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We propose a novel system for portrait relighting and background replacement, which maintains high-frequency boundary details and accurately synthesizes the subject's appearance as lit by novel illumination, thereby producing realistic composite images for any desired scene. Our technique includes foreground estimation via alpha matting, relighting, and compositing. We demonstrate that each of these stages can be tackled in a sequential pipeline without the use of priors (e.g. known background or known illumination) and with no specialized acquisition techniques, using only a single RGB portrait image and a novel, target HDR lighting environment as inputs. We train our model using relit portraits of subjects captured in a light stage computational illumination system, which records multiple lighting conditions, high quality geometry, and accurate alpha mattes. To perform realistic relighting for compositing, we introduce a novel per-pixel lighting representation in a deep learning framework, which explicitly models the diffuse and the specular components of appearance, producing relit portraits with convincingly rendered non-Lambertian effects like specular highlights. Multiple experiments and comparisons show the effectiveness of the proposed approach when applied to in-the-wild images.

Current research into the development of additive layer costs shows that this technology is economical in producing small batches with ongoing centralized manufacture; however improved automation may contribute to cost efficiency in distributed manufacturing. Due to the difficulty of which additive production costs are calculated, the reach of the current studies is small. Many of today's studies analyze single-part development. Many that look at assemblies prefer not to look at the impact of the supply chain, such as inventory and shipping prices and lower probability of interruption. Analysis currently also shows that the expense of content is a significant part of the cost of a commodity made using additive layer. Technologies may, therefore, also be compatible, with two technologies being implemented side by side and advantages larger than if independently adopted. Growing usage of additive processing may contribute to a decrease in raw material costs through saving in scale. This could result in further implementation of additive layer processing through the decreased cost of the raw material. The expense of raw materials will often save on a scale if specific materials are more popular than a host of other materials. The production method for additive layers is still a significant cost driver, but this cost has decreased continuously. The average price dropped 51% between 2001 and 2011 after inflation changes

In previous years, the usage of additive layer processing grew considerably. Different companies, including motor cars, aerospace, equipment, communications and medical devices utilize additional layer production. However, at present, processed additive layer products comprise less than one percent of all items manufactured. If the prices of additive layer processing systems decline, the manner in which customers communicate with suppliers will be modified. Additional development layer innovations provide the market and culture with different possibilities. It will make the personalized development of strong lightweight goods simpler, and prototypes that with past manufacturing techniques were not feasible. However, the application of this device may be hampered and delayed by numerous obstacles. Many situations require higher costs than conventional approaches for making a component utilizing additive layer production techniques. This study reviews the cost literature for the development of additive layer and attempts to recognize situations in which additive production may be cost-effective and also to identify new methods of minimizing costs in the usage of this technology

Background and Aim: Reconstruction of interdental papillae (IDP) is among the most difficult periodontal therapy. Papillary recession is multifactorial, and several surgical, nonsurgical, and minimally invasive techniques have been suggested. The purpose of this study was to evaluate the clinical application of injectable hyaluronic acid (HA) gel for the reconstruction of IDP in Nordland and Tarnow's Class I and II papillary recession cases. Materials and Methods: In the present in vivo clinical trial, 7 patients (2 males, 5 females) with 25 defects were selected. A volume of 0.2 ml HA gel was injected at the respective areas and massaged for 2–3 min. Photographs were obtained, and the assessment of the data was performed clinically (CP-GM, interproximal width [IPW]) and by Image analysis software (black triangle height [BTH], black triangle width [BTW]). Comparison of mean values was performed using the analysis of variance, followed by Post hoc Bonferroni test. Value of P ≤ 0.05 was considered statistically significant. Results: Application of HA gel for the reconstruction of IDP was successful in 6 months. CP-GM, BTH, IPW, and BTW showed a statistically significant difference from baseline to 3 and 6 months interval (P = 0.01). Post hoc Bonferroni test for CP-GM, BTH, BTW, and IPW revealed a statistically significant difference from baseline to 3 months (P ≤ 0.05) and 6 months (P ≤ 0.05) and a nonsignificant difference at 3–6 months (P ≥ 0.05). Conclusion: Injectable HA gel is a promising minimally invasive therapy for enhancing papillary esthetics.

Additive Layer Manufacturing (ALM), also known as 3D printing technology process of manufacturing that refers models parts from wire, powder, or sheets in a process that produced layer-by-layer from computer aided manufacturing (CAM). This process enables to produce components via solid-state joining or melting process. In this paper, these methods for producing metal tool components production through processing study of ALM methods as heat transfer, processing defects, solidification, mechanical properties, solid-state precipitation and post-processing metallurgical study. The various metal ALM techniques are analysed and compared with analysis of their strengths and limitations. Most of the metal alloys fabricated and produced and developed for production of metal tool components, but recent development of ALM shows as a path for the producing and development of new materials for additive layer manufacturing processes.

