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Background: Conflicting results have been reported on the association of dietary unsaturated fatty acids (UFAs) with longevity and cardiovascular health. Most previous studies have focused only on the amount of UFAs consumed, not the timing of intake. Methods: This prospective cohort study used data from 30,136 adults aged 18 years and older. Intakes of UFAs by meal time and types were assessed by a 24-h dietary recall for two days. The covariate-adjusted survey-weighted Cox proportional hazards models were performed to evaluate the associations of dietary total unsaturated fatty acid (TUFA), polyunsaturated fatty acid (PUFA), and monounsaturated fatty acid (MUFA) intakes throughout the day and three meals with mortality. Results: During a median of 10.0 years of follow-up, 4510 total deaths occurred. All-cause mortality decreased with increasing intakes at dinner of TUFA (HR: 0.87 [0.77–0.98]), PUFA (HR: 0.81 [0.73–0.91]), and MUFA (HR: 0.88 [0.77–0.99]). With an increased intake of PUFA at dinner, CVD mortality showed a decreasing trend. However, the inverted L-shaped non-linear trend in all-cause mortality was found with increasing intake at breakfast of TUFA (HR: 1.35 [1.17–1.57], Q3 vs. Q1), PUFA (HR: 1.30 [1.13–1.50]), and MUFA (HR: 1.28 [1.13–1.45]). Meanwhile, increased breakfast intake of UFAs was associated with increased CVD and heart disease mortality. Conclusions: Meal timing influences the association of UFAs with all-cause and CVD-related mortality.

Surface-enhanced Raman scattering (SERS) provides an alternative rapid detection method for pesticide residues in food, but fenvalerate possesses poor affinity to the novel metal substrate, thus restricting its analysis. To break this bottleneck, a SERS-active platform with an Ag/rGO composite structure was engineered using a facile method for fenvalerate detection. Ag nanoparticles with a 60 nm diameter can grow evenly on the top and bottom of rGO layers under intense ultrasonic oscillation, and rGO in hybrid material acts as an ideal hotspot holder between the gaps of Ag nanoparticles, not only allowing the interaction area to be enhanced both electromagnetically and chemically but also enabling the capture and enrichment of fenvalerate pesticide molecules into the “hotspot” area to improve detection sensitivity. Ag/rGO composite substrate possesses superior SERS performance with an ultralow detectable concentration of 4-aminothiophenol (10−10 M) and good reproducibility, endowing the material with a better enhancement effect than pure Ag nanoparticles. When used as the SERS substrate for fenvalerate detection, Ag/rGO composite material showed excellent performance in both experiments and theoretical calculation, with the limit of detection (LOD) of fenvalerate being as low as 1.69 × 10−5 mg/kg and a detection model with an R2 of 99.2%, demonstrating its exciting potential as a SERS substrate for pesticides detection.

The advancement of unmanned aerial vehicles (UAVs) enables early detection of numerous disasters. Efforts have been made to automate the monitoring of data from UAVs, with machine learning methods recently attracting significant interest. These solutions often face challenges with high computational costs and energy usage. Conventionally, data from UAVs are processed using cloud computing, where they are sent to the cloud for analysis. However, this method might not meet the real-time needs of disaster relief scenarios. In contrast, edge computing provides real-time processing at the site but still struggles with computational and energy efficiency issues. To overcome these obstacles and enhance resource utilization, this paper presents a convolutional neural network (CNN) model with an early exit mechanism designed for fire detection in UAVs. This model is implemented using TSMC 40 nm CMOS technology, which aids in hardware acceleration. Notably, the neural network has a modest parameter count of 11.2 k. In the hardware computation part, the CNN circuit completes fire detection in approximately 230,000 cycles. Power-gating techniques are also used to turn off inactive memory, contributing to reduced power consumption. The experimental results show that this neural network reaches a maximum accuracy of 81.49% in the hardware implementation stage. After automatic layout and routing, the CNN hardware accelerator can operate at 300 MHz, consuming 117 mW of power.

The diamondback moth, Plutella xylostella L. (Lepidoptera: Plutellidae), is a cosmopolitan horticultural pest that is undergoing a fast, climate-driven range expansion. Its wide geographic distribution, pest status, and high incidence of insecticide resistance are directly tied to long-distance migration. Wingbeat frequency (WBF) is a key aspect of P. xylostella migratory behavior, but has received limited scientific attention. Here, we investigated the effects of environmental parameters, age, adult nutrition, and sex on P. xylostella WBF. Across experimental regimes, WBF ranged from 31.39 Hz to 78.87 Hz. Over a 10–35 °C range, the WBF of both male and female moths increased with temperature up to 62.96 Hz. Though male WBF was unaffected by humidity, females exhibited the highest WBF at 15% relative humidity (RH). WBF was unaffected by adult age, but adult nutrition exerted important impacts. Specifically, the WBF of moths fed honey water (54.66 Hz) was higher than that of water-fed individuals (49.42 Hz). Lastly, males consistently exhibited a higher WBF than females. By uncovering the biological and (nutritional) ecological determinants of diamondback moth flight, our work provides invaluable guidance to radar-based monitoring, migration forecasting, and the targeted deployment of preventative mitigation tactics.

