Miracle-dz/UniFAR-FTUs huggingface dataset:
Amsorb ® Causes No Less Carbon Monoxide Formation than Either “ New ” or “ Classic ” Sodalime

To the Editor:—Dr. Norris et al. are to be congratulated for their well-designed clinical trial examining influence of epidural anesthesia and analgesia on outcomes after abdominal aortic surgery. A few points of interest deserve more discussion. The authors based their power analysis from a review of 234 previous patients undergoing the same surgery at their institution who required an average postoperative length of stay of 13 days. Although the clinical trial did not observe differences between epidural and nonepidural groups, all study patients experienced a dramatic reduction in length of stay (from 13 to 7 days) for the same surgery at the same institution. This dramatic reduction in length of stay across all groups could easily obscure any potential clinical differences between groups and limits conclusions on effects of epidural anesthesia and analgesia for this patient population undergoing routine clinical care. Several factors may be involved in this dramatic clinical improvement in all study patients. The study protocol used a defined postoperative clinical pathway, and similar pathways have been shown in other surgical populations to decrease length of stay by 1 to 2 days. Just as important a factor in this very intensive clinical trial is the high probability of a Hawthorne effect. This is the undesired effect of an intrusive experiment simply by itself. The inherent process of being in a clinical trial or under observation can lead to enhanced efforts and cooperation in the medical staff and can motivate the patient to increased mental and physical well being. Historically, this effect is named after studies performed at the Western Electric Hawthorne Works in Chicago, where Harvard Business School professor Elton Mayo examined productivity and work conditions. Within the context of intrusive observation, productivity increased (approximately 25%) regardless of manipulation of variables such as rest breaks, work hours, temperature, humidity, and even after return of variables back to prestudy conditions. These improvements have generally been interpreted as being caused by the sheer presence of observation and experimentation regardless of variables being studied. The Hawthorne effect is a potential limitation of all prospective clinical trials where the subjects and caregivers are aware of the presence of a study. The intrusive effect of Norris et al.’s well-designed clinical trial and the use of a clinical pathway could have easily been responsible for the dramatic reduction in length of hospital stay preand post-study, and these factors may have overshadowed any effects of epidural anesthesia and analgesia that may exist in the context of ordinary clinical care. Perhaps the most reasonable conclusion from this study is that an intensive, structured, clinical trial can markedly reduce length of stay after abdominal aortic surgery.
A System For Management Of Computational Fluid Dynamics Simulations For Civil Engineering

Civil Engineering, among its many aspects, requires attention to be payed to the flow of wind over structures. One way to gain a greater understanding of the interaction of wind and structures is to use Computational Fluid Dynamics (also known as CFD). However, CFD is one of the most challenging types of scientific computing. Typically, a civil engineer who wishes to use CFD must immediately consult with a CFD professional to perform even a basic simulation. One of our goals for this project is to develop tools that can make CFD more widely useable for various types of civil engineering. In particular, a long-term motivating goal of this project is to eventually produce a “virtual wind-tunnel” that would allow users in non-CFD engineering fields to upload and analyze designs for CFD analysis, without having to retrain themselves in CFD. Also, we are interested in providing resources for beginning users of CFD, to help such beginners understand the nature of CFD work. These motivations serve as long-term goals for this project, providing direction for both present and future work. In this paper we introduce a task management system for creating and managing CFD simulations. Our design has two major pieces, a web-based front-end which controls interaction with the user and a back-end task manager which controls the dispatch of CFD tasks to various back-ends. One of our key design interests in building these two pieces was to make them extensible, so that the front-end can present many different options for CFD simulations to the user and the backend can interface with many different execution environments. In addition to these two major components, we developed a number of smaller tools, integrated into our system, specifically intended for the management of CFD tasks. In the following sections, we discuss the problems related to performing CFD, the overall architecture of our system and the specific tools which we built to help us in managing CFD. We also describe our current progress and the experiences which we have had presenting this system to groups of users. We close with our expectations for further development.
Formally Secure Compilation

