Deep learning to estimate ocean subsurface salinity structure in the Indian Ocean using satellite observations

Accurately estimating the ocean subsurface salinity structure(OSSS)is crucial for understanding ocean dynamics and predicting climate variations.We present a convolutional neural network(CNN)model to estimate the OSSS in the Indian Ocean using satellite data and Argo observations.We evaluated the performance of the CNN model in terms of its vertical and spatial distribution,as well as seasonal variation of OSSS estimation.Results demonstrate that the CNN model accurately estimates the most significant salinity features in the Indian Ocean using sea surface data with no significant differences from Argo-derived OSSS.However,the estimation accuracy of the CNN model varies with depth,with the most challenging depth being approximately 70 m,corresponding to the halocline layer.Validations of the CNN model’s accuracy in estimating OSSS in the Indian Ocean are also conducted by comparing Argo observations and CNN model estimations along two selected sections and four selected boxes.The results show that the CNN model effectively captures the seasonal variability of salinity,demonstrating its high performance in salinity estimation using sea surface data.Our analysis reveals that sea surface salinity has the strongest correlation with OSSS in shallow layers,while sea surface height anomaly plays a more significant role in deeper layers.These preliminary results provide valuable insights into the feasibility of estimating OSSS using satellite observations and have implications for studying upper ocean dynamics using machine learning techniques.

Characteristics and triggering mechanisms of early negative Indian Ocean Dipole

Negative Indian Ocean Dipole(nIOD)can exert great impacts on global climate and can also strongly influence the climate in China.Early nIOD is a major type of nIOD,which can induce more pronounced climate anomalies in summer than La Niña-related nIOD.However,the characteristics and triggering mechanisms of early nIOD are unclear.Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD,and the former accounts for over one third of all the nIOD events in the past six decades.These two types of nIODs are similar in their intensities,but are different in their spatial patterns and seasonal cycles.The early nIOD,which develops in spring and peaks in summer,is one season earlier than the La Niña-related nIOD.The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern,with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean.Opposite to the triggering mechanism of early positve IOD,the early nIOD is induced by delayed Indian summer monsoon onset.The results of this study are helpful for improving the prediction skill of IOD and its climate impacts.

Random Amplification Polymorphic DNA and Agro-Morphological Traits-Based Fingerprinting for Detection of Genetic Divergence in Indian Black Rice

In this study, 32 black rice genotypes spanning diverse geographies in India were evaluated at both phenotypic and DNA sequence levels to gain insights into their genetic makeup. Significant variations were observed for 14 agro-morphological traits, showing correlations among several yield-related traits.

Public-private-partnership needs under the National Tuberculosis Elimination Program in an Eastern Indian state

Eliminating tuberculosis(TB)is among India's top public health priorities[1].Despite the considerable progress in providing quality TB care services,the Global TB report-2022 reveals that India is amongst the eight high TB burden countries that contributed to more than two-thirds(68.3%)of the global TB cases[2].To strengthen and aid the TB elimination efforts by 2025,five years ahead of the sustainable development goal target,the Government of India,under the program,promotes intersectoral convergence with various public sector departments and the private sector.The national multisectoral action framework for TB-free India promotes private-private or public-private partnerships for sustainable and impactful Corporate Social Responsibility initiatives[3].

Chronic Hepatitis B in Indian Americans: Lack of Screening and Poor Linkage to Care