In various industrial domains, machinery plays a pivotal role, with bearing failure standing out as the most prevalent cause of malfunction, contributing to approximately 41% to 44% of all operational breakdowns. To address this issue, this research employs a lightweight neural network, boasting a mere 8.69 K parameters, tailored for implementation on an FPGA (field-programmable gate array). By integrating an incremental network quantization approach and fixed-point operation techniques, substantial memory savings amounting to 63.49% are realized compared to conventional 32-bit floating-point operations. Moreover, when executed on an FPGA, this work facilitates real-time bearing condition detection at an impressive rate of 48,000 samples per second while operating on a minimal power budget of just 342 mW. Remarkably, this system achieves an accuracy level of 95.12%, showcasing its effectiveness in predictive maintenance and the prevention of costly machinery failures.

Inherited retinal dystrophies (IRDs) are a group of heterogeneous diseases caused by genetic mutations that specifically affect the function of the rod, cone, or bipolar cells in the retina. Electroretinography (ERG) is a diagnostic tool that measures the electrical activity of the retina in response to light stimuli, and it can help to determine the function of these cells. A normal ERG response consists of two waves, the a-wave and the b-wave, which reflect the activity of the photoreceptor cells and the bipolar and Muller cells, respectively. Despite the growing availability of next-generation sequencing (NGS) technology, identifying the precise genetic mutation causing an IRD can be challenging and costly. However, certain types of IRDs present with unique ERG features that can help guide genetic testing. By combining these ERG findings with other clinical information, such as on family history and retinal imaging, physicians can effectively narrow down the list of candidate genes to be sequenced, thereby reducing the cost of genetic testing. This review article focuses on certain types of IRDs with unique ERG features. We will discuss the pathophysiology and clinical presentation of, and ERG findings on, these disorders, emphasizing the unique role ERG plays in their diagnosis and genetic testing.

This paper introduces a one-dimensional convolutional neural network (CNN) hardware accelerator. It is crafted to conduct real-time assessments of bearing conditions using economical hardware components, implemented on a field-programmable gate array evaluation platform, negating the necessity to transfer data to a cloud-based server. The adoption of the down-sampling technique augments the visible time span of the signal in an image, thereby enhancing the accuracy of the bearing condition diagnosis. Furthermore, the proposed method of quaternary quantization enhances precision and shrinks the memory demand for the neural network model by an impressive 89%. Provided that the current signal data sampling rate stands at 64 K samples/s, the proposed design can accomplish real-time fault diagnosis at a clock frequency of 100 MHz. Impressively, the response duration of the proposed CNN hardware system is a mere 0.28 s, with the fault diagnosis precision reaching a remarkable 96.37%.

Metal–organic framework (MOF) compounds are centered on metal ions or metal ion clusters, forming lattices with a highly ordered periodic porous network structure by connecting organic ligands. As MOFs have the advantages of high porosity, large specific surface area, controllable pore size, etc., they are widely used in gas storage, catalysis, adsorption, separation and other fields. SERS substrate based on MOFs can not only improve the sensitivity of SERS analysis but also solve the problem of easy aggregation of substrate nanoparticles. By combining MOFs with SERS, SERS performance is further improved, and tremendous research progress has been made in recent years. In this review, three methods of preparing MOF-based SERS substrates are introduced, and the latest applications of MOF-based SERS substrates in biosensors, the environment, gases and medical treatments are discussed. Finally, the current status and prospects of MOF-based SERS analysis are summarized.

Silver particles have been widely used in SERS detection as an enhancement substrate. The large-scale synthesis of Ag particles with controllable size and shape is still a challenge. We demonstrate a high-throughput method for the preparation of monodisperse submicron silver particles using S-shaped microfluidic chips. Submicron silver particles were prepared by a simplified reduction method. By adjusting the concentration of the reducing agent ascorbic acid and the stabilizer PVP, the particle size and morphology could be controlled, obtaining a size distribution of 1–1.2 μm for flower-like silver particles and a size distribution of 0.5–0.7 μm for quasi-spherical silver particles. This microfluidic system can be used to fabricate submicron silver particles on a large scale, continuously and stably, with a production efficiency of around 1.73 mg/min. The synthesized submicron silver particles could realize ultra-sensitive SERS detection, and the lowest concentration of rhodamine 6G (R6G) that could be detected was 10−9 M.

