Algorithms

A study of the performance of five commercial radiotherapy treatment planning systems (TPSs) for common treatment sites regarding their ability to model heterogeneities and scattered photons has been performed. The comparison was based on CT information for prostate, head and neck, breast and lung cancer cases. The TPSs were installed locally at different institutions and commissioned for clinical use based on local procedures. For the evaluation, beam qualities as identical as possible were used: low energy (6 MV) and high energy (15 or 18 MV) x-rays. All relevant anatomical structures were outlined and simple treatment plans were set up. Images, structures and plans were exported, anonymized and distributed to the participating institutions using the DICOM protocol. The plans were then re-calculated locally and exported back for evaluation. The TPSs cover dose calculation techniques from correction-based equivalent path length algorithms to modelbased algorithms. These were divided into two groups based on how changes in electron transport are accounted for ((a) not considered and (b) considered). Increasing the complexity from the relatively homogeneous pelvic region to the very inhomogeneous lung region resulted in less accurate dose distributions. Improvements in the calculated dose have been shown when models consider volume scatter and changes in electron transport, especially when the extension of the irradiated volume was limited and when low densities were present in or adjacent to the fields. A Monte Carlo calculated algorithm input data set and a benchmark set for a virtual linear accelerator have been produced which have facilitated the analysis and interpretation of the results. The more sophisticated

We study theI-Vcharacteristic of mesoscopic systems or quantum dot (QD) attached to a pair of superconducting leads. Interaction effects in the QD are considered through the charging energy of the QD; that is, the treatment of current transport under a voltage bias is performed within a coupled Poisson nonequilibrium Green function (PNEGF) formalism. We derive the expression for the current in full generality but consider only the regime where transport occurs only via a single particle current. We show for this case and for various charging energies valuesU0and associated capacitances of the QD the effect on theI-Vcharacteristic. Also the influence of the coupling constants on theI-Vcharacteristic is investigated. Our approach puts forward a novel interpretation of experiments in the strong Coulomb regime.

The applicability of a two-parameter Fickian diffusion model for predicting the skin steady-state permeability based on measurements of the transient transport of permeants across the skin was tested. Using five model permeants possessing different physicochemical properties and pig skin as the model membrane, the skin permeabilities predicted by the two-parameter Fickian diffusion model were compared with the measured skin permeabilities. Results show that the transient skin permeation profiles of the hydrophobic permeants, estradiol, testosterone, and dolichol, across splitthickness pig skin can be modeled adequately by the two-parameter Fickian diffusion model (with constant parameter values), and therefore, that this model can be utilized to shorten the experimental time required to determine the skin permeabilities of these compounds. However, the skin permeabilities of the highly hydrophilic permeants, mannitol and sucrose, predicted by the two-parameter Fickian diffusion model (with constant parameter values) were significantly lower than the experimentally determined values, indicating that the dominant skin pathway of polar permeants within the excised pig skin undergoes significant structural changes during the in vitro diffusion cell studies. Although the skin permeability values determined experimentally using the traditional steady-state method normally correspond to a highly hydrated skin sample, the two-parameter Fickian diffusion model enables an estimation of the skin permeability of the skin membrane at its less-hydrated state (a condition more representative of in vivo and clinical situations). Using the two-parameter Fickian diffusion model and a recently developed skin porous-pathway theory, the effects of skin hydration on the skin porous pathway within the excised pig skin were characterized. Specifically, we found that hydration leads to induction of new pores/reduction of the tortuosity of existing pores within the excised pig skin during the 48 h diffusion cell studies conducted, while the skin average pore radii remain relatively constant ($26 Å ) for up to 48 h. ß

People migrate to improve their well-being, whether through an expansion of economic and social opportunities or a reduction in persecution. Yet a large literature suggests that migration can be a very stressful process, with potentially negative impacts on mental health reducing the net benefits of migration. However, to truly understand the effect of migration on mental health one must compare the mental health of migrants to what their mental health would have been had they stayed in their home country. The existing literature is not able to do this and typically settles for comparing the mental health of migrants to that of natives in the destination country,which takes no account of any pre-existing differences between these groups. This paper overcomes the selection problems affecting previous studies of the effect of migration on mental health by examining a migrant lottery program. New Zealand allows a quota of Tongans to immigrate each year with a lottery used to choose amo...

