bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seroprevalence of SARS-CoV-2 anti-nucleocapsid total Ig, anti-RBD IgG antibodies, and infection in Thailand: a cross-sectional survey from October 2022 to January 2023
Authors: Chansaenroj Jira , Suntronwong Nungruthai , Kanokudom Sitthichai , Assawakosri Suvichada , Vichaiwattana Preeyaporn , Klinfueng Sirapa , Wongsrisang Lakana , Thongmee Thanunrat , Aeemjinda Ratchadawan , Khanarat Nongkanok , Srimuan Donchida , Thatsanathorn Thaksaporn , Yorsaeng Ritthideach , Katanyutanon Apirat , Thanasopon Wichai , Bhunyakitikorn Wichan , Sonthichai Chaninan , Angsuwatcharakorn Piyada , Withaksabut Withak , Wanlapakorn Nasamon , Sudhinaraset Natthinee , Poovorawan Yong 
Published: September 2023

AbstractSeroprevalence studies on SARS-CoV-2 are essential for estimating actual prevalence rates of infection and vaccination in communities. This study evaluated infection rates based on total anti-nucleocapsid immunoglobulin (N) and/or infection history. We determined the seroprevalence of anti-receptor binding domain (RBD) antibodies across age groups. A cross-sectional study was conducted in Chonburi province, Thailand, between October 2022 and January 2023. Participants included newborns to adults aged up to 80 years. All serum samples were tested for anti-N total Ig and anti-RBD IgG. The interviewer-administered questionnaires queried information on infection history and vaccination records. Of 1459 participants enrolled from the Chonburi population, ~ 72.4% were infected. The number of infections was higher in children aged < 5 years, with evidence of SARS-CoV-2 infection decreasing significantly with increasing age. There were no significant differences based on sex or occupation. Overall, ~ 97.4% of participants had an immune response against SARS-CoV-2. The anti-RBD IgG seroprevalence rate was lower in younger vaccinated individuals and was slightly increased to 100% seropositivity at ages > 60 years. Our findings will help predict the exact number of infections and the seroprevalence of SARS-CoV-2 in the Thai population. Furthermore, this information is essential for public health decision-making and the development of vaccination strategies.
A facile, rapid procedure for Knoevenagel condensation reaction catalyzed by efficient amino-bifunctional frameworks under mild conditions
Authors: Saghian Mahdie , Dehghanpour Saeed , bayatani Zahra 
Published: September 2023

AbstractA series of bifunctional hexagonal MOFs have been successfully constructed by the introduction of various amine functional groups within the unsaturated Cu-based MOF, HKUST, to access amino-modified frameworks. The prepared compounds are cost-effective and display high chemical and thermal stability. They were effectually exploited as efficacious and superb heterogeneous catalysts in rapid and facile Knoevenagel condensation reactions for a variety of substrates containing different electron-donating and electron-withdrawing substituents with very high conversion, good reusability under mild conditions, and very short reaction time. The contaminant presence of Lewis acid and basic sites resulted in efficient condensation reactions by the prepared catalysts.
Exploring GWAS and genomic prediction to improve Septoria tritici blotch resistance in wheat
Authors: Zakieh Mustafa , Alemu Admas , Henriksson Tina , Pareek Nidhi , Singh Pawan K. , Chawade Aakash 
Published: September 2023

AbstractSeptoria tritici blotch (STB) is a destructive foliar diseases threatening wheat grain yield. Wheat breeding for STB disease resistance has been identified as the most sustainable and environment-friendly approach. In this work, a panel of 316 winter wheat breeding lines from a commercial breeding program were evaluated for STB resistance at the seedling stage under controlled conditions followed by genome-wide association study (GWAS) and genomic prediction (GP). The study revealed a significant genotypic variation for STB seedling resistance, while disease severity scores exhibited a normal frequency distribution. Moreover, we calculated a broad-sense heritability of 0.62 for the trait. Nine single- and multi-locus GWAS models identified 24 marker-trait associations grouped into 20 quantitative trait loci (QTLs) for STB seedling-stage resistance. The seven QTLs located on chromosomes 1B, 2A, 2B, 5B (two), 7A, and 7D are reported for the first time and could potentially be novel. The GP cross-validation analysis in the RR-BLUP model estimated the genomic-estimated breeding values (GEBVs) of STB resistance with a prediction accuracy of 0.49. Meanwhile, the GWAS assisted wRR-BLUP model improved the accuracy to 0.58. The identified QTLs can be used for marker-assisted backcrossing against STB in winter wheat. Moreover, the higher prediction accuracy recorded from the GWAS-assisted GP analysis implies its power to successfully select superior candidate lines based on their GEBVs for STB resistance.
Effect of organic loading rates on the performance of membrane bioreactor for wastewater treatment behaviours, fouling, and economic cost
Authors: Al-Sayed Aly , Hassan Gamal K. , Al-Shemy Mona T. , El-gohary Fatma A. 
Published: September 2023