Noises in the GPS vertical coordinate time series, mainly including the white and flicker noise, have been proven to impair the accuracy and reliability of GPS products. Various methods were adopted to weaken the white and flicker noises in the GPS time series, such as the complementary ensemble empirical mode decomposition (CEEMD), wavelet denoising (WD), and variational mode decomposition (VMD). However, a single method only works at a limited frequency band of the time series, and the corresponding denoising ability is insufficient, especially for the flicker noise. Hence, in this study, we try to build two combined methods: CEEMD & WD and VMD & WD, to weaken the flicker noise in the GPS positioning time series from the Crustal Movement Observation Network of China. First, we handled the original signal using CEEMD or VMD with the appropriate parameters. Then, the processed signal was further denoised by WD. The results show that the average flicker noise in the time series was reduced from 19.90 mm/year0.25 to 2.8 mm/year0.25. This relates to a reduction of 86% after applying the two methods to process the GPS data, which indicates our solutions outperform CEEMD by 6.84% and VMD by 16.88% in weakening the flicker noise, respectively. Those apparent decreases in the flicker noises for the two combined methods are attributed to the differences in the frequencies between the WD and the other two methods, which were verified by analyzing the power spectrum density (PSD). With the help of WD, CEEMD & WD and VMD & WD can identify more flicker noise hidden in the low-frequency signals obtained by CEEMD and VMD. Finally, we found that the two combined methods have almost identical effects on removing the flicker noise in the time series for 226 GPS stations in China, testified by the Wilcoxon rank sum test.

Silver products with high relief have become popular in the silver decoration industry. However, it is difficult to obtain these products through conventional processing at ambient temperature. The aim of this work is to solve this problem by increasing the deformation temperature. Detailed studies were conducted on the evolution of microstructure characteristics in bulk high-purity silver by electron backscatter diffraction (EBSD) to achieve high-relief applications at elevated temperatures. The high temperature sample is mainly composed of recrystallized and substructured grains, exhibiting a more stable state than the ambient temperature sample. More than 70% annealing twins are observed in the hot-working sample. They are characterized by the amount of Σ3n-type triple grain boundary junctions within large grain clusters formed by multiple twinning. These particular boundaries improve the intergranular corrosion resistance and degradation, which is significantly essential for high-purity silver jewelry exposed to sweat and air. The closed multi-coining processes at different temperatures were conducted subsequently. The performance of workpieces demonstrates that increasing the deformation temperature is a viable alternative for producing durable high-relief silver products.

Thiamethoxam, a nicotinic pesticide used worldwide, can cause great harm to the environment and even to human health, and aptamers, known as chemical antibodies, have high affinity and specificity for the target, as well as great potential in detecting small molecules such as pesticides. In this paper, we report a highly sensitive biosensor system for thiamethoxam residue detection based on aptamer technology. After 15 rounds of screening with the pressurized GO-SELEX technology, we found that the aptamer libraries of the 5th and 9th rounds showed high affinity by the capture method. Four candidate aptamers were obtained by high-throughput sequencing and secondary structure prediction. Among them, the aptamer named Thi-5R-18 from the 5th round was demonstrated to possess the highest affinity by isothermal titration calorimetry, with a dissociation constant (Kd) of 4.935 × 10−5 M. The results of molecular docking showed that thiamethoxam and Thi-5R-18 were combined with bases G-15, A-19, and T-71 through hydrogen bonding and π–π interaction.Thi-5R-18 was used as a recognition element to construct a AuNPs colorimetric aptasensor, achieving an ultralow detection limit of 0.37 nM. More importantly, this colorimetric aptasensor can be used for quantitative detection of thiamethoxam on tea leaves, with a recovery of 96.94%~105.86%. This study provides a highly sensitive biosensor for detection of thiamethoxam residue.

The detection of bifenthrin is closely related to the adsorption of SERS substrates. In this study, superparamagnetic Fe3O4@Au MNPs coated with GO were used to detect the adsorption and enrichment of bifenthrin molecules with benzene rings. Firstly, the thermal solvent method synthesized Fe3O4 magnetic nanoparticles (MNPs) with a particle size of ~250 nm. Next, polyethylene imide (PEI) was used as an intermediate layer to modify the surface of Fe3O4 to form a positively charged ultra-thin polymer middle layer. Next, the gold shell was developed by adsorption of ~20 nm AuNPs, without affecting the magnetic properties. Then, the additional amount of colloidal gold and GO on SERS performance was systematically studied. Using crystal violet (CV) as the probe, we investigated the SERS performance of composite nanomaterials. The lowest detected concentration reached 10−8 mol/L, confirming that the composite functional material had good SERS activity and magnetic properties. Finally, the substrate was used to detect bifenthrin in an acetone solution, and the lowest detection concentration was 10−8 mol/L. These results showed that the prepared GO/Fe3O4@Au MNPs were efficient SERS substrates that could detect bifenthrin pesticide residue with high sensitivity.