In the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-rays but also for studies which explore the functional status of the body using positron-emitting radioisotopes. This report reviews the historical and physical basis of medical imaging techniques using positron-emitting radioisotopes. Mathematical methods which enable three-dimensional distributions of radioisotopes to be reconstructed from projection data (sinograms) acquired by detectors suitably positioned around the patient are discussed. The extension of conventional twodimensional tomographic reconstruction algorithms to fully three-dimensional reconstruction is described in detail. © Parallel projection Eqn. (3.1), <\> = 0 p(s, 0 = 0) © Filtering Eqn. (3.2) Two disks equal concentrations À © Backprojection Eqn. (3.5)

We develop an unsupervised approach to condition monitoring of cellular networks using competitive neural algorithms. Training is carried out with state vectors representing the normal functioning of a simulated CDMA2000 network. Once training is completed, global and local normality profiles (NPs) are built from the distribution of quantization errors of the training state vectors and their components, respectively. The global NP is used to evaluate the overall condition of the cellular system. If abnormal behavior is detected, local NPs are used in a component-wise fashion to find abnormal state variables. Anomaly detection tests are performed via percentile-based confidence intervals computed over the global and local NPs. We compared the performance of four competitive algorithms (WTA, FSCL, SOM and Neural-Gas) and the results suggest that the joint use of global and local NPs is more efficient and more robust than current single-threshold methods. and Wideband CDMA, respectively, which are 3G technologies capable of providing speeds of up to 2Mbits/sec. 2 CDMA2000, also called 1xRTT (single carrier radio transmission technology), is a 3G wireless technology based on the CDMA platform which has the capability of providing speeds of up to 144 Kbps.

1 ESGE recommends cold snare polypectomy (CSP) as the preferred technique for removal of diminutive polyps (size ≤ 5 mm). This technique has high rates of complete resection, adequate tissue sampling for histology, and low complication rates. (High quality evidence, strong recommendation.) 2 ESGE suggests CSP for sessile polyps 6 - 9 mm in size because of its superior safety profile, although evidence comparing efficacy with hot snare polypectomy (HSP) is lacking. (Moderate quality evidence, weak recommendation.) 3 ESGE suggests HSP (with or without submucosal injection) for removal of sessile polyps 10 - 19 mm in size. In most cases deep thermal injury is a potential risk and thus submucosal injection prior to HSP should be considered. (Low quality evidence, strong recommendation.) 4 ESGE recommends HSP for pedunculated polyps. To prevent bleeding in pedunculated colorectal polyps with head ≥ 20 mm or a stalk ≥ 10 mm in diameter, ESGE recommends pretreatment of the stalk with injec...

A novel automatic 3D+time left ventricle (LV) segmentation framework is proposed for cardiac magnetic resonance (CMR) datasets. The proposed framework consists of three conceptual blocks to delineate both endo and epicardial contours throughout the cardiac cycle: 1) an automatic 2D midventricular initialization and segmentation; 2) an automatic stack initialization followed by a 3D segmentation at the end-diastolic phase; and 3) a tracking procedure. Hereto, we propose to adapt the recent B-spline Explicit Active Surfaces (BEAS) framework to the properties of CMR images by integrating dedicated energy terms. Moreover, we extend the coupled BEAS formalism towards its application in 3D MR data by adapting it to a cylindrical space suited to deal with the topology of the image data. Furthermore, a fast stack initialization method is presented for efficient initialization and to enforce consistent cylindrical topology. Finally, we make use of an anatomically constrained optical flow method for temporal tracking of the LV surface.

