3D Radar and Camera Co-Calibration: A Flexible and Accurate Method for Target-based Extrinsic Calibration

Advances in autonomous driving are inseparable from sensor fusion. Heterogeneous sensors are widely used for sensor fusion due to their complementary properties, with radar and camera being the most equipped sensors. Intrinsic and extrinsic calibration are essential steps in sensor fusion. The extrinsic calibration, independent of the sensor's own parameters, and performed after the sensors are installed, greatly determines the accuracy of sensor fusion. Many target-based methods require cumbersome operating procedures and well-designed experimental conditions, making them extremely challenging. To this end, we propose a flexible, easy-to-reproduce and accurate method for extrinsic calibration of 3D radar and camera. The proposed method does not require a specially designed calibration environment, and instead places a single corner reflector (CR) on the ground to iteratively collect radar and camera data simultaneously using Robot Operating System (ROS), and obtain radar-camera point correspondences based on their timestamps, and then use these point correspondences as input to solve the perspective-n-point (PnP) problem, and finally get the extrinsic calibration matrix. Also, RANSAC is used for robustness and the Levenberg-Marquardt (LM) nonlinear optimization algorithm is used for accuracy. Multiple controlled environment experiments as well as real-world experiments demonstrate the efficiency and accuracy (AED error is 15.31 pixels and Acc up to 89\%) of the proposed method

mmFall: Fall Detection using 4D MmWave Radar and a Hybrid Variational RNN AutoEncoder

In this paper we propose mmFall - a novel fall detection system, which comprises of (i) the emerging millimeter-wave (mmWave) radar sensor to collect the human body's point cloud along with the body centroid, and (ii) a variational recurrent autoencoder (VRAE) to compute the anomaly level of the body motion based on the acquired point cloud. A fall is claimed to have occurred when the spike in anomaly level and the drop in centroid height occur simultaneously. The mmWave radar sensor provides several advantages, such as privacycompliance and high-sensitivity to motion, over the traditional sensing modalities. However, (i) randomness in radar point cloud data and (ii) difficulties in fall collection/labeling in the traditional supervised fall detection approaches are the two main challenges. To overcome the randomness in radar data, the proposed VRAE uses variational inference, a probabilistic approach rather than the traditional deterministic approach, to infer the posterior probability of the body's latent motion state at each frame, followed by a recurrent neural network (RNN) to learn the temporal features of the motion over multiple frames. Moreover, to circumvent the difficulties in fall data collection/labeling, the VRAE is built upon an autoencoder architecture in a semi-supervised approach, and trained on only normal activities of daily living (ADL) such that in the inference stage the VRAE will generate a spike in the anomaly level once an abnormal motion, such as fall, occurs. During the experiment, we implemented the VRAE along with two other baselines, and tested on the dataset collected in an apartment. The receiver operating characteristic (ROC) curve indicates that our proposed model outperforms the other two baselines, and achieves 98% detection out of 50 falls at the expense of just 2 false alarms.Comment: Preprint versio

mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs

In this paper, mm-Pose, a novel approach to detect and track human skeletons in real-time using an mmWave radar, is proposed. To the best of the authors' knowledge, this is the first method to detect >15 distinct skeletal joints using mmWave radar reflection signals. The proposed method would find several applications in traffic monitoring systems, autonomous vehicles, patient monitoring systems and defense forces to detect and track human skeleton for effective and preventive decision making in real-time. The use of radar makes the system operationally robust to scene lighting and adverse weather conditions. The reflected radar point cloud in range, azimuth and elevation are first resolved and projected in Range-Azimuth and Range-Elevation planes. A novel low-size high-resolution radar-to-image representation is also presented, that overcomes the sparsity in traditional point cloud data and offers significant reduction in the subsequent machine learning architecture. The RGB channels were assigned with the normalized values of range, elevation/azimuth and the power level of the reflection signals for each of the points. A forked CNN architecture was used to predict the real-world position of the skeletal joints in 3-D space, using the radar-to-image representation. The proposed method was tested for a single human scenario for four primary motions, (i) Walking, (ii) Swinging left arm, (iii) Swinging right arm, and (iv) Swinging both arms to validate accurate predictions for motion in range, azimuth and elevation. The detailed methodology, implementation, challenges, and validation results are presented.Comment: Submitted to IEEE Sensors Journa

