Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined Antitumor Therapy Using In Situ Injectable Hydrogels Formulated with Albumin Nanoparticles Containing Indocyanine Green, Chlorin e6, and Perfluorocarbon in Hypoxic Tumors

Combined therapy using photothermal and photodynamic treatments together with chemotherapeutic agents is considered one of the most synergistic treatment protocols to ablate hypoxic tumors. Herein, we sought to fabricate an in situ-injectable PEG hydrogel system having such multifunctional effects. This PEG hydrogel was prepared with (i) nabTM-technique-based paclitaxel (PTX)-bound albumin nanoparticles with chlorin-e6 (Ce6)-conjugated bovine serum albumin (BSA-Ce6) and indocyanine green (ICG), named ICG/PTX/BSA-Ce6-NPs (~175 nm), and (ii) an albumin-stabilized perfluorocarbon (PFC) nano-emulsion (BSA-PFC-NEs; ~320 nm). This multifunctional PEG hydrogel induced moderate and severe hyperthermia (41−42 °C and >48 °C, respectively) at the target site under two different 808 nm laser irradiation protocols, and also induced efficient singlet oxygen (1O2) generation under 660 nm laser irradiation supplemented by oxygen produced by ultrasound-triggered PFC. Due to such multifunctionality, our PEG hydrogel formula displayed significantly enhanced killing of three-dimensional 4T1 cell spheroids and also suppressed the growth of xenografted 4T1 cell tumors in mice (tumor volume: 47.7 ± 11.6 and 63.4 ± 13.0 mm3 for photothermal and photodynamic treatment, respectively, vs. PBS group (805.9 ± 138.5 mm3), presumably based on sufficient generation of moderate heat as well as 1O2/O2 even under hypoxic conditions. Our PEG hydrogel formula also showed excellent hyperthermal efficacy (>50 °C), ablating the 4T1 tumors when the irradiation duration was extended and output intensity was increased. We expect that our multifunctional PEG hydrogel formula will become a prototype for ablation of otherwise poorly responsive hypoxic tumors.
Maintenance resources configuration model for complex system based on downtime

To improve effective operation rate of the manufacturing equipment and reduce the downtime,by taking the complex system as study object and considering integral influences of spare parts and repair equipments,aquantitative model of failure outage rate was established based on the configuration quantities of maintenance resources.Then,the optimized configuration was performed.According to hierarchy of the system,system failure outage rate model was established by two steps.Optimization model for the configuration quantities of the spare parts and repair equipments was proposed with constraints on failure outage rate,and was solved by using marginal analysis algorithm.Finally,an example was provided to verify the validity of the models.
AN ARTIFICIAL INTELLIGENCE APPROACH TO PREDICTION OF EXTREME EVENTS: THE CASE OF STORMS IN WESTERN FRANCE

Abstract. Storms represent an increased source of risk that affects human life, property, and the environment. Prediction of these events, however, is challenging due to their low frequency of occurrence. This paper proposed an artificial intelligence approach to address this challenge and predict storm characteristics and occurrence using a gated recurrent unit (GRU) neural network and a support vector machine (SVM). Historical weather and marine measurements collected from buoy data, as well as a database of storms containing all the extreme events that occurred in Brittany and Pays de la Loire regions, Western France, since 1996, were used. Firstly, GRU was used to predict the characteristics of storms (wind speed, pressure, humidity, temperature, and wave height). Then, SVM was introduced to identify storm-specific patterns and predict storm occurrence. The approach adopted leads to the prediction of storms and their characteristics, which could be used widely to reduce the awful consequences of these natural disasters by taking preventive measures.
The Anti-Epileptic Effects of Carbenoxolone In Vitro and In Vivo

