A summary of common grading systems used in neurosurgical practice

BACKGROUND: Grading and scoring systems are routinely used across various specialties in medicine and surgery. They help us assess the severity of disease and often guide management as well. In addition, grading systems allow us to prognosticate and gauge outcomes. Neurosurgeons also utilize an array of scores and grading systems. This article aims to collate some of the common grading systems used in neurosurgical practice to be utilized as an easy reference especially for junior doctors and other health-care providers working in this field. METHODS: An initial literature search was carried out to look at the grading systems in use. These were then distilled down to the ones that are frequently used in clinical neurosurgical practice based on my own experience as a doctor working in a tertiary neurosurgical unit. Neuro-oncology scoring systems were excluded from the study. RESULTS: Grading systems are grouped based on the area of neurosurgical practice they fall into such as cranial, vascular, spinal, and miscellaneous. A brief description of each grading system is provided and the conditions when they can be used in a tabular format. Discussion on the advantages and disadvantages of each grading system is not included in the study. CONCLUSION: The list of grading systems in this article is not exhaustive. To the best of my knowledge, there seems to be no recent article, which summarizes them concisely. I hope that this summary will benefit the neurosurgical community and wider audience

Low-velocity Impact Analysis of Composite Repair Patches of Different Shapes

The area under crack for various structures can be effectively repaired by the use of composite materials. Low velocity impact can cause barely visible damage to the interior structure of laminated composite. These impacts can cause delamination in composite materials. In this study, a Finite Element Analysis was conducted using Abaqus/Explicit and the results of the analysis were compared to the experimental data from literature. E-glass/epoxy composite laminate was subjected to a low velocity impact test. To study the effect of patch repair, a composite patch was applied on a cracked laminate and a low velocity impact was then conducted on this model. The FEA results were validated with the experimental data and an approach to model an ideal composite patch shape was conducted. Different patch shapes like square, rectangle, circle and ellipse were designed and analyzed on the crack by keeping the surface area of the patch common. All these patches were compared and an ideal patch shape was found for the model on the basis of stress concentration on the patch. Finally a parametric study was performed considering the change in impactor speed and impactor material on the impact damage. Thus, this research work readily demonstrates the effectiveness of finite element analysis of low velocity impact

Compensatory Assistance To The Victims Of Acid Attacks

Violence with throwing acid is a heinous act of crime which falls under the offence against body. Attack of acid is mostly committed against women who are of young age. It is an intentional act, object in most cases to take revenge. Basically, it is gender based violence and gradually increasing against women. Acid that normally used in attack are easily available in market. The Criminal Law (Amendment) Act, 2013 and guidelines issued by the apex court under the Laxmi case regarding compensation and assistance in favour of acid attack survivor, so the proper treatment can be done, expense can be bearable and victim can face the challenges. Through this research paper scholar wants to highlight on caused, impact and relief provide by the state to the innocent victim and also recommended that proper check should be done on sale of acids

Analysis and synthesis of iris images

Of all the physiological traits of the human body that help in personal identification, the iris is probably the most robust and accurate. Although numerous iris recognition algorithms have been proposed, the underlying processes that define the texture of irises have not been extensively studied. In this thesis, multiple pair-wise pixel interactions have been used to describe the textural content of the iris image thereby resulting in a Markov Random Field (MRF) model for the iris image. This information is expected to be useful for the development of user-specific models for iris images, i.e. the matcher could be tuned to accommodate the characteristics of each user\u27s iris image in order to improve matching performance. We also use MRF modeling to construct synthetic irises based on iris primitive extracted from real iris images. The synthesis procedure is deterministic and avoids the sampling of a probability distribution making it computationally simple. We demonstrate that iris textures in general are significantly different from other irregular textural patterns. Clustering experiments indicate that the synthetic irises generated using the proposed technique are similar in textural content to real iris images

Study on plastic and mechanical properties of plastic stabilized returned plastic concretes containing supplementary cementitious materials

The growing concern for ready mix concrete industry is the disposal of returned unused concrete. In a plastic state, the concrete is a perishable product and the disposal of any unused concrete provides a set of challenges. However, little is known about the most effective parameters for recycling of returned plastic concrete without adversely affecting its properties. The present research has conducted laboratory trials to establish an optimal process for stabilizing returned plastic concretes using set-retarding admixture called “stabilizer”. Three types of cements, widely used in construction industry in Australia, are used in this research. The first is the ordinary Portland cement (OPC), while the rest are blended cements containing 25% class F fly ash and 65% slag as partial replacement of OPC

Interpretable Machine Learning Methods for Prediction and Analysis of Genome Regulation in 3D

