Hierarchical multihead self-attention for time-series-based fault diagnosis

Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent years.However,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of training.To overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical process.First,a sliding window strategy is adopted to construct the normalized time-series dataset.Second,the HMSAN is developed to extract the time-relevant features from the time-series process data.It improves the basic self-attention model in both width and depth.With the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features.However,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis performance.With the hierarchical structure,the redundant information is reduced and the deep local time-related features are further extracted.Besides,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency.Finally,the effectiveness of the proposed method is demonstrated by two chemical cases.The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches.

Modeling urban redevelopment:A novel approach using time-series remote sensing data and machine learning

Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban studies and decisionmakers to foster sustainable urban development.Traditional mapping methods heavily depend on field surveys and subjective questionnaires,yielding less objective,reliable,and timely data.Recent advancements in Geographic Information Systems(GIS)and remote-sensing technologies have improved the identification and mapping of urban redevelopment through quantitative analysis using satellite-based observations.Nonetheless,challenges persist,particularly concerning accuracy and significant temporal delays.This study introduces a novel approach to modeling urban redevelopment,leveraging machine learning algorithms and remote-sensing data.This methodology can facilitate the accurate and timely identification of urban redevelopment activities.The study’s machine learning model can analyze time-series remote-sensing data to identify spatio-temporal and spectral patterns related to urban redevelopment.The model is thoroughly evaluated,and the results indicate that it can accurately capture the time-series patterns of urban redevelopment.This research’s findings are useful for evaluating urban demographic and economic changes,informing policymaking and urban planning,and contributing to sustainable urban development.The model can also serve as a foundation for future research on early-stage urban redevelopment detection and evaluation of the causes and impacts of urban redevelopment.

Missing Value Imputation for Radar-Derived Time-Series Tracks of Aerial Targets Based on Improved Self-Attention-Based Network

The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random missing(RM)that differs significantly from common missing patterns of RTT-AT.The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation.Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss.In this paper,a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed.Our model consists of two probabilistic sparse diagonal masking self-attention(PSDMSA)units and a weight fusion unit.It learns missing values by combining the representations outputted by the two units,aiming to minimize the difference between the missing values and their actual values.The PSDMSA units effectively capture temporal dependencies and attribute correlations between time steps,improving imputation quality.The weight fusion unit automatically updates the weights of the output representations from the two units to obtain a more accurate final representation.The experimental results indicate that,despite varying missing rates in the two missing patterns,our model consistently outperforms other methods in imputation performance and exhibits a low frequency of deviations in estimates for specific missing entries.Compared to the state-of-the-art autoregressive deep learning imputation model Bidirectional Recurrent Imputation for Time Series(BRITS),our proposed model reduces mean absolute error(MAE)by 31%~50%.Additionally,the model attains a training speed that is 4 to 8 times faster when compared to both BRITS and a standard Transformer model when trained on the same dataset.Finally,the findings from the ablation experiments demonstrate that the PSDMSA,the weight fusion unit,cascade network design,and imputation loss enhance imputation performance and confirm the efficacy of our design.

Seed Storability in Rice: Physiological Foundations, Molecular Mechanisms, and Applications in Breeding

Long-term storage of crop seeds is critical for the conservation of germplasm resources, ensuring food supply, and supporting sustainable production. Rice, as a major food staple, has a substantial stock for consumption and production worldwide. However, its food value and seed viability tend to decline during storage. Understanding the physiological responses and molecular mechanisms of aging tolerance forms the basis for enhancing seed storability in rice. This review outlines the latest progress in influential factors, evaluation methods, and identification indices of seed storability. It also discusses the physiological consequences, molecular mechanisms, and strategies for breeding aging-tolerant rice in detail. Finally, it highlights challenges in seed storability research that require future attention. This review offers a theoretical foundation and research direction for uncovering the mechanisms behind seed storability and breeding aging-tolerant rice.

Advances in Wireless,Batteryless,Implantable Electronics for Real‑Time,Continuous Physiological Monitoring

This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.

Physiological Mechanism of Exogenous Selenium in Alleviating Mercury Stress on Pakchoi(Brassica campestris L.)

The objective of this study was to explain the physiological mechanisms through which Na_(2)SeO_(3) mitigates the growth and developmental inhibition of pakchoi under HgCl_(2)stress.The results showed that treatment with HgCl_(2)(40 mg L^(−1))led to reduced biomass,dwarfing,root shortening,and root tip necrosis in pakchoi.Compared to control(CK),the activities of superoxide dismutase(SOD)and peroxidase(POD)in Hg treatment increased,and the content of malondialdehyde(MDA)also dramatically increased,which negatively impacted the growth of pakchoi.Low concentrations of Na_(2)SeO_(3)(0.2 mg L^(−1))significantly increased the content of soluble sugars compared with control,while chlorophyll,soluble proteins,free amino acids,and vitamin C had no significant changes.The results of the mixed treatments with HgCl_(2)and Na_(2)SeO_(3) suggested that selenium may be able to reduce the toxicity of mercury in pakchoi.The biomass,plant height,root length,chlorophyll content,soluble protein,other physiological indicators,and proline showed significant increases compared with the HgCl_(2)treatment.Additionally,the MDA content and mercury accumulation in pakchoi decreased.Our results revealed the antagonistic effects of selenium and mercury in pakchoi.Thus,a theoretical basis for studying pakchoi’s mercuryexcreted and selenium-rich cultivation technology was provided.

Artificial intelligence in physiological characteristics recognition for internet of things authentication

Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)systems.However,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral characteristics.Behavioral characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in practice.However,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate authentication.Thus,we review the literature on the use of AI in physiological characteristics recognition pub-lished after 2015.We use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their limitations.We also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.

Implantable Electrochemical Microsensors for In Vivo Monitoring of Animal Physiological Information

In vivo monitoring of animal physiological information plays a crucial role in promptly alerting humans to potential diseases in animals and aiding in the exploration of mechanisms underlying human diseases.Currently,implantable electrochemical microsensors have emerged as a prominent area of research.These microsensors not only fulfill the technical requirements for monitoring animal physiological information but also offer an ideal platform for integration.They have been extensively studied for their ability to monitor animal physiological information in a minimally invasive manner,characterized by their bloodless,painless features,and exceptional performance.The development of implantable electrochemical microsensors for in vivo monitoring of animal physiological information has witnessed significant scientific and technological advancements through dedicated efforts.This review commenced with a comprehensive discussion of the construction of microsensors,including the materials utilized and the methods employed for fabrication.Following this,we proceeded to explore the various implantation technologies employed for electrochemical microsensors.In addition,a comprehensive overview was provided of the various applications of implantable electrochemical microsensors,specifically in the monitoring of diseases and the investigation of disease mechanisms.Lastly,a concise conclusion was conducted on the recent advancements and significant obstacles pertaining to the practical implementation of implantable electrochemical microsensors.

Exogenous calcium enhances the physiological status and photosynthetic capacity of rose under drought stress

Drought(water shortage)can substantially limit the yield and economic value of rose plants(Rosa spp.).Here,we characterized the effect of exogenous calcium(Ca^(2+))on the antioxidant system and photosynthesis-related properties of rose under polyethylene glycol 6000(PEG6000)-induced drought stress.Chlorophyll levels,as well as leaf and root biomass,were significantly reduced by drought;drought also had a major effect on the enzymatic antioxidant system and increased concentrations of reactive oxygen species.Application of exogenous Ca^(2+)increased the net photosynthetic rate and stomatal conductance of leaves,enhanced water-use efficiency,and increased the length and width of stomata following exposure to drought.Organ-specific physiological responses were observed under different concentrations of Ca^(2+).Application of 5 mmol·L^(-1)Ca^(2+)promoted photosynthesis and antioxidant activity in the leaves,and application of 10 mmol·L^(-1)Ca^(2+)promoted antioxidant activity in the roots.Application of exogenous Ca^(2+)greatly enhanced the phenotype and photosynthetic capacity of potted rose plants following exposure to drought stress.Overall,our findings indicate that the application of exogenous Ca^(2+)enhances the drought resistance of roses by promoting physiological adaptation and that it could be used to aid the cultivation of rose plants.

