Search

Introduction Lung cancer is a significant cause of mortality, especially among smokers. Lung cancer and smoking are strongly associated, according to numerous studies. Methods Publications related to smoking and lung cancer were retrieved from the Science Citation Index Expanded (SCIE) database of the Web of Science Core Collection for the period 1994–2023. Descriptive and visual analyses were performed on the topics, journals, countries, institutions, authors, and citations of the publications. Results A total of 728 articles were retrieved from the Web of Science (WOS) SCIE database for the period January 1994 to December 2023, and the number of publications in the relevant literature demonstrated a progressive increase with time. A total of 647 articles were classified as experimental, while 81 were classified as reviews. The studies were published in 200 journals. The three journals that published the most articles were the American Journal of Epidemiology with 82 articles, Lung Cancer with 34 articles, and Cancer Causes and Control with 26 articles. The three most prolific countries were the United States (286 articles, 38.3%; 15879 citations), China (116 articles, 15.9%; 2911 citations), and France (75 articles, 10.3%; 3694 citations). The four most popular keywords in this field are ‘early cancer detection’, ‘experimental’, ‘CT’, and ‘survival rate’. Conclusions The findings of our study revealed key areas for focus in smoking and lung cancer research, having a view of supplying important data and motivation for further investigations.

In this study, we propose an intelligent drinking water controller based on programmable logic controller (PLC) specifically designed for pig breeding, which significantly reduces the water waste caused by the use of traditional drinking bowls by regulating the frequency and flow of water release. In addition, the drinking water system has a tracking and recording function, which can record the frequency and duration with which fattening pigs drink water in each pen in detail, thus providing farmers with a wealth of pig health and behavior data to help optimize breeding management decisions. In order to deeply analyze the effects of the intelligent drinking water controller on the growth, resources environment and economic benefits of fattening pigs under the condition of large-scale breeding, a single factor comparison experiment was designed.In this experiment, 84 fattening pigs were selected and distributed in 12 pens. Among them, six pens were randomly designated as the control group;the pig in this group used ordinary drinking water bowls for the water supply. The other six pens were designated as the experimental group;the pigs in this group used the intelligent drinking water controller. The experimental results showed that in the experimental group with the intelligent drinking water controller, the average daily water waste per finishing pig was only 0.186 L (p < 0.05), accounting for only 25.98% of the average daily water waste per pig in the control group (p < 0.05). In terms of water quality, the intelligent drinking water controller also showed better performance, and the performance indicators were effectively reduced, with the highest reduction reaching 39.86%, which greatly reduced water pollution. Compared with the traditional drinking bowl, the average daily weight increment of fattening pigs in the pen using the intelligent drinking water controller was increased by 0.02 kg. In terms of long-term benefits, the PLC-based intelligent drinking water controller significantly improves the economic returns of the farm and has a positive impact on pig health. The high frequency data collection of the pigs’ drinking habits through the intelligent drinking water controller can also provide data support for the subsequent establishment of a pig water-drinking behavior analysis model.

Gardenia fruit is a popular functional food and raw material for natural pigments. It comes from a wide range of sources, and different products sharing the same name are very common. Volatile organic compounds (VOCs) are important factors that affect the flavor and quality of gardenia fruit. This study used the Heracles NEO ultra-fast gas phase electronic nose with advanced odor analysis performance and high sensitivity to analyze six batches of gardenia fruit from different sources. This study analyzed the VOCs to find a way to quickly identify gardenia fruit. The results show that this method can accurately distinguish the odor characteristics of various gardenia fruit samples. The VOCs in gardenia fruit are mainly organic acid esters, ketones, and aldehyde compounds. By combining principal component analysis (PCA) and discriminant factor analysis (DFA), this study found that the hexanal content varied the most in different gardenia fruit samples. The VOCs allowed for the fruit samples to be grouped into two main categories. One fruit sample was quite different from the fruits of other origins. The results provide theoretical support for feasibility of rapid identification and quality control of gardenia fruit and related products in the future.

