Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

How forest age impacts on net primary productivity: Insights from future multi-scenarios

Forest net primary productivity(NPP)constitutes a key flux within the terrestrial ecosystem carbon cycle and serves as a significant indicator of the forests carbon sequestration capacity,which is closely related to forest age.Despite its significance,the impact of forest age on NPP is often ignored in future NPP projections.Here,we mapped forest age in Hunan Province at a 30-m resolution utilizing a combination of Landsat time series stack(LTSS),national forest inventory(NFI)data,and the relationships between height and age.Subsequently,NPP was derived from NFI data and the relationships between NPP and age was built for various forest types.Then forest NPP was predicted based on the NPP-age relationships under three future scenarios,assessing the impact of forest age on NPP.Our findings reveal substantial variations in forest NPP in Hunan Province under three future scenarios:under the age-only scenario,NPP peaks in 2041(133.56TgC·yr^(−1)),while NPP peaks three years later in 2044(141.14TgC·yr^(−1))under the natural development scenario.The maximum afforestation scenario exhibits the most rapid increase in NPP,with peaking in 2049(197.95TgC·yr^(−1)).However,with the aging of the forest,NPP is projected to then decrease by 7.54%,6.07%,and 7.47%in 2060,and 20.05%,19.74%,and 28.38%in 2100,respectively,compared to their peaks under the three scenarios.This indicates that forest NPP will continue to decline soon.Controlling the age structure of forests through selective logging,afforestation and reforestation,and encouraging natural regeneration after disturbance could mitigate this declining trend in forest NPP,but implications of these measures on the full forest carbon balance remain to be studied.Insights from the future multi-scenarios are expected to provide data to support sustainable forest management and national policy development,which will inform the achievement of carbon neutrality goals by 2060.

Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, and euphotic zone depth in the northern Bay of Bengal

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.

Anomaly Detection Method Using Feature Reconstruction Based Knowledge Distillation

In recent years,anomaly detection has attracted much attention in industrial production.As traditional anomaly detection methods usually rely on direct comparison of samples,they often ignore the intrinsic relationship between samples,resulting in poor accuracy in recognizing anomalous samples.To address this problem,a knowledge distillation anomaly detection method based on feature reconstruction was proposed in this study.Knowledge distillation was performed after inverting the structure of the teacher-student network to avoid the teacher-student network sharing the same inputs and similar structure.Representability was improved by using feature splicing to unify features at different levels,and the merged features were processed and reconstructed using an improved Transformer.The experimental results show that the proposed method achieves better performance on the MVTec dataset,verifying its effectiveness and feasibility in anomaly detection tasks.This study provides a new idea to improve the accuracy and efficiency of anomaly detection.

Clinicopathological features of 11 cases of chronic hepatitis B infection complicated with primary biliary cholangitis

BACKGROUND Only a few cases of chronic hepatitis B(CHB)with primary biliary cholangitis(PBC)have been reported based on histological evidence from liver biopsies.AIM To observe the clinicopathological features and outcomes of 11 patients with CHB infection complicated by PBC.METHODS Eleven patients with CHB and PBC who underwent liver biopsy at the Zhenjiang Third Hospital,affiliated with Jiangsu University,and Wuxi Fifth People’s Hospital,from January 2005 to September 2020,were selected.All patients initially visited our hospital with CHB and were pathologically diagnosed with CHB and PBC.RESULTS Only five had elevated alkaline phosphatase levels,nine were positive for antimitochondrial antibody(AMA)-M2,and two were negative for AMA-M2.Two had jaundice and pruritus symptoms,10 had mildly abnormal liver function,and one had severely elevated bilirubin and liver enzyme levels.The pathological characteristics of CHB complicated by PBC overlapped with those of PBCautoimmune hepatitis(AIH).When necroinflammation of the portal area is not obvious,the pathological features of PBC are predominant,similar to the features of PBC alone.When the interface is severe,biliangitis will occur,with a large number of ductular reactions in zone 3.Unlike the PBC-AIH overlap pathology,this pathology is characterized by a small amount of plasma cell infiltration.Unlike PBC,lobulitis is often observed.CONCLUSION This is the first large case series to show that the rare pathological features of CHB with PBC are similar to those of PBC-AIH and small duct injury was observed.

