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In order to explore the effect of electron beam irradiation sterilization on the quality of Panax notoginseng powder, the effects of different irradiation doses (0, 2, 4, 6, 8, 13 kGy) on the number of microorganisms, moisture content, total ash, alcohol-soluble extracts, active ingredients, the antioxidant capacity and fingerprint of Panax notoginseng powder were investigated. The results showed that electron beam irradiation could effectively kill microorganisms in Panax notoginseng powder, the D10 value of total aerobic microbial count was 2.04 kGy, and the number of microorganisms fell below the detection standard limit when the irradiation dose was 4 kGy. The antioxidant capacity was significantly improved (P

Natural killer cells (NKCs) are non-specific immune lymphocytes with diverse morphologies. Their broad killing effect on cancer cells has led to increased attention towards activating NKCs for anticancer immunotherapy. Consequently, understanding the motion characteristics of NKCs under different morphologies and modeling their collective dynamics under cancer cells has become crucial. However, tracking small NKCs in complex backgrounds poses significant challenges, and conventional industrial tracking algorithms often perform poorly on NKC tracking datasets. There remains a scarcity of research on NKC dynamics. In this paper, we utilize deep learning techniques to analyze the morphology of NKCs and their key points. After analyzing the shortcomings of common industrial multi-object tracking algorithms like DeepSORT in tracking natural killer cells, we propose Distance Cascade Matching and the Re-Search method to improve upon existing algorithms, yielding promising results. Through processing and tracking over 5000 frames of images, encompassing approximately 300,000 cells, we preliminarily explore the impact of NKCs’ cell morphology, temperature, and cancer cell environment on NKCs’ motion, along with conducting basic modeling. The main conclusions of this study are as follows: polarized cells are more likely to move along their polarization direction and exhibit stronger activity, and the maintenance of polarization makes them more likely to approach cancer cells; under equilibrium, NK cells display a Boltzmann distribution on the cancer cell surface.

Advanced Air Mobility (AAM) is a concept that is expected to transform the current air transportation system and provide more flexibility, agility, and accessibility by extending the operations to urban environments. This study focuses on flight test, integration, and analysis considerations for the feasibility of the future AAM concept and showcases the outputs of the Air Mobility Urban-Large Experimental Demonstration (AMU-LED) project demonstrations at Cranfield University. The purpose of the Cranfield demonstrations is to explore the integrated decentralized architecture of the AAM concept with layered airspace structure through various use cases within a co-simulation environment consisting of real and simulated standard-performing vehicle (SPV) and high-performing vehicle (HPV) flights, manned, and general aviation flights. Throughout the real and simulated flights, advanced U-space services are demonstrated and contingency management activities, including emergency operations and landing, are tested within the developed co-simulation environment. Moreover, flight tests are verified and validated through key performance indicator analysis, along with a social acceptance study. Future recommendations on relevant industrial and regulative activities are provided.

The development of the HSR station area is the result of the combined effect of the three elements of transport, place, and industry. This study introduces the industrial dimension and constructs the node-place-industry model to empirically analyze the development potential of station areas along the Hunan section of the Beijing–Guangzhou and the Shanghai–Kunming high-speed railway lines. The results show that (1) the development of the three spatial elements of the station area is mostly out of sync, and the node value has the highest fit with the integrated potential value of the station area; (2) there is a significant correlation between the magnitude of the combined potential of the station area and the site location, station class and time of development; (3) according to the results of the cluster analysis, it was found that most of the stations were in a state of disequilibrium, and the main reason was that the functional value of the place did not match with the value of industrial aggregation. In particular, the introduction of the industry dimension extends the NP model and establishes a tessellated analytical framework for station type classification, providing an interesting assessment tool for the sustainable development of transport hub areas.

The emerging field of Advanced Air Mobility (AAM) holds great promise for revolutionizing transportation by enabling the efficient, safe, and sustainable movement of people and goods in urban and regional environments. AAM encompasses a wide range of electric vertical take-off and landing (eVTOL) aircraft and infrastructure that support their operations. In this work, we first present a new airspace structure by considering different layers for standard-performing vehicles (SPVs) and high-performing vehicles (HPVs), new AAM services for accommodating such a structure, and a holistic contingency management concept for a safe and efficient traffic environment. We then identify the requirements and development process of a testing and simulation infrastructure for AAM demonstrations, which specifically aim to explore the decentralized architecture of the proposed concept and its use cases. To demonstrate the full capability of AAM, we develop an infrastructure that includes advanced U-space services, real and simulated platforms that are suitable for future AAM use cases such as air cargo delivery and air taxi operations, and a co-simulation environment that allows all of the AAM elements to interact with each other in harmony. The considered infrastructure is envisioned to be used in AAM integration-related efforts, especially those focusing on U-space service deployment over a complex traffic environment and those analyzing the interaction between the operator, the U-space service provider (USSP), and the air traffic controller (ATC).

