Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of Facebook behaviors on the prediction of review helpfulness

Facebook reviews contain reviews and reviewers' information and include a set of likes, comments, sharing, and reactions called Facebook Behaviors (FBs). We extend existing research on review helpfulness to fit Facebook reviews by demonstrating that Facebook behaviors can impact review helpfulness. This study proposes a theoretical model that explains reviews' helpfulness based on FBs and baseline features. The model is empirically validated using a real Facebook data set and different feature selection methods (FS) to determine the importance level of such features to maximize the helpfulness prediction. Consequently, a combination of the impactful features is identified based on a robust and effective model. In this context, the like and love behaviors deliver the best predictive performance. Furthermore, we employ different classification techniques and a set of influencer features. The results showed the performance of the proposed model by 0.925 of accuracy.The outcomes of the current study can be applied to develop a smart review ranking system for Facebook product pages.
DIGITAL INEQUALITIES AMONG HUNGARIAN YOUTH

The study presents an empirical research carried out among Hungarian young internet users, focusing on digital inequalities. Since earlier researches with similar focus have shown important cognitive-cultural differences in use of the new technologies, the empirical research was amended with two integrating concepts - lifestyle and knowledge styles (cognitive styles). As a result of the erosion of traditional social stratification structures, the diversification of life patterns and of lifestyles, it is presumable that differences in youth's use of technology can be captured to a smaller degree through traditional models, and to a greater degree through models supplemented with lifestyle and cognitive style.
The long and sinuous road to phage-based therapy of Clostridioides difficile infections

With the antibiotic crisis and the rise in antimicrobial resistance worldwide, new therapeutic alternatives are urgently needed. Phage therapy represents one of the most promising alternatives but for some pathogens, such as Clostridioides difficile, important challenges are being faced. The perspective of phage therapy to treat C. difficile infections is complicated by the fact that no strictly lytic phages have been identified so far, and current temperate phages generally have a narrow host range. C. difficile also harbors multiple antiphage mechanisms, and the bacterial genome is often a host of one or multiple prophages that can interfere with lytic phage infection. Nevertheless, due to recent advances in phage host receptor recognition and improvements in genetic tools to manipulate phage genomes, it is now conceivable to genetically engineer C. difficile phages to make them suitable for phage therapy. Other phage-based alternatives such as phage endolysins and phage tail-like bacteriocins (avidocins) are also being investigated but these approaches also have their own limitations and challenges. Last but not least, C. difficile produces spores that are resistant to phage attacks and all current antibiotics, and this complicates therapeutic interventions. This mini-review gives a brief historical overview of phage work that has been carried out in C. difficile, presents recent advances in the field, and addresses the most important challenges that are being faced, with potential solutions.
On the (in)Security of the Control Plane of SDN Architecture: A Survey

Software-Defined Networking (SDN) has revolutionized the networking landscape by offering programmable control and optimization of network resources. However, SDN architecture’s inherent flexibility and centralized control expose it to new security risks. In this paper, we have presented a comprehensive study focused on the security implications associated with the control plane of SDN, which serves as a critical layer responsible for its network orchestration. We have addressed some pressing security concerns in SDN deployments by examining control plane vulnerabilities and explicit attacks. Through extensive analysis, we have investigated various control plane attacks. By meticulously exploring each attack vector, we have shed light on its mechanisms, potential impact and countermeasures. Furthermore, we have emphasized the interdependencies between the control plane, application plane, and data plane, highlighting how compromises in the control plane can propagate and impact the entire network infrastructure. Our research contributes to a deeper understanding of the specific vulnerabilities within SDN, focusing on the control plane as the primary target. By providing insights into the security landscape of SDN, network administrators, researchers, and security practitioners can develop proactive defense strategies and fortify the security posture of SDN deployments. We have underscored the importance of integrating robust security mechanisms to safeguard the control plane and maintain the overall security of SDN architectures. Our comprehensive analysis of control plane attacks in SDN elucidates the evolving security challenges posed by the programmability and centralization of network control. By addressing these vulnerabilities, we have tried to pave the way for future researchers to develop effective security solutions and ensure SDN networks’ resilience and integrity.
Strengthening the Role of Women (wives) of Fishermen Through Corporate Social Responsibility (CSR) Programs to Improve the Fishermen's Economy on the Coast of North Aceh, Indonesian