AbstractAlthough submerged membrane bioreactor (MBR) are widely used in treating municipal wastewater and recovery of potential resources, membrane operational parameters and membrane fouling control remain debated issues. In this study, the treatment of municipal wastewater by MBR at high-biomass sludge (MLSS (g/L) ranging from 5.4 g/L to 16.1 g/L) was assessed at an organic loading rates (OLRs) ranging from 0.86 to 3.7 kg COD/m3d. The correlation between trans-membrane pressure and total fouling resistance was thoroughly investigated in this study. According to the findings, greater OLRs of 0.86 to 3.7 kg COD/m3d caused a decrease in COD, BOD, and NH4–N removal efficiency, and higher OLRs of 3.7 kg COD/m3d resulted in a higher increase in total fouling resistance (Rt). The economic study of using the MBR system proved that for a designed flow rate of 20 m3/d, the payback period from using the treated wastewater will be 7.98 years, which confirms the economic benefits of using this MBR for treating municipal wastewater. In general, understanding the challenges facing the efficiency of MBR would improve its performance and, consequently, the sustainability of wastewater reclamation.
Design and control of a self-adjusting outdoor landscape wall
Authors: Cui Ru 
Published: September 2023

AbstractThis paper designs an outdoor landscape wall, which is equipped with an electrical motor, a sunlight intensity sensor and a rain sensor. The plants in the landscape wall will be rotated indoors when the weather is bad. To the contrary, based on signals from the sunlight intensity sensor, the plants can be rotated outdoors to get suitable sunlight. The dynamics of the electrical motor current control loop is much higher than the requirement of the position control loop. The whole control system can be divided into two subsystems: out-loop position control system and inner-loop current control system. An adaptive control strategy is proposed for out-loop position control. A nonlinear controller based on feedback linearization is developed for inner-loop current control. The two subsystems are synthesized with a first-order filter. Simulations are conducted to verify the proposed control strategy. The simulation results demonstrate that high-performance position tracking can be achieved under parameter uncertainty and disturbance.
Estimation of cumulative amplitude distributions of miniature postsynaptic currents allows characterising their multimodality, quantal size and variability
Authors: Gordleeva Susanna , Dembitskaya Yulia , Kazantsev Victor , Postnikov Eugene B. 
Published: September 2023

AbstractA miniature postsynaptic current (mPSC) is a small, rare, and highly variable spontaneous synaptic event that is generally caused by the spontaneous release of single vesicles. The amplitude and variability of mPSCs are key measures of the postsynaptic processes and are taken as the main characteristics of an elementary unit (quantal size) in traditional quantal analysis of synaptic transmission. Due to different sources of biological and measurement noise, recordings of mPSCs exhibit high trial-to-trial heterogeneity, and experimental measurements of mPSCs are usually noisy and scarce, making their analysis demanding. Here, we present a sequential procedure for precise analysis of mPSC amplitude distributions for the range of small currents. To illustrate the developed approach, we chose previously obtained experimental data on the effect of the extracellular matrix on synaptic plasticity. The proposed statistical technique allowed us to identify previously unnoticed additional modality in the mPSC amplitude distributions, indicating the formation of new immature synapses upon ECM attenuation. We show that our approach can reliably detect multimodality in the distributions of mPSC amplitude, allowing for accurate determination of the size and variability of the quantal synaptic response. Thus, the proposed method can significantly expand the informativeness of both existing and newly obtained experimental data. We also demonstrated that mPSC amplitudes around the threshold of microcurrent excitation follow the Gumbel distribution rather than the binomial statistics traditionally used for a wide range of currents, either for a single synapse or when taking into consideration small influences of the adjacent synapses. Such behaviour is argued to originate from the theory of extreme processes. Specifically, recorded mPSCs represent instant random current fluctuations, among which there are relatively larger spikes (extreme events). They required more level of coherence that can be provided by different mechanisms of network or system level activation including neuron circuit signalling and extrasynaptic processes.
Monitoring the abundance of flying insects and atmospheric conditions during a 9-month campaign using an entomological optical sensor
Authors: Saha Topu , Genoud Adrien P. , Williams Gregory M. , Thomas Benjamin P. 
Published: September 2023