Ankle Foot Orthoses (AFOs) to promote walking ability are a common treatment in patients with neurological or muscular diseases. However, guidelines on the prescription of AFOs are currently based on a low level of evidence regarding their efficacy. Recent studies aiming to demonstrate the efficacy of wearing an AFO in respect to walking ability are not always conclusive. In this paper it is argued to recognize two levels of evidence related to the ICF levels. Activity level evidence expresses the gain in walking ability for the patient, while mechanical evidence expresses the correct functioning of the AFO. Used in combination for the purpose of evaluating the efficacy of orthotic treatment, a conjunct improvement at both levels reinforces the treatment algorithm that is used. Conversely, conflicting outcomes will challenge current treatment algorithms and the supposed working mechanism of the AFO. A treatment algorithm must use relevant information as an input, derived from measur...

This paper presents a spike-based model which employs neurons with functionally distinct dendritic compartments for classifying high dimensional binary patterns. The synaptic inputs arriving on each dendritic subunit are nonlinearly processed before being linearly integrated at the soma, giving the neuron a capacity to perform a large number of input-output mappings. The model utilizes sparse synaptic connectivity; where each synapse takes a binary value. The optimal connection pattern of a neuron is learned by using a simple hardware-friendly, margin enhancing learning algorithm inspired by the mechanism of structural plasticity in biological neurons. The learning algorithm groups correlated synaptic inputs on the same dendritic branch. Since the learning results in modified connection patterns, it can be incorporated into current event-based neuromorphic systems with little overhead. This work also presents a branch-specific spike-based version of this structural plasticity rule. The proposed model is evaluated on benchmark binary classification problems and its performance is compared against that achieved using Support Vector Machine (SVM) and Extreme Learning Machine (ELM) techniques. Our proposed method attains comparable performance while utilizing 10 to 50% less computational resources than the other reported techniques.

This is a literature review about large granular lymphocyte leukemia (LGLL), a rare and misdiagnosed oncohematological disease, characterized by a clonal expansion of T-cells (T-LGLL) or NK-cells (NK-LGLL) in the bone marrow and/or peripheral blood. The clinical features of LGLL include cytopenias (anemia, neutropenia and thrombocytopenia), lymphocytosis (usually discrete), lymphadenopathy, hepatomegaly, splenomegaly, immune abnormalities and constitutional symptoms (fever, night sweats and weight loss). The diagnosis is based on the confirmation of the clonality of T-cells or NK-cells (polymerase chain reaction and Southern blot are the two methods most commonly used) and typical findings of the immunophenotypic analysis of peripheral blood lymphocytes (flow cytometry analyses for specific surface antigens). In contrast to the chronic and indolent course of T-LGLL, NK-LGLL has an acute presentation and poor clinical outcome. There are different current treatment options, depending on clinical presentation.

In the past decades, it has become increasingly apparent that in addition to therapeutic effect, drugs need to exhibit favourable absorption, distribution, metabolism and excretion (ADME) characteristics to produce a desirable response in vivo. As the recent progress in drug discovery technology enables rapid synthesis of vast numbers of potential drug candidates, robust methods are required for the effective screening of compounds synthesized within such programs, so that compounds with poor pharmacokinetic properties can be rejected at an early stage of drug development. Furthermore, a viable in silico method would save resources by enabling virtual screening of drug candidates already prior to synthesis. This review gives a general overview of the approaches aimed at predicting biological permeation, one of the cornerstones behind the ADME behaviour of drugs. The most important experimental and computational models are reviewed. Physicochemical factors underlying the permeation process are discussed.

