Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximizing smart pump technology to enhance patient safety.

SMART PUMP TECHNOLOGY Infusion pumps are defined by the US Food and Drug Administration as an external medical device used to deliver fluids into a patient’s body in a controlled manner. Smart pump infusion technology encompasses a variety of intravenous infusion devices with built-in computers containing electronic libraries of information on selected drugs and fluids with corresponding administration dose/rate limits. Smart pump technology was introduced into clinical practice in the early 2000s andhas continued to grow in the technology’s role in reducing patient harm associated with medication administration. Strategies to mitigate errors across the medication pathway of prescribing, transcribing, dispensing, administration, and documentation have been implemented. However, more than half of reportedmedication errors occur during the final step of administration. Thus, the emerging technology of a smart pump incorporates fluid/drug administration recommendations and alarms to alert the nurse to real or potential administration errors during the programming of the pump, assisting with the safety of that final step of medication administration. However, smart pumps are not very smart on their own; the technology depends on the active use of the medication libraries within the pump on a consistent basis. Maintaining an accurate medication library is an essential piece to the successful and complete adoption of smart pump infusion technology in practice. The clinical nurse specialist (CNS) plays a vital role in providing essential information to maintain the medication library, assisting with maximal smart pump technology use in practice, and obtaining reports demonstrating the effectiveness of the device in reducing patient harm.
Mindfulness as Clinical Training: Student Perspectives on the Utility of Mindfulness Training in Fostering Clinical Intervention Skills

Mindfulness training is increasingly being recommended as a strategy for fostering therapeutic effectiveness. We used a qualitative methodology to explore the potential utility of mindfulness training in helping beginning MSW students develop clinical intervention skills. Students reported that the training helped them manage distractions and anxiety, facilitated their ability to attend and respond to the client, and encouraged them to be more self-aware and flexible in their thinking in the classroom and in the field. Mindfulness training may strengthen current cognitive and behavioral training strategies, while providing a means of integrating affective and sensory learning into the training process.
A Good Fit: Japan's Solar Power Program and Prospects for the New Power System

The Japanese earthquake and tsunami of 11 March 2011 spurred numerous discussions and debates regarding the national energy policy of Japan. One of the outcomes of this process was a new feed-in tariff (FIT) program to promote renewable energy, including photovoltaic (PV) systems, that went into effect on 1 July 2012. This new incentive program is expected to completely change the PV market in Japan, which has historically been dominated by residential PV applications. The FIT will drive not only the residential sector but also the nonresidential sector, including the new entrants to the Japanese power generation business: megawatt-scale PV power plants. Accelerating the introduction of renewable energy is important not only for diversifying Japan's sources of energy (for energy security) and combating global warming (for the environment) but also for the development of green industries (for the economy). It is essential that Japan create an environment conducive to the expansion of renewable energy in Japan by identifying the appropriate mix of regulatory measures (e.g., FITs), public support, and private-sector voluntary efforts best suited to each energy source. This article describes the current status of the PV market in Japan; the new FIT program and its impacts on the PV market; and further institutional, technical, and R&D challenges for PV dissemination.
A novel member of the transmembrane serine/threonine kinase receptor family is specifically expressed in the gonads and in mesenchymal cells adjacent to the müllerian duct.

The activin and TGF-beta type II receptors are members of a separate subfamily of transmembrane receptors with intrinsic protein kinase activity, which also includes the recently cloned TGF-beta type I receptor. We have isolated and characterized a cDNA clone (C14) encoding a new member of this subfamily. The domain structure of the C14-encoded protein corresponds with the structure of the other known transmembrane serine/threonine kinase receptors. It also contains the two inserts in the kinase domain that are characteristic for this subfamily. Using in situ hybridization, C14 mRNA was detected in the mesenchymal cells located adjacent to the müllerian ducts of males and females at day 15 (E15) of embryonic development. Marked C14 mRNA expression was also detected in the female gonads. In female E16 embryos, the C14 mRNA expression pattern remained similar to that in E15 embryos. However, in male E16 embryos C14 mRNA was detected in a circular area that includes the degenerating müllerian duct. The expression of C14 mRNA was also studied using RNase protection assays. At E15 and E16, C14 mRNA is expressed in the female as well as in the male urogenital ridge. However, at E19, a high C14 mRNA level in the female urogenital ridge contrasts with a lack of C14 mRNA in the male urogenital ridge. This correlates with the almost complete degeneration of the müllerian ducts in male embryos at E19. C14 mRNA expression was also detected in embryonic testes at E15, E16 and E19 using RNase protection assays, but at much lower levels than those found in the developing ovaries. (ABSTRACT TRUNCATED AT 250 WORDS)
Efficient deadlock detection for concurrent systems