Gap junctions (GJs) are intercellular junctions that allow the direct transfer of ions and small molecules between neighboring cells, and GJs between astrocytes play an important role in the development of various pathologies of the brain, including regulation of the pathological neuronal synchronization underlying epileptic seizures. Recently, we found that a pathological change is observed in astrocytes during the ictal and interictal phases of 4-aminopyridin (4-AP)-elicited epileptic activity in vitro, which was correlated with neuronal synchronization and extracellular epileptic electrical activity. This finding raises the question: Does this signal depend on GJs between astrocytes? In this study we investigated the effect of the GJ blocker, carbenoxolone (CBX), on epileptic activity in vitro and in vivo. Based on the results obtained, we came to the conclusion that the astrocytic syncytium formed by GJ-associated astrocytes, which is responsible for the regulation of potassium, affects the formation of epileptic activity in astrocytes in vitro and epileptic seizure onset. This effect is probably an important, but not the only, mechanism by which CBX suppresses epileptic activity. It is likely that the mechanisms of selective inhibition of GJs between astrocytes will show important translational benefits in anti-epileptic therapies.
Improving Communications to Increase Nonindustrial Private Forest Landowner (NIPF) Participation in Forest Certification Programs: A Case Study in Arkansas, USA

Despite the socioeconomic and ecological significance of the 10.4 million acres of forestland owned by nonindustrial private forest (NIPF) landowners across Arkansas (approximately 58% of forestland in the state), only 5% of this land is certified through the American Tree Farm System. As such, understanding how to improve the reach and content of communications to NIPF landowners is vital for expanding certification participation and subsequent improvement of forest management in Arkansas and throughout the southern United States. To explore current and optimal communications to increase NIPF participation, we employed Berlo’s source–message–channel–receiver (SMCR, 1960) model to analyze survey data collected from Arkansas NIPF landowners regarding their familiarity with, interest in, and information sources for forest certification programs. Our results indicate that NIPF landowners have a relatively low familiarity with certification programs and a low interest in adopting a certification program regardless of personal involvement throughout the certification process, the transparency of on-sight inspections to the public, and the requirements of forest management plans. However, positive correlations were found between self-reported familiarity with certification programs and the perceived usefulness of various information sources, indicating that communications to NIPF landowners have the ability to be influential. Furthermore, the results showed that the greatest perceived benefits to landowners were improved timber growth and health, better management actions, and environmentally-friendly timber harvesting, whereas the most concerning perceived drawbacks were increased record-keeping and paperwork as well as management costs. These findings will offer actionable insights into future messaging campaigns and provide directions for new approaches of reaching NIPF landowners to increase their participation in forest certification.
Relationships of Pelvic Vein Diameter and Reflux with Clinical Manifestations of Pelvic Venous Disorder

The causes of chronic pelvic pain (CPP) in patients with pelvic venous disorder (PeVD) are not completely understood. Various authors consider dilation of pelvic veins (PeVs) and pelvic venous reflux (PVR) as the main mechanisms underlying symptomatic forms of PeVD. The aim of this study was to assess relationships of pelvic vein dilation and PVR with clinical manifestations of PeVD. This non-randomized comparative cohort study included 80 female patients with PeVD who were allocated into two groups with symptomatic (n = 42) and asymptomatic (n = 38) forms of the disease. All patients underwent duplex scanning and single-photon emission computed tomography (SPECT) of PeVs with in vivo labeled red blood cells (RBCs). The PeV diameters, the presence, duration and pattern of PVR in the pelvic veins, as well as the coefficient of pelvic venous congestion (CPVC) were assessed. Two groups did not differ significantly in pelvic vein diameters (gonadal veins (GVs): 7.7 ± 1.3 vs. 8.5 ± 0.5 mm; parametrial veins (PVs): 9.8 ± 0.9 vs. 9.5 ± 0.9 mm; and uterine veins (UVs): 5.6 ± 0.2 vs. 5.5 ± 0.6 mm). Despite this, CPVC was significantly higher in symptomatic versus asymptomatic patients (1.9 ± 0.4 vs. 0.7 ± 0.2, respectively; p = 0.008). Symptomatic patients had type II or III PVR, while asymptomatic patients had type I PVR. The reflux duration was found to be significantly greater in symptomatic versus asymptomatic patients (median and interquartile range: 4.0 [3.0; 5.0] vs. 1.0 [0; 2.0] s for GVs, p = 0.008; 4.0 [3.0; 5.0] vs. 1.1 [1.0; 2.0] s for PVs, p = 0.007; and 2.0 [2.0; 3.0] vs. 1.0 [1.0; 2.0] s for UVs, p = 0.04). Linear correlation analysis revealed a strong positive relationship (Pearson’s r = 0.78; p = 0.007) of CPP with the PVR duration but not with vein diameter. The grade of PeV dilation may not be a determining factor in CPP development in patients with PeVD. The presence and duration of reflux in the pelvic veins were found to be predictors of the development of symptomatic PeVD.
Climate change and the future of the Olympic Winter Games: athlete and coach perspectives

