Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomistic modeling of electromechanical properties of piezoelectric zinc oxide nanowires

Currently, numerous articles are devoted to examining the influence of geometry and charge distribution on the mechanical properties and structural stability of piezoelectric nanowires (NWs). The varied modeling techniques adopted in earlier molecular dynamics (MD) works dictated the outcome of the different efforts. In this article, comprehensive MD studies are conducted to determine the influence of varied interatomic potentials (partially charged rigid ion model, [PCRIM] ReaxFF, charged optimized many-body [COMB], and Buckingham), geometrical parameters (cross-section geometry, wire diameter, and length), and charge distribution (uniform full charges versus partially charged surface atoms) on the resulting mechanical properties and structural stability of zinc oxide (ZnO) NWs. Our optimized parameters for the Buckingham interatomic potential are in good agreement with the existing experimental results. Furthermore, we found that the incorrect selection of interatomic potentials could lead to excessive overestimate (61%) of the elastic modulus of the NW. While NW length was found to dictate the strain distribution along the wire, impacting its predicted properties, the cross-section shape did not play a major role. Assigning uniform charges for both the core and surface atoms of ZnO NWs leads to a drastic decrease in fracture properties.
External Validation and Updating of the Cardiac Surgery Score for Prediction of Mortality in a Cardiac Surgery Intensive Care Unit.

OBJECTIVE To externally validate the predictive performance of the logistic and additive Cardiac Surgery Score (CASUS), a postoperative severity of illness score designed specifically for prediction of mortality in the cardiac surgery intensive care unit. DESIGN A retrospective analysis of prospectively collected data between July 1, 2012, and September 30, 2015. SETTING Single university cardiac surgery intensive care unit in Canada. PARTICIPANTS Consecutive adult patients (n = 4,519) admitted to the intensive care unit after cardiac surgery. INTERVENTION None. MEASUREMENTS AND MAIN RESULTS The mortality predicted by logistic CASUS was calculated for each patient on admission day 0 and postoperative days 2, 4, 7, and 10 using the original model equation. The mortality predicted by additive CASUS was determined on each day with separate logistic regression models, using the total score as a single variable. The observed mortality was 1.8%. Logistic CASUS overestimated mortality by 78%, 59%, 51%, 52%, and 29% on days 0, 2, 4, 7, and 10, respectively. After model updating with logistic calibration, logistic CASUS consistently provided estimates of death comparable with the observed mortality, as determined with the Hosmer-Lemeshow goodness-of-fit test. The stability of those estimates was confirmed by bootstrapping. Similar calibration results were obtained with additive CASUS. Logistic and additive CASUS had good discrimination with areas under the receiver operating characteristic curve greater than 0.7 on each study day. CONCLUSIONS Recalibrated logistic CASUS reliably predicts mortality in the intensive care unit after cardiac surgery. Logistic regression models derived from additive CASUS perform as well as logistic CASUS.
Hierarchical land cover and vegetation classification using multispectral data acquired from an unmanned aerial vehicle

ABSTRACT The use of multispectral cameras deployed on unmanned aerial vehicles (UAVs) in land cover and vegetation mapping applications continues to improve and receive increasing recognition and adoption by resource management and forest survey practitioners. Comparisons of different camera data and platform performance characteristics are an important contribution in understanding the role and operational capability of this technology. In this article, object-based classification accuracies for different cover types and vegetation species of interest in central Ontario were examined using data from three UAV-based multispectral cameras. Five land-cover classes (forest, shrub, herbaceous, bare soil, and built-up) were determined to be up to 95% correct overall with calibrated multispectral Parrot Sequoia digital camera data compared to independent field observations. The levels of classification accuracy decreased approximately 10–15% when spectrally less capable consumer-grade RGB sensors were used. Multispectral Parrot Sequoia classification accuracy was approximately 89% when more detailed vegetation classes, including individual deciduous tree species, shrub communities and agricultural crops, were analysed. Additional work is suggested in the use of such UAV multispectral and point cloud data in ash tree discrimination to support emerald ash borer infestation detection and management, and in analysis of functional and structural vegetation characteristics (e.g. leaf area index).
Validation of Three Models for Prediction of Blood Transfusion during Cesarean Delivery Admission

