Miracle-dz/UniFAR-FTUs huggingface dataset:
Helping Adolescents at Risk: Prevention of Multiple Problem Behaviors

Youth with Multiple Problems. The Extent and Consequences of Multiple Problems. Ted R. Miller, The Social Costs of Adolescent Problem Behavior. Influences on the Development of Multiple Problems. Prevention of Adolescent Problems through Interventions in the Preteen Years. Prevention Practices Targeting All Adolescents. Interventions Targeting Adolescents with Behavior Problems. Comprehensive Community and Statewide Interventions. Integrating Science and Practice to Enhance the Well-Being of Children and Adolescents.
Karlsruhe Reports in Informatics 2011,1

Today’s computing systems typically execute task-speciﬁc software on general purpose hardware. As a consequence, the software layer must make do with whatever instructions, information, and services the underlying hardware exposes. This restriction can lead to implementing ineﬃcient approximations rather than the intended functionality of software. For example, virtual memory subsystems in operating systems often approximate the desired least recently used (or least frequently used ) strategy for page replacement using a two-handed clock algorithm just because the hardware only provides a single referenced bit rather than the required timestamp (or reference counter) per page. Programmable hardware such as suﬃciently large ﬁeld programmable gate arrays (FPGAs) has been available for quite some years and could be used to give software developers the possibility to alter or augment the hardware to better match their demands. However, there is no basic system available that can serve as a starting point for FPGA-based HW/SW research and that is both suﬃciently powerful and easy enough to work with. In this report, we describe the OpenProcessor platform, a free and open source computing platform, comprising both synthesizable hardware and support software. The hardware is described in Verilog, ready for deployment on an FPGA development board, and designed with a focus on extensibility and simplicity rather than utmost performance in order to attract many developers. The software stack comprises a microkernel-based operating system oﬀering a subset of the POSIX API to execute on the FPGA plus a number of management and monitoring services to run on an attached PC.
Effects of Classroom Ventilation Rate and Temperature on Students’ Test Scores

Using a multilevel approach, we estimated the effects of classroom ventilation rate and temperature on academic achievement. The analysis is based on measurement data from a 70 elementary school district (140 fifth grade classrooms) from Southwestern United States, and student level data (N = 3109) on socioeconomic variables and standardized test scores. There was a statistically significant association between ventilation rates and mathematics scores, and it was stronger when the six classrooms with high ventilation rates that were indicated as outliers were filtered (> 7.1 l/s per person). The association remained significant when prior year test scores were included in the model, resulting in less unexplained variability. Students’ mean mathematics scores (average 2286 points) were increased by up to eleven points (0.5%) per each liter per second per person increase in ventilation rate within the range of 0.9–7.1 l/s per person (estimated effect size 74 points). There was an additional increase of 12–13 points per each 1°C decrease in temperature within the observed range of 20–25°C (estimated effect size 67 points). Effects of similar magnitude but higher variability were observed for reading and science scores. In conclusion, maintaining adequate ventilation and thermal comfort in classrooms could significantly improve academic achievement of students.
Applicability of averaged concentrations in determining geochemical reaction rates in heterogeneous porous media

This work examines the applicability of averaged concentrations, a mathematical analog of field-measured solute concentrations averaged over a large number of pores, in determining mineral reaction rates in heterogeneous porous media. Pore-scale network models were used to represent sandstones with anorthite and kaolinite as reactive minerals that are heterogeneously distributed in space. Reaction rates calculated from averaged concentrations were compared to true reaction rates that take into account variabilities in individual pore properties. Simulations were run under the highly acidic conditions relevant to geological CO2 sequestration in deep brine formations under various mineralogical and flow conditions. Results show that, under conditions where incomplete mixing arises, the averaged concentrations and analogously the field-measured concentrations, do not accurately reflect reaction progress. Over the length scale of several millimeters, the anorthite dissolution rates can be overestimated by a factor of three. For kaolinite, due to its highly nonlinear reaction rate law, even the reaction direction may be incorrectly determined, with precipitation predicted as dissolution. The extent of errors introduced depends on the extent of incomplete mixing. Conditions that homogenize the concentration fields, such as small reactive mineral clusters, abundant reactive minerals, and very fast or very slow flow rates, minimize errors introduced from averaging. These results indicate that the averaging scheme may partly contribute to the often-cited laboratory-field rate discrepancy and have important implications for the interpretation of concentration data obtained from field investigation.
A generalized coverage-preserving scheduling in WSNs: A case study in structural health monitoring

