Search results for: drought tolerance indices

Authors: Sajjad Rezaei, Mahdieh Molanouri Shamsi, Azadeh Jamali

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Background and purpose: Surfactant protein D (SP-D) is a lung-specific protein that is detectable in human plasma. Effect of exercise training on SP-D levels as well as its relation to metabolic indices is not known. The present study then aimed to investigate the effects of 10 weeks of aerobic training on serum levels of SP-D and insulin resistance in women with type 2 diabetes. Materials and methods: Twenty-two overweight women with type 2 diabetes mellitus were recruited through deliberate sampling and randomly assigned to intervention and control groups (11 in each group). The intervention group underwent a progressive aerobic training program for 10 weeks, 3 days per week, 30-55 min/day at 50-75% heart rate reserve (HRR). Control group continued with its everyday routine. Blood samples were obtained before and after training for biochemical analysis. Within-group and between-group differences were analyzed with paired and independent t-tests in spss software, respectively, and the relation between variables was analyzed with Pearson’s correlation coefficient (all at P = 0.05). Results: Significant differences were observed between groups in leptin, glucose, waist circumference and VO2 max after training. SP-D was decreased and VO2 max was increased significantly in intervention group. However, no significant correlation was observed between SP-D and other variables. Conclusion: Since there was no corresponding decrease in insulin resistance with decreased levels of SP-D, it seems unlikely for SP-D to mediate the association between obesity and insulin resistance in type 2 diabetics.

Keywords: exercise training, SP-D, insulin resistance, type 2 diabetes

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Authors: D. Hilton

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An analysis of the Australian Diabetes Screening Study estimated undiagnosed diabetes mellitus [DM] prevalence in a high risk general practice based cohort. DM prevalence varied from 9.4% to 18.1% depending upon the diagnostic criteria utilised with age being a highly significant risk factor. Utilising the gold standard oral glucose tolerance test, the prevalence of DM was 22-23% in those aged >= 70 years and <15% in those aged 40-59 years. Opportunistic screening in Australian general practice potentially can identify many persons with undiagnosed type 2 DM. An Australian Bureau of Statistics document published three years ago, reported the highest rate of DM in men aged 65-74 years [19%] whereas the rate for women was highest in those over 75 years [13%]. If you consider that the Australian Bureau of Statistics report in 2007 found that 13% of the population was over 65 years of age and that this will increase to 23-25% by 2056 with a further projected increase to 25-28% by 2101, obviously this information has to be factored into the equation when age related diabetes prevalence predictions are calculated. This 10-15% proportional increase of elderly persons within the population demographics has dramatic implications for the estimated number of elderly persons with DM in these age groupings. Computational methodology showing the age related demographic changes reported in these official statistical documents will be done showing estimates for 2056 and 2101 for different age groups. This has relevance for future diabetes prevalence rates and shows that along with many countries worldwide Australia is facing an increasing pandemic. In contrast Japan is expected to have a decrease in the next twenty years in the number of persons with diabetes.

Keywords: epidemiological methods, aging, prevalence, diabetes mellitus

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Authors: S. Zev Kalifon

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The question of polygamy for Moslem minorities in Western nations has often been raised in the political and social discourse. Can polygamy be tolerated as a religious or human right in the West. For example, before the 2015 election in Israel, changes were made in the electoral system, which encouraged three small Arab parties to merge into one list. This “Unity List” included the socially liberal Communist list and a socially conservative Islamist list. Two members of the Islamist list were polygamists. Some rival politicians called for the election board to disqualify these men (and even the whole list) from the election process. This request was denied by the courts, and the men were elected to the parliament. Their subsequent seating in the parliament was questioned by many on both the liberal and conservative sides of the political spectrum. Some political commentators went so far as to describe polygamy as a “mark of disgrace” (a term usually reserved for people convicted on corruption charges). There are also problems in other areas of society; these include the rights of these families for welfare and social services (public policy issues) and residence in Israel. Using qualitative methods (primarily historical and archival data), this paper will analyze at the historic and cultural processes which created the intense opposition to polygamy in Judaism (for Israel) and Christianity (for the Western world). It will look at the debate over the "religious right" of polygamy for Moslem citizens in Israel and other Western cultures. Finally, it will examine the political, cultural, and demographic pressures which encourage polygamy in these minorities. This paper will demonstrate that the debate over polygamy is more than a question of religious freedom or human rights or multi-culturalism. It is a central symbol of modernity and the Western worldview.

