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This paper presents a literature survey documenting the evolution of continuum robots over the past two decades (1999–present). Attention is paid to bioinspired soft robots with respect to the following three design parameters: structure, materials, and actuation. Using this three-faced prism, we identify the uniqueness and novelty of robots that have hitherto not been publicly disclosed. The motivation for this study comes from the fact that continuum soft robots can make inroads in industrial manufacturing, and their adoption will be accelerated if their key advantages over counterparts with rigid links are clear. Four different taxonomies of continuum robots are included in this study, enabling researchers to quickly identify robots of relevance to their studies. The kinematics and dynamics of these robots are not covered, nor is their application in surgical manipulation.

Ensuring that intelligent vehicles do not cause fatal collisions remains a persistent challenge due to pedestrians’ unpredictable movements and behavior. The potential for risky situations or collisions arising from even minor misunderstandings in vehicle–pedestrian interactions is a cause for great concern. Considerable research has been dedicated to the advancement of predictive models for pedestrian behavior through trajectory prediction, as well as the exploration of the intricate dynamics of vehicle–pedestrian interactions. However, it is important to note that these studies have certain limitations. In this paper, we propose a novel graph-based trajectory prediction model for vehicle–pedestrian interactions called Holistic Spatio-Temporal Graph Attention (HSTGA) to address these limitations. HSTGA first extracts vehicle–pedestrian interaction spatial features using a multi-layer perceptron (MLP) sub-network and max pooling. Then, the vehicle–pedestrian interaction features are aggregated with the spatial features of pedestrians and vehicles to be fed into the LSTM. The LSTM is modified to learn the vehicle–pedestrian interactions adaptively. Moreover, HSTGA models temporal interactions using an additional LSTM. Then, it models the spatial interactions among pedestrians and between pedestrians and vehicles using graph attention networks (GATs) to combine the hidden states of the LSTMs. We evaluate the performance of HSTGA on three different scenario datasets, including complex unsignalized roundabouts with no crosswalks and unsignalized intersections. The results show that HSTGA outperforms several state-of-the-art methods in predicting linear, curvilinear, and piece-wise linear trajectories of vehicles and pedestrians. Our approach provides a more comprehensive understanding of social interactions, enabling more accurate trajectory prediction for safe vehicle navigation.

Pedestrian understanding of driver intent is key to pedestrian safety on the road and in parking lots. With the development of autonomous vehicles (AVs), the human driver will be removed, and with it, the exchange that occurs between drivers and pedestrians (e.g., head nods, hand gestures). One possible solution for augmenting that communication is an array of high-intensity light-emitting diodes (LEDs) to project vehicle-to-pedestrian (V2P) messages on the ground plane behind a reversing vehicle. This would be particularly beneficial to elderly pedestrians, who are at particular risk of being struck by reversing cars in parking lots. Their downward gaze and slower reaction time make them particularly vulnerable. A survey was conducted to generate designs, and a simulator experiment was conducted to measure detection and reaction times. The study found that elderly pedestrians are significantly more likely to detect an additional projected message on the ground than detect the existing brake light alone when walking in a parking lot.

This chapter discusses the mathematical problem in image segmentation, image statistics for segmentation, and statistical image segmentation. Image statistics for segmentation include Gaussian statistics, Fourier statistics, covariance statistics, and label statistics. Statistical image segmentation includes vehicle segmentation, aerial image segmentation, and segmentation for image compression. Segmentation is a fundamental low-level operation on images. When statistical methods are employed for image segmentation, there is always an associated multivariate optimization problem. The number of variables involved in the problem varies according to the dimensionality of the prior pdf's domain space. For example, the maximum a posteriori (MAP) estimation procedure in the vehicle segmentation application has an associated three-parameter optimization problem. Although the MAP estimation procedure in the segmentation for image compression application has an associated 64 × 64 parameter optimization problem, the functions that need to be maximized with respect to these variables are typically nonconcave and contain many local maxima. This implies that simple gradient-based optimization algorithms cannot be employed as they are prone to converge to a local maxima. Statistical methods for image segmentation abound with a wide variety of algorithms to address such multivariate optimization problems.

