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The ocean environment monitoring system is of great significance to the researchers because the ocean is the storehouse of natural resources. It is critical to comprehend and assess the ocean’s environmental conditions. Several studies have been conducted over the last several decades that use sophisticated information and communication techniques to ensure the ocean ecosystem. Wireless sensor networks (WSNs) are a promising technology to monitor the ocean environment, which delivers significant benefits such as enhanced accuracy and real-time observations. The advancements in sensor technology such as micro electromechanical systems (MEMS), integrated systems, distributed processing, wireless communications, and wireless sensor applications have contributed to the development of WSNs. This paper describes the utilization of WSN and analyzes the previous and existing project works and technologies used for ocean environment monitoring through WSNs, and also includes the MEMS sensor technology used for monitoring various ocean parameters such as ocean wave monitoring, water conductivity, temperature, and depth of ocean.

In this review paper we have done extensive reading of various research paper on Text Detection and Recognition from images by different authors of around the world. Each research paper deploys different algorithms and strategies for text detection and text recognition of image. At last, we have compared the Accuracy as well as Precision and Recall Rate of the various methods used in different research paper. Keywords: Accuracy, Precision, recall rate, Digit recognition.

Polyphenolic compounds in the Mediterranean diet have received increasing attention due to their protective properties in amyloid neurodegenerative and many other diseases. Here, we have demonstrated for the first time that polyphenol oleuropein aglycone (OleA), which is the most abundant compound in olive oil, has multiple potencies for the inhibition of amyloid self-assembly of pro-inflammatory protein S100A9 and the mitigation of the damaging effect of its amyloids on neuroblastoma SH-SY5Y cells. OleA directly interacts with both native and fibrillar S100A9 as shown by intrinsic fluorescence and molecular dynamic simulation. OleA prevents S100A9 amyloid oligomerization as shown using amyloid oligomer-specific antibodies and cross-β-sheet formation detected by circular dichroism. It decreases the length of amyloid fibrils measured by atomic force microscopy (AFM) as well as reduces the effective rate of amyloid growth and the overall amyloid load as derived from the kinetic analysis of amyloid formation. OleA disintegrates already preformed fibrils of S100A9, converting them into nonfibrillar and nontoxic aggregates as revealed by amyloid thioflavin-T dye binding, AFM, and cytotoxicity assays. At the cellular level, OleA targets S100A9 amyloids already at the membranes as shown by immunofluorescence and fluorescence resonance energy transfer, significantly reducing the amyloid accumulation in GM1 ganglioside containing membrane rafts. OleA increases overall cell viability when neuroblastoma cells are subjected to the amyloid load and alleviates amyloid-induced intracellular rise of reactive oxidative species and free Ca2+. Since S100A9 is both a pro-inflammatory and amyloidogenic protein, OleA may effectively mitigate the pathological consequences of the S100A9-dependent amyloid-neuroinflammatory cascade as well as provide protection from neurodegeneration, if used within the Mediterranean diet as a potential preventive measure.

Discontinuous Galerkin methods are popular because they can achieve high order where the solution is smooth, because they can capture shocks while needing only nearest-neighbor communication, and because they are relatively easy to formulate on complex meshes. We perform a detailed comparison of various limiting strategies presented in the literature applied to the equations of general relativistic magnetohydrodynamics. We compare the standard minmod/$\Lambda\Pi^N$ limiter, the hierarchical limiter of Krivodonova, the simple WENO limiter, the HWENO limiter, and a discontinuous Galerkin-finite-difference hybrid method. The ultimate goal is to understand what limiting strategies are able to robustly simulate magnetized TOV stars without any fine-tuning of parameters. Among the limiters explored here, the only limiting strategy we can endorse is a discontinuous Galerkin-finite-difference hybrid method., Comment: matches published version. 21 pages, 12 figures. Added KH instability, TOV runs with classical limiters. arXiv admin note: text overlap with arXiv:2109.11645