Severe low-level vulnerabilities abound in today’s computer systems, allowing cyber-attackers to remotely gain full control. This happens in big part because our programming languages, compilers, and architectures were designed in an era of scarce hardware resources and too often trade off security for efficiency. The semantics of mainstream low-level languages like C is inherently insecure, and even for safer languages, establishing security with respect to a high-level semantics does not guarantee the absence of low-level attacks. Secure compilation using the coarse-grained protection mechanisms provided by mainstream hardware architectures would be too inefficient for most practical scenarios. SECOMP1 is a new ERC-funded project aimed at leveraging emerging hardware capabilities for fine-grained protection to build the first, efficient secure compilers for realistic lowlevel programming languages (the C language, and Low [27] a safe subset of C embedded in F [2, 30] for verification). These compilers will provide a more secure semantics for source programs and will ensure that high-level abstractions cannot be violated even when interacting with untrusted lowlevel code. To achieve this level of security without sacrificing efficiency, our secure compilers target a tagged architecture [4, 13], which associates a metadata tag to each
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In everyday life, we are constantly surrounded by complex and cluttered scenes. In such cluttered environ-ments, visual perception is primarily limited by crowding, the deleterious inﬂuence of nearby objects on object recognition. For the past several decades, visual crowding was assumed to occur at a single stage, only between low-level features or object parts, thus dismantling, destroying, or ﬁltering object information. A large and converging body of evidence has demonstrated that this assumption is false: crowding occurs at multiple stages of visual analysis, and information passes through crowding at each of these stages. This converging empirical evidence points to a seeming paradox: crowding happens at multiple levels, which would seem to impair object recognition, and yet visual information at each of those levels is maintained intact and inﬂuences subsequent higher-level visual processing. Thus, while crowding impairs the access we have to visual information at many levels, it does not impair the representation of that information. The resolution of this paradox reveals how the visual system strikes a balance between the limits of object selection and the desire to represent multiple levels of visual information throughout cluttered scenes. Understanding crowding is therefore key to resolving the relationship between the richness of object and scene representations and the limits of conscious object recognition.
Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments : Field Evidence and Implications for Tournament Design

Tournaments are widely used in the economy to organize production and innovation. We study individual contestant-level data on 2796 contestants in 774 software algorithm design contests with random assignment. Precisely conforming to theory predictions, the performance response to added contestants varies non-monotonically across contestants of different abilities; most respond negatively to competition; highest-skilled contestants respond positively. In counterfactual simulations, we interpret a number of tournament design policies (number of competitors, prize allocation and structure, divisionalization, open entry) as a means of reconciling non-monotonic incentive responses to competition, effectively manipulating the number and skills distribution of contestants facing one another. JEL Codes: D02, J4, L2, M5 * Boudreau: London Business School, Strategy Department (email: kboudreau@london.edu); Helfat: Dartmouth University, Strategy Department (email: constance.e.helfat@tuck.dartmouth.edu); Lakhani: Harvard Business School: Department of Technology and Operations Management (email: klakhani@hbs.edu); Menietti: Harvard-NASA Tournament Laboratory (email: mmenietti@fas.harvard.edu). We are grateful to members of the TopCoder executive team for considerable attention, support, and resources in the carrying out of this project, including Jack Hughes, Rob Hughes, Mike Lydon, and Ira Heffan. For helpful comments, we thank seminar participants at Duke University, Georgia Tech and London Business School. The authors would like to acknowledge financial support from London Business School Research and Materials Development Grant and the NASA-Tournament Laboratory. All errors are our own.
Tweets and Trades: The Information Content of Stock Microblogs

Microblogging forums (e.g., Twitter) have become a vibrant online platform for exchanging stock‐related information. Using methods from computational linguistics, we analyse roughly 250,000 stock‐related messages (so‐called tweets) on a daily basis. We find an association between tweet sentiment and stock returns, message volume and trading volume, as well as disagreement and volatility. In contrast to previous related research, we also analyse the mechanism leading to an efficient aggregation of information in microblogging forums. Our results demonstrate that users providing above average investment advice are retweeted (i.e., quoted) more often and have more followers, which amplifies their share of voice.
International Journal of Current Science Research and Review

