Frequency of Firearm Injuries, Deaths and Related Factors in Kanpur, India; an Original Study with Review of Literature

Background:Studies on fatal firearm injuries have been published in various countries. However, their pattern and incidence in various regions of India has largely gone unreported. Methods: Present study was conducted to evaluate fatal firearm injuries, their pattern, associated factors, cause of deathand postmortem findings among their victims referred to the mortuary of Kanpur medical college and comparing it with the pattern seen in other countries. Results:Sixty six firearm fatalities autopsied during the August 2008 to July 2010 were studied. 92% were victims of homicidal attacks, 2% suicidal and 2% accidental. In 4% deaths motive could not be ascertained. Conclusion:This is in sharp contrast to the pattern seen in other countries where suicides were the predominant group. In maximum cases, illegal country made firearms was involved with the norm of single firing. Abdomen (39%) and head (30.30%) were the two most common entry sites for the bullets, a pattern somewhat similar to that of other countries. Survival time, cause of death and motives of incidence were also studied. 

Renal endothelial injury and microvascular dysfunction in acute kidney injury

The kidney is comprised of heterogeneous cell populations that function together to perform a number of tightly controlled, complex and interdependent processes. Renal endothelial cells contribute to vascular tone, regulation of blood flow to local tissue beds, modulation of coagulation and inflammation, and vascular permeability. Both ischemia and sepsis have profound effects on the renal endothelium, resulting in microvascular dysregulation resulting in continued ischemia and further injury. In recent years, the concept of the vascular endothelium as an organ that is both the source of and target for inflammatory injury has become widely appreciated. Here we revisit the renal endothelium in the light of ever evolving molecular advances

Electrical conductivity of CNT/polymer composites: 3D printing, measurements and modeling

We present electrical conductivity measurements and modeling aspects of carbon nanotube (CNT)/polymer composites enabled via fused filament fabrication (FFF) additive manufacturing (AM). CNT/polylactic acid (PLA) and CNT/high density polyethylene (HDPE) filament feedstocks were synthesized through melt blending with controlled CNT loading to realize 3D printed polymer nanocomposites. Electrical conductivity of 3D printed CNT/PLA and CNT/HDPE composites was measured for various CNT loadings. Low percolation thresholds were obtained from measured data as 0.23 vol. % and 0.18 vol. % of CNTs for CNT/PLA and CNT/HDPE nanocomposites, respectively. Moreover, a micromechanics-based two-parameter agglomeration model was developed to predict the electrical conductivity of CNT/polymer composites. We further show that the two agglomeration parameters can also be used to describe segregated structures, wherein nanofillers are constrained to certain locations within the matrix. To the best of our knowledge, this is the first ever electrical conductivity model to account for segregation of CNTs in the matrix. A good agreement between measured conductivity and predictions demonstrates the adequacy of the proposed model. We further evince the robustness of the model by accurately capturing the conductivity measurements reported in the literature for both elastomeric and thermoplastic nanocomposites. The findings of the study would provide guidelines for the design of electro-conductive polymer nanocomposites

Birefringence analysis of multilayer leaky cladding optical fibre

We analyse a multilayer leaky cladding (MLC) fibre using the finite element method and study the effect of the MLC on the bending loss and birefringence of two types of structures: (i) a circular core large-mode-area structure and (ii) an elliptical-small-core structure. In a large-mode-area structure, we verify that the multilayer leaky cladding strongly discriminates against higher order modes to achieve single-mode operation, the fibre shows negligible birefringence, and the bending loss of the fibre is low for bending radii larger than 10 cm. In the elliptical-small-core structure we show that the MLC reduces the birefringence of the fibre. This prevents the structure from becoming birefringent in case of any departures from circular geometry. The study should be useful in the designs of MLC fibres for various applications including high power amplifiers, gain flattening of fibre amplifiers and dispersion compensation.Comment: 18 page

Heterosis study in Okra [Abelmoschus esculentus (L.) Moench] genotypes for pod yield attributes