Docking scoring functions are notoriously weak predictors of binding affinity. They typically assign a common set of weights to the individual energy terms that contribute to the overall energy score, however, these weights should be gene family-dependent. In addition, they incorrectly assume that individual interactions contribute towards the total binding affinity in an additive manner. In reality, noncovalent interactions often depend on one another in a nonlinear manner. In this paper we show how the use of support vector machines (SVMs), trained by associating sets of individual energy terms retrieved from molecular docking with the known binding affinity of each compound from high-throughput screening experiments, can be used to improve the correlation between known binding affinities and those predicted by the docking program eHiTS. We construct two prediction models; a regression model trained using IC 50 values from BindingDB, and a classification model trained using active and decoy compounds from the Directory of Useful Decoys (DUD). Moreover, to address the issue of overrepresentation of negative data in highthroughput screening data sets, we have designed a multiple-planar SVM training procedure for the classification model. The increased performance that both SVMs give when compared with the original eHiTS scoring function highlights the potential for using nonlinear methods when deriving overall energy scores from their individual components. We apply the above methodology to train a new scoring function for direct inhibitors of M.tuberculosis (M.tb) InhA. By combining ligand binding site comparison with the new scoring function, we propose that phosphodiesterase inhibitors can potentially be repurposed to target M.tb InhA. Our methodology may be applied to other gene families for which target structures and activity data are available, as demonstrated in the work presented here.

Waikato Environment for Knowledge Analysis (WEKA) is a comprehensive suite of Java class libraries that implement many state-of-the-art machine learning/data mining algorithms. Non-programmers interact with the software via a user interface component called the Knowledge Explorer.

This study was performed with the aim of determining the diagnostic profile of newborns with hypotonia and of analyzing the usefulness of different procedures in the diagnostic process. One hundred thirty-eight hypotonic newborns were identified through the search of hospital records in a 10-year period: 121 (88%) had central hypotonia and 13 (9%) had peripheral hypotonia, whereas 4 (3%) remained unclassified. Analysis of the contribution of clinical data and results of investigations led to the construction of an algorithm, by which all cases in the group were diagnosed. Step 1, which included clinical data and results of examinations, solved 50% of all diagnosed cases. Neuroimaging techniques made up step 2 and contributed to the diagnosis in 13%. Step 3 was accomplished by a search through Oxford Medical Databases, which yielded the final diagnosis in 9%, whereas karyotyping and fluorescent in situ hybridization for Prader-Willi syndrome comprised step 4 and contributed to the di...

Techniques of molecular biology have improved diagnostic sensitivity, accuracy and validity in forensic medicine very much, especially in the field of identification (paternity testing, stain analysis). Since more than 10 years these techniques -meanwhile well established in clinical disciplines -are used also for other applications in forensic medicine: determination of cause and manner of death, tissue identification by mRNA and microRNA, examination of gene expression levels (survival time, time since death, cause of death), toxicogenetics.

DLP is a data security technology that detects and prevents data breach incidents  by monitoring data in-use, in-motion and at-rest.  It has been widely applied for regulatory compliances, data privacy  and intellectual property protection. This talk will introduce basic concepts and security models to describe DLP systems with high level architecture.  DLP is an interesting discipline with content inspection techniques supported by sophisticated algorithms.  Special investigation will be taken for  a few algorithms:  document fingerprinting,  data record fingerprinting, scalable M-pattern string match and etc..

In Industrial environments, huge amount of data is being generated which in turn collected indatabase anddata warehouses from all involved areas such as planning, process design, materials, assembly, production, quality, process control, scheduling, fault detection,shutdown, customer relation management, and so on. Data Mining has become auseful tool for knowledge acquisition for industrial process of Iron and steel making. Due to the rapid growth in Data Mining, various industries started using data mining technology to search the hidden patterns, which might further be used to the system with the new knowledge which might design new models to enhance the production quality, productivity optimum cost and maintenance etc. The continuous improvement of all steel production process regarding the avoidance of quality deficiencies and the related improvement of production yield is an essential task of steel producer. Therefore, zero defect strategy is popular today and to maintain it several quality assurance techniques areused. The present report explains the methods of data mining and describes its application in the industrial environment and especially, in the steel industry.

Nowadays the main usage of the word "heuristic" is mostly the adjective in the sense of "guiding discovery" or "improving problem solving." The greek mathematicians  used two ways to find a solution: They began by assuming the problem solved and worked from there or they started from the admitted body of mathematical knowledge and worked towards the desired result (analysis or synthesis).

