Miracle-dz/UniFAR-FTUs huggingface dataset:
The Connected Community Pharmacy: Benefits for Healthcare and Implications for Health Policy

The need for interoperability of healthcare Information Technology (IT) systems in order to provide safe, efficient, and coordinated healthcare is universally recognized. Various health economies, such as the United Kingdom, the United States, and Australia, are seeking to develop regional, state-wide, or national systems of healthcare interoperability. In England, the community pharmacy network is a significant health provider, with important implications for provision of healthcare in deprived areas because of its accessibility. Historically, however, community pharmacies have operated on a silo basis, and have not shared information on their activities with, or been able to access information from, other National Health Service (NHS) healthcare providers. The development of services such as the Electronic Prescription Service and the Summary Care Record in England have helped to connect community pharmacy with the NHS infrastructure, and more comprehensive systems and datasets are proposed to integrate community pharmacy with the NHS in future. This paper will review the benefits of the connected community pharmacy, based on developments to date and reviewing evidence from other countries. It will describe some of the future developments that will support the connected community pharmacy in England, and discuss some of the implications for pharmacists and health policy makers.
When things go wrong: a practical guide to dealing with complaints

Complaints inevitably accompany clinical care. This article explores complaints primarily in the context of the UK National Health Service complaints system. However, much of the content will apply to other settings, such as the independent sector. The infrequent but serious ramifications of complaints are also considered, including retraining and suspension. The article is written from a medical perspective but considers the roles of other professionals, the organisation and the complainant.
Effects of average and specific context probability on reduction of function words BE and HAVE

Abstract In a study of word shortening of HAVE and contraction of BE, it is found that both high transitional probability and high average context probability (low informativity) result in reduction. Previous studies have found this effect for content words and this study extend the findings to function words. Average context probability is by construction type, showing that words are shorter in constructions with high average predictability, namely in perfect constructions for HAVE and in future and progressive constructions for BE. These findings show that in cases of grammaticalization, it is not an increase in frequency that results in reduction, but a decrease in informativity.
ANKARA İLİ ETİMESGUT İLÇESİ’NDEKİ PARKLARDA BAKIM ÇALIŞMALARININ İRDELENMESİ

Bu calismada, Ankara Ili Etimesgut Ilcesi’ndeki parklarda bakim calismalari irdelenmistir. Calismanin amaci, ilce sinirlari icindeki acik-yesil alanlardaki bakim calismalarini (sulama, gubreleme, budama, tirmiklama, ilaclama, cim bicme… vb.) uygulama zamanlari ve uygulama yontemleri acisindan Avrupa ve Turkiye standartlariyla karsilastirmak ve eksiklikleri tespit ederek, cozum icin oneriler getirmektir.Calisma kapsaminda, genel anlamda bakim calismalari irdelenmis ve bulunan veriler Etimesgut olcegine indirgenmistir.Parklarin genel yapisi ve parklara iliskin olcutler, parklarda uygulanan bakim-onarim calismalari degerlendirilerek, 2 ana yontemle sonuca ulasilmistir. Arastirma sonucunda, bakim-onarim calismalarinin kimi zaman dogru isleyisinin yaninda, gecekondu bolgesi ve ikincil yasam alanlarinin bir arada bulundugu ilcede, kisi basina dusen yesil alan miktarini arttirmak icin calismalara devam edildigi, ancak kisa vadeli dusunulerek tesis edilen yesil alanlarda cevresel etkenler, bilincsiz calisanlar, vandalizm, yetersiz kontrol, ihale sistemindeki yanlisliklara bagli olarak bakim-onarim calismalarinin olumsuz yonleri tespit edilmistir. Bakim calismalarinda basari ve surdurulebilirligi saglamak icin gunubirlik cozumlerin yerine, kalici cozum onerileri getirilmistir.
A single chip iΔ-Σ ADC with a built-in variable gain stage and DAC with a charge integrating subconverter for a 5 V 9600-b/s modem