ABSTRACT The International Olympic Committee recognizes the risks climate change pose to the Games and its responsibility to lead on climate action. Winter is changing at the past Olympic Winter Games (OWG) locations and an important perspective to understand climate change risk is that of the athletes who put themselves at risk during these mega-sport events. A survey of 339 elite athletes and coaches from 20 countries was used to define fair and safe conditions for snow sports competitions. The frequency of unfair-unsafe conditions has increased over the last 50 years across the 21 OWG host locations. The probability of unfair-unsafe conditions increases under all future climate change scenarios. In a low emission scenario aligned to the Paris Climate Agreement, the number of climate reliable hosts remains almost unchanged throughout the twenty-first century (nine in mid-century, eight in late century). The geography of the OWG changes radically if global emissions remain on the trajectory of the last two decades, leaving only one reliable host city by the end of the century. Athletes expressed trepidation over the future of their sport and the need for the sporting world to be a powerful force to inspire and accelerate climate action.
Identification of Traffic Accident Patterns via Cluster Analysis and Test Scenario Development for Autonomous Vehicles

Increased safety is one of the main motivations for traffic research and planning. The arduous task has two components: (i) improving the existing traffic policies based on a good understanding of risk factors related to trends in traffic accidents, and (ii) underpinning the emerging technologies that will advance the safety of vehicles. For the latter route, the introduction of connected and automated vehicles (CAVs) is a promising option as CAVs can potentially reduce the number of accidents. However, to reap their benefits, they need to be introduced in a safe manner and tested for their ability to safely deal with risky scenarios. However, the identification of such test scenarios remains a key challenge for the industry. This study contributes to both routes to increased safety by (i) analyzing UK’s STATS19 accident data to identify patterns in past traffic accidents, and (ii) utilizing this information to systematically generate scenarios for CAV testing. For task (i), the patterns in the accidents were identified in terms of static and time-dependent internal and external factors. For this purpose, the study employed a clustering algorithm, COOLCAT, which is particularly suitable for dealing with high-dimensional categorical data. Six different clusters emerged naturally as a result of the algorithm. To interpret the findings, we applied a frequency analysis to each cluster. The frequency tests showed that in each cluster, certain distinct real-world situations were represented more significantly compared to the non-clustered reference case, which are the markers of each cluster. The second task (ii) complemented the first task by synthesizing the relationships between attributes. This was done by association rule mining using the market basket analysis approach. The method enabled us to develop, drawing from the characteristics of the clusters, non-trivial test scenarios that can be used in the testing of CAVs, especially in virtual testing.
The Pretreatment Controlling Nutritional Status Score in Ovarian Cancer: Influence on Prognosis, Surgical Outcome, and Postoperative Complication Rate

