Miracle-dz/UniFAR-FTUs huggingface dataset:
Teachers’ Understanding and Mastery of the Syntax of Advanced Reading for Elementary School Students during the Covid-19 Pandemic

This research aims to analyze the understanding and mastery of elementary school (SD) teachers in Central Java in applying the syntax of advanced reading learning models during the covid-19 pandemic. Focus group discussion (FGD) was conducted by involving 30 elementary school teachers using the open inquiry method. The discussion discussed several topics related to the teacher's perspective on the application of the advanced reading learning model that was applied during the pandemic, and the advantages and disadvantages of the learning model that became the basis for analyzing the extent to which teachers understand and master the learning models they have implemented in schools so far. Interactive analysis was used to collect, reduce, present, and draw conclusions from the data obtained. The results of this study indicate that during the covid-19 pandemic, teachers implemented advanced reading learning models both online and blended learning. Blended learning is more widely applied because if it is only online learning, there are many technical obstacles and students still need face-to-face teacher assistance. Most teachers stated that they needed a learning model that could be flexibly applied to online, offline, and mixed learning to maximize advanced reading skills. Teachers also need innovative and varied learning models to learn during the pandemic, which is uncertain when it will end.
Investigation of Brain Function-Related Myokine Secretion by Using Contractile 3D-Engineered Muscle

Brain function-related myokines, such as lactate, irisin, and cathepsin B (CTSB), are upstream factors that control brain-derived neurotrophic factor (BDNF) expression and are secreted from skeletal muscle by exercise. However, whether irisin and CTSB are secreted by muscle contraction remains controversial. Three-dimensional (3D)-engineered muscle (3D-EM) may help determine whether skeletal muscle contraction leads to the secretion of irisin and CTSB, which has never been identified with the addition of drugs in conventional 2D muscle cell cultures. We aimed to investigate the effects of electrical pulse stimulation (EPS)-evoked muscle contraction on irisin and CTSB secretion in 3D-EM. The 3D-EM, which consisted of C2C12 myoblasts and type-1 collagen gel, was allowed to differentiate for 2 weeks and divided into the control and EPS groups. EPS was applied at 13 V, 66 Hz, and 2 msec for 3 h (on: 5 s/off: 5 s). Irisin and CTSB secretion into the culture medium was measured by Western blotting. Irisin secretion was significantly increased following EPS (p < 0.05). However, there was no significant difference in CTSB secretion between the two groups. The present study suggests that irisin may be a contractile muscle-derived myokine, but CTSB is not secreted by EPS-evoked muscle contractile stimulation in 3D-EM.
Clinical Features of Lid Margin, Meibomian Gland and Tear Film Changes in Patients with Primary Pterygium

Introduction: The aim of this study was to clinically evaluate lid margin abnormality, meibomian glands expression and tear function changes in patients with primary pterygium. Methods: Fifty normal and 50 primary pterygia participants without other ocular pathologies were randomly selected from patients who attended an ophthalmology visit. The lid margin abnormality, meibomian gland expression, tear breakup time, Schirmer’s test results and ocular surface disease index (OSDI) were evaluated. Multiple tear meniscus values include the lower tear meniscus height (TMH), tear meniscus depth (TMD) and tear meniscus area (TMA) were also measured using time-domain ocular coherence tomography. Comparative analyses between groups were performed for all parameters. A statistical significance level of P < 0.05 was considered. Association of ocular surface disease index with lid margin abnormality scores, meibomian gland expression and tear break-up time were evaluated. Results: Ocular surface disease index, lid margin abnormality and meibomian gland expression scores were significantly higher in primary pterygium patients than in normals (P < 0.001). Tear break-up time, Schirmer’s test results, lower TMH, TMD and TMA values donot differ between the two groups (P > 0.05). Correlation analysis demonstrated that lid margin abnormality, meibomian gland expression and tear break-up time were significantly correlated with ocular surface disease index (P < 0.05). Conclusions: Primary pterygium may cause alteration of lid margin and meibomian glands expressions, which is associated with ocular discomfort. Early detection of lid margin and meibomian gland changes seem to be important to understand the relationship between pterygium, tear film functions and changes of the ocular surface.
Biomimetic Antibacterial Pro-Osteogenic Cu-Sericin MOFs for Osteomyelitis Treatment