A 12-b, 19.2-ksamples/s /spl Delta/-/spl Sigma/ A/D and D/A converter for a 9600-b/s facsimile modem analog front end is described. In the proposed /spl Delta/-/spl Sigma/ ADC, the reference voltage is varied to adjust the signal gain, thus, eliminating the need of a variable gain amplifier. The /spl Delta/-/spl Sigma/ DAC uses a 4-b charge integrating subconverter which is insensitive to process variations. >
Consumer confidence indices and stock markets' meltdowns

Consumer confidence indices (CCIs) are a closely monitored barometer of countries' economic health and an informative forecasting tool. Using European and US data, we provide a case study of the two recent stock market meltdowns (the post-dotcom bubble correction of 2000–2002 and the 2007–2009 decline at the beginning of the financial crisis) to contribute to the discussion on their appropriateness as proxies for stock markets' investor sentiment. Investor sentiment should positively covary with stock market movements [DeLong, Shleifer, Summers, and Waldmann. 1990. “Noise Trader Risk in Financial Markets. ” Journal of Political Economy 98 (4): 703–738]; however, we find that the CCI–stock market relationship is not universally positive. We also do not find support for the information effect documented in the previous literature, but identify a more subtle relationship between consumer expectations about future household finances and stock market fluctuations.
hynet: An Optimal Power Flow Framework for Hybrid AC/DC Power Systems

High-voltage direct current (HVDC) systems are increasingly incorporated into today's AC power grids, necessitating optimal power flow (OPF) tools for the analysis, planning, and operation of such hybrid systems. To this end, we introduce hynet, a Python-based open-source OPF framework for hybrid AC/DC grids with point-to-point and radial multi-terminal HVDC systems. hynet's design promotes ease of use and extensibility, which is supported by the particular mathematical model and software design presented in this paper. The system model features a unified representation of AC and DC subgrids as well as a concise and flexible converter model, which enable the compact description of a hybrid AC/DC power system and its OPF problem. To support convex relaxation based OPF solution techniques, a state space relaxation is introduced to obtain a unified OPF formulation that is analogous to the OPF of AC power systems. This enables the direct generalization of relaxation-related results for AC grids to hybrid AC/DC grids, which is shown for the semidefinite and second-order cone relaxation as well as associated results on exactness and locational marginal prices. Finally, hynet's object-oriented software design is discussed, which provides extensibility via inheritance and standard design patterns, and its robust and competitive performance is illustrated with case studies.
Psychosocial Support in Adolescents and Young Adults With Cancer

Abstract Various forms of psychosocial support have been suggested in working with adolescents and young adults (AYAs) as they attempt to cope with cancer, including peer-based interventions, individual psychoeducational counseling, and skill-based interventions. More recently, modern electronic applications created technology-based ways to deliver information and support and have grown in popularity to satisfy AYA needs for information and support. Such support should be offered routinely rather than in a response to a crisis. This article focuses on psychosocial interventions for AYAs aged 15 to 39 years with cancer at diagnosis, during treatment, and shortly after.
Obstructive sleep apnea and dyslipidemia: from animal models to clinical evidence