Recurrent neural networks have achieved outstanding recognition performance for handwriting identification despite the enormous variety observed across diverse handwriting structures, and poor-quality scanned documents. Initially, we proposed a BiLSTM baseline model with a sequential architecture well-suited for modeling text lines due to its capacity to learn probability distributions over character or word sequences. However, employing such recurrent paradigms prevents parallelization and suffers from vanishing gradients for long sequences during training. To alleviate these limitations, we propose four significant contributions to this work. First, we devised an end-to-end model composed of a split-attention CNN-backbone that serves as a feature extraction method and a self-attention Transformer encoder-decoder that serves as a transcriber method to recognize handwriting manuscripts. The multi-head self-attention layers in an encoder-decoder transformer-based enhance the model’s ability to tackle handwriting recognition and learn the linguistic dependencies of character sequences. Second, we conduct various studies on transfer learning (TL) from large datasets to a small database, determining which model layers require fine-tuning. Third, we attained an efficient paradigm by combining different strategies of TL with data augmentation (DA). Finally, since the robustness of the proposed model is lexicon-free and can recognize sentences not presented in the training phase, the model is only trained on a few labeled examples with no extra cost of generating and training on synthetic datasets. We recorded comparable and outperformed Character and Word Error Rates CER/WER on four benchmark datasets to the most recent models (SOTA). The code and models will be uploaded on Github.

A study was held at N. E. Borlaug Crop Research Centre during the kharif season of 2018-19, 2019-2020 and 2020-21. The seeds of various basmati and non-basmati lines were irradiated with ϒ rays at NBRI, Lucknow in 2018-19. The seeds were grown in the same year, the observed viability was less than 99.7 % (M1). The seeds were very meagre and so they were collected and grown in the kharif season of 2019-20. In this generation a screening test for examining BLB resistance was conducted. Resistant mutants were identified in the M2 generation. Similarly, the seeds obtained from M2 were grown as the M3 generation and again screening was done for the BLB. Some mutants were identified which revealed resistance and could be used in the future breeding program for the alleviation of disease susceptibility and catering resistance.

Due to the nonlinear nature of the dynamics of a robot manipulator, controlling the robot meticulously is a challenging issue for control engineers. The key purpose of this paper is to provide an a...

Imaging techniques such as X-ray, computerized tomography scan and magnetic resonance imaging are useful in the correct diagnosis of a disease or deformity in the organ. Two-dimensional imaging techniques such as X-ray give a clear picture of simple bone deformity but fail in visualizing multiple fractures in a bone. Moreover, these lack in providing a multi-angle view of a bone. Three-dimensional techniques such as computerized tomography scan and magnetic resonance imaging present a correct orientation of fracture geometry. Computerized tomography scan is a collection of multiple slices of an image. These slices provide a fair idea about a fracture but fail in the measurement of correct dimensions of a fractured fragment and to observe its geometry. It also exposes a patient with carcinogenic radiations. Magnetic resonance imaging induces a strong magnetic field. So, it becomes ineffective for organs containing metallic implants. The high cost of three-dimensional imaging techniques makes them inaccessible for economic weaker section of society. The limitations of two- and three-dimensional imaging techniques motivate researchers to propose an innovative machine learning model ‘CT slices to $3$-D convertor’ that accepts multiple slices of an image and yields a multi-dimensional view at all possible angles from 0 degree to 360 degree for an input image.

Pro-inflammatory and amyloidogenic S100A9 protein is central to the amyloid-neuroinflammatory cascade in neurodegenerative diseases. Polyoxometalates (POMs) constitute a diverse group of nanomaterials, which showed potency in amyloid inhibition. Here, we have demonstrated that two selected nanosized niobium POMs, Nb10 and TiNb9, can act as potent inhibitors of S100A9 amyloid assembly. Kinetics analysis based on ThT fluorescence experiments showed that addition of either Nb10 or TiNb9 reduces the S100A9 amyloid formation rate and amyloid quantity. Atomic force microscopy imaging demonstrated the complete absence of long S100A9 amyloid fibrils at increasing concentrations of either POM and the presence of only round-shaped and slightly elongated aggregates. Molecular dynamics simulation revealed that both Nb10 and TiNb9 bind to native S100A9 homo-dimer by forming ionic interactions with the positively charged Lys residue-rich patches on the protein surface. The acrylamide quenching of intrinsic fluorescence showed that POM binding does not perturb the Trp 88 environment. The far and near UV circular dichroism revealed no large-scale perturbation of S100A9 secondary and tertiary structures upon POM binding. These indicate that POM binding involves only local conformational changes in the binding sites. By using intrinsic and 8-anilino-1-naphthalene sulfonate fluorescence titration experiments, we found that POMs bind to S100A9 with a Kd of ca. 2.5 μM. We suggest that the region, including Lys 50 to Lys 54 and characterized by high amyloid propensity, could be the key sequences involved in S1009 amyloid self-assembly. The inhibition and complete hindering of S100A9 amyloid pathways may be used in the therapeutic applications targeting the amyloid-neuroinflammatory cascade in neurodegenerative diseases.