Purpose:This study confers growth the female role of fishermen during CSR programs to recover the frugality of fishermen on the Northern Aceh coast. During a CSR program based on strengthening the role of women, it is hoped that it can increase the economic revenue of fishing families along the Northern Aceh coast. Method:This research uses a sociological legal method, with news causes consisting of primary data and secondary data. This research is qualitative study using a sociological legal approach. Primary data collection is supervised by structured interview techniques, while secondary data collection is supervised by searching the literature in the form of regulations and protocols, journal books, and research results. Results and Conclusions: The findings of the research are that CSR programs were not administered by the firm as prescribed in the laws and prinmethodciplesre. One of the initiatives that companies can take to strengthen the role of coastal women is to conduct coaching or skill growth Exercising for fishermen's wives to manage the family economy. Research implications: Exercising or leadership can be given for dry fish making, brick and woven pallet making business. Exercising is supervised from the production stage to advertising. Originality/value: The Exercising is supervised with mentors to successful entrepreneurs who are qualified and have many rewards, including monitoring and evaluation for the growth of the firm's program.
Structural Phase Changes of Liquid Water in Alpine Snow

ice, water and air influences both the ele~ magnetic and hydraulic response, and this 0 a way to experimentally determine water ge etry in the different saturation regimes. Experimental results of a ten-year field study a given. Field measurements have been carried out in the Alpine regions of the Stubai Alps in Austria, whereby only old or fim-type snow h been used with mean grain sizes exceeding 1 mm in diameter and which is characterized by several melt freeze cycles.
Investigation and evaluation of a 3D‐printed optical modified cultivation vessel for improved scattered light measurement of biotechnologically relevant organisms

In the field of bioprocess development miniaturization, parallelization and flexibility play a key role reducing costs and time. To precisely meet these requirements, additive manufacturing (3D‐printing) is an ideal technology. 3D‐printing enables rapid prototyping and cost‐effective fabrication of individually designed devices with complex geometries on demand. For successful bioprocess development, monitoring of process‐relevant parameters, such as pH, dissolved oxygen (DO), and biomass, is crucial. Online monitoring is preferred as offline sampling is time‐consuming and leads to loss of information. In this study, 3D‐printed cultivation vessels with optical prisms are evaluated for the use in upstream processes of different industrially relevant microorganisms and cell lines. It was shown, that the 3D‐printed optically modified well (OMW) is of benefit for a wide range of biotechnologically relevant microorganisms and even for mammalian suspension cells. Evaluation tests with Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae, and Chinese hamster ovary (CHO) cells were performed, providing highly reproducible results. Growth behavior of OMW cultures was comparable to behavior of shake flask (SF) cultivations and the signal to noise ratio in online biomass measurement was shown to be reduced up to 95.8% by using the OMW. Especially the cultivation phases with low turbidity respective optical densities below 1.0 rel.AU could be monitored accurately for the first time. Furthermore, it was demonstrated that the 3D‐printed optics are transferable to different well geometries and sizes, enabling efficient biomass monitoring for individual requirements with tailor‐made 3D‐printed cultivation vessels in small scale.
Reppoints-Based Multiscale Task Enhancement Network and Sample Assignment Method for Oriented Object Detection

