Deterimination [sic] of focal depths of earthquakes in the mid-oceanic ridges from amplitude spectra of surface waves.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth and Planetary Sciences, 1969.Bibliography: leaves 140-144.Ph.D

Body Mass Index–Mortality Relationship in Severe Hypoglycemic Patients With Type 2 Diabetes

AbstractBackgroundHypoglycemia is associated with a higher risk of death. This study analyzed various body mass index (BMI) categories and mortalities of severe hypoglycemic patients with type 2 diabetes mellitus (DM) in a hospital emergency department.MethodsThe study included 566 adults with type 2 diabetes who were admitted to 1 medical center in Taiwan between 2008 and 2009 with a diagnosis of severe hypoglycemia. Mortality data, demographics, clinical characteristics and the Charlson’s Comorbidity Index were obtained from the electronic medical records. Patients were stratified into 4 study groups as determined by the National institute of Health (NiH) and World Health organization classification for BMi, and the demographics were compared using the analysis of variance and χ2 test. Kaplan-Meier’s analysis and the Cox proportional-hazards regression model were used for mortality, and adjusted hazard ratios were adjusted for each BMi category among participants.ResultsAfter controlling for other possible confounding variables, BMI <18.5 kg/m2 was independently associated with low survival rates in the Cox regression analysis of the entire cohort of type 2 DM patients who encountered a hypoglycemic event. Compared to patients with normal BMI, the mortality risk was higher (adjusted hazard ratios = 4.9; 95% confidence interval [CI] = 2.4-9.9) in underweight patients. Infection-related causes of death were observed in 101 cases (69.2%) and were the leading cause of death.ConclusionsAn independent association was observed between BMI less than 18.5 kg/m2 and mortality among type 2 DM patient with severe hypoglycemic episode. Deaths were predominantly infection related

Hazard-based risk grouping effectively stratifying breast cancer patients in post-irradiation long-term heart diseases: a population-based cohort study

BackgroundEven though advanced radiotherapy techniques provide a better protective effect on surrounding normal tissues, the late sequelae from radiation exposure to the heart are still considerable in breast cancer patients. The present population-based study explored the role of cox-regression-based hazard risk grouping and intended to stratify patients with post-irradiation long-term heart diseases.Materials and methodsThe present study investigated the Taiwan National Health Insurance (TNHI) database. From 2000 to 2017, we identified 158,798 breast cancer patients. Using a propensity score match of 1:1, we included 21,123 patients in each left and right breast irradiation cohort. Heart diseases, including heart failure (HF), ischemic heart disease (IHD), and other heart diseases (OHD), and anticancer agents, including epirubicin, doxorubicin, and trastuzumab, were included for analysis.ResultsPatients received left breast irradiation demonstrated increased risks on IHD (aHR, 1.16; 95% CI, 1.06–1.26; p &lt; 0.01) and OHD (aHR, 1.08; 95% CI, 1.01–1.15; p &lt; 0.05), but not HF (aHR, 1.11; 95% CI, 0.96–1.28; p = 0.14), when compared with patients received right breast irradiation. In patients who received left breast irradiation dose of &gt;6,040 cGy, subsequent epirubicin might have a trend to increase the risk of heart failure (aHR, 1.53; 95% CI, 0.98–2.39; p = 0.058), while doxorubicin (aHR, 0.59; 95% CI, 0.26–1.32; p = 0.19) and trastuzumab (aHR, 0.93; 95% CI, 0.33–2.62; p = 0.89) did not. Older age was the highest independent risk factor for post-irradiation long-term heart diseases.ConclusionGenerally, systemic anticancer agents are safe in conjunction with radiotherapy for managing post-operative breast cancer patients. Hazard-based risk grouping may help stratify breast cancer patients associated with post-irradiation long-term heart diseases. Notably, radiotherapy should be performed cautiously for elderly left breast cancer patients who received epirubicin. Limited irradiation dose to the heart should be critically considered. Regular monitoring of potential signs of heart failure may be conducted

A non-linear structure-preserving matrix method for the computation of the coefficients of an approximate greatest common divisor of two Bernstein polynomials