Keywords: human rights, Judaism, multi-culturalism, polygamy, western values

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Authors: T. P. Muhammed Jamsheer

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This paper tries to explains some of differences between migrants and non-migrants households by taking ten indicators like land ownership, land distribution, lease in land, lease out land, demand of labour, supply of labour, land operational potential, holding of agriculture implements and livestock’s, irrigation potential of households and credit holding by the households of highly dry, drought affected, poverty stricken, multi caste and pluralistic sub castes village in very backward Mahabubnagar district of Andhra Pradesh. The paper is purely field work based research and conducted census survey of field work among the 298 households in highly dry village called Keppatta from Bhoothpur mandel. One of the main objectives of the paper is that, to find out the factors which differentiate migrants and non-migrants households and what are distress elements which forced the poor peasants migrants to outside the village. It concludes that among the migrants and non-migrants households and among the differences between the categories wise of both types of households, there are differences, except two indicators like lease in and lease out, all other indicators like land holding pattern, demand and supply of labour, land operation, irrigation potential, implements and livestock and credit facilities of migrants and non-migrants households shows that non-migrants have high share than the migrants households. This paper also showing the landed households are more migrants, means among the BC and FC households landed households are migrants while SC landless are more migrants which is contradictory to general/existing literatures conclusion that, landless are more migrant than landed households, here also showing that when the number of land in acres increases the share of SC is declining while the share of FC is increasing among the both migrants and non-migrants households. In the class wise SC households are more in distress situation than any other class and that might be leading to the highest share of migrants from the respective village. In the logistic econometric model to find out the relation between migration and other ten variables, the result shows that supply of labour, lease in of the land and size of the family are statically significantly related with migration and all other variables not significant relation with migration although the theoretical explanation shows the different results.

Keywords: class, migrants, non migrants, economic indicators, distress factors

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Authors: M. J. Pourvaghar, M. E. Bahram, M. Sayyah, Sh. Khoshemehry

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Adiponectin is a cytokine secreted by the adipose tissue that functions as an anti-inflammatory, antiathrogenic and anti-diabetic substance. Its density is inversely correlated with body mass index. The purpose of this research was to examine the effect of 12 weeks of high intensity interval training (HIIT) with the level of serum adiponectin and some selected adiposity markers in overweight and fat college students. This was a clinical research in which 24 students with BMI between 25 kg/m² to 30 kg/m². The sample was purposefully selected and then randomly assigned into two groups of experimental (age =22.7±1.5 yr.; weight = 85.8±3.18 kg and height =178.7±3.29 cm) and control (age =23.1±1.1 yr.; weight = 79.1±2.4 kg and height =181.3±4.6 cm), respectively. The experimental group participated in an aerobic exercise program for 12 weeks, three sessions per weeks at a high intensity between 85% to 95% of maximum heart rate (considering the over load principle). Prior and after the termination of exercise protocol, the level of serum adiponectin, BMI, waist to hip ratio, and body fat percentages were calculated. The data were analyzed by using SPSS: PC 16.0 and statistical procedure such as ANCOVA, was used. The results indicated that 12 weeks of intensive interval training led to the increase of serum adiponectin level and decrease of body weight, body fat percent, body mass index and waist to hip ratio (P < 0.05). Based on the results of this research, it may be concluded that participation in intensive interval training for 12 weeks is a non-invasive treatment to increase the adiponectin level while decreasing some of the anthropometric indices associated with obesity or being overweight.

Keywords: adiponectin, cardiovascular, interval, overweight, training

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Authors: Timma Reddy, Srikonda Ramesh

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India has been traditionally vulnerable to natural disasters such as Floods, droughts, cyclones, earthquakes and landslides. It has become a recurrent phenomenon as observed in last five decades. The survey indicates that about 60% of the landmass is prone to earthquakes of various intensities; over 40 million hectares is prone to floods; about 8% of the total area is prone to cyclones and 68% of the area is susceptible to drought. Climate change is likely to be perceived through experience of extreme weather events. There is growing societal concern about climate change, given the potential impacts of associated natural hazards such as cyclones, flooding, earthquakes, landslides etc, hence it is essential and crucial to strengthening our settlements to respond to such calamities. So, the research paper focus is to analyze the effective planning strategy/mechanism to integrate disaster mitigation measures in coastal regions in general and Capital Region of Andhra Pradesh in particular. The basic hypothesis is to govern the appropriate special planning considerations would facilitate to have organized way of protective life and properties from natural disasters. And further to integrate the infrastructure planning with conscious direction would provide an effective mitigations measures. It has been planned and analyzed to Vijayawada city with conscious land use planning with reference to space syntax trajectory in accordance to required social infrastructure such as health facilities, institution areas and recreational and other open spaces. It has been identified that the geographically ideal location with reference to the population densities based on GIS tools the properness strategies can be effectively integrated to protect the life and to save the properties by means of reducing the damage/impact of natural disasters in general earth quake/cyclones or floods in particularly.

