Miracle-dz/UniFAR-FTUs huggingface dataset:
START (screening tool to alert doctors to the right treatment)--an evidence-based screening tool to detect prescribing omissions in elderly patients.

BACKGROUND Inappropriate prescribing encompasses acts of commission i.e. giving drugs that are contraindicated or unsuitable, and acts of omission i.e. failure to prescribe drugs when indicated due to ignorance of evidence base or other irrational basis e.g. ageism. There are considerable published data on the prevalence of inappropriate prescribing; however, there are no recent published data on the prevalence of acts of omission. The aim of this study was to calculate the prevalence of acts of prescribing omission in a population of consecutively hospitalised elderly people. METHODS A screening tool (screening tool to alert doctors to the right treatment acronym, START), devised from evidence-based prescribing indicators and arranged according to physiological systems was prepared and validated for identifying prescribing omissions in older adults. Data on active medical problems and prescribed medicines were collected in 600 consecutive elderly patients admitted from the community with acute illness to a teaching hospital. On identification of an omitted medication, the patient's medical records were studied to look for a valid reason for the prescribing omission. RESULTS Using the START list, we found one or more prescribing omissions in 57.9% of patients. In order of prevalence, the most common prescribing omissions were: statins in atherosclerotic disease (26%), warfarin in chronic atrial fibrillation (9.5%), anti-platelet therapy in arterial disease (7.3%) and calcium/vitamin D supplementation in symptomatic osteoporosis (6%). CONCLUSION Failure to prescribe appropriate medicines is a highly prevalent problem among older people presenting to hospital with acute illness. A validated screening tool (START) is one method of systematically identifying appropriate omitted medicines in clinical practice.
Tuberculosis incidence among contacts of active pulmonary tuberculosis.

BACKGROUND Treatment of latent tuberculosis (TB) infection (LTBI) in Brazil is recommended only in the case of contacts of pulmonary smear-positive TB patients aged<or=15 years with a tuberculin skin test (TST)>or=10 mm and no previous bacille Calmette-Guérin (BCG) vaccination or with a TST>or=15 mm regardless of previous BCG vaccination. OBJECTIVE To evaluate the 2-year incidence and predictors of TB among contacts who did not meet the Brazilian criteria for LTBI treatment. DESIGN Retrospective cohort study. Contacts aged between 12 and 15 years and those aged>or=15 years who did not meet the Brazilian criteria for LTBI treatment were enrolled in the study. RESULTS TB incidence was 3.2% (22/667), with an estimated TB rate of 1649 per 100000 population. Risk of TB was greater among the 349 contacts with TST>or=5 mm (5.4%) compared to the 318 contacts with TST<5 mm (0.9%; RR 6.04, 95%CI 1.7-20.6). CONCLUSION The high incidence of TB among contacts who did not meet the Brazilian criteria for LTBI treatment strongly suggests that these criteria should be reviewed. Furthermore, even among BCG-vaccinated contacts, TST induration>or=5 mm was the only variable that predicted the development of TB disease within 2years.
ΣΔ ADC Design Considerations for an UMTS Receiver

This paper gives an insight on how to derive the minimum required specifications both for the anti-aliasing filter (AAF) and the analog-to-digital converter (ADC) in the case of an UMTS receiver. Based on the receiver specifications, we come up with a design plan for both discrete time ΣΔ ADC as well as for a continuous time ΣΔ ADC.
Environmental controls on the distribution and diversity of lentic Chironomidae (Insecta: Diptera) across an altitudinal gradient in tropical South America

Abstract To predict the response of aquatic ecosystems to future global climate change, data on the ecology and distribution of keystone groups in freshwater ecosystems are needed. In contrast to mid‐ and high‐latitude zones, such data are scarce across tropical South America (Neotropics). We present the distribution and diversity of chironomid species using surface sediments of 59 lakes from the Andes to the Amazon (0.1–17°S and 64–78°W) within the Neotropics. We assess the spatial variation in community assemblages and identify the key variables influencing the distributional patterns. The relationships between environmental variables (pH, conductivity, depth, and sediment organic content), climatic data, and chironomid assemblages were assessed using multivariate statistics (detrended correspondence analysis and canonical correspondence analysis). Climatic parameters (temperature and precipitation) were most significant in describing the variance in chironomid assemblages. Temperature and precipitation are both predicted to change under future climate change scenarios in the tropical Andes. Our findings suggest taxa of Orthocladiinae, which show a preference to cold high‐elevation oligotrophic lakes, will likely see range contraction under future anthropogenic‐induced climate change. Taxa abundant in areas of high precipitation, such as Micropsectra and Phaenopsectra, will likely become restricted to the inner tropical Andes, as the outer tropical Andes become drier. The sensitivity of chironomids to climate parameters makes them important bio‐indicators of regional climate change in the Neotropics. Furthermore, the distribution of chironomid taxa presented here is a vital first step toward providing urgently needed autecological data for interpreting fossil chironomid records of past ecological and climate change from the tropical Andes.
Cold shock response and low temperature adaptation in psychrotrophic bacteria.

