bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 infection segmentation using hybrid deep learning and image processing techniques
Authors: Antar Samar , Abd El-Sattar Hussein Karam Hussein , Abdel-Rahman Mohammad H. , F. M. Ghaleb Fayed 
Published: December 2023

AbstractThe coronavirus disease 2019 (COVID-19) epidemic has become a worldwide problem that continues to affect people’s lives daily, and the early diagnosis of COVID-19 has a critical importance on the treatment of infected patients for medical and healthcare organizations. To detect COVID-19 infections, medical imaging techniques, including computed tomography (CT) scan images and X-ray images, are considered some of the helpful medical tests that healthcare providers carry out. However, in addition to the difficulty of segmenting contaminated areas from CT scan images, these approaches also offer limited accuracy for identifying the virus. Accordingly, this paper addresses the effectiveness of using deep learning (DL) and image processing techniques, which serve to expand the dataset without the need for any augmentation strategies, and it also presents a novel approach for detecting COVID-19 virus infections in lung images, particularly the infection prediction issue. In our proposed method, to reveal the infection, the input images are first preprocessed using a threshold then resized to 128 × 128. After that, a density heat map tool is used for coloring the resized lung images. The three channels (red, green, and blue) are then separated from the colored image and are further preprocessed through image inverse and histogram equalization, and are subsequently fed, in independent directions, into three separate U-Nets with the same architecture for segmentation. Finally, the segmentation results are combined and run through a convolution layer one by one to get the detection. Several evaluation metrics using the CT scan dataset were used to measure the performance of the proposed approach in comparison with other state-of-the-art techniques in terms of accuracy, sensitivity, precision, and the dice coefficient. The experimental results of the proposed approach reached 99.71%, 0.83, 0.87, and 0.85, respectively. These results show that coloring the CT scan images dataset and then dividing each image into its RGB image channels can enhance the COVID-19 detection, and it also increases the U-Net power in the segmentation when merging the channel segmentation results. In comparison to other existing segmentation techniques employing bigger 512 × 512 images, this study is one of the few that can rapidly and correctly detect the COVID-19 virus with high accuracy on smaller 128 × 128 images using the metrics of accuracy, sensitivity, precision, and dice coefficient.
Orchestration of saccadic eye-movements by brain rhythms in macaque Frontal Eye Field
Authors: Shaverdi Yeganeh , Setarehdan Seyed Kamaledin , Treue Stefan , Esghaei Moein 
Published: December 2023

AbstractVisual perception has been suggested to operate on temporal ‘chunks’ of sensory input, rather than on a continuous stream of visual information. Saccadic eye movements impose a natural rhythm on the sensory input, as periods of steady fixation between these rapid eye movements provide distinct temporal segments of information. Ideally, the timing of saccades should be precisely locked to the brain’s rhythms of information processing. Here, we investigated such locking of saccades to rhythmic neural activity in rhesus monkeys performing a visual foraging task. We found that saccades are phase-locked to local field potential oscillations (especially, 9–22 Hz) in the Frontal Eye Field, with the phase of oscillations predictive of the saccade onset as early as 100 ms prior to these movements. Our data also indicate a functional role of this phase-locking in determining the direction of saccades. These findings show a tight—and likely important—link between oscillatory brain activity and rhythmic behavior that imposes a rhythmic temporal structure on sensory input, such as saccadic eye movements.
Biological and mechanical influence of three-dimensional microenvironment formed in microwell on multicellular spheroids composed of heterogeneous hair follicle stem cells
Authors: Lee Seungjin , Kim Nackhyoung , Kim Sung-Hwan , Um Soo-Jong , Park Joong Yull 
Published: December 2023

AbstractHair loss caused by malfunction of the hair follicle stem cells (HFSCs) and physical damage to the skin is difficult to recover from naturally. To overcome these obstacles to hair follicle (HF) regeneration, it is essential to understand the three-dimensional (3D) microenvironment and interactions of various cells within the HFs. Therefore, 3D cell culture technology has been used in HF regeneration research; specifically, multicellular spheroids have been generally adapted to mimic the 3D volumetric structure of the HF. In this study, we culture HF-derived cells, which are mainly composed of HFSCs, in the form of 3D spheroids using a microwell array and discuss the effects of the 3D cellular environment on HF morphogenesis by expression measurements of Sonic hedgehog signaling and stem cell markers in the HF spheroids. Additionally, the influences of microwell depth on HF spheroid formation and biological conditions were investigated. The biomolecular diffusion and convective flow in the microwell were predicted using computational fluid dynamics, which allows analysis of the physical stimulations occurring on the spheroid at the micro-scale. Although a simple experimental method using the microwell array was adopted in this study, the results provide fundamental insights into the physiological phenomena of HFs in the 3D microenvironment, and the numerical analysis is expected to shed light on the investigation of the geometric parameters of the microwell system.
The influence of upward social comparison on retail trading behaviour
Authors: Andraszewicz Sandra , Kaszás Dániel , Zeisberger Stefan , Hölscher Christoph 
Published: December 2023