Lipid metabolism deregulation constitutes the pathogenic basis for the development of atherosclerosis and justifies a high incidence of cardiovascular-related morbidity and mortality. Some data suggest that dyslipidemia may be associated with sleep-disordered breathing, mainly obstructive sleep apnea (OSA), due to alterations in fundamental biochemical processes, such as intermittent hypoxia (IH). The aim of this systematic review was to identify and critically evaluate the current evidence supporting the existence of a possible relationship between OSA and alterations in lipid metabolism. Much evidence shows that, during the fasting state, OSA and IH increase lipid delivery from the adipose tissue to the liver through an up-regulation of the sterol regulatory element-binding protein-1 and stearoyl-CoA desaturase-1, increasing the synthesis of cholesterol esters and triglycerides. In the postprandial state, lipoprotein clearance is delayed due to lower lipoprotein lipase activity, probably secondary to IH-up-regulation of angiopoietin-like protein 4 and decreased activity of the peroxisome proliferator-activated receptor alpha. Moreover, oxidative stress can generate dysfunctional oxidized lipids and reduce the capacity of high-density lipoproteins (HDL) to prevent low-density lipoprotein (LDL) oxidation. In the clinical field, several observational studies and a meta-regression analysis support the existence of a link between OSA and dyslipidemia. Although there is evidence of improved lipid profile after apnea-hypopnea suppression with continuous positive airway pressure (CPAP), the majority of the data come from observational studies. In contrast, randomized controlled trials evaluating the effects of CPAP on lipid metabolism present inconclusive results and two meta-analyses provide contradictory evidence.
Review of Application of Optimization Techniques in Smart Grids

The smart grids can optimize the use of various generation sources and reduce cost. With new developments in renewable energy, distributed generation, the traditional power grids are being converted to smart grids. This paper provides a survey of the literature that focuses on the use of optimization techniques in SG, prominently in generation, transmission and distribution systems. It is anticipated that this paper will help in finding future research scopes and strategies efforts for improving the SG.
The Recovery Process and People with Serious Mental Illness Living in the Community

Abstract Several trends have moved the concept of recovery to the forefront of mental health policy and service delivery for people with serious mental illnesses. This article describes an occupational therapy based model to examine recovery using a four-stage approach. The model demonstrates the complexity of recovery as a construct and emphasizes the value of quantitative data for program planning and evaluation purposes and need for a qualitative measure to assure adherence to the individualized nature of recovery as a process.
Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis

Change detection has been a challenging visual task due to the dynamic nature of real-world scenes. Good performance of existing methods depends largely on prior background images or a long-term observation. These methods, however, suffer severe degradation when they are applied to detection of instantaneously occurred changes with only a few preceding frames provided. In this paper, we exploit spatio-temporal convolutional networks to address this challenge, and propose a novel retrospective convolution, which features efficient change information extraction between the current frame and frames from historical observation. To address the problem of foreground-specific over-fitting in learning-based methods, we further propose a data augmentation method, named static sample synthesis, to guide the network to focus on learning change-cued information rather than specific spatial features of foreground. Trained end-to-end with complex scenarios, our framework proves to be accurate in detecting instantaneous changes and robust in combating diverse noises. Extensive experiments demonstrate that our proposed method significantly outperforms existing methods.
Response to: The GPRC5A frameshift variant c.183del is not associated with increased breast cancer risk in BRCA1 mutation carriers

Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland Department of Tumor Growth Biology, N.N. Petrov Institute of Oncology, Saint Petersburg, Russia Department of Medical Genetics, Saint Petersburg Pediatric Medical University, Saint Petersburg, Russia Department of Oncology, I.I. Mechnikov North-Western Medical University, Saint Petersburg, Russia Department of Oncology, Saint Petersburg State University, Saint Petersburg, Russia
ParsRec: A Novel Meta-Learning Approach to Recommending Bibliographic Reference Parsers

Bibliographic reference parsers extract machine-readable metadata such as author names, title, journal, and year from bibliographic reference strings. To extract the metadata, the parsers apply heuristics or machine learning. However, no reference parser, and no algorithm, consistently gives the best results in every scenario. For instance, one tool may be best in extracting titles in ACM citation style, but only third best when APA is used. Another tool may be best in extracting English author names, while another one is best for noisy data (i.e. inconsistent citation styles). In this paper, which is an extended version of our recent RecSys poster, we address the problem of reference parsing from a recommender-systems and meta-learning perspective. We propose ParsRec, a meta-learning based recommender-system that recommends the potentially most effective parser for a given reference string. ParsRec recommends one out of 10 open-source parsers: Anystyle-Parser, Biblio, CERMINE, Citation, Citation-Parser, GROBID, ParsCit, PDFSSA4MET, Reference Tagger, and Science Parse. We evaluate ParsRec on 105k references from chemistry. We propose two approaches to meta-learning recommendations. The first approach learns the best parser for an entire reference string. The second approach learns the best parser for each metadata type in a reference string. The second approach achieved a 2.6% increase in F1 (0.909 vs. 0.886) over the best single parser (GROBID), reducing the false positive rate by 20.2% (0.075 vs. 0.094), and the false negative rate by 18.9% (0.107 vs. 0.132).
Detection Algorithm of Crossroad Traffic Accident Using the Sequence of Traffic Lights

