bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nocturnal exposure to a preferred ambient scent does not affect dream emotionality or post-sleep core affect valence in young adults
Authors: Martinec Nováková Lenka , Miletínová Eva , Kliková Monika , Bušková Jitka 
Published: May 2024

AbstractEmotions experienced within sleep mentation (dreaming) affect mental functioning in waking life. There have been attempts at enhancing dream emotions using olfactory stimulation. Odors readily acquire affective value, but to profoundly influence emotional processing, they should bear personal significance for the perceiver rather than be generally pleasant. The main objective of the present sleep laboratory study was to examine whether prolonged nocturnal exposure to self-selected, preferred ambient room odor while asleep influences emotional aspects of sleep mentation and valence of post-sleep core affect. We asked twenty healthy participants (12 males, mean age 25 ± 4 years) to pick a commercially available scented room diffuser cartridge that most readily evoked positively valenced mental associations. In weekly intervals, the participants attended three sessions. After the adaptation visit, they were administered the odor exposure and odorless control condition in a balanced order. Participants were awakened five minutes into the first rapid eye movement (REM) stage that took place after 2:30 a.m. and, if they had been dreaming, they were asked to rate their mental sleep experience for pleasantness, emotional charge, and magnitude of positive and negative emotions and also to evaluate their post-sleep core affect valence. With rs < 0.20, no practically or statistically significant differences existed between exposure and control in any outcome measures. We conclude that in young, healthy participants, the practical value of olfactory stimulation with self-selected preferred scents for enhancement of dream emotions and post-sleep core affect valence is very limited.
Position-resolved charge collection of silicon carbide detectors with an epitaxially-grown graphene layer
Authors: Lopez Paz Ivan , Godignon Philippe , Moffat Neil , Pellegrini Giulio , Rafí Joan Marc , Rius Gemma 
Published: May 2024

AbstractSilicon carbide (SiC) has outstanding physical properties therefore, diodes based on SiC are being considered for many radiation detection applications such as particle accelerator experiments and medical dosimetry. Moreover, by reducing the metal on the surface of the diode there is the potential to enhance its performance in some fields where the presence of metal is detrimental. To this end, SiC detectors with an epitaxially-grown graphene layer (EG), that substitutes the metallic contact, in the sensitive region were produced at IMB-CNM, profiting from the conductivity of the mono-atomic layer material. To isolate the effect of the graphene on the charge collection, samples without graphene were produced in parallel. In this paper, the effect of EG on Silicon Carbide p-in-n radiation detectors is studied in terms of charge collection with a radioactive source and by means of the transient current technique (TCT), which allows for position-dependent signal formation analysis. As a result of the former, we show the capability of the EG-SiC sensor for charge collection after signal integration, to a resolution close to that of a sensor fully metallised. Moreover, from the TCT studies, we observe uniform charge collection across the active region, as well as an up-to $$\sim $$
∼
40% transient amplitude damping which, compared with the $$\sim $$
∼
90% on the sample containing no metallic contact, proves that the presence of graphene benefits the performance of the device and that the technology is viable for radiation detection as an alternative to metal.
Smart traffic management of vehicles using faster R-CNN based deep learning method
Authors: Chaudhuri Arindam 
Published: May 2024

AbstractWith constant growth of civilization and modernization of cities all across the world since past few centuries smart traffic management of vehicles is one of the most sorted after problem by research community. Smart traffic management basically involves segmentation of vehicles, estimation of traffic density and tracking of vehicles. The vehicle segmentation from videos helps realization of niche applications such as monitoring of speed and estimation of traffic. When occlusions, background with clutters and traffic with density variations, this problem becomes more intractable in nature. Keeping this motivation in this research work, we investigate Faster R-CNN based deep learning method towards segmentation of vehicles. This problem is addressed in four steps viz minimization with adaptive background model, Faster R-CNN based subnet operation, Faster R-CNN initial refinement and result optimization with extended topological active nets. The computational framework uses adaptive background modeling. It also addresses shadow and illumination issues. Higher segmentation accuracy is achieved through topological active net deformable models. The topological and extended topological active nets help to achieve stated deformations. Mesh deformation is achieved with minimization of energy. The segmentation accuracy is improved with modified version of extended topological active net. The experimental results demonstrate superiority of this framework with respect to other methods.
The local mechanosensitive response of primary cardiac fibroblasts is influenced by the microenvironment mechanics
Authors: Braidotti Nicoletta , Demontis Giorgia , Conti Martina , Andolfi Laura , Ciubotaru Catalin Dacian , Sbaizero Orfeo , Cojoc Dan 
Published: May 2024

