A game player expertise level classification system using electroencephalography (EEG)

The success and wider adaptability of smart phones has given a new dimension to the gaming industry. Due to the wide spectrum of video games, the success of a particular game depends on how efficiently it is able to capture the end users' attention. This leads to the need to analyse the cognitive aspects of the end user, that is the game player, during game play. A direct window to see how an end user responds to a stimuli is to look at their brain activity. In this study, electroencephalography (EEG) is used to record human brain activity during game play. A commercially available EEG headset is used for this purpose giving fourteen channels of recorded EEG brain activity. The aim is to classify a player as expert or novice using the brain activity as the player indulges in the game play. Three different machine learning classifiers have been used to train and test the system. Among the classifiers, naive Bayes has outperformed others with an accuracy of 88%, when data from all fourteen EEG channels are used. Furthermore, the activity observed on electrodes is statistically analysed and mapped for brain visualizations. The analysis has shown that out of the available fourteen channels, only four channels in the frontal and occipital brain regions show significant activity. Features of these four channels are then used, and the performance parameters of the four-channel classification are compared to the results of the fourteen-channel classification. It has been observed that support vector machine and the naive Bayes give good classification accuracy and processing time, well suited for real-time applications

Utilization of Palm Oil Mill Residue as Sustainable Pavement Materials: A Review

The advances in industrial technology have led to a major rise in the amount and forms of residue, especially during the processing of agricultural products. With the paradigm shift towards renewable energy and sustainability, there is much emphasis on biomass energy around the world which generates an immense volume of residues yearly. These residues are burgeoning issues because they are not effectively managed and utilized. Hence, one solution is utilizing them in the pavement industry. This article focuses on palm oil mill residues that are abundantly available and discarded in Malaysia. This study evaluates published works of literature relating to the utilization of these residues like the Palm Oil Fiber (POF), Palm Oil Fuel Ash (POFA), and Palm Oil Clinker (POC) and Palm Kernel Shell (PKS) in the pavement industry. The outcome of the review acknowledges the greater sustainability potential of these residues with affirmative and satisfactory performance via the result of numerous research work. Also, with a reduction in CO2-emission, low radioactivity, and heavy metal leaching level. Therefore, the review suggests more exploration and utilization of the residue in the pavement industry since it promotes safety and harness sustainability

Utilization of palm oil mill residue as sustainable pavement materials: A review

The advances in industrial technology have led to a major rise in the amount and forms of residue, especially during the processing of agricultural products. With the paradigm shift towards renewable energy and sustainability, there is much emphasis on biomass energy around the world which generates an immense volume of residues yearly. These residues are burgeoning issues because they are not effectively managed and utilized. Hence, one solution is utilizing them in the pavement industry. This article focuses on palm oil mill residues that are abundantly available and discarded in Malaysia. This study evaluates published works of literature relating to the utilization of these residues like the Palm Oil Fiber (POF), Palm Oil Fuel Ash (POFA), and Palm Oil Clinker (POC) and Palm Kernel Shell (PKS) in the pavement industry. The outcome of the review acknowledges the greater sustainability potential of these residues with affirmative and satisfactory performance via the result of numerous research work. Also, with a reduction in CO2-emission, low radioactivity, and heavy metal leaching level. Therefore, the review suggests more exploration and utilization of the residue in the pavement industry since it promotes safety and harness sustainability

APOE-ɛ4, white matter hyperintensities, and cognition in Alzheimer and Lewy body dementia

Objective To determine if APOE ε4 influences the association between white matter hyperintensities (WMH) and cognitive impairment in Alzheimer disease (AD) and dementia with Lewy bodies (DLB). Methods A total of 289 patients (AD = 239; DLB = 50) underwent volumetric MRI, neuropsychological testing, and APOE ε4 genotyping. Total WMH volumes were quantified. Neuropsychological test scores were included in a confirmatory factor analysis to identify cognitive domains encompassing attention/executive functions, learning/memory, and language, and factor scores for each domain were calculated per participant. After testing interactions between WMH and APOE ε4 in the full sample, we tested associations of WMH with factor scores using linear regression models in APOE ε4 carriers (n = 167) and noncarriers (n = 122). We hypothesized that greater WMH volume would relate to worse cognition more strongly in APOE ε4 carriers. Findings were replicated in 198 patients with AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI-I), and estimates from both samples were meta-analyzed. Results A significant interaction was observed between WMH and APOE ε4 for language, but not for memory or executive functions. Separate analyses in APOE ε4 carriers and noncarriers showed that greater WMH volume was associated with worse attention/executive functions, learning/memory, and language in APOE ε4 carriers only. In ADNI-I, greater WMH burden was associated with worse attention/executive functions and language in APOE ε4 carriers only. No significant associations were observed in noncarriers. Meta-analyses showed that greater WMH volume was associated with worse performance on all cognitive domains in APOE ε4 carriers only. Conclusion APOE ε4 may influence the association between WMH and cognitive performance in AD and DLB