AbstractOnline investing is often facilitated by digital platforms, where the information of peer top performers can be widely accessible and distributed. However, the influence of such information on retail investors’ psychology, their trading behaviour and potential risks they may be prone to is poorly understood. We investigate the impact of upward social comparison on risk-taking, trading activity and investor satisfaction using a tailored experiment with 807 experienced retail investors trading on a dynamically evolving simulated stock market, designed to systematically measure various facets of trading activity. We find that investors presented with an upward social comparison take more risk and trade more actively, and they report significantly lower satisfaction with their own performance. Our findings demonstrate the pitfalls of modern investment platforms with peer information and social trading. The broad implications of this study also provide guidelines for improving retail investor satisfaction and protection.
Strain-based method for fatigue failure prediction of additively manufactured lattice structures
Authors: Coluccia Antonio , De Pasquale Giorgio 
Published: December 2023

AbstractLattice structures find application in numerous technological domains, including aerospace and automotive industries for structural components, biomedical sector implants, and heat exchangers. In many instances, especially those pertaining to structural applications, fatigue resistance stands as a critical and stringent requirement. The objective of this paper is to advance the analysis of fatigue failure in additively manufactured lattice structures by introducing a predictive fatigue failure model based on the finite element (FE) method and experimentally validating the results. The model utilizes linear homogenization to reduce computational effort in FE simulations. By employing a strain-based parameter, the most critical lattice cell is identified, enabling the prediction of fatigue crack nucleation locations. The Crossland multiaxial fatigue failure criterion is employed to assess the equivalent stress, furnishing the fatigue limit threshold essential for predicting component failure. Inconel 625 specimens are manufactured via the laser-based powder bed fusion of metals additive manufacturing process. In order to validate the model, cantilevers comprising octa-truss lattice cells in both uniform and graded configurations undergo experimental testing subjected to bending loads within the high cycle fatigue regime. The proposed methodology effectively forecasts the location of failure in seventeen out of eighteen samples, establishing itself as a valuable tool for lattice fatigue analysis. Failure consistently manifests in sections of uniform and graded lattice structures characterized by the maximum strain tensor norm. The estimated maximum force required to prevent fatigue failure in the samples is 20 N, based on the computed Crossland equivalent stress.
Automating licking bias correction in a two-choice delayed match-to-sample task to accelerate learning
Authors: Do Jongrok , Jung Min Whan , Lee Doyun 
Published: December 2023

AbstractAnimals often display choice bias, or a preference for one option over the others, which can significantly impede learning new tasks. Delayed match-to-sample (DMS) tasks with two-alternative choices of lickports on the left and right have been widely used to study sensory processing, working memory, and associative memory in head-fixed animals. However, extensive training time, primarily due to the animals' biased licking responses, limits their practical utility. Here, we present the implementation of an automated side bias correction system in an olfactory DMS task, where the lickport positions and the ratio of left- and right-rewarded trials are dynamically adjusted to counterbalance mouse’s biased licking responses during training. The correction algorithm moves the preferred lickport farther away from the mouse’s mouth and the non-preferred lickport closer, while also increasing the proportion of non-preferred side trials when biased licking occurs. We found that adjusting lickport distances and the proportions of left- versus right-rewarded trials effectively reduces the mouse’s side bias. Further analyses reveal that these adjustments also correlate with subsequent improvements in behavioral performance. Our findings suggest that the automated side bias correction system is a valuable tool for enhancing the applicability of behavioral tasks involving two-alternative lickport choices.
Highly efficient and selective integrated directional couplers for multigas sensing applications
Authors: Thottoli Ajmal , Biagi Gabriele , Vorobev Artem S. , Giglio Marilena , Magno Giovanni , O’Faolain Liam , Grande Marco 
Published: December 2023

