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Introduction Postprandial hypoglycemia (PH) is a poorly understood phenomenon. Five-hour oral glucose tolerance test (5-OGTT) is often a useful laboratory investigation to understand and establish a diagnosis of PH. The aim of this study is to present the patterns observed during 5-OGTT performed in cases with PH in a tertiary hospital in Nepal. Methods 5-OGTTs were performed on 52 patients who complained symptomatic postprandial neuroglycopenic symptoms, at the Nepal Medicity hospital during the period of 2 years from 2017 to 2019. The anthropometry, medical history, serum glucose; insulin and cortisol were obtained. The homeostatic model assessment score for insulin resistance (HOMA-IR) based on fasting glucose and insulin levels were calculated. Data was analyzed using SPSS (Version 20.0). Results 21 (40.4%) patients out of 52 developed hypoglycemia [blood glucose < 55mg/dl (3.1mmol/L)], among them nine patients developed hypoglycemia at 3 hours, 11 at 4 hours and one at 5 hours post glucose load. The fasting insulin level in patients who developed hypoglycemia was 12.1 ± 5.8 μU/ml compared to the insulin level analyzed at the point of hypoglycemic episode which was 6.4 ± 1.8 μU/ml, P

Feed and fodder comprises about 65% of the cost of milk production of a dairy industry. It is a crucial input for enhancing the milk production. To address the issue of fodder availability at first, its assessment is required. Thus, we have implemented remote sensing technique for fodder crop assessment at state level to create a baseline for fodder crop availability for dairy managers to plan for its procurement during deficit and for better management purposes during its excess. We have devised a technique for remote sensing-based fodder crop assessment based on spectral pattern of growth, i.e. normalised difference vegetation index profile and land surface wetness index profile of series of IRS LISS-III satellite data taken during the crop growth cycle for a hybrid method of crop classification. Second objective to address the issue of mitigating the deficit of fodder crops, we have demonstrated the satellite derived intersection of probable high soil wetness area and available current fallows during a crop growing season which can be utilised for growing fodder crops. For macro-level planning in a state for developing new fodder-growing areas, we have demonstrated the availability of soil wetness factor from SMAP data. Fallow land available between two cropping seasons can be identified through remote sensing for growing short duration fast growing fodder crops. This project has been a demonstration project for AMUL in Gujarat to implement it subsequently at national level.

Purpose This study aims to examine whether adding a quantity scarcity message to a monetary discount helps to improve consumers’ offer-related perceptions and intentions, and how the effectiveness of that message compares with adding time restriction to the offer. Design/methodology/approach Two experiments, where participants evaluated retail ads and responded to relevant measures, were conducted in two country markets. Findings Adding either a quantity scarcity message or time restriction to a monetary discount increases the potency of a retail offer. Further, when an offer ad emphasizes product and price-related cues in a balanced manner, time restriction results in more favorable consumer perceptions than scarcity. However, this difference in the messages’ efficacy disappears when the offer strongly emphasizes price-related cues. Research limitations/implications The US market sample is more homogeneous than the Indian one. Discounts were presented in terms of advertised reference prices; further research with other discount formats is desirable. Practical implications Understanding the relative efficacy of quantity scarcity message and time restriction in discounted retail offers can give managers flexibility in the use of these tools. Originality/value This paper addresses scholars’ call for theory-grounded research that provides guidance to retailers on the use of sales promotional tools.

Although consumers do not usually take kindly to price increases, their perceptions of fairness of price increases are contingent on relevant factors. This study investigates consumers' perceptions of the fairness of retail price increase by a domestic versus a foreign brand, as moderated by consumers' ethnocentricity, bias toward inferring a profit motive from a price increase (i.e., “profit stickiness”), and relevant contextual information. Over the course of two sets of experiments, the authors find that ethnocentricity does not necessarily lead to the intuitively expected favorable (unfavorable) bias toward (against) a domestic (foreign) brand's decision to raise prices, subject to profit stickiness and contextual information. These findings have implications for theory, practice, and further research.

