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This study presents an improved understanding of the stress distribution in the joint region of weak-axis connections in steel MRFs, and based on this understanding, connection configurations have been proposed for the column-to-foundation connections Columns in MRFs are subjected to lateral forces along their strong and weak axes. To ensure ductile response, analysis, and requisite provisions of column foundation connections along the strong axis have been dealt with in detail. In this study, preliminary inelastic finite element analyses are conducted to study the flow of forces near the weak axis column-to-foundation connection. Theoretical axial load P in the column that produces the worst V-M (shear-moment) loading is identified. Based on these loads a cover plated and ribbed configuration is proposed for the weak- axis column-base (WACB) connection. Nonlinear finite element analyses are performed under monotonic, and FEMA recommended multi-cycle loadings using ABAQUS software to evaluate the performance of the proposed connection configurations and the associated design procedures. The performance of the new weak-axis connections (WACs) is compared with that of the existing connections in terms of von Mises stress, shear stress, normal stress, load deformation response, energy dissipated, and cumulative plastic strain excursion. It was observed that WACB connections in steel MRFs need to be reinforced to keep the stress in CJP welds connecting the column to the base plate below the yield stress even at the lateral drift levels much lower than those expected of about 4–6% lateral drifts. The proposed configuration results in increased moment of inertia of the column about the weak axis and hence enhances the seismic response. [ABSTRACT FROM AUTHOR]

Background: Primary acquired Cholesteatoma is a complex issue for otolaryngologists, with its development mechanisms still unclear due to the intricate anatomy of this region. It's aetiopathogenesis remains poorly understood and this aggressive clinical condition often leads to various complications. Recent research explores myofibroblast and fibronectin's potential roles in pathomechanisms of Cholesteatoma. Objective: To determine and analyze the role of myofibroblast and fibronectin in the aetiopathogenesis of Cholesteatoma. Methodology: In a cross-sectional study at a tertiary care hospital, 30 patients with chronic suppurative otitis media with cholesteatoma were surgically treated, and intraoperative biopsy specimens were collected. These specimens were processed and subjected to histopathological examination, including immunohistochemical staining with Alpha-smooth muscle actin and anti-fibronectin antibody to identify myofibroblast and fibronectin presence. The data were then analyzed to investigate the aetiopathogenesis of cholesteatoma in this cohort. Results: On immunostaining, 25 blocks (83.33%) were positively stained for Alpha-SMA (p-value—0.0007), whereas 29 blocks (96.67%) were positively stained for fibronectin (p-value < 0.0001), suggesting a statistically significant association between the presence of both myofibroblast and fibronectin with cholesteatoma perimatrix. Additionally, a statistically significant association was noted between complications and positive staining for myofibroblast (p-value − 0.0415) and positive staining for fibronectin (p-value—0.0254). Conclusions: Our study indicates that Cholesteatoma retraction and progression are driven by myofibroblast and fibronectin mechanisms, and also links them to disease severity. This understanding opens avenues for innovative diagnostics and treatments targeting these biomarkers. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 attributed to severe acute respiratory syndrome has been implicated with life threatening opportunistic infections like mucormycosis. COVID-19 is a hyperferritinemic syndrome and emerging data project the role of iron in the susceptibility and pathogenesis of mucormycosis but whether high ferritin is an indicator of severity of mucormycosis is debated. The study aimed to determine the relationship between serum ferritin levels and the extent of involvement of COVID-19 associated mucormycosis. A hospital based observational study was conducted with a sample size of 70. All biopsy confirmed cases of COVID-19 associated mucormycosis were included. Retrospective data from hospital records prepared at the time of patient admission were retrieved. The imaging data was used to determine the extent of disease involvement and serum ferritin values were analysed. During the study period 40 patients had mild extent mucormycosis and 30 had severe extent. A statistically significant difference was seen in levels of serum ferritin between mild extent mucormycosis and severe extent involvement (p < 0.01). COVID-19 associated Mucormycosis patients tend to have higher serum ferritin values especially in severe extent disease and with active COVID-19 infection along with diabetes mellitus as a potent aggravating factor. [ABSTRACT FROM AUTHOR]