This dissertation addresses three basic issues that arise in the use of Gaussian Markov random fields (GMRFs) in image modelling: the multi-resolution properties, the valid parameter space, and the existence of Maximum Likelihood (ML) and Maximum Entropy (ME) parameter estimates. For the multi-resolution properties, we study GMRFs under two types of resolution transformations, Sampling and Block-to-Point. We show that under both these transformations the coarser level fields are non-Markov, and obtain exact descriptions for their covariances and power spectra. To approximate the coarser level non-Markov fields as GMRFs, we propose a new methodology called the Covariance Invariance Approximation (CIA) and study its measure-theoretic properties. We argue that CIA is better suited to image processing than the free-energy based approximations used in renormalization group studies. On the valid parameter space issue, for both 1-D infinite-length GM processes and 2-D infinite-lattice GMRFs, we present a complete procedure for verifying the validity of a given set of parameters. We illustrate this result by applying it to second-order fields in both 1-D and 2-D, and obtain an explicit and simple description of the respective parameter spaces. We observe that in both these examples, the valid parameter space is considerably larger than the space implied by the previously known sufficient condition. For both 1-D and 2-D finite-lattice fields, we show that the valid parameter space does not admit a simple description. The infinite-lattice conditions, however, provide a tight lower-bound approximation to the valid parameter space of finite-lattice fields. Finally, we consider the existence of the ML and the ME estimates for GMRF parameters. The existence of ME estimates is closely related to the extendibility of covariance sequences. Using this fact in conjunction with our results on the valid parameter space of GMRFs, we obtain analytical and computational solutions to the existence problem. For several examples, we obtain an explicit set of conditions that ascertain extendibility and hence existence. For the general case, we propose a cutting-plane algorithm as an alternative to the two numerical procedures that already exist for determining extendibility, namely, the linear programming algorithm and expanding-hull algorithm. Next, we explore the duality between the valid parameter space of GMRFs and the space of extendible covariances, and their relationships with the space of admissible covariances for finite-size data sequences. Using duality, we also relate the existence of ML estimates to extendibility and show that the existence of ML estimates would have to be ascertained through a computationally intensive linear programming procedure. Finally, we present some results regarding the extendibility of covariances over increasing window sizes.

Despite the exalted status of sputum mycobacterial load for gauging pulmonary tuberculosis treatment and progress, Chest X-rays supplement valuable information for taking instantaneous therapeutic decisions, especially during the COVID-19 pandemic. Even though literature on individual parameters is overwhelming, few studies have explored the interaction between radiographic parameters denoting severity with mycobacterial burden signifying infectivity. By using a sophisticated approach of integrating Chest X-ray parameters with sputum mycobacterial characteristics, evaluated at all the three crucial time points of TB treatment namely pre-treatment, end of intensive phase and completion of treatment, utilizing the interactive Cox Proportional Hazards model, we aimed to precisely deduce predictors of unfavorable response to TB treatment. We extracted de-identified data from well characterized clinical trial cohorts that recruited rifampicin-sensitive Pulmonary TB patients without any comorbidities, taking their first spell of anti-tuberculosis therapy under supervision and meticulous follow up for 24 months post treatment completion, to accurately predict TB outcomes. Radiographic data independently obtained, interpreted by two experienced pulmonologists was collated with demographic details and, sputum smear and culture grades of participants by an independent statistician and analyzed using the Cox Proportional Hazards model, to not only adjust for confounding factors including treatment effect, but also explore the interaction between radiological and bacteriological parameters for better therapeutic application. Of 667 TB patients with data available, cavitation, extent of involvement, lower zone involvement, smear and culture grade at baseline were significant parameters predisposing to an unfavorable TB treatment outcome in the univariate analysis. Reduction in radiological lesions in Chest X-ray by at least 50% at 2 months and 75% at the end of treatment helped in averting unfavorable responses. Smear and Culture conversion at the end of 2 months was highly significant as a predictor (p<0.001). In the multivariate analysis, the adjusted hazards ratios (HR) for an unfavorable response to TB therapy for extent of involvement, baseline cavitation and persistence (post treatment) were 1.21 (95% CI: 1.01-1.44), 1.73 (95% CI: 1.05-2.84) and 2.68 (95% CI: 1.4-5.12) respectively. A 3+ smear had an HR of 1.94 (95% CI: 0.81-4.64). Further probing into the interaction, among patients with 3+ and 2+ smears, HRs for cavitation were 3.26 (95% CI: 1.33-8.00) and 1.92 (95% CI: 0.80-4.60) while for >2 zones, were 3.05 (95% CI: 1.12-8.23) and 1.92 (95% CI: 0.72-5.08) respectively. Patients without cavitation, zonal involvement <2, and a smear grade less than 2+ had a better prognosis and constituted minimal disease. Baseline Cavitation, Opacities occupying >2 zones and 3+ smear grade individually and independently forecasted a poorer TB outcome. The interaction model revealed that Zonal involvement confined to 2 zones, without a cavity and smear grade up to 2+, constituting \"minimal disease\", had a better prognosis. Radiological clearance >50% along with smear conversion at the end of intensive phase of treatment, observed to be a reasonable alternative to culture conversion in predicting a successful outcome. These parameters may potentially take up key positions as stratification factors for future trials contemplating on shorter TB regimens.