Keywords: modular, trajectories, social infrastructure, evidence based syntax, drills and equipments, GIS, geographical micro zoning, high resolution satellite image

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Authors: Ahmed Ali Samejo, Riffat Sultana

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Pakistan has the sandy Thar Desert in the eastern area, which share border line with India and has exotic fauna and flora, the livelihood of native people rely on livestock and rain fed cultivated fields. The climate of Thar Desert is very harsh and stressful due to frequent drought and very little rainfall, which may occur during monsoon season in the months of July to October and temperature is high, and wind speed also increases in April to June. Schistocerca gregaria is a destructive pest of vegetation from Mauritania to the border line of Pakistan and India. Sometimes they produce swarms which consume all plant where ever they land down and cause the loss in agro-economy of the world. During the recent study, we observed that vegetation was not unique throughout the Thar Desert in the year 2015, because the first spell of rainfall showered over all areas of the Thar Desert in July. However, the second and third spell of rain was confined to village Mahandre jo par and surroundings from August to October. Consequently, vegetation and cultivated crops grew up specially bajra crop (Pennistum glaucum). The climate of Mahandre jo par and surroundings became favorable for S.gregaria, and remaining areas of Thar Desert went hostile. Therefore desert locust attracted to the pleasant area (Mahandre jo par and surroundings) and gradually concentrated, increased reproductive activities, but did not gregarize due to the harvest of bajra crop and the onset of the winter season with an immediate decrease in temperature. An outbreak was near to come into existence, and thereupon conditions become stressful for hoppers to continue further development. Afore mentioned was one reason behind hurdle to the outbreak, another reason might be that migration and concentration of desert locust took place at the end of the season, so climate becomes unfavorable for hoppers, due to dryness of vegetation. Soils also become dry, because rainfall was not showered in end of the season, that’s why eggs that were deposited in late summer were desiccated. This data might be proved fruitful to forecast any outbreak update in future.

Keywords: agro-economy, destructive pest, climate, outbreak, vegetation

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Authors: Elvira Hörandl

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The term “Geographical parthenogenesis” describes the phenomenon that asexual organisms usually occupy larger and more northern distribution areas than their sexual relatives and tend to colonize previously glaciated areas. Several case studies in flowering plants confirm the geographical pattern, but the causal factors behind the phenomenon are still unclear. Previous authors regarded predominant polyploidy in asexual (apomictic) plants as the main factor. However, the geographical pattern is not the rule for sexual polyploids. Recent research confirmed a previous hypothesis of the author that a combination of factors is acting: Although uniparental reproduction provides better colonization abilities, it is most efficient in combination with polyploidy. I will present results on case studies in the genus Ranunculus of both autopolyploid and allopolyploid species and species complexes reproducing via facultative apomixis. Polyploidy seems to contribute mainly to a better tolerance of colder climates and temperate extremes, whereby epigenetic flexibility, changes in gene expression, and phenotypic plasticity play an important role in occupying ecological niches under harsh conditions. Phylogenomic studies entangle complex hybrid origins of asexual taxa, which increases intragenomic heterozygosity of asexual plants. Interestingly, our results suggest an association of sexuality with abiotic stresses, specifically with light stress, which might explain that still, most plants in high altitudes and in southern areas retain sexual reproduction despite other climatic conditions that would favor apomictic plants. We conclude that geographical parthenogenesis results from the complex interplay of the genomic constitution, mode of reproduction and environmental factors.

Keywords: apomixis, polyploidy, hybridization, abiotic stress, epigenetics, phylogenomics

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Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

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Authors: Peter John, Zainab Ali, Attya Bhatti

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Rheumatoid Arthritis (RA) is a systemic autoimmune inflammatory disease that primarily affects the joints. RA is caused in many cases by the interaction between genes and environmental factors, including tobacco, that primarily involves synovial joints. It typically starts in small peripheral joints, is usually symmetric, and progresses to involve proximal joints if left untreated. The prevalence of rheumatoid arthritis varies substantially around the globe, ranging from 0·25% to 1%.3. Rheumatoid arthritis can affect individuals of any age, with an increased incidence in people older than 40 years. Women are affected two to three times more frequently than men. The present work involved evaluating the toxicity and therapeutic potential of Dodonaea viscosa in a collagen-induced arthritic mouse model. Chemical analysis exhibited that Dodonaea viscosa has high levels of beneficial compounds, including phenols, flavonoids, and other phytochemicals. The Dodonaea viscosa showed significant antioxidant, anti-inflammatory, and anti-arthritic potential without toxic effects. Arthritic mice treated with Dodonaea viscosa showed reduced levels of rheumatoid factor and paw edema, while no significant effects on spleen indices and radiological examination of paws were found compared to control untreated arthritic mice. In summary, the Dodonaea viscosa treatment results in improvement in Arthritic Mice Model for which further studies are required.

Keywords: rheumatoid arthritis, dodonaea viscisa, anti-inflammatory, anti-rheumatic

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Authors: Megersa Olumana Dinka, Kassahun Birhanu Tadesse

