The tiger (
Panthera tigris
), which is the largest living feline, is waging a grim battle for survival, with only less than 2300 left out in the wild. Information on the cause of death of every ...single tiger is important, as it will help in devising suitable conservation measures. However, most of the deaths reported in the wild are due to ‘unknown etiology’ and reports on infectious causes are almost absent. The present paper describes the death of a wild tiger, associated with infection of the submucosal hookworm of large felines,
Galoncus perniciosus
. Necropsy revealed that the small intestinal serosa was congested with extensive paint-brush haemorrhages for the most part. There were about 27 intestinal nodules, each measuring about 1.5 cm in diameter, containing haemorrhagic exudate and parasites identified as
G. perniciosus
. The serosa also showed clear ante-mortem circumferential tears in seven places; some of them were superficial, limited to the serosa, while others extended into the
muscularis mucosa.
The possibility of death due to septicaemia or neurogenic shock resulting from galoncosis is discussed based on the circumstances and distinct necropsy lesions. The implications of such infectious diseases on the tiger conservation strategy are also discussed.
Normal vascular is associated with gradual change of vascular structure and function, resulting in increased arterial stiffening and decreased arterial compliance. Arterial stiffness is a marker of ...vascular ageing and a predictor of cardiovascular events. Premature or early vascular ageing is measured by pulse wave velocity or the arterial augmentation index based on pulse wave analysis.
To study the predictor of vascular dysfunctions in high risk young adult offsprings of type 2 diabetes mellitus and hypertensive parents.
The analytical cross-sectional studies were carried out in 90 subjects (45 males and 45 females), aged 18-25 years. They were divided into three groups based on their family history, known case of type 2 DM or hypertension in their parents. Group 1- control, Group 2- DM, Group 3-Hypertensive. In all subjects, anthropometrical data, blood pressure and peripheral pulse wave velocity were measured. One-way ANOVA was applied to determine the predictor factors of pulse wave velocity within and between groups. The following parameters were included in these analyses: age, gender, body mass index, hip waist index, heart rate, blood pressure and pulse wave velocity.
A post-test analysis revealed that peripheral pulse wave velocity (PWV), early part of systolic phase (P1) was increased significantly than later part systolic phase (P2), p-value in both diabetic and hypertensive groups were compared with control group. (p≤0.001, ANOVA) Augmentation index (P2/P1) was also increased significantly in both diabetic and hypertensive groups than control group (p≤0.001, ANOVA).
The findings of present study suggest that, although related, peripheral augmentation index AIx and PWV provide early identification of high risk groups. Implication of life style modification is the first intervention to consider in adults followed by drug therapy to control risk factors. Specifically, AIx might provide a more sensitive marker of arterial aging in younger individuals.
On the Biometric Capacity of Generative Face Models Boddeti, Vishnu Naresh; Sreekumar, Gautam; Ross, Arun
2023 IEEE International Joint Conference on Biometrics (IJCB),
2023-Sept.-25
Conference Proceeding
Odprti dostop
There has been tremendous progress in generating realistic faces with high fidelity over the past few years. Despite this progress, a crucial question remains unanswered: "Given a generative face ...model, how many unique identities can it generate?" In other words, what is the biometric capacity of the generative face model? A scientific basis for answering this question will benefit evaluating and comparing different generative face models and establish an upper bound on their scalability. This paper proposes a statistical approach to estimate the biometric capacity of generated face images in a hyperspherical feature space. We employ our approach on multiple generative models, including unconditional generators like StyleGAN, Latent Diffusion Model, and "Generated Photos," as well as DCFace, a class-conditional generator. We also estimate capacity w.r.t. demographic attributes such as gender and age. Our capacity estimates indicate that (a) under ArcFace representation at a false acceptance rate (FAR) of 0.1%, StyleGAN3 and DCFace have a capacity upper bound of 1.43 \times 10^{6} and 1.190 \times 10^{4}, respectively; (b) the capacity reduces drastically as we lower the desired FAR with an estimate of 1.796 \times 10^{4} and 562 at FAR of 1% and 10%, respectively, for StyleGAN3; (c) there is no discernible disparity in the capacity w.r.t gender; and (d) for some generative models, there is an appreciable disparity in the capacity w.r.t age. Code is available at https://github.com/humananalysis/capacity-generative-face-models.
A middle-aged adult patient with a history of aortic root replacement with a mechanical valved conduit and remote chest trauma was referred to our institution with prosthetic endocarditis. ...Transoesophageal echocardiogram at our institution confirmed a near-complete dehiscence of the prosthetic aortic valve from the conduit, with significant perivalvular flow forming a pseudoaneurysm. The patient underwent a high-risk re-operation, involving redo aortic root replacement with a homograft after extensive debridement of the infected tissue. The patient was discharged to an outside facility after an uncomplicated hospital course, and remains stable.
There has been tremendous progress in generating realistic faces with high fidelity over the past few years. Despite this progress, a crucial question remains unanswered: "Given a generative face ...model, how many unique identities can it generate?" In other words, what is the biometric capacity of the generative face model? A scientific basis for answering this question will benefit evaluating and comparing different generative face models and establish an upper bound on their scalability. This paper proposes a statistical approach to estimate the biometric capacity of generated face images in a hyperspherical feature space. We employ our approach on multiple generative models, including unconditional generators like StyleGAN, Latent Diffusion Model, and "Generated Photos," as well as DCFace, a class-conditional generator. We also estimate capacity w.r.t. demographic attributes such as gender and age. Our capacity estimates indicate that (a) under ArcFace representation at a false acceptance rate (FAR) of 0.1%, StyleGAN3 and DCFace have a capacity upper bound of \(1.43\times10^6\) and \(1.190\times10^4\), respectively; (b) the capacity reduces drastically as we lower the desired FAR with an estimate of \(1.796\times10^4\) and \(562\) at FAR of 1% and 10%, respectively, for StyleGAN3; (c) there is no discernible disparity in the capacity w.r.t gender; and (d) for some generative models, there is an appreciable disparity in the capacity w.r.t age. Code is available at https://github.com/human-analysis/capacity-generative-face-models.
A new species of Gymnostachyum Nees (Acanthaceae), G. warrieranum K. M. P. Kumar, Balach. & V. B. Sreek. from the Western Ghats of India is described and illustrated. IUCN status, distribution, ...phenetic relationships, phenology and plastid genome variation are discussed and a key to the Gymnostachyum species distributed in Kerala is also provided for easy identification.
Conventional techniques fail to guarantee successful tracking of the global maximum power point under partial-shading conditions. This results in significant reduction in the power generated as wells ...as the reliability of the photovoltaic energy production system. For the effective utilization of solar panel under partial shading condition, global maximum power point tracking method (GMPPT) is required. This paper discusses an improved perturb and observe technique for tracking global maximum power point of photovoltaic arrays that has better performance even under partial shading condition than the conventional tracking algorithms. Initially GMPP is located by adjusting the control signal and then the control moves to local MPP stage. For the present study, single ended primary inductance converter is used as the dc-dc interface for MPP Tracking. This is a buck-boost derived converter which is better suited for photovoltaic applications than conventional buck-boost converter. Solar panel has been modelled and partial shading effects are implemented. Simulation results showing the performance of modified algorithm are presented with the help of MATLAB/Simulink.
A middle-aged adult patient with a history of aortic root replacement with a mechanical valved conduit and remote chest trauma was referred to our institution with prosthetic endocarditis. ...Transoesophageal echocardiogram at our institution confirmed a near-complete dehiscence of the prosthetic aortic valve from the conduit, with significant perivalvular flow forming a pseudoaneurysm. The patient underwent a high-risk re-operation, involving redo aortic root replacement with a homograft after extensive debridement of the infected tissue. The patient was discharged to an outside facility after an uncomplicated hospital course, and remains stable.
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