Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Traditional Chinese Medical Science Characteristic Nursing Mode Based on Evidence-Based Medicine to Puerperal Breast Tenderness and Pain

Objective To explore the effects of traditional Chinese medicine (TCM) characteristic nursing mode based on evidence-based medicine on parturients with breast tenderness and pain. Method 100 parturients with postpartum breast pain treated at Taizhou First People's Hospital from January 2020 to December 2021 were selected. Among them, 51 cases received routine nursing intervention (general group, GG) and 49 cases received TCM characteristic nursing based on evidence-based medicine (comprehensive group, CG). The pain number (NRS) score, lactation effect, breastfeeding self-efficacy (BSES-SF) score, anxiety and depression, and nursing satisfaction of the two groups were compared. In addition, the pregnant women were followed up after discharge to investigate the rate of exclusive breastfeeding. Result Three days after intervention, NRS score, SAS score, and SDS score in the CG were significantly lower than those in the GG. The level of serum prolactin and total breast lactation yield in the GG were better than those in the CG. BSES-SF score, nursing satisfaction, and exclusive breastfeeding rate in the CG were higher than those in the GG. Conclusion Evidence-based TCM care can significantly reduce postpartum breast tenderness, increase milk production, improve exclusive breastfeeding, and help relieve emotional distress.
Impact of the 2019 Coronavirus Infectious Disease (COVID-19) pandemic on onset to door time and admissions of new onset acute ischemic stroke in a tertiary care level hospital in North India

Context: Coronavirus infectious disease (COVID-19) pandemic disrupted the already marginalized healthcare provision in resource limited countries like India. Aims: This study compared onset to door time and temporal trends of admissions to seek medical care in new onset acute ischaemic stroke during the COVID-19 period with a representative pre-COVID-19 period in rural background. Settings and Design: Prospective Cross-sectional study in a tertiary level hospital in North India. Methods and Material: Study included new onset acute ischaemic stroke admitted within first 2 weeks of symptoms onset. Subjects were divided into: Group A – Pre-COVID-19 stroke, Group B – Non-COVID-19 Stroke, and Group C - Stroke, positive for COVID-19. Detailed epidemiological, clinical profile, onset to door time and temporal trends of admissions were recorded. Statistical Analysis Used: Chi square/Fisher's exact test and Independent Samples T test or Mann–Whitney U test were used for categorical and continuous variables. Results: Onset to door time in new onset acute ischaemic stroke was significantly prolonged by 6 h in COVID-19 period (median (interquartile range), 19 (12–27) h) as compared with pre-COVID-19 period. Admissions of new onset acute ischaemic stroke were significantly less in COVID-19 period. Comorbidities and severity of stroke (mean National Institutes of Health Stroke Scale, 20 ± 4) were more during the COVID-19 period. Incidence and mortality of COVID-19 positive new onset acute ischaemic stroke were 0.95% and 38%. Conclusions: Onset to door time in new onset acute ischaemic stroke was significantly prolonged in COVID-19 as compared with pre-COVID-19 period. The admissions were fewer with more severity and comorbidities in COVID-19 period. COVID-19 positive stroke patients had more severity and mortality as compared with non-COVID-19 stroke.
Analysing Global Research on Stock Market Anomalies: A Behavioural Finance Perspective

Investors’ psychology and behaviours have been known to influence the emergence of capital market imperfections. The corpus of studies on this matter is copious but conflicting as researchers approach the subject from two major perspectives. Against this background, this study aims to review and establish the global research trend in behavioural finance examining stock market anomalies vis-à-vis its opposing paradigm (i.e., the efficient market hypothesis). Based on an extensive review of the types of anomalies published by scholars over 53 years (1968 – 2021), this study generated search strings targeting the appropriate investor behaviours as responses to stock market anomalies. The study applied bibliometric analysis and drew 1,767 documents from the Scopus database, which were later reduced to 1,436 after applying the exclusion criteria. The analyses revealed that authors prefer to disseminate their research on stock market anomalies in refereed journals and also attempt to unravel the contrast between rational and behavioural dynamics of investor decision-making based on short-term observations. Also, most of the studies fall under the general economics and business subject groups, indicating authors' preoccupation with general rather than specific matters on stock market anomalies. Further, the study highlighted the global distribution of studies on stock market anomalies, the top prolific authors in the field, the top journal sources, and the Scopus profiles of selected top authors. Based on these results, recommendations for future studies were given.
A Real-Time EMG-Based Fixed-Bandwidth Frequency-Domain Embedded System for Robotic Hand