AbstractMonitoring the dynamics of insect populations is key to assessing the impact of human activities on insect populations. However, traditional methodologies relying on physical traps have inherent limitations in accurately monitoring insect abundance. Here, we present findings from a 9-month campaign conducted in New Jersey, USA, utilizing a near-infrared optical sensor known as eBoss. From April to December 2022, the eBoss derived the aerial density (insect/m3) and biomass density (mg/m3) with a 1-min resolution from a total of 302,093 insect observations. The data collected were analyzed in relation to air temperature, relative humidity, and wind speed. The results revealed that the abundance of flying insects exhibited an initial increase from April to June, reaching a peak of 0.094 insect/m3 and 1.34 mg/m3, followed by a subsequent decline towards the end of the year. Our investigation showed a surge in insect abundance above 12.5 °C, with particularly high levels observed between 19 and 31 °C. The impact of relative humidity and wind speed on insect populations was also explored. Overall, this campaign demonstrated the efficacy of photonic sensors in gathering novel and extensive data for the field of entomology, paving the way for improved understanding and management of insect populations.
Natural scene reconstruction from fMRI signals using generative latent diffusion
Authors: Ozcelik Furkan , VanRullen Rufin 
Published: September 2023

AbstractIn neural decoding research, one of the most intriguing topics is the reconstruction of perceived natural images based on fMRI signals. Previous studies have succeeded in re-creating different aspects of the visuals, such as low-level properties (shape, texture, layout) or high-level features (category of objects, descriptive semantics of scenes) but have typically failed to reconstruct these properties together for complex scene images. Generative AI has recently made a leap forward with latent diffusion models capable of generating high-complexity images. Here, we investigate how to take advantage of this innovative technology for brain decoding. We present a two-stage scene reconstruction framework called “Brain-Diffuser”. In the first stage, starting from fMRI signals, we reconstruct images that capture low-level properties and overall layout using a VDVAE (Very Deep Variational Autoencoder) model. In the second stage, we use the image-to-image framework of a latent diffusion model (Versatile Diffusion) conditioned on predicted multimodal (text and visual) features, to generate final reconstructed images. On the publicly available Natural Scenes Dataset benchmark, our method outperforms previous models both qualitatively and quantitatively. When applied to synthetic fMRI patterns generated from individual ROI (region-of-interest) masks, our trained model creates compelling “ROI-optimal” scenes consistent with neuroscientific knowledge. Thus, the proposed methodology can have an impact on both applied (e.g. brain–computer interface) and fundamental neuroscience.
Rise of post-pandemic resilience across the distrust ecosystem
Authors: Illari Lucia , Restrepo Nicholas J. , Johnson Neil F. 
Published: September 2023

AbstractWhy does online distrust (e.g., of medical expertise) continue to grow despite numerous mitigation efforts? We analyzed changing discourse within a Facebook ecosystem of approximately 100 million users who were focused pre-pandemic on vaccine (dis)trust. Post-pandemic, their discourse interconnected multiple non-vaccine topics and geographic scales within and across communities. This interconnection confers a unique, system-level (i.e., at the scale of the full network) resistance to mitigations targeting isolated topics or geographic scales—an approach many schemes take due to constrained funding. For example, focusing on local health issues but not national elections. Backed by numerical simulations, we propose counterintuitive solutions for more effective, scalable mitigation: utilize “glocal” messaging by blending (1) strategic topic combinations (e.g., messaging about specific diseases with climate change) and (2) geographic scales (e.g., combining local and national focuses).
Early acquired resistance to EGFR-TKIs in lung adenocarcinomas before radiographic advanced identified by CT radiomic delta model based on two central studies
Authors: Li Xiumei , Zhang Chengxiu , Li Tingting , Lin Xiuqiang , Wu Dongmei , Yang Guang , Cao Dairong 
Published: September 2023

