Miracle-dz/UniFAR-FTUs huggingface dataset:
Association Between Neutrophil-Lymphocyte Ratio and Gestational Diabetes—A Systematic Review and Meta-Analysis

Abstract A growing body of evidence shows that the neutrophil-lymphocyte ratio (NLR) is a surrogate index of systemic inflammation in several chronic diseases. Conflicting associations between NLR and gestational diabetes mellitus (GDM) have been reported in individual studies. This meta-analysis sought to investigate the association between NLR and GDM. The PubMed, EMBASE, and Google Scholar databases were searched to identify relevant articles. The pooled standardized mean difference with 95% CI was calculated using a random-effects model. Subgroup and meta-regression analysis were carried out to control for the effects of GDM diagnostic criteria, ethnicity, body mass index (BMI), and age. Eleven eligible articles were included, containing 1271 participants with GDM and 1504 controls. Pooled outcomes indicated a higher NLR in GDM pregnancies than in normoglycemic controls (SMD = 0.584; 95% CI, 0.339–0.830; P < .001), although extensive heterogeneity between studies was noted. Subgroup analysis revealed that the higher pooled estimate in GDM was not affected by diagnostic criteria, ethnicity, or BMI, although matching for BMI reduced heterogeneity between studies. This meta-analysis supports the higher NLR in GDM described by some individual studies.
Using Modal Participation to Improve Numerical Stability in Power System Simulations

This work presents a method for improving the numerical stability of the trapezoidal solver in discretized power system simulations. The approach identifies the appropriate physical locations in the system to apply optimized damping networks that mitigate spurious numerical oscillations. The identification procedure is based on the concept of state participation in the weak system modes. State participation is determined using the participation matrix, a concept borrowed from power system stability. The approach is tested on a standard benchmark system and the results are compared with the backward Euler method. Comparison shows that the trapezoidal method with the applied optimized damping is better able to capture high frequency transients while retaining acceptable numerical stability.
2D WSe2 Flakes for Synergistic Modulation of Grain Growth and Charge Transfer in Tin‐Based Perovskite Solar Cells

Tin (Sn)‐based perovskites with favorable optoelectronic properties and ideal bandgaps have emerged as promising alternatives to toxic lead (Pb)‐based perovskites for photovoltaic applications. However, it is challenging to obtain high‐quality Sn‐based perovskite films by solution process. Here, liquid‐exfoliated 2D transition‐metal dichalcogenides (i.e., MoS2, WS2, and WSe2) with smooth and defect‐free surfaces are applied as growth templates for spin‐coated FASnI3 perovskite films, leading to van der Waals epitaxial growth of perovskite grains with a growth orientation along (100). The authors find that WSe2 has better energy alignment with FASnI3 than MoS2 and WS2 and results in a cascade band structure in resultant perovskite solar cells (PSCs), which can facilitate hole extraction and suppress interfacial charge recombination in the devices. The WSe2‐modified PSCs show a power conversion efficiency up to 10.47%, which is among the highest efficiency of FASnI3‐based PSCs. The appealing solution phase epitaxial growth of FASnI3 perovskite on 2D WSe2 flakes is expected to find broad applications in optoelectronic devices.
How Threatened Is Scincella huanrenensis? An Update on Threats and Trends

It is important to understand the dynamics of population size to accurately assess threats and implement conservation activities when required. However, inaccurate estimates are harming both the threat estimation process, and the resulting conservation actions. Here, we address the extinction threats to Scincella huanrenensis, a species described in the People’s Republic of China, but also occurring on the Korean peninsula. Estimating the threats to the species is not an easy task due to its unknown population status in the Democratic People’s Republic of Korea. Here we analysed the literature to acquire the known presence point for the species, along with datapoints originating from opportunistic field surveys, and employed habitat suitability models to estimate the range of the species. We then followed the categories and criteria of the IUCN Red List of Threatened Species to assess the extinction risk of the species. We found the species not to be fitting the threatened category at the global scale based on the range size, the only category for which enough data was available. We recommend the status of the species on the IUCN Red List of Threatened Species to be updated as it is now listed as critically endangered (CR), a listing fitting a national assessment for the People’s Republic (PR) of China. While this species is possibly less threatened than currently listed, this is not a genuine improvement, and specific conservation aspects should not be neglected due to its specialisation to medium to high elevation habitat.
High-Resolution Estimates of Fire Severity—An Evaluation of UAS Image and LiDAR Mapping Approaches on a Sedgeland Forest Boundary in Tasmania, Australia