Wireless sensor networks (WSNs) are generally used to monitor, in an area, certain phenomena which can be events or targets that users are interested. To extend the system lifetime, a widely used technique is `Energy-Efficient Coverage-Preserving Scheduling(EECPS)', in which at any time, only part of the nodes are activated to fulfill the function. To determine which nodes should be activated at a certain time is the key for the EECPS and this problem has been studied extensively. Existing solutions are based on the assumption that each node has a fixed coverage area, and once the event/target occurs in this area, it can be detected by this sensor. However, this coverage model is not always valid. In some applications such as structural health monitoring (SHM) and volcano monitoring, to fulfill a required function always requires low level collaboration from multiple sensors. The coverage area for individual sensor node therefore cannot be defined explicitly since single sensor is not able to fulfill the function alone, even it is close to the event or target to be monitored. In this paper, using an example of SHM, we illustrate how to support EECPS in some special applications of WSNs. We re-define the `coverage' and based on the new coverage model, two methods are proposed to partition the deployed sensor nodes into qualified cover sets such that the system lifetime can be maximized by letting these sets work by turns. The performance of the methods is demonstrated through extensive simulation and experiment.
Improving effective bandwidth through compiler enhancement of global and dynamic cache reuse

While CPU speed has been improved by a factor of 6400 over the past twenty years, memory bandwidth has increased by a factor of only 139 during the same period. Consequently, on modern machines the limited data supply simply cannot keep a CPU busy, and applications often utilize only a few percent of peak CPU performance. The hardware solution, which provides layers of high-bandwidth data cache, is not effective for large and complex applications primarily for two reasons: far-separated data reuse and large-stride data access. The first repeats unnecessary transfer and the second communicates useless data. Both waste memory bandwidth. This dissertation pursues a software remedy. It investigates the potential for compiler optimizations to alter program behavior and reduce its memory bandwidth consumption. To this end, this research has studied a two-step transformation strategy: first fuse computations on the same data and then group data used by the same computation. Existing techniques such as loop blocking can be viewed as an application of this strategy within a single loop nest. In order to carry out this strategy to its full extent, this research has developed a set of compiler transformations that perform computation fusion and data grouping over the whole program and during the entire execution. The major new techniques and their unique contributions are: Maximal loop fusion : an algorithm that achieves maximal fusion among all program statements and bounded reuse distance within a fused loop. Inter-array data regrouping : the first to selectively group global data structures and to do so with guaranteed profitability and compile-time optimality. Locality grouping and dynamic packing: the first set of compiler-inserted and compiler-optimized computation and data transformations at run time. These optimizations have been implemented in a research compiler and evaluated on real-world applications on SGI Origin2000. The result shows that, on average, the new strategy eliminates 41% of memory loads in regular applications and 63% in irregular and dynamic programs. As a result, the overall execution time is shortened by 12% to 77%. In addition to compiler optimizations, this research has developed a performance model and designed a performance tool. The former allows precise measurement of the memory bandwidth bottleneck; the latter enables effective user tuning and accurate performance prediction for large applications: neither goal was achieved before this thesis.
Automated Delineation of Subgroups in Web Video: A Medical Activism Case Study

Web 2.0 tools in general, and Web video in particular, provide new ways for activists to express their viewpoints to a broad audience. In this paper we deployed tools that have been used to find subgroups automatically in social networks and applied them to the problem of distinguishing between two sides of a controversial issue based on patterns of online interaction. We explored the problem of distinguishing between anti- and pro-vaccination activists based on a social network of videos and associated comments posted on YouTube. Videos for the analysis were selected by submitting the term “vaccination” to a search on YouTube. A content analysis of the selected videos was then performed (Keelan et al, 2007) to classify videos as pro- or anti-vaccination. Then, a modified version of the SCAN method (Chin and Chignell, 2008) for identifying cohesive subgroups in social networks was applied to the social network inferred from the discussions about the videos. Results showed that a cohesive subgroup of anti-vaccination people existed in discussions around anti-vaccination videos, whereas discussions around pro-vaccination videos included both anti-vaccination and pro-vaccination people. Implications of the method and results for more general delineation of types of medical activism and the opposing camps within those camps are discussed.
EglN2 positively regulates mitochondrial function in breast cancer

ABSTRACT Oxygen sensing is associated with mitochondrial function. EglN2, which contributes to breast tumorigenesis as a prolyl hydroxylase, has recently been identified as a transcription co-activator through interaction with NRF1 and PGC1α to regulate mitochondrial function under conditions of normoxia and hypoxia. FDXR is the important downstream target gene that mediates this regulation.
A 195mW, 9.1MVertices/s fully programmable 3D graphics processor for low power mobile devices