AbstractThe design and fabrication of a compact, low-loss, broadband directional coupler (DC) based duplexer operating in the near-infrared (NIR) region are demonstrated. The duplexer exhibits high selectivity and coupling efficiency (CE), for target wavelengths of 1530 nm and 1653.7 nm, making it applicable in systems for the multi-gas detection of ammonia and methane. The measured CE for the duplexer is 73% and 76% at 1530 nm and 1653.7 nm respectively. These results demonstrate the effectiveness of the duplexer as a broadband and scalable power source for highly sensitive sensing techniques, like quartz-enhanced photoacoustic spectroscopy (QEPAS). Its compact size and low-loss characteristics make it highly portable and well-suited for drone-based multi-gas detection applications.
Proximate composition, lipid and elemental profiling of eight varieties of avocado (Persea americana)
Authors: Nasri Chaimae , Halabi Yasmina , Hajib Ahmed , Choukri Hasnae , Harhar Hicham , Lee Learn-Han , Mani Vasudevan , Ming Long Chiau , Goh Khang Wen , Bouyahya Abdelhakim , Tabyaoui Mohamed 
Published: December 2023

AbstractEight Moroccan avocado varieties were analyzed for their nutritional composition and physicochemical properties. The nutritional contents of the sample were determined through the evaluation of the moisture, oil, ash, protein, and carbohydrate contents, and energy value calculation. Additionally, macroelements (Ca, Mg, and Na) and microelements (Fe, Zn, Cu, and Mn) were determined in the mineral profile. Oils were examined also for their fatty acid, phytosterol, and tocopherol profiles. As a result of the study, the avocado presents significant differences between the eight studied varieties (p < 0.05), with regard to moisture content (57.88 g/100 g to 84.71 g/100 g), oil content (8.41 g/100 g to 57.88 g/100 g), ash (0.57 g/100 g to 1.37 g/100 g), protein content (5.7 g/100 g to 8.61 g/100 g), carbohydrate content (5.63 g/100 g to 14.61 g/100 g), and energy value (99.9 kcal/100 g to 316.8 kcal/100 g). Sodium (5783.01 mg/kg to 12,056.19 mg/kg) was the predominant macro-element in all varieties, followed by calcium (295.95 mg/kg to 531.67 mg/kg), and magnesium (246.29 mg/kg to 339.84 mg/kg). Copper (85.92 mg/kg to 112. 31 mg/kg) was the main microelement in all varieties, followed by iron (8.5 mg/kg to 20.32 mg/kg), and manganese (7.3 mg/kg to 18.45 mg/kg), while zinc (1.72 mg/kg to 5.66 mg/kg) was detected in small amounts. In addition, significant difference was observed in lipid profiles, according to the eight studied varieties (p < 0.05). Avocado oils were mainly composed of monounsaturated fatty acids (76.89 g/100 g to 84.7 g/100 g), with oleic acid (50.38 g/100 g to 71.49 g/100 g) standing out as particularly characteristic, while β-sitosterol (l2365.58 mg/kg to 4559.27 mg/kg), and α-tocopherol (30.08 mg/kg to 182.94 mg/kg) were among its major phytosterols and tocopherols. All avocado varieties represented in this study can be consumed as a fruit as an excellent source of energy, minerals, fatty acids, phytosterols, and tocopherols. The regular consumption of this fruit provides the body with several essential nutrients.
HLA-B*46:01:01:01 and HLA-DRB1*09:01:02:01 are associated with anti-rHuEPO-induced pure red cell aplasia
Authors: Suttichet Thitima Benjachat , Chamnanphon Monpat , Pongpanich Monnat , Chokyakorn Sarun , Kupatawintu Pawinee , Srichomthong Chalurmpon , Chetruengchai Wanna , Chuntakaruk Hathaichanok , Rungrotmongkol Thanyada , Chariyavilaskul Pajaree , Shotelersuk Vorasuk , Praditpornsilpa Kearkiat 
Published: December 2023