The signals from electromyography (EMG) have been used for volitional control of robotic assistive devices with the challenges of performance improvement. Currently, the most common method of EMG signal processing for robot control is RMS (root mean square)-based algorithm, but system performance accuracy can be affected by noise or artifacts. This study hypothesized that the frequency bandwidths of noise and artifacts are beyond the main EMG signal frequency bandwidth, hence the fixed-bandwidth frequency-domain signal processing methods can filter off the noise and artifacts only by processing the main frequency bandwidth of EMG signals for robot control. The purpose of this study was to develop a cost-effective embedded system and short-time Fourier transform (STFT) method for an EMG-controlled robotic hand. Healthy volunteers were recruited in this study to identify the optimal myoelectric signal frequency bandwidth of muscle contractions. The STFT embedded system was developed using the STM32 microcontroller unit (MCU). The performance of the STFT embedded system was compared with RMS embedded system. The results showed that the optimal myoelectric signal frequency band responding to muscle contractions was between 60 and 80 Hz. The STFT embedded system was more stable than the RMS embedded system in detecting muscle contraction. Onsite calibration was required for RMS embedded system. The average accuracy of the STFT embedded system is 91.55%. This study presents a novel approach for developing a cost-effective and less complex embedded myoelectric signal processing system for robot control.
Aerobic Exercise Alleviates the Impairment of Cognitive Control Ability Induced by Sleep Deprivation in College Students: Research Based on Go/NoGo Task

The purpose of this study was to observe whether aerobic exercise is able to alleviate the impairment of cognitive control ability in college students by sleep deprivation through cognitive control (Go-NoGo task) and blood-based markers. Taking 30 healthy college students (15 males and 15 females) as participants, using a random cross-over design within groups, respectively perform one night of sleep deprivation and one night of normal sleep (8 h). The exercise intervention modality was to complete a 30-min session of moderate-intensity aerobic exercise on a power bicycle. Change in cognitive control was assessed using the Go/NoGo task paradigm; 5-ht and blood glucose contentwere determined by enzyme-linked immuno sorbent assay and glucose oxidase electrode Measurement, respectively. The results showed that sleep deprivation could significantly reduce the response inhibition ability and response execution ability, and significantly reduce the blood 5-ht content (p< 0.01). Thirty minutes of moderate intensity aerobic exercise intervention significantly increased response inhibition ability and response execution ability, significantly increased blood 5-ht content (p<0.01), and did not change serum glucose levels. Conclusion: An acute aerobic exercise can alleviate the cognitive control impairment caused by sleep deprivation, and 5-ht may be one of the possible mechanisms by which aerobic exercise alleviates the cognitive control impairment caused by sleep deprivation.
Assessment of TiO2 Nanoparticle Impact on Surface Morphology of Chinese Hamster Ovary Cells