With the development of chromosome conformation capture-based techniques, we now know that chromatin is packed in three-dimensional (3D) space inside the cell nucleus. Changes in the 3D chromatin architecture have already been implicated in diseases such as cancer. Thus, a better understanding of this 3D conformation is of interest to help enhance our comprehension of the complex, multipronged regulatory mechanisms of the genome. The work described in this dissertation largely focuses on development and application of interpretable machine learning methods for prediction and analysis of long-range genomic interactions output from chromatin interaction experiments. In the first part, we demonstrate that the genetic sequence information at the ge- nomic loci is predictive of the long-range interactions of a particular locus of interest (LoI). For example, the genetic sequence information at and around enhancers can help predict whether it interacts with a promoter region of interest. This is achieved by building string kernel-based support vector classifiers together with two novel, in- tuitive visualization methods. These models suggest a potential general role of short tandem repeat motifs in the 3D genome organization. But, the insights gained out of these models are still coarse-grained. To this end, we devised a machine learning method, called CoMIK for Conformal Multi-Instance Kernels, capable of providing more fine-grained insights. When comparing sequences of variable length in the su- pervised learning setting, CoMIK can not only identify the features important for classification but also locate them within the sequence. Such precise identification of important segments of the whole sequence can help in gaining de novo insights into any role played by the intervening chromatin towards long-range interactions. Although CoMIK primarily uses only genetic sequence information, it can also si- multaneously utilize other information modalities such as the numerous functional genomics data if available. The second part describes our pipeline, pHDee, for easy manipulation of large amounts of 3D genomics data. We used the pipeline for analyzing HiChIP experimen- tal data for studying the 3D architectural changes in Ewing sarcoma (EWS) which is a rare cancer affecting adolescents. In particular, HiChIP data for two experimen- tal conditions, doxycycline-treated and untreated, and for primary tumor samples is analyzed. We demonstrate that pHDee facilitates processing and easy integration of large amounts of 3D genomics data analysis together with other data-intensive bioinformatics analyses.Mit der Entwicklung von Techniken zur Bestimmung der Chromosomen-Konforma- tion wissen wir jetzt, dass Chromatin in einer dreidimensionalen (3D) Struktur in- nerhalb des Zellkerns gepackt ist. Änderungen in der 3D-Chromatin-Architektur sind bereits mit Krankheiten wie Krebs in Verbindung gebracht worden. Daher ist ein besseres Verständnis dieser 3D-Konformation von Interesse, um einen tieferen Einblick in die komplexen, vielschichtigen Regulationsmechanismen des Genoms zu ermöglichen. Die in dieser Dissertation beschriebene Arbeit konzentriert sich im Wesentlichen auf die Entwicklung und Anwendung interpretierbarer maschineller Lernmethoden zur Vorhersage und Analyse von weitreichenden genomischen Inter- aktionen aus Chromatin-Interaktionsexperimenten. Im ersten Teil zeigen wir, dass die genetische Sequenzinformation an den genomis- chen Loci prädiktiv für die weitreichenden Interaktionen eines bestimmten Locus von Interesse (LoI) ist. Zum Beispiel kann die genetische Sequenzinformation an und um Enhancer-Elemente helfen, vorherzusagen, ob diese mit einer Promotorregion von Interesse interagieren. Dies wird durch die Erstellung von String-Kernel-basierten Support Vector Klassifikationsmodellen zusammen mit zwei neuen, intuitiven Visual- isierungsmethoden erreicht. Diese Modelle deuten auf eine mögliche allgemeine Rolle von kurzen, repetitiven Sequenzmotiven (”tandem repeats”) in der dreidimensionalen Genomorganisation hin. Die Erkenntnisse aus diesen Modellen sind jedoch immer noch grobkörnig. Zu diesem Zweck haben wir die maschinelle Lernmethode CoMIK (für Conformal Multi-Instance-Kernel) entwickelt, welche feiner aufgelöste Erkennt- nisse liefern kann. Beim Vergleich von Sequenzen mit variabler Länge in überwachten Lernszenarien kann CoMIK nicht nur die für die Klassifizierung wichtigen Merkmale identifizieren, sondern sie auch innerhalb der Sequenz lokalisieren. Diese genaue Identifizierung wichtiger Abschnitte der gesamten Sequenz kann dazu beitragen, de novo Einblick in jede Rolle zu gewinnen, die das dazwischen liegende Chromatin für weitreichende Interaktionen spielt. Obwohl CoMIK hauptsächlich nur genetische Se- quenzinformationen verwendet, kann es gleichzeitig auch andere Informationsquellen nutzen, beispielsweise zahlreiche funktionellen Genomdaten sofern verfügbar. Der zweite Teil beschreibt unsere Pipeline pHDee für die einfache Bearbeitung großer Mengen von 3D-Genomdaten. Wir haben die Pipeline zur Analyse von HiChIP- Experimenten zur Untersuchung von dreidimensionalen Architekturänderungen bei der seltenen Krebsart Ewing-Sarkom (EWS) verwendet, welche Jugendliche betrifft. Insbesondere werden HiChIP-Daten für zwei experimentelle Bedingungen, Doxycyclin- behandelt und unbehandelt, und für primäre Tumorproben analysiert. Wir zeigen, dass pHDee die Verarbeitung und einfache Integration großer Mengen der 3D-Genomik- Datenanalyse zusammen mit anderen datenintensiven Bioinformatik-Analysen erle- ichtert

