The Global Precipitation Measurement (GPM) Mission: Overview and U.S. Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. Building upon the success of the U.S.-Japan Tropical Rainfall Measuring Mission (TRMM), the National Aeronautics and Space Administration (NASA) of the United States and the Japan Aerospace and Exploration Agency (JAXA) will deploy in 2013 a GPM "Core" satellite carrying a KulKa-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Imager (GMI) to establish a new reference standard for precipitation measurements from space. The combined active/passive sensor measurements will also be used to provide common database for precipitation retrievals from constellation sensors. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer- 2 (AMSR-2) on the GCOM-Wl satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian Megha-Tropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites, and (8) a microwave imager under planning for the Defense Weather Satellite System (DWSS)

The Devastating 2022 M6.2 Afghanistan Earthquake: Challenges, Processes, and Implications

On June 21st, a Mw6.2 earthquake struck the Afghan-Pakistan-border-region, situated within the India-Asia collision. Thousand thirty-nine deaths were reported, making the earthquake the deadliest of 2022. We investigate the event\u27s rupture processes by combining seismological and geodetic observations, aiming to understand what made it that fatal. Our Interferometric Synthetic Aperture Radar-constrained slip-model and regional moment-tensor inversion, confirmed through field observations, reveal a sinistral rupture with maximum slip of 1.8 m at 5 km depth on a N20°E striking, sub-vertical fault. We suggest that not only external factors (event-time, building stock) but fault-specific factors made the event excessively destructive. Surface rupture was favored by the rock foliation, coinciding with the fault strike. The distribution of Peak-Ground-Velocity was governed by the sub-vertical fault. Maximum slip was large compared to other events globally and might have resulted in peak-frequencies coinciding with resonance-frequencies of the local buildings and demonstrates the devastating impact of moderate-size earthquakes

Entropic effects on the Size Evolution of Cluster Structure

We show that the vibrational entropy can play a crucial role in determining the equilibrium structure of clusters by constructing structural phase diagrams showing how the structure depends upon both size and temperature. These phase diagrams are obtained for example rare gas and metal clusters.Comment: 5 pages, 3 figure

The devastating 2022 M6.2 Afghanistan earthquake: Challenges, processes, and implications

On June 21st, a Mw6.2 earthquake struck the Afghan-Pakistan-border-region, situated within the India-Asia collision. Thousand thirty-nine deaths were reported, making the earthquake the deadliest of 2022. We investigate the event's rupture processes by combining seismological and geodetic observations, aiming to understand what made it that fatal. Our Interferometric Synthetic Aperture Radar-constrained slip-model and regional moment-tensor inversion, confirmed through field observations, reveal a sinistral rupture with maximum slip of 1.8 m at 5 km depth on a N20°E striking, sub-vertical fault. We suggest that not only external factors (event-time, building stock) but fault-specific factors made the event excessively destructive. Surface rupture was favored by the rock foliation, coinciding with the fault strike. The distribution of Peak-Ground-Velocity was governed by the sub-vertical fault. Maximum slip was large compared to other events globally and might have resulted in peak-frequencies coinciding with resonance-frequencies of the local buildings and demonstrates the devastating impact of moderate-size earthquakes

Early prediction of response to radiotherapy and androgen-deprivation therapy in prostate cancer by repeated functional MRI: a preclinical study