Unlike normal images, remote sensing images (RSIs) often contain complex backgrounds and multiscale targets with arbitrary directions. This makes the existing detection methods ineffective. In contrast to the usual rotating frame RSI target detection methods, the Reppoints-based method can learn autonomously to capture target features of arbitrary pose based on the target’s characteristics. Therefore, a new Reppoints-based detector is proposed in this letter to improve the accuracy from multiple perspectives. To better expand the receptive fields and obtain finer features, the multiscale task enhancement network (MSTEN) preserves the multiscale receptive fields and multiscale information through the deformable convolution (DCN) and the skip connection, while improving the feature extraction capability of the network for targets of arbitrary orientation. At the same time, the network adapts the features to the characteristics of different tasks to better suit the needs of the respective tasks. Finally, the dynamic reppoints learning (DRL) is proposed to select samples that perform well in both the regression and classification tasks. The experimental results on two challenging datasets, DOTA and HRSC2016, show the effectiveness of our proposed method.
Associations of High-Density Lipoprotein Functionality with Coronary Plaque Characteristics in Diabetic Patients with Coronary Artery Disease: Integrated Backscatter Intravascular Ultrasound Analysis

High-density lipoprotein (HDL) functionality has been reported to be associated with coronary artery disease (CAD). However, little is known about the impact of HDL functionality on coronary atherosclerosis. Thirty-eight type 2 diabetic patients with CAD who underwent percutaneous coronary intervention were examined. Coronary atheroma burden and plaque composition of the culprit lesions were assessed using conventional gray-scale and integrated backscatter intravascular ultrasound. HDL-mediated cholesterol efflux capacity (HDL-CEC) and HDL antioxidant capacity, estimated as HDL inflammatory index (HII), were examined. The associations between HDL functionality and coronary plaques were analyzed using multivariate data analysis, including principal components analysis and orthogonal partial least squares (OPLS) models. Percent atheroma volume was correlated with HDL-CEC (r = 0.34, p = 0.04) but not with HII (p = 0.65). The OPLS model demonstrated that the percentage lipid volume was significantly associated with HDL functionality [coefficient (95% confidence interval); HDL-CEC: −0.26 (−0.49, −0.04); HII: 0.34 (0.08, 2.60), respectively]. HII exhibited the highest variable importance in projection score, indicating the greatest contribution. HDL functionality was associated with coronary plaque composition, a key component of plaque vulnerability. Our findings highlight the potential importance of HDL functionality for coronary plaque stabilization.
New Advances in Detecting the Distal Geochemical Footprints of Porphyry Systems— Epidote Mineral Chemistry as a Tool for Vectoring and Fertility Assessments

Propylitic alteration halos to porphyry deposits are characterized by low- to moderate intensity replacements of primary feldspars and mafic minerals by epidote, chlorite, calcite ± actinolite, pyrite, prehnite and zeolites. The pyrite halo that surrounds porphyry deposits typically extends part way through the propylitic halo, and provides strong responses to conventional geochemical and geophysical exploration techniques. When exploring outside of the pyrite halo, porphyry deposits have proven to be difficult to detect based simply on the presence of weak epidote-chlorite alteration. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses of epidote from propylitic alteration zones around porphyry and skarn deposits in the central Baguio district, Philippines, have shown that low-level hypogene geochemical dispersion halos can be detected at considerably greater distances than can be achieved by conventional rock chip sampling of altered rocks. Epidote chemistry can provide vectoring information to the deposit center and potentially provides insights into the potential metal endowment of the porphyry system, providing explorers with both vectoring and fertility assessment tools. Epidote chemistry varies with respect to distance from porphyry deposit centers, with the highest concentrations of proximal pathfinder elements (e.g., Cu, Mo, Au, Sn) detected in epidote from close to the potassic alteration zone. Distal pathfinder elements (e.g., As, Sb, Pb, Zn, Mn) are most enriched in epidote more than 1.5 km from the deposit center. Rare earth elements and Zr are most enriched in epidote from the edge of the pyrite halo. The lateral zonation in epidote chemistry implies that at Baguio the geochemical dispersion patterns were produced by lateral outflow of spent fluids from the porphyry center, rather than from ingress of peripheral, non-magmatic waters.
The influence of product price and quality on customer loyalty with customer satisfaction as an intervening variable at PT. Brother Group, Medan