In this work, we demonstrate the strategic incorporation of p-type NiO and f-MWCNTs into n-type TiO2-active layer that leads to significant augmentation in the power conversion efficiency (PCE) of dye-sensitized solar cells (DSSCs). The NiO@f-MWCNT composites were prepared by in situ precipitation method with different concentrations of MWCNTs. The presence of NiO as and MWCNTs has been confirmed by scanning electron microscopy (SEM), transmission electron microscope (TEM), Fourier transform infrared (FTIR) and Raman spectroscopy. The structural orientation was also confirmed by X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) measurements. The optical measurements like UV–Vis absorbance and photoluminescence spectra confirmed the band gap, absorption and electronic transitions. Fluorescence resonance energy transfer (FRET) mechanism exists in between N719 dye and NiO. The electrochemical measurements confirmed the facile charge transfer kinetics within all the samples and delivered superior PCE values of composites. However, the highest PCE values of 6.50% were observed in 20% composite due to maximum charge transfer kinetics and least recombination processes. The improvement in PCE values due to enhanced light-absorbing ability as well as superior charge conducting ability, lower internal resistance and lower charge recombination rate of NiO@f-MWCNT perfectly matching with N719 dye. As a strategic incorporation, nearly 34% enhancement was noticed in PCE values over bare TiO2 photoanode, opening new horizons for photoanode modification using uniquely functionalized MWCNT. [ABSTRACT FROM AUTHOR]

Anaplasma genus has been classified under the family Anaplasmataceae of order Rickettsiales, which contains the spp. Anaplasma marginale, Anaplasma bovis, Anaplasma centrale, Anaplasma platys and Anaplasma phagocytophilum is accountable for a broad range of diseases in both man and animal medicine around the globe. A multiplex PCR procedure was designed to identify A. marginale, A. bovis, and A. platys simultaneously by employing species-specific primers targeting the msp4 (Anaplasma marginale), 16S rRNA (Anaplasma bovis), and groEL (Anaplasma platys) genes. The sensitivity of the assay was ascertained by tenfold dilutions of DNA obtained from cattle blood infected with A. marginale, A. bovis, and A. platys was used to evaluate the test sensitivity. A total of 31 Anaplasma genus positive samples were subjected to mPCR by using species specific primers for simultaneous detection of all the three species. All the 31 samples showed amplification of 753 bp fragment specific for A. marginale and 61.29% of the samples showed amplification of 547 bp fragment specific for A. bovis. The 470 bp DNA fragment specific for A. platys was found in 96.7% of samples. The lower limit of detection of the method for A. platys, A. marginale and A. bovis was found to be 4.4, 0.44 and 0.044 ng/µl, respectively. [ABSTRACT FROM AUTHOR]

Early-season agricultural drought is frequent over South Asian region due to delayed or deficient monsoon rainfall. These drought events often cause delay in sowing and can even result in crop failure. The present study focuses on monitoring early-season agricultural drought in a semi-arid region of India over 5-year period (2016–2020). It utilizes hydro-climatic and biophysical variables to develop a combined drought index (CDI), which integrates anomalies in soil moisture conditions, rainfall, and crop-sown area progression. Synthetic aperture radar (SAR)–based soil moisture index (SMI) represents in situ measured soil moisture with reasonable accuracy (r=0.68). Based on the highest F1-score, SAR backscatter in VH (vertical transmit-horizontal receive) polarization with specific values for parameter threshold (−18.63 dB) and slope threshold (−0.072) is selected to determine the start of season (SoS) with a validation accuracy of 73.53%. The CDI approach is used to monitor early-season agricultural drought and identified drought conditions during June–July in 2019 and during July in 2018. Conversely, 2020 experienced consistently wet conditions, while 2016 and 2017 had near-normal conditions. Overall, the study highlights the use of SAR data for early-season agricultural drought monitoring, which is mainly governed by soil moisture–driven crop-sowing progression. The proposed methodology holds potential for effective monitoring, management, and decision-making in early-season agricultural drought scenarios. [ABSTRACT FROM AUTHOR]

