Detection of natural structures and classification of HCI-HPR data using robust forward search algorithm

Purpose – The purpose of this paper is to proposes a forward search algorithm for detecting and identifying natural structures arising in human-computer interaction (HCI) and human physiological response (HPR) data. Design/methodology/approach – The paper portrays aspects that are essential to modelling and precision in detection. The methods involves developed algorithm for detecting outliers in data to recognise natural patterns in incessant data such as HCI-HPR data. The detected categorical data are simultaneously labelled based on the data reliance on parametric rules to predictive models used in classification algorithms. Data were also simulated based on multivariate normal distribution method and used to compare and validate the original data. Findings – Results shows that the forward search method provides robust features that are capable of repelling over-fitting in physiological and eye movement data. Research limitations/implications – One of the limitations of the robust forward search algorithm is that when the number of digits for residuals value is more than the expected size for stack flow, it normally yields an error caution; to counter this, the data sets are normally standardized by taking the logarithmic function of the model before running the algorithm. Practical implications – The authors conducted some of the experiments at individual residence which may affect environmental constraints. Originality/value – The novel approach to this method is the detection of outliers for data sets based on the Mahalanobis distances on HCI and HPR. And can also involve a large size of data with p possible parameters. The improvement made to the algorithm is application of more graphical display and rendering of the residual plot

A Control System for Detecting Emotions on Visual Interphase Stimulus

Complex dynamic contents of visual stimuli induce implicit reactions in a user. This leads to changes in physiological processes of the user which is referred to as stress. Our goal is to model and produce a system that represents the mechanical interactions of the body and eye movement behavior. We are particularly concerned with the skin conductance response (SCR) and eye fixations to visual stimulus and build a dynamic system that detects stress and its correlates to visual widgets. The process consists of the following modules: (1) a hypothesis generator for suggesting possible structural changes that result from the direct interaction with visual stimulus, (2) an information source for responding to operator querying about users’ interactive and physiological processes, and (3) a continuous system simulator for simulating and illustrating physiological reactions during interaction. This model serves as an infrastructure for modeling physiological processes and could be of benefit in usability laboratory, web developers, and designers of interactive systems, enabling evaluators to visualize interface as a better access to identifying areas that cause stress to users

The link between energy consumption and economic growth: Evidence from transition economies (1985-2017)

Economies around the world are on the move to ensure sustainable economic development and a clean atmosphere through the use of renewable energy sources. The importance of energy to all human aspects has been spiking as the world keeps evolving. This has made an exciting field of research to major academicians towards providing sound measures to governments in areas of developing the society at large. Using a systematic method of literature review, this work analyses the energy trend, as well as the energy-growth nexus research, carried out in transition economies. The concluding result after the systematic review shows that (14%) of the study confirms the growth hypothesis, (54%) feedback hypothesis, (9%) neutrality hypothesis, and (23%) conservation hypothesis

Impact of Energy Consumption on Industrial Growth in a Transition Economy: Evidence from Nigeria

This research investigates the impact of energy consumption on industrial growth. Variables used are; manufacturing vale added (dependent variable, electricity consumption, per capita income, exchange rate, import, and export by using yearly time series data from 1985 through 2017 in Nigeria. The OLS method of egression was used to estimate the equation in the period under review. Unit root test, Co-integration test and Granger causality were carried out to test for stationarity, long run relationship, and causal relationship, respectively. Results show a negative and insignificant relationship between electricity consumption and industrial growth. The unit root test shows that all variables are integrated of order one except for the exchange rate, which is stationary at level. The Co-integration test indicates that there exists the presence of long-run relationships. The granger causality indicates the growth hypothesis from industries in Nigeria. Generally, this paper stresses the dangers of inadequate electricity supply in the functioning of industries and businesses, which further worsens overall growth in the Nigerian economy

Optimized Inhibitors of MDM2 via an Attempted Protein-Templated Reductive Amination

Innovative and efficient hit-identification techniques are required to accelerate drug discovery. Protein-templated fragment ligations represent a promising strategy in early drug discovery, enabling the target to assemble and select its binders from a pool of building blocks. Development of new protein-templated reactions to access a larger structural diversity and expansion of the variety of targets to demonstrate the scope of the technique are of prime interest for medicinal chemists. Herein, we present our attempts to use a protein-templated reductive amination to target protein-protein interactions (PPIs), a challenging class of drug targets. We address a flexible pocket, which is difficult to achieve by structure-based drug design. After careful analysis we did not find one of the possible products in the kinetic target-guided synthesis (KTGS) approach, however subsequent synthesis and biochemical evaluation of each library member demonstrated that all the obtained molecules inhibit MDM2. The most potent library member (Ki=0.095 μm) identified is almost as active as Nutlin-3, a potent inhibitor of the p53-MDM2 PPI

Determinants of stillbirth from two observational studies investigating deliveries in Kano, Nigeria