There is also a shorter literature extract of this paper in academia.edu.

Introduction for second edition /  Preface

When in 1989 an anonymous reviewer commented on my short paper that “this classification should be extended to description of distributed systems,” (Yet another approach to classification of redundancy, CIM IMEKO Symp.1990, Helsinki, pp. 117-124) I was really excited, because people in the research community were thinking much deeper and wider than myself (- I had just defended my PhD).

Further, fault tolerance was migrating to dependability (Jean Claude Laprie was an indisputable authority and expert in this domain, see more:  www.springer.com/gb/book/9783709191729, which later emerged as the concept of resilience.

In principle, all these new properties had a concrete reasoning and meaning behind them: when something erroneous has happens, any system of our design should be able to cope with the problem. Options vary, as well as circumstances and area of application, thus:

- If it stops the error propagating and freezes in a safe state, it is fail-stop, or fail-safe;
- If it can cope with permanent faults inside the system, it is a fault tolerant system;
- When it continues with reduced functionality, it is graceful degradation;
- If it is designed with attention having been paid to reliability, availability and maintenance or serviceability, it is
      dependable system;
- If it capable to of tolerating obstacles caused by internal and external factors and can spring back, recover and continue, then a system can be considered as resilient.

There are two major ways to achieve any of the properties mentioned above: at  system level, or at local level (technological). Obviously, any reasonable combination of both levels is also welcome. In this book we do not want to repeat our papers and books
(https://www.springer.com/gb/book/9783319150680, https://www.springer.com/gb/book/9783319468129)
but to incorporate into the second edition any significant progress that has emerged.
Speaking about ICT systems, especially safety-critical and real-time ones, we might think about the implementation of resilience from the system level down through to hardware and systems software. In addition, we need to consider that each of the parts will both interact with and support each other.

NFRs (Non-Functional Requirements) of each part of the system were considered, such as:

- Performance;
- Reliability;
- Efficiency (mostly energy efficient).

Therefore, the systems that we design should be PRE-smart and provide these properties throughout the life cycle. 

Neither of  our books to date  - have appeared as complete. These books have been used in China, Switzerland, Russia and USA, (mostly Masters and PhD students) and we have received substantial feedback, such as:

- While reliability of hardware and availability at the system level are explained and fine, there are no sections, or chapters about performance, especially where parallel and distributed systems are concerned;
- How to apply (as mentioned in the above review) the classification and properties of resilience for and within distributed systems;
- How real-time and safety-critical applications should be treated considering the system resilience: rules for system and for packages - have they changed?

It was especially satisfying as  we have  discovered that these segments are being updated by researchers around the globe, providing excellent contributions to the content.

Thus, our book became and evolving system in itself, aggregating our further efforts with the efforts and results of our colleagues from China, Switzerland, UK and Russia. Our book has therefore become itself resilient, benefiting from the contributions from the following:

Performance chapter (including element level performance and parallel design was prepared and included using materials and having contributions from:

-  Professor Hao Kai, Shantou University, China;
- Simon Monkman, IT-ACS Ltd researcher.

System software chapters were part of substantial efforts from:

- Professor Eugeny Zuev and his team in Technopolis, Kazan, Russia.

In turn, requested in 1989 consideration of system level of resilience for distributed systems were developed as two chapters: system level and algorithmic implementation prepared by me and Stephen Farrell. In these chapters we have introduced a concept of desperation ( for transactions within distributed systems) and show that our existing and new results, even patented: https://www.ipo.gov.uk/p-ipsum/Case/PublicationNumber/GB2448351

can be extremely useful making the whole network really resilient and achieving by far better service for applications, especially when critical level of their use was assumed.