AimWe performed a comparative study to investigate the efficacy of closed system transfer devices (CSTDs) on the safe handling of injectable hazardous drugs (HDs).MethodsThe exposure assessments of cyclophosphamide and cytarabine were performed under traditional or CSTDs. For preparation activity, chemotherapy contamination samples on protective equipment (such as gloves and masks) were collected. The contamination analysis was performed by liquid chromatography with tandem mass spectrometry (LC-MS/MS). A 6-item form was distributed monthly (form M1–M6, total 6 months) to assess the pharmacists' experience on ergonomics, encumbrance, and safety impression.ResultsTotally, 96 wiping samples were collected throughout the study. The numbers of contaminated cyclophosphamide samples reduced under CSTD were −37.8, −41.6, −67.7, −47.3, and −22.9% and cytarabine were −12.3, −12.1, −20.6, −69.6, and −56.7% for left countertop, right countertop, medial glass, air-intake vent and door handle, as compared to traditional devices. The reduction was similar to pharmacist devices, i.e., −48.2 and −50.0% for masks and gloves cyclophosphamide contamination, −18.0 and −42.4% for cytarabine. This novel system could improve contamination on dispensing table, transfer container, and dispensing basket by −16.6, −6.0, and −22.3% for cyclophosphamide and −28.5, −22.5, and −46.2% for cytarabine. A high level of satisfaction was consistently associated with ergonomics for CSTD during the compounding process. Meanwhile, a slightly decreased satisfaction on ergonomics, encumbrance, and safety impression was observed for the traditional system between M2 and M3.ConclusionClosed system transfer devices are offering progressively more effective alternatives to traditional ones and consequently decrease chemotherapy exposure risk on isolator surfaces.

Ascites is a typical symptom of liver cirrhosis that is caused by a variety of liver diseases. Ascites severely affects the life quality of patients and needs long-term treatment. 25a is a specific urea transporter inhibitor with a diuretic effect that does not disturb the electrolyte balance. In this study, we aimed to determine the therapeutic effect of 25a on ascites with a dimethylnitrosamine (DMN)-induced cirrhotic rat model. It was found that 100 mg/kg of 25a significantly increased the daily urine output by 60% to 97% and reduced the daily abdominal circumference change by 220% to 260% in cirrhotic rats with a water intake limitation. The 25a treatment kept the serum electrolyte levels within normal ranges in cirrhotic rats. The H&E and Masson staining of liver tissue showed that 25a did not change the cirrhotic degree. A serum biochemical examination showed that 25a did not improve the liver function in cirrhotic rats. A Western blot analysis showed that 25a did not change the expression of fibrosis-related marker protein α-SMA, but significantly decreased the expressions of type I collagen in the liver of cirrhotic rats, indicating that 25a did not reverse cirrhosis, but could slow the cirrhotic progression. These data indicated that 25a significantly reduced ascites via diuresis without an electrolyte imbalance in cirrhotic rats. Our study provides a proof of concept that urea transporter inhibitors might be developed as novel diuretics to treat cirrhotic ascites.

In the application of on-board chargers, LLC resonant converters need to work in multiple operating modes to achieve wide-range output requirements. For the most commonly used single-phase and three-phase LLC topologies, the time domain expressions of all possible operating modes are introduced to predict voltage and current behaviors. Based on the mode analysis, the 6-element boundary gain design method is proposed to design a wide gain range LLC resonant converter. The resonant current is used as the basis for ZVS judgment and the transformation trend of ZVS in the full operating range is given. Through reasonable distribution of the boost region and the buck region, the resonant devices can be designed more appropriately to achieve lower conduction loss and higher efficiency. Finally, the prototypes of 3.3kW and 6.6 kW are built to verify the theoretical analysis of the method in single-phase LLC and three-phase LLC.

Abstract We present a facile and effective method for fabrication of the localized surface plasmon resonance (LSPR) optical fiber sensor assisted by two polydopamine (PDA) layers with enhanced plasmonic sensing performance. The first PDA layer was self-polymerized onto the bare optical fiber to provide the catechol groups for the reduction from Ag+ to Ago through chelating and redox activity. As the reduction of Ag+ proceeds, Ag nanoparticles (NPs) were grown in-situ on the PDA layer with uniform distribution. The second PDA layer was applied to prevent Ag NPs from oxidating and achieve an improvement of LSPR signal. The PDA/Ag/PDA-based optical fiber sensor has an enhanced LSPR sensitivity of 961 nm/RIU and excellent oxidation resistance. The stable PDA/Ag/PDA-based LSPR sensor with high optical performance is very promising for future application in optical sensing field.