Breast cancer is very prevalent and because of its death rate is taken into deliberation to be the second dangerous disease in the world. There is a relentless effort to create more effective techniques for an early and reliable diagnosis. Classical approaches require oncologists to investigate breast lesions to detect and classify different cancer stages. Such manual attempts in many cases are time-consuming and inefficient. Hence there is a requirement for effective methods to diagnose cancer cells with high accuracy without human involvement. A "Moon Phase Wavelet Chain Rule Model" has been proposed in this research we introduced Moon Light Dimming Illumination Technique and Smart Recon Techniques. Thus, it overcomes the dense mass accumulation by providing a clear view of fat density, heterogeneous density, tumour size and thus it reduces the beam hardening problems. Our work has initiated Modified Segmented Stationary Wavelet Transform and Multivariable Chain Rule-Based Back Propagation Neural Network, to improvised the features extraction and classifying the phases of breast cancer by avoiding the under and overfitting problems. The proposed model reduces the dense mass accumulation, beam hardening, and obtains a segmented feature image for feature extraction.The Accuracy, Sensitivity, Specificity, Recall, Precision, prevalence performances of 98.62%, 98.25%, 97.52%, 98.25%, 97.25%, and 25.03% respectively. Hence, the outcome of the proposed model has been showing that our system is a promising and robust method for detecting breast cancer. [ABSTRACT FROM AUTHOR]

Assessing the extent of hailstorm-affected crop is one of the thrust areas for quantifying mid-season adversities under crop insurance values chain. This study evaluated the pre- and post-hailstorm responses of potato crop, over different spectral bands and vegetation indices derived from Sentinel-2 data, towards assessment of damage severity classes. The potato crop was mapped using pre-event satellite data with overall accuracy of 88% (k = 0.82). Pair-wise Games–Howell t-test showed significant differences among the post-hailstorm potato severity classes in red, near infrared and short-wave infrared (SWIR) bands and normalized vegetation indices. Percentage change (from pre- to post-event) in band reflectance and vegetation indices showed a better sensitivity in differentiating damage severities. Differential behaviour of SWIR-1 (Band-11) and SWIR-2 (Band-12) was observed within severely affected potato crop under dry and wet soil conditions. Decision matrix based on percentage change in normalized difference vegetation index (ΔNDVI) and normalized difference tillage index (ΔNDVI) could able to capture the damage severity classes with an overall accuracy of 86.7%. Higher proportion of affected area was found to be associated with larger percentage of potato yield reduction based on measured yield data at insurance unit level. The proposed methodological approach could be adopted for operational assessment of the impact of hailstorm events on other crops with required modifications. [ABSTRACT FROM AUTHOR]

Over the last couple of decades, several copula based methods have been proposed in the literature to test for independence among several random variables. But these existing tests are not invariant under monotone transformations of the variables, and they often perform poorly if the dependence among the variables is highly non-monotone in nature. In this article, we propose a copula based measure of dependency and use it to construct some distribution-free tests of independence. The proposed measure and the resulting tests, all are invariant under permutations and strictly monotone transformations of the variables. Our dependency measure involves a kernel function with an associated bandwidth parameter. We adopt a multi-scale approach, where we look at the results obtained for several choices of the bandwidth and aggregate them judiciously. Large sample properties of the dependency measure and the resulting tests are derived under appropriate regularity conditions. Several simulated and real data sets are analyzed to compare the performance of the proposed tests with some popular tests available in the literature. [ABSTRACT FROM AUTHOR]

Present study is a maiden attempt to assess net ecosystem exchange (NEE) of carbon dioxide (CO2) flux from jute crop (Corchorus olitorius L.) in the Indo-Gangetic plain by using open-path eddy covariance (EC) technique. Diurnal variations of NEE were strongly influenced by growth stages of jute crop. Daytime peak NEE varied from − 5 µmol m−2 s−1 (in germination stage) to − 23 µmol m−2 s−1 (in fibre development stage). The ecosystem was net CO2 source during nighttime with an average NEE value of 5–8 μmol m−2 s−1. Combining both daytime and nighttime CO2 fluxes, jute ecosystem was found to be a net CO2 sink on a daily basis except the initial 9 days from date of sowing. Seasonal and growth stage-wise NEEs were computed, and the seasonal total NEE over the jute season was found to be − 268.5 gC m−2 (i.e. 10.3 t CO2 ha-1). In different jute growth stages, diurnal variations of NEE were strongly correlated (R2 > 0.9) with photosynthetic photon flux density (PPFD). Ecosystem level photosynthetic efficiency parameters were estimated at each growth stage of jute crop using the Michaelis–Menten equation. The maximum values of photosynthetic capacity (Pmax, 63.3 ± 1.15 µmol CO2 m−2 s−1) and apparent quantum yield (α, 0.072 ± 0.0045 µmol CO2 µmol photon−1) were observed during the active vegetative stage, and the fibre development stage, respectively. Results of the present study would significantly contribute to understanding of the carbon flux from the Indian agro-ecosystems, which otherwise are very sparse. [ABSTRACT FROM AUTHOR]

