Miracle-dz/UniFAR-FTUs huggingface dataset:
Disclosure Standards for Social Media and Generative Artificial Intelligence Research: Toward Transparency and Replicability

Social media dominate today’s information ecosystem and provide valuable information for social research. Market researchers, social scientists, policymakers, government entities, public health researchers, and practitioners recognize the potential for social data to inspire innovation, support products and services, characterize public opinion, and guide decisions. The appeal of mining these rich datasets is clear. However, there is potential risk of data misuse, underscoring an equally huge and fundamental flaw in the research: there are no procedural standards and little transparency. Transparency across the processes of collecting and analyzing social media data is often limited due to proprietary algorithms. Spurious findings and biases introduced by artificial intelligence (AI) demonstrate the challenges this lack of transparency poses for research. Social media research remains a virtual “wild west,” with no clear standards for reporting regarding data retrieval, preprocessing steps, analytic methods, or interpretation. Use of emerging generative AI technologies to augment social media analytics can undermine validity and replicability of findings, potentially turning this research into a “black box” enterprise. Clear guidance for social media analyses and reporting is needed to assure the quality of the resulting research. In this article, we propose criteria for evaluating the quality of studies using social media data, grounded in established scientific practice. We offer clear documentation guidelines to ensure that social data are used properly and transparently in research and applications. A checklist of disclosure elements to meet minimal reporting standards is proposed. These criteria will make it possible for scholars and practitioners to assess the quality, credibility, and comparability of research findings using digital data.
A new 14,15-dinor-labdane Glucoside from Crassocephalum Mannii

A new 14,15-dinor-labdane glucoside, named crassoside A (1), was isolated from the aerial parts of Crassocephalum mannii. The structure of 1 was elucidated on the basis of spectroscopic analysis (1H NMR, 13C NMR, HMQC, HMBC and NOEs). Compound 1 demonstrated a low inhibitory effect against COX-1, but was inactive against COX-2.
Preliminary Study on the Effects of Saline Water Irrigation on Soil Salinization in Deep Groundwater Area:A case study of Minqin oasis

Massive exploitation of underground water in Minqing oasis in recent decades caused a sharp decline in groundwater level,and underground salt water is still being mined for agricultural irrigation.The present study investigates the effects of salt water irrigation on soil salinity in the deep groundwater zone by using the field experiment.The salt from irrigation water is the main source of salt accumulated in soil surface of areas where groundwater table is very deep and saline water is used for agricultural irrigation.During the process of saline water irrigation,soil salinity of the root zone increased rapidly after previous fresh water leaching process.High salt concentration of the irrigation water leads to a significant increase of soil salinity in the soil.The rate of salt accumulation were 22.67% and 35.30% under 2 g·L-1 and 5 g·L-1 saline water irrigation respectively.Referring to sweet melon planted with high ridge and film mulching,the soil salt is leached significantly under film-furrow irrigation.However,due to the field partially covered by film mulching,uncovered soil encounters a strong evaporation which results in salt accumulation.Saline water irrigation increases pH value and enhances soil Exchangeable Sodium Percentage(ESP),especially when the salinity of irrigation water is 5 g·L-1.The ESP value is 5.7 in plough layer and soil shows slight alkalization when 5 g·L-1 salt water is used.
Commonsense Injection in Conversational Systems: An Adaptable Framework for Query Expansion

Recent advancements in conversational agents are leading a paradigm shift in how people search for their information needs, from text queries to entire spoken conversations. This paradigm shift poses a new challenge: a single question may lack the context driven by the entire conversation. We propose and evaluate a framework to deal with multi-turn conversations with the injection of commonsense knowledge. Specifically, we propose a novel approach for conversational search that uses pre- trained large language models and commonsense knowledge bases to enrich queries with relevant concepts. Our framework comprises a generator of candidate concepts related to the context of the conversation and a selector for deciding which candidate concept to add to the current utterance to improve retrieval effectiveness. We use the TREC CAsT datasets and ConceptNet to show that our framework improves retrieval performance by up to 82% in terms of Recall@200 and up to 154% in terms of NDCG@3 as compared to the performance achieved by the original utterances in the conversations.
ImmunoPET Targeting Receptor Tyrosine Kinase: Clinical Applications