Micromelalopha troglodyta (Graeser) (Lepidoptera: Notodontidae) is a notorious pest of poplar. Coevolution with poplars rich in plant secondary metabolites prompts M. troglodyta to expand effective detoxification mechanisms against toxic plant secondary metabolites. Although glutathione S-transferases (GSTs) play an important role in xenobiotic detoxification in M. troglodyta, it is unclear how GSTs act in response to toxic secondary metabolites in poplar. In this study, five GST gene core promoters were accurately identified by a 5’ loss luciferase reporter assay, and the core promoters were significantly induced by two plant secondary metabolites in vitro. Two transcription factors, cap ‘n’ collar C (CncC) and aryl hydrocarbon receptor nuclear translocator (ARNT), were cloned in M. troglodyta. MtCncC and MtARNT clustered well with other insect CncCs and ARNTs, respectively. In addition, MtCncC and MtARNT could bind the MtGSTt1 promoter and strongly improve transcriptional activity, respectively. However, MtCncC and MtARNT had no regulatory function on the MtGSTz1 promoter. Our findings revealed the molecular mechanisms of the transcription factors MtCncC and MtARNT in regulating the GST genes of M. troglodyta. These results provide useful information for the control of M. troglodyta.

Constitutive models play a significant role in understanding the deformation behavior of materials and in optimizing the manufacturing process. In order to improve the reliability of calculation results, the high temperature flow behavior of TA31 titanium alloy obtained from an annealed hot-rolled plate has been investigated by a Gleeble-3500 thermo-mechanical simulator. The isothermal hot compression tests are conducted in the temperature range of 850 to 1050 °C and the strain rate range from 0.001 to 10 s−1 with a height reduction of 60%. The annealed TA31 shows a dynamic recovery characteristic during thermo-mechanical processing. The experimental data have been used to develop an Arrhenius-type constitutive model and a modified Johnson–Cook model under the consideration of coupling effect on strain, temperature, and strain rate, as well as the strain-softening phenomenon. The material parameters are determined by a global optimization method based on the initial values by means of a regression method. A comparation of the predicted results has been performed based on the modified Johnson–Cook model and those acquired from the Arrhenius-type model. The correlation coefficient and average absolute relative error of the modified Johnson–Cook model are 4.57% and 0.9945, respectively. However, when the optimization method has been applied, they are 15.77% and 0.9620 for the Arrhenius-type model, respectively. These results indicate that the modified Johnson–Cook model is more accurate and efficient in predicting the flow stress of annealed TA31 titanium alloy under a set of model material parameters. Furthermore, the simple mathematical expression of this model is helpful to incorporate it into the finite element software to obtain detailed and valuable information during the thermo-mechanical processing simulation for TA31 in further work.

A resistant strain (MRS) of Sitobion miscanthi was cultured by continuous selection with malathion for over 40 generations. The MRS exhibited 32.7-fold resistance to malathion compared to the susceptible strain (MSS) and 13.5-fold, 2.9-fold and 4.8-fold cross-resistance for omethoate, methomyl and beta-cypermethrin, respectively. However, no cross-resistance was found to imidacloprid in this resistant strain. The realized heritability for malathion resistance was 0.02. Inhibitors of esterase activity, both triphenyl phosphate (TPP) and S,S,S,-tributyl phosphorotrithioate (DEF) as synergists, exhibited significant synergism to malathion in the MRS strain, with 11.77-fold and 5.12-fold synergistic ratios, respectively, while piperonyl butoxide (PBO) and diethyl maleate (DEM) showed no significant synergism in the MRS strain. The biochemical assay indicated that carboxylesterase activity was higher in MRS than in MSS. These results suggest that the increase in esterase activity might play an important role in S. miscanthi resistance to malathion. Imidacloprid could be used as an alternative for malathion in the management of wheat aphid resistance.

Tissue inhibitors of metalloproteinases (TIMPs) play a crucial role in endogenous angiogenesis besides the regulation of matrix metalloproteinase (MMP) activity. Associations between TIMP-2 gene polymorphisms and the risk of retinopathy of prematurity (ROP) were examined. Premature infants born between 2009 and 2018 were included. Five single-nucleotide polymorphisms (SNPs) of TIMP-2 were analyzed with real-time polymerase chain reaction (PCR). Multivariate logistic regression was applied to model associations between TIMP-2 polymorphisms and ROP susceptibility and severity. The GA+AA genotype in individuals with the TIMP-2 polymorphism of rs12600817 was associated with a higher risk of ROP (odds ratio [OR]: 1.518, 95% confidence interval [CI]: 1.028–2.242) compared with their wild-type genotypes. The AA genotype (OR: 1.962, 95% CI: 1.023–3.762) and the AA+GA genotype (OR: 1.686, 95% CI: 1.030–2.762) in individuals with the rs12600817 polymorphism had higher risks of severe, treatment-requiring ROP relative to their wild-type counterparts. In patients with treatment-requiring ROP, the AG+GG genotypes in the TIMP-2 polymorphism of rs2889529 were correlated with the treatment response (p = 0.035). The TIMP-2 polymorphism of rs12600817 help in predicting ROP risks in preterm infants, while the polymorphism of rs2889529 can serve as a genetic marker in evaluating the ROP treatment response.

The Aphis gossypii is an important pest that can damage cotton plants and can cause a huge economic loss worldwide. Chemical control is a main method to manage this pest, but the cotton aphid resistance to insecticides has become a severe problem in the management of the cotton aphid. It is important to introduce a novel insecticide for rotational application with other insecticides. Broflanilide, as a meta-diamide insecticide with a special mode of action, showed high efficiency against lepidopterous larvae. However, we found that broflanilide possessed high insecticidal activity against the sap-sucking pest A. gossypii. The susceptibility of A. gossypii to broflanilide from 20 field populations in main cotton planting areas of China in 2021 was determined by the leaf-dipping method. LC50 values of broflanilide to A. gossypii ranged from 0.20 μg mL−1 to 1.48 μg mL−1. The susceptible baseline of A. gossypii to broflanilide was established with the LC50 value of 0.41 μg mL−1 and might be used to calculate the resistance ratio (RR) of cotton aphid population in broflanilide resistance monitoring. The RR value of field populations in China was from 0.49 to 3.61 in 2021. It suggested that the broflanilide may be a potential agent in the resistance management of A. gossypii to insecticides. These results are significantly useful for the rational chemical control of cotton aphids.

The resistance of cotton aphids to various forms of commonly used pesticides has seriously threatened the safety of the cotton production. Afidopyropen is a derivative of microbial metabolites with pyropene insecticide, which has been shown to be effective in the management of Aphis gossypii. Several field populations of Aphis gossypii were collected from the major cotton-producing regions of China from 2019 to 2021. The resistance of these populations to afidopyropen was estimated using the leaf-dipping method. The LC50 values of these field populations ranged from 0.005 to 0.591 mg a.i. L−1 in 2019, from 0.174 to 4.963 mg a.i. L−1 in 2020 and from 0.517 to 14.16 mg a.i. L−1 in 2021. The resistance ratios for all A. gossypii populations ranged from 0.03 to 3.97 in 2019, from 1.17 to 33.3 in 2020 and from 3.47 to 95.06 in 2021. The afidopyropen resistance exhibited an increasing trend in the field populations of Cangzhou, Binzhou, Yuncheng, Kuerle, Kuitun, Changji and Shawan from 2019 to 2021. This suggests that the resistance development of the cotton aphid to afidopyropen is inevitable. Therefore, it is necessary to rotate or mix afidopyropen with other insecticides in order to inhibit the development of afidopyropen resistance in field populations.

The combination of microfluidic technology and surface-enhanced Raman spectroscopy (SERS) has the advantages of being label-free, fingerprint spectroscopy, and high sensitivity, which giving the combination great potential for rapid trace-level biological and environmental analysis. In this review, we summarized the recent progress in these two fields, e.g., microfluidics and SERS, including the basic strategies of a simple and versatile microfluidic-SERS detection system and its wide-ranging applications. Moreover, we listed the main challenges and future directions of the microfluidic-SERS systems; proposed on-chip applications beyond SERS; developed a more efficient, more sensitive, and more convenient microfluidic-SERS system; and formed a more complete on-site real-time detection technology.