AbstractCardiac fibroblasts (CFs) are essential for preserving myocardial integrity and function. They can detect variations in cardiac tissue stiffness using various cellular mechanosensors, including the Ca2+ permeable mechanosensitive channel Piezo1. Nevertheless, how CFs adapt the mechanosensitive response to stiffness changes remains unclear. In this work we adopted a multimodal approach, combining the local mechanical stimulation (from 10 pN to 350 nN) with variations of culture substrate stiffness. We found that primary rat CFs cultured on stiff (GPa) substrates showed a broad Piezo1 distribution in the cell with particular accumulation at the mitochondria membrane. CFs displayed a force-dependent behavior in both calcium uptake and channel activation probability, showing a threshold at 300 nN, which involves both cytosolic and mitochondrial Ca2+ mobilization. This trend decreases as the myofibroblast phenotype within the cell population increases, following a possible Piezo1 accumulation at focal adhesion sites. In contrast, the inhibition of fibroblasts to myofibroblasts transition with soft substrates (kPa) considerably reduces both mechanically- and chemically-induced Piezo1 activation and expression. Our findings shed light on how Piezo1 function and expression are regulated by the substrate stiffness and highlight its involvement in the environment-mediated modulation of CFs mechanosensitivity.
Information processing style and institutional trust as factors of COVID vaccine hesitancy
Authors: Zhao Wanchen , Russell Catherine Maya , Jankovsky Anastasia , Cannon Tyrone D. , Pittenger Christopher , Pushkarskaya Helen 
Published: May 2024

AbstractThis study investigates the factors contributing to COVID vaccine hesitancy. Vaccine hesitancy has commonly been attributed to susceptibility to misinformation and linked to particular socio-demographic factors and personality traits. We present a new perspective, emphasizing the interplay between individual cognitive styles and perceptions of public health institutions. In January 2020, before the COVID-19 pandemic, 318 participants underwent a comprehensive assessment, including self-report measures of personality and clinical characteristics, as well as a behavioral task that assessed information processing styles. During 2021, attitudes towards vaccines, scientists, and the CDC were measured at three time points (February–October). Panel data analysis and structural equation modeling revealed nuanced relationships between these measures and information processing styles over time. Trust in public health institutions, authoritarian submission, and lower information processing capabilities together contribute to vaccine acceptance. Information processing capacities influenced vaccination decisions independently from the trust level, but their impact was partially mediated by authoritarian tendencies. These findings underscore the multifactorial nature of vaccine hesitancy, which emerges as a product of interactions between individual cognitive styles and perceptions of public health institutions. This novel perspective provides valuable insights into the underlying mechanisms that drive this complex phenomenon.
T-reg transcriptomic signatures identify response to check-point inhibitors
Authors: Noblejas-López María del Mar , García-Gil Elena , Pérez-Segura Pedro , Pandiella Atanasio , Győrffy Balázs , Ocaña Alberto 
Published: May 2024

AbstractRegulatory T cells (Tregs) is a subtype of CD4+ T cells that produce an inhibitory action against effector cells. In the present work we interrogated genomic datasets to explore the transcriptomic profile of breast tumors with high expression of Tregs. Only 0.5% of the total transcriptome correlated with the presence of Tregs and only four transcripts, BIRC6, MAP3K2, USP4 and SMG1, were commonly shared among the different breast cancer subtypes. The combination of these genes predicted favorable outcome, and better prognosis in patients treated with checkpoint inhibitors. Twelve up-regulated genes coded for proteins expressed at the cell membrane that included functions related to neutrophil activation and regulation of macrophages. A positive association between MSR1 and CD80 with macrophages in basal-like tumors and between OLR1, ABCA1, ITGAV, CLEC5A and CD80 and macrophages in HER2 positive tumors was observed. Expression of some of the identified genes correlated with favorable outcome and response to checkpoint inhibitors: MSR1, CD80, OLR1, ABCA1, TMEM245, and ATP13A3 predicted outcome to anti PD(L)1 therapies, and MSR1, CD80, OLR1, ANO6, ABCA1, TMEM245, and ATP13A3 to anti CTLA4 therapies, including a subgroup of melanoma treated patients. In this article we provide evidence of genes strongly associated with the presence of Tregs that modulates the response to check point inhibitors.
Ratio of plasma IL-13/TNF- ∝ and CXCL10/CCL17 predicts mepolizumab and omalizumab response in asthma better than eosinophil count or immunoglobulin E level
Authors: Akenroye Ayobami , Nopsopon Tanawin , Hacker Jonathan J. , Laidlaw Tanya M. 
Published: May 2024