The amyloid cascade is central for the neurodegeneration disease pathology, including Alzheimer’s and Parkinson’s, and remains the focus of much current research. S100A9 protein drives the amyloid-neuroinflammatory cascade in these diseases. DOPA and cyclen-based compounds were used as amyloid modifiers and inhibitors previously, and DOPA is also used as a precursor of dopamine in Parkinson’s treatment. Here, by using fluorescence titration experiments we showed that five selected ligands: DOPA-D-H-DOPA, DOPA-H-H-DOPA, DOPA-D-H, DOPA-cyclen, and H-E-cyclen, bind to S100A9 with apparent Kd in the sub-micromolar range. Ligand docking and molecular dynamic simulation showed that all compounds bind to S100A9 in more than one binding site and with different ligand mobility and H-bonds involved in each site, which all together is consistent with the apparent binding determined in fluorescence experiments. By using amyloid kinetic analysis, monitored by thioflavin-T fluorescence, and AFM imaging, we found that S100A9 co-aggregation with these compounds does not hinder amyloid formation but leads to morphological changes in the amyloid fibrils, manifested in fibril thickening. Thicker fibrils were not observed upon fibrillation of S100A9 alone and may influence the amyloid tissue propagation and modulate S100A9 amyloid assembly as part of the amyloid-neuroinflammatory cascade in neurodegenerative diseases.

Deposition of fibrillar amyloid β (Aβ) in senile plaques is a pathological signature of Alzheimer’s disease. However, senile plaques also contain many other components, including a range of different proteins. Although the composition of the plaques can be analyzed in post-mortem tissue, knowledge of the molecular details of these multiprotein inclusions and their assembly processes is limited, which impedes the progress in deciphering the biochemical mechanisms associated with Aβ pathology. We describe here a bottom-up approach to monitor how proteins from human cerebrospinal fluid associate with Aβ amyloid fibrils to form plaque particles. The method combines flow cytometry and mass spectrometry proteomics and allowed us to identify and quantify 128 components of the captured multiprotein aggregates. The results provide insights into the functional characteristics of the sequestered proteins and reveal distinct interactome responses for the two investigated Aβ variants, Aβ(1–40) and Aβ(1–42). Furthermore, the quantitative data is used to build models of the structural organization of the multiprotein aggregates, which suggests that Aβ is not the primary binding target for all the proteins; secondary interactions account for the majority of the assembled components. The study elucidates how different proteins are recruited into senile plaques and establishes a new model system for exploring the pathological mechanisms of Alzheimer’s disease from a molecular perspective.

A classical solution where the (scalar) field value moves by an ${\cal O}(1)$ range in Planck units is believed to signal the breakdown of Effective Field Theory (EFT). One heuristic argument for this is that such a field will have enough energy to be inside its own Schwarzschild radius, and will result in collapse. In this paper, we consider an inverse problem: what kind of field ranges arise during the gravitational collapse of a classical field? Despite the fact that collapse has been studied for almost a hundred years, most of the discussion is phrased in terms of fluid stress tensors, and not fields. An exception is the scalar collapse made famous by Choptuik. We re-consider Choptuik-like systems, but with the emphasis now on the evolution of the scalar. We give strong evidence that generic spherically symmetric collapse of a massless scalar field leads to super-Planckian field movement. But we also note that in every such supercritical collapse scenario, the large field range is hidden behind an apparent horizon. We also discuss how the familiar perfect fluid models for collapse like Oppenheimer-Snyder and Vaidya should be viewed in light of our results., v3: references and minor improvements