The variability and inhomogeneity of solar energy limits the development of solar heating systems (SHS) in many fields. In order to improve the utilization efficiency of SHS, this paper takes three typical cities (Xi’an, Dunhuang, Lhasa) as the research object, studies the operation state of SHS in student dormitory buildings, and puts forward a corresponding optimization strategy. The research shows that the reduction of water supply temperature will improve the operation efficiency and energy saving effect of a spontaneous combustion heat pump and that there is an optimal volume of heat storage water tank (HSWT), which can make the energy saving effect of SHS run better. The optimization of the SHS shows the water supply temperature is 35 °C, and the optimal volume of HSWT is 15 m3 in the “Resource-general area (Ⅲ)” represented by Xi’an, 25 m3 in the “Resource-rich area (Ⅱ)” represented by Dunhuang, and 40 m3 in the “Resource-richer area (Ⅰ)” represented by Lhasa. With the increase in the abundance of solar energy resources in the region, the optimal volume of HSWT also increases. Meanwhile, the solar energy contribution rate of the three regions in descending order is 61.3% (Lhasa), 32.8% (Dunhuang), and 25.9% (Xi’an). After optimization, the contribution of SHS increased by about 5%. The research results will help improve the efficiency of SHS in cold areas of China and make the system more efficient and energy efficient during operation.

Pesticide resistance in insects is an example of adaptive evolution occurring in pest species and is driven by the artificial introduction of pesticides. The diamondback moth (DBM), Plutella xylostella (Lepidoptera: Plutellidae), has evolved resistance to various insecticides. Understanding the genetic changes underpinning the resistance to pesticides is necessary for the implementation of pest control measures. We sequenced the genome of six resistant and six susceptible DBM individuals separately and inferred the genomic regions of greatest divergence between strains using FST and θπ. Among several genomic regions potentially related to insecticide resistance, CYP6B6-like was observed with significant divergence between the resistant and susceptible strains, with a missense mutation located near the substrate recognition site (SRS) and four SNPs in the promoter. To characterize the relative effects of directional selection via insecticide tolerance (‘strain’) as compared to acute exposure to insecticide (‘treatment’), four pairwise comparisons were carried out between libraries to determine the differentially expressed genes. Most resistance-related differentially expressed genes were identified from the comparison of the strains and enriched in pathways for exogenous detoxification including cytochrome P450 and the ABC transporter. Further confirmation came from the weighted gene co-expression network analysis, which indicated that genes in the significant module associated with chlorantraniliprole resistance were enriched in pathways for exogenous detoxification, and that CYP6B6-like represented a hub gene in the “darkred” module. Furthermore, RNAi knock-down of CYP6B6-like increases P. xylostella sensitivity to chlorantraniliprole. Our study thus provides a genetic foundation underlying selection for pesticide resistance and plausible mechanisms to explain fast evolved adaptation through genomic divergence and altered gene expression in insects.

In the sequential three-way decision model (S3WD), conditional probability and decision threshold pair are two key elements affecting the classification results. The classical model calculates the conditional probability based on the strict equivalence relationship, which limits its application in reality. In addition, little research has studied the relationship between the threshold change and its cause at different granularity levels. To deal with these deficiencies, we propose a novel sequential three-way decision model and apply it to medical diagnosis. Firstly, we propose two methods of calculating conditional probability based on similarity relation, which satisfies the property of symmetry. Then, we construct an S3WD model for a medical information system and use three different kinds of cost functions as the basis for modifying the threshold pair at each level. Subsequently, the rule of the decision threshold pair change is explored. Furthermore, two algorithms used for implementing the proposed S3WD model are introduced. Finally, extensive experiments are carried out to validate the feasibility and effectiveness of the proposed model, and the results show that the model can achieve better classification performance.

Background: Little is known about the role of dietary diversity changes in affecting cognitive function among older people. Therefore, we aimed to evaluate the associations between dietary diversity scores (DDS) changes with cognitive impairment among older adults in a large prospective cohort. Methods: Cognitive function was assessed using the Mini-Mental State Examination questionnaire at baseline and follow-up. A total of 9726 participants without Parkinson’s disease, dementia, or cognitive impairment were enrolled at baseline. Nine food groups were collected using simplified FFQ at baseline and follow-up surveys. Then nine food groups change patterns and DDS change patterns (overall, plant-based and animal-based) were assessed. The associations of above DDS changes patterns with subsequent cognitive impairment were evaluated. A multivariable-adjusted Cox proportional hazards model was used to estimate HRs and 95%CIs. Results: We documented 2805 cognitive impairments during 52,325 person-years of follow-up. Compared to high-to-high overall DDS change patterns, the multivariable adjusted HRs (95%CI) for high-to-medium, medium-to-medium, medium-to-low, low-to-medium and low-to-low DDS change patterns were 1.33 (1.12–1.57), 1.11 (0.94–1.32), 1.61 (1.39–1.86), 2.00 (1.66–2.40), 2.30 (1.90–2.78) and 2.80 (2.23–3.53), respectively. Compared with participants with stable DDS change pattern, those who in large improvement of DDS had a 13% lower risk of cognitive impairment (HRs, 0.87; 95%CI: 0.78–0.98). The associations of plant-based DDS, animal-based DDS, or nine food groups DDS change patterns with cognitive impairment were in a similar direction to the main result. Conclusions: Protective associations between maintaining high DDS and a reduced risk of cognitive impairment were observed. In contrast, lowering or maintaining a lower DDS increases the risk of cognitive impairment.

