Metal Forming Force Measurement

ME450 Capstone Design and Manufacturing Experience: Fall 2015Clips and Clamps Industries (CCI) produces small metal parts, many of which are formed using metal forming fourslide machines. CCI’s fourslide machines have been experiencing failures and increased maintenance due to the usage of high-strength steels that require more force to form. In order to minimize damage and maintenance, CCI has asked to implement a sensor that detects the forces on the slide while the machine is in operation, to incorporate a safety control to automatically shut off the machine when a programmed force is exceeded, and to calculate the maximum tonnage rating on the forming section—specifically the front slide as this is the area prone to failure. This design must also be scalable so that it may be implemented on both the smaller, S3F and larger, S4F machines. After initial research and defining the project scope, finite element analysis simulations on the slide and gathering feedback from sponsors at CCI and professors at the University of Michigan, the final design was solidified as a Wintriss strain link sensor bolted to the top of the slide. Through Solidworks CAD models, data was gathered regarding strains on the slide to justify the location of the sensor while assuring that the design would not hinder the fourslide machine operation or compromise safety. The risk associated with the design has been assessed in both a risk analysis and FMEA, raising concerns with safety and potential failures. The final design has been manufactured and was installed in a fourslide machine at CCI. To validate whether the design meets the project requirements, the strain link was calibrated with a load cell to ensure accuracy as well as tested to ensure functionality of auto-shutoff capability. Additionally, through theoretical modeling including finite element and fatigue analysis, the maximum tonnage rating was determined to be 4.5 tons. This maximum tonnage rating will be validated and further refined through empirical testing over time carried out by CCI.http://deepblue.lib.umich.edu/bitstream/2027.42/117336/1/ME450-F15-Project17-FinalReport.pd

A Unified Framework for Discovering Discrete Symmetries

We consider the problem of learning a function respecting a symmetry from among a class of symmetries. We develop a unified framework that enables symmetry discovery across a broad range of subgroups including locally symmetric, dihedral and cyclic subgroups. At the core of the framework is a novel architecture composed of linear and tensor-valued functions that expresses functions invariant to these subgroups in a principled manner. The structure of the architecture enables us to leverage multi-armed bandit algorithms and gradient descent to efficiently optimize over the linear and the tensor-valued functions, respectively, and to infer the symmetry that is ultimately learnt. We also discuss the necessity of the tensor-valued functions in the architecture. Experiments on image-digit sum and polynomial regression tasks demonstrate the effectiveness of our approach

Study cellular reponses at the microscale by creating heterogenity in cultured cells using a microfluidic probe

We introduce a new approach to study cellular responses in different cell subpopulations while not disrupting the microenvironments. We believe this might become a useful tool to investigate resistance-related cellular responses in cancer cells. Please click Additional Files below to see the full abstract

Study of sodium potassium tantalate mixed system

184-187Ceramic pellets of Na1-xKxTaO3 (x= 0 & 0.5) system have been prepared by solid state reaction method and sintering process. The prepared samples are characterized by XRD and SEM techniques. Lattice parameters have been calculated by XRD pattern and grain size has been calculated by SEM. It has been observed that the prepared samples show orthorhombic structure at room temperature

SMARThealth PRegnancy And Mental Health study: protocol for a situational analysis of perinatal mental health in women living in rural India

Introduction: The situation for women experiencing mental health problems during pregnancy and postpartum in rural India is critical: a high burden of disease, a high estimated number of women are undiagnosed and untreated with mental health problems, a substantial gap in research on women's perinatal health, and severe stigma and discrimination. The SMARThealth Pregnancy study is a cluster randomised trial using a digital intervention to identify and manage anaemia, hypertension, and diabetes in the first year after birth in rural India. Within this study, the SMARThealth Pregnancy and Mental Health (PRAMH) study is a situational analysis to understand mental health problems during pregnancy and in the first year following birth in this population. Methods/design: This situational analysis aims to analyse and to assess the context of perinatal mental health, health services, barriers, facilitators, and gaps in Siddipet district of Telangana state in India, to develop an implementation framework for a future intervention. A tested, standardised situational analysis tool will be adapted and applied to perinatal mental health in rural India. A desktop and policy review will be conducted to identify and analyse relevant mental health and pregnancy care policies at the national and state levels. We will conduct in-depth interviews with policymakers, planners, mental health professionals and other experts in perinatal mental health (n = 10–15). We will also conduct focus group discussions with key stakeholders, including women with perinatal mental health problems, their families and carers, and community health workers (n = 24–40). A theory of change workshop with key stakeholders will be conducted which will also serve as a priority setting exercise, and will clarify challenges and opportunities, priorities, and objectives for a pilot intervention study. The analysis of qualitive data will be done using thematic analysis. Based on the data analysis and synthesis of the findings, an implementation framework will be developed to guide development, testing and scale up of a contextually relevant intervention for perinatal mental health. Discussion: The situational analysis will help to establish relationships with all relevant stakeholders, clarify the context and hypotheses for the pilot intervention and implementation