Despite cautionary advice against it, delighting consumers by offering them pleasant surprises is widely advocated. In this paper, using a low-price guarantee context, we show that retailers’ attempts to use surprise gains to delight consumers might lead to subpar outcomes, if a countervailing cognition such as suspicion of retailer opportunism dominates consumers’ thinking. In a low-price guarantee, retailers promise consumers refunds if consumers discover a lower price for a purchased product. We propose that providing a surprise component in the refund over and above the promised refund might boomerang, by increasing the likelihood of countervailing cognitions related to opportunistic signaling, in turn decreasing future purchase intentions. Over multiple studies, we provide evidence for this proposition, illustrate the underlying process, and identify boundary conditions.

Detection of crop stress is one of the major applications of remote sensing in agriculture. Many researchers have confirmed the ability of remote sensing techniques for detection of pest/disease on cotton. The objective of the present study was to evaluate the relation between the mealybug severity and remote sensing indices and development of a model for mapping of mealybug damage using remote sensing indices. The mealybug-infested cotton crop had a significantly lower reflectance (33%) in the near infrared region and higher (14%) in the visible range of the spectrum when compared with the non-infested cotton crop having near infrared and visible region reflectance of 48 % and 9% respectively. Multiple Linear regression analysis showed that there were varying relationships between mealybug severity and spectral vegetation indices, with coefficients of determination (r2) ranging from 0.63 to0.31. Model developed in this study for the mealybug damage assessment in cotton crop yielded significant relationship (r2=0.863) and was applied on satellite data of 21st September 2009 which revealed high severity of mealybug and it was low on 24th September 2010 which confirmed the significance of the model and can be used in the identification of mealybug infested cotton zones. These results indicate that remote sensing data have the potential to distinguish damage by mealybug and quantify its abundance in cotton.

Assessing the nature and extent of damage due to natural calamities remains one of the thrust areas in monitoring resource inventory through remote sensing. The effect of the cyclone Phailin and the post-incessant rains during second fortnight of October 2013 on coastal Odisha was studied in terms of rice area flooded, submerged and damaged. Multi-temporal SAR data were analysed to obtain the rice mask, and from this rice mask, the flood affected rice area was determined. Taluka-wise and district-wise crop loss proportion was estimated, and the overall production loss has been estimated. SAR data aided in delineation of flooded regions, while AWiFS NDVI data of subsequent dates showed both continued inundation and crop vigour status post-flood time period. The ground truth indicated that a major portion of the inundated region was not rice but was typha grasses and harvested rice field which should not be accounted as damage to rice crop. The damage on crop yield was difficult to assess; however, the inundation of the crop at panicle initiation and flowering would have impact on grain filling (results in chaffiness) and was considered as completely damaged. Most of the current inundated rice regions fall in this category. It was estimated that a total of 0.167 million hectares and 0.37 million tons of rice crop was lost in the cyclone and floods. The district-level percentage area of rice flooded was communicated to State Remote Sensing Centre in four days timeframe. The overall accuracy obtained for the validation of the ground truth sites was 91.5 %.

Based on recalculations of effect size (Cohen's d) and confidence intervals around these estimates (ESC forthcoming) re-interpret some of the findings from our 2011 Journal of Business Research article (Dutta and Pullig 2011). In response, we critique two aspects of P&S's conclusions, the use of ES&CI in a dichotomous nature and the assumed superiority of the ES&CI approach. In addition, we discuss the implications of the ES&CI results for the substantive domain of our research and findings. Specifically, the ES&CI results do not “overturn” our conclusions, but indicate that for two variables our results should be considered tentative while for two variables the ES&CI approach leads to similar conclusions. We conclude with a discussion of the implications of the larger debate between reporting traditional null hypothesis statistical testing (NHST), ES&CI, or both in behavioral research in marketing and business-related disciplines.

Remote sensing technology becomes an effective and inexpensive technique for detecting disease in vegetation. In this study, an attempt has been done to discriminate healthy and late blight affected crop using remote sensing based indices such as NDVI and LSWI. NDVI and LSWI spectral profiles between healthy and late blight affected crop shows large difference. Mean difference in reflectance between two acquired dates Jan. 10 and 29, 2009 crop clusters varied from 31.28 % in red band, 7.7 % in NIR band and 6.23 % in SWIR bands in healthy crops while in late blight affected crops it is −15.5 % in red, 44.4 % in NIR and −14.61 % in SWIR bands. Negative percentage differences in reflectance indicate reflectance increases from Jan. 10, 2009 to Jan. 29, 2009, while positive difference indicate decrease in reflectance between the two dates. Since potato is an irrigated crop, these differences in reflectance are attributed to prevalent disease at that time. It is found that severely affected areas are Bardhman, Arambag, Bishnupur, Ghatal and Hugli taluka with crop damage areas are 4036.66, 1138.68, 2025.23, 469.15, and 380.08 ha, respectively.