Sesame (Sesamum indicum L.) is one of the oldest cultivated plants in the world and is also known as ‘queen’ of oilseed crops. The production of sesame is not consistent compared to other oilseed crops as it is susceptible to waterlogging and low temperature conditions and constant devastating effects of various diseases. Phytophthora blight caused by Phytophthora nicotianae is an economically important oomycete pathogen affecting sesame plant growth and yield to great extent. This disease is predominant in all sesame growing areas. Mutant varieties resistant to Phytophthora blight in sesame have been developed in the Republic of Korea and Sri Lanka. In the present study, 416 gamma-rays induced M3 mutants were raised at Palampur, 164 mutants at Kangra and 314 at Akrot in India. The mutants were screened for Phytophthora blight resistance both under natural field as well as laboratory conditions through ‘detached leaf technique’ at Palampur. Out of these, 186 and 62 M4 mutants were screened again under natural field conditions at Palampur and Kangra, respectively during rainy season of 2016. Based on the screening for 2 years through ‘detached leaf technique’ as well as under natural field conditions, twelve mutants having moderate to high resistance against Phytophthora blight could be isolated. One mutant P97-1 (300 Gy) exhibited highly resistant reaction against Phytophthora blight during both seasons. The isolated mutant can further be utilized in hybridization programme for the introgression of Phytophthora blight resistance in sesame.

This paper presents the optimal design procedure of a flywheel using a cubic B-spline curve. The flywheel plays a vital role in storing kinetic energy in modern machines. The kinetic energy evaluates the performance of the flywheel. In order to improve the kinetic energy of a flywheel, a shape optimization model of the flywheel, with maximization of kinetic energy, is formulated using a cubic spline curve under the constraints of the mass of flywheel, and the maximum value of Von Mises stresses at all points along the radial direction. The Von Mises stresses at all points are determined using the two-point boundary value differential equation. The control points of the cubic B-spline curve are taken as design variables. Then the formulated problem is solved using particle swarm algorithm (PSO), genetic algorithm (GA), and Jaya algorithm. The proposed approach is applied to the flywheel of an agricultural thresher machine. It is found that the Jaya algorithm gives better results compared to the other algorithms. The optimized shape of the flywheel is simulated using MSC ADAMS software.

Mixed-variable optimization problems consist of the continuous, integer, and discrete variables generally used in various engineering optimization problems. These variables increase the computational cost and complexity of optimization problems due to the handling of variables. Moreover, there are few optimization algorithms that give a globally optimal solution for non-differential and non-convex objective functions. Initially, the Jaya algorithm has been developed for continuous variable optimization problems. In this paper, the Jaya algorithm is further extended for solving mixed-variable optimization problems. In the proposed algorithm, continuous variables remain in the continuous domain while continuous domains of discrete and integer variables are converted into discrete and integer domains applying bound constraint of the middle point of corresponding two consecutive values of discrete and integer variables. The effectiveness of the proposed algorithm is evaluated through examples of mixed-variable optimization problems taken from previous research works, and optimum solutions are validated with other mixed-variable optimization algorithms. The proposed algorithm is also applied to two-plane balancing of the unbalanced rigid threshing rotor, using the number of balance masses on plane 1 and plane 2. It is found that the proposed algorithm is computationally more efficient and easier to use than other mixed optimization techniques.

Tillage operations play an important role in soil manipulation processes. This paper aim to design a vibratory mechanism for agricultural tillage operation which would provide the desired motion and path to the cutting tool in the soil. A four-bar mechanism is designed through the principles of mechanism synthesis technique. The dimensions obtained are modelled and validated through MATLAB and MSC Adams to examine whether the tillage tool follows the required trajectory or not. Velocity and acceleration analysis are also studied for the designed mechanism. The study confirmed that the tillage tool followed the required sinusoidal path and completed the objective of vibratory tillage operation.

While extracting land cover from remote sensing images, each pixel in the image is allocated to one of the possible class. In reality different land covers within a pixel can be found due to continuum of variation in landscape and intrinsic mixed nature of most classes. Mixed pixels may not be appropriately processed by traditional image classifiers, which assume that pixels are pure. The existence of mixed pixels led to the development of several approaches for soft (often termed fuzzy in the remote sensing literature) classification in which each pixel is allocated to all classes in varying proportions. However, while the proportions of each land cover within each pixel may be predicted, the spatial location of each land cover within each pixel is not. Thus, it is important to develop and implement a classifier that can work as soft classifiers for landslide identification. This work is an attempt to document and identify landslide areas by five spectral indices using temporal multi-spectral images from IRS-P6 LISS-IV images. To improve the spectral properties of spectral indices for specific class identification (in this case landslide) a Class Based Sensor Independent (CBSI) technique proposed. The result indicates that CBSI based Transformed Normalized Difference Vegetation Index (TNDVI) temporal indices data gives better results for landslide identification with minimum entropy and membership range.