<p>Abstract</p> <p>Background</p> <p>In modern cancer medicine, morphological magnetic resonance imaging (MRI) is routinely used in diagnostics, treatment planning and assessment of therapeutic efficacy. During the past decade, functional imaging techniques like diffusion-weighted (DW) MRI and dynamic contrast-enhanced (DCE) MRI have increasingly been included into imaging protocols, allowing extraction of intratumoral information of underlying vascular, molecular and physiological mechanisms, not available in morphological images. Separately, pre-treatment and early changes in functional parameters obtained from DWMRI and DCEMRI have shown potential in predicting therapy response. We hypothesized that the combination of several functional parameters increased the predictive power.</p> <p>Methods</p> <p>We challenged this hypothesis by using an artificial neural network (ANN) approach, exploiting nonlinear relationships between individual variables, which is particularly suitable in treatment response prediction involving complex cancer data. A clinical scenario was elicited by using 32 mice with human prostate carcinoma xenografts receiving combinations of androgen-deprivation therapy and/or radiotherapy. Pre-radiation and on days 1 and 9 following radiation three repeated DWMRI and DCEMRI acquisitions enabled derivation of the apparent diffusion coefficient (ADC) and the vascular biomarker <it>K</it>^trans, which together with tumor volumes and the established biomarker prostate-specific antigen (PSA), were used as inputs to a back propagation neural network, independently and combined, in order to explore their feasibility of predicting individual treatment response measured as 30 days post-RT tumor volumes.</p> <p>Results</p> <p>ADC, volumes and PSA as inputs to the model revealed a correlation coefficient of 0.54 (p < 0.001) between predicted and measured treatment response, while <it>K</it>^trans, volumes and PSA gave a correlation coefficient of 0.66 (p < 0.001). The combination of all parameters (ADC, <it>K</it>^trans, volumes, PSA) successfully predicted treatment response with a correlation coefficient of 0.85 (p < 0.001).</p> <p>Conclusions</p> <p>We have in a preclinical investigation showed that the combination of early changes in several functional MRI parameters provides additional information about therapy response. If such an approach could be clinically validated, it may become a tool to help identifying non-responding patients early in treatment, allowing these patients to be considered for alternative treatment strategies, and, thus, providing a contribution to the development of individualized cancer therapy.</p

PCA-based lung motion model

Organ motion induced by respiration may cause clinically significant targeting errors and greatly degrade the effectiveness of conformal radiotherapy. It is therefore crucial to be able to model respiratory motion accurately. A recently proposed lung motion model based on principal component analysis (PCA) has been shown to be promising on a few patients. However, there is still a need to understand the underlying reason why it works. In this paper, we present a much deeper and detailed analysis of the PCA-based lung motion model. We provide the theoretical justification of the effectiveness of PCA in modeling lung motion. We also prove that under certain conditions, the PCA motion model is equivalent to 5D motion model, which is based on physiology and anatomy of the lung. The modeling power of PCA model was tested on clinical data and the average 3D error was found to be below 1 mm.Comment: 4 pages, 1 figure. submitted to International Conference on the use of Computers in Radiation Therapy 201

Molecular profiling of signet ring cell colorectal cancer provides a strong rationale for genomic targeted and immune checkpoint inhibitor therapies

We would like to thank all patients whose samples were used in this study. We are also thankful to the Northern Ireland Biobank and Grampian Biorepository for providing us with tissue blocks and patient data; and Dr HG Coleman (Queen’s University Belfast) for her advice on statistical analyses. This work has been carried out with financial support from Cancer Research UK (grant: C11512/A18067), Experimental Cancer Medicine Centre Network (grant: C36697/A15590 from Cancer Research UK and the NI Health and Social Care Research and Development Division), the Sean Crummey Memorial Fund and the Tom Simms Memorial Fund. The Northern Ireland Biobank is funded by HSC Research and Development Division of the Public Health Agency in Northern Ireland and Cancer Research UK through the Belfast CRUK Centre and the Northern Ireland Experimental Cancer Medicine Centre; additional support was received from Friends of the Cancer Centre. The Northern Ireland Molecular Pathology Laboratory which is responsible for creating resources for the Northern Ireland Biobank has received funding from Cancer Research UK, Friends of the Cancer Centre and Sean Crummey Foundation.Peer reviewedPublisher PD

Expression of CDX2 and Hepatocyte Antigen in Benign and Malignant Lesions of Gallbladder and Its Correlation with Histopathologic Type and Clinical Outcome