AbstractTreatment of anemia in patients with chronic kidney disease (CKD) with recombinant human erythropoietin (rHuEPO) can be disrupted by a severe complication, anti-rHuEPO-induced pure red cell aplasia (PRCA). Specific HLA genotypes may have played a role in the high incidence of PRCA in Thai patients (1.7/1,000 patient years vs. 0.03/10,000 patient years in Caucasians). We conducted a case–control study in 157 CKD patients with anti-rHuEPO-induced PRCA and 56 controls. The HLA typing was determined by sequencing using a highly accurate multiplex single-molecule, real-time, long-read sequencing platform. Four analytical models were deployed: Model 1 (additive: accounts for the number of alleles), Model 2 (dominant: accounts for only the presence or absence of alleles), Model 3 (adjusted additive with rHuEPO types) and Model 4 (adjusted dominant with rHuEPO types). HLA-B*46:01:01:01 and DRB1*09:01:02:01 were found to be independent risk markers for anti-rHuEPO-induced PRCA in all models [OR (95%CI), p-values for B*46:01:01:01: 4.58 (1.55–13.51), 0.006; 4.63 (1.56–13.75), 0.006; 5.72 (1.67–19.67), 0.006; and 5.81 (1.68–20.09), 0.005; for DRB1*09:01:02:01: 3.99 (1.28–12.49), 0.017, 4.50 (1.32–15.40), 0.016, 3.42 (1.09–10.74), 0.035, and 3.75 (1.08–13.07), 0.038, in Models 1–4, respectively. HLA-B*46:01:01:01 and DRB1*09:01:02:01 are susceptible alleles for anti-rHuEPO-induced PRCA. These findings support the role of HLA genotyping in helping to monitor patients receiving rHuEPO treatment.
HOXA10 promotes Gdf5 expression in articular chondrocytes
Authors: Murakami Tomohiko , Ruengsinpinya Lerdluck , Takahata Yoshifumi , Nakaminami Yuri , Hata Kenji , Nishimura Riko 
Published: December 2023

AbstractGrowth differentiation factor 5 (GDF5), a BMP family member, is highly expressed in the surface layer of articular cartilage. The GDF5 gene is a key risk locus for osteoarthritis and Gdf5-deficient mice show abnormal joint development, indicating that GDF5 is essential in joint development and homeostasis. In this study, we aimed to identify transcription factors involved in Gdf5 expression by performing two-step screening. We first performed microarray analyses to find transcription factors specifically and highly expressed in the superficial zone (SFZ) cells of articular cartilage, and isolated 11 transcription factors highly expressed in SFZ cells but not in costal chondrocytes. To further proceed with the identification, we generated Gdf5-HiBiT knock-in (Gdf5-HiBiT KI) mice, by which we can easily and reproducibly monitor Gdf5 expression, using CRISPR/Cas9 genome editing. Among the 11 transcription factors, Hoxa10 clearly upregulated HiBiT activity in the SFZ cells isolated from Gdf5-HiBiT KI mice. Hoxa10 overexpression increased Gdf5 expression while Hoxa10 knockdown decreased it in the SFZ cells. Moreover, ChIP and promoter assays proved the direct regulation of Gdf5 expression by HOXA10. Thus, our results indicate the important role played by HOXA10 in Gdf5 regulation and the usefulness of Gdf5-HiBiT KI mice for monitoring Gdf5 expression.
An intercomparison of weather normalization of PM2.5 concentration using traditional statistical methods, machine learning, and chemistry transport models
Authors: Zheng Huang , Kong Shaofei , Zhai Shixian , Sun Xiaoyun , Cheng Yi , Yao Liquan , Song Congbo , Zheng Zhonghua , Shi Zongbo , Harrison Roy M. 
Published: December 2023

AbstractTraditional statistical methods (TSM) and machine learning (ML) methods have been widely used to separate the effects of emissions and meteorology on air pollutant concentrations, while their performance compared to the chemistry transport model has been less fully investigated. Using the Community Multiscale Air Quality Model (CMAQ) as a reference, a series of experiments was conducted to comprehensively investigate the performance of TSM (e.g., multiple linear regression and Kolmogorov–Zurbenko filter) and ML (e.g., random forest and extreme gradient boosting) approaches in quantifying the effects of emissions and meteorology on the trends of fine particulate matter (PM2.5) during 2013−2017. Model performance evaluation metrics suggested that the TSM and ML methods can explain the variations of PM2.5 with the highest performance from ML. The trends of PM2.5 showed insignificant differences (p > 0.05) for both the emission-related ($${{\rm{PM}}}_{2.5}^{{\rm{EMI}}}$$

PM

2.5

EMI

) and meteorology-related components between TSM, ML, and CMAQ modeling results. $${{\rm{PM}}}_{2.5}^{{\rm{EMI}}}$$