The increasing number of competitors forces companies to be more competitive in their actions and decision-making in marketing their products or services. Customer loyalty becomes the target of every company so that the company can survive and grow in the market. Product quality and product prices certainly have an influence on customer satisfaction and customer loyalty. The purpose of this research is to determine the influence of product prices and product quality on customer satisfaction and customer loyalty, and whether there is a correlation between customer satisfaction and customer loyalty. In conducting the research, the researcher used primary data obtained from questionnaires distributed to the customers of PT. Brother Group, Medan. The number of respondents used was 92. This primary data was processed using the statistical software SPSS 22. Tests conducted included validity tests, reliability tests, classic assumption tests such as normality tests, multicollinearity tests, and heteroscedasticity tests, followed by path analysis then hypothesis tests which include partial tests, determination tests, and also Sobel tests. In this study, price was coded as (x1), product quality as (x2), customer satisfaction as (Z), and customer loyalty as (Y). The results obtained in this study show that x1 has a significant effect on Y with a t-count value of 2.615 > t-table 1.661. x2 does not have a significant effect on Y with a t-count value of 0.788 < t-table 1.661. x1 has a significant effect on Z, with a t-count value of 5.243 > t-table 1.661, x2 has a significant effect on Z with a t-count value of 3.314 > t-table 1.661, Z has a significant effect on Y with a t-count value of 6.222 > t-table which is 1.661, x1 has an effect on Y with Z as an intervening variable with a t-count value of 3.941633 > t-table value of 1.661, x2 has an effect on Y with Z as an intervening variable with a t-count value of 2.930647902 > t-table value of 1.661.
Extradural lumbar arteriovenous fistula imitating a synovial cyst: illustrative case

BACKGROUND Spinal dural arteriovenous fistula is the most common spinal vascular malformation. It usually presents with neurological deficits due to venous congestive myelopathy. Sometimes, however, the symptoms are radicular and can imitate those of a disc hernia or synovial cyst. OBSERVATIONS In this illustrated case, a 34-year-old male patient presented with radicular pain due to nerve root compression. In the magnetic resonance imaging (MRI) examination of the spine, a synovial cyst was suspected, so the patient underwent no further examination before surgery. Intraoperatively, the authors were surprised to see a vascular malformation, which was shown to be an extradural arteriovenous fistula according to the histopathological examination. LESSONS In atypical MRI findings of the spine, vascular malformations should be considered. In cases with a spinal dural arteriovenous fistula, the thrombosis risk can be high and lead to a need for prolonged anticoagulation.
Does the Dizziness Handicap Inventory—Children and Adolescents (DHI-CA) Demonstrate Properties to Support Clinical Application in the Post-Concussion Population: A Rasch Analysis

The purpose of this cross-sectional validation study was to evaluate the clinical utility of the DHI-CA by (1) examining its dimensionality using exploratory factor analysis (EFA) and (2) calibrating DHI-CA items (using the multidimensional Rasch model) to obtain item difficulty levels. A retrospective chart review was conducted for 132 patients between the ages of 8 and 18 years (mean age = 15.3 ± 2.1 years) from a multidisciplinary post-concussion management tertiary center. Data were extracted on age, sex, and DHI-CA. EFA revealed that 12 out of 25 items did not fit in the subscale that they were originally described under, indicating poor dimensionality. Calibration of items on the Wright Maps revealed that 50% of the items pooled in the lower difficulty level, indicating a potential ceiling effect. Corrected item–rest correlations for the physical, emotional, walking/mobility, and community participation ranged from 0.44–0.66, 0.27–0.61, 0.54–0.57, and 0.32–0.69 (p < 0.001), respectively. The clinical utility of the DHI-CA was found to be questionable due to the presence of double-barreled items and the ceiling effect. Clinicians must supplement data from the DHI-CA with other measures and patient interviews to make informed clinical decisions specific to the post-concussion population until new, robust, and valid measures are developed.
A Magnetic Field Sensor Based on Directional Coupling in a Magnetic Fluid-Filled Photonic Crystal Fiber

