Miracle-dz/UniFAR-FTUs huggingface dataset:
Perspectives of clinical handover processes: a multi-site survey across different health professionals.

AIMS AND OBJECTIVES To examine the perspectives of health professionals of different disciplines about clinical handover. BACKGROUND Ineffective handovers can cause major problems relating to the lack of delivery of appropriate care. DESIGN A prospective, cross-sectional design was conducted using a survey about clinical handover practices. METHODS Health professionals employed in public metropolitan hospitals, public rural hospitals and community health centres were involved. The sample comprised doctors, nurses and allied health professionals, including physiotherapists, social workers, pharmacists, dieticians and midwives employed in Western Australia, New South Wales, South Australia and the Australian Capital Territory. The survey sought information about health professionals' experiences about clinical handover; their perceived effectiveness of clinical handover; involvement of patients and family members; health professionals' ability to confirm understanding and to clarify clinical information; role modelling behaviour of health professionals; training needs; adverse events encountered and possibilities for improvements. RESULTS In all, 707 health professionals participated (response rate = 14%). Represented professions were nursing (60%), medicine (22%) and allied health (18%). Many health professionals reported being aware of adverse events where they noticed poor handover was a significant cause. Differences existed between health professions in terms of how effectively they gave handover, perceived effectiveness of bedside handover vs. nonbedside handover, patient and family involvement in handover, respondents' confirmation of understanding handover from their perspective, their observation of senior health professionals giving feedback to junior health professionals, awareness of adverse events and severity of adverse events relating to poor handovers. CONCLUSIONS Complex barriers impeded the conduct of effective handovers, including insufficient opportunities for training, lack of role modelling, and lack of confidence and understanding about handover processes. RELEVANCE TO CLINICAL PRACTICE Greater focus should be placed on creating opportunities for senior health professionals to act as role models. Sophisticated approaches should be implemented in training and education.
PKC-Dependent Human Monocyte Adhesion Requires AMPK and Syk Activation

PKC plays a pivotal role in mediating monocyte adhesion; however, the underlying mechanisms of PKC-mediated cell adhesion are still unclear. In this study, we elucidated the signaling network of phorbol ester PMA-stimulated human monocyte adhesion. Our results with pharmacological inhibitors suggested the involvement of AMPK, Syk, Src and ERK in PKC-dependent adhesion of THP-1 monocytes to culture plates. Biochemical analysis further confirmed the ability of PMA to activate these kinases, as well as the involvement of AMPK-Syk-Src signaling in this event. Direct protein interaction between AMPK and Syk, which requires the kinase domain of AMPK and linker region of Syk, was observed following PMA stimulation. Notably, we identified Syk as a novel downstream target of AMPK; AICAR can induce Syk phosphorylation at Ser178 and activation of this kinase. However, activation of AMPK alone, either by stimulation with AICAR or by overexpression, is not sufficient to induce monocyte adhesion. Studies further demonstrated that PKC-mediated ERK signaling independent of AMPK activation is also involved in cell adhesion. Moreover, AMPK, Syk, Src and ERK signaling were also required for PMA to induce THP-1 cell adhesion to endothelial cells as well as to induce adhesion response of human primary monocytes. Taken together, we propose a bifurcated kinase signaling pathway involved in PMA-mediated adhesion of monocytes. PKC can activate LKB1/AMPK, leading to phosphorylation and activation of Syk, and subsequent activation of Src and FAK. In addition, PKC-dependent ERK activation induces a coordinated signal for cytoskeleton rearrangement and cell adhesion. For the first time we demonstrate Syk as a novel substrate target of AMPK, and shed new light on the role of AMPK in monocyte adhesion, in addition to its well identified functions in energy homeostasis.
Corrugated-Diaphragm Based Fiber Laser Hydrophone with Sub-100 μPa/Hz1/2 Resolution