Osteomyelitis is an inflammation of the bone caused by bacterial infection. It usually develops from broken bones, decayed teeth, or heavily punctured wounds. Multi-drug-resistant bacteria are the major hurdle in the treatment of osteomyelitis. The ever-rising antibiotic resistance even leads to amputations or fatalities as a consequence of chronic osteomyelitis. Hence, a single agent with antibacterial activity as well as bone regenerative properties can serve as a potential off-the-shelf product in the treatment of osteomyelitis. Herein, the antibacterial and pro-osteogenic characteristics of copper sericin (Cu-SER) metal–organic frameworks (MOFs) are reported. Sericin, a silk protein with antibacterial activity and an osteoinduction property, acts as an organic template for the deposition of Cu-SER MOFs, similar to collagen during biomineralization in bone. The MOFs exhibit cytocompatibility and osteogenic activity in a dose-dependent manner, as revealed by cell proliferation (alamarBlue) and mineralization (Alizarin Red S and Energy Dispersive X-ray analysis). The bactericidal activity of Cu-SER MOFs was investigated by scanning electron microscopy and a growth kinetic analysis. Together, the report illuminates the unique phenomenon of Cu-SER MOFs that kill bacteria upon contact while being well-tolerated by primary human cells. Hence, Cu-SER MOFs hold the potential to minimize antibiotic dependence.
Comparative Analysis of Original and Replaced Gut Microbiomes within Same Individuals Identified the Intestinal Microbes Associated with Weight Gaining

The precise mechanisms of action of the host’s gut microbiome at the level of its constituting bacteria are obscure in most cases despite its definitive role. To study the precise role of the gut microbiome on the phenotypes of a host by excluding host factors, we analyzed two different gut microbiomes within the same individual mouse after replacing the gut microbiome with a new one to exclude the host factors. The gut microbiome of conventional C57BL/6 mice was randomly reestablished by feeding fecal samples from obese humans to the mice, and depleting their original gut microbiome with an antibiotic and antifungal treatment. Comparison of body weight changes before and 3 months after the replacement of the gut microbiome showed that the gut microbiome replacement affected the body weight gain in three different ways: positive, medium, and negative. The differences in body weight gain were associated with establishment of a different kind of gut microbiome in each of the mice. In addition, body weight gaining was negatively associated with the Firmicutes/Bacteroidetes ratio, which is consistent with previous recent findings. Thorough statistical analysis at low taxonomic levels showed that uncultured bacteria NR_074436. 1, NR_144750. 1, and NR_0421101. 1 were positively associated with body weight gain, while Trichinella pseudospiralis and uncultured bacteria NR_024815. 1 and NR_144616. 1 were negatively associated. This work shows that replacement of the gut microbiome within the same individual provides an excellent opportunity for the purpose of gut microbiome analysis by excluding the host factors.
Diagnosis in Neuroendocrine Neoplasms: From Molecular Biology to Molecular Imaging

Simple Summary Neuroendocrine neoplasms are a small group of malignancies with a diverse prognosis and behaviour. In order to offer an adequate treatment, physicians need to perform a proper diagnosis, staging and stratification. This review aims to help to integrate the information from pathology, immunohistochemistry, molecular biology and imaging to guide this process. Abstract Neuroendocrine neoplasms (NENs) are a heterogeneous group of tumours with a diverse behaviour, biology and prognosis, whose incidence is gradually increasing. Their diagnosis is challenging and a multidisciplinary approach is often required. The combination of pathology, molecular biomarkers, and the use of novel imaging techniques leads to an accurate diagnosis and a better treatment approach. To determine the functionality of the tumour, somatostatin receptor expression, differentiation, and primary tumour origin are the main determining tumour-dependent factors to guide treatment, both in local and metastatic stages. Until recently, little was known about the biological behaviour of these tumours. However, in recent years, many advances have been achieved in the molecular characterization and diagnosis of NENs. The incorporation of novel radiotracer-based imaging techniques, such as 68Gallium-DOTATATE PET-CT, has significantly increased diagnostic sensitivity, while introducing the theragnosis concept, offering new treatment strategies. Here, we will review current knowledge and novelties in the diagnosis of NENs, including molecular biology, pathology, and new radiotracers.
Design of Control System of Once-Through Steam Generator Based on Proximal Policy Optimization Algorithm

Because of the characteristics of the small water volume of OTSG, it is hard to control the outlet steam pressure when the load is changed or disturbed. This study is devoted to the control of the once-through steam generator (OTSG). A double-layer controller based on the PPO algorithm is proposed to control the outlet steam pressure of OTSG. The bottom layer is the PID controller; it directly regulates the OTSG feed water valve and then controls the steam pressure. The top layer of the controller is the agent based on the PPO algorithm, which is responsible for optimizing the parameters of the PID in real time to obtain better control performance. The agent chooses PID parameters as actions to the environment, and then, the reward value is obtained through the reward function of the environment which enables online learning of the agent. Compared with the PID controller, the simulation experiment result shows that the method not only has a good control performance but also has a good anti-interference ability.
Factors Influencing Imported Beef Purchase Intention: A Case Study in Long Bien District, Hanoi, Vietnam