I Schagaev

The revised general solubility equation (GSE) is used along with four different methods including Huuskonen's artificial neural network (ANN) and three multiple linear regression (MLR) methods to estimate the aqueous solubility of a test set of the 21 pharmaceutically and environmentally interesting compounds. For the selected test sets, it is clear that the GSE and ANN predictions are more accurate than MLR methods. The GSE has the advantages of being simple and thermodynamically sound. The only two inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (K ow ). No fitted parameters and no training data are used in the GSE, whereas other methods utilize a large number of parameters and require a training set. The GSE is also applied to a test set of 413 organic nonelectrolytes that were studied by Huuskonen. Although the GSE uses only two parameters and no training set, its average absolute errors is only 0.1 log units larger than that of the ANN, which requires many parameters and a large training set. The average absolute error AAE is 0.54 log units using the GSE and 0.43 log units using Huuskonen's ANN modeling. This study provides evidence for the GSE being a convenient and reliable method to predict aqueous solubilities of organic compounds.

Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin’s innovative computer application to the humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: 1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science; and 2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors’ status, were determining factors.

Ultrasound of the shoulder is a powerful and accurate method for the examination of the rotator cuff, biceps mechanism and the synovium. This article describes the anatomy, standard examination technique, indications, pitfalls and potential errors. It lists suggested imaging algorithms for a range of shoulder pathology.

There is broad interest in predicting the clinical course of mental disorders from early, multimodal clinical and biological information. Current computational models, however, constitute a significant barrier to realizing this goal. The early identification of trauma survivors at risk of post-traumatic stress disorder (PTSD) is plausible given the disorder's salient onset and the abundance of putative biological and clinical risk indicators. This work evaluates the ability of Machine Learning (ML) forecasting approaches to identify and integrate a panel of unique predictive characteristics and determine their accuracy in forecasting non-remitting PTSD from information collected within10 days of a traumatic event. Data on event characteristics, emergency department observations, and early symptoms were collected in 957 trauma survivors, followed for fifteen months. An ML feature selection algorithm identified a set of predictors that rendered all others redundant. Support Vector Machines (SVMs) as well as other ML classification algorithms were used to evaluate the forecasting accuracy of i) ML selected features, ii) all available features without selection, and iii) Acute Stress Disorder (ASD) symptoms alone. SVM also compared the prediction of a) PTSD diagnostic status at 15 months to b) posterior probability of membership in an empirically derived non-remitting PTSD symptom trajectory. Results are expressed as mean Area Under Receiver Operating Characteristics Curve (AUC). The feature selection algorithm identified 16 predictors, present in !95% cross-validation trials. The accuracy of predicting non-remitting PTSD from that set (AUC ¼ .77) did not differ from predicting from all available information (AUC ¼ .78). Predicting from ASD symptoms was not better then chance (AUC ¼ .60). The prediction of PTSD status was less accurate than that of membership in a non-remitting trajectory (AUC ¼ .71). ML methods may fill a critical gap in forecasting PTSD. The ability to identify and integrate unique risk indicators makes this a promising approach for developing algorithms that infer probabilistic risk of chronic posttraumatic stress psychopathology based on complex sources of biological, psychological, and social information.

Journalism and the Press have always been deeply influenced by technological changes, and so they are in the digital world: from the competition of new media and the challenges of the Web 2.0 to the creation of a new way to produce news, i.e. automated journalism. Between the different notions of the use of AI in the Press field (automated journalism, robot journalism, News-Writing Bots, algorithmic journalism) in this paper the wording "automated journalism" is preferred as long as it seems to describe in a better way the practice of this type of journalism and it seems more used by the scholars who have studied this topic. Automated journalism is the use of AI, i.e. software or algorithms, in order to automatically generate news stories without any contribution of human beings, apart from that of programmers who (eventually) have developed the algorithm.

With the institutionalization of algorithms as content creators, professional journalism is facing transformation and novel ethical challenges. This article focuses on the concept of Algorithmic Journalism on the basis of natural language generation and provides a framework to identify and discuss ethical issues. The analysis builds on the moral theories of deontology, utilitarianism, virtue ethics, and contractualism and remaps the ethical discussion for Algorithmic Journalism at the intersection of digital media ethics and cyberethics. In order to capture the whole range of potential shifts and challenges in journalism ethics the article combines the ethical multi-layer system of responsibility by Pürer with the classification of journalism by Weischenberg, Malik, and Scholl on an organizational, professional/individual, and social/audience sphere. This analytical framework is then complemented with attributes derived from the technical potential of Algorithmic Journalism. As a result, the analysis uncovers new ethical challenges and shifts of responsibility in news production for journalism practice and journalism research at the  levels of objectivity, authority, transparency, and at the level of implicit or explicit values.

