A portable hyperspectral sensor collects reflectance spectra in the 350-2500 nm range, allowing the identification of not only inorganic but also organiac materials. In this paper, a non-invasive and non-destructive characterization of pictorial binders was used. The results show that their main spectral differences are located between 1200-2400 nm. It is also indicated that when a binder is mixed with colorants, some modifications occur in respect to its original spectrum. In addition, the first derivative transformation of original spectra allows an easier identification of these organic binders, where the most discriminating regions are 1160-1250 nm and 1660-1800 nm.

Efficient evaluation of biotoxicity of organics is of vital significance to resource utilization and environmental protection. In this study, toxicity of 110 alcohol compounds to tadpoles of Rana temporaria is adopted as the dependent variable and 1388 physiochemical parameters (features) calculated by PCLIENT are used for representing each compound. A feature selection pipeline with three steps is developed to refine the feature subset: 282 features that significantly correlated with biotoxicity of chemical compounds are preliminarily selected via the maximum information coefficient (MIC); 138 descriptors that have positive contribution to the model’s performance are reserved after a support vector regression (SVR) based backward elimination; 18 descriptors are finally selected via a forward selection process that integrated minimal redundancy maximal relevance (mRMR), MIC and SVR. In terms of feature subsets with different numbers of variables, quantitative structure activity relationship (QSAR) models are built using multiple linear regression (MLR), partial least square regression (PLS) and SVR, respectively. The independent prediction evaluation index, Q2, increases from -74.787, 0.824 and 0.868 to 0.892, 0.878 and 0.940, for the three regression models, respectively. Results suggest that nonlinear feature selection methods involved in MIC and SVR can effectively eliminate irrelevant descriptors. SVR outperforms classical statistical models to QSAR modeling on high-dimensional data containing nonlinear relationship between features. The methods proposed in this study have a potential application in the QSAR research field such as biotoxicity compounds.

Detecting spoofing attacks on the positions of unmanned aerial vehicles (UAVs) within a swarm is challenging. Traditional methods relying solely on individually reported positions and pairwise distance measurements are ineffective in identifying the misbehavior of malicious UAVs. This paper presents a novel systematic structure designed to detect and mitigate spoofing attacks in UAV swarms. We formulate the problem of detecting malicious UAVs as a localization feasibility problem, leveraging the reported positions and distance measurements. To address this problem, we develop a semidefinite relaxation (SDR) approach, which reformulates the non-convex localization problem into a convex and tractable semidefinite program (SDP). Additionally, we propose two innovative algorithms that leverage the proximity of neighboring UAVs to identify malicious UAVs effectively. Simulations demonstrate the superior performance of our proposed approaches compared to existing benchmarks. Our methods exhibit robustness across various swarm networks, showcasing their effectiveness in detecting and mitigating spoofing attacks. Specifically, the detection success rate is improved by up to 65%, 55%, and 51% against distributed, collusion, and mixed attacks, respectively, compared to the benchmarks.

Abstract As an alternative type of tea product, tartary buckwheat tea (TBT) has become popular in the current market because of its rich taste, natural healthiness and convenience of use. Because sensory evaluation is easily affected by the individual differences and external factors that affect human assessors, the present study used intelligent sensory systems (electronic nose, electronic tongue and electronic eye) to analyze different types of TBT to establish a scientific basis for its quality characteristics. Results showed that obvious differences in color, aroma and taste were found among the different types of teas. The taste differences in the TBT were mainly acquired by the CTS sensor (saltiness) and ANS sensor (sweetness), with the greatest number of volatile substance was detected in the whole plant tea. Overall, intelligent sensory technology could accurately evaluate TBT thus providing the capability to meet the needs of different types of consumers and of different occasions.

Titanium dioxide (TiO2) is a kind of wide-bandgap semiconductor. Nano-TiO2 devices exhibit size-dependent and novel photoelectric performance due to their quantum limiting effect, high absorption coefficient, high surface-volume ratio, adjustable band gap, etc. Due to their excellent electronic performance, abundant presence, and high cost performance, they are widely used in various application fields such as memory, sensors, and photodiodes. This article provides an overview of the most recent developments in the application of nanostructured TiO2-based optoelectronic devices. Various complex devices are considered, such as sensors, photodetectors, light-emitting diodes (LEDs), storage applications, and field-effect transistors (FETs). This review of recent discoveries in TiO2-based optoelectronic devices, along with summary reviews and predictions, has important implications for the development of transitional metal oxides in optoelectronic applications for researchers.