The process of nanoparticles entering the cells of living organisms is an important step in understanding the influence of nanoparticles on biological processes. The interaction of nanoparticles with the cell membrane is the first step in the penetration of nanoparticles into cells; however, the penetration mechanism is not yet fully understood. This work reported the study of the interaction between TiO2 nanoparticles (TiO2-NPs) and Chinese hamster ovary (CHO) cells using an in vitro model. The characterization of crystalline phases of TiO2 NPs was evaluated by transmission electron microscopy (TEM), X-ray diffraction (XRD) spectrum, and atomic force microscopy (AFM). Interaction of these TiO2 nanoparticles (TiO2- NPs) with the CHO cell membrane was investigated using atomic force microscopy (AFM) and Raman spectroscopy. The XRD analysis result showed that the structure of the TiO2 particles was in the rutile phase with a crystallite size of 60 nm, while the AFM result showed that the particle size distribution had two peaks with 12.1 nm and 60.5 nm. The TEM analysis confirmed the rutile phase of TiO2 powder. Our study showed that exposure of CHO cells to TiO2-NPs caused morphological changes in the cell membranes and influenced the viability of cells. The TiO2-NPs impacted the cell membrane surface; images obtained by AFM revealed an ‘ultra structure‘ with increased roughness and pits on the surface of the membrane. The depth of the pits varied in the range of 40–80 nm. The maximal depth of the pits after the treatment with TiO2-NPs was 100% higher than the control values. It is assumed that these pits were caveolae participating in the endocytosis of TiO2-NPs. The research results suggest that the higher maximal depth of the pits after the exposure of TiO2-NPs was determined by the interaction of these TiO2-NPs with the cell’s plasma membrane. Moreover, some of pits may have been due to plasma membrane damage (hole) caused by the interaction of TiO2-NPs with membrane constituents. The analysis of AFM images demonstrated that the membrane roughness was increased with exposure time of the cells to TiO2-NPs dose. The average roughness after the treatment for 60 min with TiO2-NPs increased from 40 nm to 78 nm. The investigation of the membrane by Raman spectroscopy enabled us to conclude that TiO2-NPs interacted with cell proteins, modified their conformation, and potentially influenced the structural damage of the plasma membrane.
Autonomous Robotic Manipulation: Real-Time, Deep-Learning Approach for Grasping of Unknown Objects

Recent advancement in vision-based robotics and deep-learning techniques has enabled the use of intelligent systems in a wider range of applications requiring object manipulation. Finding a robust solution for object grasping and autonomous manipulation became the focus of many engineers and is still one of the most demanding problems in modern robotics. This paper presents a full grasping pipeline proposing a real-time data-driven deep-learning approach for robotic grasping of unknown objects using MATLAB and convolutional neural networks. The proposed approach employs RGB-D image data acquired from an eye-in-hand camera centering the object of interest in the field of view using visual servoing. Our approach aims at reducing propagation errors and eliminating the need for complex hand tracking algorithm, image segmentation, or 3D reconstruction. The proposed approach is able to efficiently generate reliable multi-view object grasps regardless of the geometric complexity and physical properties of the object in question. The proposed system architecture enables simple and effective path generation and a real-time tracking control. In addition, our system is modular, reliable, and accurate in both end effector path generation and control. We experimentally justify the efficacy and effectiveness of our overall system on the Barrett Whole Arm Manipulator.
Thermal remote sensing for plant ecology from leaf to globe

Surface temperatures are mechanistically linked to vegetation biophysical and physiological processes. Although remote sensing in the thermal infrared (TIR) domain can offer novel insights into the impacts of changing surface temperatures on vegetation, the transformative potential of remote sensing for plant ecology has not yet been realized. Remotely sensed surface temperatures can be used to derive stomatal behaviour and identify stressful environmental conditions in near‐real time. Plant species, traits and structural characteristics can be evaluated with high spectral resolution TIR emissivity. Beyond canopy scales, thermal remote sensing can enhance the inferences obtained from manipulative experiments and empirical evidence, providing unique insight into shifts in species ranges and phenology with changing climate conditions. Scaling leaf traits, canopy structure and regional patterns require an integrated understanding of both process and technology. Theory linking surface temperatures to vegetation dynamics is summarized from an energy balance perspective. We outline scaling considerations including the impacts of morphology on leaf energy balance, canopy structure influences on convective heat exchange and potential confounding impacts of non‐vegetated surfaces. Synthesis. We introduce a unifying framework to link leaf to globe through thermal remote sensing. Recent and emerging advances in sensors, data availability and analytics, together with synergies between TIR remote sensing and other data sources, present a timely opportunity for ecologists to advance our understanding of plant physiology, ecology and biogeography with thermal remote sensing.
Personal Control and Antisocial Coaching: A Test of Self-Control and Control Balance Theories