This paper describes a non-linear structure-preserving ma trix method for the com- putation of the coefficients of an approximate greatest commo n divisor (AGCD) of degree t of two Bernstein polynomials f ( y ) and g ( y ). This method is applied to a modified form S t ( f, g ) Q t of the t th subresultant matrix S t ( f, g ) of the Sylvester resultant matrix S ( f, g ) of f ( y ) and g ( y ), where Q t is a diagonal matrix of com- binatorial terms. This modified subresultant matrix has sig nificant computational advantages with respect to the standard subresultant matri x S t ( f, g ), and it yields better results for AGCD computations. It is shown that f ( y ) and g ( y ) must be pro- cessed by three operations before S t ( f, g ) Q t is formed, and the consequence of these operations is the introduction of two parameters, α and θ , such that the entries of S t ( f, g ) Q t are non-linear functions of α, θ and the coefficients of f ( y ) and g ( y ). The values of α and θ are optimised, and it is shown that these optimal values allo w an AGCD that has a small error, and a structured low rank approxi mation of S ( f, g ), to be computed

Oncogenic deubiquitination controls tyrosine kinase signaling and therapy response in acute lymphoblastic leukemia

Dysregulation of kinase signaling pathways favors tumor cell survival and therapy resistance in cancer. Here, we reveal a posttranslational regulation of kinase signaling and nuclear receptor activity via deubiquitination in T cell acute lymphoblastic leukemia (T-ALL). We observed that the ubiquitin-specific protease 11 (USP11) is highly expressed and associates with poor prognosis in T-ALL. USP11 ablation inhibits leukemia progression in vivo, sparing normal hematopoiesis. USP11 forms a complex with USP7 to deubiquitinate the oncogenic lymphocyte cell-specific protein-tyrosine kinase (LCK) and enhance its activity. Impairment of LCK activity leads to increased glucocorticoid receptor (GR) expression and glucocorticoids sensitivity. Genetic knockout of USP7 improved the antileukemic efficacy of glucocorticoids in vivo. The transcriptional activation of GR target genes is orchestrated by the deubiquitinase activity and mediated via an increase in enhancer-promoter interaction intensity. Our data unveil how dysregulated deubiquitination controls leukemia survival and drug resistance, suggesting previously unidentified therapeutic combinations toward targeting leukemia

An approach to the diagnosis of lumbar disc herniation using deep learning models

Background: In magnetic resonance imaging (MRI), lumbar disc herniation (LDH) detection is challenging due to the various shapes, sizes, angles, and regions associated with bulges, protrusions, extrusions, and sequestrations. Lumbar abnormalities in MRI can be detected automatically by using deep learning methods. As deep learning models gain recognition, they may assist in diagnosing LDH with MRI images and provide initial interpretation in clinical settings. YOU ONLY LOOK ONCE (YOLO) model series are often used to train deep learning algorithms for real-time biomedical image detection and prediction. This study aims to confirm which YOLO models (YOLOv5, YOLOv6, and YOLOv7) perform well in detecting LDH in different regions of the lumbar intervertebral disc.Materials and methods: The methodology involves several steps, including converting DICOM images to JPEG, reviewing and selecting MRI slices for labeling and augmentation using ROBOFLOW, and constructing YOLOv5x, YOLOv6, and YOLOv7 models based on the dataset. The training dataset was combined with the radiologist’s labeling and annotation, and then the deep learning models were trained using the training/validation dataset.Results: Our result showed that the 550-dataset with augmentation (AUG) or without augmentation (non-AUG) in YOLOv5x generates satisfactory training performance in LDH detection. The AUG dataset overall performance provides slightly higher accuracy than the non-AUG. YOLOv5x showed the highest performance with 89.30% mAP compared to YOLOv6, and YOLOv7. Also, YOLOv5x in non-AUG dataset showed the balance LDH region detections in L2-L3, L3-L4, L4-L5, and L5-S1 with above 90%. And this illustrates the competitiveness of using non-AUG dataset to detect LDH.Conclusion: Using YOLOv5x and the 550 augmented dataset, LDH can be detected with promising both in non-AUG and AUG dataset. By utilizing the most appropriate YOLO model, clinicians have a greater chance of diagnosing LDH early and preventing adverse effects for their patients

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure