State tagging for improved Earth and environmental data quality assurance

Environmental data allows us to monitor the constantly changing environment that we live in. It allows us to study trends and helps us to develop better models to describe processes in our environment and they, in turn, can provide information to improve management practices. To ensure that the data are reliable for analysis and interpretation, they must undergo quality assurance procedures. Such procedures generally include standard operating procedures during sampling and laboratory measurement (if applicable), as well as data validation upon entry to databases. The latter usually involves compliance (i.e., format) and conformity (i.e., value) checks that are most likely to be in the form of single parameter range tests. Such tests take no consideration of the system state at which each measurement is made, and provide the user with little contextual information on the probable cause for a measurement to be flagged out of range. We propose the use of data science techniques to tag each measurement with an identified system state. The term “state” here is defined loosely and they are identified using k-means clustering, an unsupervised machine learning method. The meaning of the states is open to specialist interpretation. Once the states are identified, state-dependent prediction intervals can be calculated for each observational variable. This approach provides the user with more contextual information to resolve out-of-range flags and derive prediction intervals for observational variables that considers the changes in system states. The users can then apply further analysis and filtering as they see fit. We illustrate our approach with two well-established long-term monitoring datasets in the UK: moth and butterfly data from the UK Environmental Change Network (ECN), and the UK CEH Cumbrian Lakes monitoring scheme. Our work contributes to the ongoing development of a better data science framework that allows researchers and other stakeholders to find and use the data they need more readily

Radiotherapy in Medulloblastoma—Evolution of Treatment, Current Concepts and Future Perspectives

Medulloblastoma is the most frequent malignant brain tumor in children. During the last decades, the therapeutic landscape has changed significantly with craniospinal irradiation as the backbone of treatment. Survival times have increased and treatments were stratified according to clinical and later molecular risk factors. In this review, current evidence regarding the efficacy and toxicity of radiotherapy in medulloblastoma is summarized and discussed mainly based on data of controlled trials. Current concepts and future perspectives based on current risk classification are outlined. With the introduction of CSI, medulloblastoma has become a curable disease. Due to combination with chemotherapy, survival rates have increased significantly, allowing for a reduction in radiation dose and a decrease of toxicity in low- and standard-risk patients. Furthermore, modern radiotherapy techniques are able to avoid side effects in a fragile patient population. However, high-risk patients remain with relevant mortality and many patients still suffer from treatment related toxicity. Treatment needs to be continually refined with regard to more efficacious combinatorial treatment in the future

New methodologies for interconnect reliability assessments of integrated circuits

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2000.Includes bibliographical references (leaves 245-251).The stringent performance and reliability demands that will accompany the development of next-generation circuits and new metallization technologies will require new and more accurate means of assessing interconnect reliability. Reliability assessments based on conventional methodologies are flawed in a number of very important ways, including the disregard of the effects of complex interconnect geometries on reliability. New models, simulations and experimental methodologies are required for the development of tools for circuit-level and process-sensitive reliability assessments. Most modeling and experimental characterization of interconnect reliability has focused on simple straight lines terminating at pads or vias. However, laid-out integrated circuits usually have many interconnects with junctions and wide-to-narrow transitions. In carrying out circuit-level reliability assessments it is important to be able to assess the reliability of these more complex shapes, generally referred to as "trees". An interconnect tree consists of continuously connected high-conductivity metal within one layer of metallization. Trees terminate at diffusion barriers at vias and contacts, and, in the general case, can have more than one terminating branch when the tree includes junctions. We have extended the understanding of "immortality" demonstrated and analyzed for straight stud-to-stud lines, to trees of arbitrary complexity. We verified the concept of immortality in interconnect trees through experiments on simple tree structures. This leads to a hierarchical approach for identifying immortal trees for specific circuit layouts and models for operation. We suggest a computationally efficient and flexible strategy for assessment of the reliability of entire integrated circuits. The proposed hierarchical reliability analysis can provide reliability assessments during the design and layout process (Reliability Computer Aided Design, RCAD). Design rules are suggested based on calculations of the electromigration-induced development of inhomogeneous steadystate mechanical stress states. Failure of interconnects by void nucleation in single-layermetallization, as well as failure by void growth in the presence of refractory metal shunt layers are taken into account. The proposed methodology identifies a large fraction of interconnect trees in a typical design as immune to electromigration-induced failure. To complete a circuit-level-reliability analysis, it is also necessary to estimate the lifetimes of the mortal trees. We have developed simulation tools that allow modeling of stress evolution and failure in arbitrarily complex trees. We have demonstrated the validity of these models and simulations through comparisons with experiments on simple trees, such as "L"- and "T"-shaped trees with different current configurations. Because analyses made using simulations are computationally intensive, simulations should be used for analysis of the least reliable trees. The reliability of the majority of the mortal trees can be assessed using a conservative default model based on nodal reliability analyses for the assessment of electromigration-limited reliability of interconnect trees. The lifetimes of the nodes are calculated by estimating the times for void nucleation, void growth to failure, and formation of extrusions. The differences between straight stud-to-stud lines and interconnect trees are studied by investigating the effects of passive and active reservoirs on electromigration. Models and simulations were validated through comparisons with experiments on simple tree structures, such as lines broken into two limbs with different currents in each limb. Models, simulations and experimental results on the reliability of interconnect trees are shown to yield mutually consistent results. Taken together, the results from this research have provided the basis for the development of the first RCAD tool capable of accurate circuit-level, processing sensitive and layout-specific reliability analyses.by Stefan P. Hau-Riege.Ph.D

Use of metformin and outcome of patients with newly diagnosed glioblastoma: Pooled analysis