Purpose of study: Additive manufacturing processes taking the basic information form computer-aided design (CAD) file to convert into the stereolithography (STL) data file. Today additive layer manufacturing processes are playing a very vital role in manufacturing parts with high rate of effectiveness and accuracy. CAD software is approximated to sliced containing information of each layer by layer that is printed. The main purpose of the study is to discuss the scientific and technological challenges of additive layer manufacturing processes for making polymer components production through various technological parameters and problem-solving techniques of layer manufacturing processes. Main findings: Additive layer manufacturing is simply another name for 3D printing or rapid prototyping. As 3D printing has evolved as a technology, it has moved beyond prototyping and into the manufacturing space, with small runs of finished components now being produced by 3D printing machines around the world. Additive layer manufacturing (ALM) is the opposite of subtractive manufacturing, in which material is removed to reach the desired shape Methodology Used: The continuous and increasing growth of additive layer manufacturing processes to discuss with different experimental behavior through simulations and graphical representations. In ALM, 3D parts are built up in successive layers of material under computer control. In its early days, 3D printing was used mainly for rapid prototyping, but it is now frequently used to make finished parts the automotive and aerospace sectors, amongst many others. The originality of study: At the present time, the technologies of additive manufacturing are not just using for making models with the plastics but using polymer materials. It is possible to make finished products developed with high accuracy and save a lot of time and there is the possibility of testing more models.

Purpose of the study: Additive layer manufacturing is basically different from the traditional formative manufacturing process where a complete structure can be constructed into designed shape from layer to layer manufacturing rather than other methods or casting, forming or other machining processes. Additive layer manufacturing is a highly versatile, flexible, and customizable. Methodology: In this paper, we discussed high-performance computing and process control of AM methods by using different parameters. The significant interest in making complex, innovative and robust products by using AM methods to great extent to deal with work is needed in AM challenges relevant to key enabling technologies namely different materials and metrology to achieve functionally and reproductive ways. Main Findings: In this paper, we discussed major processes that highly accurate and the key applications, challenges and recent developments of future additive Am processes. Applications of this study: Additive layer manufacturing methods to develop the most highly and controlled methods for producing a variety of complex shapes and structures. The significant role of AM layer technology is to make produce the most economical and highly effective methods. In this study, we compared different AM methods for achieving the most highly and controlled methods of AM technology. Novelty/Originality of this study: Today manufacturing trends are very highly impacted by technologies globalizations. Various manufactures are using layer manufacturing into their best practices so that they can be changes in the global economy and manufacturing.

Regenerative Braking System is the latest frontier of research and study in electric vehicles. Big firms are investing a lot to incorporate this system in vehicles. We through our project have tried to broaden the area of study and implementation of Regenerative Braking system even in Electric Bikes. Regenerative Braking system has been incorporated in many four-wheelers but its presence in the zone of two-wheelers is still untouched, so we decided to make a move to contribute our learning and skills to explore in this untouched sector of two-wheelers. We have manufactured a model to test Regenerative Braking system in an electric bike and have made an attempt to prove it worth through our efforts.

Context: Major limitations of conventional radiography are overlapping and lack of 3D information. Surgical exposure, though being able to provide accurate information, provides very little time to plan-out the type of periodontal regeneration required during surgery. Cone Beam Computed Tomography (CBCT) has emerged as a feasible tool and found to be accurate. Unfortunately, in-vivo studies are still scarce. Aim: Aim of the present study was to assess the efficacy of CBCT in the detection of periodontal bony defects while determining its quantitative precision in the measurement of alveolar bone height as against the open flap debridement (OFD) procedure which is set as the gold standard. Setting and Design: Present study is a cross-sectional study. Materials and Methods: The present study includes patients with Chronic Periodontitis indicated for periodontal surgeries. Bone defects were measured with the help of CBCT and with William's periodontal probe during surgical intervention and compared. Statistical Analysis: Measurements were compared with Student's t-test; unpaired t-test & correlation were tested with Pearson's correlation coefficient test. P < 0.05 was considered statistically significant. Results: The mean CBCT & surgical value of palatal/lingual & distal sites of anterior teeth showed statistically significant difference (P = 0.001). All the values for posterior teeth were statistically non-significant. Conclusion: Statistically CBCT & clinical measurement with OFD have similar potential of accuracy to access the bony topography but CBCT provides good accessibility to visualize the sites which are difficult to access during surgical interventions like palatal sites & the distal sites of the posterior teeth.

We present "The Relightables", a volumetric capture system for photorealistic and high quality relightable full-body performance capture. While significant progress has been made on volumetric capture systems, focusing on 3D geometric reconstruction with high resolution textures, much less work has been done to recover photometric properties needed for relighting. Results from such systems lack high-frequency details and the subject's shading is prebaked into the texture. In contrast, a large body of work has addressed relightable acquisition for image-based approaches, which photograph the subject under a set of basis lighting conditions and recombine the images to show the subject as they would appear in a target lighting environment. However, to date, these approaches have not been adapted for use in the context of a high-resolution volumetric capture system. Our method combines this ability to realistically relight humans for arbitrary environments, with the benefits of free-viewpoint volumetric capture and new levels of geometric accuracy for dynamic performances. Our subjects are recorded inside a custom geodesic sphere outfitted with 331 custom color LED lights, an array of high-resolution cameras, and a set of custom high-resolution depth sensors. Our system innovates in multiple areas: First, we designed a novel active depth sensor to capture 12.4 MP depth maps, which we describe in detail. Second, we show how to design a hybrid geometric and machine learning reconstruction pipeline to process the high resolution input and output a volumetric video. Third, we generate temporally consistent reflectance maps for dynamic performers by leveraging the information contained in two alternating color gradient illumination images acquired at 60Hz. Multiple experiments, comparisons, and applications show that The Relightables significantly improves upon the level of realism in placing volumetrically captured human performances into arbitrary CG scenes.