This study aims to uncover key factors influencing adoption process of BIM technology in an engineering consultant firm, Penta Rekayasa. The research employs mixed-methods approach combining quantitative analysis and qualitative input from industry experts and user judgement. A comprehensive of reviewing existing literature used to design a conceptual framework. A modified Technology Acceptance Model (TAM) of Unified Theory of Acceptance and Use of Technology (UTAUT) chosen as a main landing theory to design conceptual framework. Additionally, seven main constructs identified to influence usage behavior along with seven hypotheses proposed: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Organizational Support (OS), Resistance to Change (RC), Facilitating Condition (FC) and Behavioral Intention (BI). Primary data is collected using questionnaire and semi-structure interview, further analysis is carried out utilizing SmartPLS software's Partial Least Squares Structural Equation Modelling (PLS-SEM) and thematic analysis for interview analysis. The findings demonstrate that four major constructs are regarded as influencing factors in the Penta BIM adoption process: Performance Expectancy (PE), Effort Expectancy (EE), Resistance to Change (RC), and Behavioral Intention (BI). Other three are neither supported as the path coefficient, p-values and t-values threshold is exceed. The result of thematic analysis using Braun & Clarke's six-phase framework show three main problems arises that negatively influence the adoption process: Social influence and organizational support – unsupportive figure; Resistance to change – Penta’s employee resist to change; and facilitating condition – socialization and training importance. Based on user judgement, theories or practical article, and expert opinion; business solutions are proposed: Develop training and development system that can be used for BIM and future training; budgeting external education include seminar or bootcamp; Held internal meeting with stakeholders to increase the employee engagement and aligned goals with high management profile figure. For a long-term goal, Penta may also consider to develop BIM division in order to increase the speed of project completion. Lastly, the actionable schedule of implementation plan is proposed based on internal recommendation, project design life cycle, and working schedule to ensure the effectiveness of the program.
The Use of Artificial Neural Network in Option Pricing : The Case of S & P 100 Index Options

Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance. Keywords—Option Pricing, Neural Network, S&P 100 Index, American/European options
Breaking Up Is Hard To Do: Modeling Security Threats for Smart Cards

Smart card systems differ from conventional computer systems in that different aspects of the system are not under a single trust boundary. The processor, I/O, data, programs, and network may be controlled by different, and hostile, parties. We discuss the security ramifications of these "splits" in trust, showing that they are fundamental to a proper understanding of the security of systems that include smart cards.
A Study on the Secure ebXML Transaction Models

ebXML (Electronic Business using eXtensible Markup Language) is an e-business standard, sponsored by UN/CEFACT and OASIS, which enables enterprises to exchange business messages, conduct trading relationships, communicate data in common terms and define and register business processes. While there is tremendous e-business value in the ebXML, security remains an unsolved problem and one of the largest barriers to adoption. XML security technologies emerging recently have extensibility and flexibility suitable for security implementation such as encryption, digital signature, access control and authentication. In this paper, we propose ebXML business transaction models that allow trading partners to securely exchange XML based business transactions by employing XML security technologies. We show how each XML security technology meets the ebXML standard by constructing the test software and validating messages between the trading partners. Keywords—Electronic commerce, e-business standard, ebXML, XML security, secure business transaction.
Scholarship@Western Scholarship@Western

When performing a long chain of actions in rapid sequence, future movements need to be planned concurrently with ongoing action. However, how far ahead we plan, and whether this ability improves with practice, is currently unknown. Here, we designed an experiment in which healthy volunteers produced sequences of 14 finger presses quickly and accurately on a keyboard in response to numerical stimuli. On every trial, participants were only shown a fixed number of stimuli ahead of the current keypress. The size of this viewing window varied between 1 (next digit revealed with the pressing of the current key) and 14 (full view of the sequence). Participants practiced the task for 5 days, and their performance was continuously assessed on random sequences. Our results indicate that participants used the available visual information to plan multiple actions into the future, but that the planning horizon was limited: receiving information about more than three movements ahead did not result in faster sequence production. Over the course of practice, we found larger performance improvements for larger viewing windows and an expansion of the planning horizon. These findings suggest that the ability to plan future responses during ongoing movement constitutes an important aspect of skillful movement. Based on the results, we propose a framework to investigate the neuronal processes underlying simultaneous planning and execution.
Toward Optimal Configuration Space Sampling