With an increase in the frequency and severity of wildfires across the globe and resultant changes to long-established fire regimes, the mapping of fire severity is a vital part of monitoring ecosystem resilience and recovery. The emergence of unoccupied aircraft systems (UAS) and compact sensors (RGB and LiDAR) provide new opportunities to map fire severity. This paper conducts a comparison of metrics derived from UAS Light Detecting and Ranging (LiDAR) point clouds and UAS image based products to classify fire severity. A workflow which derives novel metrics describing vegetation structure and fire severity from UAS remote sensing data is developed that fully utilises the vegetation information available in both data sources. UAS imagery and LiDAR data were captured pre- and post-fire over a 300 m by 300 m study area in Tasmania, Australia. The study area featured a vegetation gradient from sedgeland vegetation (e.g., button grass 0.2m) to forest (e.g., Eucalyptus obliqua and Eucalyptus globulus 50m). To classify the vegetation and fire severity, a comprehensive set of variables describing structural, textural and spectral characteristics were gathered using UAS images and UAS LiDAR datasets. A recursive feature elimination process was used to highlight the subsets of variables to be included in random forest classifiers. The classifier was then used to map vegetation and severity across the study area. The results indicate that UAS LiDAR provided similar overall accuracy to UAS image and combined (UAS LiDAR and UAS image predictor values) data streams to classify vegetation (UAS image: 80.6%; UAS LiDAR: 78.9%; and Combined: 83.1%) and severity in areas of forest (UAS image: 76.6%, UAS LiDAR: 74.5%; and Combined: 78.5%) and areas of sedgeland (UAS image: 72.4%; UAS LiDAR: 75.2%; and Combined: 76.6%). These results indicate that UAS SfM and LiDAR point clouds can be used to assess fire severity at very high spatial resolution.
Molecular cloning and functional characterization of two insect chitin deacetylases from the American white moth, Hyphantria cunea

Chitin deacetylases (CDAs) convert chitin into chitosan and play crucial roles in the insect biological processes, including growth and development. In this study, two CDA‐encoding genes, HcCDA1 and HcCDA4, were identified from Hyphantria cunea. Conserved Domain Database for HcCDA1 identified a chitin‐binding peritrophin‐A domain (ChBD), a low‐density lipoprotein receptor class A domain (LDLa), and a putative CDA‐like catalytic domain (CDA), whereas HcCDA4 lacked the LDLa domain. Phylogenetic comparison with other insect CDAs revealed that HcCDA1 belonged to the insect group I CDA and HcCDA4 belonged to group III. qRT‐PCR results showed that HcCDA1 and HcCDA4 were more highly expressed in newly moulted 5th‐instar larvae, and HcCDA1 was highly expressed in the integument, whereas HcCDA4 was abundantly transcribed in the integument and hindgut. Western blot revealed that the expression of HcCDA1 and HcCDA4 in translational levels were consistent with the transcription. Double‐stranded RNA injection of HcCDA1 and HcCDA4 into H. cunea larvae significantly reduced HcCDA transcript levels, resulted in larval–pupal moulting difficulty, and produced high larval mortality. These results demonstrate important contributions of HcCDA1 and HcCDA4 to insect moulting and development and provide potential new targets for designing effective double‐stranded RNA‐based pesticides to protect crops.
Thermal Characterizations of a Lithium Titanate Oxide-Based Lithium-Ion Battery Focused on Random and Periodic Charge-Discharge Pulses