We present a novel technique to relight images of human faces by learning a model of facial reflectance from a database of 4D reflectance field data of several subjects in a variety of expressions and viewpoints. Using our learned model, a face can be relit in arbitrary illumination environments using only two original images recorded under spherical color gradient illumination. The output of our deep network indicates that the color gradient images contain the information needed to estimate the full 4D reflectance field, including specular reflections and high frequency details. While capturing spherical color gradient illumination still requires a special lighting setup, reduction to just two illumination conditions allows the technique to be applied to dynamic facial performance capture. We show side-by-side comparisons which demonstrate that the proposed system outperforms the state-of-the-art techniques in both realism and speed.

A rare case of a type III Monteggia fracture equivalent with compartment syndrome is reported here. Literature is very scanty about this rare combination of injuries which we are discussing. Timely intervention can lead to a satisfactory outcome even in these complex injuries.

The technical feasibility of commercial gas production from microbially enhanced coalbed methane (MECBM) reservoirs can be divided into two broad categories: microbial treatment procedures and reservoir suitability. At this time, studies investigating the changes in reservoir-scale properties of coal as a result of bioconversion are lacking. This paper, first of a two-part series, presents the experimental work aimed at investigating the changes in sorption-induced strain response of coal to helium and methane flooding as a result of bioconversion. The strain and its variation, critical to producing methane after bioconversion, were established for coal treated for three periods, 15, 30 and 60 days. The results indicated a softer coal post-bioconversion which, in turn, resulted in inelastic strain with initial helium injection. However, past this initial compression, the bioconverted coal behavior was similar to untreated coal during continued helium injection/depletion. Methane flooding resulted in decreased sorption-induced shrinkage post-treatment, the decrease in Langmuir pressure and volume constants becoming larger with continued treatment. The observed results were used to understand the changes in coal structure for production of biogenic coalbed methane (BCBM) from depleted CBM reservoirs, recharged with methane using the bioconversion technology. The second part presents a detailed analysis of the experimental results to evaluate the behavior and performance of BCBM reservoirs.

Experimental data obtained for the strain response of coal to helium and methane flooding, pre-and post-bioconversion, was used to evaluate the reservoir-scale implications of coal bioconversion. Analysis showed that reservoir parameters, Langmuir-type strain ( ∊ l ) and pressure ( P ∊ ), rebound (Prb) and recovery (Prc) pressures decreased post-bioconversion non-linearly with the volume of biogenic methane produced. Also, the solid-matrix compressibility (CS) increased and shrinkage/swelling (Cm) compressibility decreased post-bioconversion. The effective stress and permeability response of coal to depletion was suppressed after microbial treatment. Finally, bioconversion resulted in softening of the coal matrix as well as ‘excess’ volumetric shrinkage post-methane depletion, enhancing the reservoir permeability. However, the increase was insignificant and was overshadowed by the effect of bioconversion induced swelling, which resulted in a significant reduction in reservoir permeability. The non-linear dependence of Cm to pore pressure resulted in its rebound past an inflection pressure (PI), identifiable for coal treated for longer durations. This was used to define an ideal condition, beyond which there was some improvement in reservoir performance. Effective stress response of coals before and after treatment was then used to rate the suitability of coals to bioconversion from a reservoir perspective.

Background: Four cannulated cancellous screws (CCS) in diamond configuration have been recommended by some authors for fixation of intracapsular neck of femur (ICNF) fracture with posterior comminution in adults. This is also supported by biomechanical studies. However, the clinical usefulness of this biomechanical advantage is not known. This study evaluates the outcomes of displaced, comminuted ICNF fracture in young adults managed by four CCS fixation in diamond configuration. Materials and Methods: 25 patients who met the inclusion criteria were operated during the study period. Four patients were lost to followup in the first 6 weeks postoperatively, and one patient died in first 6 months of followup unrelated to surgery. Thus, twenty patients were followed up for a mean period of 33.3 months (range 25–38 months). In all patients, fracture fixation was done with four CCS in diamond configuration. Union at fracture site and avascular necrosis (AVN) of femoral head was assessed on serial plain radiographs. Functional outcome was evaluated by Harris hip score. Results: Eighteen patients had union, two patients had nonunion, and two patients had AVN of femoral head. All the sixteen patients who had union without AVN had good or excellent functional outcome. Conclusions: The present study concludes that four CCS fixation in diamond configuration appears to be a reasonable choice of fixation for displaced fracture ICNF with comminution in young adults. However, further evaluation with better study design and larger patient population is required for definite conclusions.