This paper proposes a novel hybrid teaching–learning particle swarm optimization (HTLPSO) algorithm, which merges two established nature-inspired algorithms, namely, optimization based on teaching–learning (TLBO) and particle swarm optimization (PSO). The HTLPSO merges the best half of population obtained after the teacher phase in TLBO with the best half of the population obtained after PSO. The population so obtained is used subsequently in learner phase of TLBO. To validate the proposed algorithm, five constrained benchmark functions are considered to prove its robustness and efficiency. The proposed algorithm is applied to synthesize four-bar linkage for prescribed path. It is found that the HTLPSO performs better than other single nature-inspired algorithms for path synthesis problem in mechanism theory. Hence, HTLPSO may prove to be an important tool for mechanism design to follow the prescribed path.

The interaction of α‐synuclein (αS) with membranes is thought to be critical in the etiology of Parkinson's disease. Besides oligomeric αS aggregates that possibly form membrane pores, the aggregation of αS into amyloid fibrils has been reported to disrupt membranes. The mechanism by which aggregation affects the integrity of membranes is, however, unknown. Here, we show that whereas mature αS fibrils only weakly adhere to POPC/POPG giant unilamellar vesicles (GUVs), fibrillization of αS on the membrane results in large‐scale membrane remodeling. Fibrils that grow on the vesicle surface stiffen the membrane and make the initially spherical membrane become polyhedral. Additionally, membrane‐attached fibrils extract lipids. The lipid extraction and membrane remodeling of growing fibrils can consume the complete bilayer surface and results in loss of vesicle content. These observations suggest that there are several mechanisms by which growing fibrils can disrupt membrane function.

Tillage system design is one of the important areas of interest for farming community. Oscillatory tillage is one such area which reduces the draft consumption and plays a crucial role to farmers during soil manipulation process. The paper deals to design a vibratory mechanism to provide a continuous motion to the tillage tool for following a particular path adopted from the literature through proper synthesis theory and procedure. A four bar mechanism is designed through proper synthesis procedure to identify the dimensions. Analytical and optimal synthesis method is followed during the design process. Optimization algorithms such as hybrid teaching–learning particle swarm optimization based algorithm (HTLPSO), teaching–learning based algorithm, and particle swarm optimization is used to find the values of the design variables. MATLAB is the software used for the synthesis and analysis process. It is observed in the study that designed four mechanism follows the required path for vibratory tillage operation. The results attained through optimization algorithm in HTLPSO performed better for the required path than other nature-inspired algorithms. Also the developed vibratory cultivator performed better in the field trials.

The paper presents to design a vibratory mechanism for agricultural tillage operation. Agriculture tillage plays an important role for crop cultivation. There are different unit farm operations. Tillage is the mechanical manipulation of soil to obtain suitable soil condition for seed germination and growth. There are two basic soil manipulation processes such as primary and secondary. Draft consumption plays a vital role while performing the operations. Vibratory tillage concept was introduced since 1955 which results in low draft consumption. Tools oscillate in a particular mode of oscillation with certain amplitude and frequency along with the implement forward motion. The objective of the paper is to design an optimal four-bar mechanism for vibratory agricultural tillage operation to trace the desired experimental trajectory by the tillage tool in the field.

The rich pool of protein conformations combined with the dimensions and properties of carbon nanotubes create new possibilities in functional materials and nanomedicine. Here, the intrinsically disordered protein α-synuclein is explored as a dispersant of single-walled carbon nanotubes (SWNTs) in water. We use a range of spectroscopic methods to quantify the amount of dispersed SWNT and to elucidate the binding mode of α-synuclein to SWNT. The dispersion ability of α-synuclein is good even with mild sonication and the obtained dispersion is very stable over time. The whole polypeptide chain is involved in the interaction accompanied by a fraction of the chain changing into a helical structure upon binding. Similar to other dispersants, we observe that only a small fraction (15-20%) of α-synuclein is adsorbed on the SWNT surface with an average residence time below 10 ms.

Computer-aided tools help in shortening and eradicating numerous repetitive tasks that reduces the gap between digital model and actual product. Use of these tools assists in realizing free-form objects such as custom fit products as described by a stringent interaction with the human body. Development of such a model presents a challenging situation for reverse engineering (RE) which is not analogous with the requirement for generating simple geometric models. Hence, an alternating way of producing more accurate three-dimensional models is proposed. For creating accurate 3D models, point clouds are processed through filtering, segmentation, mesh smoothing and surface generation. These processes help in converting the initial unorganized point data into a 3D digital model and simultaneously influence the quality of model. This study provides an optimum balance for the best accuracy obtainable with maximum allowable deviation to lessen computer handling and processing time. A realistic non trivial case study of free-form prosthetic socket is considered. The accuracy obtained for the developed model is acceptable for the use in medical applications and FEM analysis.