Physiological Response Mechanism and Drought Resistance Evaluation of Passiflora edulis Sims under Drought Stress

In order to explore the response mechanism of Passiflora edulis Sims to drought stress,the changes in morpho-logical and physiological traits of Passiflora edulis Sims under different drought conditions were studied.A total of 7 germplasm resources of Passiflora edulis Sims were selected and tested under drought stress by the pot culture method under 4 treatment levels:75%–80%(Control,CK)of maximumfield water capacity,55%–60%(Light Drought,LD)of maximumfield water capacity,i.e.,mild drought,40%–45%(Moderate Drought,MD)of max-imumfield water capacity,i.e.,moderate drought and 30%–35%(Severe Drought,SD)of maximumfield water capacity,i.e.,severe drought.On the 40th day of drought treatment,13 indices,including seedling growth mor-phology,physiology,and biochemistry,were measured.The results showed that under drought stress,the height and ground diameter of P.edulis Sims gradually decreased with increasing drought stress,and there were signifi-cant differences in seedling height and ground diameter among the treatments.Drought stress significantly inhib-ited the growth of seven P.edulis Sims varieties.The contents of soluble sugar(SS),soluble protein(SP),proline(Pro),and other substances in P.edulis Sims basically increased with increasing drought stress.With the aggrava-tion of drought stress,the malondialdehyde(MDA)content of P.edulis Sims tended to increase to different degrees,the superoxide dismutase(SOD)activity and peroxidase(POD)activity both tended to increase atfirst and then decrease,and the change in catalase(CAT)activity mostly showed a gradual increasing trend.The con-tents of endogenous hormones in P.edulis Sims significantly differed under different degrees of drought stress.With the aggravation of drought stress,the abscisic acid(ABA)content of P.edulis Sims tended to increase,whereas the contents of gibberellin(GA),indoleacetic acid(IAA),and zeatin nucleoside(ZR)exhibited a down-ward trend.A comprehensive evaluation of the drought resistance of seven P.edulis Sims varieties was conducted based on the principal component analysis method,and the results showed that the drought resistance decreased in the order XH-BL>XH-TWZ>TN1>GH1>ZJ-MT>LP-LZ>DH-JW.

Physiological Analysis of Drought Resistance of Seven Cultivars Spring Wheat in Northern Regions of China

In order to determine the physiological mechanism of drought resistance of northern wheat in China,six drought resistant wheat and one sensitivity to drought wheat were planted in pots.They were subjected to drought treatment and normal water when the plants grew to the 3-leaf stage.Samples were collected at 10,20,30,and 40 days after the drought treatment,respectively.The electrical conductivity,photosynthetic parameters,chlorophyll fluorescence parameters,sugar content,proline content,protein content,and active oxygen scavenging enzyme activity of the plants were detected,and the agronomic traits of the wheat varieties were investigated at maturity.The results indicated that the phenotype and yield-related factors of Darkhan 144 changed little under the drought stress.The relative electrical conductivity of Kefeng 6 and Darkhan 166 was lower under the drought stress,and their cell membrane was less damaged.The Darkhan 144 and Darkhan 166 had higher drought resistance coefficients,and were the wheat varieties with stronger drought resistance.However,the physiological mechanisms of drought resistance of these three wheat were different:Darkhan 144 maintained a higher photosynthetic activity under the drought stress;Darkhan 166 maintained a higher protein content,photosynthetic activity and active oxygen scavenging enzyme activity.In addition,other drought-resistant varieties Kefeng 6,Kefeng 10 and Longmai 26 had a higher content of osmoregulatory substances under the drought stress.

Physiological and Transcriptome Analysis Illuminates the Molecular Mechanisms of the Drought Resistance Improved by Alginate Oligosaccharides in Triticum aestivum L.

Alginate oligosaccharides(AOS)enhance drought resistance in wheat(Triticum aestivum L.),but the definite mechanisms remain largely unknown.The physiological and transcriptome responses of wheat seedlings treated with AOS were analyzed under drought stress simulated with polyethylene glycol-6000.The results showed that AOS promoted the growth of wheat seedlings and reduced oxidative damage by improving peroxidase and superoxide dismutase activities under drought stress.A total of 10,064 and 15,208 differentially expressed unigenes(DEGs)obtained from the AOS treatment and control samples at 24 and 72 h after dehydration,respectively,were mainly enriched in the biosynthesis of secondary metabolites(phenylpropanoid biosynthesis,flavonoid biosynthesis),carbohydrate metabolism(starch and sucrose metabolism,carbon fixation in photosynthetic organisms),lipid metabolism(fatty acid elongation,biosynthesis of unsaturated fatty acids,alpha-linolenic acid metabolism,cutin,suberine and wax biosynthesis),and signaling transduction pathways.The up-regulated genes were related to,for example,chlorophyll a-b binding protein,amylosynthease,phosphotransferase,peroxidase,phenylalanine ammonia lyase,flavone synthase,glutathione synthetase.Signaling molecules(including MAPK,plant hormones,H_(2)O_(2) and calcium)and transcription factors(mainly including NAC,MYB,MYB-related,WRKY,bZIP family members)were involved in the AOS-induced wheat drought resistance.The results obtained in this study help underpin the mechanisms of wheat drought resistance improved by AOS,and provides a theoretical basis for the application of AOS as an environmentally sustainable biological method to improve drought resistance in agriculture.