Background: Complex distal end of humerus fractures are one of the most challenging cases in orthopedics. There is a paucity of literature on outcomes of parallel reconstruction plates using olecranon osteotomy technique along with large sample size. This study focuses primarily on rate of various complications encountered in intraarticular AO Type C distal humerus fractures. Materials and Methods: In this prospective study, we included 94 patients with isolated closed intraarticular AO type C distal and humerus injuries. Exclusion criteria were polytrauma, open injuries, and pathological fractures (except osteoporosis). The followup was done immediate postoperatively, 6 weeks, 6 months, 1 year and at 2 years. Range of motion (ROM), Mayo Elbow Performance Score (MEPS), and Disabilities of the Arm, Shoulder, and Hand (DASH) score was recorded at each visit. Assessment of union was done based on X-ray. Patients were classified into two groups; Group 1 – patients without complications (n = 64) and Group 2 – with one or more complications. Results: The average duration of surgery was 2 h and 15 min. The complication rate was 31.9% (30/94), however, a total of 45 complications were noted. The difference between ROM in the two groups was statistically significant (P < 0.05), however, the difference between MEPS and DASH score was not statistically significant. The most common complication found was ulnar nerve neuropathy. Conclusion: Parallel plating using olecranon osteotomy is an acceptable approach for this fracture, but due to inherent nature of this injury, it has its own set of complications which must be counseled before surgery and active participation of patient is required to obtain realistic expectations and goals for the future.

Reporting a rare scenario of hypoglossal nerve palsy in craniovertebral tuberculosis. Two patients presented in outpatient department with chief complaints of pain in neck, restricted neck movements, gait changes, difficulty in speech and weakness in all the extremities. On the basis of clinicoradiological correlation, the patients were diagnosedwithtuberculosis of C1–C2 spine. They were started on antituberculosis therapy Category 1. The patients improved clinically and there was no worsening of symptoms, but they noticed tongue deviation and hypotrophy on one side of the tongue. C1–C2 tuberculosis along with cranial nerve palsy, especially hypoglossal nerve is one of the rarest presentations. Hypoglossal nerve arises from the medulla, exits through hypoglossal canal in the base of the skull and traverses neck to supply tongue musculature. Prevertebral fascia extends from superior mediastinum to base of the skull. Abscess in this area can cause either actual compression of the hypoglossal canal or C1 and base of the skull dissociation which can lead to compression of the canal.

Motivated by augmented and virtual reality applications such as telepresence, there has been a recent focus in real-time performance capture of humans under motion. However, given the real-time constraint, these systems often suffer from artifacts in geometry and texture such as holes and noise in the final rendering, poor lighting, and low-resolution textures. We take the novel approach to augment such real-time performance capture systems with a deep architecture that takes a rendering from an arbitrary viewpoint, and jointly performs completion, super resolution, and denoising of the imagery in real-time. We call this approach neural (re-)rendering , and our live system "LookinGood". Our deep architecture is trained to produce high resolution and high quality images from a coarse rendering in real-time. First, we propose a self-supervised training method that does not require manual ground-truth annotation. We contribute a specialized reconstruction error that uses semantic information to focus on relevant parts of the subject, e.g. the face. We also introduce a salient reweighing scheme of the loss function that is able to discard outliers. We specifically design the system for virtual and augmented reality headsets where the consistency between the left and right eye plays a crucial role in the final user experience. Finally, we generate temporally stable results by explicitly minimizing the difference between two consecutive frames. We tested the proposed system in two different scenarios: one involving a single RGB-D sensor, and upper body reconstruction of an actor, the second consisting of full body 360° capture. Through extensive experimentation, we demonstrate how our system generalizes across unseen sequences and subjects.

Background: Cementless implants were introduced approximately three decades ago in order to address aseptic loosening of cemented hip prostheses with the aim of early mobilisation, better functional result and bone stock preservation. The primary objective of this study is to introduce a new cementless HA coated implant and report its minimum 2 year follow up results. Material & method: This is a prospective, multi-centre, consecutive series, clinical outcomes study with 75 patients. Inclusion criteria for the study were age 21- 85 years, BMI

In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses. Prior art either assumes small motion between frames or relies on local descriptors, which cannot handle large motion or visually ambiguous body parts, e.g., left vs. right hand. In contrast, we propose a deep learning framework that maps each pixel to a feature space, where the feature distances reflect the geodesic distances among pixels as if they were projected onto the surface of a 3D human scan. To this end, we introduce novel loss functions to push features apart according to their geodesic distances on the surface. Without any semantic annotation, the proposed embeddings automatically learn to differentiate visually similar parts and align different subjects into an unified feature space. Extensive experiments show that the learned embeddings can produce accurate correspondences between images with remarkable generalization capabilities on both intra and inter subjects.1