AbstractTo date, most studies to identify biomarkers associated with response to the anti-interleukin 5 agent, mepolizumab, and to the anti-immunoglobulin E agent, omalizumab have focused on clinically available biomarkers, such as the peripheral blood eosinophil counts (BEC) and total immunoglobulin E (IgE). However, these biomarkers often have low predictive accuracy, with many patients with eosinophilic or allergic asthma failing to demonstrate clinical response to mepolizumab or omalizumab respectively. In this study, we evaluated the association of baseline pre-biologic plasma levels of 26 cytokines and chemokines, including T-helper 1 (Th1)-, Th2-, Th17-related cytokines, and their ratios with subsequent clinical response to mepolizumab or omalizumab. We defined clinical response as a reduction in the baseline annual exacerbation rate by half or more over the one-year period following initiation of the biologic. Baseline levels of plasma IL-13 were differentially elevated in responders versus non-responders to mepolizumab and plasma CXCL10 levels were differentially elevated in responders to omalizumab. The ratio of IL-13/TNF-α had the best sensitivity and specificity in predicting response to mepolizumab and CXCL10/CCL17 to omalizumab, and these performed better as predictive biomarkers of response than BEC and IgE. Cytokines and chemokines associated with airway eosinophilia, allergic inflammation, or Th2 inflammation, such as IL-13 and CXCL10, may be better predictors of clinical response to mepolizumab and omalizumab, than IL-5 or IgE, the targets of mepolizumab and omalizumab.
Detecting emotions through EEG signals based on modified convolutional fuzzy neural network
Authors: Ahmadzadeh Nobari Azar Nasim , Cavus Nadire , Esmaili Parvaneh , Sekeroglu Boran , Aşır Süleyman 
Published: May 2024

AbstractEmotion is a human sense that can influence an individual’s life quality in both positive and negative ways. The ability to distinguish different types of emotion can lead researchers to estimate the current situation of patients or the probability of future disease. Recognizing emotions from images have problems concealing their feeling by modifying their facial expressions. This led researchers to consider Electroencephalography (EEG) signals for more accurate emotion detection. However, the complexity of EEG recordings and data analysis using conventional machine learning algorithms caused inconsistent emotion recognition. Therefore, utilizing hybrid deep learning models and other techniques has become common due to their ability to analyze complicated data and achieve higher performance by integrating diverse features of the models. However, researchers prioritize models with fewer parameters to achieve the highest average accuracy. This study improves the Convolutional Fuzzy Neural Network (CFNN) for emotion recognition using EEG signals to achieve a reliable detection system. Initially, the pre-processing and feature extraction phases are implemented to obtain noiseless and informative data. Then, the CFNN with modified architecture is trained to classify emotions. Several parametric and comparative experiments are performed. The proposed model achieved reliable performance for emotion recognition with an average accuracy of 98.21% and 98.08% for valence (pleasantness) and arousal (intensity), respectively, and outperformed state-of-the-art methods.
The optimization method of wing plasma ice shape regulation based on quantitative assessment of flight risk
Authors: Li Zhe , Dou Pengfei , Huang Qiao 
Published: May 2024