Simple Summary Receptor tyrosine kinases (RTKs) are a family of transmembrane proteins that play crucial roles in regulating various cellular processes. The introduction of ImmunoPET targeting RTKs by specific monoclonal antibodies (mAbs) or antibody fragments is regarded as a promising tool for imaging treatment efficacy and developing anticancer drugs. Herein, we review the current clinical research on ImmunoPET targeting RTKs, with particular interest in the epidermal growth factor family, or HER family, and vascular endothelial-derived growth factor/receptor. Abstract Receptor tyrosine kinases, or RTKs, are one large family of cell surface receptors involved in signal transduction, which represent an integral part of the signaling pathways. They play a crucial role in most important cellular processes, starting with the cell cycle, proliferation and differentiation, as well as cell migration, metabolism and survival. The introduction of ImmunoPET evaluating the expression of RTKs by specific monoclonal antibodies (mAbs) or antibody fragments is regarded as a promising tool for imaging treatment efficacy and developing anticancer therapeutics. Our review focuses mainly on the current clinical research regarding ImmunoPET targeting RTKs, with particular interest in the epidermal growth factor family, or HER family, and vascular endothelial-derived growth factor/receptor.
Inhibitory Effects of Scopoletin in Collagen-induced Human Platelet Aggregation

Platelet aggregation is essential for the formation of a hemostatic plug in the case of blood vessel damage. On the other hand, excessive platelet aggregation may cause cardiovascular disorders, such as thrombosis, atherosclerosis, and myocardial infarction. Scopoletin, which found in the root of plants in the genus Scopolia or Artemisia, has anti-coagulation and anti-malaria effects. This study examined the effects of scopoletin on human platelet aggregation induced by collagen. Scopoletin had anti-platelet effects via the down-regulation of thromboxane A2 (TXA2) production and intracellular Ca mobilization ([Ca]i), which are aggregation-inducing molecules produced in activated platelets. On the other hand, scopoletin increased both the cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) levels, which are known as intracellular Ca-antagonists and aggregation-inhibiting molecules. In particular, scopoletin increased the potently cAMP level more than cGMP, which led to suppressed fibrinogen binding to IIb/3 in collagen-induced human platelet aggregation. In addition, scopoletin inhibited collagen-elevated adenosine triphosphate (ATP) release in a dose-dependent manner. The results suggest that aggregation amplification through granule secretion is inhibited by scopoletin. Therefore, scopoletin has potent anti-platelet effects and may have potential for the prevention of platelet-derived vascular diseases.
Study of the low-cost HIPS and paraffin-based terahertz optical components

The ever-increasing popularity of the terahertz (THz) frequency range reveals the increasingly obvious applicability limiting factor – the price of the final setup. This study is intended to contribute to the solution by evaluating the THz frequency range suitability of the optical components, fabricated using two easily accessible materials – high impact polystyrene (HIPS) and paraffin. The primary analysis using time-domain spectroscopy (TDS) revealed promising results, as both materials had sufficient refractive indexes of n ≈ 1.55 and a high transmittance. That allowed one to assume the feasibility of creating a low-cost THz frequency range lens. Lenses of focal lengths of f = 20, 30, 40 mm were fabricated using extrusion 3D printing and paraffin moulding. The produced lenses showcased the satisfactory beam focusing ability, comparable to that of already existing much less cost-efficient solutions. The THz imaging using the fabricated lenses has successfully been realized, proving the applicational possibilities of the imaging system with the proposed low-cost components employed.
The Effectiveness of E-Learning Madrasah in Teaching Reading toward Students' Reading Achievement in MTsN 2 Kota Kediri