The light transport (LT) of a scene describes how it appears under different lighting and viewing directions, and complete knowledge of a scene's LT enables the synthesis of novel views under arbitrary lighting. In this paper, we focus on image-based LT acquisition, primarily for human bodies within a light stage setup. We propose a semi-parametric approach to learn a neural representation of LT that is embedded in the space of a texture atlas of known geometric properties, and model all non-diffuse and global LT as residuals added to a physically-accurate diffuse base rendering. In particular, we show how to fuse previously seen observations of illuminants and views to synthesize a new image of the same scene under a desired lighting condition from a chosen viewpoint. This strategy allows the network to learn complex material effects (such as subsurface scattering) and global illumination, while guaranteeing the physical correctness of the diffuse LT (such as hard shadows). With this learned LT, one can relight the scene photorealistically with a directional light or an HDRI map, synthesize novel views with view-dependent effects, or do both simultaneously, all in a unified framework using a set of sparse, previously seen observations. Qualitative and quantitative experiments demonstrate that our neural LT (NLT) outperforms state-of-the-art solutions for relighting and view synthesis, without separate treatment for both problems that prior work requires., Camera-ready version for TOG 2021. Project Page: http://nlt.csail.mit.edu/

Casually-taken portrait photographs often suffer from unflattering lighting and shadowing because of suboptimal conditions in the environment. Aesthetic qualities such as the position and softness of shadows and the lighting ratio between the bright and dark parts of the face are frequently determined by the constraints of the environment rather than by the photographer. Professionals address this issue by adding light shaping tools such as scrims, bounce cards, and flashes. In this paper, we present a computational approach that gives casual photographers some of this control, thereby allowing poorly-lit portraits to be relit post-capture in a realistic and easily-controllable way. Our approach relies on a pair of neural networks---one to remove foreign shadows cast by external objects, and another to soften facial shadows cast by the features of the subject and to add a synthetic fill light to improve the lighting ratio. To train our first network we construct a dataset of real-world portraits wherein synthetic foreign shadows are rendered onto the face, and we show that our network learns to remove those unwanted shadows. To train our second network we use a dataset of Light Stage scans of human subjects to construct input/output pairs of input images harshly lit by a small light source, and variably softened and fill-lit output images of each face. We propose a way to explicitly encode facial symmetry and show that our dataset and training procedure enable the model to generalize to images taken in the wild. Together, these networks enable the realistic and aesthetically pleasing enhancement of shadows and lights in real-world portrait images, (updated version); SIGGRAPH 2020;Project webpage: https://people.eecs.berkeley.edu/~cecilia77/project-pages/portrait Video: https://youtu.be/M_qYTXhzyac

The increasing demand for 3D content in augmented and virtual reality has motivated the development of volumetric performance capture systemsnsuch as the Light Stage. Recent advances are pushing free viewpoint relightable videos of dynamic human performances closer to photorealistic quality. However, despite significant efforts, these sophisticated systems are limited by reconstruction and rendering algorithms which do not fully model complex 3D structures and higher order light transport effects such as global illumination and sub-surface scattering. In this paper, we propose a system that combines traditional geometric pipelines with a neural rendering scheme to generate photorealistic renderings of dynamic performances under desired viewpoint and lighting. Our system leverages deep neural networks that model the classical rendering process to learn implicit features that represent the view-dependent appearance of the subject independent of the geometry layout, allowing for generalization to unseen subject poses and even novel subject identity. Detailed experiments and comparisons demonstrate the efficacy and versatility of our method to generate high-quality results, significantly outperforming the existing state-of-the-art solutions.

Microbially enhanced coalbed methane (MECBM) aims to replicate the natural process of microbial methane generation in coal under in situ conditions. Considerable work has been reported over the years to optimize the associated microbial geo-chemistry. However, there is very little insight with regards to changes in the physical structure of coal due to bioconversion, and its impact on fluid flow properties. This paper presents the result of an image and fractal-based approach used to evaluate the changes in physical properties of coal. Samples of coal treated over 30, 60 and 120 days respectively were imaged before and after bioconversion. The results revealed that coal bioconversion resulted in swelling of the coal matrix. Cleats narrower than 5 µm reduced in its width post-bioconversion. A 77% drop in the permeability of coal is expected from the obtained results. Bioconversion also resulted in separation of thin layers of coal flakes from the coal surface, serving as a potential source of fines. Fractal analysis of the images revealed a decrease in the fractal dimension post bioconversion, which is in agreement with the previously reported studies, thus corroborating the variations in sorption-trends observed due to bioconversion. Additionally, the methodology to determine the fractal dimension via two-dimensional image processing was modified to improve its accuracy, and remove the dependency of the dimension to the scale of the obtained images. Bioconversion also resulted in formation of new pores/fractures. Shorter treatment duration resulted in nanometer-scale discontinuous pores, which do not contribute to Darcian flow. Longer treatment periods resulted in sub-micron wide continuous pores. Also, few larger fractures (>5 µm wide) saw an increase in its aperture post-treatment. This opens up new avenues, such as, utilizing artificially induced fracturing techniques to enhance biogenic methane production in future.