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Irrigation suitability of shallow groundwater (SGW) was investigated by taking thirty groundwater samples from piezometers and hand-dug wells in Wonji Shoa Sugar Estate (WSSE) (Ethiopia). Many physicochemical parameters (Mg²⁺, Na⁺, Ca²⁺, K⁺, CO₃-, SO4²⁻, HCO₃⁻, Cl⁻, TH, EC, TDS and pH) were analyzed following standard procedures. Different irrigation indices (MAR, SSP, SAR, RSC, KR, and PI) were also used for SGW suitability assessment. If all SGW are blended and used for irrigation, the salinity problem would be slight to moderate, and 100% of potential sugarcane yield could be obtained. The infiltration and sodium ion toxicity problems of the blended water would be none to moderate, and slight to moderate, respectively. As sugarcane is semi-tolerant to sodium toxicity, no significant sodium toxicity problem would be expected from the use of blended water. Blending SGW would also reduce each chloride and boron ion toxicity to none. In general, the rating of SGW was good to excellent for irrigation in terms of average EC (salinity), and excellent in terms of average SAR (infiltration). The SGW of the WSSE was categorized under C3S1 (high salinity and low sodium hazard). In conclusion, the conjunctive use of groundwater for irrigation would help to reduce the potential effect of waterlogging and salinization and their associated problems on soil and sugarcane production and productivity. However, a high value of SSP and RSC indicate a high possibility of infiltration problem. Hence, it is advisable to use the SGW for irrigation after blending with surface water. In this case, the optimum blending ratio of the surface to SGW sources has to be determined for sustainable sugarcane productivity.

Keywords: blending, infiltration, salinity, sodicity, sugarcane, toxicity

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Authors: Teklebrhan Kidane

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The aim of this study is to investigate the species diversity and relative abundance of migratory waterbirds in Abijata Lake, an Important Bird Area and potential Ramsar site located in the Central Rift Valley of Ethiopia. The study was carried out, using line transect method along the shoreline and open area of the Lake. The data was analyzed with different diversity indices; t-Test and descriptive statistics. Thirty-two migratory waterbird species grouped into twelve families consisting of globally threatened birds were identified and recorded. Family Scolopacidae (12 species) had the highest number of species. The lowest number of species was observed under the families Ciconidae, Accipitridae, Laridae and Falconidae with one species each. The recorded bird species comprised 19 Palearctic, 5 Intra-African, 2 local migrants as well as 6 resident Palearctic migratory waterbird species. The dry season had higher species diversity (H'=1.01) compared to the wet season (H'=0.76). The highest and lowest diversity of migratory waterbirds were recorded during January (H'= 1.28) and June (H'= 0.52), respectively. However, the highest evenness (E) of bird species was recorded during wet season (E=0.21) and lower during the dry season (E=0.09). The computed seasonal effect reveals that there is significant effect of seasons on species diversity (t=2.80, P < 0.05), but the effect of seasons on individuals of migratory bird species was not significant (t=1.42, P > 0.05). Even though Lake Abijata is the sanctuary of several migratory waterbirds, anthropogenic activities are rigorously threatening their survival. Therefore, it needs an urgent conservation concern.

Keywords: migration, important bird area, species diversity, wetland birds

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Adiaha A. A. Ugwumba, Femi V. Oluwale

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Sizes at maturity (Lₘ₅₀), fecundity, sex ratio, and gonadosomatic indices (GSI) of the reticulate knife fish, Papyrocranus afer, collected from Lekki Lagoon, were investigated. A Total of 1154 specimens with standard lengths of 5.2-75.9 cm (mean = 34.86±17.2cm) and body weight of 7.9-1, 958.8g (mean = 249.12±28.56g) were collected by means of artisanal passive and active gears (traps, long lines, and nets) and examined. Sexes of fish specimens were determined macroscopically and microscopically after dissection. The length at which 50% of the fish population reached sexual maturity (Lₘ₅₀) was considered as length at sexual maturity. Fecundity was determined by total counts of eggs; sex ratio by the proportion of males to females, while GSI was determined as gonad weight expressed as a percentage of total body weight. Results showed that the most frequently caught fish was 34.5cm long, while the sizes at maturity were 49.1cm (males) and 53.4cm (females). Matured specimens had characteristic urinogenital papillae prominent in males but vestigial in females. Sex ratio (1: 0.6; Male: female) was significantly different (X² (1) = 32.21, p < 0.0001). Fecundity was low (mean 49 ± 17 eggs for a fish of 52.86 ±7.53cm); it increased with fish size (r = 0.71). Higher GSI during the rainy season with a peak in July (female: 0.44 ± 0.14 %; male: 0.22 ± 0.01 %) indicated seasonal/annual spawning. Low fecundity and annual spawning underlined the need for sustainable management of this species in Lekki Lagoon.

Keywords: breeding season, fecundity, gonad maturity, Lekki lagoon, Papyrocranus afer, sex ratio

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Authors: Sandeep Thakur, Ismail Mondal, Phani Bhusan Ghosh, Papita Das, Tarun Kumar De

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Sundarbans Reserve forest of India has been undergoing major transformations in the recent past owing to population pressure and related changes. This has brought about major changes in the spatial landscape of the region especially in the western parts. This study attempts to assess the impacts of the Landcover changes on the mangrove habitats. Time series imageries of Landsat were used to analyze the Normalized Differential Vegetation Index (NDVI) patterns over the western parts of Indian Sundarbans forest in order to assess the heath of the mangroves in the region. The images were subjected to Land use Land cover (LULC) classification using sub-pixel classification techniques in ERDAS Imagine software and the changes were mapped. The spatial proliferation of aquaculture farms during the study period was also mapped. A multivariate regression analysis was carried out between the obtained NDVI values and the LULC classes. Similarly, the observed meteorological data sets (time series rainfall and minimum and maximum temperature) were also statistically correlated for regression. The study demonstrated the application of NDVI in assessing the environmental status of mangroves as the relationship between the changes in the environmental variables and the remote sensing based indices felicitate an efficient evaluation of environmental variables, which can be used in the coastal zone monitoring and development processes.