AbstractEarly acquired resistance (EAR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in lung adenocarcinomas before radiographic advance cannot be perceived by the naked eye. This study aimed to discover and validate a CT radiomic model to precisely identify the EAR. Training cohort (n = 67) and internal test cohort (n = 29) were from the First Affiliated Hospital of Fujian Medical University, and external test cohort (n = 29) was from the Second Affiliated Hospital of Xiamen Medical College. Follow-up CT images at three different times of each patient were collected: (1) baseline images before EGFR-TKIs therapy; (2) first follow-up images after EGFR-TKIs therapy (FFT); (3) EAR images, which were the last follow-up images before radiographic advance. The features extracted from FFT and EAR were used to construct the classic radiomic model. The delta features which were calculated by subtracting the baseline from either FFT or EAR were used to construct the delta radiomic model. The classic radiomic model achieved AUC 0.682 and 0.641 in training and internal test cohorts, respectively. The delta radiomic model achieved AUC 0.730 and 0.704 in training and internal test cohorts, respectively. Over the external test cohort, the delta radiomic model achieved AUC 0.661. The decision curve analysis showed that when threshold of the probability of the EAR to the EGFR-TKIs was between 0.3 and 0.82, the proposed model was more benefit than treating all patients. Based on two central studies, the delta radiomic model derived from the follow-up non-enhanced CT images can help clinicians to identify the EAR to EGFR-TKIs in lung adenocarcinomas before radiographic advance and optimize clinical outcomes.
Assessing the roles of shape prototypicality and sexual dimorphism in ratings of the trustworthiness of faces
Authors: Leger Kathlyne , Dong Junzhi , DeBruine Lisa M. , Jones Benedict C. , Shiramizu Victor K. M. 
Published: September 2023

AbstractPerceptions of the trustworthiness of faces predict important social outcomes, including economic exchange and criminal sentencing decisions. However, the specific facial characteristics that drive trustworthiness perceptions remain poorly understood. Here we investigated this issue by exploring possible relationships between ratings of the trustworthiness of face images and objective assessments of two aspects of face shape that researchers have previously argued are important for perceptions of trustworthiness: distinctiveness and sexual dimorphism. Here we report that faces with more distinctive shapes are rated as less trustworthy, but that sexual dimorphism of face shape is not significantly correlated with trustworthiness ratings. These results suggest that distinctiveness of face shape plays a more important role in trustworthiness perceptions than does sexual dimorphism and suggest that perceptions of trustworthiness may stem, at least in part, from the ‘anomalous-is-bad’ stereotype.
Genetic diversity and ancestry of the Khmuic-speaking ethnic groups in Thailand: a genome-wide perspective
Authors: Kampuansai Jatupol , Wongkomonched Rattanasak , Kutanan Wibhu , Srikummool Metawee , Seetaraso Tanapon , Sathupak Suwapat , Thongkumkoon Patcharawadee , Sangphukieo Apiwat 
Published: September 2023

AbstractThe Khmuic-speaking populations are believed to be the descendants of one of the earliest groups to settle in Mainland Southeast Asia. In Thailand, there are two agricultural Khmuic-speaking ethnic groups, the Khamu and Lua (Htin). These peoples primarily reside in scattered locations along the mountainous Thailand–Laos border in Nan province. In this study, we conducted genome-wide SNP analysis on 81 individuals from three Khamu and two Lua villages in northern Thailand. Our findings revealed that both the Khamu and Lua groups possess genetic structures that are distinct from other ethnicities in Southeast Asia, indicating a unique history of migration and settlement. Within the Khmuic group, the Khamu populations living in different locations exhibited similar genetic structures and displayed genetic affinities only with some hill-tribes and Tai-Kadai (Kra-Dai)-speaking groups in Thailand, suggesting potential intermixing or cultural exchange. Furthermore, the Lua people displayed a distinctive population structure, which could be attributed to the founder effect and endogamous marriage practices. Additionally, we discovered a relationship between the Khmuic-speaking populations in Thailand and a Neolithic ancient sample obtained from the Tham Pha Ling archaeological site in Laos. This study provides new insight into genetic substructure within the Khmuic-speaking people and their potential relationship to the indigenous inhabitants of Mainland Southeast Asia.
Engaging a national-scale cohort of smart thermometer users in participatory surveillance
Authors: Tseng Yi-Ju , Olson Karen L. , Bloch Danielle , Mandl Kenneth D. 
Published: September 2023