Thermal characterization of lithium-ion batteries is essential to improve an efficient thermal management system for lithium-ion batteries. Besides, it is needed for safe and optimum application. The investigated lithium-ion battery in the present research is a commercially available lithium titanate oxide-based lithium-ion battery, which can be used in different applications. Different experimental facilities were used to measure lithium-ion battery heat generation at different operating conditions and charge and discharge rates in this investigation. Isothermal battery calorimeter is the exclusive calorimeter globally, suitable for lithium-ion batteries’ accurate thermal measurements. Pulse charge and discharge in different increments of state of charge were applied to the lithium titanate oxide-based lithium-ion battery to designate the heat generation of the lithium-ion battery cell. Three different cases were studied. The precise effects of different state-of-charge levels and current-rates on lithium-ion battery total generated heat was investigated. The maximum heat generation during 13 A, 40 A, 50 A, 60 A and 100 A pulse discharges were 0.231 Wh, 0.77 Wh, 0.507 Wh, 0.590 Wh and 1.13 Wh correspondingly. It could be inferred that in the case of periodic charge and discharge pulses applied to the lithium titanate oxide-based lithium-ion battery, important parameters including state of charge, current rates, initial cycling, and temperature have a significant influence on total generated heat.
Bioactivity Screening of Endophytic Fungus Eutypa linearis isolated from Coleus amboinicus (Lour.)

Email: puji_astuti@ugm.ac. id Coleus amboinicus (Lour.) is a medicinal plant containing various bioactive compounds. Endophytes are microorganisms living inside the intracellular tissue of plants and are known as the source of bioactive compounds. In order to explore the potential of endophytes in producing novel bioactive compounds, this study focused on isolating endophytic fungi from the leaves of C.amboinicus, characterizing, and screening their metabolite bioactivity during submerged culture fermentation. Isolation of endophytic fungi from the leaves segment of C.amboinicus was conducted in PDA media and fungus identification was carried out by analyzing its morphology and through molecular examination. The production of metabolites was examined using thin-layer chromatography and gas chromatography. Identification of the endophytic fungus showed 98.84% similarity with Eutypa linearis. This species was fermented by submersion in PDB medium for 14 days under dark and exposed to light conditions. The fermentation broth was extracted using ethyl acetate. The results showed that exposure to light influenced metabolite production. The ethyl acetate extract exhibited antioxidant and cytotoxic activities. Antioxidant activity of this extract as examined by DPPH assay showed IC50 of 105.31±2. 11μg/mL. Cytotoxic activity against the Hela cell line was known to be the best compared with other cell lines (IC50 302.28±10.30 μg/mL) although it was found to be nonselective (SI<3). The extract contained five major compounds namely benzenemethanol, 4-nitro-(CAS) p-nitrobenzyl alcohol; 2-pentadecanone (CAS) pentadecan-2-one; (1R*,6S*,10R*)-5,5-dimethyl-11,12-dioxatricyclo[8.2. 1.0(1,6)] tridecan-10-ol; 9,12-cctadecadienoic acid (Z,Z)-, methyl ester (CAS) methyl linoleate; and 3furanacetic acid, 4-hexyl-2,5-dihydro-2,5-dioxo(CAS) 2-carboxymethyl-3-Nhexyl-maleic anhydride.
Low-temperature sprayed carbon electrode in modular HTL-free perovskite solar cells: a comparative study on the choice of carbon sources