Some Features of Black Carbon Aerosols Connected with Regional Climate Over Pristine Environment

The authors report the results of aethalometer black carbon(BC)aerosol measurements carried out over a rural(pristine)site,Panchgaon,Haryana State,India during the winter months of 2021-2022 and 2022-2023.They are compared with collocated and concurrent observations from the Air Quality Monitoring Station(AQMS),which provides synchronous air pollution and surface meteorological parameters.Secular variations in BC mass concentration are studied and explained with variations in local meteorological parameters.The biomass burning fire count retrievals from NASA-NOAA VIIRS satellite,and backward airmass trajectories from NOAA-ERL HYSPLIT Model analysis have also been utilized to explain the findings.They reveal that the north-west Indian region contributes maximum to the BC mass concentration over the study site during the study period.Moreover,the observed BC mass concentrations corroborate the synchronous fire count,primary and secondary pollutant concentrations.The results were found to aid the development of mitigation methods to achieve a sustainable climate system.

Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line

Software Product Line(SPL)is a group of software-intensive systems that share common and variable resources for developing a particular system.The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints(CTC).CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things(IoT)devices because different Internet devices and protocols are communicated.Therefore,managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex,time-consuming,and hard.However,the CTC problem needs to be considered in previously proposed approaches such as Commonality VariabilityModeling of Features(COVAMOF)andGenarch+tool;therefore,invalid products are generated.This research has proposed a novel approach Binary Oriented Feature Selection Crosstree Constraints(BOFS-CTC),to find all possible valid products by selecting the features according to cardinality constraints and cross-tree constraint problems in the featuremodel of SPL.BOFS-CTC removes the invalid products at the early stage of feature selection for the product configuration.Furthermore,this research developed the BOFS-CTC algorithm and applied it to,IoT-based feature models.The findings of this research are that no relationship constraints and CTC violations occur and drive the valid feature product configurations for the application development by removing the invalid product configurations.The accuracy of BOFS-CTC is measured by the integration sampling technique,where different valid product configurations are compared with the product configurations derived by BOFS-CTC and found 100%correct.Using BOFS-CTC eliminates the testing cost and development effort of invalid SPL products.

Menstrual and Reproductive Characteristics of Patients with Primary Sjogren’s Syndrome:A 7-year Single-center Retrospective Study

Objective Primary Sjogren’s syndrome(pSS)is a systemic autoimmune disease that mainly affects the exocrine gland,especially in women.Currently,the results of studies on the menstruation or fertility of pSS patients remain controversial.This study aimed to examine the menstrual and reproductive characteristics of pSS patients.Methods Clinical data of 449 pSS patients who were admitted to Tongji Hospital in Hubei,China,from January 2015 to November 2021 were obtained and their menstrual and reproductive information analyzed.In addition,the clinical features of pSS patients with premenopausal or postmenopausal onset were compared.Results The spontaneous abortion rate of pSS patients was not higher than the reported rate of the general population and that the age of menarche,menstrual cycle,and menstrual period of pSS patients did not significantly differ from those reported in the general population;however,early menopause seemed to be more common in pSS patients.Skin involvement(27.96%vs.15.00%,P=0.005)and hyperglobulinemia(10.64%vs.4.16%,P=0.033)were more common in patients with premenopausal pSS onset,but patients with postmenopausal onset had a significantly greater incidence of interstitial lung disease(32.50%vs.17.02%,P=0.0004).Also,erythropenia(47.00%vs.31.25%,P=0.002),hypoalbuminemia(19.49%vs.8.22%,P=0.0009),and prevalence of high hypersensitive C-reactive protein levels(21.67%vs.10.94%,P=0.005)were more common in pSS patients with postmenopausal onset.Notably,the rate of abnormal pregnancy was significantly greater in patients with premenopausal onset(9.72%vs.2.50%,P=0.011).Conclusion Patients with pSS onset before or after menopause may have different risks in pulmonary involvement and laboratory manifestations.