The purpose of this research was to describe the effectiveness of using E-learning Madrasah in teaching reading. This research was conducted using a descriptive quantitative approach, precisely the experimental method and the technique was used in data collection was a posttest-only control design. This research conducted to find out is there any significant different in student’s reading achievement between the experimental class and the control class. This research was conducted on 7th grade students of MTsN 2 Kota Kediri. The researcher used two classes, namely class 7I as an experimental class with a total of 35 students, and class 7J as a control class with a total of 36 students. The instrument that used was posttest and the data were analyzed by T-Test. The result of this research indicates that the student's English reading achievements in the experimental class has the mean score 80,00 which is categorized as GOOD based on the categorization table, the student's English reading achievements in the control class has the mean score 69,17 which is categorized as GOOD based on the categorization table, and the result of T-Test show that t = 3,740, df = N-2 (71-2 = 69), Sig. (2-tailed) = 0,000, and 95% confidence interval ranging from 16,612 to 5,054. The Sig. (2-tailed) is lower than 5% (0.000< 0.05), it can be concluded that there is significant difference between the experimental class and the control class.
Rationally Designed Novel Phenyloxazoline Synthase Inhibitors: Chemical Synthesis and Biological Evaluation to Accelerate the Discovery of New Antimycobacterial Antibiotics

The uncontrolled spread of drug-resistant tuberculosis (DR-TB) clinical cases necessitates the urgent discovery of newer chemotypes with novel mechanisms of action. Here, we report the chemical synthesis of rationally designed novel transition-state analogues (TSAs) by targeting the cyclization (Cy) domain of phenyloxazoline synthase (MbtB), a key enzyme of the conditionally essential siderophore biosynthesis pathway. Following bio-assay-guided evaluation of TSA analogues preferentially in iron-deprived and iron-rich media to understand target preferentiality against a panel of pathogenic and non-pathogenic mycobacteria strains, we identified a hit, i.e., TSA-5. Molecular docking, dynamics, and MMPBSA calculations enabled us to comprehend TSA-5’s stable binding at the active site pocket of MbtB_Cy and the results imply that the MbtB_Cy binding pocket has a strong affinity for electron-withdrawing functional groups and contributes to stable polar interactions between enzyme and ligand. Furthermore, enhanced intracellular killing efficacy (8 μg/mL) of TSA-5 against Mycobacterium aurum in infected macrophages is noted in comparison to moderate in vitro antimycobacterial efficacy (64 μg/mL) against M. aurum. TSA-5 also demonstrates whole-cell efflux pump inhibitory activity against Mycobacterium smegmatis. Identification of TSA-5 by focusing on the modular MbtB_Cy domain paves the way for accelerating novel anti-TB antibiotic discoveries.
Buspirone Enhances Cell Survival and Preserves Structural Integrity during Oxidative Injury to the Retinal Pigment Epithelium

Chronic oxidative stress impairs the normal functioning of the retinal pigment epithelium (RPE), leading to atrophy of this cell layer in cases of advance age-related macular degeneration (AMD). The purpose of our study was to determine if buspirone, a partial serotonin 1A (5-HT1A) receptor agonist, protected against oxidative stress-induced changes in the RPE. We exposed differentiated human ARPE-19 cells to paraquat to induce oxidative damage in culture, and utilized a mouse model with sodium iodate (NaIO3)-induced oxidative injury to evaluate the effect of buspirone. To investigate buspirone’s effect on protective gene expression, we performed RT–PCR. Cellular toxicities and junctional abnormalities due to paraquat induction in ARPE-19 cells and buspirone’s impact were assessed via WST-1 assays and ZO-1 immunostaining. We used spectral-domain optical coherence tomography (SD-OCT) and ZO-1 immunostaining of RPE/choroid for structural analysis. WST-1 assays showed dose-dependent protection of viability in buspirone-treated ARPE-19 cells in culture and preservation of RPE junctional integrity under oxidative stress conditions. In the NaIO3 model, daily intraperitoneal injection (i.p.) of buspirone (30 mg/kg) for 12 days improved the survival of photoreceptors compared to those of vehicle-treated eyes. ZO-1-stained RPE flat-mounts revealed the structural preservation of RPE from oxidative damage in buspirone-treated mice, as well as in buspirone-induced Nqo1, Cat, Sqstm1, Gstm1, and Sod2 genes in the RPE/choroid compared to untreated eyes. Since oxidative stress is implicated in the pathogenesis AMD, repurposing buspirone, which is currently approved for the treatment of anxiety, might be useful in treating or preventing dry AMD.
Calculating Time-Specific Flux of Runoff Using DEM Considering Storm Sewer Collection Systems

AbstractA new technique is proposed for calculating time-specific accumulative flux of surface runoff from a digital elevation model (DEM). The method incorporates ancillary datasets required to determine the depth of effective rainfall and a priori information on surface and underground storm sewer collection systems, permitting grid-based hydrologic analysis using a DEM. The diffusion wave equation is used to analyze temporal changes in surface runoff variables such as flow depth and velocity. Therefore, time-specific accumulative flux of surface runoff for each DEM cell, and for inlets and outfalls of the storm sewer collection systems, can be calculated and used to simulate the propagation of flood waves around storm sewers. The technique was applied to the Sangdong tailings dam in Korea that has both surface drainage and storm sewers. The proposed technique provides better time-specific hydrologic information on watersheds that contain both surface and underground storm sewer collection systems, whic.
Teaching Reading to English Language Learners: Insights from Linguistics.

Big Ideas and Research That Guide the Profession. First-Language Influence in Second-Language Acquisition. ELL Oracy: Listening Comprehension and Oral Language Development. Learning to Read, Write, and Spell Words in English as a New Language. Using Morphemes to Learn Vocabulary. Word Formation Processes, Cognates, and Collocations. "The Same, but Different": Reading Fluency in English as a New Language. Achieving Comprehension in L2 English Reading. Writing to Learn in English across the Curriculum. Glossary.
Intracellular Degradation of SARS-CoV-2 N-Protein Caused by Modular Nanotransporters Containing Anti-N-Protein Monobody and a Sequence That Recruits the Keap1 E3 Ligase

The proper viral assembly relies on both nucleic acids and structural viral proteins. Thus a biologically active agent that provides the degradation of one of these key proteins and/or destroys the viral factory could suppress viral replication efficiently. The nucleocapsid protein (N-protein) is a key protein for the SARS-CoV-2 virus. As a bioactive agent, we offer a modular nanotransporter (MNT) developed by us, which, in addition to an antibody mimetic to the N-protein, contains an amino acid sequence for the attraction of the Keap1 E3 ubiquitin ligase. This should lead to the subsequent degradation of the N-protein. We have shown that the functional properties of modules within the MNT permit its internalization into target cells, endosome escape into the cytosol, and binding to the N-protein. Using flow cytometry and western blotting, we demonstrated significant degradation of N-protein when A549 and A431 cells transfected with a plasmid coding for N-protein were incubated with the developed MNTs. The proposed MNTs open up a new approach for the treatment of viral diseases.
EARLY DIAGNOSIS OF ANASTOMOTIC LEAKAGE AFTER ELECTIVE COLO-RECTAL SURGERY USING DUTCH LEAKAGE SCORE – A PROSPECTIVE OBSERVATIONAL STUDY

Introduction: Anastomotic leakage is a major complication after colorectal surgery, with reported incidence of 2–7%. To limit the clinical consequences, it should be detected and treated as soon as possible. Leak usually becomes apparent between 5 and 7 days postoperatively. A standardized post-operative score, Dutch Leakage Score (DLS) can be a useful clinical tool to reduce delay in diagnosis of anastomotic leak (AL) and reduce mortality. A score of <4 was considered negative while a score of 4 or more was considered positive. Methods: Total 110 patients were enrolled after written informed consent during March 2021–October 2022 at a tertiary care hospital in Odisha. DLS was measured before surgery and on POD2, POD3, and POD6. Results: Among the 110 patients, the AL rate was 16.4%. With respect to AL, DLS cutoff of 2.5 on POD2 had positive predictive value (PPV) of 53.10% and a negative predictive value (NPV) of 98.70%. DLS cutoff of 4.0 on POD3 had a PPV of 80.90% and a NPV 98.90%. DLS cutoff of 3.0 on POD6 had a PPV of 84.20% and a NPV of 96.70%. The most common day of AL was the fifth P.O. D (in seven patients) followed by sixth P.O. D (in five patients). Conclusion: DLS is a good positive and excellent negative predictor of AL. DLS is an easy bedside assessment to gauge the likelihood of AL in the early post-operative period.
Unsupervised Domain Adaptation for Instance Segmentation: Extracting Dwellings in Temporary Settlements Across Various Geographical Settings

Dwelling information is essential for humanitarian emergency response during or in the aftermath of disasters, especially in temporary settlement areas hosting forcibly displaced people. To map dwellings, the integration of very high-resolution remotely sensed imagery in computer vision models plays a key role. However, state-of-the-art deep learning models have two known downsides: 1) lack of generalization across space and time under changing scenes and object characteristics, and 2) extensive demand for annotated samples for training and validation. Both could pose a critical challenge during an emergency. To bypass this problem, this study deals with unsupervised domain adaptation for instance segmentation using a single-stage instance segmentation model, namely segmenting objects by location (SOLO). The goal is to adapt a SOLO model trained on a labeled source domain to detect dwellings in an unlabeled target domain. In this context, we study three domain adaptation techniques based on adversarial learning, domain discrepancy, and domain alignment mapping. We also propose domain similarity at different levels to understand its implication on domain adaptation. Experiments are conducted on very high-resolution satellite images obtained from four temporary settlement areas located in different countries and exhibiting various spatial characteristics. Analysis results show that in most source–target combinations unsupervised domain adaptation improves the performance by a large margin even surpassing a model trained with supervised learning. There is also an observed performance deviation among implemented strategies and different source–target dataset combinations. From the in-depth analysis of domain similarity at the image, object, and deep feature space levels, the former is more correlated with unsupervised domain adaptation performance.
Design of High-Speed, Low-Power Sensing Circuits for Nano-Scale Embedded Memory

This paper comparatively reviews sensing circuit designs for the most widely used embedded memory, static random-access memory (SRAM). Many sensing circuits for SRAM have been proposed to improve power efficiency and speed, because sensing operations in SRAM dominantly determine the overall speed and power consumption of the system-on-chip. This phenomenon is more pronounced in the nanoscale era, where SRAM bit-cells implemented near minimum-sized transistors are highly influenced by variation effects. Under this condition, for stable sensing, the control signal for accessing the selected bit-cell (word-line, WL) should be asserted for a long time, leading to increases in the power dissipation and delay at the same time. By innovating sensing circuits that can reduce the WL pulse width, the sensing power and speed can be efficiently improved, simultaneously. Throughout this paper, the strength and weakness of many SRAM sensing circuits are introduced in terms of various aspects—speed, area, power, etc.
Regional Differences in the Influence of COVID-19 Pandemic on Physical Activity Among Chinese Adults: A Social-Ecological Perspective

PURPOSE: Physical activity confers benefits by mitigating the adverse physical and mental effects of coronavirus disease 2019 (COVID-19). Nevertheless, during a public health crisis, in which group-based physical activity is restricted, participation in such activities may be influenced not only by social distancing policies, but also by individual and environmental factors. As such, this study adopted a socio-ecological perspective to explore the impact of multidimensional factors on physical activity across diverse regions during the COVID-19 pandemic.METHODS: Cross-sectional data from the 2021 Chinese General Social Survey (CGSS) were used. A total of 8148 respondents from 12 provinces and metropolitan cities were pooled. Two types of physical activity (walking and moderate-to-vigorous exercise) were included in the statistical tests. A three-step hierarchical regression analysis was used to analyze the incremental predictive power of factors related to intrapersonal, interpersonal and community resources for physical activity.RESULTS: Findings highlighted the significance of intrapersonal (e.g., age, sex, socio-economic status, health status, and household registration area), interpersonal (e.g., neighborhood help and friendship), and community (e.g., exercise facility, fresh food accessibility, public facility, and residential safety) resources. These factors were significantly associated with Chinese adults’ participation in physical activity across various regions.CONCLUSIONS: Findings of this study provide an initial validation of the socio-ecological approach to studying physical activity during the COVID-19 pandemic, suggesting that strategies aimed at promoting the benefits of exercise should include multiple factors that influence the likelihood of Chinese adults engaging in physical activity.