Miracle-dz/UniFAR-FTUs huggingface dataset:
“We are doing it together”; The integral role of caregivers in a patients’ transition home from the medicine unit

Background An admission to hospital for acute illness can be difficult for patients and lead to high levels of anxiety. Patients are given a lot of information throughout their hospital stay and instructions at discharge to follow when they get home. For complex medical patients, the ability to retain, understand, and adhere to these instructions is a critical marker of a successful transition. This study was undertaken to explore factors impacting the ability of patients to understand and adhere to instructions. Methods A qualitative design of interviews with patients and caregivers was used. Participants were adult patients and caregivers with congestive heart failure, chronic obstructive pulmonary disease, or community-acquired pneumonia being discharged home from three academic acute care hospitals in Ontario, Canada. Semi structured interviews were conducted with participants within one week following their discharge from hospital. Interviews were audiotaped and transcribed. Five independent researchers participated in an iterative process of coding, reviewing, and analyzing the interviews using direct content analysis. Results In total, 27 participants completed qualitative interviews. Analysis revealed the role of the caregiver to be critical in its relation to the ability of patients to understand and adhere to discharge instructions. Within the topic of caregiving, we draw on three areas of insight: The first clarified how caregivers support patients after they are discharged home from the hospital. The second highlighted how caregiver involvement impacts patient understanding and adherence to discharge instructions. The third revealed system factors that influence a caregiver’s involvement when receiving discharge instructions. Conclusion Caregivers play an important role in the transition of a complex medical patient by impacting a patient’s ability to understand and adhere to their discharge instructions. The themes identified in this paper highlight opportunities for healthcare providers and institutions to effectively involve caregivers during transitions from acute care hospitals to home.
Patients at High Risk of Intervention for Pediatric Traumatic Liver Injury.

OBJECTIVES Nonoperative management of hemodynamically stable liver lacerations in pediatric trauma patients is a safe and effective management strategy for pediatric patients; approximately 90% will be successfully managed nonoperatively. No study has specifically identified risk criteria for the need for intervention versus observation alone. Our objective for this study was to determine risk factors from the physical examination, computed tomography scan, and laboratory results associated with intervention for liver laceration. METHODS We performed a retrospective cohort study using data from the Pediatric Emergency Care Applied Research Network Intra-abdominal Injuries Study public use data set. Data were collected prospectively at the time of enrollment; a limited data set was released for public use in 2014. Patients were included if they were diagnosed with a liver laceration by computed tomography scan. We used bivariable and multivariable analyses to determine associations of specific risk factors with intervention, defined as laparotomy, angiographic embolization, blood transfusion, death, or return to emergency department for any reason within 30 days. RESULTS Of the 12,044 patients in the Intra-abdominal Injuries Study, 282 were diagnosed with a liver laceration. All patients were hospitalized, and 99 (35.1%) underwent an intervention. Variables were then eliminated if more than 10% of cases were missing data. Multivariable logistic regression identified the following independent risk factors for intervention: white blood cell count greater than 15 K/mcl (adjusted odds ratio [adjOR], 2.83; 95% confidence interval [CI], 1.43-5.63), pelvic fracture (adjOR, 2.50; 95% CI, 1.02-6.10), liver injury greater than grade 2 (adjOR, 2.16; 95% CI, 1.06-4.40), Glasgow Coma Scale score less than 15 (adjOR, 4.77; 95% CI, 2.27-7.63), and hematocrit less than 32% (adjOR, 4.79; 95% CI, 2.00-11.46). CONCLUSIONS We identified 5 high-risk criteria associated with intervention for traumatic liver laceration in pediatric patients. Prospective studies are necessary to validate these results before using them to determine disposition of pediatric patients with traumatic liver injuries.
Where next with HDL assays?