In this work, a beat-frequency encoded fiber laser hydrophone is developed for high-resolution acoustic detection by using an elastic corrugated diaphragm. The diaphragm is center-supported by the fiber. Incident acoustic waves deform the diaphragm and induce a concentrated lateral load on the laser cavity. The acoustically induced perturbation changes local optical phases and frequency-modulates the radio-frequency beat signal between two orthogonal lasing modes of the cavity. Theoretical analysis reveals that a higher corrugation-depth/thickness ratio or larger diaphragm area can provide higher transduction efficiency. The experimentally achieved average sensitivity in beat-frequency variation is 185.7 kHz/Pa over a bandwidth of 1 kHz. The detection capability can be enhanced by shortening the cavity length to enhance the signal-to-noise ratio. The minimum detectable acoustic pressure reaches 74 µPa/Hz1/2 at 1 kHz, which is comparable to the zeroth order sea noise.
Distributed EDCA bursting: improving cluster-based communication in IVC

Cluster-based communication is a staple topic in vehicular networks. Clustering communication nodes promise to reduce channel contention, enable building backbones and might improve spatial reuse. In this paper we propose a seemingly simple, yet unexplored idea: extending 802.11 frame bursting MAC access to multiple stations aggregated into a cluster. The focus of the paper is thus not building a cluster, but exploring what is the gain that can be achieved by the standard 802.11p channel access if we introduce the principle of frame bursting (presently not allowed in 802.11p standard, but the key factor for the efficiency of 802.11n/ac WiFi channel access). The key scientific question is if we can extend the frame bursting mechanism so that only the cluster leader contends for the channel reserving a Transmission Opportunity that is used by all the vehicles in the cluster transmitting a coordinated burst of frames. We describe in detail the idea, highlight the problems that can be encountered in its implementation (the devil, as usual is in details), and present some preliminary results for a special class of clusters: Cooperative driving platoons of cars.
Filtered Z-closure supernetworks for extracting and visualizing recurrent signal from incongruent gene trees.

Most modern phylogenetic inference methods assume that data should be fitted to a set of possible trees, from which the optimal tree is to be identified. A bifurcat ing tree-like diagram is thought to best represent evo lutionary history. This expectation follows largely from the view that (i) simultaneous divergence of multiple organismal lineages from the same common ancestor is likely to be rare (Hennig, 1966), hence the bifurcat ing attribute; and (ii) reticulate patterns of relationship caused by hybridization, horizontal gene transfer, and gene conversion and recombination are relatively mi nor deviations from an underlying single bifurcating pattern of evolution (Brown et al., 2001; Daubin et al., 2003). Whether most of the pattern of evolutionary history is truly bifurcating is still uncertain, but it has become in creasingly evident that complications such as hybridiza tion, horizontal gene transfer, and lineage sorting of ancestral polymorphisms are not as rare as once sup posed (Takahashi et al., 2001; P? bo, 2003; Zhaxybayeva et al., 2004; Gogarten and Townsend, 2005). Under these conditions, individual gene histories may not be con gruent with the general pattern of species or higher taxon relationships, and a phylogenetic tree estimated from the combined (concatenated) gene sequence rep resents an oversimplified version of the genetic history (Huber and Moulton, 2005; Morrison, 2005; Huson and Bryant, 2006). An usual alternative to simultaneous anal ysis of combined sequences from multiple gene parti tions is to present a consensus tree as a representation of relationships common to each individual gene tree, but this also suffers from oversimplification (Swofford, 1991) and can be performed only when each gene tree has the same taxon representation. A solution to the oversimplification and taxon constraints to topological congruence would allow visualization of both the princi pal conflicting patterns among individual gene trees and the phylogenetic patterns common among trees that may not overlap completely in taxon representation (partial trees). Huson et al. (2004) presented the Z-closure method for constructing a supernetwork from a set of partial trees. In cases where gene trees contain numerous dif ferent incongruent relationships, the resulting supernet work can, however, be too complex to visualize and interpret. Huson et al. (2006), therefore, extended the supernetwork approach to enable filters to remove re lationships (splits) from the supernetwork that are rep resented only once or sporadically among the source trees. The result is a network that summarizes the rela
Efficacy of Medications Approved for the Treatment of Alcohol Dependence and Alcohol Withdrawal Syndrome in Female Patients: A Descriptive Review