A 195 mW, 9.1Mvertices/s fully programmable 3D graphics engine is designed and implemented in 0.13 mum CMOS process for mobile devices. The power-optimized unified shader architecture provides high performance programmable vertex shading and programmable pixel shading with 35% area and 28% power reduction. The logarithmic lighting engine and specialized lighting instruction improves the vertex throughput to 9. 1Mvertices/s including full OpenGL lighting, which is 2.5 times higher performance compared with previous works. The 313 graphics engine was successfully demonstrated on the system evaluation board.
Adaptive parameter estimation with nonswitching reaching law for variable structure control of a nanopositioning stage

In this paper, an innovative motion controller is proposed to compensate for both the nonlinear hysteresis and the vibration dynamics effects of a nanopositioning stage driven by piezoelectric actuators. With the increasing of operating bandwidth and motion range, large positioning errors are produced because of the hysteresis, vibration, external disturbance and noise, as well as uncompleted modeled dynamic errors. The main contribution of this work is that an adaptive approach is developed to estimate these uncertainties and errors in real-time. Furthermore, a nonswitching type of reaching law for variable structure control of the discrete-time system is applied to regulate the position state, which is effective to compensate for nonrepeating disturbance. In addition, the proposed control algorithm is applied to experimentally validate the effectiveness of enhancing the performance in precise positioning control of the nanopositioning stage.
An high voltage CMOS voltage regulator for automotive alternators with programmable functionalities and full reverse polarity capability

This paper presents an innovative and effective approach to design and test a regulator for an automotive alternator with programmable functionalities. The prototype system consists of two different parts: an integrated circuit (IC) and a FPGA. The IC, implemented in austriamicrosystems HVCMOS 0.35 µm technology, includes all the high voltage parts and a power switch with very low ON resistance. It is able to manage full reverse polarity on every pin, including the reverse battery condition, and over voltages up to 50 V. The programmability is guaranteed through the FPGA. This prototype system can be used to develop a new type of intelligent smart and flexible regulators which implement many additional programmable functions that give the car maker a better control and allow to reduce vehicle fuel consumption and CO2 emissions. In the demonstrator all the implemented functions, including regulation, can be changed during the development phase and many properties, including loop stability, can be checked before releasing a final version of the regulator. The proposed system is also included in a standard brush-holder that can be mounted on Valeo Engine and Electrical System mechatronic alternator and verified directly in a real application.
An Empirical Study on the Enterprise Cloud Service Adoption

Enterprise cloud service is a new IS paradigm which allows the storage of data, application software, and even operating platform over the Internet so that a corporation can use them at any time and at any place. It differs from the conventional information systems in that it doesn’t require the companies to build up their own IS resource by allowing them to lease it over the Internet. With this innovative service offering, many companies have expressed much interest to adopt cloud services in practice. However, their apparent adoption behaviors appear to be quite inconsistent. This seemingly comes from the fact that cloud service is not a single product, but a set of different service provisioning options which have different incentives and risks to adopt. This paper configures what kind of service provisioning options are relevant to the true adoption intent of the enterprises and investigates how the intention to adopt differs among various service provisioning options. An integrated research model is set up with the concepts of IS maturity and outsourcing, and tested with the data collected from about two hundred SMEs. From the empirical study, it is found that perceived benefit and risk is differently affecting on the adoption intent, and the conceived conflict between high IS maturity level, especially with high IS infra asset, is negatively affecting on the adoption intent with some cloud service provisioning options.
Observer based self-triggered control of linear plants with unknown disturbances

This paper addresses the control of linear time-invariant plants in the presence of unknown disturbances when the plant's output is only measured at sampling instants determined by a self-triggering strategy. In a self-triggered scenario, the controller is allowed to choose when the next sampling time should occur and does so based on available measurements and on a priori knowledge about the plant. The proposed solution is a cascade interconnection of a discrete time observer and a self-triggered controller designed for state feedback. We focus our attention on discrete-time observers that are input-to-state stable (ISS) with respect to disturbances for all possible sequences of sampling times. Self-triggered control strategies presented in the literature are known to be ISS with respect to observation errors and exogenous disturbances. Due to the cascade structure of the closed-loop system, we conclude that the closed-loop is rendered ISS with respect to all bounded exogenous disturbances.
Forced Simulation(cid:0) A Formal Approach to Component(cid:1)Based Synthesis

Embedded systems are application(cid:8)speci(cid:16)c digital systems which are nor(cid:8) mally designed using a microprocessor along with a set of programmable hardware and software components(cid:14) Component(cid:8)based synthesis of these systems will lead to the reuse of a vast library of hardware and software components and also facilitate rapid prototyping(cid:14) However component based synthesis is still low key(cid:0) a primary reason being the lack of any systematic attempt at the development of automatic component identi(cid:16)cation algo(cid:8) rithms(cid:14) In (cid:20)(cid:1)(cid:7)(cid:21) an algorithm to map a design function to a device from a library of system(cid:8)level components was proposed(cid:14) However(cid:0) it was not based on a formal setting and no proof of correctness was presented(cid:14) In this paper(cid:0) we propose a novel notion of simulation called forced simulation to formalize the correspondence between a function and a device(cid:14) What distinguishes forced simulation from other techniques is the idea of forcing via an external interface(cid:0) which can be automatically synthesized(cid:0) and is useful for adapting the system level component to the given design functionality(cid:14) We have proposed two di(cid:17)erent types of forced simulation depending on the handling of internal events(cid:14)
Automatic Kernel Regression Modelling Using Combined Leave-One-Out Test Score and Regularised Orthogonal Least Squares