Concurrent systems are prone to deadlocks that arise from competing access to shared resources and synchronization between the components. At the same time, concurrency leads to a dramatic increase of the possible state space due to interleavings of computations, which makes standard verification techniques often infeasible. Previous work has shown that approximating the state space of component based systems by computing invariants allows to verify much larger systems then standard methods that compute the exact state space. The approach comes with the drawback, though, that not all of the reported specification violations may be reachable in the system. This paper deals with that problem by combining the information from the invariant with model checking techniques and strategies for reducing the memory footprint. The approach is implemented as post processing step for generating the exact set of reachable specification violations along with traces to demonstrate the error.
Caspase-dependent and -independent lipotoxic cell-death pathways in fission yeast

Understanding the mechanisms underlying lipid-induced cell death has significant implications in both cell biology and human diseases. Previously, we showed that fission-yeast Schizosaccharomyces pombe cells deficient in triacylglycerol synthesis display apoptotic markers upon entry into stationary phase. Here, we characterize the sequential molecular events that take place at the onset of cell death in S. pombe, including a surge of diacylglycerol, post-mitotic arrest, alterations in mitochondrial activities and in intracellular redox balance, chromatin condensation, nuclear-envelope fragmentation, and eventually plasma-membrane permeabilization. Our results demonstrated active roles of mitochondria and reactive oxygen species in cell death, and identified novel cell-death regulators – including metacaspase Pca1, BH3-domain protein Rad9, and diacylglycerol-binding proteins Pck1 and Bzz1. Most importantly, we show that, under different conditions and stimuli, failure to maintain intracellular-lipid homeostasis can lead to cell death with different phenotypic manifestations, genetic criteria and cellular mechanisms, pointing to the existence of multiple lipotoxic pathways in this organism. Our study represents the first in-depth analysis of cell-death pathways in S. pombe.
Localisation and capacitation-dependent loss of buffalo sperm-coating antigens shared with rat sperm

Summary The heterodimeric sperm-coating protein CFS was previously localised on the middle-piece region of rat spermatozoa by anti-CFS rabbit antibodies. CFS-immunorelated antigens were detected in the secretion of the water buffalo seminal vesicle by protein electrophoresis and Western blotting. Spermatozoa from buffalo epididymal cauda were incubated with the rat antigen and, upon immunostaining with anti-CFS antibodies and goat anti-rabbit fluorescein isothiocyanate (FITC)-conjugated IgGs, CFS was found attached on both the post-acrosomal region and the tail. Indirect immunofluorescence analysis permitted the localisation of CFS-related antigens on the same domains of buffalo ejaculated spermatozoa. These results suggest that the buffalo antigens not only share some epitopes with the homologous rat antigen but may also have some of its functional properties. Ejaculated spermatozoa were capacitated in vitro and then assayed for their content of CFS-like antigens. An inverse relationship was found between the levels of capacitation and the amounts of antigens detected, thus suggesting that the in vitro treatment was effective at removing CFS-related proteins from the cell surface. Titration of these proteins to proteins to monitor plasma membrane changes during sperm manipulation or to evaluate sperm quality is proposed.
Defensive stakeholder management in European universities: an institutional logics perspective

Earlier studies on stakeholder management in European universities focused on proactive strategies, that is, substantive organizational practices to establish and maintain mutually beneficial exchanges between universities and their stakeholders. We argue that the literature on stakeholder management has to be extended by theorizing defensive strategies (i.e. verbal or symbolic accounts in response to stakeholder criticism). Drawing on the institutional logics perspective, we investigate how and why a highly reputed, research-intensive European university deploys defensive strategies in the mass media. Our single-case study demonstrates that defensive strategies vary depending on the type of stakeholder criticism. Our study indicates that the relations between universities and their critical stakeholders can be consensual, but only if stakeholders criticize organizational values belonging to the institutional logic(s) from which universities operate.
Enabling SDN applications on Software-Defined Infrastructure