Streets are an important component of urban landscapes and reflect the image, quality of life, and vitality of public spaces. With the help of the Google Cityscapes urban dataset and the DeepLab-v3 deep learning model, we segmented panoramic images to obtain visual statistics, and analyzed the impact of built environment attributes on a restaurant’s popularity. The results show that restaurant reviews are affected by the density of traffic signs, flow of pedestrians, the bicycle slow-moving index, and variations in the terrain, among which the density of traffic signs has a significant negative correlation with the number of reviews. The most critical factor that affects ratings on restaurants’ food, indoor environment and service is pedestrian flow, followed by road walkability and bicycle slow-moving index, and then natural elements (sky openness, greening rate, and terrain), traffic-related factors (road network density and motor vehicle interference index), and artificial environment (such as the building rate), while people’s willingness to stay has a significant negative effect on ratings. The qualities of the built environment that affect per capita consumption include density of traffic signs, pedestrian flow, and degree of non-motorized design, where the density of traffic signs has the most significant effect.

This paper considers current personalized recommendation approaches based on computational social systems and then discusses their advantages and application environments. The most widely used recommendation algorithm, personalized advice based on collaborative filtering, is selected as the primary research focus. Some improvements in its application performance are analyzed. First, for the calculation of user similarity, the introduction of computational social system attributes can help to determine users’ neighbors more accurately. Second, computational social system strategies can be adopted to penalize popular items. Third, the network community, identity, and trust can be combined as there is a close relationship. Therefore, this paper proposes a new method that uses a computational social system, including a trust model based on community relationships, to improve the user similarity calculation accuracy to enhance personalized recommendation. Finally, the improved algorithm in this paper is tested on the online reading website dataset. The experimental results show that the enhanced collaborative filtering algorithm performs better than the traditional algorithm.

Social media and other online sites are being increasingly scrutinized as platforms for cyberbullying and hate speech. Many machine learning algorithms, such as support vector machines, have been adopted to create classification tools to identify and potentially filter patterns of negative speech. While effective for prediction, these methodologies yield models that are difficult to interpret. In addition, many studies focus on classifying comments as either negative or neutral, rather than further separating negative comments into subcategories. To address both of these concerns, we introduce a two-stage model for classifying text. With this model, we illustrate the use of internal lexicons, collections of words generated from a pre-classified training dataset of comments that are specific to several subcategories of negative comments. In the first stage, a machine learning algorithm classifies each comment as negative or neutral, or more generally target or nontarget. The second stage of model building leverages the internal lexicons (called L2CLs) to create features specific to each subcategory. These features, along with others, are then used in a random forest model to classify the comments into the subcategories of interest. We demonstrate our approach using two sets of data. Supplementary materials for this article are available online.

To compare the wear of conventional ultra-high molecular weight polyethylene (CUHMWPE) and highly cross-linked polyethylene (HCLPE) in hip revision with liner exchange fixed with original locking mechanism using analysis of history medical data.From Jan. 1, 2000, to Dec. 31, 2007, 26 patients (with 29 involved hips) underwent liner exchange revision fixed with the original locking mechanism due to wear of CUHMWPE and/or osteolysis. The mean age was 53 ± 9 years at the time of the primary total hip arthroplasty (THA) and 64 ± 9 years at the revision. The exchanged liners (Marathon, Depuy) were made of HCLPE. Annual X-rays were used to measure linear wear and osteolysis. The annual linear penetration was measured using PolyWare® software (Draftware Inc.). Annual Harris Hip Scores(HSS) were recorded.The mean follow-up time between the primary and revision THAs was 11 ± 2 years and 8 ± 2 years after revision. The mean Harris Hip Score(HHS) before primary THA, 1 year after primary THA, before revision and 1 year after revision was 43±5, 85±5, 71±6, 83±7 individually. The mean penetration of the CUHMWPE and HCLPE liners occurring in the first year were 0.44 ± 0.28 mm and 0.38 ± 0.14 mm, respectively (p = 0.211). The mean annual linear penetration of CUHMWPE and HCLPE from the second year onward were 0.29±0.09 mm and 0.08 ± 0.03 mm respectively (p