AbstractParticipatory surveillance systems crowdsource individual reports to rapidly assess population health phenomena. The value of these systems increases when more people join and persistently contribute. We examine the level of and factors associated with engagement in participatory surveillance among a retrospective, national-scale cohort of individuals using smartphone-connected thermometers with a companion app that allows them to report demographic and symptom information. Between January 1, 2020 and October 29, 2022, 1,325,845 participants took 20,617,435 temperature readings, yielding 3,529,377 episodes of consecutive readings. There were 1,735,805 (49.2%) episodes with self-reported symptoms (including reports of no symptoms). Compared to before the pandemic, participants were more likely to report their symptoms during pandemic waves, especially after the winter wave began (September 13, 2020) (OR across pandemic periods range from 3.0 to 4.0). Further, symptoms were more likely to be reported during febrile episodes (OR = 2.6, 95% CI = 2.6–2.6), and for new participants, during their first episode (OR = 2.4, 95% CI = 2.4–2.5). Compared with participants aged 50–65 years old, participants over 65 years were less likely to report their symptoms (OR = 0.3, 95% CI = 0.3–0.3). Participants in a household with both adults and children (OR = 1.6 [1.6–1.7]) were more likely to report symptoms. We find that the use of smart thermometers with companion apps facilitates the collection of data on a large, national scale, and provides real time insight into transmissible disease phenomena. Nearly half of individuals using these devices are willing to report their symptoms after taking their temperature, although participation varies among individuals and over pandemic stages.
Weighted spin torque nano-oscillator system for neuromorphic computing
Authors: Böhnert T. , Rezaeiyan Y. , Claro M. S. , Benetti L. , Jenkins A. S. , Farkhani H. , Moradi F. , Ferreira R. 
Published: September 2023

AbstractNeuromorphic computing is a promising strategy to overcome fundamental limitations, such as enormous power consumption, by massive parallel data processing, similar to the brain. Here we demonstrate a proof-of-principle implementation of the weighted spin torque nano-oscillator (WSTNO) as a programmable building block for the next-generation neuromorphic computing systems (NCS). The WSTNO is a spintronic circuit composed of two spintronic devices made of magnetic tunnel junctions (MTJs): non-volatile magnetic memories acting as synapses and non-linear spin torque nano-oscillator (STNO) acting as a neuron. The non-linear output based on the weighted sum of the inputs is demonstrated using three MTJs. The STNO shows an output power above 3 µW and frequencies of 240 MHz. Both MTJ types are fabricated from a multifunctional MTJ stack in a single fabrication process, which reduces the footprint, is compatible with monolithic integration on top of CMOS technology and paves ways to fabricate more complex neuromorphic computing systems.
Contextual cueing of visual search reflects the acquisition of an optimal, one-for-all oculomotor scanning strategy
Authors: Seitz Werner , Zinchenko Artyom , Müller Hermann J. , Geyer Thomas 
Published: September 2023

AbstractVisual search improves when a target is encountered repeatedly at a fixed location within a stable distractor arrangement (spatial context), compared to non-repeated contexts. The standard account attributes this contextual-cueing effect to the acquisition of display-specific long-term memories, which, when activated by the current display, cue attention to the target location. Here we present an alternative, procedural-optimization account, according to which contextual facilitation arises from the acquisition of generic oculomotor scanning strategies, optimized with respect to the entire set of displays, with frequently searched displays accruing greater weight in the optimization process. To decide between these alternatives, we examined measures of the similarity, across time-on-task, of the spatio-temporal sequences of fixations through repeated and non-repeated displays. We found scanpath similarity to increase generally with learning, but more for repeated versus non-repeated displays. This pattern contradicts display-specific guidance, but supports one-for-all scanpath optimization.