Purpose of review The inverse association between HDL cholesterol (HDL-C) and cardiovascular disease (CVD) has been unequivocally proven in the past several decades. However, some interventions aiming to increase HDL-C failed to reduce CVD risk. HDL is structurally and functionally complex and HDL-associated metrics other than HDL-C, such as the concentration, composition, and functionality of HDL particles, have been considered as better determinants of CVD risk. A large body of recent research has addressed changes in HDL functions and HDL subpopulations in CVD with the goal of discovering novel and reliable biomarkers and targets for the treatment or prevention of CVD. Recent findings We have reviewed recent findings on HDL composition, HDL particle concentrations, and cell-cholesterol efflux capacity that have lately contributed to our understanding of HDL's role in CVD. Summary We point out that a major problem in HDL research is the lack of standardization of HDL assays that has led to discrepancies among studies. Therefore, there is a need for new standardized assays that capture the complexities of key HDL parameters.
An Evaluation Methodology of Cloud Service Quality Based on Queuing Model

With the rapid development of Internet technology, online applications have become an indispensable part of government, enterprise and engineering fields. Most enterprises have utilized the advantages of cloud computing and refactored the applications with the service-oriented architecture (SOA) in order to solve the huge number of online users, soaring data and fluctuant load. According to the cloud services quality which evaluated in different cloud computing resources, developer choose the suitable size of the service cluster to meet the needs of enterprise services in the distributed service cluster. It can not only ensure the stable operation of online applications, but also maximize the reduction of basic costs. Therefore, it is important to evaluate the quality of cloud services accurately. This paper proposes an evaluation method of cloud service quality based on queuing model. The M/M/1 and M/M/s queuing models are used to analyze and evaluate the quality of single node service and cluster service respectively. By the method proposed in this paper can not only choose the suitable size of the service cluster for online applications, but also perform dynamic scheduling of cloud resources. Finally, the feasibility and practicability of this method is verified by experiments.
An introduction to plant phylogenomics with a focus on palms

Phylogenomics refers to the use of phylogenetic trees to interpret gene function and genome evolution and to the use of genome-scale data to build phylogenetic trees. The field of phylogenomics has advanced rapidly in the past decade due to the now widespread availability of next generation sequencing technologies, which themselves continue to change at a rapid pace and drive down the cost of sequencing per base pair. In this review, we discuss genomic resources available to palm biologists in the form of complete genomes (plastid, mitochondrial, nuclear) and sequenced transcriptomes, all of which can be leveraged to study non-model palm taxa. We also discuss various approaches to generating phylogenomic data in palms, such as next-generation sequencing technologies and methodological approaches that allow acquisition of large volumes of biologically and phylogenetically meaningful data without the need to sequence entire genomes (e.g. genome skimming, RAD-seq, targeted sequence capture). This review was designed for those unfamiliar with phylogenomics and associated methods, but who are interested in engaging in phylogenomics research. We discuss several considerations required for designing phylogenetic projects using genomic data, such as available computing capabilities and level of bioinformatics expertise. We then review some recent, empirical examples of palm phylogenomic studies and how they are shaping the future of palm systematics and evolutionary biology.
A Leak-Resilient Dual Stack Scheme for Backward-Edge Control-Flow Integrity

Manipulations of return addresses on the stack are the basis for a variety of attacks on programs written in memory unsafe languages. Dual stack schemes for protecting return addresses promise an efficient and effective defense against such attacks. By introducing a second, safe stack to separate return addresses from potentially unsafe stack objects, they prevent attacks that, for example, maliciously modify a return address by overflowing a buffer. However, the security of dual stacks is based on the concealment of the safe stack in memory. Unfortunately, all current dual stack schemes are vulnerable to information disclosure attacks that are able to reveal the safe stack location, and therefore effectively break their promised security properties. In this paper, we present a new, leak-resilient dual stack scheme capable of withstanding sophisticated information disclosure attacks. We carefully study previous dual stack schemes and systematically develop a novel design for stack separation that eliminates flaws leading to the disclosure of safe stacks. We show the feasibility and practicality of our approach by presenting a full integration into the LLVM compiler framework with support for the x86-64 and ARM64 architectures. With an average of 2.7% on x86-64 and 0.0% on ARM64, the performance overhead of our implementation is negligible.
Dimensional ridge alterations following tooth extraction. An experimental study in the dog.