Background: Chronic hepatitis B (CHB) is a major cause of liver-related morbidity and mortality in the United States (US) and globally. CHB disproportionately affects Asian Americans and many other immigrant minority populations, primarily owing to the high prevalence of CHB in their countries of origin. India is a country with a medium-to-high prevalence of hepatitis B (HB) (>2%) and has over 40 million people infected with hepatitis B virus (HBV), with more than 115,000 deaths annually from HBV-related complications. Indian Americans are one of the largest immigrant populations in the US but remain underdiagnosed and poorly linked to clinical care. We, therefore, assessed the HBV prevalence and evaluated the linkage-to-care (LTC) among Indian Americans to develop strategic plans to reduce the impact of HBV in the US. Methods: Between April 2022 and January 2024, serologic screening and surveys were provided to 328 Indian American adults (age 20 - 80) in New York City. All participants were tested for a triple panel consisting of hepatitis B surface antigen (HBsAg), hepatitis B surface antibody (anti-HBs), and hepatitis B core IgG antibody (anti-HBc). A survey was conducted on the subjects chronically infected with HBV regarding their histories of infection. Self-administered questionnaires were employed to evaluate demographic and epidemiologic characteristics. Results: Of 328 screened and evaluated (246 males and 82 females), 10 (3.0%) were HBV-infected, 222 (67.7%) were susceptible to HBV, and 96 (29.3%) were immune. The prevalence of chronic HBV varied between the age groups: 4.6% (age 20 - 40), 3.4% (age 41 - 60), and 1.7% (age 61 - 80). Of 10 chronically infected, only two subjects had been previously diagnosed but were not engaged in care. Conclusion: HBV disproportionately affects Asian Americans, primarily owing to immigration from parts of the world where the disease is endemic. Indian Americans belong to an intermediate-risk group, with an HBV prevalence of >2%, but remain underdiagnosed and poorly linked to care. Our pilot study on Indian American populations, the first of its kind, demonstrates a 3% prevalence of CHB, none of whom are linked to care. In addition, this population has a high percentage of unimmune subjects, creating a large reservoir for future infection. With the growing population of Indian Americans, our findings can be used to develop community-based strategies for HBV screenings and LTC that target high-risk groups.

Below-Moho Earthquakes of Tibet,Himalaya,the Indian Foreland,and Worldwide:How,Where and Why?

We seek to understand lithospheric rheology by mapping continental earthquake depths relative to Moho depth,across the entire India/Asia convergent orogen,and eventually worldwide.Such mapping has particular value in geothermometry,and potentially in identifying regions of delamination.How:We are extending our Sn/Lg method beyond amplitude ratios of regional seismic phases measured on arrays(array Sn/Lg method,Wang and Klemperer,2021)to include frequency proxies for earthquake depth relative to Moho(Wang&Klemperer,2024a,b;Harris et al.,2024).

Influence of edaphic factors on distribution and condition of Himalayan silver birch(Betula utilis D.Don)communities in the northwestern Indian Himalayas

The basic concept of phytosociology is crucial for the assessment of species composition and dynamic ecological succession of forests supporting ecological services,functions,disturbance,and resilience that lead to the development of integrated areas such as ecological niche modeling and contribute to identifying the valuable bio-indicators which can be used in framing conservation and management planning.B.utilis is one of the most dominant tree species of treeline ecotone in the Himalayan Region.The species is also considered as indicator species for monitoring the past and recent climate change impact.The current study was carried out in the natural populations of B.utilis from the sub-alpine zone of North-western Indian Himalaya.The birch dominated forest harbors a total of 305 plant species comprising Angiosperms(51 families,160 genera and 277 species),Gymnosperms(03 families,05 genera and 07 species)and Pteridophytes(07 families,11 genera and 21 species)with Asteraceae,Ranunculaceae and Rosaceae as dominant family.Birch forests are found dominant in shady moist habitat and North West aspect.Geographical characteristics,anthropogenic and developmental activities affect the population structure of B.utilis and associated species.However,the species has fair regeneration status in the study area.The acidic nature of soil pH and spatial variation in edaphic characteristics may be due to geographical differences,rooting patterns and litter accumulation of below and above-ground vegetation.Biomass estimation of a representative population of B.utilis from each site showed that TAGBD,TCD and TBD were found maximum in ST3(Hamta Pass II site).The CCA analysis determined that environmental variables such as altitude,organic matter,available phosphorous,organic carbon,available nitrogen,and electrical conductivity played a significant role in determining tree species composition and distribution in B.utilis dominated forests.