Abstract Objective Prediction of blood transfusion during delivery admission allows for clinical preparedness and risk mitigation. Although prediction models have been developed and adopted into practice, their external validation is limited. We aimed to evaluate the performance of three blood transfusion prediction models in a U.S. cohort of individuals undergoing cesarean delivery. Study Design This was a secondary analysis of a multicenter randomized trial of tranexamic acid for prevention of hemorrhage at time of cesarean delivery. Three models were considered: a categorical risk tool (California Maternal Quality Care Collaborative [CMQCC]) and two regression models (Ahmadzia et al and Albright et al). The primary outcome was intrapartum or postpartum red blood cell transfusion. The CMQCC algorithm was applied to the cohort with frequency of risk category (low, medium, high) and associated transfusion rates reported. For the regression models, the area under the receiver-operating curve (AUC) was calculated and a calibration curve plotted to evaluate each model's capacity to predict receipt of transfusion. The regression model outputs were statistically compared. Results Of 10,785 analyzed individuals, 3.9% received a red blood cell transfusion during delivery admission. The CMQCC risk tool categorized 1,970 (18.3%) individuals as low risk, 5,259 (48.8%) as medium risk, and 3,556 (33.0%) as high risk with corresponding transfusion rates of 2.1% (95% confidence interval [CI]: 1.5–2.9%), 2.2% (95% CI: 1.8–2.6%), and 7.5% (95% CI: 6.6–8.4%), respectively. The AUC for prediction of blood transfusion using the Ahmadzia and Albright models was 0.78 (95% CI: 0.76–0.81) and 0.79 (95% CI: 0.77–0.82), respectively ( p = 0.38 for difference). Calibration curves demonstrated overall agreement between the predicted probability and observed likelihood of blood transfusion. Conclusion Three models were externally validated for prediction of blood transfusion during cesarean delivery admission in this U.S. cohort. Overall, performance was moderate; model selection should be based on ease of application until a specific model with superior predictive ability is developed. Key Points A total of 3.9% of individuals received a blood transfusion during cesarean delivery admission. Three models used in clinical practice are externally valid for blood transfusion prediction. Institutional model selection should be based on ease of application until further research identifies the optimal approach.
Siliceous sponge spicules, silicoflagellates, and ebridians from hole 918D, continental rise of the Greenland margin

Sediments recovered from Hole 918D on the continental rise of the Greenland Margin were found to contain siliceous sponge spicules, silicoflagellates, and ebridians. An extreme fossil-barren interval occurred in lower Miocene and upper Miocene sediments of the core, with sponge spicules occurring in the middle Miocene. Though generally rare, the sponge spicules were morphologically diverse, with monaxons being the most abundant. Other morphologies and an undescribed spicule type were found. Representatives of several silicoflagellate genera were found in a narrow horizon of the upper Pliocene. The silicoflagellates were of a variety of ages, showing that this layer has been reworked. This interval also included two large ebridians, Triskelion gorgon and Adonnadonna primadonna, that have not been previously described from the North Atlantic. od t no vesns specolute ugh sechisin, om red f the onge ere 31 s; 8Dcalizes rg, pisify hlpes hich ave triINTRODUCTION Ocean Drilling Program (ODP) Leg 152 recovered sediment samples from six sites off the Greenland coast in order to study the rift volcanism and history of glaciation of the area. These sites were on a northwest-southeast transect across the East Greenland Margin, approximately 130 km from the Greenland coast near the center of a seaward-dipping reflector sequence (SDRS) (Fig. 1). A diverse assemblage of siliceous sponge spicules were found in middle Miocene sediments from Site 918D. The spicules were not generally abundant but were well preserved. The assemblage was dominated by monaxons with other spicule morphologies representing a fraction of total spicule abundance. The abundance and diversity of sponge spicules at Hole 918D are tabulated in this study (Table 1). Sponge spicules from deep ocean sediments have been studied infrequently. The results of this study can be compared to those of McCartney (1987, 1990), Ahlbach and McCartney (1992) and Zolnik et al., (1992); see McCartney (1990) for a tabulation of other sponge spicule literature from deep ocean studies. These studies show a generally similar diversity, with monaxons being the predominant spicule group. Palmer (1988) and Ivanik (1983) found abundant tetraxonal and triaxonal spicules and used their relative abundances to make paleobathymetric interpretations, but these spicule types were not abundant in this study.
Institutional Residence Protects Against Cognitive Frailty: A Cross-Sectional Study