Olibanum is a resinous traditional Chinese medicine that is directly used as a powder. It is widely used in China and is often combined with other traditional Chinese medicine powders to promote blood circulation and relieve pain, as well as to treat rheumatism, rheumatoid arthritis, and osteoarthritis. Powdered traditional Chinese medicine is often easily contaminated by microorganisms and 60Co irradiation is one of the good sterilization methods. Volatile organic compounds (VOCs) are the main active ingredient of olibanum. The aim of this study was to validate the optimum doses of 60Co irradiation and its effect on VOCs. 60Co irradiation was applied in different doses of 0 kGy, 1.5 kGy, 3.0 kGy, and 6.0 kGy. Changes in VOCs were detected using gas chromatography ion mobility spectrometry. A total of 81 VOCs were identified. The odor fingerprint results showed that, with an increase in irradiation dose, most of the VOCs of olibanum changed. Through principal component analysis, cluster analysis, and partial least squares discriminant analysis, it was demonstrated that, at 1.5 kGy, the impact of radiation on the VOCs of olibanum was minimal, indicating this is a relatively good irradiation dose. This study provides a theoretical basis for the irradiation processing and quality control of resinous medicinal materials such as olibanum and it also provides a good reference for irradiation technology development and its application to functional foods, thus making it both significant from a research perspective and useful from an application perspective.

Heavy metal (HM) stress is a non-negligible abiotic stress that seriously restricts crop yield and quality, while the sprout stage is the most sensitive to stress and directly impacts the growth and development of the later stage. Melatonin (N-acetyl-5-methoxytryptamine), as an exogenous additive, enhances stress resistance due to its ability to oxidize and reduce. However, few reports on exogenous melatonin to tiger nuts under HM stress have explored whether exogenous melatonin enhances plants' resistance to heavy metals. Here, “Jisha 2″ was used as material, with a stress concentration of 5 mg/L and 100 μmol/L of CdCl2 to explore whether exogenous melatonin enhances plant resistance and molecular mechanism. The result revealed that stress limits growth, while melatonin alleviated the sprout damage under stress from the phenotypes. Moreover, stress-enhanced reactive oxygen species (ROS) accumulation and membrane lipid peroxidation, while melatonin-increased ROS reduce damage via the analysis of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) and malondialdehyde (MDA) content, hydrogen peroxide (H2O2), superoxide anion (O2-), and Electrolyte leakage (El). Further results indicated that HM leads to DNA damage while exogenous melatonin will repair the damage by analyzing random amplified polymorphic DNA (RAPD), DNA cross-linking, 8-hydroxy-20-deoxyguanine level, and relative density of apurinic sites. Furthermore, gene expression in the DNA-repaired pathway exhibited similar results. These results applied that exogenous melatonin released the hurt caused by HM stress, with DNA repair and ROS balance serving as candidate pathways. This study elucidated the mechanism of melatonin's influence and provided theoretical insights into its application in tiger nuts.

Herein, a series of SO42−-CeO2 catalysts were synthesized by a sol-gel method for the selective catalytic reduction of NO by NH3 (NH3-SCR). The introduction of SO42− endowed composite catalyst with higher catalytic activity than pure CeO2. In particular, 3% SC with 3% SO42− showed over 90% NO removal between 247 and 450 °C. SO42− promoted the increase of Ce3+ content, adsorbed oxygen, and surface acidity of the composites. Furthermore, the interaction between SO42− and cerium oxide induced the synergistic effect between acidic sites and redox sites in the NH3-SCR reaction. The introduction of SO42− significantly supported the increase of B-acid and the enhancement of l-acid sites, and promoted the NH3-SCR reaction to follow both Eley-Rideal and Langmuir-Hinshelwood mechanisms.