Monocrotophos Induced Apoptosis in PC12 Cells: Role of Xenobiotic Metabolizing Cytochrome P450s

Monocrotophos (MCP) is a widely used organophosphate (OP) pesticide. We studied apoptotic changes and their correlation with expression of selected cytochrome P450s (CYPs) in PC12 cells exposed to MCP. A significant induction in reactive oxygen species (ROS) and decrease in glutathione (GSH) levels were observed in cells exposed to MCP. Following the exposure of PC12 cells to MCP (10−5 M), the levels of protein and mRNA expressions of caspase-3/9, Bax, Bcl2, P53, P21, GSTP1-1 were significantly upregulated, whereas the levels of Bclw, Mcl1 were downregulated. A significant induction in the expression of CYP1A1/1A2, 2B1/2B2, 2E1 was also observed in PC12 cells exposed to MCP (10−5 M), whereas induction of CYPs was insignificant in cells exposed to 10−6 M concentration of MCP. We believe that this is the first report showing altered expressions of selected CYPs in MCP-induced apoptosis in PC12 cells. These apoptotic changes were mitochondria mediated and regulated by caspase cascade. Our data confirm the involvement of specific CYPs in MCP-induced apoptosis in PC12 cells and also identifies possible cellular and molecular mechanisms of organophosphate pesticide-induced apoptosis in neuronal cells

Cucurbitacin D Reprograms Glucose Metabolic Network in Prostate Cancer

Prostate cancer (PrCa) metastasis is the major cause of mortality and morbidity among men. Metastatic PrCa cells are typically adopted for aberrant glucose metabolism. Thus, chemophores that reprogram altered glucose metabolic machinery in cancer cells can be useful agent for the repression of PrCa metastasis. Herein, we report that cucurbitacin D (Cuc D) effectively inhibits glucose uptake and lactate production in metastatic PrCa cells via modulating glucose metabolism. This metabolic shift by Cuc D was correlated with decreased expression of GLUT1 by its direct binding as suggested by its proficient molecular docking (binding energy -8.5 kcal/mol). Cuc D treatment also altered the expression of key oncogenic proteins and miR-132 that are known to be involved in glucose metabolism. Cuc D (0.1 to 1 µM) treatment inhibited tumorigenic and metastatic potential of human PrCa cells via inducing apoptosis and cell cycle arrest in G2/M phase. Cuc D treatment also showed inhibition of tumor growth in PrCa xenograft mouse model with concomitant decrease in the expression of GLUT1, PCNA and restoration of miR-132. These results suggest that Cuc D is a novel modulator of glucose metabolism and could be a promising therapeutic modality for the attenuation of PrCa metastasis

Computational Immunohistochemistry: Recipes for Standardization of Immunostaining

Cancer diagnosis and personalized cancer treatment are heavily based on the visual assessment of immunohistochemically-stained tissue specimens. The precision of this assessment depends critically on the quality of immunostaining, which is governed by a number of parameters used in the staining process. Tuning of the staining-process parameters is mostly based on pathologists' qualitative assessment, which incurs inter- and intra-observer variability. The lack of standardization in staining across pathology labs leads to poor reproducibility and consequently to uncertainty in diagnosis and treatment selection. In this paper, we propose a methodology to address this issue through a quantitative evaluation of the staining quality by using visual computing and machine learning techniques on immunohistochemically-stained tissue images. This enables a statistical analysis of the sensitivity of the staining quality to the process parameters and thereby provides an optimal operating range for obtaining high-quality immunostains. We evaluate the proposed methodology on HER2-stained breast cancer tissues and demonstrate its use to define guidelines to optimize and standardize immunostaining