Based on the complex aging background, more and more older people have to live in an institution in later life in China. The prevalence of cognitive frailty (CF) is more higher in institutions than in communities. Rarely studies were conducted on the relationship between institutional residence and CF. Hence, this study were performed to determine the relationship between institutional residence (living in a nursing home) and CF in older adults. A total of 1004 older community residents and 111 older nursing home residents over 50 years of age from Hefei, Anhui Province, China were recruited. CF included physical frailty (PF) and mild cognitive impairment (MCI). PF was assessed using the Chinese version of the Fried frailty scale, MCI was assessed using the Montreal Cognitive Assessment, and the common associated factors including sedentary behavior, exercise, intellectual activity, comorbidity, medication, chronic pain, sleep disorders, nutritional status and loneliness were analyzed using regression logistic models. Multivariate regression logistic analysis showed that exercise (P = .019, odds ratio [OR] = 0.494, 95% confidence interval [CI]: 0.274-0.891), intellectual activity (P = .019, OR = 0.595, 95% CI: 0.380-0.932), medication use (P = .003, OR = 2.388, 95% CI: 1.339-4.258), chronic pain (P = .003, OR = 1.580, 95% CI: 1.013-2.465) and loneliness (P = .000, OR = 2.991, 95% CI: 1.728-5.175) were significantly associated with CF in community residents; however, only sedentary behavior (P = .013, OR = 3.851, 95% CI: 1.328-11.170) was significantly associated with CF in nursing home residents. Our findings suggest that nursing homes can effectively address many common risk factors for CF, including lack of exercise and intellectual activity, medication use, chronic pain, and loneliness, better than the community setting. Thus, residing in a nursing home is conducive to the intervention of CF.
Pirfenidone inhibits TGF‐β1‐induced metabolic reprogramming during epithelial‐mesenchymal transition in non‐small cell lung cancer

Abstract Metastasis is an important contributor to increased mortality rates in non‐small cell lung cancer (NSCLC). The TGF‐β signalling pathway plays a crucial role in facilitating tumour metastasis through epithelial‐mesenchymal transition (EMT). Glycolysis, a key metabolic process, is strongly correlated with NSCLC metastasis. Pirfenidone (PFD) has been shown to safely and effectively inhibit TGF‐β1 in patients with lung diseases. Furthermore, TGF‐β1 and glycolysis demonstrate an interdependent relationship within the tumour microenvironment. Our previous study demonstrated that PFD effectively inhibited glycolysis in NSCLC cells, prompting further investigation into its potential antitumour effects in this context. Therefore, the present study aims to investigate the potential antitumour effect of PFD in NSCLC and explore the relationship among TGF‐β1, glycolysis and EMT through further experimentation. The antitumour effects of PFD were evaluated using five different NSCLC cell lines and a xenograft tumour model. Notably, PFD demonstrated a significant antitumour effect specifically in highly glycolytic H1299 cells. To elucidate the underlying mechanism, we compared the efficacy of PFD after pretreatment with either TGF‐β1 or a TGF‐β receptor inhibitor (LY2109761). The energy metabolomics analysis of tumour tissue demonstrated that PFD, a chemosensitizing agent, reduced lactate and ATP production, thereby inhibiting glycolysis and exerting synergistic antineoplastic effects. Additionally, PFD combined with cisplatin targeted TGF‐β1 to inhibit glycolysis during EMT and enhanced the chemosensitization of A549 and H1299 cells. The magnitude of the anticancer effect exhibited by PFD was intricately linked to its metabolic properties.
Współczesny transport i sedymentacja żwirów w dolinie Dunajca