AbstractPlasma ice shape regulation is a technology which uses plasma actuator to regulate the continuous ice into safer intermittent ice by its significant thermal effect with limited energy. Whether plasma ice shape regulation could reduce flight risk is a new problem under the wing with continuous ice. The 3D printed ice shapes were arranged on the leading edge of the wing based on NACA0012 airfoil, aiming to simulate the configuration after ice shape regulation. And the aerodynamic parameters were obtained by wind tunnel experiments. The experimental results showed that the ratio of signal regulation ice width $$d$$
d
to chord length of the wing $$b_{A}$$

b
A

determined the aerodynamic characteristics, and the aerodynamic characteristics changed better compared with configuration of the continuous ice. However, the flight risk of the wing under given regulation ratio is unknown. Based on the straight and swept wing after regulating, the flight safety boundaries were simulated by the reachable set method. Further, a method of quantitative assessment of flight risk is proposed. Quantitative values of risk were calculated. The results show that the flight risk all decreases from level 2 to level 4 compared with configuration of the continuous ice when $$d/b_{A}$$

d
/

b
A

equals 0.15 under conditions of swept and straight wing.
High surface area and interconnected nanoporosity of clay-rich astromaterials
Authors: Garvie Laurence A. J. , Trif László , Cotto-Figueroa Desireé , Asphaug Erik , Hoover Christian G. 
Published: May 2024

AbstractPorosity affects key astromaterial processes from disruption in our atmosphere and impact with the ground, to the comminution of boulders by thermal and impact processes and slope mechanics on asteroid surfaces, to access and utilization of in-situ resources. Whereas the bulk porosity of clay-rich meteorites is well established, the magnitude of their surface area and nano-scale porosity is poorly known. Here we use N2 BET gas adsorption to measure the specific surface area and nanoscale pore distribution in several clay-rich meteorites. Two recent falls Tarda (C2-ung) and Aguas Zarcas (CM2) have specific surface areas of 72.5 and 16.5 m2/g, respectively. However, the specific surface area of Tarda ranges from 33.7 to 81.6 m2/g depending on outgassing conditions. The Tarda surface area is dominated by an interconnected network of ~ 3-nm-sized pores, whereas Aguas Zarcas shows a lower density of ~ 3 nm pores and broader size distribution around 40 nm. In contrast, Ivuna and Orgueil (CI1) have surface areas of ~ 15 to 18 m2/g: the low values compared to Tarda are likely due to the neoformation of pore-blocking minerals during atmospheric exposure. These data suggest that returned samples from asteroids Ryugu and Bennu, which are mineralogically and texturally similar to Tarda, also have interconnected nano-scale porosity with high surface area.
Changes in wet bulb globe temperature and risk to heat-related hazards in Bangladesh
Authors: Kamal A. S. M. Maksud , Fahim Abul Kashem Faruki , Shahid Shamsuddin 
Published: May 2024

AbstractThe rise in temperatures and changes in other meteorological variables have exposed millions of people to health risks in Bangladesh, a densely populated, hot, and humid country. To better assess the threats climate change poses to human health, the wet bulb globe temperature (WBGT) is an important indicator of human heat stress. This study utilized high-resolution reanalysis data from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF ERA5) to analyze the spatiotemporal changes in outdoor WBGT across Bangladesh from 1979 to 2021, employing Liljegren's model. The study revealed an increase in the annual average WBGT by 0.08–0.5 °C per decade throughout the country, with a more pronounced rise in the southeast and northeast regions. Additionally, the number of days with WBGT levels associated with high and extreme risks of heat-related illnesses has shown an upward trend. Specifically, during the monsoon period (June to September), there has been an increase of 2–4 days per decade, and during the pre-monsoon period (March to May), an increase of 1–3 days per decade from 1979 to 2021. Furthermore, the results indicated that the escalation in WBGT has led to a five-fold increase in affected areas and a three-fold increase in days of high and extreme heat stress during the monsoon season in recent years compared to the earlier period. Trend and relative importance analyses of various meteorological variables demonstrated that air temperature is the primary driver behind Bangladesh's rising WBGT and related health risks, followed by specific humidity, wind speed, and solar radiation.
The association of hypertension among married Indian couples: a nationally representative cross-sectional study
Authors: Varghese Jithin Sam , Ghosh Arpita , Stein Aryeh D. , Narayan K. M. Venkat , Patel Shivani A. 
Published: May 2024