Due to their outstanding advantages like excellent moisture resistance and compatibility with up-scalable manufacturing processes, carbon (C) electrode hole transport layer (HTL)-free perovskite solar cells (PSCs) represent an excellent solution to the serious limitations caused by the commonly used HTL and expensive noble metal electrode. The C-electrode can be deposited using different techniques from various carbon allotropes and their derivatives. However, the choice of optimal carbon sources is still open to debate, which will certainly have a strong effect on the performance and long-term stability of the resulting PSCs. Here, the modular HTL-free C-PSCs were assembled by the lamination of two independently processed half-stacks of a semi-cell and a charge collector, where the C-electrodes were processed using a simple spray coating technique at low temperature (85 °C). Three typical carbon sources were used, i.e., multiwall carbon nanotube (MWCNT), carbon nanocoil (CNC), and graphene. A comparative study was conducted to determine the best candidate. Results indicated that MWCNT might be more preferable as the back electrode in HTL-free PSCs in terms of well-aligned band alignment, superior ability in extraction and collection of photo-generated holes. As a result, an improved power conversion efficiency (PCE) of 11.2% was achieved for modular MWCNT-based PSCs, and much improved thermal and humidity stabilities were also demonstrated. Our achievement demonstrates the irreplaceable role of tri-functional MWCNT in C-based HTL-free PSCs with integrated function: (i) back electrode; (ii) hole extraction and collection; and (iii) excellent moisture barrier.
Intelligent Detection of False Information in Arabic Tweets Utilizing Hybrid Harris Hawks Based Feature Selection and Machine Learning Models

Fake or false information on social media platforms is a significant challenge that leads to deliberately misleading users due to the inclusion of rumors, propaganda, or deceptive information about a person, organization, or service. Twitter is one of the most widely used social media platforms, especially in the Arab region, where the number of users is steadily increasing, accompanied by an increase in the rate of fake news. This drew the attention of researchers to provide a safe online environment free of misleading information. This paper aims to propose a smart classification model for the early detection of fake news in Arabic tweets utilizing Natural Language Processing (NLP) techniques, Machine Learning (ML) models, and Harris Hawks Optimizer (HHO) as a wrapper-based feature selection approach. Arabic Twitter corpus composed of 1862 previously annotated tweets was utilized by this research to assess the efficiency of the proposed model. The Bag of Words (BoW) model is utilized using different term-weighting schemes for feature extraction. Eight well-known learning algorithms are investigated with varying combinations of features, including user-profile, content-based, and words-features. Reported results showed that the Logistic Regression (LR) with Term Frequency-Inverse Document Frequency (TF-IDF) model scores the best rank. Moreover, feature selection based on the binary HHO algorithm plays a vital role in reducing dimensionality, thereby enhancing the learning model’s performance for fake news detection. Interestingly, the proposed BHHO-LR model can yield a better enhancement of 5% compared with previous works on the same dataset.
Effect of urea on the surface and thermodynamic properties of some micellar solutions

From the surface tension data, surface and thermodynamic properties of sodium dodecyl sulfate (SDS), dodecyltrimethylammonium bromide (DTAB) and Trion X-100 in aqueous solutions, containing varying amounts of urea have been obtained. Whereas the addition of urea causes a decrease in the critical micelle concentration (CMC) of SDS solution, it results in the increase of CMC values of DTAB and Triton X-100. Tile micellization in the bulk solution and the adsorption of surfactant at the liquid-air interface in the presence of urea are favoured both by energy as well as entropy effects.
Keeping up with influencers: exploring the impact of social presence and parasocial interactions on Instagram

Abstract An experiment was conducted to examine the level of social presence and the mediating role of parasocial interaction in influencer marketing. In a simulated fitness influencer’s Instagram posts, social presence significantly predicts individuals’ purchase intent toward the brand featured in the posts as well as self-efficacy, working through parasocial interactions. Parasocial interaction with influencers serves as a mediator, while influencers can act as role models to motivate people to take action and benefit the brand by encouraging consumers to purchase the products featured in their posts. Higher social presence in the posts led individuals to feel that the posts were less promotional. The effect of parasocial interaction was moderated by advertising recognition, such that lower social presence posts appeared to suggest a promotional appeal and negatively affected purchase intent. Thus, social presence and parasocial interaction are key predictors of successful influencer marketing, yet they can pose a concern because they may hinder consumers from developing accurate persuasion knowledge.
Use of collaborative concept mapping in team diagnosis