Recent transport and sedimentation of gravels in the Dunajec valley (western Carpathians) Variation in petrographic composition of gravel in the Dunajec River, as well as size, roundness and sphericity variation of granite pebbles are the subject of the present paper. The size and shape control of pebble orientation is described with a discussion on the mechanism of transport and deposition. The possibility of determining transport direction and estimating its, length is also presented.
Benthic biofilm controls on fine particle dynamics in streams

Benthic (streambed) biofilms metabolize a substantial fraction of particulate organic matter and nutrient inputs to streams. These microbial communities comprise a significant proportion of overall biomass in headwater streams, and they present a primary control on the transformation and export of labile organic carbon. Biofilm growth has been linked to enhanced fine particle deposition and retention, a feedback that confers a distinct advantage for the acquisition and utilization of energy sources. We quantified the influence of biofilm structure on fine particle deposition and resuspension in experimental stream mesocosms. Biofilms were grown in identical 3 m recirculating flumes over periods of 18–47 days to obtain a range of biofilm characteristics. Fluorescent, 8 µm particles were introduced to each flume, and their concentrations in the water column were monitored over a 30 min period. We measured particle concentrations using a flow cytometer and mesoscale (10 µm to 1 cm) biofilm structure using optical coherence tomography. Particle deposition‐resuspension dynamics were determined by fitting results to a stochastic mobile‐immobile model, which showed that retention timescales for particles within the biofilm‐covered streambeds followed a power‐law residence time distribution. Particle retention times increased with biofilm areal coverage, biofilm roughness, and mean biofilm height. Our findings suggest that biofilm structural parameters are key predictors of particle retention in streams and rivers.
Perceived and Received Social Support and Illness Acceptance Among Breast Cancer Patients: The Serial Mediation of Meaning-Making and Fear of Recurrence

Abstract Background and Purpose The literature indicates connections between social support and acceptance of a personal diagnosis of breast cancer, but these relationships are likely to be mediated due to numerous connections between social support and illness acceptance with meaning-making and fear of recurrence. We decided to investigate whether meaning-making and fear of recurrence serially mediated the relationship between perceived and received social support and illness acceptance. Methods The current research examined 246 adult women patients with a breast cancer diagnosis who were undergoing radiotherapy/chemotherapy treatment in oncological hospitals. This cross-sectional study based on a mediational model was reported according to the STROBE checklist. Results Our results supported the mediational model in which meaning-making and fear of recurrence serially mediated the relationship of both perceived and received social support with illness acceptance. Furthermore, the mediating power of meaning-making was more significant than the fear of recurrence. Conclusion Meaning structures and anxiety played an important mediating role in breast cancer patients. Finding additional meaning and goals and experiencing lower fear enables the patients to effectively make use of social support and accept their illness. Practice implications The current study identified factors that increase illness acceptance among breast cancer patients as it showed that patients can gain a greater understanding of the nature of their illness by becoming more aware of their own goals and values and reduce anxiety by learning about their current state of the illness.
Low Winter Soil Temperature Affets Summertime Nutrient Uptake Capacity and Growth Rate of Mountain Birch Seedlings in the Subarctic