The present study is a maiden attempt to assess jute crop lodging due to super cyclone Amphan (20 May 2020) by synergistic use of Sentinel-2 (optical) and Sentinel-1 (SAR) data over part of West Bengal, India. Pre-event Sentinel-2 data (9 April, 14 May) along with the ground information were used to map the jute crop of the affected districts with accuracy of 85%. The cross-polarized backscatter (σ0VH) of Sentinel-1 was found to be sensitive to the sudden change in the canopy structure due to lodging and partial flooding. ▵ σ VH 0 (σ0VH_22 May − σ0VH_16 May) indicating post-event damage was > 2.5 dB over the affected jute crop and δ σ VH 0 (σ0VH_22 May − σ0VH_28 May) representing post-event recovery showed > 1.5 dB for recovered crop, depending on the crop vigor/height. Decision matrix was prepared combining ▵ σ VH 0 and δ σ VH 0 for NDVI-based crop vigor strata (low, medium, and high) to classify the area into affected, marginally affected and normal. Overall accuracy of the classified map was found to be 84.12% with kappa coefficient of 0.74. Nearly, 12.5% of the jute area, i.e., 38,119 ha was found to be either affected or marginally affected due to Amphan and distributed in the southern part of Murshidabad, north-eastern Nadia, northern 24 Paraganas (N), and middle region of Hooghli district. Geospatial map of block-wise affected jute area was prepared to facilitate informed decision making. The study demonstrated an operational methodology for assessing crop lodging due to natural calamities to support relief management and crop insurance. [ABSTRACT FROM AUTHOR]

A stereoselective method has been developed for the chiral separation of the enantiomers of eight antiretroviral (ARV) drugs under subcritical conditions using a supercritical fluid chromatography apparatus. The ARVs: abacavir, tenofovir alafenamide, lamivudine, efavirenz, atazanavir, emtricitabine, dolutegravir and darunavir, are used to treat the human immunodeficiency virus (HIV). The antiretroviral therapy has been planned to manage and control the severity of HIV and prolong the patient's life. The use of multiple drugs that act on different viral targets is known as highly active antiretroviral therapy, which slows down the development of AIDS and prevents opportunistic infections that often lead to death. The immobilized meta-substituted polysaccharide-derived carbamate columns (CSPs) have been chosen for chiral SFC separation of selected ARVs. The ARVs enantioseparation was achieved on CSPs by using different alcohol co-solvents (methanol, ethanol and isopropyl alcohol) with diethylamine (DEA) as an additive to the mobile phase. These CSPs exhibit an exceptional level of complementary chiral recognition characteristics by applying different screening and method optimization strategies. The cellulose tris(3,5-dichlorophenylcarbamate) immobilized on silica gel was found to be useful for the chiral SFC analysis of abacavir, lamivudine, efavirenz combination ARV analysis, and the method was optimized by studying the effects of different mobile phase additives, column temperatures and flow rates. The amylose tris(3-chloro, 5-methylphenyl carbamate) immobilized on silica gel was found to be useful for the chiral SFC analysis of emtricitabine, abacavir and dolutegravir combination ARV drugs. [ABSTRACT FROM AUTHOR]