OBJECTIVE To study dimensional alterations of the alveolar ridge that occurred following tooth extraction as well as processes of bone modelling and remodelling associated with such change. MATERIAL AND METHODS Twelve mongrel dogs were included in the study. In both quadrants of the mandible incisions were made in the crevice region of the 3rd and 4th premolars. Minute buccal and lingual full thickness flaps were elevated. The four premolars were hemi-sected. The distal roots were removed. The extraction sites were covered with the mobilized gingival tissue. The extractions of the roots and the sacrifice of the dogs were staggered in such a manner that all dogs contributed with sockets representing 1, 2, 4 and 8 weeks of healing. The animals were sacrificed and tissue blocks containing the extraction socket were dissected, decalcified in EDTA, embedded in paraffin and cut in the buccal-lingual plane. The sections were stained in haematoxyline-eosine and examined in the microscope. RESULTS It was demonstrated that marked dimensional alterations occurred during the first 8 weeks following the extraction of mandibular premolars. Thus, in this interval there was a marked osteoclastic activity resulting in resorption of the crestal region of both the buccal and the lingual bone wall. The reduction of the height of the walls was more pronounced at the buccal than at the lingual aspect of the extraction socket. The height reduction was accompanied by a "horizontal" bone loss that was caused by osteoclasts present in lacunae on the surface of both the buccal and the lingual bone wall. CONCLUSIONS The resorption of the buccal/lingual walls of the extraction site occurred in two overlapping phases. During phase 1, the bundle bone was resorbed and replaced with woven bone. Since the crest of the buccal bone wall was comprised solely of bundle this modelling resulted in substantial vertical reduction of the buccal crest. Phase 2 included resorption that occurred from the outer surfaces of both bone walls. The reason for this additional bone loss is presently not understood.
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

Background Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking. Methods Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge. Results In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P = 0.19) and specificity to 75.7% (±11.7%, P < 0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P < 0.01) and level-II (75.7%, P < 0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P < 0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge. Conclusions For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification. Clinical trial number This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; https://www.drks.de/drks_web/).
MicroRNA-92a-3p inhibits the cell proliferation, migration and invasion of Wilms tumor by targeting NOTCH1

Dysregulation of miR-92a-3p has been shown to contribute to many tumorigenic processes, and is correlated with tumor progression and prognosis. However, the association between miR-92a-3p and the clinicopathological features of Wilms tumorand its regulatory mechanism remain unknown. In the present study, we demonstrated that miR-92a-3p was downregulated in Wilms tumor tissues and was significantly correlated with the lung metastasis of patients with Wilms tumor. Furthermore, miR-92a-3p mimics suppressed Wilms tumor cell proliferation, migration and invasion by in vitro assays. In addition, miR-92a-3p knockdown promoted tumor progression. Moreover, miR-92a-3p was shown to target directly the 3′-UTR of NOTCH1 mRNA by Dual-Luciferase reporter assays in Wilm's tumor cells. miR-92a-3p mimics decreased the expression of mRNA and protein of NOTCH1. miR-92a-3p inhibitor enhanced NOTCH1 expression by using western blotting and qPCR. In Wilms tumor tissues, NOTCH1 was highly expressed when compared with that in adjacent non-tumor tissues. NOTCH1 expression was found to be negatively correlated with miR-92a-3p in tumor tissues. Knockdown of NOTCH1 expression reversed the promotive effect of miR-92a-3p inhibitor on the cell proliferation, migration and invasion in Wilms tumor. In conclusion, miR-92a-3p blocks the progression of Wilms tumor by targeting NOTCH1.
Implementation of finite set model predictive current control for shunt active filter

The present paper investigates the effectiveness of Finite Set Model Predictive Current Control (FS-MPCC) for Shunt Active Filter SAF and its implementation on real bench. The method uses a Multivariable Filter MVF to extract the fundamental components of currents and voltages of the grid. The predictive control method uses a cost function containing the error of the filtered currents to be controlled. The performances of the control method are revealed throw simulation and experimental results and then commented. The obtained results show that predictive control is a powerful control method for such application in term of tracking performance and quality energy.
Colorectal cancer: A looming threat, opportunities, and challenges for the Saudi population and its healthcare system

© 2018 Saudi Journal of Gastroenterology | Published by Wolters Kluwer ‐ Medknow Global colorectal cancer (CRC) is projected to increase by 60% as early as 2030 which translates into 2.2 million new CRC cases and 1.1 million deaths. [1] Whereas these statistics indicate looming challenges, unprecedented opportunities enabling early diagnosis and a cure are also rapidly becoming part of clinical practice. CRC‐related statistics are alarming for the Kingdom of Saudi Arabia. Saudi Cancer Registry data reveal CRC to be the second most common cancer across the population. [2,3] Despite this scenario, institution of CRC screening and early diagnosis remains a formidable challenge. [4‐6] As a consequence, up to 24% of these patients have advanced disease with distant metastasis at initial diagnosis. [2] The disconnect between the magnitude of the problem and the necessary national action plan is obvious. Efforts to fill this gap include the empowerment of the primary healthcare system while being cognizant of the younger age population polarity of this nation. Indeed CRC “age‐shift” to younger populations is now well recognized, as has been reported from the United States of America. [7] Thus, an inclusive and well‐orchestrated program is essential to address this looming threat on a national front.
Functional abdominal pain and discomfort (IBS) is not associated with faecal microbiota composition in the general population