In this paper we discuss how to enable Software-Defined Networking (SDN) applications on Software-Defined Infrastructure (SDI) which is an approach for integrated control and management of converged computing and networking resources. Current separated resource management for computing or networking resources is not sufficient for addressing applications and multimedia services that require guaranteed service and quality levels. In addition, current resource management is not capable of managing heterogeneous resources that include computing and networking resources in combination with other resources such as programmable hardware, GPUs and network processors. We present an SDI that provides pluggable resource management modules for scheduling, networking control, fault management, and so on. This paper focuses on the design and implementation of a networking control module that enables SDN applications using information available from other modules. Currently, we have deployed the network control module in the practical multi-tier cloud infrastructure, SAVI Testbed. We present real measurements that show the functional evaluation results of our network control module.
Glial Control of Endocannabinoid Heterosynaptic Modulation in Hypothalamic Magnocellular Neuroendocrine Cells

Cannabinoid receptors are functionally operant at both glutamate and GABA synapses on hypothalamic magnocellular neuroendocrine cells; however, retrograde endocannabinoid actions are evoked at only glutamate synapses. We tested whether the functional targeting of evoked retrograde endocannabinoid actions to glutamate, and not GABA, synapses on magnocellular neurons is the result of the spatial restriction of extracellular endocannabinoids by astrocytes. Whole-cell GABA synaptic currents were recorded in magnocellular neurons in rat hypothalamic slices following manipulations to reduce glial buffering of extracellular signals. Depolarization- and glucocorticoid-evoked retrograde endocannabinoid suppression of synaptic GABA release was not detected under normal conditions, but occurred in both oxytocin and vasopressin neurons under conditions of attenuated glial coverage and depressed glial metabolic function, suggesting an emergent endocannabinoid modulation of GABA synapses with the loss of astrocyte function. Tonic endocannabinoid suppression of GABA release was insensitive to glial manipulation. Blocking cannabinoid transport mimicked, and increasing the extracellular viscosity reversed, the effect of suppressed glial buffering on the endocannabinoid modulation of GABA release. Evoked, but not tonic, endocannabinoid modulation of GABA synapses was mediated by 2-arachidonoylglycerol. Therefore, depolarization- and glucocorticoid-evoked 2-arachidonoylglycerol release from magnocellular neurons is spatially restricted to glutamate synapses by astrocytes, but spills over onto GABA synapses under conditions of reduced astrocyte buffering; tonic endocannabinoid modulation of GABA release, in contrast, is likely mediated by anandamide and is insensitive to astrocytic buffering. Astrocytes, therefore, provide dynamic control of stimulus-evoked 2-arachidonoylglycerol, but not tonic anandamide, regulation of GABA synaptic inputs to magnocellular neuroendocrine cells under different physiological conditions.
Measuring Stress, Anxiety, and Depression in PTSD Sufferers Using Micro-Movements from Video

Heart rate variability (HRV) is commonly used to analyze stress, anxiety, and depression in persons suffering from post-traumatic stress disorder (PTSD). Heart rate can be visualized using micro-movements in the skin using the Euler video magnification (EVM) method. HRV may be used to help persons with startle reactions associated with PTSD. This paper examines how heart rate can be captured from video using a tool designed for use by therapists and social workers that treat PTSD sufferers. We tested the tool against subjects with known heart rates taken using a fitness monitor. Also, the tool was tested against YouTube videos of individuals talking about their experiences with PTSD. Results showed that the tool was able to depict decreases in heart rate variability for individuals in the YouTube videos. However, the tool could not process videos with darker skinned individuals in our accuracy study.
Supervised Fine Tuning for Word Embedding with Integrated Knowledge

Learning vector representation for words is an important research field which may benefit many natural language processing tasks. Two limitations exist in nearly all available models, which are the bias caused by the context definition and the lack of knowledge utilization. They are difficult to tackle because these algorithms are essentially unsupervised learning approaches. Inspired by deep learning, the authors propose a supervised framework for learning vector representation of words to provide additional supervised fine tuning after unsupervised learning. The framework is knowledge rich approacher and compatible with any numerical vectors word representation. The authors perform both intrinsic evaluation like attributional and relational similarity prediction and extrinsic evaluations like the sentence completion and sentiment analysis. Experiments results on 6 embeddings and 4 tasks with 10 datasets show that the proposed fine tuning framework may significantly improve the quality of the vector representation of words.
Steganalysis using logistic regression

We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.
A flight simulator approach to the visualization of dynamic medical data