OBJECTIVE: Impingement syndrome is the most common differential in a patient presenting to an orthopaedic OPD with shoulder pain. Impingement syndrome is often managed with subacromial corticosteroid injection, which can be instilled using either landmark guided (LMG) approach or with the assistance of ultrasound (US). This study was envisaged to enquire whether ultrasound assistance improves the accuracy, efficacy or safety profile of the injection. METHODS: 60 patients of rotator cuff syndrome underwent diagnostic ultrasound. They were randomly assigned to receive subacromial injection of 2 ml (40 mg/ml) methylprenisolone and 2 ml of 1% lignocaine combination either by US assistance (n = 30) or using LMG assistance (n = 30). The patients were evaluated before injection and on follow up visits at day 5, week 3, week 6 and 3rd month by a single assessor. The assessor was blinded of the treatment group to which patient belonged. Clinical assessment included demographic and clinical data, accuracy of injection, VAS (0–100) for pain, Constant score with goniometer evaluation of range of motion, patient’s self assessment proforma and post injection side effects if any. RESULTS: Initial demographic, clinical and US findings in the groups exhibited no significant differences. The accuracy of US guided injections (100%) was more when compared from LMG injection (93.3%). Both VAS and Constant score showed significant improvement following steroid injection up to 3 months of follow up. However the differences in the two groups were not significant suggesting comparable efficacy of the two approaches. (Mean VAS score decrease: 27.23 for US and 25.16 for LMG, p

Background: Comparision of results and complications of exposed versus buried Kirschner wires (K-wires) after open reduction of lateral condyle fractures is scarce and mainly from western population; hence, we envisaged to study the safety and efficacy of exposed and buried K-wires used for fixation of displaced pediatric fracture of the lateral condyle of humerus in Indian setup. Materials and Methods: A prospective, nonrandomized, comparative study was conducted in 50 patients with age

Langerhans cell histiocytosis (LCH) is characterised by an abnormal histiocytic accumulation in tissues such as the lung, spleen, bone marrow, skin, central nervous system, liver and lymph nodes, causing focal or systemic effects. No specific clinical & radiographic presenta -tion of LCH is described in literature. This poses a diagnostic dilemma for surgeons. The scapula is the site of 3% of bone tumours, while for LCH it is the least common site. In a 10-year-old boy with isolated lesion of the scapula with no other systemic involvement, and no specific finding in MRI or CT scan of scapula, diagnosis was confirmed on biopsy. Division into single and multi-system disease is paramount in treatment, given that it is a single system disease. The patient improved clinically on follow-up of 2 years. The scapula is one of the rarest site of LCH, and because various lesions mimic each other, a biopsy is always required, with immunohistochemistry for CD68 & S-100. This was only a single system disease, so conservative management was performed, and the patent improved clinically.Keywords: Histiocytosis, Langerhans-cell; Scapula; Immunohistochemistry.

Volumetric (4D) performance capture is fundamental for AR/VR content generation. Whereas previous work in 4D performance capture has shown impressive results in studio settings, the technology is still far from being accessible to a typical consumer who, at best, might own a single RGBD sensor. Thus, in this work, we propose a method to synthesize free viewpoint renderings using a single RGBD camera. The key insight is to leverage previously seen “calibration” images of a given user to extrapolate what should be rendered in a novel viewpoint from the data available in the sensor. Given these past observations from multiple viewpoints, and the current RGBD image from a fixed view, we propose an end-to-end framework that fuses both these data sources to generate novel renderings of the performer. We demonstrate that the method can produce high fidelity images, and handle extreme changes in subject pose and camera viewpoints. We also show that the system generalizes to performers not seen in the training data. We run exhaustive experiments demonstrating the effectiveness of the proposed semi-parametric model (i.e. calibration images available to the neural network) compared to other state of the art machine learned solutions. Further, we compare the method with more traditional pipelines that employ multi-view capture. We show that our framework is able to achieve compelling results, with substantially less infrastructure than previously required.

We explore total scene capture -- recording, modeling, and rerendering a scene under varying appearance such as season and time of day. Starting from internet photos of a tourist landmark, we apply traditional 3D reconstruction to register the photos and approximate the scene as a point cloud. For each photo, we render the scene points into a deep framebuffer, and train a neural network to learn the mapping of these initial renderings to the actual photos. This rerendering network also takes as input a latent appearance vector and a semantic mask indicating the location of transient objects like pedestrians. The model is evaluated on several datasets of publicly available images spanning a broad range of illumination conditions. We create short videos demonstrating realistic manipulation of the image viewpoint, appearance, and semantic labeling. We also compare results with prior work on scene reconstruction from internet photos., To be presented at CVPR 2019 (oral). Supplementary video available at http://youtu.be/E1crWQn_kmY

Aerial images usually are huge (around 2K resolution). Such high-resolution images contain thousands of small objects, and detecting all of them is a very challenging problem. The complexity of detection and classification in real-time is much higher than the usual images (

Oral squamous cell carcinoma metastasizes commonly to the lung, brain, skin, and occasionally to the bones such as vertebra and ribs. However, spread to the dorsal vertebra with cord compression is an extremely rare presentation. This case highlights this rare entity which was managed surgically. It enabled in ameliorating patient's distressing pain and restoring quality of life.