A study was conducted at Vegetable Research Farm, Department of Horticulture, Institute of Agriculture Sciences, Banaras Hindu University, Varanasi during Spring-Summer and Rainy season of 2012 and 2013 using 12 diverse parental lines of okra and their 66 F1 hybrids (through diallel cross-excluding reciprocals) with the objective to measure the extent of heterosis over better parent and standard commercial check varieties for the purpose of judging the extent up to which heterosis can be exploited in commercial okra breeding. The extent of heterosis for five best crosses over better parent and check (48.32 % to 82.42 % and 7.13 % to 35.66 %, respectively) for yield per hectare suggested the great scope of realizing higher yield in okra through heterosis breeding. Other economic traits also recorded moderate to high level of heterosis over the better parents. The cross combination IC -282280×EC – 329380showed high heterosis over better parent and standard check for pod yield (82.42 % and 35.66 %), number of pods per plant (62.82 % and 48.54 %) and respectively. This particular cross combination eventually resulted the height magnitude of heterobeltiosis and standard heterosis for the most of the desirable growth parameters as well as yield attributing characters which may be taken for further breeding programme

G x E evaluation for feed barley genotypes evaluated in country by AMMI analysis

AMMI analysis of feed barley genotypes exhibited highly significant effects of environments, genotypes and interactions for both the years. The major portion of the total variance was described by the environmental effects up to 45.6% and 42.3% in respective years. The genotypes effects contributed marginally as of only 8.6% and 6.9% of total variation. The significant interaction effects were partitioned into IPCA1, IPCA2 , IPCA3 and IPCA4; which explained upto 42.4, 18.3, 9.7 and 8.1% of the first year and 32.2, 20.3, 15.6 and 10.5% for second year. The cumulative effect of first two interaction principal components comes out to 60.7% and 52.3% respectively. Maximum genotype yield during study period varied from 49.8 to 48 whereas the lowest yield ranged from 37 to 36.4 q/ha. AMMI stability index identified genotypes G9(BH 972), G15(JB 274) for former and G23(DWRB 109) & G2(KB 1205) for latter year. AMMI distance marked G15(JB 274) & G7(NDB 1561) for first and genotypes G26(UPB 1034) & G23(DWRB 109) for the second year. Desirable genotypes for selection would be G11(PL 871), G27(PL 872) and G23(DWRB 109), G20(BH 946) for respective years a per the GSI score. Genotypes with IPCA-1 scores close to zero identified G1(PL 751), G9(BH 972) and G27(PL 872 ) for first year and G5(RD 2786), G4(NDB 1554) and G24 (UPB 1036) for second year would have wider adaptation to the tested environments as per AMMI graphical plots

Robustness of Fusion-based Multimodal Classifiers to Cross-Modal Content Dilutions

As multimodal learning finds applications in a wide variety of high-stakes societal tasks, investigating their robustness becomes important. Existing work has focused on understanding the robustness of vision-and-language models to imperceptible variations on benchmark tasks. In this work, we investigate the robustness of multimodal classifiers to cross-modal dilutions - a plausible variation. We develop a model that, given a multimodal (image + text) input, generates additional dilution text that (a) maintains relevance and topical coherence with the image and existing text, and (b) when added to the original text, leads to misclassification of the multimodal input. Via experiments on Crisis Humanitarianism and Sentiment Detection tasks, we find that the performance of task-specific fusion-based multimodal classifiers drops by 23.3% and 22.5%, respectively, in the presence of dilutions generated by our model. Metric-based comparisons with several baselines and human evaluations indicate that our dilutions show higher relevance and topical coherence, while simultaneously being more effective at demonstrating the brittleness of the multimodal classifiers. Our work aims to highlight and encourage further research on the robustness of deep multimodal models to realistic variations, especially in human-facing societal applications. The code and other resources are available at https://claws-lab.github.io/multimodal-robustness/.Comment: Accepted at the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP); Full Paper (Oral