A Feature-Based Parametric Product Modeling System in CIMS Environment

This paper proposes an approach of developing the feature based parametric product modeling system which is suitable for integrated engineering design in CIMS environment.The architecture of ZD--MCADII and the characteristics of its each module are introduced in detail. ZD--MCADII’s product data is managed by an object--oriented database management system OSCAR, and the product model is built according to the standard STEP. The product design is established on a unified product model, and all the product data are globally associated in ZD--MCADII. ZD--MCADII provides various design features to facilitate the product design, and supports the integrity of CAD, CAPP and CAM.

Simulation of the Ecosystem Productivity Responses to Aerosol Diffuse Radiation Fertilization Effects over the Pan-Arctic during 2001–19

The pan-Arctic is confronted with air pollution transported from lower latitudes.Observations have shown that aerosols help increase plant photosynthesis through the diffuse radiation fertilization effects(DRFEs).While such DRFEs have been explored at low to middle latitudes,the aerosol impacts on pan-Arctic ecosystems and the contributions by anthropogenic and natural emission sources remain less quantified.Here,we perform regional simulations at 0.2o×0.2ousing a well-validated vegetation model(Yale Interactive terrestrial Biosphere,YIBs)in combination with multi-source of observations to quantify the impacts of aerosol DRFEs on the net primary productivity(NPP)in the pan-Arctic during 2001-19.Results show that aerosol DRFEs increase pan-Arctic NPP by 2.19 Pg C(12.8%)yr^(-1)under clear-sky conditions,in which natural and anthropogenic sources contribute to 8.9% and 3.9%,respectively.Under all-sky conditions,such DRFEs are largely dampened by cloud to only 0.26 Pg C(1.24%)yr^(-1),with contributions of 0.65% by natural and 0.59% by anthropogenic species.Natural aerosols cause a positive NPP trend of 0.022% yr^(-1)following the increased fire activities in the pan-Arctic.In contrast,anthropogenic aerosols induce a negative trend of-0.01% yr^(-1)due to reduced emissions from the middle latitudes.Such trends in aerosol DRFEs show a turning point in the year of 2007 with more positive NPP trends by natural aerosols but negative NPP trends by anthropogenic aerosols thereafter.Though affected by modeling uncertainties,this study suggests a likely increasing impact of aerosols on terrestrial ecosystems in the pan-Arctic under global warming.

Primary sclerosing cholangitis associated colitis: Characterization of clinical, histologic features, and their associations with liver transplantation

BACKGROUND Primary sclerosing cholangitis(PSC)associated inflammatory bowel disease(IBD)is a unique form of IBD(PSC-IBD)with distinct clinical and histologic features from ulcerative colitis(UC)and Crohn disease(CD).In patients with PSC and IBD,the severity of the two disease processes may depend on each other.AIM To study the histologic and clinical features of PSC patients with and without IBD.METHODS We assessed specimens from patients with UC(n=28),CD(n=10),PSC and UC(PSC-UC;n=26);PSC and CD(PSC-CD;n=6);and PSC and no IBD(PSC-no IBD;n=4)between years 1999-2013.PSC-IBD patients were matched to IBD patients without PSC by age and colitis duration.Clinical data including age,gender,age at IBD and PSC diagnoses,IBD duration,treatment,follow-up,orthotopic liver transplantation(OLT)were noted.RESULTS PSC-UC patients had more isolated right-sided disease(P=0.03),and less active inflammation in left colon,rectum(P=0.03 and P=0.0006),and overall(P=0.0005)compared to UC.They required less steroids(P=0.01)and fewer colectomies(P=0.03)than UC patients.The PSC-CD patients had more ileitis and less rectal involvement compared to PSC-UC and CD.No PSC-CD patients required OLT compared to 38%of PSC-UC(P=0.1).PSC-IBD(PSC-UC and PSCCD)patients with OLT had severe disease in the left colon and rectum(P=0.04).CONCLUSION PSC-UC represents a distinct form of IBD.The different disease phenotype in PSC-IBD patients with OLT may support liver-gut axis interaction,however warrants clinical attention and further research.