The transient technique for laboratory permeability measurement, proposed by Brace et al. (J Geophys Res 73:2225–2236, 1968) and widely used for conventional gas reservoir rocks, is the preferred method when testing low-permeability rocks in the laboratory. However, Brace et al.’s solution leads to considerable errors since it does not take into account compressive storage and sorption effect when applied to sorptive rocks, such as, coals and shales. To verify the applicability of this solution when used to characterize fluid flow behavior of coal, an in-depth investigation of permeability evolution for flow of helium and methane depletion was conducted for San Juan coals using the pressure pulse-decay method under best replicated in situ conditions. Three permeability solutions, Brace et al.’s (1968), Dicker and Smits’s (International meeting on petroleum engineering, Society of Petroleum Engineers, 1988) and Cui et al.’s (Geofluids 9:208–223, 2009), were utilized to establish the permeability trends. Both helium and methane permeability results exhibited very small difference between the Brace et al.’s solution and Dicker and Smits’s solution, indicating that the effect of compressive storage is negligible. However, methane permeability enhancement at low pressures due to coal matrix shrinkage resulting from gas desorption can be significant and this was observed in pressure response plots and the estimated permeability values using Cui et al.’s solution only. Therefore, it is recommended that Cui et al.’s solution be employed to correctly include the sorption effect when testing coal permeability using the transient technique. A series of experiments were also carried out to establish the stress-dependent permeability trend under constant effective stress condition, and then quantify the sole contribution of the sorption effect on permeability variation. By comparison with the laboratory data obtained under in situ stress/strain condition, it was verified that accelerated CBM production can be achieved by reducing the horizontal stresses.

This study was aimed at identifying the changes in coal storage and transport properties affecting gas production from coal-gas reservoirs, when treated with microbial consortia to generate/enhance production of methane. The work expanded on the technology of bio-conversion, first proposed in order to imitate the natural/microbial process of biogenic gasification leading to recharging coalbed methane reservoirs or, setting up natural gas reservoirs in non-producing coalbeds or, to coal waste, typically in the form of fines/ultra-fines. The pressure parameter was considered critical since, with continued production of methane, the produced gas would first diffuse into the coal matrix and get adsorbed with increasing pressure. During production, the pressure would decrease and the process would be reversed, gas diffusing out of the coal matrix and arriving at the cleat system. The experimental work tested the variation in the sorption and diffusion properties of treated coal, post continued bio-conversion since these are the first two physical phenomena in CBM production. During the first phase, single component sorption–diffusion experiments were carried out using methane and CO2 on virgin coals retrieved from the Illinois basin. Coals were then treated with nutrient amended microbial consortia for different periods. Gas production was monitored over thirty and sixty day periods of treatment after which, sorption–diffusion experiments were repeated on treated coals, thus establishing a trend over the sixty-day period. The sorption data was characterized using the Langmuir model. The variation trend in the value of diffusion coefficient, D, was also established as a function of pore pressure. The results indicated an increase in the sorption capacity of coal as a result of continued bioconversion. This was attributed to increased pore surface area due to microbial actions resulting in changes in the pore size or, creation of new pores. It was further shown that the rate of diffusion increased, especially for methane, which exhibited rates higher than that for CO2. These findings clearly support improved gas storage capacity with continued bio-conversion as well as significantly enhanced diffusion rates. As a continuation of this effort, change in permeability, the second gas transport phenomenon in coal-gas production, is currently being evaluated.

A laboratory-scale coal permeability measurement study using the pressure pulse decay method was carried out to establish the permeability variation trend impacted by the combined effects of effective stresses and coal matrix shrinkage associated with gas depletion under uniaxial strain condition for San Juan basin coal. The experimental results showed that increased effective horizontal stress negatively impacts permeability enhancement. Furthermore, effective horizontal stress dominates the permeability variation. Finally, the rate of permeability increase accelerates dramatically at low pressures as a result of decrease in effective horizontal stress due to the matrix shrinkage effect. The established pressure-dependent-permeability (PdK) was compared with modeled results using two models, Harpalani and Chen and Shi and Durucan, both based on variations in effective horizontal stress. The match with the results obtained using the Harpalani and Chen model was perfect when appropriate initial cleat porosity and matrix shrinkage strain parameters were used. However, given the analytical conditions presented, the agreement between experimental and modeled results using the Shi and Durucan model was poor. After reviewing the fundamental principles behind model development, a modification was made, based on geo-mechanical principles. The measured permeability variation matched well with the results predicted by the modified model when appropriate cleat compressibility values were used. Basically, the revised model increases the effect of matrix shrinkage on permeability changes with continued depletion. The modeled results showed a permeability trend consistent with the experimental result although the permeability of coal was overestimated at low pressures.

Cirsoid aneurysms (arteriovenous malformations [AVMs]) of the scalp are rarely encountered in neurosurgical practice. Patients with AVM of the scalp present clinically at times with headache and a small innocuous-looking subcutaneous scalp lump or a large, pulsatile mass with or without bruit, which has a propensity to massive hemorrhage. Complex vascular anatomy and interconnections, high shunt flow, and possible cosmetic complications tend to make their management difficult. We report a rare case of young man who presented with progressively enlarging swelling over left fronto-temporo-parietal and occipital region of the scalp since 8 years. Digital subtraction angiography of internal and external carotid vessels revealed high-flow, complex left parietal scalp AVM supplied by multiple tortuous feeders from left superficial temporal artery (STA), left middle meningeal artery, left occipital artery with collateral supply from right occipital artery, and right STA. Drainage into external jugular vein through multiple tortuous frontal, temporal, and occipital scalp veins with venous varix. Being high-flow shunt and because of suspected cosmetic complications, surgical excision was considered.

