Energy expenditure analysis of redesigned mechanical assists for medium girder bridge

U.S. Army bridge crew soldiers perform tough manual material handling (MMH) tasks during the assembly of a Medium Girder Bridge (MGB). The bridge parts are very heavy and are manually lifted from pallets, carried to the construction site and assembled with other bridge parts. An energy expenditure study on the soldiers handling the bridge parts revealed that the energy expenditure rate of the soldiers exceeds the NIOSH prescribed safety limit of 3.5 Kcal/min. This leads to high risk of musculoskeletal disorders. The study deals with modifying the first redesign of mechanical assists for medium girder bridge (MGB) and studying the energy expended by soldiers during MGB construction while using the modified assists and comparing it to the energy expended by soldiers while using the current assists. The first redesign required minor modification to improve usability and performance. An effort was put to address these issues. The approach for this research involved redesign based on a field test performed with the first redesigned assists and observation of the bridge building process using recorded video tapes. The thesis research involved design modifications, prototype manufacturing and energy expenditure study using Energy Expenditure Prediction Program (EEPP). The EEPP study revealed that the redesigned mechanical assists reduced the average energy expenditure rate of soldiers by 33%. The average team energy expenditure was reduced by 50% --Abstract, page iii

Three-dimensional printing and nanotechnology for enhanced implantable materials

Orthopedic and oro-maxillofacial implants have revolutionized treatment of bone diseases and fractures. Currently available metallic implants have been in clinical use for more than 40 years and have proved medically efficacious. However, several drawbacks remain, such as excessive stiffness, accumulation of metal ions in surrounding tissue, growth restriction, required removal/revision surgery, inability to carry drugs, and susceptibility to infection. The need for additional revision surgery increases financial costs and prolongs recovery time for patients. These metallic implants are bulk manufactured and often do not meet patient\u27s requirements. A surgeon must machine (cut, weld, trim or drill holes) them in order to best suit the patient specifications. Over the past few decades, attempts have been made to replace these metallic implants with suitable biodegradable materials to prevent secondary/revision surgery. Recent advances in biomaterials have shown multiple uses for lactic acid polymers in bone implant technology. However, a targeted/localized drug delivery system needs to be incorporated in these polymers, and they need to be customized to treat orthopedic implant-related infections and other bone diseases such as osteomyelitis, osteosarcoma and osteoporosis. Rapid Prototyping (RP) using additive manufacturing (AM) or 3D printing could allow customization of constructs for personalized medicine. The goal of this study was to engineer customizable and biodegradable implant materials that can elute bioactive compounds for personalized medicine and targeted drug delivery. Post-operative infections are the most common complications following dental, orthopedic and bone implant surgeries. Preventing post-surgical infections is therefore a critical need that current polymethylmethacrylate (PMMA) bone cements fail to address. Calcium Phosphate Cements (CPCs) are unique in their ability to crystallize calcium and phosphate salts into hydroxyapatite (HA) and hence is naturally osteoconductive. Due to its low mechanical strength, its use in implant fixation and bone repair is limited to nonload-bearing applications. Novel CPCs were formulated and were doped with drug loaded Halloysite Nanotubes (HNTs) to enhance their mechanical and anti-infective properties. In this study we also explored the use of customized biopolymer filaments and 3D printing technology to treat bone diseases such as osteomyelitis, osteosarcoma, and osteoporosis. Biopolymer filaments were successfully loaded with antibiotics, chemotherapeutics and hormones (female sex hormones). Using a Fused Deposition Modeling (FDM)-based 3D printer, these customized filaments were fabricating into 3D scaffolds. Constructs with variable mechanical strengths and porosities were successfully designed and 3D printed. Scanning electron microscopy was used to study the surface architecture of the scaffolds. Compression and flexural testing was conducted for testing the mechanical strength of the constructs. Bacterial and suitable cell culture studies were applied to test bioactivity of the constructs. From above experiments, this study showed that 3D printing technology can be used to fabricate bioactive biopolymers for personalized medicine and localized drug delivery

Feature Grouping Using Weighted L1 Norm For High-Dimensional Data

Building effective prediction models from high-dimensional data is an important problem in several domains such as in bioinformatics, healthcare analytics and general regression analysis. Extracting feature groups automatically from such data with several correlated features is necessary, in order to use regularizers such as the group lasso which can exploit this deciphered grouping structure to build effective prediction models. Elastic net, fused-lasso and Octagonal Shrinkage Clustering Algorithm for Regression (oscar) are some of the popular feature grouping methods proposed in the literature which recover both sparsity and feature groups from the data. However, their predictive ability is affected adversely when the regression coefficients of adjacent feature groups are similar, but not exactly equal. This happens as these methods merge such adjacent feature groups erroneously, which is widely known as the misfusion problem. In order to solve this problem, in this thesis, we propose a weighted L1 norm-based approach which is effective at recovering feature groups, despite the proximity of the coefficients of adjacent feature groups, building extremely accurate prediction models. This convex optimization problem is solved using the fast iterative soft-thresholding algorithm (FISTA). We depict how our approach is more successful than competing feature grouping methods such as the elastic net, fused-lasso and oscar at solving the misfusion problem on synthetic datasets. We also compare the goodness of prediction of our algorithm against state-of-the-art non-convex feature grouping methods when applied on a real-world breast cancer dataset, the 20-Newsgroups dataset and synthetic datasets