This paper introduces an automatic robust nonlinear identification algorithm using the leave-one-out test score also known as the PRESS (Predicted REsidual Sums of Squares) statistic and regularised orthogonal least squares. The proposed algorithm aims to achieve maximised model robustness via two effective and complementary approaches, parameter regularisation via ridge regression and model optimal generalisation structure selection. The major contributions are to derive the PRESS error in a regularised orthogonal weight model, develop an efficient recursive computation formula for PRESS errors in the regularised orthogonal least squares forward regression framework and hence construct a model with a good generalisation property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated model construction procedure without resort to any other validation data set for model evaluation.
Big-data-driven innovation for enterprises: innovative big value paradigms for next-generation digital ecosystems

Among the various interpretations and meanings of the well-known Vs (Volume, Velocity, Variety) of Big Data, V as Value represents the most significant and critical innovation for enterprises, which are a well-known case of digital ecosystems. The key issue for big enterprise data consists in extracting knowledge for creating new value and innovation for the target enterprise. Therefore, the big data analytics phase plays a critical role to this end. Following these considerations, in this paper we provide the following three contributions: (i) an overview of most relevant proposals in the context of big data innovation for enterprises; (ii) a reference architecture for supporting advanced big data analytics over big enterprise data; (iii) a discussion on future challenges in the context of big data innovation for enterprises.
Transdermal Oxygen Does Not Improve Sternal Wound Oxygenation in Patients Recovering from Cardiac Surgery

BACKGROUND:Sternal wound dehiscence and infection complicate 1% of cardiac surgeries. Tissue oxygen tension (PsqO2) is the primary determinant of surgical wound infection risk and is often critically low in surgical incisions. We tested the hypothesis that local transdermal delivery of oxygen improves oxygenation in sternotomy wounds after cardiac surgery. Our secondary hypothesis was that supplemental inspired oxygen improves sternal wound PsqO2. METHODS:After undergoing cardiopulmonary bypass, 30 patients randomly received (1) 2 EpiFlo oxygen generators (Ogenix, Inc., Beachwood, OH) that provided oxygen at 6 mL/h into an occlusive wound dressing or (2) identical-appearing inactive generators. PsqO2 and temperature were measured in the wound ≈5 mm below the skin surface. PsqO2 and arterial oxygen (Pao2) were measured 1 h after intensive care unit admission (Fio2 = 60%) and on the first and second postoperative mornings at Fio2 of both 30% and 50% in random order. RESULTS:Data from four patients were excluded for technical reasons. Patient characteristics were similar in each group, as were type of surgery and perioperative management. Increasing Fio2 from 30% to 50% improved Pao2 from 99 [84–116] to 149 [128–174] mm Hg (P < 0.001, mean [95% CI]) and sternal wound PsqO2 from 23 [16–33] to 27 [19–38] mm Hg (P < 0.001). In contrast, local oxygen delivery did not improve tissue oxygenation: 24 [14–41] vs 25 [16–41] mm Hg (P = 0.88). CONCLUSIONS:Additional inspired oxygen improved Pao2 and sternal wound PsqO2 after bypass and may, consequently, reduce infection risk. However, oxygen insufflated locally into an occlusive dressing did not improve wound PsqO2 and, therefore, does not appear to be useful clinically in cardiac surgery patients to reduce sternal wound infections.
Patients with oral anticoagulation

Summary Oral anticoagulation with a vitamin K-antagonist requires special consideration when surgery or interventional procedures are planned. This is mainly due to the half life of vitamin K-antagonists and to the need for safe and effective anticoagulation prior to and during surgery as well as in the postoperative period. So far, the continuous infusion of unfractionated heparin (UFH) has been the medication of choice to ,,bridge“ patients to surgery. The use of low molecular weight heparins (LMWH) has been prospectively investigated in this setting and represents a safe alternative. The advantages of LMWH are the better dose-response relationship and reduced need for monitoring. This facilitates the bridging procedure to be started out of hospital, which may reduce hospital stay and associated costs. Furthermore, the so-called bridging of patients with oral anticoagulation prior to and during surgery reduces bleeding complications and maintains a safe anticoagulation for patients at risk.