PM

2.5

EMI

estimated from ML showed the least difference to that from CMAQ. Considering the medium computing resources and low model biases, the ML method is recommended for weather normalization of PM2.5. Sensitivity analysis further suggested that the ML model with optimized hyperparameters and the exclusion of temporal variables in weather normalization can further produce reasonable results in emission-related trends of PM2.5.
Polarization superposition of room-temperature polariton condensation
Authors: Moriyama Yuta , Inukai Takaya , Hirao Tsukasa , Ueda Yusuke , Takahashi Shun , Yamashita Kenichi 
Published: December 2023

AbstractA methodology for forming a qubit state is essential for quantum applications of room temperature polaritons. While polarization degree of freedom is expected as a possible means for this purpose, the coupling of linearly polarized polariton condensed states has been still a challenging issue. In this study, we show a polarization superposition of a polariton condensed states in an all-inorganic perovskite microcavity at room temperature. We achieved the energy resonance of the two orthogonally polarized polariton modes with the same number of antinodes by exploiting the blue shift of the polariton condensed state. The polarization coupling between the condensed states results in a polarization switching in the polariton lasing emission. The orthorhombic crystal structure of the perovskite active layer and/or a slight off-axis orientation of the perovskite crystal axis from the normal direction of microcavity plane enables the interaction between the two orthogonally polarized states. These observations suggest the use of polariton polarization states as a promising room temperature quantum technology.
Machine learning identifies risk factors associated with long-term sick leave following COVID-19 in Danish population
Authors: Jakobsen Kim Daniel , O’Regan Elisabeth , Svalgaard Ingrid Bech , Hviid Anders 
Published: December 2023

Abstract
Background
Post COVID-19 condition (PCC) can lead to considerable morbidity, including prolonged sick-leave. Identifying risk groups is important for informing interventions. We investigated heterogeneity in the effect of SARS-CoV-2 infection on long-term sick-leave and identified subgroups at higher risk.

Methods
We conducted a hybrid survey and register-based retrospective cohort study of Danish residents who tested positive for SARS-CoV-2 between November 2020 and February 2021 and a control group who tested negative, with no known history of SARS-CoV-2. We estimated the causal risk difference (RD) of long-term sick-leave due to PCC and used the causal forest method to identify individual-level heterogeneity in the effect of infection on sick-leave. Sick-leave was defined as >4 weeks of full-time sick-leave from 4 weeks to 9 months after the test.

Results
Here, in a cohort of 88,818 individuals, including 37,482 with a confirmed SARS-CoV-2 infection, the RD of long-term sick-leave is 3.3% (95% CI 3.1% to 3.6%). We observe a high degree of effect heterogeneity, with conditional RDs ranging from −3.4% to 13.7%. Age, high BMI, depression, and sex are the most important variables explaining heterogeneity. Among three-way interactions considered, females with high BMI and depression and persons aged 36–45 years with high BMI and depression have an absolute increase in risk of long-term sick-leave above 10%.

Conclusions
Our study supports significant individual-level heterogeneity in the effect of SARS-CoV-2 infection on long-term sick-leave, with age, sex, high BMI, and depression identified as key factors. Efforts to curb the PCC burden should consider multimorbidity and individual-level risk.
Tackling the outer membrane: facilitating compound entry into Gram-negative bacterial pathogens
Authors: Saxena Deepanshi , Maitra Rahul , Bormon Rakhi , Czekanska Marta , Meiers Joscha , Titz Alexander , Verma Sandeep , Chopra Sidharth 
Published: December 2023

AbstractEmerging resistance to all available antibiotics highlights the need to develop new antibiotics with novel mechanisms of action. Most of the currently used antibiotics target Gram-positive bacteria while Gram-negative bacteria easily bypass the action of most drug molecules because of their unique outer membrane. This additional layer acts as a potent barrier restricting the entry of compounds into the cell. In this scenario, several approaches have been elucidated to increase the accumulation of compounds into Gram-negative bacteria. This review includes a brief description of the physicochemical properties that can aid compounds to enter and accumulate in Gram-negative bacteria and covers different strategies to target or bypass the outer membrane-mediated barrier in Gram-negative bacterial pathogens.
Copper-catalyzed desymmetric silylative-cyclization of 1,6-diynes for synthesis of spirocyclic compounds
Authors: Shan Cui-Cui , Wang Zi-Lu , Xu Yun-He 
Published: December 2023

The silylative-cyclization desymmetrization of 1,6-diynes has been realized. This reaction enabled the construction of silyl-functionalized spirocyclic oxindoles, indanone, quinolinone, and tetralone derivatives from readily available 1,6-diynes.