We read with interest the study by Simren et al 1 addressing the correlation between GI symptoms and functional GI disorders (eg, irritable bowel syndrome (IBS)) and the comment by Hadizadeh et al 2 reporting abdominal pain sensation to be associated with an altered faecal microbiota composition. Hadizadeh et al 2 propose from their study on 159 individuals that their results may allow to develop novel tools for diagnosis and management of IBS and dyspepsia. We tried to replicate their findings in the population-based Study of Health in Pomerania (SHIP-Trend)3 using stool samples from 906 volunteers to analyse faecal microbiota composition and diversity by 16S rRNA gene sequencing as previously described.4 Twenty participants were excluded for incomplete phenotypic data or antibiotic treatment at sample collection. Of the remaining 886 individuals (age: 51 years (40–61), median (first to third quartiles); female: 56.4%), 172 (19.4%) reported abdominal pain or discomfort for at least 3 days per month during the last 3 months (cases), whereas 714 did not (controls). To estimate …
Towards Si photonics based transceivers using directly modulated heterogeneously integrated DFB lasers

High speed directly modulated single mode lasers are becoming important optical components for the short reach communication. On the other hand, Si photonics opens up new opportunities to explore the transceivers for the short reach applications. We have fabricated a heterogeneously integrated DFB laser on a Si photonic circuit as a transmitter. For the receiver, a low voltage Si waveguide-coupled Ge avalanche photodetector has been used. We have successfully demonstrated error free transmission of a 10 Gb/s NRZ-OOK signal over 20 km single mode fiber using a silicon on insulator (SOI) based transmitter and receiver.
Diagnosis and imaging of essential and other tremors

Everyone suffers from trembling hands from time to time. For instance, when you are nervous, such as during a speech, or after a few of cups of coffee. Some people tremble considerably more than others: they are not at all nervous, but tremble none the less. This can be related to several different tremor diagnoses, from the most common: essential tremor, to the most well known: tremor in Parkinson’s disease. It is important to distinguish one type from the other, as both prognosis and treatment vary substantially. The first part of this thesis investigates tremor diagnosis, in which consultation by a neurologist including the physical examination is of primary importance. We investigated 5 typical characteristics that point to certain tremors and established that these tests differentiate the different tremor syndromes quite well. Next, we focused on muscle investigation (EMG), and found that certain advanced techniques are of additional value in diagnosis. In the second part of this thesis, the focus shifts towards the most common form of tremor, essential tremor, and how it is generated in the brain. By using a combination of simultaneously recorded muscle investigation (EMG) and brain scans (fMRI), we were able to establish increased, abnormal activity in the little brain or cerebellum and the network it is a part of. The knowledge from this thesis is of immediate additional value in daily clinical practice on the one hand, while on the other hand it adds to our understanding of essential tremor.
Domain2Vec: Vector representation of mobile server's domain based on mobile user visiting sequences

With the rapid development of mobile devices and wireless technologies, mobile Internet plays an essential role for delivering networked services in our daily life. Thus, understanding of mobile applications and user behavior is important for better networked services provisioning. In this paper, we propose a novel latent vector representation method of mobile server's domain, named Domain2Vec. The mobile user visiting sequences are extracted from the big traffic flow data that is collected by network traffic monitors from the core network of ISP. The vector representation learning is based on three-layer neural network (i.e. Word2Vec) model. The result of vector representation can be used as input of various classification or clustering tasks. we apply Domain2Vec to multi-class classification task of mobile servers, and validate the performance of the proposed method. Furthermore, we analyze the business interests relations between domains by measuring the similarity of domain vectors.
The Distributive, Graded Lattice of EL Concept Descriptions and its Neighborhood Relation

For the description logic EL, we consider the neighborhood relation which is induced by the subsumption order, and we show that the corresponding lattice of EL concept descriptions is distributive, modular, graded, and metric. In particular, this implies the existence of a rank function as well as the existence of a distance function.