AbstractMounting evidence demonstrates that intimate partners sharing risk factors have similar propensities for chronic conditions such as hypertension. The objective was to study whether spousal hypertension was associated with one’s own hypertension status independent of known risk factors, and stratified by socio-demographic subgroups (age, sex, wealth quintile, caste endogamy). Data were from heterosexual married couples (n = 50,023, women: 18–49 years, men: 21–54 years) who participated in the National Family Health Survey-V (2019–2021). Hypertension was defined as self-reported diagnosis of hypertension or average of three blood pressure measurements ≥ 140 systolic or 90 mmHg diastolic BP. Among married adults, the prevalence of hypertension among men (38.8 years [SD 8.3]) and women (33.9 years [SD 7.9]) were 29.1% [95% CI 28.5–29.8] and 20.6% [95% CI 20.0–21.1] respectively. The prevalence of hypertension among both partners was 8.4% [95% CI 8.0–8.8]. Women and men were more likely to have hypertension if their spouses had the condition (husband with hypertension: PR 1.37 [95% CI 1.30–1.44]; wife with hypertension: PR 1.32 [95% CI 1.26–1.38]), after adjusting for known risk factors. Spouse’s hypertension status was consistently associated with own status across all socio-demographic subgroups examined. These findings present opportunities to consider married couples as a unit in efforts to diagnose and treat hypertension.
Nonlinear mechanical response analysis and convolutional neural network enabled diagnosis of single-span rotor bearing system
Authors: Qian Bing , Cai Yinhui , Ran Yinkang , Sun Weipeng 
Published: May 2024

AbstractThe wide application of rotating machinery has boosted the development of electricity and aviation, however, long-term operation can lead to a variety of faults. The use of different measures to deal with corresponding malfunctions is the key to generating benefits, so it is significant to carry out the fault diagnosis of rotating machinery. In this work, a test bench for single-span rotor bearings was established, three faults, including spindle bending, spindle crack without end loading and spindle crack with end loading, are experimental analyzed with basic mechanical response. Moreover, a diagnosis is performed using a convolutional neural network, according to the differences in mechanical responses of the three faults obtained from experiments. For three faults, the change in the properties of spindle itself results in different axis trajectories and spectra. Compared with spindle bending fault, spindle crack fault not only cause 1×, 2×, 3× frequency component excitation, also 4×, 5× frequency component excitation. Additionally, the classification accuracy of the training set and the test set under machine learning for the three types of working conditions is 100%. This indicates that the network can significantly identify signal features so as to make effective fault classification.
The mental health toll among healthcare workers during the COVID-19 Pandemic in Malawi
Authors: Maliwichi Limbika , Kondowe Fiskani , Mmanga Chilungamo , Mchenga Martina , Kainja Jimmy , Nyamali Simunye , Ndasauka Yamikani 
Published: May 2024

AbstractThe COVID-19 pandemic has affected the mental health of healthcare workers worldwide, with frontline personnel experiencing heightened rates of depression, anxiety, and posttraumatic stress. This mixed-methods study aimed to assess the mental health toll of COVID-19 on healthcare workers in Malawi. A cross-sectional survey utilising the Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9), and Primary Care PTSD Screen for DSM-5 (PC-PTSD-5) was conducted among 109 frontline healthcare workers. Additionally, in-depth interviews were conducted with 16 healthcare workers to explore their experiences and challenges during the pandemic. The results indicated a high prevalence of COVID-19-related depression (31%; CI [23, 41]), anxiety (30%; CI [22, 40]), and PTSD (25%; CI [17, 34]) among participants. Regression analysis revealed significantly higher rates of depression, anxiety, and PTSD among healthcare workers in city referral hospitals compared to district hospitals. Qualitative findings highlighted the emotional distress, impact on work and personal life, and experiences of stigma and discrimination faced by healthcare workers. The stress process model provided a valuable framework for understanding the relationship among pandemic-related stressors, coping resources, and mental health outcomes. The findings underscore the urgent need for interventions and support systems to mitigate the mental health impact of COVID-19 on frontline healthcare workers in Malawi. Policymakers should prioritise the assessment and treatment of mental health problems among this critical workforce to maintain an effective pandemic response and build resilience for future crises.