Objective of this study was to identify stripe rust affected areas of wheat crop as well as evaluation of remote sensing (RS) derived indices. Moderately low temperature and high humidity favour the growth of yellow rust. Most affected areas of Punjab are the foothill districts such as Gurdaspur, Hoshiarpur and Ropar. Occurrence of yellow rust is possible when maximum temperature for day is below 15 °C and Temperature difference of day’s maximum and minimum temperature is less than 5 °C during the early growth of wheat. Forecast of the infestation was done using 3 days forecast of weather data obtained from Weather Research and Forecasting (WRF) model at 5 km resolution. Weather forecast used was obtained from Meteorological and Oceanographic Satellite Data Archival System (MOSDAC) site and post infestation, identification of specific locations were done using multi-date IRS AWiFS data. It is an attempt for early detection through 3 days advance forewarning of weather which will be handy tool for planners to expedite relief measures in case of epidemic with a more focused zones of infestation as well as for crop insurers to know the location and extent of damage affected areas.

Unfamiliar brands face the formidable challenge of effectively signaling the quality of their products to consumers. Yet, a current market search reveals that unfamiliar brands attempt to signal quality by offering product warranties. Furthermore, many of these unfamiliar brands offer warranties that are considerably longer than the warranty lengths for comparable products from recognized brands. We label these warranties as exaggerated since they clearly outlive the consumers’ expected period of use for such products (e.g., 10 years warranty on a hoodie).

Despite the prevalence of exaggerated advertised reference prices (ARPs) in retail ads and the potential for consumer vulnerability to false reference prices, research identifying boundary conditions to the effectiveness of exaggerated ARPs is scarce. We demonstrate that exaggerated ARPs are much more effective in favorably influencing consumers’ perceptions of retail offers when they feel time pressure while evaluating such offers. Further, although past research indicates that high promotion frequency weakens the effectiveness of exaggerated ARPs, we show that this is not observed when time pressure is present. We discuss the implications of this research and provide directions for future research.

Remote sensing has become a very powerful tool for crop condition assessment and management. The objective of this study was to understand the effectiveness of basal crop coefficient (Kcb) values estimated from remote sensing and their application in real time crop water requirement. During the crop growing season, the value of Kc for most agricultural crops increase from a minimum value at emergence in relation to change in canopy development, until a maximum Kc is reached at full canopy cover. The study was carried out for the Cotton crop in Sirsa district of Haryana. A spectral index such as SAVI (Soil Adjusted Vegetation Index) and Fractional Vegetation Cover (Fc) was used to estimate Kcb value. High spatial resolution Landsat TM 5 images were used to generate a spectral profile of NDVI, SAVI, and Fc for different crop cover. Using, available empirical models from literature, crop coefficient was derived from SAVI values. Reference Crop Evapotranspiration (ET0) was estimated using Blaney-Criddle Method, taking weather data from ICAR Research Station Observatory. The crop coefficients derived from Remote Sensing data were used along with ET0 values to estimate crop evapotranspiration (ETc). The result showed that the spatial distribution of seasonal ETc varied depending upon sowing date and other condition. The estimated crop evapotranspiration (ETc) pattern was compared with fractional vegetation cover. Spatial distribution map of cotton ETc, basal crop coefficient, and fractional vegetation cover showed areas of high and low water demand. This work can help in water management practices for better irrigation management.

Low-price guarantees help buyers make inferences about retailers’ prices. However, researchers are concerned that consumers might be vulnerable to relying on guarantees associated with high market prices. Furthermore, truly low-priced retailers that issue low-price guarantees might be vulnerable to consumers’ discounting of such guarantees. This article experimentally assesses these concerns and finds that the effects of adding a low-price guarantee to a low or high offer price on consumers’ pre-purchase perceptions depend on consumers’ confidence in their product category price knowledge and their decision involvement. The article explores the implications of the findings and provides directions for further research.