The instability of solar energy and its resource distribution characteristics make it difficult to judge its suitability in practical engineering applications, which hinders its promotion and application. In order to better promote the effective use of solar energy and promote the solar heating system, it is necessary to put forward a simple method of judging the suitability of the solar heating system for engineering application. This study puts forward “F, Q” as the basis for judging the suitability of solar heating systems built on the roof. Two types of public buildings, office buildings and three-star hotels, are taken as the research objects. DeST software is used to change the heating area of the building by superimposing floors to simulate the heat load of the building when the heating area changes. A dynamic simulation coupling model of solar heating system is established in the TRNSYS software to analyze the operating status of the system under all working conditions. The functional relationship between “F, Q” and solar energy guarantee rate is established, and the solar energy contribution rate is divided into three regions of F < 30%, 30% ≤ F ≤ 50%, and F > 50%. The evaluation standard of the building suitability of the solar energy heating system is established according to the scope of “F, Q” in different regions (An office building for, e.g., if the contribution rate of solar heating system is required to be greater than 50%, the “F” of these four areas should be greater than 0.11388, 0.15543, 0.10572, and 0.04511.), and the effectiveness of “F” is verified through actual cases verified by other scholars in the research. The method proposed in this paper is helpful to judge the suitability of solar heating systems in different regions and different types of conventional buildings, so as to better promote solar heating systems.

Chitinases are of great importance in chitin degradation and remodeling in insects. However, the genome-wide distribution of chitinase-like gene family in Bemsia tabaci, a destructive pest worldwide, is still elusive. With the help of bioinformatics, we annotated 14 genes that encode putative chitinase-like proteins, including ten chitinases (Cht), three imaginal disk growth factors (IDGF), and one endo-β-N-acetylglucosaminidase (ENGase) in the genome of the whitefly, B. tabaci. These genes were phylogenetically grouped into eight clades, among which 13 genes were classified in the glycoside hydrolase family 18 groups and one in the ENGase group. Afterwards, developmental expression analysis suggested that BtCht10, BtCht5, and BtCht7 were highly expressed in nymphal stages and exhibit similar expression patterns, implying their underlying role in nymph ecdysis. Notably, nymphs exhibited a lower rate of survival when challenged by dsRNA targeting these three genes via a nanomaterial-promoted RNAi method. In addition, silencing of BtCht10 significantly resulted in a longer duration of development compared to control nymphs. These results indicate a key role of BtCht10, BtCht5, and BtCht7 in B. tabaci nymph molting. Our research depicts the differences of chitinase-like family genes in structure and function and identified potential targets for RNAi-based whitefly management.

In order to reveal the formation mechanism of different garnets and its implications for the fluid evolution in the Laoshankou Fe-Cu-Au deposit in the northern margin of East Junggar (NW China), three types of garnet have been investigated in detail in this study. (1) Type 1 grossular, formed at Ca-silicate stage (stage I, the pre-mineralization stage), was replaced by Type 2 garnet and magnetite, and displays a compositional range of Grs44–53Adr44–53, which has relatively lower total REE (rare earth elements) contents (8.14–32.8 ppm) and markedly depleted LREE (light rare earth elements) with distinctive positive Eu anomaly (1.36–9.61). (2) Type 2 Al-rich andradite, formed at the early sub-stage of amphibole-epidote-magnetite stage (stage II, the main magnetite mineralization stage), can be divided into two sub-types, i.e., Type 2a and Type 2b. Type 2a garnets exhibit polysynthetic twinning and relatively narrow compositional variations of Adr63–66Grs31–34 with HREE-(heavy rare-earth elements) enrichment and positive Eu anomalies (3.22–3.69). Type 2b garnets own wide compositional variations of Adr55–77Grs21–43 with relatively higher REE contents (49.1–124 ppm), markedly depleted LREE and a distinctive positive Eu anomaly (2.11–4.61). (3) Type 3 andradite (Adr>91) associated with sulfide stage (stage III, the main copper-gold mineralization stage) is different from other types of garnets in Laoshankou, which are characterized by lowest total REE contents (1.66–91.1 ppm), flat HREE patterns, LREE-enrichment and the strongest positive Eu anomalies (3.31–45.48). Incorporation of REE into garnet is largely controlled by external factors, such as fluid chemistry, pH, ƒO2 and water-rock ratios as well as its crystal chemistry. Type 1 and 2 garnets mainly follow the creation of X2+ (e.g., Ca2+) site vacancy, e.g., [X2+]−3VIII[]+1VIII[REE3+]+2VIII. The REE3+ substitution mechanism for Type 3 garnet is the Na+-REE3+ coupled substitutions, e.g., [X2+]−2VIII[X+]+1VIII[REE3+]+1VIII, without the evaluation of the creation of site vacancy. The compositional variations from Type 1 to Type 3 garnet indicate significant differences of fluid compositions and physicochemical conditions, and can be used to trace the fluid–rock interaction and hydrothermal evolution of garnet. Type 1 grossular was formed by magmatic fluid under low water–rock ratios and ƒO2, and neutral pH environment by diffusion metasomatism in a nearly closed system with the preferential incorporation into the grossular of HREE. As the long fluid pore residence and continuing infiltration metasomatism under nearly closed-system conditions, fluids with high water/rock ratios were characterized by increased ƒO2, more active incorporation of Fe3+ and REE, and formed Type 2 Al-rich andradite. In contrast, Type 3 garnet formed by oxidizing magmatic fluid under a mildly acidic environment with highest ƒO2 and water–rock ratios, and was influenced by externally derived high salinity and Ca-rich fluids in an open system. Thus, the geochemical features of different types and generations of garnets in the Laoshankou deposit can provide important information of fluid evolution, revealing a transition from neutral magmatic fluid to oxidizing magmatic fluid with addition of external non-magmatic Ca-rich fluid from the Ca-silicate stage to the sulfide stage. The above proved the fluid evolution process further indicates that the Laoshankou deposit prefers to be an IOCG-like (iron oxide-copper-gold) deposit rather than a typical skarn deposit.