Tantra is a system of knowledge based upon empirical as well as experiential understanding. The Kalacaka Tantra was the last major Buddhist Tantrik text written in lndia during early 11th century. This book has left indelible mark over different regions of Asia in the last thousand years of its journey. Kalacakra Tantra has fascinated Mongol court and the last Czar King. Unlike other world-religions which claim monopoly over Truth, Kalacakra philosophy propagates grand synthesis of world-views. Though steeped deeply into Buddhist philosophy, the book heavily borrows from different prevalent world-views.

This text is also a repository of different disciplines of knowledge extant during its time like astronomy, geography, alchemy, armament technology, dramaturgy, aesthetics, contemplative subtle neuroscience and mathematics. This Tantra attempted to construct a universal algorithm running through the physical, biotic and linguistic universe. The algorithm has philosophical underpinning in

The Buddhist concept of dependent origination, the chain of causation. Evam, the principle of similarity defies such causality and connects different realms. While the whole cosmos has been conceptualized as breathing and sentient, this text also reduces everything unto machines pervaded by wheels. Apart front the Vimalprabha commentary composed during the mid- 11"' century, there is no verse by verse commentary available to the general reader.

I have attempted translation of the full text from Sanskrit original and have also contributed a new detailed commentary. The complete project runs into five volumes containing 2700 pages.

This book also contains a 225 page long Introduction that locates mysterious Sambhala and Oddiyana and unravels description of Asian geography in the text and its 11th  century commentary with Mt. Kailash at the centre. This book showcaseS lndia's continuous effort to chisel Buddhist philosophy and to retain its position as the repository of authentic Buddhist Dharma as well as philosophy.

This paper describes the highlights of presentations and discussions during the Third International BCI Meeting in a workshop that evaluated potential brain-computer interface (BCI) signals and currently available recording methods. It defined the main potential user populations and their needs, addressed the relative advantages and disadvantages of noninvasive and implanted (i.e., invasive) methodologies, considered ethical issues, and focused on the challenges involved in translating BCI systems from the laboratory to widespread clinical use. The workshop stressed the critical importance of developing useful applications that establish the practical value of BCI technology.

This study is concerned with understanding of the formation of ore deposits (precious and base metals) and contributes to the exploration and discovery of new occurrences using artificial neural networks. From the different digital data sets available in BRGM&#x27;s GIS ...

Young patients with early osteoarthritis (OA) represent a challenging population due to a combination of high functional demands and limited treatment options. Conservative measures such as injection and physical therapy can provide short-term pain relief but are only palliative in nature. Joint replacement, a successful procedure in the older population, is controversial in younger patients, who are less satisfied and experience higher failure rates. Therefore, while traditionally not indicated for the treatment of OA, cartilage repair has become a focus of increased interest due to its potential to provide pain relief and alter the progression of degenerative disease, with the hope of delaying or obviating the need for joint replacement. The field of cartilage repair is seeing the rapid development of new technologies that promise greater ease of application, less demanding rehabilitation and better outcomes. Concurrent procedures such as meniscal transplantation and osteotomy, however, remain of crucial importance to provide a normalized biomechanical environment for these new technologies. Level of evidence Systematic review, Level II.