The prevalence of childhood and adolescent obesity is increasing worldwide as well as in India. Prader--Willi syndrome (PWS) is one of the most common causes of syndromic obesity with varied clinical manifestations across different lifespan. Herewith, we describe clinical and molecular characteristics of eight PWS who were diagnosed in an obesity clinic of tertiary care hospital.AimThe prevalence of childhood and adolescent obesity is increasing worldwide as well as in India. Prader--Willi syndrome (PWS) is one of the most common causes of syndromic obesity with varied clinical manifestations across different lifespan. Herewith, we describe clinical and molecular characteristics of eight PWS who were diagnosed in an obesity clinic of tertiary care hospital.Clinically suspected cases of PWS were screened between January 2014 and January 2022. Detailed history and clinical examination were done to look for typical features of PWS like characteristic facial appearance, short stature, obesity, hyperphagia, delayed puberty or hypogonadism, diabetes mellitus, developmental delay, cognitive dysfunction, learning disabilities or abnormal behavior. All were evaluated, with 75 g oral glucose tolerance tests (GTT), HbA1c, Free T4, TSH, LH, FSH, testosterone, and growth hormone level. Intelligent quotient (IQ) of each patient was assessed by a psychiatrist using Binet-Kamat test. Molecular confirmation of clinically suspected PWS was done by either Methylation-specific polymerase chain reaction (MS-PCR) or Fluorescence in situ Hybridization (FISH) methods.Materials and MethodsClinically suspected cases of PWS were screened between January 2014 and January 2022. Detailed history and clinical examination were done to look for typical features of PWS like characteristic facial appearance, short stature, obesity, hyperphagia, delayed puberty or hypogonadism, diabetes mellitus, developmental delay, cognitive dysfunction, learning disabilities or abnormal behavior. All were evaluated, with 75 g oral glucose tolerance tests (GTT), HbA1c, Free T4, TSH, LH, FSH, testosterone, and growth hormone level. Intelligent quotient (IQ) of each patient was assessed by a psychiatrist using Binet-Kamat test. Molecular confirmation of clinically suspected PWS was done by either Methylation-specific polymerase chain reaction (MS-PCR) or Fluorescence in situ Hybridization (FISH) methods.Based on clinical and molecular characteristics, eight were diagnosed as PWS. Except one, all were male with characteristic facies, mean age of study cohort was 12 years and mean BMI of 44.58. Obesity, short stature, hyperphagia, hypotonia, and mild to moderate mental retardation were noted in entire (100%) PWS study population. All male PWS patients had cryptorchidism, which was bilateral in six patients and unilateral (right undescended testes) in one. Apart from obesity, short stature, other endocrine associations noted were diabetes mellitus in 50% and subclinical hypothyroidism in 37% of PWS. Molecular characteristics of PWS were confirmed by Methylation-specific PCR in seven and by FISH method in one.ResultsBased on clinical and molecular characteristics, eight were diagnosed as PWS. Except one, all were male with characteristic facies, mean age of study cohort was 12 years and mean BMI of 44.58. Obesity, short stature, hyperphagia, hypotonia, and mild to moderate mental retardation were noted in entire (100%) PWS study population. All male PWS patients had cryptorchidism, which was bilateral in six patients and unilateral (right undescended testes) in one. Apart from obesity, short stature, other endocrine associations noted were diabetes mellitus in 50% and subclinical hypothyroidism in 37% of PWS. Molecular characteristics of PWS were confirmed by Methylation-specific PCR in seven and by FISH method in one.Prader-Willi syndrome should be kept in mind in case of childhood or adolescent obesity with short stature, hypotonia, cryptorchidism, and developmental delay or cognitive dysfunction. Judicious use of molecular diagnostic testing should be made in all clinically suspected cases. Early diagnosis and appropriate management of this complex disorder by a multidisciplinary team will improve the quality of life and treatment outcome.ConclusionPrader-Willi syndrome should be kept in mind in case of childhood or adolescent obesity with short stature, hypotonia, cryptorchidism, and developmental delay or cognitive dysfunction. Judicious use of molecular diagnostic testing should be made in all clinically suspected cases. Early diagnosis and appropriate management of this complex disorder by a multidisciplinary team will improve the quality of life and treatment outcome.