ABSTRACT Although the study of sports deviance has gained traction across a variety of academic disciplines, existing research often lacks theoretical guidance and ignores criminological insight. To fill this gap in the literature, the current study employs structural equation modeling to test the efficacy of self-control and control balance theory in explaining antisocial coaching behaviors among a sample of 196 Iranian soccer coaches. Results indicate that low self-control, sport control deficit, low informal sanction, and deviant motivation have direct effects on antisocial coaching. In addition, low self-control, sport control deficit, and situational provocation have indirect effects on antisocial coaching. These findings expand the scope of traditional criminological theories to the study of sports deviance and provide guidance for the development of proactive policy solutions aimed to reduce antisocial coaching behaviors.
Movement, Behavior, and Habitat Use of Whale Sharks (Rhincodon typus) in the Tropical Eastern Pacific Ocean

Whale sharks (Rhincodon typus) are found circumglobally in tropical, subtropical, and warm temperate waters, and their known seasonal aggregations and migratory movements are influenced by factors such as ocean currents, thermobiological systems, and patterns of productivity. Several locations in the eastern tropical Pacific Ocean are known habitats for R. typus; Although it has long been known that whale sharks aggregate along the Panama coast, little is known in relation to their movement patterns, behavior, and habitat use. In this study, we investigated the movements and behaviors of R. typus tagged in Panama in relation to oceanographic variables and examined the overlap of foraging habitat and migratory routes with marine protected areas (MPAs), industrial fishing areas, and marine traffic. Satellite tracks from 30 R. typus tagged in the coastal waters of Panama were examined, including nine tags suspicious of earlier detachment. A hidden Markov model was then used to identify different behavioral states (foraging and migrating) and their relationships with environmental variables (sea surface temperature, primary productivity, chlorophyll-a concentrations, and eddy location/speed) Tracks were also superimposed on maps of MPAs, industrial fishing areas, and regional marine vessel traffic to identify the degree of overlap. Rhincodon typus foraged mainly within the Panamanian exclusive economic zone but also moved north and south along the coast and out to the open ocean. Significant differences in environmental conditions were found between sites in which foraging and migrating behaviors were recorded. Higher productivity and chlorophyl concentration were associated with foraging behavior, while higher eddy speeds were observed when sharks migrated. Rhincodon typus used MPAs; however, there was a high degree of overlap between their habitat and areas of industrial fishing and marine vessel traffic. Our results highlight the use of the coastal waters of Panama, oceanic seamounts, and ridges, MPAs and industrial fishing areas by R. typus for foraging and migration. Additionally, our findings highlight the importance of satellite tracking studies for understanding the behavior and habitat use of highly mobile migratory species, such as R. typus.
Heat Shock Alters the Proteomic Profile of Equine Mesenchymal Stem Cells

The aim of this research was to determine the impact of heat stress on cell differentiation in an equine mesenchymal stem cell model (EMSC) through the application of heat stress to primary EMSCs as they progressed through the cell specialization process. A proteomic analysis was performed using mass spectrometry to compare relative protein abundances among the proteomes of three cell types: progenitor EMSCs and differentiated osteoblasts and adipocytes, maintained at 37 °C and 42 °C during the process of cell differentiation. A cell-type and temperature-specific response to heat stress was observed, and many of the specific differentially expressed proteins were involved in cell-signaling pathways such as Notch and Wnt signaling, which are known to regulate cellular development. Furthermore, cytoskeletal proteins profilin, DSTN, SPECC1, and DAAM2 showed increased protein levels in osteoblasts differentiated at 42 °C as compared with 37 °C, and these cells, while they appeared to accumulate calcium, did not organize into a whorl agglomerate as is typically seen at physiological temperatures. This altered proteome composition observed suggests that heat stress could have long-term impacts on cellular development. We propose that this in vitro stem cell culture model of cell differentiation is useful for investigating molecular mechanisms that impact cell development in response to stressors.
Parallel Architecture of Convolutional Bi-Directional LSTM Neural Networks for Network-Wide Metro Ridership Prediction