Clinical and pathological features and risk factors for primary breast cancer patients

BACKGROUND Breast cancer is the most common malignancy in women all around the world.According to the latest statistics in 2018,there were more than 2.08 million new breast cancer cases all around the world and more than 620000 deaths;the proportion of breast cancer deaths in women with cancer is 15%.By studying age,clinicopathological characteristics and molecular classification,age at menarche,age at birth,number of births,number of miscarriages,lactation time,surgical history of benign breast lesions,history of gynecological diseases,and other factors,we retrospectively summarized and compared the disease history of patients with primary breast cancer and patients with benign thyroid tumors admitted to our hospital in the past 10 years to explore the clinicopathological characteristics and risk factors for primary breast cancer.AIM To investigate the clinical and pathological features and risk factors for primary breast cancer treated at our center in order to provide a reference for the prevention and treatment of breast cancer in the Zhuhai-Macao region.METHODS Through a retrospective case-control study,149 patients with primary breast cancer diagnosed and treated at Zhuhai Hospital of Guangdong Provincial Hospital of Traditional Chinese Medicine from January 2013 to March 2020 were included as a case group,and 165 patients with benign breast tumors diagnosed and treated from January 2019 to March 2020 were included as a control group.The data collected included age,age at menarche,age at first birth,number of births,number of miscarriages,lactation time,history of surgery for benign breast lesions,history of familial malignant tumors,history of gynecological diseases,history of thyroid diseases,and the tumor characteristics of the patients in the case group including pathological diagnosis,pathological type,tumor size,lymph node metastasis,distant metastasis,stage,and molecular classification,among others.In the case group,the chi-square test was used to analyze the clinical and pathological features of patients in three age groups(<40,40-59,and≥60 years).A multifactor logistic regression analysis was used to analyze correlations between the two groups.RESULTS Among 149 patients with primary breast cancer,the average age was 48.20±12.06 years,and the proportion of patients at 40-59 years old was the highest,accounting for 61.8%of cases.The molecular type was mainly luminal B type,accounting for 69.2%of cases,and at the time of diagnosis,the tumor stage was mainly stage I/II,accounting for 62.4%of cases.There were no statistically significant differences in the distributions of tumor location,pathological type,tumor size,lymph node metastasis,stage,or molecular classification among the three age groups(<40,40-59,and≥60 years)(P≥0.05).The differences in the distribution of distant metastasis among the three age groups(<40,40-59,and≥60 years)were statistically significant(P<0.01).The differences in lactation time,history of familial malignant tumors,history of gynecological diseases,and history of thyroid diseases between the two groups were not statistically significant(P≥0.05).The differences in age at disease diagnosis,age at menarche,and history of surgery for benign breast lesions were statistically significant(P<0.01).The difference in age at first birth was also statistically significant(P<0.05).CONCLUSION The highest incidence of breast cancer in the Zhuhai-Macao region is present among women aged 40-59 years.There is a larger proportion of stage I/II patients,and the luminal B type is the most common molecular subtype.Distant metastasis occurs mainly in the≥60-year-old group at the first diagnosis;increased age,late age at menarche,and late age at first birth may be risk factors for primary breast cancer,and a history of surgery for benign breast lesions may be a protective factor for primary breast cancer.

Didactic Sequences as an Educational Product to Facilitate Teaching-Learning Processes in Lato Sensu Graduate Courses in the Area of Health Management in Primary Care

Teaching strategies can be considered as techniques that are constructed to be used with the objective of promoting teaching and learning in the classroom, so that the teacher is considered a mentor, as he is the one who selects, analyzes, studies, organizes, builds and proposes the most classic tools to facilitate the learning process [1]. This study is an experience report related to the construction of an educational product that consists of the elaboration of pedagogical strategies, characterized by five didactic sequences in the perspective of collaborating with teaching-learning processes in lato sensu graduate courses. The themes that are part of the didactic sequences were built based on the results obtained in scientific research carried out during the development of the strict sensu postgraduate course in Teaching in Health and Technology, which involved: the work of coordinators who work in the field of health management in Primary Care, situations that challenge the management of Primary Care and the potentialities of work in the management of Primary Care. The didactic sequences have fun teaching strategies that provide meaningful learning for a future qualified professional performance. These sequences involve the use of active methodologies and the use of digital tools. The educational product developed seeks to promote benefits that can collaborate with the improvement of Primary Care Management and teaching-learning processes in the training of health professionals. Therefore, the pedagogical strategies, as well as its entire construction process, were developed through the collaboration of professors of the Health and Society discipline at the State University of Health Sciences of Alagoas (UNCISAL), seeking to make it qualify for effective construction of knowledge and that promote its wide use in the academic environment.