Effects of Light Quality on Growth and Physiological Characteristics of Neopyropia yezoensis Free Living Conchocelis

[Objectives]To study the differences of growth rate,morphology,ultrastructure,pigment content and antioxidant enzyme activity of free-living conchocelis of cultivated type of Neopyropia yezoensis under different light qualities(white,red,blue,and green light).[Methods]The study was carried out through light quality design and culture,growth rate determination,microstructure and ultrastructure observation,chlorophyll a content and carotenoid content determination,phycobiliprotein content determination,malondialdehyde(MDA)content determination,superoxide dismutase(SOD)activity determination.[Results]After 21 d of culture,the specific growth rate(SGR)and chlorophyll a content of free-living conchocelis of N.yezoensis were significantly increased by white light(WL),followed by red light(RL)and green light(GL),and they were the lowest under blue light(BL).Compared with the WL group,the BL group had the highest content of phycoerythrin(PE),and the RL and GL groups had the highest content of phycocyanin(PC).The algal body of WL group was normal black brown,and the cell wall was the thickest.In RL and GL groups,the algal bodies were green,and their diameters and cell wall thicknesses were similar to those in WL group.In BL group,the algal body was bright red,the diameter was the smallest,the cell wall was the thinnest,and the ultrastructure showed that the number of plastoglobulus on the thylakoid was the largest.After BL irradiation,the highest MDA content and the lowest SOD activity were observed.The results revealed that WL is the most beneficial to the growth of free-living conchocelis,followed by RL and GL,while BL has adverse effects.[Conclusions]This study explored the most suitable light quality conditions for the propagation of free-living conchocelis.It is expected to provide germplasm guarantee for the production and seedling of N.yezoensis.

Semi-implantable device based on multiplexed microfilament electrode cluster for continuous monitoring of physiological ions

Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in biological subjects.Current semi-implantable devices are mainly based on single-parameter detection.Miniaturized semi-implantable electrodes for multiparameter sensing have more restrictions on the electrode size due to biocompatibility considerations,but reducing the electrode surface area could potentially limit electrode sensitivity.This study developed a semi-implantable device system comprising a multiplexed microfilament electrode cluster(MMEC)and a printed circuit board for real-time monitoring of intra-tissue K^(+),Ca^(2+),and Na^(+)concentrations.The electrode surface area was less important for the potentiometric sensing mechanism,suggesting the feasibility of using a tiny fiber-like electrode for potentiometric sensing.The MMEC device exhibited a broad linear response(K^(+):2–32 mmol/L;Ca^(2+):0.5–4 mmol/L;Na^(+):10–160 mmol/L),high sensitivity(about 20–45 mV/decade),temporal stability(>2weeks),and good selectivity(>80%)for the above ions.In vitro detection and in vivo subcutaneous and brain experiment results showed that the MMEC system exhibits good multi-ion monitoring performance in several complex environments.This work provides a platform for the continuous real-time monitoring of ion fluctuations in different situations and has implications for developing smart sensors to monitor human health.