Accurate metro ridership prediction can guide passengers in efficiently selecting their departure time and transferring from station to station. An increasing number of deep learning algorithms are being utilized to forecast metro ridership due to the development of computational intelligence. However, limited efforts have been exerted to consider spatiotemporal features, which are important in forecasting ridership through deep learning methods, in large-scale metro networks. To fill this gap, this paper proposes a parallel architecture comprising convolutional neural network (CNN) and bi-directional long short-term memory network (BLSTM) to extract spatial and temporal features, respectively. Metro ridership data are transformed into ridership images and time series. Spatial features can be learned from ridership image data by using CNN, which demonstrates favorable performance in video detection. Time series data are input into the BLSTM which considers the historical and future impacts of ridership in temporal feature extraction. The two networks are concatenated in parallel and prevented from interfering with each other. Joint spatiotemporal features are fed into a fully connected network for metro ridership prediction. The Beijing metro network is used to demonstrate the efficiency of the proposed algorithm. The proposed model outperforms traditional statistical models, deep learning architectures, and sequential structures, and is suitable for ridership prediction in large-scale metro networks. Metro authorities can thus effectively allocate limited resources to overcrowded areas for service improvement.
CK2β Is a Gatekeeper of Focal Adhesions Regulating Cell Spreading

CK2 is a hetero-tetrameric serine/threonine protein kinase made up of two CK2α/αʹ catalytic subunits and two CK2β regulatory subunits. The free CK2α subunit and the tetrameric holoenzyme have distinct substrate specificity profiles, suggesting that the spatiotemporal organization of the individual CK2 subunits observed in living cells is crucial in the control of the many cellular processes that are governed by this pleiotropic kinase. Indeed, previous studies reported that the unbalanced expression of CK2 subunits is sufficient to drive epithelial to mesenchymal transition (EMT), a process involved in cancer invasion and metastasis. Moreover, sub-stoichiometric expression of CK2β compared to CK2α in a subset of breast cancer tumors was correlated with the induction of EMT markers and increased epithelial cell plasticity in breast carcinoma progression. Phenotypic changes of epithelial cells are often associated with the activation of phosphotyrosine signaling. Herein, using phosphotyrosine enrichment coupled with affinity capture and proteomic analysis, we show that decreased expression of CK2β in MCF10A mammary epithelial cells triggers the phosphorylation of a number of proteins on tyrosine residues and promotes the striking activation of the FAK1-Src-PAX1 signaling pathway. Moreover, morphometric analyses also reveal that CK2β loss increases the number and the spatial distribution of focal adhesion signaling complexes that coordinate the adhesive and migratory processes. Together, our findings allow positioning CK2β as a gatekeeper for cell spreading by restraining focal adhesion formation and invasion of mammary epithelial cells.
Women’s empowerment and social innovation in childcare: the case of Barcelona, Spain

ABSTRACT Social innovation and empowerment are complex concepts that, from an analytical point of view, are not necessarily related. One explicit goal of social innovation is to empower communities, as well as the individuals that are involved in activities within those communities, but this does not necessarily always occur. Here we address the question ‘Does social innovation in early childhood education and care (ECEC) empower women? ’ First, we explore whether the projects we examine can be defined as social innovations. Second, we analyse to what extent arrangements that are identified as innovative in ECEC empower the mothers who choose them. We argue that if the characteristics of a particular social innovation project enhance or reinforce the capabilities of the women who participate in it, that experience will most probably empower them; if not, this is unlikely to occur. Our empirical material includes 37 interviews with key informants, educators, and mothers involved in these non-institutionalized projects, collected in Barcelona. Our results reveal the socioeconomic bias in these projects, as well as the costs derived for both sets of participants (mothers and educators). They also show the wider social impact that stems from these projects being under-regulated.