Brand crises are adverse events that threaten brand reputations. Research indicates that corporate responses to crises play a role in restoring brand equity. However, there is confusion as to the best type of response. On the one hand, there is a strong advocacy for a singular type of response strategy, corrective action, regardless of the crisis type, while on the other, there is support for a contingency-based view suggesting that the relative efficacy of responses depends on other factors. We contribute to this contingency-based view by comparing the efficacy of three major response strategies (denial, reduction-of-offensiveness and corrective action) in restoring post-crisis brand confidence and choice likelihood. We find that the relative effectiveness of response strategies depends on the nature of the brand crisis. Consequently, a “one type fits all” strategy for post-crisis responses can be suboptimal. We discuss the implications of our findings and provide directions for future research.

Consumer regret can result in unfavorable outcomes for marketers. To prevent regret, many retailers promise to refund money to consumers who discover lower prices after purchase. The authors show that a refund's effect on felt regret depends on how consumers view these promises. If consumers mainly view them as protective tools (i.e., adopt a protection focus), postrefund regret is minimal. If consumers primarily view such promises as sources of information about the retailer's price status (i.e., adopt an information focus), regret persists even after refund. The authors show that regret persists with these consumers because finding a lower price results in a perception of trust violation. They find that subject to boundary conditions, using a disclaimer that states that the retailer does not claim to offer the lowest prices helps avoid this negative outcome for information-focused consumers. The authors contribute to the literature on outcome reversibility and regret by showing that outcome reversal does not necessarily obviate regret. In addition, they show that regulatory focus serves as the motivational basis for how consumers view refund promises.

Purpose – The purpose of this paper is to study the effectiveness of multiple signals. Specifically, the paper investigates how the individual strength of a marketplace signal varies as a function of whether consumers are exposed to that signal alone or in combination with another signal.Design/methodology/approach – The research uses experimental designs to empirically address the research questions. Hypotheses are formulated primarily based on signaling theory and these hypotheses are tested with laboratory experiments using real consumers.Findings – The key finding is that a signal's stand‐alone credibility largely determines whether its individual strength would be diluted or augmented by the coexistence of another signal. Further, when signals with different stand‐alone strengths coexist, the individual strength of the weaker signal is higher than when that signal is present alone. These effects are observed in brick‐and‐mortar and online shopping media.Originality/value – Past research reports mixed...

In this research we distinguish between ads that compare two different brands (Across-Brand Comparison or ABC ads) and those that compare different versions of the same brand (Within-Brand Comparison or WBC ads). Results from an experiment indicate that when comparative ads use attributes that are relevant to product performance, ad type and brand image interact such that an ABC ad leads to less favorable consumer perceptions than a WBC ad when image of the sponsor brand is low but not when it is high. However, when the ads use attributes that are irrelevant to product performance an ABC ad leads to less favorable consumer outcomes than a WBC ad, regardless of the image of the sponsor brand. We further propose and show that ad believability mediates these effects. Theoretical and practical implications of the findings are discussed and directions for future research are provided.

Low price signals (LPS), pricing tools where retailers promise to match or beat competitors' prices, have been increasingly popular in offline and online markets. We compare consumer evaluation of offline and online LPS as a function of how deeply they process the signals. Results of an experiment indicate that regardless of retail media consumers accept an LPS as an indicator of low price when they do not elaborate sufficiently on the signal. However, at high levels of elaboration, consumers challenge the assumptions underlying their acceptance of the signal at lower levels of elaboration whereby they become more skeptical of an online signal than an offline signal resulting in lower efficacy of the former. Implications of these findings for consumer vulnerability to false low price signaling are discussed along with other theoretical and managerial implications. Additionally, directions for future research are provided.

Spot-vegetation 10 day NDVI composites over Orissa state were analysed to study rice crop inventory and condition assessment. A total of 17 images from July to December during the monsoon (kharif) season of 1998 (S1) and 2001 (S2) a drought and normal year, respectively were analysed. A hierarchical decision rule-based approach that successively eliminated data loss, non vegetated land, forest cover, fallow and other crops was adopted for rice inventory. NDVI temporal profiles of rice could distinguish autumn and winter rice. The total monsoon rice area identified by RS in the state was 4.5 M ha in 1998 and 4.05 M ha in 2001 and was within 7 percent of the state level rice estimate given by Directorate of Economic Survey (DES) i.e., 4.26 and 4.22 M ha, respectively. A new profile fit i.e., a six parameter modified Gaussian approach was adopted. The spectral profile indicated higher mean NDVI at peak growth profile of lowland winter rice (sown in June-July) in 2001-02 compared to 1998-1999. Thus, 2001-2002 rice was seen to be normal while in 1998-1999 a drought affected year. District-wise NDVI profiles of rice were generated and peak NDVI and date at peak profile were found to be correlated with rice yield at district and agro-climatic zone level. Use of rainfall with spectral profile parameters in yield model group of districts or zonal level improved coefficient of determination. This study demonstrates the utility of 1 km and 10 day NDVI composite data for rice crop assessment during monsoon season.