In this paper, a dual-core photonic crystal fiber (DC-PCF) sensitivity sensor filled with magnetic liquid is introduced and investigated with the finite element method (FEM). To regulate the energy coupling involving the two cores, the magnetic fluid is filled into the pore between the two cores. To adjust the coupling between the supermodes in the DC-PCF, the refractive index (RI) of the air hole filled magnetic fluid may change due to the external magnetic field. This specifically created a magnetic fluid-filled DC-PCF; the magnetic fluid-filled hole is not used as the core for energy transmission, thus avoiding transmission loss. The dip wavelength and the magnetic field displayed an excellent linear connection between 80 and 260 Oe, depending on the numerical data. The detection sensitivity of the magnetic field reached 515.75 pm/Oe at a short fiber length of 482 µm. The designed magnetic fluid-filled DC-PCF has high sensitivity and small volume and has great application prospects in magnetic field detection in the medical and industrial fields.
Warming experiment indicates that increasing global temperatures may not affect windows of opportunity for salt marsh seedlings

With increasing global temperatures, it remains unclear, how seedling emergence and survival will be affected in highly dynamic ecosystems like salt marshes. Our study combines passive and active warming treatments with the natural inundation dynamics of salt marshes. We studied the effects of active soil and passive air warming (ambient temperature, + 1.5°C and + 3.0°C) on seedling numbers of different species in three salt marsh zones (pioneer zone, low marsh, and high marsh) and on seedling survival (lifespan), seedling diversity and species richness in two salt marsh zones (low marsh and high marsh) in situ. We found a significant influence of warming on Shannon diversity at two dates, but we found no significant effects of warming on seedling number and survival. However, we found trends, which differed between zones. In the pioneer zone, seedling numbers were slightly higher in the warming treatments than in the ambient treatment from April to June. Whereas, in the high marsh, seedling numbers decreased more in the warming treatments during the same period. The median lifespan was slightly reduced under warming treatments. We conclude warming might have increased drought stress for seedlings in the high marsh, which led to the trend of lower seedling numbers and shorter survival times. Seedling number decreased with elevation, which could be attributed to both species‐specific strategies and differences in available space. Median survival differed significantly between species, which we assume is due to differing life‐history traits like seed size and if the species are annual or perennial.
A Novel Vectorized Curved Road Representation Based Aerial Guided Unmanned Vehicle Trajectory Planning

Unmanned vehicles frequently encounter the challenge of navigating through complex mountainous terrains, which are characterized by numerous unknown continuous curves. Drones, with their wide field of view and ability to vertically displace, offer a potential solution to compensate for the limited field of view of ground vehicles. However, the conventional approach of path extraction solely provides pixel-level positional information. Consequently, when drones guide ground unmanned vehicles using visual cues, the road fitting accuracy is compromised, resulting in reduced speed. Addressing these limitations with existing methods has proven to be a formidable task. In this study, we propose an innovative approach for guiding the visual movement of unmanned ground vehicles using an air–ground collaborative vectorized curved road representation and trajectory planning method. Our method offers several advantages over traditional road fitting techniques. Firstly, it incorporates a road star points ordering method based on the K-Means clustering algorithm, which simplifies the complex process of road fitting. Additionally, we introduce a road vectorization model based on the piecewise GA-Bézier algorithm, enabling the identification of the optimal frame from the initial frame to the current frame in the video stream. This significantly improves the road fitting effect (EV) and reduces the model running time (T—model). Furthermore, we employ smooth trajectory planning along the “route-plane” to maximize speed at turning points, thereby minimizing travel time (T—travel). To validate the efficiency and accuracy of our proposed method, we conducted extensive simulation experiments and performed actual comparison experiments. The results demonstrate the superior performance of our approach in terms of both efficiency and accuracy.