DISSEMINATED TUBERCULOSIS PRESENTING AS HEMOPHAGOCYTIC LYMPHOHISTIOCYTOSIS

ABSTRACTHemophagocytic lymphohistiocytosis (HLH) is an immune dysregulation syndrome which is characterized by widespread but ineffective activationof immune system of our body. This activation leads to release of a large pool of cytokines from the activated lymphocytes and macrophages. Thishypercytokinemia leads to the development of characteristic features of HLH such as fever, cytopenias, hepatosplenomegaly, raised serum ferritinlevel, hemophagocytosis in marrow/spleen/lymph nodes, low fibrinogen and or hypertriglyceridemia, low natural killer cell activity, and high-solubleCD25 [1]. Five out of the above eight features are required for the diagnosis. There are 2 variants of HLH, primary HLH; where the defect in theimmune system is hereditary and secondary HLH; where it is caused by other secondary diseases such as infections, hematological malignancies,autoimmune and auto-inflammatory diseases. In this article, we have reported a case of HLH, which was secondary to disseminated tuberculosis.There are only few case reports of HLH secondary to disseminated tuberculosis. Mortality may be as high as 50%. Although tuberculosis has variousmanifestations, our patient presented with fever, skin rash, cytopenias, splenomegaly, and very high ferritin. Marrow examination showed epithelioidgranuloma, hemophagocytosis, and positive Ziehl–Neelsen staining. At present, no definite treatment guidelines have been formulated becauseof multiple drug interactions and toxicities. We treated our patient with non-hepatotoxic anti-tubercular drugs and steroids, followed by additionof isoniazid, rifampicin, and pyrazinamide on improvement of hepatic profile. Thus, high index of clinical suspicion, prompt diagnosis, and earlymanagement may reduce the mortality in this devastating disease. Moreover, this is more common in immunocompromised patients, but here, wehave diagnosed this case in an immunocompetent man.Keywords: Erythematous rash, Fever, Disseminated tuberculosis

Cadmium induces lung inflammation independent of lung cell proliferation: a molecular approach

<p>Abstract</p> <p>Background</p> <p>Cadmium is one of the inflammation-related xenobiotics and has been regarded as a potent carcinogen. The relationship between inflammation and cell proliferation due to chronic infection has been studied, but the mechanism is not fully clear. Though the mode of cadmium toxicity is well characterized in animal cells, still it requires some further investigations. Previously we reported that cadmium induces immune cell death in Swiss albino mice. In the present study we showed that instead of inducing cell death mechanism, cadmium in low concentration triggers proliferation in mice lung cell and our results reveals that prior to the induction of proliferation it causes severe inflammation.</p> <p>Methods</p> <p>Swiss albino mice were treated with different concentrations of cadmium to determine the LD50. Mice were subdivided (5 mice each) according to the exposure period (15, 30, 45, 60 days) and were given sub lethal dose (5 mg/Kg body weight) of cadmium chloride and ibuprofen (50 mg/Kg body weight, recommended dose) once in a week. SEM and histology were performed as evidence of changes in cellular morphology. Inflammation was measured by the expression of Cox-2 and MMPs. Expression of proinflammatory cytokines (Cox-2, IL-6), signaling and cell cycle regulatory molecules (STAT3, Akt, CyclinD1) were measured by western blot, ELISA and immunoprecipitation. Mutagenecity was evidenced by comet assay. Cell proliferation was determined by cell count, cell cycle and DNA analysis.</p> <p>Results</p> <p>Prolonged exposure of low concentration of cadmium resulted in up regulation of proinflammatory cytokines and cell cycle regulatory molecules. Though NSAIDs like Ibuprofen reduces the expression of inflammatory cytokines, but it did not show any inhibitory effect on cadmium adopted lung cell proliferation.</p> <p>Conclusion</p> <p>Our results prove that cadmium causes both inflammation and cell proliferation when applied in a low dose but proliferative changes occur independent of inflammation.</p

Rare site of presentation of a rare manifestation of graves’ disease

Infiltrative dermopathy is an uncommon manifestation of Graves’ disease frequently involving the lower extremities. The pretibial area is most commonly involved. Rarely the fingers, hands, elbows, arms, or face are affected. Skin thickening is the characteristic abnormality. Localized myxedema is an autoimmune manifestation of Graves’ disease. Here, we report the case of a 45-year-old who presented with thyroid-associated orbitopathy and localized myxoedema over both the shoulders. In a patient who has long-standing hyperthyroidism, the diagnosis of infiltrative dermopathy is usually confirmed by the location, non-pitting nature, and distinct borders of the lesions. As most of these lesions are asymptomatic, no specific therapy is required