The aim of this study was to evaluate whether the number of women recruited for studies to establish the efficacy of medications approved for treatment of alcohol dependence (AD) and of alcohol withdrawal syndrome (AWS) is sufficient to reveal possible gender differences in the response to these medications and in suggesting the use of different doses in female patients. Our results show that the rates of women recruited for studies evaluating the efficacy of disulfiram (1%), benzodiazepines (3%), and anticonvulsants (13%) were too low to establish possible gender differences. The rates of women recruited for studies evaluating the efficacy of acamprosate (22%), naltrexone (23%), and nalmefene (30%) were higher and allowed evaluation of data obtained for female patients. Women receive medications for treatment of AD and/or AWS for which efficacy has been demonstrated in studies in which men were more largely represented.
Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs

Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source. In this paper, we propose Linear Energy Prediction “LINE-P”, a lightweight, yet relatively accurate model based on approximation and sampling theory; LINE-P is suitable for dual-source energy harvesting. Simulations and comparisons against existing similar models have been conducted with low and medium resolutions (i.e., 60 and 22 min intervals/24 h) for the solar energy source (low variations) and with high resolutions (15 min intervals/24 h) for the wind energy source. The results show that the accuracy of the solar-based and wind-based predictions is up to approximately 98% and 96%, respectively, while requiring a lower complexity and memory than the other models. For the cases where LINE-P’s accuracy is lower than that of other approaches, it still has the advantage of lower computing requirements, making it more suitable for embedded implementation, e.g., in wireless sensor network coordinator nodes or gateways.
Characterization of health complaints before and after removal of amalgam fillings — 3-year follow-up

Abstract Objective. Some patients attribute health complaints to amalgam fillings and report improvement of health after replacement of amalgam fillings. The aim of the present study was to characterize the changes of different health complaints after replacement of amalgam fillings and compare with an external reference group from the general population. Materials and methods. The study group included 20 patients with health complaints attributed to amalgam fillings who were participants in the treatment group of a clinical trial at the Norwegian Dental Biomaterials Adverse Reaction Unit. The patients were asked to indicate the intensity of local and general health complaints on numeric rating scales (0–10) before removal of amalgam fillings and at follow-up 3 years after removal. Data from the patient group were compared with data from an external reference group (n = 441). Results. Before treatment the mean intensity of complaints were on a higher level in the treatment group compared to the reference group. The most frequently reported complaints in the treatment group were gastrointestinal symptoms, fatigue, pain from muscles and joints, symptoms from ear/nose/throat and difficulty concentrating. From pre-treatment examination to the 3-year follow-up 20 of 23 health complaints decreased, being statistically significant for taste disturbances, pain from muscles and joints, gastrointestinal complaints, complaints from ear/nose/throat and fatigue. Conclusions. The inter-individual variation of intensities of health complaints was considerable and the reduction of health complaints varied for the different complaints. Several factors may be of importance for the observed reduction of complaint intensity.
Acute rotator cuff tears

### What you need to know A 45 year old woman falls on ice and injures her shoulder. Assessment at her local hospital reveals bruising only and no bony injury on plain radiographs. Despite ongoing reassurance and participation in a physiotherapy programme for three months, she continues to complain of pain, weakness, and inability to raise her arm. Eventually she is referred to a specialist shoulder clinic, where an ultrasound scan confirms she has suffered an acute full thickness tear of her supraspinatus tendon. Failing to identify an acute full thickness rotator cuff tear is a common problem, and this article is aimed at raising awareness of the condition and its correct management. The article is directed to all clinicians, but especially emergency department clinicians, trauma clinic clinicians, and general practitioners, who tend to see such cases. The rotator cuff comprises four important muscles (supraspinatus, infraspinatus, teres minor, and subscapularis) which attach close to the humeral head via tendons and are critically involved in stability and function of the shoulder. A rotator cuff tear is when one or more of these tendons tears or detaches from the humerus (fig 1). These tears can vary in size and be acute or chronic. Chronic full and partial thickness tears are due to tendon degeneration and attrition, and these patients …
The relationship between physical activity and food intake