Environmental characteristics of trace metals in seawater from the Ninety East Ridge in the Indian Ocean

The Ninety East Ridge in the Indian Ocean has complex and unique characteristics.The concentrations and distribution characteristics of 10 trace metals(V,Cr,Mn,Fe,Co,Ni,Cu,Cd,Pb,and U)in seawater from the Ninety East Ridge in the Indian Ocean were investigated.Results show that the average concentrations of different trace metals in all the collected seawater samples were 1.134μg/L for V,0.158μg/L for Cr,0.489μg/L for Mn,0.427μg/L for Fe,0.011μg/L for Co,0.395μg/L for Ni,0.403μg/L for Cu,0.097μg/L for Cd,0.139μg/L for Pb,and 3.470μg/L for U.Differences in the horizontal and vertical distributions of all measured trace metals were revealed,and the occurrence of high concentrations was nonuniform.In addition,the significant differences in the concentration distribution of different trace metals in seawater on both sides of the Ninety East Ridge present regional segmentation in the area for various trace metals in deep sea water.This study provided basic data for future investigations on the environmental and ecological impact of trace metals in the Indian Ocean and the potential water mass transport mechanism.

Synergistic Impacts of Indian Ocean SST and Indo-China Peninsula Soil Moisture on the 2020 Record-breaking Mei-yu

The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.

Distribution and influencing factors of microeukaryote in different water layers of the southwestern Indian Ocean Ridge

Microeukaryotes play a vital role in shaping marine ecosystems,especially in marine productivity,the microbial food web,and carbon cycle.The Indian Ocean is one of the largest oligotrophic areas in the world,but little is known about the biodiversity of microeukaryotes in the area.The community composition and geographical distribution of microeukaryotes collected from the surface(SUR)and deep chlorophyll maximum(DCM)layers in the southwestern Indian Ocean were studied using high-throughput sequencing of the 18S rRNA gene.The metagenomic data helped quantify the impact of environmental factors on microeukaryotic communities.The relative abundance of different taxa groups exhibited distinct patterns between SUR and DCM layers,except for the most dominant Dinoflagellata that accounted for more than 40.6%abundance in each sample.Radiolaria was much more abundant in the nutrient-rich DCM layer than the SUR layer.The community similarity of microeukaryotes decreased with increasing of geographic distance,whereas the temperature and inorganic nitrogen were the most important environmental parameters to community structure.Abundant communities were more influenced by dispersal limitations and rare communities were more responsive to environmental factors.Correlation network analyses revealed strong biotic interactions indicative of parasitism,predation and competition,and their contribution to microeukaryotic population in diverse environments.Overall,this study provided insights into the biodiversity of microeukaryotes by characterizing the differences between water layers and identifying the driving factors in the ocean.

Observation of Low-Level Jets in the Eastern Tropical Indian Ocean Based on Shipborne Coherent Doppler Lidar

In contrast to the Pacific and Atlantic Oceans,the Indian Ocean has lacked in-situ observations of wind profiles over open sea areas for decades.In 2021,a shipborne coherent Doppler lidar(CDL)was used to observe in-situ wind profiles in the eastern tropical Indian Ocean.This equipment successfully captured low-level jets(LLJs)in the region,and their characteristics were thoroughly analyzed.Results reveal that the observed wind speed of LLJs in the eastern Indian Ocean ranges from 6 m s^(-1) to 10 m s^(-1) during the boreal winter and spring seasons,showing a height range of 0.6 to 1 km and two peak times at 0800 and 2000 UTC.This wind shear is weaker than that in land or offshore areas,ranging from 0 s^(-1) to 0.006 s^(-1).Moreover,the accuracy of the CDL data is compared to that of ERA5 data in the study area.The results indicate that the zonal wind from ERA5 data significantly deviated from the CDL measurement data,and the overall ERA5 data are substantially weaker than the in-situ observations.Notably,ERA5 underestimates northwestward LLJs.

Corrections of shipboard GPS radiosonde soundings and applications on historical records in the eastern tropical Indian Ocean and South China Sea