The objective of the paper was to analyze the factors influencing the purchase intention of consumers for imported beef in Long Bien district, Hanoi. Quantitative and qualitative methods were employed in this study based on an online survey using a structured questionnaire. The data were collected from 388 consumers who bought imported beef or had an intent to buy in the future. Structural equation modeling (SEM) was used to analyze the data. The results of this study showed that the factor of perceived quality and the factor of clear information on the packaging with the country of origin were the significant factors that increased purchase intention. These factors also contributed to increasing the positive attitudes towards the consumption of imported beef. Attitudes were also a mediating factor that positively influenced purchase intention. In addition, the availability of the product in the market contributed to the stronger purchase intention towards imported beef.
SVChecker: a deep learning-based system for smart contract vulnerability detection

The detection of smart contracts vulnerability is a valuable research problem because smart contracts hold a huge amount of cryptocurrency. In the past, popular detection tools were mainly based on some traditional techniques such as fuzzing and symbolic execution, which rely on fixed expert features or patterns and often miss many vulnerabilities. Recent machine learning approaches alleviate this issue but do not notice the semantic information in the source code. In this paper, we develop a system called SVChecker to classify the smart contract source code written in Solidity. To show the superiority of our system, we conduct experiments on more than 40,000 smart contracts collected from Ethereum. Empirically, our experimental results demonstrate that our system outperforms all popular detection tools.
Theorizing Populist Radical-Right Foreign Policy: Ideology and Party Positioning in France and Germany

The success of anti-establishment parties across Europe has fueled debate on the role of populism for foreign policy and its contemporary contestation. The almost-election of Marine Le Pen to the French presidency in 2017, the successes of the Alternative für Deutschland (AfD) in Germany's 2017 and 2021 federal elections, and the central role these populist radical-right (PRR) parties henceforth play in structuring political debate make their wider foreign policy positions an issue of central concern. Yet, we still lack a thorough understanding how populism and radical-right ideology jointly produce a distinct foreign policy positioning beyond European integration. This article tries to narrow this gap by conceptualizing PRR positioning on trade, climate change, development policies, hegemony, and security and defense issues. The comparative analysis of official documents and voting behavior reveals only subtle differences between the Rassemblement national and the AfD, while demonstrating broad commonalities that have the potential to inform research across other cases and world regions on PRR parties’ foreign policy positioning.
In Search of Synergistic Insect Repellents: Modeling of Muscarinic GPCR Interactions with Classical and Bitopic Photoactive Ligands

Insect vector-borne diseases pose serious health problems, so there is a high demand for efficient molecules that could reduce transmission. Using molecular docking and molecular dynamics (MD) simulation, we studied a series of compounds acting on human and insect muscarinic acetylcholine receptors (mAChRs), a novel target of synergistic agents in pest control. We characterized early conformational changes of human M1 and fruit fly type-A mAChR G protein-coupled receptors (GPCRs) in response to DEET, IR3535, and muscarine binding based on the MD analysis of the activation microswitches known to form the signal transduction pathway in class A GPCRs. We indicated groups of microswitches that are the most affected by the presence of a ligand. Moreover, to increase selectivity towards insects, we proposed a new, bitopic, photoswitchable mAChR ligand—BQCA-azo-IR353 and studied its interactions with both receptors. Modeling data showed that using a bitopic ligand may be a promising strategy in the search for better insect control.
Research on How the U.S. Artificial Intelligence Expands the Chinese Media Market

Technological change drives industrial change is the driver of industry innovation and is the unchanging law of development. The United States has been in a robust innovation ecosystem, walking in the pioneer port in the field of artificial intelligence, and its cognitive and strategic position has been firmly at the forefront of the world. The role and function of the media give it the presence of monitoring the social environment, coordinating social relations, passing on culture, providing entertainment, educating the public, delivering information, and guiding the values of the masses. Hence, the impact of artificial intelligence, the weight of its use in the media, is broad and far-reaching. Taking China and the United States as two world economic systems as models, this paper actively discusses the layout and application of the development of artificial intelligence in the media in the United States, summarizes its essence and advantages, and deeply explores how to better develop, expand and integrate Chinese media. This paper finds that due to the differences between China and the United States in institutional mechanisms, audience habits, cultural beliefs and communication methods, we should better integrate resources, narrow the differences, effectively localize and deepen the development of artificial intelligence. Due to the lack of relevant research, this paper will be beneficial to explore the research of artificial intelligence media in China and the United States, and provide some basic viewpoints for the research in this field.
Plant Volatiles and Herbivore Induced Plant Volatiles from Chili Pepper Act as Attractant of the Aphid Parasitoid Aphelinus varipes (Hymenoptera: Aphelinidae)