The frequently used aerospace materials, i.e., ultra-high-strength maraging steel (250) and corrosion-resistant 13-8 Mo stainless steel in the solution-annealed and cold-worked condition, have been joined by three fusion welding processes, namely interpulse TIG welding, and high energy density fusion processes like electron beam welding (EBW) and laser beam welding (LBW). The interpulse TIG welding process was carried out by using W2 grade maraging steel filler wire. The dissimilar joints were welded by EBW and LBW processes without any filler wire. All the dissimilar welded joints were characterized by microstructural observations and validated by mechanical properties in the as-welded as well as precipitation-hardened conditions after welding. The weld microstructures and microhardness profiles were correlated to the tensile strength of weld. Electron beam welded joint with precipitation hardening after welding, i.e., soaking at 510 °C and subsequent air cooling, demonstrated the superior mechanical properties among all the welds. [ABSTRACT FROM AUTHOR]

An algorithm for density-based subspace clustering of given data is proposed here. Unlike the existing density-based subspace clustering algorithms which find clusters using spatial proximity, existence of common high-density regions is the condition for grouping of features here. The proposed method is capable of finding subspace clusters based on both linear and nonlinear relationships between features. Unlike existing density-based subspace clustering algorithms, the values of parameters for density estimation need not be provided by the user. These values are calculated for each pair of features using data distribution in space corresponding to the particular pair of features. This allows proposed approach to find subspace clusters where relationship between different features exists at different scales. The performance of proposed algorithm is compared with other subspace clustering methods using artificial and real-life datasets. The proposed method is seen to find subspace clusters embedded in 5 artificial datasets with greater G score. It is also seen that the proposed method is able to find subspace clusters corresponding to known classes in 4 real-life datasets, with greater accuracy. [ABSTRACT FROM AUTHOR]

Cell biasing is an effective solution for mobile user offloading in Heterogeneous Cellular Network (HetNet). Cell biasing modifies the user association criteria by incorporating Range Expansion Bias (REB) in traditional reference signal based user association technique. For sparse user distribution, REB for picocells does not offload users located outside RSRP Threshold Coverage Area. This is because the actual Reference Signal Received Power (RSRP) value for such users is lesser than the threshold RSRP value for successful communication. On the other hand, using a negative REB value for dense user distribution around picocells is not desirable because it leads to higher interference at users and high energy consumption at macrocells. In this paper, we suggest a unified framework for coverage optimization using spectrum slicing and transmit power spreading. Our proposed framework considers a combination of subchannel transmit power and REB which is based on the user distribution around picocells. Additionally, in order to protect the signal quality of macrocell users located close to picocells, we suggest location aware subchannel allocation technique. This technique maximizes the number of Interference Free subchannels for macrocell users. Obtained results show that our proposed framework can significantly improve the coverage and system blocking for HetNet. [ABSTRACT FROM AUTHOR]

The state of the art in wireless communication is highly spectrum efficient but performs poorly in terms of energy efficiency. With widespread deployment, battery operated devices, escalating energy cost, and inherent energy inefficiency of the Carrier Sense Multiple Access protocol in wireless, it is of prime importance today to look for improved energy efficiency in wireless communication. One promising solution is to use multi clock-rate sampling devices in conjunction with frequency agnostic preamble detection. This reduces the power consumed by wireless devices in idle listening, without significantly affecting the throughput and spectrum efficiency. In this paper, we model such a device as a Markov chain and determine its performance in terms of power consumption and goodput, and discuss the elemental trade-off between the two. The analytical results are verified using extensive simulation and compared with existing techniques. A preamble construction scheme that allows devices with different downclocking levels to coexist in the same network is also explored. Finally, we propose a novel preamble compression scheme based on Robust Header Compression to provide improved performance and scalability. [ABSTRACT FROM AUTHOR]

In this paper, parameter optimization of FSW of cryorolled AA2219 alloy was carried out to obtain defect free weld joint with maximum weld strength. To achieve this, artificial neural network (ANN) was used to model the relationship between the input parameters and the mechanical and corrosion properties (output) of the weld joints. The optimal FSW parameters were determined by genetic algorithm (GA). The feasible solution of the GA was tool rotational speed of 1005 rpm, tool travel speed of 20 mm/min and tool tilt angle of 3°. The feasible parameter was used to weld and check the ability of the parameter to produce better weld joint than the L9 orthogonal array parameters. The weld, subjected to the confirmation test, was investigated by means of metallurgical, mechanical, and corrosion testing. This process reduces the costs associated with trial runs to obtain optimal parameters and also the production cost of the cryorolled (CR) plate which is high. [ABSTRACT FROM AUTHOR]