Shipboard radiosonde soundings are important for detecting and quantifying the multiscale variability of atmosphere-ocean interactions associated with mass exchanges.This study evaluated the accuracies of shipboard Global Positioning System(GPS)soundings in the eastern tropical Indian Ocean and South China Sea through a simultaneous balloon-borne inter-comparison of different radiosonde types.Our results indicate that the temperature and relative humidity(RH)measurements of GPS-TanKong(GPS-TK)radiosonde(used at most stations before 2012)have larger biases than those of ChangFeng-06-A(CF-06-A)radiosonde(widely used in current observation)when compared to reference data from Vaisala RS92-SGP radiosonde,with a warm bias of 5℃and dry bias of 10%during daytimes,and a cooling bias of-0.8℃and a moist bias of 6%during nighttime.These systematic biases are primarily attributed to the radiation effects and altitude deviation.An empirical correction algorithm was developed to retrieve the atmospheric temperature and RH profiles.The corrected profiles agree well with that of RS92-SGP,except for uncertainties of CF-06-A in the stratosphere.These correction algorithms were applied to the GPS-TK historical sounding records,reducing biases in the corrected temperature and RH profiles when compared to radio occultation data.The correction of GPS-TK historical records illustrated an improvement in capturing the marine atmospheric structure,with more accurate atmospheric boundary layer height,convective available potential energy,and convective inhibition in the tropical ocean.This study contributes significantly to improving the quality of GPS radiosonde soundings and promotes the sharing of observation in the eastern tropical Indian Ocean and South China Sea.

Accuracy assessment of global vertical displacement loading tide models for the equatorial and Indian Ocean

The three-dimensional displacements caused by ocean loading effects are significant enough to impact spatial geodetic measurements on sub-daily or longer timescales,particularly in the vertical direction.Currently,most tide models incorporate the distribution of vertical displacement loading tides;however,their accuracy has not been assessed for the equatorial and Indian Ocean regions.Global Positioning System(GPS)observations provide high-precision data on sea-level changes,enabling the assessment of the accuracy and reliability of vertical displacement tide models.However,because the tidal period of the K_(2) constituent is almost identical to the orbital period of GPS constellations,the estimation of the K_(2) tidal constituent from GPS observations is not satisfactory.In this study,the principle of smoothness is employed to correct the systematic error in K_(2) estimates in GPS observations through quadratic fitting.Using the adjusted harmonic constants from 31 GPS stations for the equatorial and Indian Ocean,the accuracy of eight major constituents from five global vertical displacement tide models(FES2014,EOT11a,GOT4.10c,GOT4.8,and NAO.99b)is evaluated for the equatorial and Indian Ocean.The results indicate that the EOT11a and FES2014 models exhibit higher accuracy in the vertical displacement tide models for the equatorial and Indian Ocean,with root sum squares errors of 2.29 mm and 2.34 mm,res-pectively.Furthermore,a brief analysis of the vertical displacement tide distribution characteristics of the eight major constituents for the equatorial and Indian Ocean was conducted using the EOT11a model.

Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Contrasting physical mechanisms of yellowfin tuna fluctuations between the western and eastern Indian Ocean

As an economically critical pelagic migratory species,yellowfin tuna(Thunnus albacores,YFT)is very sensible to physical and environmental conditions,such as sea surface temperature(SST),ocean heat content(OHC),and the mixed layer depth(MLD).We investigated the impact of SST,OHC,and MLD on fluctuations of YFT catch in the western/eastern Indian Ocean using the long time series of 63-year environmental and YFT datasets.We found that the impact of SST on YFT was heavily overestimated in the past,and MLD plays a more critical role in the YFT catch fluctuation.When the MLD deepens(>34.8 m),SST was more influential in predicting the catches of YFT than OHC in the western Indian Ocean,and OHC was more critical to YFT than SST in the eastern Indian Ocean.However,when the MLD shallows(<34.8 m),MLD was more vital to predict the catch per unit effort(CPUE)of YFT than SST/OHC in the western.After 2000,there was an asynchronous pattern of YFT CPUE induced by higher frequency variations and ocean hiatus of SST/OHC signals in the western and eastern Indian Oceans basins.The impact of the subsurface hiatus may induce the decrease of YFT in the eastern Indian Ocean.The above findings clarified a non-stationary relationship between the environmental factors and catches of YFT and provided new insights into variations in YFT abundance.