Keywords: aquaculture farms, LULC, Mangrove, NDVI

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Authors: Ange Weinrabe, James Tran, Ian B. Hickie

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Risk-taking behaviour is common during youth. In the time between adolescence and early adulthood, young people (aged 15-25 years) are more vulnerable to mood disorders, such as anxiety and depression. What impact does an emerging mood disorder have on decision-making in youth at critical decision points in their lives? In this article, we explore the impact of risk and ambiguity on youth decision-making in a clinical setting using a well-known economic experiment. At two time points, separated by six to eight weeks, we measured risky and ambiguous choices concurrently with findings from three psychological questionnaires, the 10-item Kessler Psychological Distress Scale (K10), the 17-item Quick Inventory of Depressive Symptomatology Adolescent Version (QIDS-A17), and the 12-item Somatic and Psychological Health Report (SPHERE-12), for young help seekers aged 16-25 (n=30, mean age 19.22 years, 19 males). When first arriving for care, we found that 50% (n=15) of participants experienced severe anxiety (K10 ≥ 30) and were severely depressed (QIDS-A17 ≥ 16). In Session 2, taking attrition rates into account (n=5), we found that 44% (n=11) remained severe across the full battery of questionnaires. When applying multiple regression analyses of the pooled sample of observations (N=55), across both sessions, we found that participants who rated severely anxious avoided making risky decisions. We suggest there is some statistically significant (although weak) (p=0.09) relation between risk and severe anxiety scores as measured by K10. Our findings may support working with novel tools with which to evaluate youth experiencing an emerging mood disorder and their cognitive capacities influencing decision-making.

Keywords: anxiety, decision-making, risk, adolescence

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Amina M. Ibrahim, Ahmed A. Abdel-Haleem, Rania G. Taha

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Metal pollution results in many dangerous consequences to the environment and human health due to the bioaccumulation in their tissues. The present study aims to measure the bioaccumulation factor of the Manganese (Mn) heavy metal in Biomphlaria alexandrina snails' tissues and water samples. The present results showed the concentration of Mn heavy metal in water (87.5 mg/l) and its bioaccumulation factor in Helisoma duryi tissue was higher than that in tissues of Physa acuta and B. alexandrina snails. Results showed that 87.5 mg/l Mn concentration had miracidial and cercaricidal activities. Also, this concentration decreased the mean total number of the hemocytes after exposure for 24h or 48h, while increased both the mean mortality and phagocytic indices of the hemocytes of exposed snails. It caused alterations in the cytomorphology of the hemocytes of exposed snails after 24 or 48h, where, the granulocytes had irregular cell membrane, and forming pseudopodia. Besides, both levels of Testosterone (T) and Estradiol (E) were increased after exposure to 87.5mg/l Mn metal compared to the control group. Also, it increased MDA (Malonaldehyde) and TAC (Total antioxidant capacity) contents, while, decreased SOD (superoxide dismutase). Besides, it caused great histopathological damages in both hermaphrodite and digestive glands, represented in the degeneration of the gonadal, digestive, secretory cells and the connective tissues. Therefore, B. alexandrina might be used as sensitive bio-indicator of pollution with Mn heavy metal to avoid ethics rules; beside they are easily available and large in number.

Keywords: manganese metal, B. alexandrina, hormonal alterations, histopathology

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Authors: Muhammad Ashfaq, Muhammad Saleem Haider, Muhammad Ali, Muhammad Sajjad, Amna Ali, Urooj Mubashar

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Phenotypic diversity was confirmed by measuring different morphological traits i.e. seed traits (seed length, seed width, seed thickness, seed length-width ratio, 1000 grain weight) and root-shoot traits (shoot length, root length, shoot fresh weight, root fresh weight, root-shoot ratio, root numbers and root thickness). Variance and association study of desirable traits determine the genotypic differences among the rice germplasm. All the traits showed significant differences among the genotypes. The traits were studied in Randomized complete block design (RCBD) at different water levels. Some traits showed positive correlation with each other and beneficial for increasing the yield and production of the crop. Seed thickness has positive correlation with seed length and seed width (r= 0.104**, r=0.246**). On the other hand, various root shoot traits showed positive highly significant association at different water levels i.e. root length, fresh root weight, root thickness, shoot thickness and root numbers. Our main focus to study the performance/correlation of root shoots traits under stress condition. Fresh root weight, shoot thickness and root numbers showed positive significant association with shoot length, root length, fresh root and shoot weight (r=0.2530**, r=0.2891**, r=0.4626**, r=0.4515**, r=0.5781**, r=0.7164**, r=0.0603**, r= 0.5570**, r=0.5824**). Long root length genotypes favors and suitable for drought stress conditions and screening of diverse genotypes for the further development of new plant material that performing well under different environmental conditions. After screening genetic diversity of potential rice, lines were studied to check the polymorphism by using some SSR markers. DNA was extracted, and PCR analyses were done to study PIC values and allelic diversity of the genotypes. The main objective of this study is to screen out the genotypes on the basis of various genotypic and phenotypic traits.