Abstract Introduction The Controlling Nutritional (CONUT) Status score is an established predictor of impaired prognosis in patients with solid tumors. The aim of this study was to investigate the prognostic value of the CONUT score for overall survival and perioperative complication rates in patients with epithelial ovarian cancer. Patients In this retrospective study we assessed the data of 337 consecutive patients with ovarian cancer. The CONUT score was associated with surgical outcome, postoperative complications and clinicopathological parameters. We used univariate log-rank test and multivariable Cox regression models to evaluate the association between pretreatment CONUT scores and survival. Results A low CONUT score (0 – 2) was associated with an early FIGO stage (p = 0.004), complete tumor resection (p < 0.001), less neoadjuvant chemotherapy (p = 0.017) and other histologies than serous cystadenocarcinoma (p = 0.006). Postoperative complications were observed in 51.4% and 60.5% of patients with a CONUT score of 0 – 2 and a score > 2, respectively (p = 0.161). A shorter overall survival was observed in patients with a CONUT score > 2 compared to patients with a low CONUT score, with 5-year overall survival rates of 31.5% and 58.7%, respectively (p < 0.001). In multivariable analysis, both advanced age (p < 0.001) and FIGO stage (p < 0.001), residual disease (p < 0.001) and a high CONUT score (p = 0.048) were independently associated with unfavorable overall survival. Conclusion Pretreatment CONUT score is an independent prognostic marker for overall survival and associated with successful surgery. Patients with a high CONUT score might benefit from pretreatment nutritional intervention.
Feed Forward Fuzzy-PI Pitch-control for Large-scale Wind Turbines

A dynamical model of wind turbine has been built.Based on analyzing characteristics of the model and requisitions of pitch control,an approach,combining dynamical feed forward and fuzzy-PI,is being presented.Simulation results of the control system with the model considering trailing vortex shows more strong anti-interference capability and more effective than traditional PI method.
Technology solutions for interpreters: the VIP system

Interpreting technologies have abruptly entered the profession in recent years. However, technology still remains a relatively marginal topic of academic debate, although interest in developing tailor-made solutions for interpreters has risen sharply. This paper presents the VIP system, one of the research outputs of the homonymous project VIP - Voice-text Integrated system for interPreters, and its continuation (VIP II). More specifically, a technology-based terminology workflow for simultaneous interpretation is presented.
High-frequency Measurement and Calculation Study of Systematic Errors of High-rolling Projectile Roll Angle Based on a Combination of MR /GNSS

In order to study the systematic errors of MR /GNSS measurement system and improve its measuring frequency,a high-frequency measuring method for the projectile roll angle and angular rate,which is based on the assumptions of small angle-of-attack and single axis rotation,is established by using the flight characteristics of high-spin projectile. The systematic error equations of roll angle and angular rate are derived. The real-time systematic error of this combined measuring system in the global scope is calculated by establishing the simulation model with pitch angle as a variable. The results of 6-DOF exterior ballistic simulation show that the overall roll angle error is less than ± 5° and the angular rate error is less than ± 5° /s after the region of smaller angle between projectile axis and geomagnetic vector is excluded.In the condition of medium or small launching angle,the roll angle calculation method based on MR /GNSS can meet the needs of high-frequency and high-accuracy roll angle measurement for the high-spin projectile.
Multi‐defect segmentation from façade images using balanced copy–paste method

Façade defect is an unavoidable and considerable problem to existing buildings and can cause great influence to building owners. The traditional manual façade inspection method is costly, inefficient, and unsafe. Although recent studies achieved the classification of façade defects from images, pixel‐level façade defect segmentation has not been tackled. Therefore, this study proposed and implemented a balanced copy–paste method with the Mask Region‐based Convolutional Neural Network (Mask R‐CNN) model to realize automatic detection and segmentation of façade defects. The proposed balanced copy–paste method was able to improve the recognition accuracy for minority classes and small objects. The proposed method was applied to a façade defect dataset with 2286 images that contained six common categories of defects. Comparisons with three other methods demonstrated that the proposed method could achieve the highest accuracy in defect detection (mean average precision (mAP) = 33.33) and segmentation (mAP = 27.26). Furthermore, compared to the original dataset, the proposed method could result in the greatest accuracy improvement for both minority classes (31% in detection and 32% in segmentation) and small objects (23% in detection and 19% in segmentation). Compared to the traditional over‐sampling method and other methods based on algorithm level, the proposed method also showed higher computational efficiency.
A Deep CNN based Kaggle Contest Winning Model to Recognize Real-Time Facial Expression