Visualization of 3-D medical scan data (e.g.: MRI, CT, PET) is often performed using surface rendering or volume rendering. Volume rendering is well suited for applications where the assignment of color and opacity values is straightforward given the image voxel intensities. This is true of CT data where there is a strong correlation between Hounsfield units and tissue types. Surface rendering is well suited for applications where segmentation of key structures is a necessary step for good visualization, such as with MRI data, and a polygonal mesh can be wrapped around segmented structures to form a surface model.
Source-Normalized LDA for Robust Speaker Recognition Using i-Vectors From Multiple Speech Sources

The recent development of the i-vector framework for speaker recognition has set a new performance standard in the research field. An i-vector is a compact representation of a speakers utterance extracted from a total variability subspace. Prior to classification using a cosine kernel, i-vectors are projected into an linear discriminant analysis (LDA) space in order to reduce inter-session variability and enhance speaker discrimination. The accurate estimation of this LDA space from a training dataset is crucial to detection performance. A typical training dataset, however, does not consist of utterances acquired through all sources of interest for each speaker. This has the effect of introducing systematic variation related to the speech source in the between-speaker covariance matrix and results in an incomplete representation of the within-speaker scatter matrix used for LDA. The recently proposed source-normalized (SN) LDA algorithm improves the robustness of i-vector-based speaker recognition under both mis-matched evaluation conditions and conditions for which inadequate speech resources are available for suitable system development. When evaluated on the recent NIST 2008 and 2010 Speaker Recognition Evaluations (SRE), SN-LDA demonstrated relative improvements of up to 38% in equal error rate (EER) and 44% in minimum DCF over LDA under mis-matched and sparsely resourced evaluation conditions while also providing improvements in the common telephone-only conditions. Extending on these initial developments, this study provides a thorough analysis of how SN-LDA transforms the i-vector space to reduce source variation and its robustness to varying evaluation and LDA training conditions. The concept of source-normalization is further extended to within-class covariance normalization (WCCN) and data-driven source detection.
A Scalable Multi-User Uplink for Wi-Fi

Mobile devices have fewer antennas than APs due to size and energy constraints. This antenna asymmetry restricts uplink capacity to the client antenna array size rather than the AP's. To overcome antenna asymmetry, multiple clients can be grouped into a simultaneous multi-user transmission to achieve a full rank transmission that matches the number of antennas at the AP. In this paper, we design, implement, and experimentally evaluate MUSE, the first distributed and scalable system to achieve full-rank uplink multi-user capacity without control signaling for channel estimation, channel reporting, or user selection. Our experiments demonstrate full-rank multiplexing gains in the evaluated scenarios that show linear gains as the number of users increase while maintaining constant overhead.
A Rapid Switch Bridge Selection Method for Fully Integrated DCDC Buck Converters

This letter presents a method for optimum selection of synchronous buck converter switch bridge topology and devices in the CMOS technology of choice. The comparative method targets maximum power efficiency, and it assumes an application where the dc-dc converter is on the same IC as the load with a known constant operating point. As its principal idea, the method circumvents the need for exhaustive comparative simulation work to cover the vast design space of available MOS device and cascode/noncascode topology combinations. Instead, the method narrows the space by using a set of basic parameters to approximate the best combination. The result, thus, provides sharp focus for subsequent detailed design and topology-dependent optimization. The method is illustrated by comparing its results to simulations of synchronous 3.31. 65-V buck converters in 45 and 65-nm CMOS with core, I/O, and high-voltage devices.
Vision-based Unmanned Aerial Vehicle detection and tracking for sense and avoid systems

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is challenging both from a detection point of view, as there are no markers on the targets available, and from a tracking perspective, due to misdetection and false positives. Furthermore, the methods need to be computationally light, despite the complexity of computer vision algorithms, to be used on UAVs with limited payload. To address these issues we propose a multi-staged framework that incorporates fast object detection using an AdaBoost-based approach, coupled with an on-line visual-based tracking algorithm and a recent sensor fusion and state estimation method. Our framework allows for achieving real-time performance with accurate object detection and tracking without any need of markers and customized, high-performing hardware resources.
Test patterns for android mobile applications

Mobile applications are a rapidly increasing part of our daily life, featuring more than one million applications and fifty billions downloads in the two major markets. Thus, it is important to ensure their functional correctness. The Pattern-Based GUI Testing (PBGT) project presented an approach for systematising and automating the GUI testing of web applications by modelling testing goals with User Interface Test Patterns(UITPs), i.e., test strategies for recurring behaviour of the UI. This paper extends the set of UITPs used by the PBGT project with three UITPs specific to the testing of mobile applications: Side Drawer, Orientation and Resources Dependency.