Keywords: rice, morphological traits, association, germplasm, genetic diversity, water levels, variation

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Authors: Parul Suraia, Harshit Sosan Lakra

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Indigenous communities represent some of the most marginalized populations globally, with India labeled as tribals, experiencing particularly pronounced marginalization and a concerning decline in their numbers. These communities often inhabit geographically challenging regions characterized by low population densities, posing significant challenges to providing essential infrastructure services. Jharkhand, a Schedule 5 state, is infamous for its low-level health status due to disparities in access to health care. The primary objective of this study is to investigate the spatial inequalities in healthcare accessibility among tribal populations within the state and pinpoint critical areas requiring immediate attention. Health indicators were selected based on the tribal perspective and association of Sustainable Goal 3 (Good Health and Wellbeing) with other SDGs. Focused group discussions in which tribal people and tribal experts were done in order to finalize the indicators. Employing Principal Component Analysis, two essential indices were constructed: the Tribal Health Index (THI) and the Tribal Health Intervention Index (THII). Index values were calculated based on the district-wise secondary data for Jharkhand. The bivariate spatial association technique, Moran’s I was used to assess the spatial pattern of the variables to determine if there is any clustering (positive spatial autocorrelation) or dispersion (negative spatial autocorrelation) of values across Jharkhand. The results helped in facilitating targeting policy interventions in deprived areas of Jharkhand.

Keywords: tribal health, health spatial disparities, health status, Jharkhand

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Authors: Awais Ahmad, Mostafa Muhammad Selim, Ali Abdullah Alderfasi

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Water limitation is undoubtedly a critical environmental constraint limiting the crop production under arid and semiarid areas. Mung bean is susceptible to both drought and water logging stresses. Therefore, present study was conducted to assess the water deficit stress consequences of yield components and water use efficiency in Mung bean. A field experiment was conducted at Educational Farm, Crop Production Department, College of Food and Agricultural Sciences, Kind Saud University, Saudi Arabia. Trail comprised of four irrigation levels — total amount of irrigation divided into irrigation intervals — (3, 5, 7 and 9 days interval) and three Mung bean genotypes; Kawmay-1, VC-2010 and King from Egypt, Thailand and China respectively. Experiment was arranged under split plot design having irrigation as main while genotype as subplot treatment, and replicated thrice. Plant height, 100 seed weight, biological yield, seed yield, harvest index and water use efficiency were recorded at harvesting. Results revealed that decrease in irrigation have significantly hampered all the studied parameters. Mung bean genotypes have also shown significant differences for all parameters, whereas irrigation genotype interaction was highly significant for seed yield, harvest index and water use efficiency (WUE) while it was significant for biological yield. Plant height and 100 seed weight were recorded non-significant for irrigation genotype interaction. A statistically highly significant correlation among recorded parameters was observed. Minimum irrigation interval (3 days) significantly produced maximum values while VC-2010 comparatively performed better under low irrigation levels. It was concluded that Mung bean may be successfully adopted under Saudi Arabian climate but it needs high water or frequent irrigation, however, genotypic differences are a hope to develop some improved varieties with high water use efficiency.

Keywords: mung bean, irrigation intervals, water use efficiency, genotypes, yield

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Authors: Hidayah Triana, Mahir S. Gani, Asmi Citra Malina, Hamka

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This study was conducted to determine genetic diversity of tiger groupers that are resistant to V. parahaemolyticus and tolerant to low extreme salinities. This research is useful to obtain superior broodstock of fish. Tiger grouper used were 6 to 8 cm obtained from Brackish Water Aquaculture Research Center Gondol (Bali). This study consists of four stages: preliminary stage was adaptation of fish exposed to several concentrations of V. parahaemolyticus (103, 104, 105, 106, and 107 CFU / ml); second stage was test of Lethal Concentration (LC50) of bacteria to fish; third stage was salinity tolerance test (low salinity 12, 14 and 16 ppt) and fourth stage was analysis of DNA profiles. For DNA profiles analysis, genomic DNA of fish were extracted for PCR using primers YNZ-22 and UBC-122 and visualized by electrophoresis method. The results showed that Lethal concentration of bacteria (LC50) to fish was 1,56x106 CFU/ml. Furthermore, survival rate of groupers exposed with low salinities (12, 14, 16 ppt) survival rates were found to be 54,17 %, 66,67 % and 79,16 % respectively. Average of DNA fragment (5 fragments) generated from primer UBC-122 in the group of fish resistant to V.parahaemolyticus and tolerant to low salinities was similar to group of susceptible to low salinities. Primer YNZ-22 generated more diverse of DNA fragments (8,0 and 5,8 fragments) both in the group of fish tolerant and susceptible to low salinities compared to primer UBC-122 (5,0 fragments). Size of DNA 1.5 kb resulted from primer YNZ-22. Primer YNZ-22 generated 4 (50 %) and 3 (42,8 %) polymorfic fragments in the group of fish tolerant and susceptible to low salinities, respectively. Four (4) monomorfic fragments were found both in the group of fish tolerant and susceptible to low salinities. Primer UBC-122 generated 6 (85,7 %) and 9 (90,0 %) polymorfic fragments in the fish tolerant and susceptible to low salinities, respectively.