Correlation of Rainfall Anomalies in Rwanda from September to December (SOND) with Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) Events

Understanding the relationship between rainfall anomalies and large-scale systems is critical for driving adaptation and mitigation strategies in socioeconomic sectors. This study therefore aims primarily to investigate the correlation between rainfall anomalies in Rwanda during the months of September to December (SOND) with the occurrences of Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) events. The study is useful for early warning and forecasting of negative effects associated with extreme rainfall anomalies across the country, using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), the National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research (NCAR) reanalysis sea surface temperature and ERA5 reanalysis datasets, during the period of 1983-2021. Both empirical orthogonal function (EOF), correlation analysis and composite analysis were used to delineate variability, relationship and the related atmospheric circulation between Rwanda seasonal rainfall September to December (SOND) with Indian Ocean Dipole (IOD) and El-Nino Southern Oscillation (ENSO). The results for Empirical Orthogonal Function (EOF) for the reconstructed rainfall data set showed three modes. EOF-1, EOF-2 and EOF-3 with their total variance of 63.6%, 16.5% and 4.8%, Indian ocean dipole (IOD) events resulted to a strong positive correlation of rainfall anomalies and Dipole model index (DMI) (r = 0.42, p value = 0.001, DF = 37) significant at 95% confidence level. The composite analysis for the reanalysis dataset was carried out to show the circulation patterns during four different events correlated with September to December seasonal rainfall in Rwanda using T-test at 95% confidence level. Wind anomaly revealed that there was a convergence of south westerly winds and easterly wind over the study area during positive Indian Ocean Diploe (PIOD) and PIOD with El Nino concurrence event years. The finding of this study will contribute to the enhancement of SOND seasonal rainfall forecasting and the reduction of vulnerability during IOD (ENSO) event years.

The Relationship between Extreme Precipitation Events in East Africa during the Short Rainy Season and Indian Ocean Sea Surface Temperature

The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.

Indian: Textile industry perspectives from 2023 and hopes for 2024

The year gone by has been one of the most challenging years for the Indian textile industry.The major challenges have been the fluctuating cotton prices,diminishing demand,capacity under-utilization and dumping of imported fabrics and garments from China and Bangladesh.The buying by the US and EU has remained quite low and that too for an unusually longer period,which has affected the exports badly.

Study on the relationship between ENSO and tropical Indian Ocean temperature

The relationship between ENSO and Indian Ocean Dipole was discussed by using the data set of sea temperature from Scripps Institute of Oceanography, the air temperature at 1000hPa from the NCEP reanalysis data and the Nino3 index from the Climate Prediction Center （CPC） of U.S.A. during the period from 1955 to 2001. The results show that there exists a Dipole on the maximum temperature anomalous level （MTAL） in the Indian Ocean, which close relates to ENSO in the Pacific Ocean. During El Nino periods there are good relationships between ENSO and Indian Ocean Dipole which maximum correlation occurring when ENSO leads by one month, but in La Nina periods the relationship is not so good. The distribution of Dipole in Indian Ocean is from northeast to southwest, which one （west） pole in 65°E - 75°E, 6°S - 10°S and the other in 85°E - 95°E, 2°N - 6°N, which is different from that defined by Saij. The correlation coefficients of Nino3 index with temperature anomalies in the west/east poles on the MTAL are over 0.4 - 0.15, respectively. It is a main sea temperature system in the tropical Indian Ocean. However, in the surface layer from sea surface to the depth of 20 m - 30 m there is no such a dipole with opposite sea temperature anomalies in the NE and SW of tropical Indian Ocean. The SSTA in the NE might be influenced by the sensible exchange process because the evolution of sea and 1 000 hPa air temperature anomaly time series of the NE of tropical Indian Ocean is quite similar except those during 1962 - 1963 and 1986. The periods of Indian Ocean Dipole are shorter than that of ENSO, and about 1 to 6-year.

Indian hedgehog在宫颈癌及其癌前病变早期诊断中的意义

[目的]探讨Indian hedgehog(IHH)过度表达在早期发现宫颈癌及其癌前病变中的病理学意义.[方法]采用免疫组织化学染色方法对37例宫颈浸润型鳞状上皮癌、37例宫颈上皮内新生物(CIN)及32例非肿瘤性宫颈病变标本进行IHH蛋白表达情况的检测.[结果]13例宫颈浸润型鳞状上皮癌、7例CINⅢ病变及2例CINⅡ病变标本中IHH特异性地表达在癌细胞和不典型增生细胞胞浆中.[结论]IHH的过度表达是早期诊断宫颈癌及其癌前病变的有效指标.