Recent studies have shown that both CDX2 and Hepatocyte antigen (Hep) are detected in different types of cancer and associated with clinical prognosis. However, fever studies have examined gallbladder cancer specimens, and little is known about the clinicopathological significance of both CDX2 and Hep expression in gallbladder adenocarcinomas. In present study, we examined the expression frequencies of CDX2 and Hepatocyte antigen (Hep), and explored their clinicopathologic significances in gallbladder adenocarcinoma. Immunohistochemistry was used to detect and compare the frequencies of CDX2 and Hep expression in 108 samples of gallbladder adenocarcinoma, 46 peri-tumor tissues and 35 chronic cholecystitis. The expression frequencies for CDX2 and Hep were 49/108 (45.4%) and 45/108 (41.7%) in gallbladder carcinoma; 13/46 (28.3%) and 11/46 (23.9) in peri-tumor tissues; 5/35 (14.3%) and 2/35 (5.7%) in chronic cholecystitis. The positive staining of CDX2 or Hep in gallbladder adenocarcinoma was significantly higher than that in peritumoral tissues (both, P < 0.05), and chronic cholecystits (both, P < 0.01). The expression of CDX2 or Hep was negatively correlated to grade of differentiation, tumor size and lymph node metastasis (P < 0.01 or P < 0.05). Elevated expression frequency of CDX2 or Hep was associated with increased overall survival (P = 0.003 or P = 0.002). Multivariate Cox regression analysis showed that CDX2 (P = 0.014) or Hep (P = 0.026) expression was an independent prognostic predictor in gallbladder adenocarcinoma. CDX2 and Hep might function as important biological markers in the development and prognosis of gallbladder adenocarcinoma

Identifying risks for male street gang affiliation: a systematic review and narrative synthesis

Gang violence has increased in recent years. Individuals are becoming gang affiliated younger, and many have suffered historic maltreatment. Subsequent exposure to violence can result in profound consequences, including acute psychological harm. This review aims to identify predictive risk factors for male street gang affiliation. A systematic literature search was conducted utilising PsycINFO, PsycARTICLES, Medline, the Cochrane Central Register of Controlled Trials, the Cochrane Database of Systematic Reviews and the Social Policy and Practice databases (from the databases’ inception to 03/04/15). From this search, n=244 peer-reviewed papers were included in an initial scoping review, and n=102 thereafter met criteria for a systematic review; a narrative synthesis follows. Gang members have typically faced numerous historic adversities across multiple domains; individual, family, peers, school and community. Cumulative factors generated an independent risk. The meta-narrative described an overarching failure to safeguard vulnerable individuals, with the motivation for gang affiliation hypothetically arising from an attempt to have their basic needs met. Clinical and research recommendations were made to inform early intervention policy and practice

TRMM Latent Heating Retrieval and Comparisons with Field Campaigns and Large-Scale Analyses

Rainfall production is a fundamental process within the Earth's hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating (LH), is one of the principal sources of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The vertical distribution of LH has a strong influence on the atmosphere, controlling large-scale tropical circulations, exciting and modulating tropical waves, maintaining the intensities of tropical cyclones, and even providing the energetics of midlatitude cyclones and other mobile midlatitude weather systems. Moreover, the processes associated with LH result in significant non-linear changes in atmospheric radiation through the creation, dissipation and modulation of clouds and precipitation. Yanai et al. (1973) utilized the meteorological data collected from a sounding network to present a pioneering work on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Yanai's paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables used in LH algorithms. This paper examines the retrieval, validation, and application of LH estimates based on rain rate quantities acquired from the Tropical Rainfall Measuring Mission satellite (TRMM). TRMM was launched in November 1997 as a joint enterprise between the American and Japanese space agencies -- with overriding goals of providing accurate four-dimensional estimates of rainfall and LH over the global Tropics and subtropics equatorward of 35o. Other literature has acknowledged the achievement of the first goal of obtaining an accurate rainfall climatology. This paper describes the second major goal of obtaining credible LH estimates as well as their applications within TRMM's zone of coverage, the standard TRMM LH products, and areas for further improvement