Teamwork is necessary to accomplish challenging and information‐rich tasks in complex industrial systems, such as fault diagnosis in nuclear power plants. To improve team performance, assistive visualization tools are used to promote communication and reduce cognitive conflicts. As a shared visualization technology, collaborative concept mapping can effectively externalize one's thoughts into a visualized structure, thereby improving the efficiency of communication and information processing. This study accordingly investigates the effects of collaborative concept mapping on team diagnosis in two fault situations with different complexity levels in a simulated nuclear power plant: one caused by a single initiating event, and the other triggered by two initiating events. The dependent variables included fault analysis score, diagnostic result score, diagnosis time, workload, score of concept map content, and fixation time on a teammate's concept map. The findings revealed that collaborative concept mapping significantly improved the diagnostic result score and shortened diagnosis time, and marginally but significantly increased the fault analysis score. However, under the more complex fault situation triggered by two initiating events, this tool also significantly increased participants’ physical load and frustration level. Future work should focus on how collaborative concept mapping can improve operator performance while causing as little extra workload as possible, as well as explore its effects on experienced operators.
Is There a Symmetry in Disease Control and Quality of Life of Patients with Rheumatoid Arthritis Treated with Biological Therapy?

This study aims to analyze and compare the disease activity control and quality of life of patients with rheumatoid arthritis (RA) who were treated with biological products in real-life settings. We tried to determine whether there is a symmetry in the performance of the biological molecules between each other and with the first Janus kinase (JAK) inhibitor. This is an observational, longitudinal, real-life study performed in the biggest rheumatology clinic during the period 2012–2020 comparing quality of life, cost of therapy, and disease control via different clinical measures. In all three disease activities measurement instruments, we observed an improvement for all biologic and target synthetic medicines. The disease activity score (DAS28) score decreased from 5.06 to 3.01, on average, for all INNs, suggesting that the majority of patients move away from moderate to low disease activity. The clinical disease activity index (CDAI) score decreased from 25.9 to 9.4, also indicating that patients with moderate disease activity reached a low level of activity. Similar results are reflected in the score, which fell from 27.7 to 10.3, again confirming the improvement to a low level of disease activity for patients treated with all INNs. Logically, with the successful control of disease activity, the quality of life (QoL) of the observed patients improved from 0.77 to 0.83 after a one-year follow up, as measured with the EuroQuol 5D-3L (EQ5D). Based on these results, we can consider that the observed biological INNs perform symmetrically in terms of the control of disease activity and improvement in the QoL of the observed patients. Biological therapy improves the disease control and quality of life of suitable patients with RA in real-life settings. All available biological therapies could be used interchangeably.
Evaluation of the self-reported questionnaires used to assess mental health after the January 2015 terrorist attacks in the Paris Region: IMPACTS survey

Introduction Structured clinical interviews are the gold standard for assessing mental health. However limited resources may allow the use of only self-report questionnaires. In the context of emergency, such as terrorist attacks, the performance and thresholds of such tools still unclear. Objectives We investigated the performance of the Posttraumatic stress disorder CheckList Scale (PCL-S) and of the Hospital Anxiety and Depression scale (HADS), both compared to the MINI Interview, among civilians and first responders involved in terrorist attacks. Methods The data came from the IMPACTS survey which was conducted from 6-10 months among civilians (N=190) and first responders (N=232) after the January 2015 terrorist attacks in the Paris Region, France. Sensitivity and specificity of the PCL-S and HADS were estimated by the ROC curve, and the optimal threshold was defined using the Youden index. Results Regarding the PCL-S: for civilians and first responders respectively, the overall AUC was 0.947 and 0.899, and the optimal threshold were 38.5 and 39.5. Regarding the HADS-D: for civilians and first responders respectively, the overall AUC was 0.908 and 0.617 and the optimal thresholds were 7.5 and 1.5. For the HADS-A for civilians and first responders respectively, the overall AUC was 0.823 and 0.717, the optimal threshold were 9.5 and 6.5. Conclusions In the context of a terrorist attack, compared to the MINI, our study underlined satisfactory performance of the PCL-S and the HADS-D in screening for PTSD and depression respectively, while the screening of anxiety using the HADS-A was unsatisfactory. Disclosure No significant relationships.