Hazard analysis is the first step in any disaster management activity. Drought is a serious environmental hazard strongly limiting the agricultural production in the tropical countries like India. A comprehensive drought hazard map is useful for multiple perspectives such as agriculture, environment and hydrology. In this study, daily rainfall data of the Climate Prediction Centre during the south-west monsoon season (June-September) of 12 years, over India was analysed. Based on rainfall and rainy days, six indicators of drought were generated which were then synthesized into a composite index of drought hazard for every 10 × 10 km pixel. The weights for the composite index were generated through variance approach. The index has effectively captured the spatial variations in meteorological drought across India by showing a typical pattern with increasing hazardous area from east to west. The drought hazard map also shows considerable agreement with the climate classification map and the drought proneness map reported by other studies. Thus, the current study presents a simple and novel approach for drought hazard analysis, using the routinely available geospatial rainfall data products. The methodology can be extended to other geographies and disasters too. Use of time series data of longer period would improve the reliability of the composite drought hazard index. [ABSTRACT FROM AUTHOR]

A study was carried out to ascertain the status of ecto-parasites infesting dogs of Shimoga region. A total of 120 dogs with the history of skin problems presented to the local hospitals and local pet clinics of Shimoga region were screened for different ecto-parasites. The ticks, fleas and lice were collected, processed and identified. The skin scrapings were also collected from the affected dogs and processed for identification of mites. Out of 120 dogs examined, 59 (49.1 %) had harboured ecto-parasites. Among 59 infested pet dogs, 22 (37.28 %) positive for Fleas, 18 (30.5 %) for ticks, 09 (15.2 %) for Lice, 07 (11.8 %) for Sarcoptic mange and 03 (5.0 %) were for Demodectic mange conditions. The two species of fleas were identified as Ctenocephalides canis 13 (59 %) and Ctenocephalides felis 9 (41 %). The ticks and lice species were identified as Riphicephalus sanguineus and Trichodectus canis respectively. The mite species infecting dogs were identified as Sarcoptes scabeii and Demodex canis based on the morphological character. The Prevalence of ectoparasites was more in stray and adults dogs compared to pet dogs and puppies respectively. [ABSTRACT FROM AUTHOR]

This article proposes a new method to estimate an existing mutual information based dependence measure using histogram density estimates. Finding a suitable bin length for histogram is an open problem. We propose a new way of computing the bin length for histogram using a function of maximum separation between points. The chosen bin length leads to consistent density estimates for histogram method. The values of density thus obtained are used to calculate an estimate of an existing dependence measure. The proposed estimate is named as Mutual Information Based Dependence Index (MIDI). Some important properties of MIDI have also been stated. The performance of the proposed method has been compared to generally accepted measures like Distance Correlation (dcor), Maximal Information Coefficient (MINE) in terms of accuracy and computational complexity with the help of several artificial data sets with different amounts of noise. The proposed method is able to detect many types of relationships between variables, without making any assumption about the functional form of the relationship. The power statistics of proposed method illustrate their effectiveness in detecting non linear relationship. Thus, it is able to achieve generality without a high rate of false positive cases. MIDI is found to work better on a real life data set than competing methods. The proposed method is found to overcome some of the limitations which occur with dcor and MINE. Computationally, MIDI is found to be better than dcor and MINE, in terms of time and memory, making it suitable for large data sets. [ABSTRACT FROM AUTHOR]

Term selection methods in text categorization effectively reduce the size of the vocabulary to improve the quality of classifier. Each corpus generally contains many irrelevant and noisy terms, which eventually reduces the effectiveness of text categorization. Term selection, thus, focuses on identifying the relevant terms for each category without affecting the quality of text categorization. A new supervised term selection technique have been proposed for dimensionality reduction. The method assigns a score to each term of a corpus based on its similarity with all the categories, and then all the terms of the corpus are ranked accordingly. Subsequently the significant terms of each category are selected to create the final subset of terms irrespective of the size of the category. The performance of the proposed term selection technique is compared with the performance of nine other term selection methods for categorization of several well known text corpora using kNN and SVM classifiers. The empirical results show that the proposed method performs significantly better than the other methods in most of the cases of all the corpora. [ABSTRACT FROM AUTHOR]