Not all features in many real-world applications, such as medical diagnosis and fraud detection, are available from the start. They are formed and individually flow over time. Online streaming feature selection (OSFS) has recently attracted much attention due to its ability to select the best feature subset with growing features. Rough set theory is widely used as an effective tool for feature selection, specifically the neighborhood rough set. However, the two main neighborhood relations, namely k-neighborhood and neighborhood, cannot efficiently deal with the uneven distribution of data. The traditional method of dependency calculation does not take into account the structure of neighborhood covering. In this study, a novel neighborhood relation combined with k-neighborhood and neighborhood relations is initially defined. Then, we propose a weighted dependency degree computation method considering the structure of the neighborhood relation. In addition, we propose a new OSFS approach named OSFS-KW considering the challenge of learning class imbalanced data. OSFS-KW has no adjustable parameters and pretraining requirements. The experimental results on 19 datasets demonstrate that OSFS-KW not only outperforms traditional methods but, also, exceeds the state-of-the-art OSFS approaches.

Plants accumulate phenolic compounds such as tannic acid to resist insect herbivores. The survival of insects exposed to toxic secondary metabolites depends on the detoxification metabolism mediated by limited groups of glutathione S-transferases (GSTs). Micromelalopha troglodyta (Graeser) (Lepidoptera: Notodontidae) is an important foliar pest of poplar trees. GSTs play an important role in xenobiotic detoxification in M. troglodyta. Five GST genes were identified in M. troglodyta and were classified into five different cytosolic GST classes, delta, omega, sigma, theta, and zeta. Real-time fluorescent quantitative polymerase chain reaction (qPCR) was used to determine the mRNA expression of the five cloned GSTs in the midguts and fat bodies of M. troglodyta. The mRNA expression of the five GSTs was significantly induced when M. troglodyta was exposed to tannic acid. To further understand the tannic acid regulatory cascade, the 5′-flanking promoter sequences of the five MtGSTs were isolated by genome walking methods, and the promoters were very active and induced by tannic acid. In summary, the induction of GST mRNA expression was due to the response of five MtGST promoters to tannic acid. Therefore, MtGST promoters play an important role in the regulation of GST transcription.

The main purpose of this study is to investigate the production behaviors of gas hydrate at site DK-2 in the Qilian Mountain permafrost using the novel five-spot well (5S) system by means of numerical simulation. The whole system is composed of several identical units, and each single unit consists of one injection well and four production wells. All the wells are placed horizontally in the hydrate deposit. The combination method of depressurization and thermal stimulation is employed for hydrate dissociation in the system. Simulation results show that favorable gas production and hydrate dissociation rates, gas-to-water ratio, and energy ratio can be acquired using this kind of multi-well system under suitable heat injection and depressurization driving forces, and the water production rate is manageable in the entire production process under current technology. In addition, another two kinds of two-spot well (2S) systems have also been employed for comparison. It is found that the 5S system will be more commercially profitable than the 2S configurations for gas production under the same operation conditions. Sensitivity analysis indicates that the gas production performance is dependent on the heat injection rate and the well spacing of the 5S system.