This paper presents a Neural-fuzzy model structure to improve the disturbance attenuation performance of a gimballed Line of Sight (LOS) stabilization system. Initially, a Fuzzy Logic Controller (FLC) based on prior qualitative information about system dynamics and linguistic performance criteria is developed. Next, proposed Neural-fuzzy model architecture is constructed, which overcome the difficulties and limitations of each isolated methodology. The Neural-fuzzy architecture is developed based on input-output data-sets available from FLC. Fuzzy curve approach is used to determine significant inputs, number of rules, initialization of connecting layers weights, and hence the model structure. Both the controller configurations are tested based on critical performance characteristics such as stability of the loop, responsiveness of the loop and insensitivity to disturbances. Finally, the comparative analysis suggests that the proposed Neural-fuzzy controller completely outperforms the FLC configuration and hence, can be very effective for more precise pointing applications.

A novel algorithm which is an ensemble of two metaphor-less algorithms is presented in this paper. The algorithm is inspired by Rao-1 and Jaya algorithms. Since the algorithm always plays around with the best and worst solutions; the algorithm is named as Best-Worst-Play (BWP) algorithm. The algorithm does not require any algorithm specific parameters, however, algorithm control parameters are required. To test the effectiveness and performance of the proposed algorithm, a number of unconstrained and constrained benchmark functions are considered. It is found that proposed algorithm has outperformed several well-established metaphor based algorithms. The proposed BWP algorithm may be used by researchers to solve the unconstrained and constrained optimization problems

In this paper, stress and eigen frequencies are analyzed through prediction of microcantilever model using design of experiment approach. The important factors affecting displacement sensitivity, stress and eigen frequencies were identified such as geometrical dimensions of microcantilever (length, breadth and thickness), modulus of elasticity of materials, applied force. Based on the selection of factors and levels, experiments were designed using L9 orthogonal array. The designed experiments were simulated with finite element method in COMSOL Multiphysics software. Further, optimum values of dimensions of microcantilever and material property are used for stress and eigen frequencies analysis. The evaluated frequencies under eigen frequency analysis revealed that designed and simulated Gallium Arsenide (GaAs) microcantilever is prone to vibrate at these frequencies, whereas stress analysis illustrates the response of structure and material properties towards reliability.

Exposure to cobalt (Co), chromium (Cr), and nickel (Ni) occurs often via skin contact and from different dental and orthopedic implants. The metal ions bind to proteins, which may induce structural changes and aggregation, with different medical consequences. We investigated human serum albumin (HSA) aggregation in the presence of Co

International audience; We report on the shape relaxation of 2D droplets, formed right after the spontaneous pinch-off of a capillary bridge-droplet confined within a Hele-Shaw cell. An array of bridge-droplets confined within a microchip device first undergo neck thinning due to the evaporation driven volume change. Subsequently, an abrupt topological change transforms each bridge-droplet into a small central satellite droplet and the twin-droplets pinned at the edges of the cell. We monitor the shape relaxation with high temporal resolution optical microscopy. Capillary action drives the 2D shape relaxation, while the viscous dissipation in the film retards it. As a result, the tip of the twin-droplets exhibit a self-similar parabolic shape evolution. Based on these observations, the lubrication-approximation model accurately predicts the internal pressure evolution and the droplet tip displacement. The geometrical confinement substantially slows down the dynamics, facilitating visualization of the capillary-viscous regime, even for low viscosity liquids. The characteristic relaxation timescale shows an explicit dependence on the confinement ratio (width/gap) and the capillary-velocity of liquid. We verify the broad applicability of the model using different liquids.

This paper presents an optimization method to find link shapes for a dynamically balanced planar four-bar mechanism. The shaking force and shaking moment developed in the mechanism due to inertia are minimized by optimally distributing the link masses. The link shapes are then found using cubic B-spline curves and an optimization problem is formulated to minimize the percentage error in resulting links inertia values in which the control points of B-spline curve are taken as the design variables. The effectiveness of the proposed method is shown by applying it to a numerical problem available in the literature.