The study was conducted to ascertain the actual status of gastro-intestinal parasites in pigs maintained under different rearing systems in Shimoga region, Karnataka state. A total of 150 Pigs fecal samples were examined, which includes 50 from organized piggery farm, Veterinary College Shimoga, 50 from private piggery farm of Shimoga and 50 from free range desi pigs of Shimoga city. The fecal samples were processed and examined by direct and sedimentation method. Out of 50 fecal samples examined from organized piggery farm, 19 were found positive for different parasitic eggs, Out of 50 fecal samples screened form private farm, 28 harbored different parasites, whereas from 50 free range desi pigs fecal samples examined, all showed one and other parasitic eggs/ova. The percent prevalence of parasitic infection is more in free range desi pigs compared to Yorkshire breeds maintained under stall fed condition. [ABSTRACT FROM AUTHOR]

Recent advances in vehicular networks have enforced researchers to focus on various information dissemination techniques. Exchanging information among the vehicles is imperative due to the ever-changing network topology in vehicular networks. However, random transmitter selection in traditional CSMA based channel access mechanism limits the delay performance. Data, such as state information, is often time critical, and hence, efficient information dissemination techniques to improve delay performance are essential. In this work, we aim to minimize the average system age which is the mean number of time slots old a vehicle's information is at all other vehicles in the network. To achieve this, we explore the benefits of simultaneous transmission along with piggybacking of information for multi-hop communication. While allowing simultaneous transmission guarantees faster dissemination of information, piggybacking facilitates dissemination of more information per transmission, thereby keeping the network more updated. We have also analysed the relationship between piggybacked information and number of vehicles in the network. Simulation results show improvement in network performance. Our analytical results are in good agreement with the simulation results. [ABSTRACT FROM AUTHOR]

Vehicular Adhoc NETworks (VANETs) are the key to the future of intelligent transportation systems. An efficient MAC protocol is of greater importance to meet the strict deadlines of safety related applications in VANETs. This work introduces a novel TDMA-based variable interval multichannel MAC protocol (TM-MAC) for VANETs. TM-MAC employs TDMA along with variable interval multichannel scheduling for providing a reliable and efficient broadcast service over a lossy wireless medium. TM-MAC reduces transmission collisions thus making Control CHannel (CCH) more reliable and provides high throughput over Service CHannel (SCH) via maximum channel utilization. The scheduling strategy ensures that vehicles are assigned a slot instantaneously. Moreover there is a reduction of almost 50 % in number of vehicles incurring merging collisions when compared with VeMAC (Omar et al. in IEEE Trans Mob Comput 12(9):1724-1736, ), an existing and recently proposed TDMA based MAC protocol. This reduction in merging collisions increased the packet delivery ratio by almost 25 % when compared with VeMAC. Extensive simulations which were done over a realistic city scenario connote the superiority of TM-MAC over existing schemes for a wide range of traffic conditions. [ABSTRACT FROM AUTHOR]

Drought is a natural climatic phenomenon occurring due to deficiency of precipitation. It is precursor of famine and is difficult to monitor due to its slow progression. The present study employs understanding drought and analyzing its various parameters such as rainfall. One of the main aspects of drought planning and mitigation includes hazard assessment, which describes the physical nature of drought and plays an important role in the relationship between vulnerability and risk. The study uses CPC rainfall time series of 12 years, 2001-2012, during the major rainfall period, i.e., southwest monsoon (June-September) over India at 10 km × 10 km pixel for the meteorological drought analysis. Drought occurrence patterns in the country in the 12-year time series period were analyzed using mean, inter-annual variability (coefficient of variation CV) and drought frequency of rainfall and rainy days. The analysis has highlighted the areas with lower mean rainfall and higher CV and higher drought frequency. Meteorological drought map based on rainfall and rainy day deviations was prepared separately, for all the 12 years, based on IMD criteria of rainfall deviations. Spatial agreement analysis between rainfall-based drought map and rainy days-based drought map was performed using kappa index. It is interesting to note that the agreement between the two maps was <50 % in all the 12 years. The result indicates that a combination of rainfall and rainy days brings additional information on drought intensity. Therefore, in this study, a methodology was suggested to generate drought maps by combining rainfall and rainy days. [ABSTRACT FROM AUTHOR]