Features of primary pancreatic lymphoma:A bi-institutional review with an emphasis on typical and atypical imaging features

BACKGROUND Primary pancreatic lymphoma(PPL)is a rare neoplasm.Being able to distinguish it from other pancreatic malignancies such as pancreatic ductal adenocarcinoma(PDAC)is important for appropriate management.Unlike PDAC,PPL is highly sensitive to chemotherapy and usually does not require surgery.Therefore,being able to identify PPL preoperatively will not only direct physicians towards the correct avenue of treatment,it will also avoid unnecessary surgical intervention.AIM To evaluate the typical and atypical multi-phasic computed tomography(CT)imaging features of PPL.METHODS A retrospective review was conducted of the clinical,radiological,and pathological records of all subjects with pathologically proven PPL who presented to our institutions between January 2000 and December 2020.Institutional review board approval was obtained for this investigation.The collected data were analyzed for subject demographics,clinical presentation,laboratory values,CT imaging features,and the treatment received.Presence of all CT imaging findings including size,site,morphology and imaging characteristics of PPL such as the presence or absence of nodal,vascular and ductal involvement in these subjects were recorded.Only those subjects who had a pre-treatment multiphasic CT of the abdomen were included in the study.RESULTS Twenty-nine cases of PPL were diagnosed between January 2000 and December 2020(mean age 66 years;13 males/16 females).All twenty-nine subjects were symptomatic but only 4 of the 29 subjects(14%)had B symptoms.Obstructive jaundice occurred in 24%of subjects.Elevated lactate dehydrogenase was seen in 81%of cases,whereas elevated cancer antigen 19-9 levels were present in only 10%of cases for which levels were recorded.The vast majority(90%)of tumors involved the pancreatic head and uncinate process.Mean tumor size was 7.8 cm(range,4.0-13.8 cm).PPL presented homogenous hypoenhancement on CT in 72%of cases.Small volume peripancreatic lymphadenopathy was seen in 28%of subjects.Tumors demonstrated encasement of superior mesenteric vessels in 69%of cases but vascular stenosis or occlusion only manifested in 5 out of the twentynine individuals(17%).Mild pancreatic duct dilatation was also infrequent and seen in only 17%of cases,whereas common bile duct(CBD)dilation was seen in 41%of subjects.Necrosis occurred in 10%of cases.Size did not impact the prevalence of pancreatic and CBD dilation,necrosis,or mesenteric root infiltration(P=0.525,P=0.294,P=0.543,and P=0.097,respectively).Pancreatic atrophy was not present in any of the subjects.CONCLUSION PPL is an uncommon diagnosis best made preoperatively to avoid unnecessary surgery and ensure adequate treatment.In addition to the typical CT findings of PPL,such as homogeneous hypoenhancement,absence of vascular stenosis and occlusion despite encasement,and peripancreatic lymphadenopathy,this study highlighted many less typical findings,including small volume necrosis and pancreatic and bile duct dilation.

Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm

Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development.

SA-MSVM:Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter

One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics.Bigdata is created from social websites like Facebook,WhatsApp,Twitter,etc.Opinions about products,persons,initiatives,political issues,research achievements,and entertainment are discussed on social websites.The unique data analytics method cannot be applied to various social websites since the data formats are different.Several approaches,techniques,and tools have been used for big data analytics,opinion mining,or sentiment analysis,but the accuracy is yet to be improved.The proposed work is motivated to do sentiment analysis on Twitter data for cloth products using Simulated Annealing incorporated with the Multiclass Support Vector Machine(SA-MSVM)approach.SA-MSVM is a hybrid heuristic approach for selecting and classifying text-based sentimental words following the Natural Language Processing(NLP)process applied on tweets extracted from the Twitter dataset.A simulated annealing algorithm searches for relevant features and selects and identifies sentimental terms that customers criticize.SA-MSVM is implemented,experimented with MATLAB,and the results are verified.The results concluded that SA-MSVM has more potential in sentiment analysis and classification than the existing Support Vector Machine(SVM)approach.SA-MSVM has obtained 96.34%accuracy in classifying the product review compared with the existing systems.