We developed a procedure for preparing a model for mapping spatially distributed zones of aphid pest (Lipaphis erysimi) outbreaks at a regional level. This study employed near-surface meteorological parameters derived from National Oceanic and Atmospheric Administration (NOAA) Television and Infra-Red Operational Satellites (TIROS) Operational Vertical Sounder (TOVS) data and field observations of disease infestation. The study area comprised three sites representing semi-arid and sub-humid regions of dominant Indian mustard (Brassica juncea L.)-growing regions of India. A model based on TOVS-derived cumulative surface air temperature and minimum specific humidity (SpH) was developed to estimate the date of ‘aphid onset’ (first appearance), date of peak infestation and location of severity with respect to aphid population density. Aphid population growth rate during the linear growth phase between aphid onset to peak was computed using SpH-weighted temperature and dates of sowing of the crop (cro...

Low-price guarantees (LPG) signal the market position of a seller’s offer price and promise to compensate consumers in case that information is erroneous. In this research, we demonstrate that when retailers default on the information provided by an LPG, consumer perceptions of the retailer suffer, but the extent of the damage depends on the conditions associated with the default. On the basis of attribution theory, we posit that consumers may attribute default to the retailer’s opportunism but emphasize this attribution differently in various default conditions. Furthermore, we show that the restoration of consumer perceptions after a refund depends on consumers’ focus in terms of the signal itself. If they consider the protective, compensatory function of a low price signal, their post-refund outcomes are more favorable; when they focus on the informational function, these outcomes are less favorable. We discuss the theoretical and practical implications of these findings.

This article presents two experimental studies examining the effects of a low price guarantee on consumers’ pre-purchase evaluations and behavioral intentions. The authors first examine how the effects of a low price guarantee are moderated by consumer perception of market price dispersion. The results show that low price guarantee effects are likely to be attenuated when consumers perceive market price dispersion for a product to be high. The second study shows that higher levels of penalty can help restore a low price guarantee's effectiveness. Specifically, a low price guarantee with progressively higher levels of penalty leads to incrementally more favorable effects on key consumer outcomes when perceived price dispersion is high. Interestingly, penalty level has no such incremental benefit in case of low perceived price dispersion. Theoretical and managerial implications of the authors’ findings, the limitations of the studies, and future research opportunities are discussed.

While past research has focused on pre-purchase effects of low price guarantee (LPG), the present paper examines probable post-purchase consequences of such signals. Results of an experiment indicate that in an effort to enhance value from a purchase, consumers are more likely to engage in post-purchase search for lower prices when a purchase is made under an LPG. The experiment also indicates that presence of an LPG encourages post-purchase search intention only for consumers who are highly motivated to enhance value. Furthermore, it is seen that an LPG that offers higher refund leads to higher post-purchase search intention and this effect is also stronger for consumers with high concerns for enhancing value. The paper discusses several important implications of these findings for signaling theory and LPG-related retailing strategy.

Pre-harvest crop production forecast has been successfully provided by remote sensing technique. However, the probability to get cloud-free optical remote sensing data during kharif season is poor. Microwave data having the capability to penetrate cloud is used in the absence of cloud free optical remote sensing data. Yield models in broad band frequency range are in development stage. Meteorological yield models are developed and predicted yield is combined with area estimated by remote sensing data to provide rice production forecast. This paper describes the methodology adopted for improving the predictability of rice yield before harvest of the crop in Bihar province by taking into consideration meteorological parameters during its growth cycle upto October. Models developed using fortnightly meteorological data have been found to give reasonably fair indications of expected yield of rice in advance of harvest. The yield predictions have been made based on meteorological data and effective rainfall based on water requirement calculations representing a group of districts under similar agro-climatic zones, which could be further improved by incorporating meteorological data of individual districts within each group.