Virtual and augmented reality technologies have seen significant growth in the past few years. A key component of such systems is the ability to track the pose of head mounted displays and controllers in 3D space. We tackle the problem of efficient 6-DoF tracking of a handheld controller from egocentric camera perspectives. We collected the HMD Controller dataset which consist of over 540,000 stereo image pairs labelled with the full 6-DoF pose of the handheld controller. Our proposed SSD-AF-Stereo3D model achieves a mean average error of 33.5 mm in 3D keypoint prediction and is used in conjunction with an IMU sensor on the controller to enable 6-DoF tracking. We also present results on approaches for model based full 6-DoF tracking. All our models operate under the strict constraints of real time mobile CPU inference.

No study in literature clearly gives advantage of one method of surgical fixation of fracture over the other in metacarpal and phalangeal bones of hand comparing wider outcome measures. A randomized controlled trial between closed reduction and percutaneous Kirschner wire fixation or open reduction and internal fixation with mini fragment plates was conducted. A total of 32 patients with 16 in each group were taken in tertiary-level teaching hospital from 2014 to 2016. Four patients lost to follow-up apart from 32 studied. Inclusion criteria were age group 16–60 years, fresh (3 days) closed shaft fractures of metacarpal and phalanges. Outcome evaluated were time to union of fracture, degree of strength achieved measured with dynamometer, DASH scoring, range of motion of hand and each digit. Both groups were comparable in terms of return to full hand function, union and total range of motion. K wire fixation results were slightly better than plating group in terms of early DASH score and grip strength after fixation. No modality was found to be superior for fixation of small bone fractures of hand. But K wire being cheaper and without inherent complication of plating like scar and tendon irritation, K wire fixation is preferred over plating in shaft fractures of metacarpal and phalanges. Level I Therapeutic study.

In this chapter, we discuss the impact of recent advancements in deep learning in the field of biometric template protection. The representation learning ability of neural networks has enabled them to achieve state-of-the-art results in several fields, including face recognition. Consequently, biometric authentication using facial images has also benefited from this, with deep convolutional neural networks pushing the matching performance numbers to all time highs. This chapter studies the ability of neural networks to learn representations which could benefit template security in addition to matching accuracy. Cryptographic hashing is generally considered most secure form of protection for the biometric data, but comes at the high cost of requiring an exact match between the enrollment and verification templates. This requirement generally leads to a severe loss in matching performance (FAR and FRR) of the system. We focus on two relatively recent face template protection algorithms that study the suitability of representations learned by neural networks for cryptographic hash based template protection. Local region hashing tackles hash-based template security by attempting exact matches between features extracted from local regions of the face as opposed to the entire face. A comparison of the suitability of different feature extractors for the task is presented and it is found that a representation learned by an autoencoder is the most promising. Deep secure encoding tackles the problem in an alternative way by learning a robust mapping of face classes to secure codes which are then hashed and stored as the secure template. This approach overcomes several pitfalls of local region hashing and other face template algorithms. It also achieves state-of-the-art matching performance with a high standard of template security.

In this paper we present a framework for secure identification using deep neural networks, and apply it to the task of template protection for face password authentication. We use deep convolutional neural networks (CNNs) to learn a mapping from face images to maximum entropy binary (MEB) codes. The mapping is robust enough to tackle the problem of exact matching, yielding the same code for new samples of a user as the code assigned during training. These codes are then hashed using any hash function that follows the random oracle model (like SHA-512) to generate protected face templates. The algorithm makes no unrealistic assumptions and offers high template security, cancelability, and matching performance comparable to the state-of-the-art. The efficacy of the approach is shown on CMU-PIE, Extended Yale B, and Multi-PIE face databases. We achieve high (~ 95%) genuine accept rates (GAR) at zero false accept rate (FAR) while maintaining a high level of template security.

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In this paper we present a framework for logo retrieval in natural images. Color-localized spatial masks are used as an alternative to computationally expensive spatial verification techniques like RANSAC. First, keypoints are detected using traditional techniques such as the SIFT detector. Local masks are defined around each keypoint that take its scale and orientation information into account. To exploit inherent color information presented in brand logos, ordered color histograms are extracted from masked regions. A separate vocabulary is constructed for both SIFT descriptors (visual word) and color histograms (color word). For faster matching during runtime, a two-stage cascaded index is designed, which maps the visual word and color word tuple to a list of relevant images. This list is finally re-ranked with BoW cosine similarity to generate relevant matches for the input query. To demonstrate the efficacy of our method, we conduct experiments on two popular logo datasets: Flickr27 and Flickr32. Our experimental results illustrate State-of-the-art retrieval performance on these datasets with potential for added speed and a lower memory footprint as indicated by the low response ratio.