Ultrasonographic Feature of Persistent Hyperplastic Primary Vitreous

Purpose:.To observe the ultrasonographic features of patients with persistent hyperplastic primary vitreous(PHPV).Methods: Thirty-two subjects(34 eyes) diagnosed with PHPV were evaluated by ultrasonography.Results:.The ultrasonography demonstrated a retrolental mass extending from the optic disc to the posterior lens capsule,manifested as band,.regular triangle,.or inverted triangle shapes..The band-shaped echo was characterized as a linear band extended from the optic disc to the posterior lens capsule..The regular triangle-shaped echo was manifested as a membranous septum with a wide base extended from the optic disc to the posterior lens capsule, and the anterior part became narrower..The inverted triangle echo was characterized as a membranous septum with a narrow base extended from the optic disc to the posterior lens capsule,.and the anterior part become wider.Conclusion:.Ultrasonography is noninvasive and safe,.and can offer real-time display of intraocular structures. This is especially important in individuals who are uncooperative or unsuitable for fundus examination due to media opacity. Combined with clinical feature, ultrasonography provides vital evidence for the diagnosis of PHPV..Thought observing ultrasonographic feature, clinicians could evaluate the size, position and severity of lesions in PHPV patients,.and which would be helpful to determine the surgical approach and clini-cal prognosis.

Diverse foraging strategies of breeding Swinhoe's Storm-petrel in the productive marginal sea of the Northwest Pacific

Understanding the foraging behavior is essential for investigating seabird ecology and conservation,as well as monitoring the well-being of the marine environment.Breeding seabirds adopt diverse foraging strategies to maximize energy gains and cope with the intensified challenges of parenting and self-maintenance.Such tradeoff may stem from the heterogeneity of food resources and the constraints of central place foraging.Nevertheless,abundant marine productivity could alleviate the energy limitation for seabirds,resulting in a consistent foraging approach.Here,we investigated the foraging strategy during the breeding season of a cryptic small-sized seabird,Swinhoe’s Storm-petrel(Hydrobates monorhis),in the Yellow Sea,a productive marginal sea of the Northwest Pacific.Using GPS tracking,we evaluated habitat preference,quantified the foraging strategy,and tested if environmental conditions and individual traits influence foraging trips.We found that Swinhoe’s Storm-petrels preferred nearshore areas with shallow water and engaged in primarily short foraging trips.Distinctive southeastward and southwestward strategies emerged when combining trip metrics,including foraging direction,duration,and maximum distance.The bathymetry,proximity to the coastline,and sea surface temperature differed in two foraging strategies.Foraging strategies exhibited flexibility between individuals,potentially explained by wing morphology,in which longer-winged birds are more likely to embark on longer-distance foraging trips.These findings highlight the impact of environmental factors and individual traits on seabirds’foraging decisions in productive marginal sea ecosystems.Our study also provides valuable insights into the foraging ecology of this Asian endemic storm-petrel.

Feature Technology in Product Modeling

A unified feature definition is proposed.Feature is form-concentrated,and can be used to model product func- tionalities,assembly relations,and part geometries.The feature model is given and a feature classification is introduced including functional,assembly,structural,and manufacturing features.A prototype modeling system is developed in Pro/ENGINEER that can define the assembly and user-defined form features.

Feature-based and objectoriented product information model for welding structure

Product information model for welding structure plays an important role for the integration of welding CAD/CAPP/CAM. However, existing CAD modeling systems are not capable of providing enough information for subsequent manufacturing activities such as CAPP and CAM. A new design approach using feature technique and object oriented programming method is put forward in this paper in order to create the product information model of welding structure. With this approach, the product information model is able to effectively support computer aided welding process planning, fixturing, assembling, path planning of welding robot and other manufacturing activities. The feature classification and representing scheme of welding structure are discussed. A prototype system is developed based on feature and object oriented programming. Its structure and functions are given in detail.