Psychrotrophic bacteria are capable of developing over a wide temperature range and they can grow at temperatures close to or below freezing. This ability requires specific adaptative strategies in order to maintain membrane fluidity, the continuance of their metabolic activities, and protein synthesis at low temperature. A cold-shock response has been described in several psychrotrophic bacteria, which is somewhat different from that in mesophilic microorganisms: (i) the synthesis of housekeeping proteins is not repressed following temperature downshift and they are similarly expressed at optimal and low temperatures (ii) cold-shock proteins or Csps are synthesized, the number of which increases with the severity of the shock (iii) a second group of cold-induced proteins, i.e. the cold acclimation proteins or Caps, comparable with Csps are continuously synthesized during prolonged growth at low temperature. Homologues to CspA, the major cold-shock protein in E. coli, have been described in various psychrotrophs, but unlike their mesophilic counterparts, they belong to the group of Caps. Although they have been poorly studied, Caps are of particular importance since they differentiate psychrotrophs from mesophiles, and they are probably one of the key determinant that allow life at very low temperature.
Gene-Based Analysis of Regionally Enriched Cortical Genes in GWAS Data Sets of Cognitive Traits and Psychiatric Disorders

Background Despite its estimated high heritability, the genetic architecture leading to differences in cognitive performance remains poorly understood. Different cortical regions play important roles in normal cognitive functioning and impairment. Recently, we reported on sets of regionally enriched genes in three different cortical areas (frontomedial, temporal and occipital cortices) of the adult rat brain. It has been suggested that genes preferentially, or specifically, expressed in one region or organ reflect functional specialisation. Employing a gene-based approach to the analysis, we used the regionally enriched cortical genes to mine a genome-wide association study (GWAS) of the Norwegian Cognitive NeuroGenetics (NCNG) sample of healthy adults for association to nine psychometric tests measures. In addition, we explored GWAS data sets for the serious psychiatric disorders schizophrenia (SCZ) (n = 3 samples) and bipolar affective disorder (BP) (n = 3 samples), to which cognitive impairment is linked. Principal Findings At the single gene level, the temporal cortex enriched gene RAR-related orphan receptor B (RORB) showed the strongest overall association, namely to a test of verbal intelligence (Vocabulary, P = 7.7E-04). We also applied gene set enrichment analysis (GSEA) to test the candidate genes, as gene sets, for enrichment of association signal in the NCNG GWAS and in GWASs of BP and of SCZ. We found that genes differentially expressed in the temporal cortex showed a significant enrichment of association signal in a test measure of non-verbal intelligence (Reasoning) in the NCNG sample. Conclusion Our gene-based approach suggests that RORB could be involved in verbal intelligence differences, while the genes enriched in the temporal cortex might be important to intellectual functions as measured by a test of reasoning in the healthy population. These findings warrant further replication in independent samples on cognitive traits.
Neural Representations and Mechanisms for the Performance of Simple Speech Sequences

Speakers plan the phonological content of their utterances before their release as speech motor acts. Using a finite alphabet of learned phonemes and a relatively small number of syllable structures, speakers are able to rapidly plan and produce arbitrary syllable sequences that fall within the rules of their language. The class of computational models of sequence planning and performance termed competitive queuing models have followed K. S. Lashley [The problem of serial order in behavior. In L. A. Jeffress (Ed.), Cerebral mechanisms in behavior (pp. 112–136). New York: Wiley, 1951] in assuming that inherently parallel neural representations underlie serial action, and this idea is increasingly supported by experimental evidence. In this article, we developed a neural model that extends the existing DIVA model of speech production in two complementary ways. The new model includes paired structure and content subsystems [cf. MacNeilage, P. F. The frame/content theory of evolution of speech production. Behavioral and Brain Sciences, 21, 499–511, 1998] that provide parallel representations of a forthcoming speech plan as well as mechanisms for interfacing these phonological planning representations with learned sensorimotor programs to enable stepping through multisyllabic speech plans. On the basis of previous reports, the model's components are hypothesized to be localized to specific cortical and subcortical structures, including the left inferior frontal sulcus, the medial premotor cortex, the basal ganglia, and the thalamus. The new model, called gradient order DIVA, thus fills a void in current speech research by providing formal mechanistic hypotheses about both phonological and phonetic processes that are grounded by neuroanatomy and physiology. This framework also generates predictions that can be tested in future neuroimaging and clinical case studies.
Cloud Service Brokerage: A systematic literature review using a software development lifecycle