This paper suggests the background image and the algorism of detecting an accident at crossroads by using the sequence of traffic light at crossroads, which is installed within the crossroads, in order to detect an accident within crossroads. A method of using the existing image contains a problem that the accident-detection ratio gets lower in a situation that noise occurs loudly given using new accident model, the confused situation, or sound source. This study used the accident detection by developing a filter of using the property of histogram in the sequence of traffic light at crossroads and the background image, in order to reduce misjudgment of an accident caused by external shadow, vehicle stoppage, vehicle headlight, and externally environmental influence. As a result of experimenting by acquiring 15 actual accident images in order to examine the performance of the suggested algorism, the accident was detected in all the 15 videos. Even as for a new accident model, the accident within crossroads could be detected.
Analytical solution for the size of the minimum dominating set in complex networks

Domination is the fastest-growing field within graph theory with a profound diversity and impact in real-world applications, such as the recent breakthrough approach that identifies optimized subsets of proteins enriched with cancer-related genes. Despite its conceptual simplicity, domination is a classical NP-complete decision problem which makes analytical solutions elusive and poses difficulties to design optimization algorithms for finding a dominating set of minimum cardinality in a large network. Here we derive for the first time an approximate analytical solution for the density of the minimum dominating set (MDS) by using a combination of cavity method and Ultra-Discretization (UD) procedure. The derived equation allows us to compute the size of MDS by only using as an input the information of the degree distribution of a given network.
Cancer-specific expression quantitative loci are affected by expression dysregulation

Expression quantitative trait loci (eQTLs) have been touted as the missing piece that can bridge the gap between genetic variants and phenotypes. Over the past decade, we have witnessed a sharp rise of effort in the identification and application of eQTLs. The successful application of eQTLs relies heavily on their reproducibility. The current eQTL databases such as Genotype-Tissue Expression (GTEx) were populated primarily with eQTLs deriving from germline single nucleotide polymorphisms and normal tissue gene expression. The novel scenarios that employ eQTL models for prediction purposes often involve disease phenotypes characterized by altered gene expressions. To evaluate eQTL reproducibility across diverse data sources and the effect of disease-specific gene expression alteration on eQTL identification, we conducted an eQTL study using 5178 samples from The Cancer Genome Atlas (TCGA). We found that the reproducibility of eQTLs between normal and tumor tissues was low in terms of the number of shared eQTLs. However, among the shared eQTLs, the effect directions were generally concordant. This suggests that the source of the gene expression (normal or tumor tissue) has a strong effect on the detectable eQTLs and the effect direction of the eQTLs. Additional analyses demonstrated good directional concordance of eQTLs between GTEx and TCGA. Furthermore, we found that multi-tissue eQTLs may exert opposite effects across multiple tissue types. In summary, our results suggest that eQTL prediction models need to carefully address tissue and disease dependency of eQTLs. Tissue-disease-specific eQTL databases can afford more accurate prediction models for future studies.
Clinical Predictors for Unsafe Direct Discharge Home Patients From Intensive Care Units