Plants have evolved a number of different chemical defenses, covering nearly all classes of (secondary) metabolites, that represent a major barrier to herbivory: some are constitutive; others are induced after attacks from herbivores (HIPVs) and may elicit the attraction of predators and parasitoids. Here, we studied how the female solitary endoparasitoid Aphelinus varipes responds to plant and host aphid volatiles in a series of experiments on five commercially important vegetables that were either healthy or infested with the aphid Myzus persicae: chili pepper, eggplant, crown daisy, Chinese cabbage and cabbage. The results for the olfactory responses of A. varipes showed that the presence of M. persicae increased the attraction of the endoparasitoid to the infested plants. In a second experiment, volatiles from highly attractive and repellent plants were obtained via headspace collection to investigate volatiles from healthy and aphid-damaged plants. The results for the differences in volatile profiles in response to aphid infestation in chili pepper cultivar were dominated by the volatile blends, including α-pinene, decanal and phthalic acid, while in cabbage they were dominated by isophorone. Moreover, when HIPVs with different concentrations were compared, α-pinene at a dose rate of 100 ng/μL attracted more parasitoids, and the comparison was useful to understand the mechanisms of plant secondary volatiles during aphid infestation and to provide new resources to control this insect pest. Overall our study shows how HIPVs can bolster tritrophic interactions by enhancing the attractiveness of parasitoids.
Performance Analysis of Metamaterial-Inspired Structure Loaded Antennas for Narrow Range Wireless Communication

Nowadays, the demand for low-cost, compact, and interference rejected antennas with ultrawideband capability has been increased. Metamaterial-inspired loaded structures have capability of providing exceptional solutions for narrow range wireless communication and low consuming power while transmitting and receiving the signal. It is a difficult task to construct ideal metamaterial-inspired antennas with a variety of features such as extremely large bandwidth, notching out undesirable bands, and frequency. Metamaterial-inspired structures such as SRR and CSRR, and triangle-shaped TCSRR are most commonly used structures to achieve optimized characteristics in ultrawideband antennas. In this paper, an extensive literature survey is accomplished to get conception about metamaterial-inspired patch antennas. This review paper elucidates variants of metamaterial-inspired structures/resonators utilized in order to acquire sundry applications such as WiMAX, WLAN, satellite communication, and radar. Various researchers have used different methodology to design, stimulate, and analyze the metamaterial-inspired structure loaded antennas. Also, the results of different metamaterial-inspired antennas such as bandwidth, gain, return loss, and resonant frequency have been also represented in this paper. This manuscript also gives brief introduction about the metamaterial, its types, and then its application in microstrip patch antenna over the last decade. This manuscript throws light over the various studies conducted in the field of metamaterial-inspired antenna in the past. It has been seen that with the inclusion of metamaterial in conventional antenna, various characteristics such as impedance bandwidth, reflection coefficient, gain, and directivity have been improved. Also, frequency rejection of narrow bands which exits in ultrawideband frequency range can be done by embedding metamaterial-inspired structures such as SRR and CSRR.
A mechanical wearing fault diagnosis method of aero-engine based on RSS-ERT

A fault diagnosis method based on RSS-ERT was proposed to deal with the mechanical wearing fault of aero-engine through combining with oil analysis. After pre-processing the element concentration data of aero-engine oil sample analysis, in order to train more models and have more randomness, Return Sampling Strategy (RSS) was adopted in the build of Extreme Random Tree (ERT) model. The coefficient of determination (R 2 ) was used to evaluate performance of the model. This model and benchmark model were used to forecast engine health parameters. The result showed that the fault diagnosis method based on RSS-ERT was accurate and superior.
Deep Learning-Based Denoising in Brain Tumor CHO PET: Comparison with Traditional Approaches

18F-choline (CHO) PET image remains noisy despite minimum physiological activity in the normal brain, and this study developed a deep learning-based denoising algorithm for brain tumor CHO PET. Thirty-nine presurgical CHO PET/CT data were retrospectively collected for patients with pathological confirmed primary diffuse glioma. Two conventional denoising methods, namely, block-matching and 3D filtering (BM3D) and non-local means (NLM), and two deep learning-based approaches, namely, Noise2Noise (N2N) and Noise2Void (N2V), were established for imaging denoising, and the methods were developed without paired data. All algorithms improved the image quality to a certain extent, with the N2N demonstrating the best contrast-to-noise ratio (CNR) (4.05 ± 3.45), CNR improvement ratio (13.60% ± 2.05%) and the lowest entropy (1.68 ± 0.17), compared with other approaches. Little changes were identified in traditional tumor PET features including maximum standard uptake value (SUVmax), SUVmean and total lesion activity (TLA), while the tumor-to-normal (T/N ratio) increased thanks to smaller noise. These results suggested that the N2N algorithm can acquire sufficient denoising performance while preserving the original features of tumors, and may be generalized for abundant brain tumor PET images.