Keywords: genetic diversity, epinephelus fuscoguttatus, V. parahaemolyticus, PCR-RAPD, low extreme salinity

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Authors: Cynthia G. Esquerre, Amparo Iris Zavaleta

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Extremophiles constitute a potentially valuable source of proteases for the development of biotechnological processes; however, the number of available studies in the literature is limited compared to mesophilic counterparts. Therefore, in this study, Peruvian halophilic microorganisms were characterized to select suitable proteolytic strains that produce active proteases under exigent conditions. Proteolysis was screened using the streak plate method with gelatin or skim milk as substrates. After that, proteolytic microorganisms were selected for phenotypic characterization and screened by a semi-quantitative proteolytic test using a modified method of diffusion agar. Finally, proteolysis was evaluated using partially purified extracts by ice-cold ethanol precipitation and dialysis. All analyses were carried out over a wide range of NaCl concentrations, pH, temperature and substrates. Of a total of 60 strains, 21 proteolytic strains were selected, of these 19 were extreme halophiles and 2 were moderates. Most proteolytic strains demonstrated differences in their biochemical patterns, particularly in sugar fermentation. A total of 14 microorganisms produced extracellular proteases, 13 were neutral, and one was alkaline showing activity up to pH 9.0. Proteases hydrolyzed gelatin as the most specific substrate. In general, catalytic activity was efficient under a wide range of NaCl (1 to 4 M NaCl), temperature (37 to 55 °C) and after an ethanol exposition performed at -20 °C for 24 hours. In conclusion, this study reported 14 candidates extremely halophiles producing extracellular proteases capable of being stable and active on a wide range of NaCl, temperature and even long lasting ethanol exposition.

Keywords: biotechnological processes, ethanol exposition, extracellular proteases, extremophiles

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Authors: Katalin Gocze, Gabriella Kiss, Zsuzsanna Gurdan, Krisztian Kvell, Attila Trabert

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Introduction: On a worldwide scale running has become an increasingly popular leisure time activity during the past decade. Since the participation rate of women has risen significantly the aim of our study was to analyze the mental status, sleeping habits and the prevalence of depression among female runners. Methods: Cross-sectional analysis included the use of validated and globally used surveys for the comprehensive evaluation of insomnia (AIS), depression (BDI), exercise dependence (EDS) and exercise addiction (EAI). Recreational and amateur female runners participating at half-marathon events in Hungary were asked to take part in our pilot study. Results: Participants mean age was 42.03±9.03 years. The prevalence of imsomnia was 18.87%. 60.34% has worries regarding their weight and 43.1% think that they have an actual weight problem. 77.6% stated that their body weight has an influence on their mood. 2.7% displayed borderline clinical depression, the prevalence of mild mood disorders was 10.81%. 17.2% had previously problems with disordered eating. Participants had a mean total EDS score of 46.94±15.55 and a mean total of 13.49±3.80 on EAI. Component scores were the highest for tolerance (a need for increased amounts of exercise to achieve the desired effect or a diminished effect occurs with continued use of the same amount of exercise). Conclusion: Even tough running can help improve mental health, tackle depression and overcome adversity, athletes are at risk of experiencing psychological difficulties which have an impact on their physical perfomance as well. Further research can help initiate targeted educational and screening programs to ensure that female athletes find a path to emotional well-being.

Keywords: depression, eating disorder, exercise addiction, exercise dependence, insomnia, running

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Authors: O. A. Anjola, M. A. Adejobi, A. Ogunbameru, F. P. Agbaye, R. O. Odunukan

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This experiment was conducted for 8 weeks to evaluate the growth performance and economics of pullets fed on different dietary energy sources. A total of 300 Harco black was used for this experiment. The birds were completely randomized and divided into four diet treatment groups. Each treatment group had three replicates of twenty-five birds per replicate. Four diets containing maize, spaghetti, noodles, and biscuit was formulated to represent diet 1, 2, 3 and 4 respectively. Diet 1 containing maize is the control, while diet 2, 3, and 4 contains spaghetti, noodles, and biscuit waste meal at 100% replacement for maize on weight for weight basis. Performance indices on Feed intake, body weight, weight gain, feed conversion ratio (FCR) and economy of production were measured. Blood samples were also collected for heamatology and serum biochemistry assessment. The result of the experiment indicated that different dietary energy source fed to birds significantly (P < 0.05) affect feed intake, body weight, weight gain, and feed conversion ratio (FCR). The best cost of feed per kilogram of body weight gain was obtained in Spaghetti based diet (₦559.30). However, the best performance were obtained from diet 1(maize), it can be concluded that spaghetti as a replacement for maize in diet of pullet is most economical and profitable for production without any deleterious effects attached. Blood parameters of birds were not significantly (p > 0.05) influenced by the use of the dietary energy sources used in this experiment.