Metformin has been linked to improve survival of patients with various cancers. There is little information on survival of glioblastoma patients after use of metformin. We assessed the association between metformin use and survival in a pooled analysis of patient data from 1,731 individuals from the randomized AVAglio, CENTRIC and CORE trials. We performed multivariate Cox analyses for overall survival (OS) and progression-free survival (PFS) comparing patients' use of metformin at baseline and/or during concomitant radiochemotherapy (TMZ/RT). Further exploratory analyses investigated the effect of metformin with a history of diabetes and nonfasting glucose levels in relation to OS or PFS of glioblastoma patients. Metformin alone or in any combination was not significantly associated with OS or PFS (at baseline, hazard ratio [HR] for OS = 0.87; 95% confidence interval [CI] = 0.65-1.16; HR for PFS = 0.84; 95% CI = 0.64-1.10; during TMZ/RT HR for OS = 0.97; 95% CI = 0.68-1.38; HR for PFS = 1.02; 95% CI = 0.74-1.41). We found a statistically nonsignificant association of metformin monotherapy with glioblastoma survival at baseline (HR for OS = 0.68; 95% CI = 0.42-1.10; HR for PFS = 0.57; 95% CI = 0.36-0.91), but not during the TMZ/RT period (HR for OS = 0.90; 95% CI = 0.51-1.56; HR for PFS = 1.05; 95% CI = 0.64-1.73). Diabetes mellitus or increased nonfasting glucose levels were not associated with a difference in OS or PFS in our selected study population. Metformin did not prolong survival of patients with newly diagnosed glioblastoma in our analysis. Additional studies may identify patients with specific tumor characteristics that are associated with potential benefit from treatment with metformin, possibly due to metabolic vulnerabilities

Early prediction of survival after open surgical repair of ruptured abdominal aortic aneurysms

Background: Scoring models are widely established in the intensive care unit (ICU). However, the importance in patients with ruptured abdominal aortic aneurysm (RAAA) remains unclear. Our aim was to analyze scoring systems as predictors of survival in patients undergoing open surgical repair (OSR) for RAAA. Methods: This is a retrospective study in critically ill patients in a surgical ICU at a university hospital. Sixty-eight patients with RAAA were treated between February 2005 and June 2013. Serial measurements of Sequential Organ Failure Assessment score (SOFA), Simplified Acute Physiology Score II (SAPS II) and Simplified Therapeutic Intervention Scoring System-28 (TISS-28) were evaluated with respect to in-hospital mortality. Eleven patients had to be excluded from this study because 6 underwent endovascular repair and 5 died before they could be admitted to the ICU. Results: All patients underwent OSR. The initial, highest, and mean of SOFA and SAPS II scores correlated significant with in-hospital mortality. In contrast, TISS-28 was inferior and showed a smaller area under the receiver operating curve. The cut-off point for SOFA showed the best performance in terms of sensitivity and specificity. An initial SOFA score below 9 predicted an in-hospital mortality of 16.2% (95% CI, 4.3–28.1) and a score above 9 predicted an in-hospital mortality of 73.7% (95% CI, 53.8–93.5, p 45), the in-hospital mortality rate was 85.7% (95% CI, 67.4–100, p < 0.01) versus 31.6% (95% CI, 10.7–52.5, p = 0.01) when it decreased. On multiple regression analysis, only the mean of the SOFA score showed a significant predictive capacity with regards to mortality (odds ratio 1.77; 95% CI, 1.19–2.64; p < 0.01). Conclusion: SOFA and SAPS II scores were able to predict in-hospital mortality in RAAA within 48 h after OSR. According to cut-off points, an increase or decrease in SOFA and SAPS II scores improved sensitivity and specificity

Light propagation in atomic Mott Insulators

We study radiation-matter interaction in a system of ultracold atoms trapped in an optical lattice in a Mott insulator phase. We develop a fully general quantum model, and we perform calculations for a one-dimensional geometry at normal incidence. Both two- and three-level $\Lambda$ atomic configurations are studied. The polariton dispersion and the reflectivity spectra are characterized in the different regimes, for both semi-infinite and finite-size geometries. We apply this model to propose a photon energy lifter experiment: a device which is able to shift the carrier frequency of a slowly travelling wavepacket without affecting the pulse shape nor its coherence

Adult Medulloblastoma: Updates on Current Management and Future Perspectives

Simple Summary Adult medulloblastoma is an extremely rare tumor of the central nervous system. Standard multimodal treatment, comprising maximal safe surgical resection followed by craniospinal radiotherapy and multi-agent chemotherapy, can improve the prognosis of this disease, producing, however, important acute and long-term toxicities. Herein, we review the state of the art for adult medulloblastoma diagnosis and treatment, presenting novel molecular advances and their therapeutic implications and discussing the central role of hub centers to guarantee the highest quality of care and a better overall outcome for this rare tumor. Medulloblastoma (MB) is a malignant embryonal tumor of the posterior fossa belonging to the family of primitive neuro-ectodermic tumors (PNET). MB generally occurs in pediatric age, but in 14-30% of cases, it affects the adults, mostly below the age of 40, with an incidence of 0.6 per million per year, representing about 0.4-1% of tumors of the nervous system in adults. Unlike pediatric MB, robust prospective trials are scarce for the post-puberal population, due to the low incidence of MB in adolescent and young adults. Thus, current MB treatments for older patients are largely extrapolated from the pediatric experience, but the transferability and applicability of these paradigms to adults remain an open question. Adult MB is distinct from MB in children from a molecular and clinical perspective. Here, we review the management of adult MB, reporting the recent published literature focusing on the effectiveness of upfront chemotherapy, the development of targeted therapies, and the potential role of a reduced dose of radiotherapy in treating this disease