Background/Objective Human walking involves the coordination of brain, nerves, and muscles. A disturbance in their coordination may result in gait disorder. The gait disorder may be treated through manually assisted gait training or with the aid of assistive devices/robotic devices. These robotic devices involve mechanisms which are synthesized using complex conventional procedures. Therefore, in this study, a new gait-based synthesis procedure is proposed, which simplifies the mechanism synthesis and helps to develop a mechanism which can be used in rehabilitation devices, bipeds, etc. Methods This article presents a novel procedure for the synthesis of 4-bar linkage using the natural gait trajectories. As opposed to the conventional synthesis procedures, in this procedure, a global reference frame is considered, which allows the use of hip trajectory while moving. Moreover, this method is divided into two stages, and five precision points are considered on the hip trajectory in each stage. In the first stage, the 4-bar linkage is designed, thereafter, the configurations of the linkage for the remaining precision points are determined in the second stage. The proposed synthesis procedure reduces the complexity involved in the synthesis and helps in the simplification of the problem formulation. A two-stage optimization problem is formulated for minimizing the error between the generated and desired hip trajectories. Two nature-inspired algorithms are used for solving the optimization problem. The obtained best results are presented, and the designed linkage is simulated in MATLAB. Results The best design of the linkage is obtained using particle swarm optimization. The trajectories generated by the designed linkage using the proposed methodology can accurately track the desired path, which indicates that designed linkage can achieve all the orientations required during walking. The positions of a whole lower limb at all the desired precision points are demonstrated by stick diagram for one gait. Conclusion The proposed methodology has reduced the complexity of synthesis procedures and used optimization techniques to obtain a feasible design of the mechanism. The stick diagram of the designed mechanism obtained using the proposed method indicates that the designed mechanism can walk smoothly. Hence, the designed mechanism can be used in the rehabilitation devices. Furthermore, a conceptual design of an exoskeleton knee is also presented. The Translational Potential of this Article Many hospitals and individuals have used the immobile and portable rehabilitation devices. These devices involve mechanisms, and the design of mechanism plays a vital role in the functioning of these devices; therefore, we have developed a new synthesis procedure for the design of the mechanism. Besides synthesis procedure, a mechanism is developed that can be used in the rehabilitation devices, bipeds, exoskeletons, etc., to benefit the society.

The aim is to construct, calibrate and validate a low-cost sensor-embedded glove and elbow brace. This article establishes a common thread between electro-goniometry and postural assessment techniques. The output voltages from the sensors were converted into angles by implementing LabVIEW-Interface-for-Arduino based graphical environment. Ten experienced weavers participated in the study. Dynamic recordings of the finger, wrist and elbow bending trajectories were measured using sensory electro-goniometer. Assessment of repetitive task technique was used to identify the postural risks. Based on data output from each sensor, the voltage to angle optimal linear models were obtained for the measurement range of 0°-90° with 5° steps. The accuracy of the sensors was found within the limits of traditional goniometry. The cost-benefit breakdown revealed that wearable electro-goniometer is cost-effective as compared to commercially available electro-goniometers. The low-cost electro-goniometric glove and elbow brace for measurements of hand movements could be a promising tool for postural assessment and safety systems.

Item does not contain fulltext We studied alpha-synuclein (alphaS) aggregation in giant vesicles, and observed dramatic membrane disintegration, as well as lipid incorporation into micrometer-sized suprafibrillar aggregates. In the presence of dye-filled vesicles, dye leakage and fibrillization happen concurrently. However, growing fibrils do not impair the integrity of phospholipid vesicles that have a low affinity for alphaS. Seeding alphaS aggregation accelerates dye leakage, indicating that oligomeric species are not required to explain the observed effect. The evolving picture suggests that fibrils that appear in solution bind membranes and recruit membrane-bound monomers, resulting in lipid extraction, membrane destabilization and the formation of lipid-containing suprafibrillar aggregates.

In this paper an ANFIS-PD+I (AFSPD+I) based hybrid force/position controller has been proposed which works effectively with unspecified robot dynamics in the presence of external disturbances. A constraint is put to limit the movement of manipulator in XY Cartesian coordinates. The validity of the proposed controller has been tested using a 6-degree of freedom PUMA robot manipulator. The performance comparison have been done with the fuzzy proportional derivative plus integral, fuzzy proportional integral derivative and conventional proportional integral derivative controllers subjected to the same data set with proposed controller. The projected AFSPD+I controller adhered to the desired path closer and smoother than the other mentioned controllers.