In face-to-face interactions, facial expressions convey nonverbal details. Since the early 1990s, researchers have been increasingly interested in automatic facial expression recognition, which is critical in human-machine interfaces. Traditional machine learning methods often necessitate a time-consuming procedure for identifying features and yield mediocre results. We propose efficient deep CNNs that are capable of accurately interpreting the semantic information available in faces without the need for hand-designing feature descriptors in an automated manner in this research paper, which makes use of recent advances in deep learning. We employ a range of loss functions and training techniques in order to learn CNNs with high classification efficiency. Using the renowned Facial Expressions Recognition (FER-2013) collection of data from the Kaggle facial expression recognition contest, the experimental findings show that our suggested networks outperform state-of-the-art techniques. On the contrary, to the competition’s winning model, our proposed networks’ parameter count is drastically reduced, resulting in an increase in average output speed of a significant magnitude and making the suggested networks a better fit for real-time applications.
Ecological Efficiency of Urban Industrial Land in Metropolitan Areas: Evidence from China

Industrial land is an indispensable strategic resource in urban development that plays an indispensable role in ensuring the industrial space of urban construction and development. Measuring and analyzing the eco-efficiency of industrial land utilization (ECILU) can provide insights into how to maximize the input–output ratio of industrial land and ensure the sustainable development of land resources and economies. Based on the undesirable output slacks-based measure (SBM) model, choosing land, capital, and labor as input indicators, and the industrial added value and carbon emissions as desirable and undesirable output indicators, this study measured the ECILUs in 78 cities and 13 metropolitan areas in four Chinese major economic zones from 2007 to 2018, analyzed their spatial and temporal evolution characteristics and regional differences, and constructed a Tobit regression model to test the influence mechanism of each variable on the ECILUs in different regions. This has important theoretical and practical significance for the Chinese government in formulating relevant policies and realizing the green utilization of urban land in the future. Empirical results showed that the ECILUs in most cities were low and that the differences between regions were large. The ECILU in the Western Economic Zone was relatively high, followed by the Eastern, Central, and Northeastern Economic Zones. According to the ECILU value and urban synergy degree of each metropolitan area, this study divided the 13 metropolitan areas into four categories. The regression analysis results showed that the variables had different effects on the ECILUs of all cities and the four economic zones in China. It is suggested that all economic zones should reinforce the optimization of industrial structure, control industrial pollutant discharge, and solve the phenomenon of labor surplus. The Eastern Zone should maintain the growth of its economy while focusing on soil quality. The Central Zone should focus on the efficient use of infrastructure, and the Western, Northeastern, and Central Zones should balance the green coverage area and the industrial land area to ensure the efficient use of urban industrial land.
Nonlinear Dynamic Characteristics of Compound Planetary Gear Train Sets Based on Harmonic Balance Method

A purely rotational model of Ravigneaux compound planetary gear train sets including time-varying mesh stiffness,synthetic mesh errors and gear backlashes is developed to show the nonlinear dynamic behavior of the system with the action of multi-clearances.The gap function is expressed as describing function and harmonic balance method(HBM) is used to convert the differential equations to nonlinear algebraic equations,which is solved iteratively by single rank inverse Broyden method.The steady state response of fundamental frequency is obtained.The influences of gear backlashes,time-varying mesh stiffness and synthetic mesh errors are analyzed by changing the value of the parameter.It is showed from the research that multiple value and amplitude jump discontinuities are presented on the dynamic curves,there the impact phenomenon is reflected.Meanwhile the nonlinearity degree of the system is increased by the coupling of stiffness fluctuation,mesh errors and backlashes.The HBM based on describing function can be used for more complicated model to obtain the steady state response of fundamental frequency,which provides a method for deeply researching the dynamic behavior of compound planetary gear train sets.