It is a commonly held belief that exercise (one method of inducing an energy deficit) causes a compensation in energy intake to match the exercise-induced energy expenditure. This could possibly lead to the belief that exercise is not a useful method of weight loss which could then be used as an excuse not to exercise. However, there is no compelling evidence to suggest that exercise drives hunger and energy intake to cause a compensation in food intake. Indeed, the evidence suggests interventions in energy expenditure are not compensated for by changes in energy intake at least in the short-term (see King et al. 19976 for a review). This suggests only weak short-term coupling between energy expenditure and energy intake. However, since the negative energy balance could not continue indefinitely an equilibrium of energy intake and energy expenditure must occur at some stage. The exact time course (and mechanism) of such a compensatory change in energy intake is not yet known. A ‘delayed’ compensatory response to physical activity has been suggested (Edholm et al. 1955; Edholm, 1977), but this phenomenon has never been replicated. One other issue concerns the effects of exercise on changes in food selection or food preferences. Another widely held belief is that exercise induces an increase in the selection of carbohydrates. The evidence for a short-term effect is not convincing, but in the long-term carbohydrate intake does increase with prolonged exercise (Wood et al. 1982). This effect could be biologically driven or occur as a result of changes of a psychological nature. At the present time some effects of exercise on appetite are clear whereas other aspects require more research. The interactions are likely to involve both physiological and psychological processes. With the renewed interest in physical activity for body weight control, it becomes increasingly important to understand more fully the effects of exercise on the control of appetite .
Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network

We propose a weakly supervised semantic segmentation algorithm based on deep neural networks, which relies on image-level class labels only. The proposed algorithm alternates between generating segmentation annotations and learning a semantic segmentation network using the generated annotations. A key determinant of success in this framework is the capability to construct reliable initial annotations given image-level labels only. To this end, we propose Superpixel Pooling Network (SPN), which utilizes superpixel segmentation of input image as a pooling layout to reflect low-level image structure for learning and inferring semantic segmentation. The initial annotations generated by SPN are then used to learn another neural network that estimates pixel-wise semantic labels. The architecture of the segmentation network decouples semantic segmentation task into classification and segmentation so that the network learns class-agnostic shape prior from the noisy annotations. It turns out that both networks are critical to improve semantic segmentation accuracy. The proposed algorithm achieves outstanding performance in weakly supervised semantic segmentation task compared to existing techniques on the challenging PASCAL VOC 2012 segmentation benchmark.
Regorafenib for treatment of hepatocellular carcinoma

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MULTIVARIABLE ROBUST CONTROL OF AN INTEGRATED NUCLEAR POWER REACTOR

The design of the main control system of the CAREM nuclear power plant is presented. This plant is an inherently safe low-power nuclear reactor with natural convection on the primary coolant circuit and is self-pressurized with a steam dome on the top of the pressure vessel (PV). It is an integrated reactor as the whole primary coolant circuit is within the PV. The primary circuit transports the heat to the secondary circuit through once-through steam generators (SG). There is a feedwater valve at the inlet of the SG and a turbine valve at the outlet of the SG. The manipulated variables are the aperture of these valves and the reactivity of the control rods. The control target is to regulate the primary and secondary pressures and to monitor steam flow reference ramps on a range of nominal flow from 100% to 40%. The requirements for the control system are robust stability, low-order simple controllers and transient/permanent error bounding. The controller design is based on a detailed RETRAN plant model, from which linear perturbed open-loop dynamic models at different powers are identified. Two low-order nominal models with their associated uncertainties are chosen for two different power ranges. Robust controllers with acceptable performances are designed for each range. Numerical optimization based on the loop-shaping method is used for the controller design. The designed controllers are implemented in the RETRAN model and tested in simulations achieving successful results.
Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.