Regional atmospheric environmental problems have become increasingly prominent due to continuous urbanization in China. In this study, the Weather Research and Forecasting (WRF) model coupled with the California Puff (CALPUFF) air quality model was applied to analyze the spatial distribution and inter-city transport of primary and secondary PM2.5 concentrations from vehicles in the Guanzhong Plain (GZP) in January 2019. The results show that the secondary PM2.5 concentration emitted by vehicles was more easily dispersed than primary PM2.5. The maximum hourly average concentrations of primary PM2.5, secondary inorganic aerosol (SIA), and secondary organic aerosol (SOA) were about 18, 9, and 2 µg/m3, respectively. Exhaust emission and secondary NO3− were the main contributors to the total PM2.5 concentration from vehicles, accounting for about 52% and 32%, respectively. The maximum contribution of vehicle emissions to the ambient PM2.5 concentration was about 19%. Inter-city transport contributed about 33% of the total PM2.5 concentration from vehicles in cities in the GZP on average. Among the PM2.5 components transported in each city, SIA was the most abundant, followed by primary PM2.5, and SOA was the least. These findings will provide valuable insights for mitigating the regional PM2.5 pollution caused by near-surface sources in urban agglomerations.

High-intensity human socioeconomic activities in Xi’an have caused fine particulate matter (PM2.5) pollution. Understanding the spatial and temporal patterns and key factors influencing PM2.5 concentration was the basic step for taking targeted measures. Thus, spatial analysis techniques are used to reveal the temporal and spatial distribution characteristics of PM2.5 in Xi’an over a long time series; wavelet analysis and Geo-detector models are applied to assess the strength of the association between meteorological and socio-economic conditions on PM2.5 concentrations. The results illustrated that the average PM2.5 concentration was 40.13 μg/m3 in 2004 and peaked at 62.06 μg/m3 in 2011, before failing to 38.77 μg/m3 by 2018. The PM2.5 concentration distribution had a characteristic of high in winter and autumn but low in spring and summer, presenting a U-shaped profile. The main distribution of PM2.5 concentrations was oriented in a northeast-southwest direction, with obvious spatial autocorrelation and spatial aggregation characteristics. The resonance cycles of the meteorological and socioeconomic elements and PM2.5 concentrations were synchronous and divergent at different scales. U-wind was the influencing factor on PM2.5 concentration with a positive correlation coefficient of 0.9. Before 2011, the interaction of temperature (Tem) and relative humidity (RH) had the greatest impact on PM2.5 concentrations. Additionally, the land use and cover change (LUCC) coupled with other factors had a large influence on PM2.5 concentrations. These relationships can shed new light on the underlying mechanisms of PM2.5 contamination at the city level, assisting relevant departments in developing effective PM2.5 pollution management strategies.

Electronic word-of-mouth (eWOM) influences consumers' purchase decisions, but few studies have investigated the antecedents that lead consumers to create different types of eWOM. From the perspective of social interactions, this research explored how two subtypes of pride not only compel consumers to create eWOM but also differently impact four types of eWOM and their mechanisms. Study 1 manipulated the pride state and found that authentic pride promoted positive eWOM and constructive eWOM, while hubristic pride promoted negative eWOM and destructive eWOM. Study 2 examined the effect of pride on eWOM at the trait level and tested the mediating effect of their use of social status pursuit strategy. Overall, this study increases the understanding of different types of eWOM and broadens the literature of the effect of pride and social status pursuit strategy in the context of consumption.

In order to study the ignition process and response characteristics of cast polymer-bonded explosives (PBX) under the action of friction, HMX-based cast PBX explosives were used to carry out friction ignition experiments at a 90° swing angle and obtain the critical ignition loading pressure was 3.7 MPa. Combined with the morphology characterization results of HMX-based cast PBX, the friction temperature rise process was numerically simulated at the macro and micro scale, and the ignition characteristics were judged. The accuracy of the numerical simulation results was ensured based on the experiment. Based on the thermal–mechanical coupling algorithm, the mechanical–thermal response of HMX-based cast PBX tablet under friction was analyzed from the macro scale. The results show that the maximum temperature rise is 55 °C, and the temperature rise of the whole tablet is not enough to ignite the explosive. Based on the random circle and morphology characterization results of tablet, the mesoscopic model of HMX-based cast PBX was constructed, and the microcrack friction formed after interface debonding was introduced into the model. The temperature rise process at the micro scale shows that HMX crystal particles can be ignited at a temperature of 619 K under 4 MPa hydraulic pressure loaded by friction sensitivity instrument. The main reason for friction ignition of HMX-based cast PBX is the friction hot spot generated by microcracks formed after interface damage of the tablet mesoscopic model, and the external friction heat between cast PBX tablet and sliding column has little effect on ignition. External friction affects the ignition of HMX-based cast PBX by influencing the formation of internal cracks and the stress at microcracks.