HIV-1-infected patients treated early with combination antiretrovirals respond favorably, but not all maintain viral suppression and improved HIV-specific Th function. To understand if genetic factors contribute to this variation, we prospectively evaluated over 18 months 21 early-treated patients stratified by alleles of class II haplotypes. All seven subjects with the DRB1*13-DQB1*06 haplotype, but only 21% of other subjects, maintained virus suppression at every posttreatment measurement. Following HIV-1 p24 antigen stimulation, PBMCs from patients with this haplotype demonstrated higher mean lymphoproliferation and IFN-gamma secretion than did cells from patients with other haplotypes. Two DRB1*13-restricted Gag epitope regions were identified, a promiscuous one that bound its putative restriction element with nanomolar affinity, and another that mapped to a highly conserved region. These findings suggest that class II molecules, particularly the DRB1*13 haplotype, have an important impact on virologic and immunologic responses. The advantage of the haplotype may relate to selection of key HIV-1 Th1 epitopes in highly conserved regions with avid binding to class II molecules. Eliciting responses to the promiscuous epitope region may be beneficial in vaccine strategies.

Multi temporal dat acquired at different growth stages increases the dimensionality information content and have advantage over single date data for crop classification. Attempt was made to select suitable single date and combination of multidate data for wheat crop classification in Nalanda district of Bihar state where pulses and other crops are also grown in rabi season. Amongst the single date data February data was found to be better for wheat classification in comparison to November. January, March and April data. Combination of first two principal components each derived from IRS LISS-I four band data acquired in January and February was found to be the best set. Wheat classification accuracy achieved was 94.54 percent.

The favourable agroclimatic conditions for orchards especially apples have increased the acreages in Himachal Pradesh (HP) which has significantly contributed in the growth of state economy. Realizing the importance of horticulture in HP and its changing scenario of the land use/land cover, a study was conducted to identify and map apple and almond plantations in the Kumarsain tehsil of Shimla district using Remote Sensing (RS) techniques. IRS-IB LISS-II False Colour Composite (FCC) diapositives of October 27, March 30 and April 20, 1992 were visually analysed for mapping apple and almond plantations. The results indicate that IRS LISS-II data of April 20 on 1∶50,000 scale was found very useful for identification and mapping of apple and almond plantations in this region. Accuracy of interpretation was also tested on sample basis assuming a binomial distribution for the probability of success/failure of sample points. The overall interpretation accuracy assessed based on 40 sample points was found to be 87 per cent at 90 per cent confidence limits.

I he aim of the piesent study was to suggest an approach for national level acreage estimation for wheat using satellite remote sensing data and demonstrate its perfromantee Multi-date moderate resolution (188 m) IRS-IC WiFS data sets were used as the core data Sampie segment approach with stratified random sampling was used for the data analysis For making meaningful comparisons over time, multi-date sets were geometncally registered and radiometrically normalised by extracting pseudo-invariant Features and performing regression analysis on the digital numbers of such features The corrected multi-temporal data sets were used in hierarchical classification scheme. The results of this exercise are presented. It appeals that there is an overestimatoin of wheat acreage The sampling effieieney was also low, indicating need to improve sampling strategy Some of the problems encountered and the corrections planned to overcome them are also discussed

The accuracy of cotton crop classification using satellite data has been assessed with respect to a detailed land cover map prepared by field survey. The effect of spatial resolution on classification accuracy was studied using LISS-I (spatial resolution 72.6 m) and LISS-II data (spatial resolution 36.25 m) of the Indian remote sensing satellite IRS-1B. The performances of the maximum likelihood and the minimum distance to mean as classifiers have also been assessed. LISS-II data have been found to give a higher classification accuracy. The estimate of cotton acreage using LISS-II data was closer to that obtained from the base map. The maximum likelihood classifier (MXL) and the minimum distance to mean (MDM) classifier performed equally well.

In an effort to study prevalence of antibiotic producing actinomycetes a total of 21 actiomycetes were isolated from 42 soil samples collected from Ranchi District (Jharkhand). These isolates were studied for their cultural, morphological and antagonistic behaviour towards bacteria, yeast and fungi including E. coli, S. aureus, S. typhi, A. niger MTCC 281, A. fumigatus MTCC 3002, S. cerevisiae MTCC 36, R. eutropa MTCC 1285. Cultural characteristics and microscopic features revealed that most of the isolates belonged to genus Streptomyces. Among the test actinomycetes, 12 isolates were found positive for complete or partial inhibition of at least one or more test microorganism. Isolate SD 9 completely inhibited E. coli, S. aureus and S. cerevisiae MTCC 36 while S. typhi was partially inhibited.