The results of the projected climate change over Cauvery basin of Tamil Nadu for A1B scenario using regional climate models showed an increasing trend for maximum, minimum temperatures and rainfall. The yields of ADT 43 rice simulated by decision support system for agricultural technology transfer with CO2 fertilization effect had shown a reduction of 135 kg ha−1 decade−1 for providing regional climates for impact studies (PRECIS) output, while there was an increase in yield by 24 kg ha−1 decade−1 for regional climate model system 3 (RegCM3) output. Suggested adaptation strategies include system of rice intensification, using temperature tolerant cultivars and using green manures/biofertilizers for economizing water and increasing the rice productivity under warmer climate.

Background. Risk factors for acquired rifampicin resistance (ARR) in human immunodeficiency virus (HIV)/tuberculosis coinfection, in the highly active antiretroviral therapy (HAART) era, needs evaluation. We studied the impact of HIV and HAART on ARR among patients taking thrice-weekly antituberculosis therapy. Methods. This cross-protocol analysis included patients with newly diagnosed, rifampicin-susceptible pulmonary tuberculosis, with and without HIV, enrolled in clinical trials (who took >80% of medication) at the National Institute for Research in Tuberculosis between 1999 and 2013. All patients received rifampicin and isoniazid for 6 months reinforced with pyrazinamide and ethambutol in the first 2 months, given thrice-weekly throughout the study along with HAART in one of the groups. Outcomes were categorized and multivariate logistic regression analysis performed to identify risk factors for ARR. Results. The per-protocol results included patients with tuberculosis: 246 HIV-uninfected patients (HIV−TB+), 212 HIV patients not on HAART (non-HAART), and 116 HIV-infected patients on HAART. Median CD4 counts of the latter 2 groups were 150 and 93 cells/μL, respectively, and the median viral loads were 147 000 and 266 000 copies/mL, respectively. Compared with HIV−TB+, the relative risks (RRs) for an unfavorable response in the coinfected, non-HAART and HAART groups were 2.1 (95% confidence interval [CI], 1.7–14.8; P < .0001) and 2.1 (95% CI, .9–5.2; P = .3), whereas for ARR, the RRs were 21.1 (95% CI, 2.6–184; P < .001) and 8.2 (95% CI, .6–104; P = .07), respectively. Conclusions. HIV-infected patients with tuberculosis treated with a thrice-weekly antituberculosis regimen are at a higher risk of ARR, compared with HIV-uninfected patients, in the presence of baseline isoniazid resistance. HAART reduces but does not eliminate the risk of ARR.

Strict thermodynamic relationships involving the activities of ions or salts govern redox potentials, pH values, equilibria, complexation, partition coefficients, the precipitation such as sulfides or hydroxides, and the electrowinning of metals.