Drought stress, an important abiotic stress, has affected global agricultural production by limiting the yield and the quality of crops. Tiger nuts (Cyperus esculentus L.) are C4 crops in the Cyperaceae family, which have high-quality wholesome ingredients. However, data on mechanisms underlying the response of tiger nuts to drought stress are few. Here, the variety of Jisha 1 and 15% polyethylene glycol (PEG; a drought stress simulator) were used to study the mechanisms of stress response in tiger nuts. Our evaluation of the changes in physiological indicators such as electrolyte leakage (El), malondialdehyde (MDA), hydrogen peroxide (H2O2), superoxide anion (O2−) and activities of reactive oxygen species (ROS) showed that 12 h was the most suitable time point to harvest and analyze the response to drought stress. Thereafter, we performed transcriptome (RNA-Seq) analysis in the control (CK) and stress treatment groups and showed that there was a total of 1760 differentially expressed genes (DEGs). Gene Ontology (GO) analysis showed that the DEGs were enriched in abscisic acid (ABA) terms, and pathways such as starch and sucrose metabolism (ko00500), phenylpropanoid biosynthesis (ko00940) and plant hormone signal transduction (ko04075) were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, quantitative real-time PCR (qRT-PCR) analysis of the DEGs demonstrated an upregulation of ABA and lignin content, as well as enzyme activities in enriched pathways, which validated the RNA-Seq data. These results revealed the pathways and mechanisms adopted by the tiger nuts in response to drought stress.

Cyperus (Cyperus esculentus L.) is an edible perennial grass-like plant, which propagates exclusively with underground tubers. Its tubers are rich in starch (20–30%), fat (25–35%), sugar (10–20%), protein (10–15%) and dietary fiber (8–9%). In addition, the tubers also contain alkaloids, organic acids, vitamins (C and E), steroids, terpenoids and other active components. The contents of oleic acid and linoleic acid in Cyperus oil are very high, which have important medicinal value and health-promoting properties. Most of the extracts from the tubers, stems and leaves of Cyperus have allelopathic potential and antibacterial, antioxidant and insecticidal activities. In recent years, the planting area of Cyperus has increased significantly all over the world, especially in China and some other countries. This paper presents the current status of Cyperus and the recent trend in research in this area. Published reports on its nutritional contents, active ingredients, medicinal efficacy, antibacterial activity and allelopathic potential were also reviewed.

Automatic detection of tomato leaf spot disease is essential for control and loss reduction. Traditional algorithms face challenges such as large amount of data, multiple training and heavy computation. In this study, a lightweight shared Siamese neural network method was proposed for tomato leaf disease identification, which is suitable for resource‐limited environments. Experiments on Plant‐Village, Taiwan and Taiwan ++ datasets show that the accuracy fluctuates very little even when trained with only 60% of the data, which confirms the effectiveness of the proposed method in the small data environment. In addition, compared with the mainstream algorithms, it improves the accuracy by up to 35.3%on Plant‐Village and two Taiwan datasets respectively. The experimental results also show that the proposed method still performs well when the data is imbalanced and the sample size is small. [ABSTRACT FROM AUTHOR]