Mobile colloids in soils and aquifers can act as carriers for adsorbed contaminants and thereby facilitate the transport of contaminants. In order to understand the problem, colloids isolated from soil were used as adsorbents for toxic metals such as Pb(II), Ni(II), Cu(II), Cr(VI) and dyes such as alizarin red and methylene blue. Column experiments were conducted to investigate the mobilization of in situ colloids from soil and their size distribution. Experiments were also conducted to study the transport of alizarin red dye through soil columns at different ionic strengths (0.01 and 0.001 M) and pH (pH 7.5, 9.5 and 11.5) and toxic metals at the ionic strength of 0.001 M. The colloids showed significant adsorption toward the contaminants with the adsorption of methylene blue reaching as high as 625 mg g. The mobilized colloids had significant difference in their size distribution, and the cumulative mass curve of colloids followed a nonlinear pattern in contrast to the previously reported linear behavior on model systems. The dye and toxic metal transport experiments suggested their sensitivity to low ionic strength influent solution, with the capacity of colloids to transport the dye and toxic metals increasing at low ionic strength and the transport of dye at high pH. With decreasing ionic strength, the release rate coefficient of dye increased. This study represents an important step to understand colloid-associated contaminant transport in natural soils. [ABSTRACT FROM AUTHOR]

Objectives: To describe the sleep patterns and problems in children aged between 12 and 36 mo of age. Methods: This cross sectional survey was collected over a span of 1 y in Advanced Pediatric Centre, PGIMER, Chandigarh and crèches of Chandigarh. Children in the age group of 12 to 36 mo were included in study. Children with chronic illness, developmental delay, seizure disorder and lack of consent were excluded. A total of 368 children were enrolled. Main outcome measures were sleep duration over 1 to 3 y of life; sleep behavior at onset, during and waking of sleep and parent reported sleep problems and their predictors. Results: The average duration of sleep was 12.5 h (S.D = 1.9). The mean total sleep duration and mean day time sleep duration decreased, while mean night time sleep increased as the age advanced from 12 to 36 mo. Following were the frequency of sleep habits seen in the index study; bed time routine was seen only in 68(18.5 %), a regular bed time ritual was seen in 281(76.4 %), 329(89.4 %) children frequently required 0-20 min time to fall asleep, 11(3 %) parents used sleep inducing drugs. Night waking (1 to 3 times a night) was seen in 297(80.7 %) and its frequency declined with age. Parent reported sleep problems were seen in 12.8 % (47/368). Lack of co-sleeping and night waking were considered as strongest predictors of parent reported sleep problems. Conclusions: Toddlers' sleep duration, night waking behavior, and day time naps decrease as the age progress while night time sleep duration increases with age. Lack of co-sleeping and night waking are considered as strongest predictors of parent reported sleep problems. [ABSTRACT FROM AUTHOR]

The k-nearest neighbor rule is a simple and effective classifier for document classification. In this method, a document is put into a particular class if the class has the maximum representation among the k nearest neighbors of the documents in the training set. The k nearest neighbors of a test document are ordered based on their content similarity with the documents in the training set. Document classification is very challenging due to the large number of attributes present in the data set. Many attributes, due to the sparsity of the data, do not provide any information about a particular document. Thus, assigning a document to a predefined class for a large value of k may not be accurate when the margin of majority voting is one or when a tie occurs. This article tweaks the knn rule by putting a threshold on the majority voting and the method proposes a discrimination criterion to prune the actual search space of the test document. The proposed classification rule will enhance the confidence of the voting process and it makes no prior assumption about the number of nearest neighbors. The experimental evaluation using various well known text data sets show that the accuracy of the proposed method is significantly better than the traditional knn method as well as some other document classification methods. [ABSTRACT FROM AUTHOR]