Purpose: To describe factors (demographics and clinical characteristics) that predict patients who are at an increased risk of adverse events or unplanned return visits to a health-care facility following discharge direct to home (DDH) from intensive care units (ICUs). Methods: Prospective cohort study of all adult patients who survived their stay in our medical–surgical–trauma ICU between February 2016 and 2017 and were discharged directly home. Patients were followed for 8 weeks postdischarge. Univariable and multivariable logistic regression analyses were performed to identify factors associated with adverse events or unplanned return visits to a health-care facility following DDH from ICU. Results: A total of 129 DDH patients were enrolled and completed the 8-week follow-up. We identified 39 unplanned return visits (URVs). There was 0% mortality at 8 weeks postdischarge. Eight potential predictors of hospital URVs (P < .2) were identified in the univariable analysis: prior substance abuse (odds ratio [OR] of URV of 2.50 [95% confidence interval: 1.08-5.80], hepatitis (OR: 6.92 [1.68-28.48]), sepsis (OR: 11.03 [1.19-102.29]), admission nine equivalents of nursing manpower score (NEMS) <24 (OR: 2.28 [1.03-5.04], no fixed address (OR: 22.9 [1.2-437.3]), ICU length of stay (LOS) <2 days (OR: 2.95 [1.28-6.78]), home discharge within London, Ontario (OR: 2.44 [1.00-5.92]), and left against medical advice (AMA; OR: 6.06 [2.04-17.98]). Conclusions: Our study identified 8 covariates that were potential predictors of URV: prior substance abuse, hepatitis, sepsis, admission NEMS <24, no fixed address, ICU LOS <2 days, home discharge within London, Ontario, and left AMA. The practice of direct discharges home from the ICU would benefit from adequately powered multicenter study in order to construct a clinical prediction model (that would require further testing and validation).
Time-series transcriptomic analysis of the kelp grouper Epinephelus moara in response to low salinity stress

ABSTRACT The Kelp grouper Epinephelus moara is one of the most widely consumed and economically important marine fish in China. The species can tolerate a wide range of salinity, but genomic resources are not available, and the molecular mechanisms underlying adaptation to salinity at the transcriptomic level remain largely unclear. In this study, the transcriptomic responses of the liver of E. moara under low salinity were investigated using the Illumina digital gene expression system. After de novo assembly, 499,356 transcripts were generated and contributed 445,068 unigenes. A total of 14, 19, 33 and 3101 genes were differentially expressed following exposure to low salinity stress for 2, 6, 24 and 48 h, respectively. Only two genes were differentially expressed in all groups. Four genes related to metabolism and ambient salinity adaption were randomly selected to validate the differentially expressed genes (DEGs) by real-time PCR. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to analyse the functional significance of DEGs, including those responding to salinity through diverse biological processes, cellular components, molecular functions, and pathways associated with metabolic and osmotic responses. This work provides new insight into the response to salinity challenges in E. moara, and the findings expand our knowledge of the molecular basis of metabolic regulation mechanisms in this species. Additionally, the transcriptional data provide a valuable resource for future molecular and genetic studies on E. moara.
TGF-β induces corneal endothelial senescence via increase of mitochondrial reactive oxygen species in chronic corneal allograft failure

The corneal endothelium (CE) dysfunction impairs optical transparency and leads to corneal allograft failure. Morphologically, CE cells are characterized by premature senescence at the late stage of corneal graft. However, the detailed molecular mechanisms are largely unknown. Here we found that transforming growth factor-β (TGF-β) is elevated in the CE of late graft failure. In addition, senescence-associated gene p21 and p16 are increased as well, which is consistent with their elevation upon TGF-β treatment in human corneal endothelial cell B4G12. Furthermore, TGF-β treatment leads to high positive ratio of SA-β-gal, indicating B4G12 cells undergo cellular senescence. Mechanistically, we demonstrated that TGF-β could induce mitochondrial ROS (mtROS) production and mtROS scavenger could rescue CE cell senescence upon TGF-β treatment. Our study provides new evidence that elevated TGF-β plays a crucial role in the CE cell senescence and loss in chronic corneal graft failure, which could be potential targets for clinical treatment.