This paper describes the methodology adopted and results obtained during forecasting of national level wheat production in India using multi-date medium resolution Advanced Wide Field Sensor (AWiFS) data. Multidate, geometrically registered and radiometrically normalized Resourcesat-1 AWiFS data were classified using hierarchical decision rules, which exploited differential crop spectral profiles of various crops in winter season. Wheat acreage estimates were arrived by aggregation of stratified samples. Wheat yields were predicted for meteorological sub-divisions by correlation weighted weather regression models developed using fortnightly temperatures. Multiple preharvest wheat acreage and production forecasts were made with additional information on spatio-temporal crop growth performance in comparison to previous / normal season.

Background Subacute bacterial endocarditis (SBE) occasionally exhibits positive cytoplasmic anti-neutrophil cytoplasmic antibody (c-ANCA) of the anti-proteinase-3 (PR-3) type. Clinically, it mimics ANCA-associated vasculitis, such as Wegener's disease with glomerulonephritis. Lung abscesses are the most common manifestation of lung involvement. We herein report a case of culture-negative SBE strongly c-ANCA/PR3-positive accompanied by pulmonary involvement and glomerulonephritis. In this case, we took biopsies of both the lung and kidney, although renal biopsy is usually preferred over lung biopsy. The lung biopsy showed severe alveolar capillaritis, suggesting vasculitis consistent with polyangiitis. The renal biopsy revealed glomerulonephritis with a membranoproliferative pattern. To our knowledge, this is the first such reported case. Case presentation A 68-year-old Chinese male patient presented to our hospital with a fever, cough, chest pain, and recurrent peripheral edema. He had a past medical history significant for treated schistosomiasis 20 years previously. Physical examination revealed palpable purpura, mild hypertension, hepatosplenomegaly, and a holosystolic cardiac murmur (Levine 2/6). Echocardiography showed tricuspid valve vegetations with moderate to severe regurgitation. Serum c-ANCA/PR3 and cryoglobulin were strongly positive. Renal biopsy results indicated membranoproliferative glomerulonephritis with several crescents. Chest CT revealed multiple intraparenchymal and subpleural nodules, and lung biopsy showed polyangiitis. The patient’s ANCA titers, glomerulonephritis, and pulmonary injury all resolved after antibiotic therapy. Conclusion SBE may present with positive c-ANCA/PR3, multiple pulmonary nodules, pulmonary polyangiitis, and glomerulonephritis clinically mimicking granulomatosis with polyangiitis (Wegener's granulomatosis).

Detection of crop stress is one of the major applications of remote sensing in agriculture. Many researchers have confirmed the ability of remote sensing techniques for detection of pest/disease on cotton. Hence, this research was designed to investigate, (1) to study the spectral properties of noninfested and mealybug infested cotton crop (ii) damage assessment using remote sensing derived index. Mealybug-infested cotton crop showed significantly lower reflectance in the near infrared region and higher in the visible region of the spectrum when compared with the non-infested cotton crop. Mealybug Pest Stress Index-8 (MPSI-8), a remote sensing index derived in this study shows a significant negative relationship with mealybug severity (r2=0.6319) and shows the potential to assessment the pest and disease damage because of its characteristic that include pigment, leaf structure, and water sensitive band. MPSI-8 depicts the change in pigment concentration and water stress and shows a negative relationship with mealybug severity. The high negative value of the index shows the high severity of mealybug. Land Surface Temperature (LST) also shows a positive and significant relationship with mealybug severity (r2=0.5921).Multiple linear regression analysis showed a strong relationships (r2=0.752) between mealybug severity and remotely derive index. Model developed in this study for the mealybug damage assessment in cotton crop yielded significant relationship (r2=0.752) and was applied on satellite data of 21st September 2009 which reveals high severity of mealybug and it was low on 24th September 2010 which confirms the significance of the model and can be used in the identification of mealybug infested cotton zones. These results indicate that remote sensing data have the potential to distinguish damage by mealybug and quantify its abundance in cotton.