Effects of different winter soil temperature on summertime growth rate of individual seedlings of mountain birch (Betula pubescens ssp. czerepanovii) were evaluated in an outdoor pot experiment in subarctic Sweden. The hypothesis tested was that low winter soil temperature could decrease growing-season nutrient uptake capacity and growth rate by injury of the root system; further, the root damage should stimulate growth of replacement roots, which should be reflected by increased summertime biomass allocation to roots. Mountain birch seedlings were exposed to two soil temperatures during wintertime by manipulation of snow depth that accumulated on top of the pots. Minimum soil temperature (hourly recordings) during winter was -1.7? C in the "protected" treatment (deep snow cover) and -10.5? C in the "exposed" treatment (thin snow cover). The treatments simulated the soil temperature conditions of a local mountain birch forest and heath site, respectively. During June and July, the relative growth rate (Ra) and nitrogen accumulation rate (RN) in the exposed treatment were lower compared to the protected treatment. In addition, the seedlings of the exposed treatment allocated a greater proportion of biomass to roots compared to the protected treatment. Thus, leaf growth was reduced in the exposed compared to the protected treatment. We concluded that lower winter temperature in soils can result in stronger root injury that stimulates the growth of replacement roots and reduces nutrient uptake capacity and growth rate during summer. In concert with other possible factors causing root disruption during winter, e.g., frequent freeze-thaw cycles, the mechanism identified here might be important for survival of tree seedlings in subarctic and alpine areas, especially near treelines. The implications are discussed specifically for mountain birch seedling growth and survival in treeless subarctic heath sites and above treelines in northern Europe.
Coyotes (Canis latrans) response to anthropogenic pressures on a heterogeneous landscape

Due to the extirpation of many large, native carnivores the coyote has become one of the most widespread and successful predators in North America. They are now considered apex predators in many ecosystems. For this reason, it is important to understand how they respond to natural and anthropogenic disturbances. For this study, ten coyotes were captured, fitted with GPS collars, and monitored for 18 months. By using GIS data from The Nature Conservancy and GPS data from the collars we were able to assess how coyote temporal activities and resource selection were affected by energy development and prescribed fires in the Tallgrass Prairie Preserve (TPP). Based on our data, it is clear coyotes strongly avoided anthropogenic structures on the landscape, but were only weakly affected by prescribed fires, and vegetation type. The coyotes on the nature preserve are also primarily nocturnal, which could be an indicator of temporal activity shifts due to anthropogenic pressures. Our data suggests that the behavior of this coyote population mirrors other studies that have evaluated behavior in relation to human presence. Coyotes represent an emerging shift in top predator species in prairie ecosystems; it is crucial to examine these species in order to understand the changes in behavioral ecology and how these changes affect the ecosystem in novel ways.
CPAP resumption after a first termination and impact on all-cause mortality in France

Extract Obstructive sleep apnoea (OSA) is the most common form of sleep disordered breathing, affecting nearly one billion individuals aged 30–69 years worldwide [1]. OSA is characterised by recurrent complete or partial pharyngeal collapse during sleep, resulting in intermittent hypoxia, intrathoracic pressure swings and arousal from sleep [2, 3]. Symptoms occurring as a direct consequence of OSA include snoring, nonrestorative sleep and excessive daytime sleepiness [2]. In addition, OSA is a risk factor for a variety of cardiovascular and metabolic comorbidities, including hypertension, atrial fibrillation and diabetes mellitus [2–8].
A novel unsupervised dynamic feature domain adaptation strategy for cross-individual myoelectric gesture recognition

Objective. Surface electromyography pattern recognition (sEMG-PR) is considered as a promising control method for human-machine interaction systems. However, the performance of a trained classifier would greatly degrade for novel users since sEMG signals are user-dependent and largely affected by a number of individual factors such as the quantity of subcutaneous fat and the skin impedance. Approach. To solve this issue, we proposed a novel unsupervised cross-individual motion recognition method that aligned sEMG features from different individuals by self-adaptive dimensional dynamic distribution adaptation (SD-DDA) in this study. In the method, both the distances of marginal and conditional distributions between source and target features were minimized through automatically selecting the optimal feature domain dimension by using a small amount of unlabeled target data. Main results. The effectiveness of the proposed method was tested on four different feature sets, and results showed that the average classification accuracy was improved by above 10% on our collected dataset with the best accuracy reached 90.4%. Compared to six kinds of classic transfer learning methods, the proposed method showed an outstanding performance with improvements of 3.2%-13.8%. Additionally, the proposed method achieved an approximate 9% improvement on a publicly available dataset. Significance. These results suggested that the proposed SD-DDA method is feasible for cross-individual motion intention recognition, which would provide help for the application of sEMG-PR based system.