A Review of Spring Boot Framework Based on REST API

This paper provides an introductory overview of the Spring framework and its application in building REST API-based web applications. It emphasizes the significance of Spring's architecture, including its modular layers, and highlights the advantages of using Spring Boot for simplifying configuration and deployment. The paper also discusses the flow of a typical Spring Boot application and the benefits of using Spring, such as rapid development, embedded server support, and extensive community resources. Overall, it offers valuable insights into leveraging Spring for efficient web application development

System architecture for an intelligent implantable bio-telemetry device

Biotelemetry has long been used for environmental and life science research to study animal populations and behavior. The use of implantable bio-telemetric techniques makes it possible to record and study physiological variables during long-term experiments with a minimum disturbance to the animal. Fully implantable telemetric techniques greatly reduce the risk of infection associated with leads and catheters protruding from the skin. In this research the design and implementation of a completely programmable bio-implantable digital system which can measure two physiological signals extended over a period of time is considered. The proposed system consists of a standalone implantable transmitter unit and a receiving base station unit. The transmitter unit measures the physiological parameter converts it to an 8-bit digital data, sends it to the inbuilt Bluetooth transceiver which then wirelessly transmits the digital data to the base station. The system utilizes the power intelligently by turning on only when needed, the rest of the time it goes to sleep mode. The biotelemetry system proposed is simple, flexible and reliable, provides accurate, continuous measurement of physiological parameters of small freely moving laboratory animals such as mice, rats or rabbits. The absence of restraints during the collection of physiological data allows studying animals with minimal stress during a long period of time in their normal housing

Classification of Prostate Cancer Patients into Indolent and Aggressive Using Machine Learning

Prostate cancer (PCa) is the second most common cancer in men in the US. Many Prostate cancers are Indolent and don’t result in cancer mortality, even without treatment. However, a significant proportion of patients with Prostate cancer have aggressive tumors that progress rapidly to metastatic disease and are often dangerous. Currently, treatment decisions for PCa patients are guided by various stratification algorithms. Among these parameters, the most important predictor of PCa mortality is the Gleason Grade (ranges from 6 to 10). Although current risk stratification tools are moderately effective, limitation remains in their ability to distinguish truly Indolent from aggressive and potentially lethal disease. Here we propose the use of Machine Learning (ML) for the classification of PC patients as having either indolent or aggressive using transcriptome data. We hypothesize that genomic alterations could lead to measurable changes distinguishing indolent from aggressive tumors. We also trained a Stacking-based model with a different set of combinations of classifiers. The highest overall accuracy of our stacking model (all samples with Gleason Grade: 6, 7, 8, 9, and 10) is 95.758% and (samples with Gleason Grade: 6, 8, 9, and 10) is 97.19%

Environment-induced corrections to the spin Hamiltonian as dynamic frequency shifts in nuclear magnetic resonance

We derive an expression for the correction to the spin-system Hamiltonian that arises due to the system-bath interaction, starting both from the standard master equation for the spin density matrix and a perturbative diagonalization of the system-bath Hamiltonian to the second order in the interaction. We show that the dynamic frequency shifts observed in the evolution of the nuclear spin coherences are a result of these Hamiltonian corrections. We present a systematic decomposition of the relaxation superoperator into Hermitian and anti-Hermitian parts as opposed to the usual practice of partitioning it into real and imaginary parts. We point out that the relaxation-induced corrections to the coherent motion arise exclusively from the anti-Hermitian part and the dissipative effects, from the Hermitian part, both, in general, being complex. However, the secular terms of this correction are found to depend only on the imaginary and the real parts, respectively

A clinical study of surgical management of paediatric humeral supracondylar fracture

Background: Injury to the supracondylar region of the humerus and complete displacement of the fragments occurs in many of the cases when children usually fall while playing. This is most common fracture seen in children, makes up to 60% of all elbow injuries. Early intervention results in excellent reduction and avoids complications. Concomitant vascular and nerve damages may occur. Open reduction and internal fixation is a helpful option for the treatment of supracondylar facture of humerus in children.Methods: Forty children who presented with displaced supracondylar fracture of the humerus were treated with open reduction and internal fixation with Kirschner (K) wires after thorough pre-operative investigation during the course of the study. Children below the age of 13 were selected irrespective of the sex.Results: Good results were obtained in 60% of the patients, fair in 30% and poor in 10%. The poor results were due to the open fracture and in two cases the patient presented very late to the hospital. Complications such as nerve injuries, vascular injuries, infections were noticed in the study. Four patients had cubitus varus and twelve patients had flexion loss on follow-up study.Conclusions: Open reduction and internal fixation with K wire is an easy, simple, inexpensive method, which has good outcome