Keywords: growth performance, spaghetti, noodles, biscuit, profit, hematology, serum biochemistry

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Authors: Keivan Jmahidi, Afshin Zahedi

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To evaluate neurotoxic effects of ACR on hypothalamus of rat, amino-cupric silver staining technique of de Olmos and electron microscopic examination were conducted. For this purpose 60 adult male Wistar rats (± 250 g) were selected. Randomly assigned groups of rats (10 rats per exposure group, as A, B, C, D, E) were exposed to 0.5, 5, 50, 100 and 500 mg/kg per day×11days i.p. respectively. The remaining 10 rats were housed in group F as control group. Control rats received daily i.p. injections of 0.9% saline (3ml/kg). As indices of developing neurotoxicity, daily weight gain, gait scores and landing hindlimb foot splay (LHF) were determined. After 11 days, two rats for silver stain, and two rats for EM, were randomly selected, dissected and proper samples were collected from hypothalamus. Rats in groups D and E died within 1-2 hours due to sever toxemia. In histopathological studies no argyrophilic neurons or processes were observed in stained sections obtained from hypothalamus of rats belong to groups A, B and F, while moderate to severe argyrophilic changes were observed in different nuclei and regions of stained sections obtained from hypothalamus of rats belong to group C. In ultrastructural studies some variations in the myelin sheet of injured axons including decompactation, interlaminar space formation, disruption of the laminar sheet, accumulation of neurofilaments, vacculation and clumping inside the axolem, and finaly complete disappearance of laminar sheet were observed.

Keywords: acrylamide (ACR), amino-cupric silver staining technique of de Olmos, argyrophilia, hypothalamic neuropathy

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Authors: Zama Mahmood

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The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: Hyun-Kyung Lee, Jehyung Oh, Young Eun Jeong, Hyun-Shik Lee

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Perfluoroalkyl compounds (PFCs) are environmental toxicants that persistently accumulate in the human blood. Their widespread detection and accumulation in the environment raise concerns about whether these chemicals might be developmental toxicants and teratogens in the ecosystem. We evaluated and compared the toxicity of PFCs of containing various numbers of carbon atoms (C8-11 carbons) on vertebrate embryogenesis. We assessed the developmental toxicity and teratogenicity of various PFCs. The toxic effects on Xenopus embryos were evaluated using different methods. We measured teratogenic indices (TIs) and investigated the mechanisms underlying developmental toxicity and teratogenicity by measuring the expression of organ-specific biomarkers such as xPTB (liver), Nkx2.5 (heart), and Cyl18 (intestine). All PFCs that we tested were found to be developmental toxicants and teratogens. Their toxic effects were strengthened with increasing length of the fluorinated carbon chain. Furthermore, we produced evidence showing that perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFuDA) are more potent developmental toxicants and teratogens in an animal model compared to the other PFCs we evaluated [perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA)]. In particular, severe defects resulting from PFDA and PFuDA exposure were observed in the liver and heart, respectively, using the whole mount in situ hybridization, real-time PCR, pathologic analysis of the heart, and dissection of the liver. Our studies suggest that most PFCs are developmental toxicants and teratogens, however, compounds that have higher numbers of carbons (i.e., PFDA and PFuDA) exert more potent effects.

Keywords: PFC, xenopus, fetax, development

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Authors: Aparna Radhakrishnan, Jancy Gupta, R. Dileepkumar

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This paper aims at assessing the Socio Economic Vulnerability (SEV) of dairy farmers to Climate Variability and Change (CVC) in 3 states of Western Ghat region in India. For this purpose, a composite SEV index has been developed on the basis of functional relationships amongst sensitivity, exposure and adaptive capacity using 30 indicators related to dairy farming underlying the principles of Intergovernmental Panel on Climate Change and Fussel framework for nomenclature of vulnerable situation. Household level data were collected through Participatory Rural Appraisal and personal interviews of 540 dairy farmers of nine taluks, three each from a district selected from Kerala, Karnataka and Maharashtra, complemented by thirty years of gridded weather data. The data were normalized and then combined into three indices for sensitivity, exposure and adaptive capacity, which were then averaged with weights given using principal component analysis, to obtain the overall SEV index. Results indicated that the taluks of Western Ghats are vulnerable to CVC. The dairy farmers of Pulpally taluka were most vulnerable having the SEV score +1.24 and 42.66% farmers under high-level vulnerability category. Even though the taluks are geographically closer, there is wide variation in SEV components. Policies for incentivizing the ‘climate risk adaptation’ costs for small and marginal farmers and livelihood infrastructure for mitigating risks and promoting grass root level innovations are necessary to sustain dairy farming of the region.

Keywords: climate change, dairy, vulnerability, livelihoods, adaptation strategies

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