Cloud Service Brokerage (CSB) is an emerging technology that has become popular with cloud computing. CSB is a middleman providing value added services, developed using standard software development lifecycle, from cloud providers to consumers. This paper provides a systematic literature review on this topic, covering 41 publications from 2009 to 2015. The paper aims to provide an overview of CSB research status, and give suggestions on how CSB research should proceed. A descriptive analysis reveals a lack of contributions from the Information Systems discipline. A software development lifecycle analysis uncovers a severe imbalance of research contributions across the four stages of software development: design, develop, deploy, and manage. The majority of research contributions are geared toward the design stage with a minimal contribution in the remaining stages. As such, we call for a balanced research endeavor across the cycle given the equal importance of each stage within the CSB paradigm.
Analysis of rare variants in the CFH gene in patients with the cuticular drusen subtype of age-related macular degeneration

Purpose Age-related macular degeneration (AMD) and cuticular drusen (CD), a clinical subtype of AMD, have been linked to genetic variants in the complement factor H (CFH) gene. In this study, we aimed to investigate the frequency of rare variants in the CFH gene in 180 cases with CD. In addition, we aimed to determine the frequency of a previously reported rare, highly penetrant CFH variant (p.Arg1210Cys) in a Dutch-German non-CD-type AMD case-control cohort, and to describe the phenotype of patients carrying the p.Arg1210Cys variant. Methods Study subjects were selected from the European Genetic Database (EUGENDA), a joint AMD database of the Radboud University Medical Centre and the University Hospital of Cologne, and graded at the Cologne Image Reading Centre and Laboratory (CIRCL). Additionally, two CD cases were recruited from the VU Medical Centre in Amsterdam. The CFH gene was analyzed in 180 CD cases with Sanger sequencing. All identified variants were analyzed for potential damaging effects with prediction software tools Sorting Intolerant from Tolerant (SIFT) and Polymorphism Phenotyping (PolyPhen). In addition, we genotyped the p.Arg1210Cys variant in 813 non-CD type AMD cases and 1175 controls. Results Sequencing identified 11 rare, heterozygous missense variants, one frameshift variant, and one splice acceptor site variant in 16 CD cases. The p.Arg1210Cys variant was identified in two CD cases but was not identified in our Dutch-German non-CD-type AMD case-control cohort. Conclusions The present study identified the presence of rare variants in the CFH gene in 16 (8.8%) of 180 patients with the CD subtype of AMD. The carriers of rare CFH variants displayed a significantly earlier age at onset than non-carriers (p=0.016). The rare missense variant p.Arg1210Cys was identified in two CD cases, but was not detected in 813 non-CD type AMD cases or in the 1,175 controls of our Dutch-German cohort. The current study suggests that the p.Arg1210Cys variant may be restricted to a subset of patients with the CD subtype of AMD. Detailed clinical phenotyping, including fluorescein angiography, of patients with AMD carrying the p.Arg1210Cys variant in other cohorts is required to confirm this finding.
Comparison of IPSCs Evoked by Spiny and Fast-Spiking Neurons in the Neostriatum

Most neurons in the neostriatum are GABAergic spiny projection neurons with extensive local axon collaterals innervating principally other spiny projection neurons. The other source of GABAergic inputs to spiny neurons derives from a small number of interneurons, of which the best characterized are the parvalbumin-containing, fast-spiking interneurons. Spiny neuron collateral inhibition was not demonstrated until recently, because the IPSPs recorded at the soma are surprisingly small. In contrast, interneuronal inhibition was readily detected, comprising much larger IPSPs. Here, we report the application of quantal analysis and compartmental modeling to compare and contrast IPSCs in spiny neurons originating from axon collaterals and interneurons. The results indicate that individual release sites at spiny and interneuron synapses have similar quantal sizes and baseline release probabilities. Interneuronal unitary IPSCs are several times larger because of their proximal location on the neuron and because they have a larger number of transmitter release sites. Despite the small amount of current they can deliver to the soma, spiny cell collateral synapses had moderately high baseline release probabilities (0.5-0.9), suggesting that they are not weak because of some form of depression or modulation. The size of unitary collateral synaptic currents increased monotonically during development. These results argue against models of competitive inhibition in neostriatum, including those in which competitive inhibition is transiently effective during development and learning, and suggest a different role for the spiny cell axon collaterals.
A Survey Of Effort Estimation Techniques For The Software Development

: Effort estimation at the early stage of the software development is one of the most challenging parts of any organization. Many organization use different techniques to evaluate effort required for producing software, at the different levels of software life cycle model. There are various models like COCOMO, COCOMO II, Putnam model that have already used to estimate the software effort for projects. Researchers have proposed many new models to evaluate Effort. The objective of this paper is to compare Putnam model, COCOMO, and ANN-COCOMO and find out which technique give more accurate results.
The algorithmic aspects of the regularity lemma