Down syndrome with ambiguous genitalia: A rare association

Down syndrome (DS) is one of the most common chromosomal disorders. Although genitourinary anomalies, such as a cryptorchidism, micropenis, posterior urethral valves, and hypospadias, have been recognized as complications, the association of ambiguous genitalia with DS has been rarely reported. We report the case of a 1-year-old baby; assigned male sex at birth who was the first child born of a non-consanguineous marriage, by vaginal delivery at term with a birth weight of 2.2 kg. The baby had clinical features suggestive of DS with a micropenis, penoscrotal hypospadias, and incompletely fused labial-scrotal folds with palpable gonads. The external masculinization score was 3/12. The child was reared as a male and hormonal investigations were suggestive of androgen insensitivity. Karyotype was 47, XY, +21

Multiple Patients Behavior Detection in Real-time using mmWave Radar and Deep CNNs

To address potential gaps noted in patient monitoring in the hospital, a novel patient behavior detection system using mmWave radar and deep convolution neural network (CNN), which supports the simultaneous recognition of multiple patients' behaviors in real-time, is proposed. In this study, we use an mmWave radar to track multiple patients and detect the scattering point cloud of each one. For each patient, the Doppler pattern of the point cloud over a time period is collected as the behavior signature. A three-layer CNN model is created to classify the behavior for each patient. The tracking and point clouds detection algorithm was also implemented on an mmWave radar hardware platform with an embedded graphics processing unit (GPU) board to collect Doppler pattern and run the CNN model. A training dataset of six types of behavior were collected, over a long duration, to train the model using Adam optimizer with an objective to minimize cross-entropy loss function. Lastly, the system was tested for real-time operation and obtained a very good inference accuracy when predicting each patient's behavior in a two-patient scenario.Comment: This paper has been submitted to IEEE Radar Conference 201

A two-hit model of alcoholic liver disease that exhibits rapid, severe fibrosis

Alcoholic liver disease (ALD) is responsible for an average of 50.4% and 44.2%of liver disease deaths among males and females respectively. Driven by alcohol misuse, ALD is often reversible by cessation of consumption. However, abstinence programs can have limited success at curtailing abuse, and the loss of life. ALD, therefore, remains a significant clinical challenge. There is a need for effective treatments that prevent or reverse alcohol-induced liver damage to complement or supplant behavioral interventions. Metabolic syndrome, which is disproportionally prevalent in ALD patients, accelerates the progression of ALD and increases liver disease mortality. Current rodent models of ALD unfortunately do not account for the contribution of the western diet to ALD pathology. To address this, we have developed a rodent model of ALD that integrates the impact of the western diet and alcohol; the WASH-diet model. We show here that the WASH diet, either chronically or in small time-restricted bouts, accelerated ALD pathology with severe steatohepatitis, elevated inflammation and increased fibrosis compared to mice receiving chronic alcohol alone. We also validated our WASH-diet model as an in vivo system for testing the efficacy of experimental ALD treatments. The efficacy of the inverse-agonist SR9238, previously shown to inhibit both non-alcohol and alcohol-induced steatohepatitis progression, was conserved in our WASH-diet model. These findings suggested that the WASH-diet may be useful for in vivo pre-clinical assessment of novel therapies

A two-hit model of alcoholic liver disease that exhibits rapid, severe fibrosis

Alcoholic liver disease (ALD) is responsible for an average of 50.4% and 44.2%of liver disease deaths among males and females respectively. Driven by alcohol misuse, ALD is often reversible by cessation of consumption. However, abstinence programs can have limited success at curtailing abuse, and the loss of life. ALD, therefore, remains a significant clinical challenge. There is a need for effective treatments that prevent or reverse alcohol-induced liver damage to complement or supplant behavioral interventions. Metabolic syndrome, which is disproportionally prevalent in ALD patients, accelerates the progression of ALD and increases liver disease mortality. Current rodent models of ALD unfortunately do not account for the contribution of the western diet to ALD pathology. To address this, we have developed a rodent model of ALD that integrates the impact of the western diet and alcohol; the WASH-diet model. We show here that the WASH diet, either chronically or in small time-restricted bouts, accelerated ALD pathology with severe steatohepatitis, elevated inflammation and increased fibrosis compared to mice receiving chronic alcohol alone. We also validated our WASH-diet model as an in vivo system for testing the efficacy of experimental ALD treatments. The efficacy of the inverse-agonist SR9238, previously shown to inhibit both non-alcohol and alcohol-induced steatohepatitis progression, was conserved in our WASH-diet model. These findings suggested that the WASH-diet may be useful for in vivo pre-clinical assessment of novel therapies