Mechanisms of HIV-Nef Induced Endothelial Cell Stress: Implications of HIV-Nef Protein Persistence in Aviremic HIV Patients

Indiana University-Purdue University Indianapolis (IUPUI)HIV-associated cardio-pulmonary vascular pathologies such as coronary artery disease, pulmonary hypertension and emphysema remain a major issue in the HIVinfected population even in the era of antiretroviral therapy (ART). The continued production of HIV encoded pro-apoptotic protein, such as Nef in latently HIV-infected cells is a possible mechanism for vascular dysfunction underlying these diseases. HIVNef persists in two compartments in these patients: (i) extracellular vesicles (EV) of plasma and bronchoalveolar lavage (BAL) fluid and (ii) PBMC and BAL derived cells. Here I demonstrate that the presence of HIV-Nef protein in cells and EV is capable of stressing endothelial cells by inducing ROS production leading to endothelial cell apoptosis. HIV-Nef protein hijacks host cell signaling by interacting with small GTP binding protein Rac1 which activates PAK2 to promote the release of pro-apoptotic cargo containing EV and surface expression of pro-apoptotic protein Endothelial Monocyte Activating Polypeptide II (EMAPII). Using this mechanism, Nef protein robustly induces apoptosis in Human Coronary Artery Endothelial Cells and Human Lung microvascular endothelial cells. Endothelial specific expression of HIV-Nef protein in transgenic mice was sufficient to induce vascular pathologies as evidenced by impaired endothelium mediated vasodilation of the aorta and vascular remodeling and emphysema like alveolar rarefaction in the lung. Furthermore, EV isolated from HIV patients on ART was capable of inducing endothelial apoptosis in a Nef dependent fashion. Of therapeutic interest, EMAPII neutralizing antibodies to block EMAPII mediated apoptosis and statin treatment to ameliorate Nef induced Rac1 signaling was capable of blocking Nef induced endothelial stress in both in vivo and in vitro. In conclusion, HIV-Nef protein uses a Rac1-Pak2 signaling axis to promote its dissemination in EV, which in turn induces endothelial cell stress after its uptake

Testing The Rambo Effect Theory: A Comparative Analysis Of Economic Integration In MERCOSUR And SADC

This paper attempts to conduct a comparative analysis between the integration processes of two regional blocs of the Global South, one in Latin America, namely the 1991-founded Common Market of South America (MERCOSUR) and the other in the southern part of Africa, namely the 1992-founded Southern African Development Community (SADC). In particular, this paper will seek to compare the economic integration process between MERCOSUR and SADC using insights of international political economy and regional cooperation. In doing so, the paper will test the \u27Rambo effect\u27 theory which claims that the dominant power of Brazil and South Africa has led to the failure of MERCOSUR and SADC respectively

EVALUATING THE EFFECTIVENESS OF MOBILE APPLICATIONS IN ENHANCING LEARNING AND DEVELOPMENT

This paper aims to examine how mobile applications relate to learning and development. It will determine whether these two factors are properly intertwined and whether these two factors are fully justified in being related. As a result of examining the literature, and reviewing the results of our survey, we have developed a framework for research. This framework will provide evidence that mobile technologies have a positive impact on classroom performance both directly and indirectly. These technologies foster the learning and development process at all levels, which ultimately enhances the individual's competency by equipping him or her with a more comprehensive skill set. A total of one hundred and eighty interviews were conducted with educators during the research process. These interviews were conducted to develop the findings presented in this article on the impact of mobile applications in the classroom as a result of the research process. There is a growing body of research that suggests the use of mobile apps can be an effective tool for fostering creativity, learning, and development in a variety of settings, both formal and informal. They have been shown to be beneficial in a number of ways when it comes to promoting learning and development. When compared to traditional methods of teaching, mobile apps have shown to be more effective in promoting holistic learning and increasing learning speed than traditional methods of teaching, especially when it comes to promoting holistic learning and increasing learning speed. With the introduction of mobile applications to the education sector, many novel learning strategies have been developed within this sector as a result of the introduction of mobile apps. The use of mobile devices in the classroom has resulted in a number of changes in this respect. The use of mobile apps can provide students with a variety of games that are designed to encourage them to engage in a positive thought process as well as allow them to gain a deeper understanding of what they are learning as they interact with the games and become engaged with them on a more personal level. "Mobile learning" refers to the use of mobile devices and apps in order to facilitate the learning process in an attempt to facilitate the learning process mobile devices and apps in order to facilitate the learning process. The term may also refer to the way in which mobile technology can be used to support a continuous learning environment