Iron phthalocyanine (FePc) with an ideal N-coordinated environment has been regarded as a promising catalyst for the oxygen reduction reaction (ORR). However, its self-aggregation and inferior stability remain to be solved for further application. Herein, poly-FePc-based hyper-crosslinked polymers with tetrathiafulvalene (TTF) modification (named pFePc-TTF) are innovatively constructed and applied as an efficient ORR catalyst for aluminum–air batteries (AABs). Thanks to the donor (TTF)–acceptor (FePc) effect, the resultant pFePc-TTF catalyst exhibits satisfactory ORR activity with a half-wave potential of 0.90 V, a four-electron transfer process, methanol tolerance, and excellent stability in alkaline electrolytes. The improved electrocatalytic performance might be ascribed to the introduction of TTF as an electron donor, which effectively modulates the electron distribution of the Fe atom and optimizes the absorption energy of intermediate species. As expected, both liquid AABs and all-solid-state flexible AABs equipped with pFePc-TTF display outstanding battery performance in comparison to those equipped with commercial Pt/C. This novel metal macrocycle-based compound provides an effective strategy for the design of efficient and durable ORR catalysts for energy-related applications. [ABSTRACT FROM AUTHOR]

The accumulation and deposition of beta-amyloid (Aß) are key neuropathological hallmarks of Alzheimer's disease (AD). PARP16, a Poly(ADP-ribose) polymerase, is a known tail-anchored endoplasmic reticulum (ER) transmembrane protein that transduces ER stress during pathological processes. Here, we found that PARP16 was significantly increased in the hippocampi and cortices of APPswe/PS1dE9 (APP/PS1) mice and hippocampal neuronal HT22 cells exposed to Aß, suggesting a positive correlation between the progression of AD pathology and the overexpression of PARP16. To define the effect of PARP16 on AD progression, adeno-associated virus mediated-PARP16 knockdown was used in APP/PS1 mice to investigate the role of PARP16 in spatial memory, amyloid burden, and neuroinflammation. Knockdown of PARP16 partly attenuated impaired spatial memory, as indicated by the Morris water maze test, and decreased amyloid deposition, neuronal apoptosis, and the production of inflammatory cytokines in the brains of APP/PS1 mice. In vitro experiments demonstrated that the knockdown of PARP16 expression rescued neuronal damage and ER stress triggered by Aß. Furthermore, we discovered that intracellular PARP16 acts as an RNA-binding protein that regulates the mRNA stability of amyloid precursor protein (APP) and protects targeted APP from degradation, thereby increasing APP levels and AD pathology. Our findings revealed an unanticipated role of PARP16 in the pathogenesis of AD, and at least in part, its association with increased APP mRNA stability. [ABSTRACT FROM AUTHOR]

Timely and accurate identification of track foreign body intrusion is of great significance for maintaining the safety of railway running. Object detection technology based on deep learning can be used to judge the foreign body in the track running area. However, the general target detection technology cannot recognise the foreign object information in complex environment, which has a certain hysteresis. In this study, adaptive adjustment is made to the algorithm according to the limited area in the railway special scene. A new Recurrent Attention Convolutional Neural Network and adaptive particle swarm fusion network is proposed. Produced in the process of image classification and regional sampling information loss, by introducing attention study under the multi‐scale recursive fusion, each scale is a network of target recognition and attention network, starting from the full image, continuously put forward attention area, and as input to realise detection to the next dimension positioning; With the help of adaptive particle swarm optimisation algorithm, the feature information at different levels is fused, and the high‐attention region is generated by continuous recursive clipping from rough to fine, The mutual enhancement of target area detection and fine‐grained features is realised. Experiments conducted by the author in Railway data set showed that its target detection accuracy reached 84.2%. Compared with other existing models, the relative accuracy gain was 10.6% and 8.1%, respectively, and the maximum gain was 6.2% compared with the self‐ablation experiment. [ABSTRACT FROM AUTHOR]

Joint optimization of maintenance and lot-sizing-related operations offers significant benefits for businesses. This research studies the joint optimization of non-cyclical preventive maintenance and capacitated lot-sizing with lost sales. The objective is to determine the optimal lot size in each period, decide the optimal preventive maintenance for servicing machines over a planning horizon, and minimize the total cost related to service, operation, setup, production, inventory, and lost sales. An innovative framework is proposed to solve the problem, consisting of a novel mixed-integer linear programming formulation and an approximative production-planning algorithm combined with a multi-neighborhood descendent approach. Extensive experiments based on real-world data are conducted to verify the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]