Efficient motion planning is obtained by focusing computation on relevant regions of configuration space. In t he following we propose a new approach to multi-query samplingbased motion planning, which exploits information obtained from earlier exploration and its current state to guide exploration. This approach attempts to minimize the selection of samples to th ose required to completely capture configuration space connect ivity. Our planner constructs an approximate model of configuration space that is used in conjunction with a utility function to select configurations with maximal expected importance giv en the planner’s current state. The resulting utility-guided planner is online and adaptive. Its behavior adjusts to the developi ng state of the motion planner and its understanding of the confi guration space. Experimental comparisons with existing planners show that this utility-guided approach significantly decreases the runtime required for motion planning.
International Journal of Advanced Research in Computer Science and Software Engineering

— The area of Human Computer Interaction will be much more effective and natural if computers can automatically recognize and classify facial expressions for supplied face images and hence perceive about emotional state of human beings. The paper explains about comparative analysis of expression recognition using two approaches. Adaptive Neuro-Fuzzy Inference System (ANFIS) and Back propagation Neural network are used as classifiers for classifying the expressions of supplied face into seven basic categories like surprise, neutral, sad, disgust, fear, happy and angry. Facial Geometry method is used for facial feature extraction. Face portion segmentation and localization is achieved using series of morphological image processing operations. In geometry method, permanent facial features like eyebrows, eyes, mouth and nose are extracted using SUSAN edge detection operator and face geometry. Experiments are carried out on JAFFE facial expression database and gives better performance in terms of 100% classification accuracy for training set and 97.142% and 94.76% average recognition accuracy for test set using ANFIS and NN approach respectively for 30 test samples.
30(1)-March 2010:29(1)-March 2009 FLM

For the Learning of Mathematics 30, 1 (March, 2010) FLM Publishing Association, Edmonton, Alberta, Canada For the purposes of this article, we concentrate on particular dynamic software environments including dynamic geometry environments (e.g., Geometer’s Sketchpad, Cabri II+) and simulation software (e.g., SimCalc MathWorlds, a dynamic algebra environment). Such software allows mathematical representations to be dynamic through particular embodied features. These include:
An Extension of Multi-Layer Perceptron Based on Layer-Topology

There are a lot of extensions made to the classic model of multi-layer perceptron (MLP). A notable amount of them has been designed to hasten the learning process without considering the quality of generalization. The paper proposes a new MLP extension based on exploiting topology of the input layer of the network. Experimental results show the extended model to improve upon generalization capability in certain cases. The new model requires additional computational resources to compare to the classic model, nevertheless the loss in efficiency isn’t regarded to be significant. Keywords—Learning algorithm, multi-layer perceptron, topology.
Integrated Energy-Aware Mechanism for MANETs using On-demand Routing

(cid:3) Abstract — Mobile Ad Hoc Networks (MANETs) are multi-hop wireless networks in which all nodes cooperatively maintain network connectivity. In such a multi-hop wireless network, every node may be required to perform routing in order to achieve end-to-end communication among nodes. These networks are energy constrained as most ad hoc mobile nodes today operate with limited battery power. Hence, it is important to minimize the energy consumption of the entire network in order to maximize the lifetime of ad hoc networks. In this paper, a mechanism involving the integration of load balancing approach and transmission power control approach is introduced to maximize the life-span of MANETs. The mechanism is applied on Ad hoc On-demand Vector (AODV) protocol to make it as energy aware AODV (EA_AODV). The simulation is carried out using GloMoSim2.03 simulator. The results show that the proposed mechanism reduces the average required transmission energy per packet compared to the standard AODV.
FECDO-Flexible and Efficient Coding for DNA Odyssey

DNA has been pursued as a compelling medium for digital data storage during the past decade. While large-scale data storage and random access have been achieved in artificial DNA, the synthesis cost keeps hindering DNA data storage from popularizing into daily life. In this study, we proposed a more efficient paradigm for digital data compressing to DNA, while excluding arbitrary sequence constraints. Both standalone neural networks and pre-trained language models were used to extract the intrinsic patterns of data, and generated probabilistic portrayal, which was then transformed into constraint-free nucleotide sequences with a hierarchical finite state machine. Utilizing these methods, a 12%-26% improvement of compression ratio was realized for various data, which directly translated to up to 26% reduction in DNA synthesis cost. Combined with the progress in DNA synthesis, our methods are expected to facilitate the realization of practical DNA data storage.