Titanium dioxide (TiO2) is a kind of wide-bandgap semiconductor. Nano-TiO2 devices exhibit size-dependent and novel photoelectric performance due to their quantum limiting effect, high absorption coefficient, high surface-volume ratio, adjustable band gap, etc. Due to their excellent electronic performance, abundant presence, and high cost performance, they are widely used in various application fields such as memory, sensors, and photodiodes. This article provides an overview of the most recent developments in the application of nanostructured TiO2-based optoelectronic devices. Various complex devices are considered, such as sensors, photodetectors, light-emitting diodes (LEDs), storage applications, and field-effect transistors (FETs). This review of recent discoveries in TiO2-based optoelectronic devices, along with summary reviews and predictions, has important implications for the development of transitional metal oxides in optoelectronic applications for researchers.

Abstract Ginkgo biloba leaves are commonly used in traditional Chinese medicine. Owing to its wide distribution across China with varying geographical environments and climatic characteristics, G. biloba leaf products have different active ingredients and degrees of activities, which poses a challenge for quality control and standardization. We aimed to identify the key factors contributing to the quality of G. biloba based on assessment of anti-aging and antioxidative components. G. biloba leaf samples collected from 14 different regions in China were analyzed for antioxidant activities by the 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical scavenging assay, and the levels of terpene lactones and flavonoids were quantified by ultra-performance liquid chromatography-tandem mass spectroscopy and high performance liquid chromatography. Correlation analysis attributed the antioxidant activity of G. biloba leaf samples of different origins to isoginkgetin and ginkgetin, which also affected the matrix metalloproteinase-1 levels of fibroblasts, determined using enzyme-linked immunosorbent assay and reverse transcription-polymerase chain reaction. Therefore, appropriate quality control of a collected G. biloba sample could be achieved by determining the levels of isoginkgetin and ginkgetin as anti-aging and antioxidant components. The results further provide a foundation for the application of G. biloba leaves as an antioxidant raw material.

Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world’s highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.

BACKGROUND: Colorectal cancer is the third leading cause of cancer deaths worldwide. Given the recent increasing trends in colorectal cancer incidence globally, up-to-date information on the colorectal cancer burden could guide screening, early detection, and treatment strategies, and help effectively allocate resources. We examined the temporal patterns of the global, regional, and national burden of colorectal cancer and its risk factors in 204 countries and territories across the past three decades. METHODS: Estimates of incidence, mortality, and disability-adjusted life years (DALYs) for colorectal cancer were generated as a part of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019 by age, sex, and geographical location for the period 1990-2019. Mortality estimates were produced using the cause of death ensemble model. We also calculated DALYs attributable to risk factors that had evidence of causation with colorectal cancer. FINDINGS: Globally, between 1990 and 2019, colorectal cancer incident cases more than doubled, from 842 098 (95% uncertainty interval [UI] 810 408-868 574) to 2·17 million (2·00-2·34), and deaths increased from 518 126 (493 682-537 877) to 1·09 million (1·02-1·15). The global age-standardised incidence rate increased from 22·2 (95% UI 21·3-23·0) per 100 000 to 26·7 (24·6-28·9) per 100 000, whereas the age-standardised mortality rate decreased from 14·3 (13·5-14·9) per 100 000 to 13·7 (12·6-14·5) per 100 000 and the age-standardised DALY rate decreased from 308·5 (294·7-320·7) per 100 000 to 295·5 (275·2-313·0) per 100 000 from 1990 through 2019. Taiwan (province of China; 62·0 [48·9-80·0] per 100 000), Monaco (60·7 [48·5-73·6] per 100 000), and Andorra (56·6 [42·8-71·9] per 100 000) had the highest age-standardised incidence rates, while Greenland (31·4 [26·0-37·1] per 100 000), Brunei (30·3 [26·6-34·1] per 100 000), and Hungary (28·6 [23·6-34·0] per 100 000) had the highest age-standardised mortality rates. From 1990 through 2019, a substantial rise in incidence rates was observed in younger adults (age <50 years), particularly in high Socio-demographic Index (SDI) countries. Globally, a diet low in milk (15·6%), smoking (13·3%), a diet low in calcium (12·9%), and alcohol use (9·9%) were the main contributors to colorectal cancer DALYs in 2019. INTERPRETATION: The increase in incidence rates in people younger than 50 years requires vigilance from researchers, clinicians, and policy makers and a possible reconsideration of screening guidelines. The fast-rising burden in low SDI and middle SDI countries in Asia and Africa calls for colorectal cancer prevention approaches, greater awareness, and cost-effective screening and therapeutic options in these regions. FUNDING: Bill & Melinda Gates Foundation.

BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01-4·94) deaths and 105 million (95·0-116) DALYs for both sexes combined, representing 44·4% (41·3-48·4) of all cancer deaths and 42·0% (39·1-45·6) of all DALYs. There were 2·88 million (2·60-3·18) risk-attributable cancer deaths in males (50·6% [47·8-54·1] of all male cancer deaths) and 1·58 million (1·36-1·84) risk-attributable cancer deaths in females (36·3% [32·5-41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6-28·4) and DALYs by 16·8% (8·8-25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9-42·8] and 33·3% [25·8-42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. FUNDING: Bill & Melinda Gates Foundation.