Background: Stillbirths are a poignant representation of global inequality. Nigeria is documented to have the second highest rate; yet, the reporting system is inadequate in most Nigerian healthcare facilities. The aim was to identify the determinants of stillbirth among deliveries in the Murtala Muhammad Specialist Hospital (MMSH), Kano, Nigeria. Methods: Two study designs were used: a case-control study (S1) and a prospective cohort study (S2). Both studies were carried out at the MMSH. For S1, stillbirths were retrospectively matched to a livebirth by time (target of 24 hours' time variation) to establish a case-control study with a 1:1 ratio. Eligibility into S2 included all mothers who were presented at the MMSH in labour regardless of birth outcome. Both were based on recruitment durations, not sample sizes (3 months and 2 months, respectively, 2017–2018). The demographic and clinical data were collected through paper-based questionnaires. Univariable logistic regression was used. Multivariable logistic regression was used to explore relationships between area type and other specific factors. Findings: Stillbirth incidence in S2 was 180/1,000 births. Stillbirth was associated with the following factors; no maternal education, previous stillbirth(s), prematurity, living in both semi-rural and rural settings, and having extended time periods between rupture of membranes and delivery. Findings of the multivariable analysis (S1 and S2) indicated that the odds of stillbirth, for those living in a rural area, were further exacerbated in those mothers who had no education, lived in a shack, or had any maternal disease. Interpretation: This research identifies the gravity of this situation in this area and highlights the need for action. Further understanding of some of the findings and exploration into associations are required to inform intervention development. Funding: This collaboration was partially supported by funding from Health and Care Research Wales

Coffee and its waste repel gravid Aedes albopictus females and inhibit the development of their embryos

Background Dengue is a prevalent arboviral disease and the development of insecticide resistance among its vectors impedes endeavors to control it. Coffee is drunk by millions of people daily worldwide, which is associated with the discarding of large amounts of waste. Coffee and its waste contain large amounts of chemicals many of which are highly toxic and none of which have a history of resistance in mosquitoes. Once in solution, coffee is brownish in colour, resembling leaf infusion, which is highly attractive to gravid mosquitoes. To anticipate the environmental issues related to the increasing popularity of coffee as a drink, and also to combat insecticide resistance, we explored the deterrence potentials of coffee leachates against the ovipositing and embryonic stages of the dengue vector, Aedes albopictus. Methods In a series of choice, no-choice, and embryo toxicity bioassays, we examined changes in the ovipositional behaviours and larval eclosion of Ae. albopictus in response to coffee extracts at different concentrations. Results Oviposition responses were extremely low when ovicups holding highly concentrated extract (HCE) of coffee were the only oviposition sites. Gravid females retained increased numbers of mature eggs until 5 days post-blood feeding. When provided an opportunity to oviposit in cups containing coffee extracts and with water, egg deposition occurred at lower rates in those containing coffee, and HCE cups were far less attractive to females than those containing water only. Females that successfully developed in a coffee environment preferentially oviposited in such cups when in competition with preferred oviposition sites (water cups), but this trait did not continue into the fourth generation. Larval eclosion occurred at lower rates among eggs that matured in a coffee environment, especially among those that were maintained on HCE-moistened substrates. Conclusions The observations of the present study indicate a pronounced vulnerability of Ae. albopictus to the presence of coffee in its habitats during the early phases of its life cycle. The observations that coffee repels gravid females and inhibits larval eclosion provide novel possibilities in the search for novel oviposition deterrents and anti-larval eclosion agents against dengue vectors.This work was supported by funds (No. 096010) from the Central Research Institute of Fukuoka University and “Long Term Research Grant (LRGS) for Infectious Diseases, 2011 – 2014, Ministry of Higher Education, Malaysia” and USM (304/Pbiology/650575/U112)

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

Background Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25–30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. Methods We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. Results Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. Conclusions Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

BACKGROUND: Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome.METHODS: We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants.RESULTS: Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving.CONCLUSIONS: Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.</p

Neonatal sepsis and mortality in low-income and middle-income countries from a facility-based birth cohort: an international multisite prospective observational study

Background Neonatal sepsis is a primary cause of neonatal mortality and is an urgent global health concern, especially within low-income and middle-income countries (LMICs), where 99% of global neonatal mortality occurs. The aims of this study were to determine the incidence and associations with neonatal sepsis and all-cause mortality in facility-born neonates in LMICs. Methods The Burden of Antibiotic Resistance in Neonates from Developing Societies (BARNARDS) study recruited mothers and their neonates into a prospective observational cohort study across 12 clinical sites from Bangladesh, Ethiopia, India, Pakistan, Nigeria, Rwanda, and South Africa. Data for sepsis-associated factors in the four domains of health care, maternal, birth and neonatal, and living environment were collected for all mothers and neonates enrolled. Primary outcomes were clinically suspected sepsis, laboratory-confirmed sepsis, and all-cause mortality in neonates during the first 60 days of life. Incidence proportion of livebirths for clinically suspected sepsis and laboratory-confirmed sepsis and incidence rate per 1000 neonate-days for all-cause mortality were calculated. Modified Poisson regression was used to investigate factors associated with neonatal sepsis and parametric survival models for factors associated with all-cause mortality. Findings Between Nov 12, 2015 and Feb 1, 2018, 29 483 mothers and 30 557 neonates were enrolled. The incidence of clinically suspected sepsis was 166·0 (95% CI 97·69–234·24) per 1000 livebirths, laboratory-confirmed sepsis was 46·9 (19·04–74·79) per 1000 livebirths, and all-cause mortality was 0·83 (0·37–2·00) per 1000 neonate-days. Maternal hypertension, previous maternal hospitalisation within 12 months, average or higher monthly household income, ward size (>11 beds), ward type (neonatal), living in a rural environment, preterm birth, perinatal asphyxia, and multiple births were associated with an increased risk of clinically suspected sepsis, laboratory-confirmed sepsis, and all-cause mortality. The majority (881 [72·5%] of 1215) of laboratory-confirmed sepsis cases occurred within the first 3 days of life. Interpretation Findings from this study highlight the substantial proportion of neonates who develop neonatal sepsis, and the high mortality rates among neonates with sepsis in LMICs. More efficient and effective identification of neonatal sepsis is needed to target interventions to reduce its incidence and subsequent mortality in LMICs. Funding Bill & Melinda Gates Foundation