Ridden .Markov Models (HMMs) are applied t.0 the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated on the globin family, the protein kinase catalytic domain, and the EF-hand calcium binding motif. In each case the parameters of an HMM are estimated from a training set of unaligned sequences. After the HMM is built, it is used to obtain a multiple alignment of all the training sequences. It is also used to search the . SWISS-PROT 22 database for other sequences. that are members of the given protein family, or contain the given domain. The Hi" produces multiple alignments of good quality that agree closely with the alignments produced by programs that incorporate threedimensional structural information. When employed in discrimination tests (by examining how closely the sequences in a database fit the globin, kinase and EF-hand HMMs), the '\ HMM is able to distinguish members of these families from non-members with a high degree ' of accuracy. Both the HMM and PROFILESEARCH ( a technique used to search for relationships between a protein sequence and multiply aligned sequences) perform better in these tests than PROSITE (a dictionary of sites and patterns in proteins). The HMM appecvs to have a slight advantage over PROFILESEARCH in terms of lower rates of false negatives and false positives, even though the HMM is trained using only unaligned sequences, whereas PROFILESEARCH requires aligned training sequences. Our results suggest the presence of an EF-hand calcium binding motif in a highly conserved and evolutionary preserved putative intracellular region of 155 residues in the a-l subunit of L-type calcium channels which play an important role in excitation-contraction coupling. This region has been suggested to contain the functional domains that are typical or essential for all L-type calcium channels regardless of whether they couple to ryanodine receptors, conduct ions or both. \ 8 Abbreviations HMM, hidden Marko,. ,,,dels; length from 130 to 170 residues (with few excep-' m, Expectetion-Maximization; ML. maximum tions) and two domains, the protein kinase catalytic like€ihood; MAP, maximum a posten'wi; hTL-score.

Quantitative ultrasound has attracted significant interest in the evaluation of bone fracture healing. Animal and clinical studies have demonstrated that the propagation velocity across fractured bones can be used as an indicator of healing. Researchers have recently employed computational methods for modeling wave propagation in bones, aiming to gain insight into the underlying mechanisms of wave propagation and to further enhance the monitoring capabilities of ultrasound. In this paper, we review the relevant literature and present the current status of knowledge.

Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome.

Changes in reimbursement policies have focused attention on the use of indwelling catheters in the critical care unit as well as their role in hospital-acquired urinary tract infections. Implementation of an evidence-based prevention program can significantly reduce both the prevalence of indwelling catheterization and the incidence of hospitalacquired catheter-associated urinary tract infection. This article describes the epidemiology and pathophysiology of catheter-associated urinary tract infection, and outlines essential elements of an evidence-based prevention program for the critical care unit. Changes in the US Centers for Medicare & Medicaid Services (CMS) inpatient prospective payment system continue to impact care delivery in the critical care unit. The Medicare Severity Diagnosis Related Group (MS-DRG) was launched in 2007, and the revised payment system was implemented in October 2008. One component of this program that has particularly impacted care delivery in the critical care unit is the identification of a number of high-cost, high-volume conditions that can be reasonably prevented via application of evidence-based interventions. 1 If the conditions are hospital acquired, the CMS will no longer reimburse the costs associated with them. Back to Top | Article Outline Catheter-Associated Urinary Tract Infection Not surprisingly, catheter-associated urinary tract infection (CAUTI) was identified as one of the original 8 potentially preventable conditions. Urinary tract infections (UTIs) account for approximately 40% of all hospital-acquired infections in the United States 2 ; more than 80% are associated with an indwelling catheter. 3 The prevalence of CAUTI in

Localization within a Wireless Sensor Network consists of defining the position of a given set of sensors by satisfying some non-functional requirements such as (1) efficient energy consumption, (2) low communication or computation overhead, (3) no, or limited, use of particular hardware components, (4) fast localization, (5) robustness, and (6) low localization error. Although there are several algorithms and techniques available in literature, localization is viewed as an open issue because none of the current solutions are able to jointly satisfy all the previous requirements. An algorithm called ROCRSSI appears to be a suitable solution; however, it is affected by several inefficiencies that limit its effectiveness in real case scenarios. This paper proposes a refined version of this algorithm, called ROCRSSI++, which resolves such inefficiencies using and storing information gathered by the sensors in a more efficient manner. Several experiments on actual devices have been perf...