Transcriptomic and physiological analyses identifying Lanzhou lily(Lilium davidii var.unicolor)drought adaptation strategies

Drought stress is the main limiting plant growth factor in arid and semiarid regions.The Lanzhou lily(Lilium davidii var.unicolor)is the only sweet-tasting lily grown in these regions of China that offers highly edible,medicinal,health,and ornamental value.The Tresor lily is an ornamental flower known for its strong resistance.Plants were grown under three different drought intensity treatments,namely,being watered at intervals of 5,15,and 25 d(either throughout the study or during specific growth stages).We measured the biomass,leaf area,photosynthetic response,chlorophyll content(SPAD value),and osmoregulation of both the Lanzhou lily and the Tresor lily(Lilium‘Tresor’).Additionally,we employed RNA sequencing(RNA-Seq)and qRT-PCR to investigate transcriptomic changes of the Lanzhou lily in response to drought stress.Results showed that under drought stress,the decreasing rate in the Lanzhou lily bulb weight was lower than the corresponding Tresor lily bulb rate;the net photosynthetic rate,transpiration rate,and stomatal conductance of the Lanzhou lily were all higher compared to the Tresor lily;osmoregulation constituents,such as glucose,fructose,sucrose,trehalose,and soluble sugar,in the Lanzhou lily were comparatively higher;PYL,NCED,and ERS genes were significantly expressed in the Lanzhou lily.Under moderate drought,the biosynthesis of flavonoids,circadian rhythms,and the tryptophan metabolism pathway of the Lanzhou lily were all significant.Under severe drought stress,fatty acid elongation,photosynthetic antenna protein,plant hormone signal transduction,flavone and flavonol biosynthesis,and the carotenoid biosynthesis pathway were all significant.The Lanzhou lily adapted to drought stress by coordinating its organs and the unique role of its bulb,regulating photosynthesis,increasing osmolyte content,activating circadian rhythms,signal transduction,fatty acid elongation metabolism,and phenylalanine and flavonoid metabolic pathways,which may collectively be the main adaptation strategy and mechanisms used by the Lanzhou lily under drought stress.

Physiological and Biochemical Mechanisms of Salinity Tolerance in Carex morrowii Boott

Carex species are widely used in many parts of the world and contain a large number of ecologically diverse species.Among the Carex species,some of them are known to be glycophytes,while others are halophytes.Carex morrowii Boott(Cyperaceae)is resistant to trample through their root structure and has an essential ornamental value in the landscape with their leaves.However,no information was found about the level of salinity tolerance/sensitivity of the Carex morrowii among these species.In the present study,changes in trace element contents(Na,K,Ca,Cu,Mn,Mg,Ni,Fe,P,Zn,and N)and their transport from roots to leaves,osmotic regulation,alterations in chlorophyll and carotenoid contents,nitrogen assimilation(nitrate reductase activity;NRA)and total soluble protein content in both roots and leaves of Carex morrowii under different salinity concentrations(50 mM,100 mM,200 mM and 300 mM NaCl)were examined in detail.Our study provides the first detailed data concerning the responses of leaves and roots and the determination of the level of salinity tolerance/sensitivity of the Carex morrowii.The K+/Na+ratio was preserved up to 200 mM NaCl,and accordingly,the element uptake and transport ratios showed that they could control moderate NaCl levels.Ca homeostasis that is maintained even in 200 mM NaCl concentration can be effective in maintaining the structural integrity and selective permeability of the cell membranes,while 300 mM NaCl concentration caused decreased photosynthetic pigments,and deterioration in element content and compartmentation.Moreover,these data suggest that plant parts of Carex morrowii respond differently against varied levels of salinity stress.Although the decrease in NR activity at 200 mM and 300 mM NaCl concentrations in the leaves,NR activity was maintained in the roots.Consequently,Carex morrowii is moderately tolerant to salinity and the carotenoid content and osmotic regulation of Carex morrowii appears to be instrumental in its survival at different salinity levels.Especially the roots of Carex morrowii have a remarkable role in salinity tolerance.

Physiological Responses of Clam(Ruditapes philippinarum)to Transport Modes with Different Temperatures

Given the increased circulation time after fishing,a series of changes take place in live clams,leading to a deterioration in quality even after death.Thus,in this study,we aimed to explore the optimal mode of transportation of clams.The container for holding clams was reformed,and a water circulation temperature control system was established.The physiological responses of clams during anhydrous and watery transportation at two temperatures(4 and 15℃)were investigated based on the aforementioned system.When comparing the transportation patterns after 3 d of transport,a higher survival rate was observed at 4℃(97%)than at 15℃(63%)in the anhydrous transportation groups and a lower survival rate was observed at 4℃(93%)than at 15℃(99%)in the watery transportation groups.In addition,the glycogen content,condition index(CI),and adenylate energy charge(A.E.C)value were higher at4℃((40.87±0.99)mg g^(-1),13.71%±0.50%and 57.45%±1.60%)than at 15℃((30.54±0.81)mg g^(-1),9.09%±0.30%and 43.12%±1.65%)in the anhydrous transportation groups.In the watery transportation groups,a lower glycogen content,CI,and A.E.C.value were observed at 4℃((33.78±0.84)mg g^(-1),9.78%±0.50%and 64.65%±1.25%)than at 15℃((41.53±0.93)mg g^(-1),12.72%±0.83%and 71.58%±1.27%).Results from this study show that anhydrous transportation(4℃)is the optimal transport condition for clams to maintain a high quality and good physiological conditions.Thus,this study will be particularly useful for establishing shellfish transportation systems.

Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects between environmental factors.We hypo-thesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.AIM To investigate the effects of meteorological factors and air pollution on depressive disorders,including their lagged effects and interactions.METHODS The samples were obtained from a class 3 hospital in Harbin,China.Daily hos-pital admission data for depressive disorders from January 1,2015 to December 31,2022 were obtained.Meteorological and air pollution data were also collected during the same period.Generalized additive models with quasi-Poisson regre-ssion were used for time-series modeling to measure the non-linear and delayed effects of environmental factors.We further incorporated each pair of environ-mental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.RESULTS Data for 2922 d were included in the study,with no missing values.The total number of depressive admissions was 83905.Medium to high correlations existed between environmental factors.Air temperature(AT)and wind speed(WS)significantly affected the number of admissions for depression.An extremely low temperature(-29.0℃)at lag 0 caused a 53%[relative risk(RR)=1.53,95%confidence interval(CI):1.23-1.89]increase in daily hospital admissions relative to the median temperature.Extremely low WSs(0.4 m/s)at lag 7 increased the number of admissions by 58%(RR=1.58,95%CI:1.07-2.31).In contrast,atmospheric pressure and relative humidity had smaller effects.Among the six air pollutants considered in the time-series model,nitrogen dioxide(NO_(2))was the only pollutant that showed significant effects over non-cumulative,cumulative,immediate,and lagged conditions.The cumulative effect of NO_(2) at lag 7 was 0.47%(RR=1.0047,95%CI:1.0024-1.0071).Interaction effects were found between AT and the five air pollutants,atmospheric temperature and the four air pollutants,WS and sulfur dioxide.CONCLUSION Meteorological factors and the air pollutant NO_(2) affect daily hospital admissions for depressive disorders,and interactions exist between meteorological factors and ambient air pollution.

Graph Construction Method for GNN-Based Multivariate Time-Series Forecasting

Multivariate time-series forecasting(MTSF)plays an important role in diverse real-world applications.To achieve better accuracy in MTSF,time-series patterns in each variable and interrelationship patterns between variables should be considered together.Recently,graph neural networks(GNNs)has gained much attention as they can learn both patterns using a graph.For accurate forecasting through GNN,a well-defined graph is required.However,existing GNNs have limitations in reflecting the spectral similarity and time delay between nodes,and consider all nodes with the same weight when constructing graph.In this paper,we propose a novel graph construction method that solves aforementioned limitations.We first calculate the Fourier transform-based spectral similarity and then update this similarity to reflect the time delay.Then,we weight each node according to the number of edge connections to get the final graph and utilize it to train the GNN model.Through experiments on various datasets,we demonstrated that the proposed method enhanced the performance of GNN-based MTSF models,and the proposed forecasting model achieve of up to 18.1%predictive performance improvement over the state-of-the-art model.

Salt stress responses in foxtail millet:Physiological and molecular regulation

Foxtail millet(Setaria italica L.),a member of the Paniceae family,is a temperate and tropical grass species that is widely cultivated on the Eurasian continent.It is Chinese in origin and possesses a small genome,short growth cycle,and strong natural abiotic stress resistance.Elucidating the mechanism of millet tolerance to salt stress is becoming increasingly important with increasing soil salinization limiting crop productivity.The responses and mechanisms of tolerance to salt stress from other model plants such as Arabidopsis and rice,were compared with those from foxtail millet to summarize current research on responses to salt stress.Numerous processes are involved in these processes,including physiological reactions,sensing,signaling,and control at the transcriptional,post-transcriptional,and epigenetic levels.To increase crop productivity and agricultural sustainability,a variety of technologies can be used to investigate how salt tolerance is mediated by physiological and molecular processes in foxtail millet.