmia located in the Middle Ages, except the capital of the region Olsztyn, can be classified as small urban developments. This group of eleven towns is dominated by the ones whose territorial coverage has not changed considerably since the location and the population ranges from a few thousand to less than twenty thousand. To this day, the historic quarters of these towns have remained the central ones in each town, and their urban structures to a various extent reveal the features characteristic for the period when they were created. The differences are due to the war damage the towns suffered at the end of World War Two and because of the different ways in which they were reconstructed afterwards. In consequence, some elements of the original town master plans have been lost. Revitalisation is an approach whose aim is to improve the quality of space and the ability of inner town areas to function. Revitalisation goes beyond the purely spatial factors, and involves broadly understood economic and social considerations. The conclusions drawn from this research pertain to benefits of using the revitalisation method in planning a sustainable development of urban structures. The development and implementation of revitalisation programmes is a very complex process that takes many years and requires an integrated and interdisciplinary team effort. This method allows us to preserve the identity of historic town areas while enabling them to play functions in the contemporary life of a town.
Scale Modular Test Platform for the Characterization of PD Measuring Systems Using HFCT Sensors

Today, online partial discharge (PD) measurements are common practice to assess the condition status of dielectrics in high-voltage (HV) electrical grids. However, when online PD measurements are carried out in electrical facilities, several disadvantages must be considered. Among the most important are high levels of changing electrical noise and interferences, signal phase couplings (cross-talk phenomena), and the simultaneous presence of various defects and difficulties in localizing and identifying them. In the last few decades, various PD-measuring systems have been developed to deal with these inconveniences and try to achieve the adequate supervision of electrical installations. In the state of the art, one of the main problems that electrical companies and technology developers face is the difficulty in characterizing the measuring system’s functionalities in laboratory setups or in real-world facilities, where simulated or real defects must be detected. This is mainly due to the complexity and costs that the laboratory setups entail and the fact that the facilities are permanently in service. Furthermore, in the latter scenario, owners cannot assign facilities to carry out the tests, which could cause irreversible damage. Additionally, with the aforementioned installations, a comparison of results over time in various locations is not possible, and noise conditions cannot be controlled to perform the characterizations in a correct way. To deal with the problems indicated, in this article, an affordable scale modular test platform that simulates an HV installation is presented, where real on-site PD measuring conditions are simulated and controlled. In this first development, the HV installation comprises a cable system connected at both ends to a gas-insulated substation (GIS). As the most common acquisition technique in online applications is based on the placement of high-frequency current transformer (HFCT) sensors in the grounding cables of facilities, the test platform is mainly adapted to carry out measurements with this type of sensor. The designed and developed test platform was validated to assess its features and the degree of convergence with a real installation, showing the convenience of its use for the appropriate and standardized characterization of PD-measuring systems.