The regularity lemma of Szemeredi (1978) is a result that asserts that every graph can be partitioned in a certain regular way. This result has numerous applications, but its known proof is not algorithmic. The authors first demonstrate the computational difficulty of finding a regular partition; they show that deciding if a given partition of an input graph satisfies the properties guaranteed by the lemma is co-NP-complete. However, they also prove that despite this difficulty the lemma can be made constructive; they show how to obtain, for any input graph, a partition with the properties guaranteed by the lemma, efficiently. The desired partition, for an n-vertex graph, can be found in time O(M(n)), where M(n)=O(n/sup 2.376/) is the time needed to multiply two n by n matrices with 0,1-entries over the integers. The algorithm can be parallelized and implemented in NC/sup 1/. <<ETX>>
Conversations about emotion in high-risk dyads

Early emotional understanding is fostered by mother–child conversation in which mothers elaboratively enhance children's understanding. Little is known of the broader relational and risk factors influencing maternal discourse style, how discourse content and quality are associated with children's emotion language, and how these predict emotion understanding. In this longitudinal study of a high-risk sample, attachment security and family risks were assessed when children were 2 years old. One year later, observations of mother–child emotion conversation yielded measures of maternal discourse content and quality, and children's emotion words and emotion labels. Child emotion understanding was independently assessed one year later as well. Central findings were: (1) content and quality of maternal discourse was negatively related to family risk factors and positively associated with secure attachment; (2) child emotion language in conversation was positively associated with secure attachment beyond the effects of child language and maternal discourse content; and (3) differences in emotion language ability predicted children's emotion understanding.
A New Adaptive Congestion Control Mechanism for the Internet Based on RED

One of the main challenges in the internet backbone is to provide an adequate quality of service (QoS) and this can be done by either adopting a suitable buffer management method or by QoS routing. One of the popular buffer management algorithms used is random early detection (RED) which falls into the category of active queue management (AQM) algorithms. There are many variant algorithms based on RED including adaptive RED and in this paper a new AQM algorithm which depends on changing the maximum dropping probability in a way that has been shown by simulation to have a similar throughput and lower delay than either RED or adaptive RED is proposed.
Possible Mechanism of Action of the Antiallergic Effect of an Aqueous Extract of Heliotropium indicum L. in Ovalbumin-Induced Allergic Conjunctivitis

Heliotropium indicum is used traditionally as a remedy for conjunctivitis in Ghana. This study therefore evaluated the antiallergic potential of an aqueous whole plant extract of Heliotropium indicum (HIE) in ovalbumin-induced allergic conjunctivitis and attempted to predict its mode of action. Clinical scores for allergic conjunctivitis induced by intraperitoneal ovalbumin sensitization (100 : 10 μg OVA/Al(OH)3 in phosphate-buffered saline [PBS]) and topical conjunctival challenge (1.5 mg OVA in 10 μL PBS) in Dunkin-Hartley guinea pigs were estimated after a week's daily treatment with 30–300 mg kg−1 HIE, 30 mg kg−1 prednisolone, 10 mg kg−1 chlorpheniramine, or 10 mL kg−1 PBS. Ovalbumin-specific IgG and IgE and total IgE in serum were estimated using Enzyme-Linked Immunosorbent Assay. Histopathological assessment of the exenterated conjunctivae was also performed. The 30 and 300 mg kg−1 HIE treatment resulted in a significantly (p ≤ 0.001) low clinical score of allergic conjunctivitis. Ovalbumin-specific IgG and IgE as well as total serum IgE also decreased significantly (p ≤ 0.01–0.001). The conjunctival tissue in HIE treated guinea pigs had mild mononuclear infiltration compared to the PBS-treated ones, which had intense conjunctival tissue inflammatory infiltration. HIE exhibited antiallergic effect possibly by immunomodulation or immunosuppression.
Deep Learning Scaling is Predictable, Empirically

Deep learning (DL) creates impactful advances following a virtuous recipe: model architecture search, creating large training data sets, and scaling computation. It is widely believed that growing training sets and models should improve accuracy and result in better products. As DL application domains grow, we would like a deeper understanding of the relationships between training set size, computational scale, and model accuracy improvements to advance the state-of-the-art. This paper presents a large scale empirical characterization of generalization error and model size growth as training sets grow. We introduce a methodology for this measurement and test four machine learning domains: machine translation, language modeling, image processing, and speech recognition. Our empirical results show power-law generalization error scaling across a breadth of factors, resulting in power-law exponents---the "steepness" of the learning curve---yet to be explained by theoretical work. Further, model improvements only shift the error but do not appear to affect the power-law exponent. We also show that model size scales sublinearly with data size. These scaling relationships have significant implications on deep learning research, practice, and systems. They can assist model debugging, setting accuracy targets, and decisions about data set growth. They can also guide computing system design and underscore the importance of continued computational scaling.