Fabrication and Biological Assessment of Antidiabetic α-Mangostin Loaded Nanosponges: In Vitro, In Vivo, and In Silico Studies

From MDPI via Jisc Publications RouterHistory: accepted 2021-10-29, pub-electronic 2021-11-01Publication status: PublishedFunder: King Saud University; Grant(s): RSP-2021/406Type 2 diabetes mellitus has been a major health issue with increasing morbidity and mortality due to macrovascular and microvascular complications. The urgent need for improved methods to control hyperglycemic complications reiterates the development of innovative preventive and therapeutic treatment strategies. In this perspective, xanthone compounds in the pericarp of the mangosteen fruit, especially α-mangostin (MGN), have been recognized to restore damaged pancreatic β-cells for optimal insulin release. Therefore, taking advantage of the robust use of nanotechnology for targeted drug delivery, we herein report the preparation of MGN loaded nanosponges for anti-diabetic therapeutic applications. The nanosponges were prepared by quasi-emulsion solvent evaporation method. Physico-chemical characterization of formulated nanosponges with satisfactory outcomes was performed with Fourier transform infra-red (FTIR) spectroscopy, differential scanning calorimetry (DSC), and scanning electron microscopy (SEM). Zeta potential, hydrodynamic diameter, entrapment efficiency, drug release properties, and stability studies at stress conditions were also tested. Molecular docking analysis revealed significant interactions of α-glucosidase and MGN in a protein-ligand complex. The maximum inhibition by nanosponges against α-glucosidase was observed to be 0.9352 ± 0.0856 µM, 3.11-fold higher than acarbose. In vivo studies were conducted on diabetic rats and plasma glucose levels were estimated by HPLC. Collectively, our findings suggest that MGN-loaded nanosponges may be beneficial in the treatment of diabetes since they prolong the antidiabetic response in plasma and improve patient compliance by slowly releasing MGN and requiring less frequent doses, respectively

APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies

Introduction Although the apolipoprotein E ε4-allele (APOE-ε4) is a susceptibility factor for Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), its relationship with imaging and cognitive measures across the AD/DLB spectrum remains unexplored. Methods We studied 298 patients (AD = 250, DLB = 48; 38 autopsy confirmed; NCT01800214) using neuropsychological testing, volumetric magnetic resonance imaging, and APOE genotyping to investigate the association of APOE-ε4 with hippocampal volume and learning/memory phenotypes, irrespective of diagnosis. Results Across the AD/DLB spectrum: (1) hippocampal volumes were smaller with increasing APOE-ε4 dosage (no genotype × diagnosis interaction observed), (2) learning performance as assessed by total recall scores was associated with hippocampal volumes only among APOE-ε4 carriers, and (3) APOE-ε4 carriers performed worse on long-delay free word recall. Discussion These findings provide evidence that APOE-ε4 is linked to hippocampal atrophy and learning/memory phenotypes across the AD/DLB spectrum, which could be useful as biomarkers of disease progression in therapeutic trials of mixed disease

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions. Funding: Bill & Melinda Gates Foundation

Mapping geographical inequalities in access to drinking water and sanitation facilities in low-income and middle-income countries, 2000-17

Background: Universal access to safe drinking water and sanitation facilities is an essential human right, recognised in the Sustainable Development Goals as crucial for preventing disease and improving human wellbeing. Comprehensive, high-resolution estimates are important to inform progress towards achieving this goal. We aimed to produce high-resolution geospatial estimates of access to drinking water and sanitation facilities. Methods: We used a Bayesian geostatistical model and data from 600 sources across more than 88 low-income and middle-income countries (LMICs) to estimate access to drinking water and sanitation facilities on continuous continent-wide surfaces from 2000 to 2017, and aggregated results to policy-relevant administrative units. We estimated mutually exclusive and collectively exhaustive subcategories of facilities for drinking water (piped water on or off premises, other improved facilities, unimproved, and surface water) and sanitation facilities (septic or sewer sanitation, other improved, unimproved, and open defecation) with use of ordinal regression. We also estimated the number of diarrhoeal deaths in children younger than 5 years attributed to unsafe facilities and estimated deaths that were averted by increased access to safe facilities in 2017, and analysed geographical inequality in access within LMICs. Findings: Across LMICs, access to both piped water and improved water overall increased between 2000 and 2017, with progress varying spatially. For piped water, the safest water facility type, access increased from 40·0% (95% uncertainty interval [UI] 39·4–40·7) to 50·3% (50·0–50·5), but was lowest in sub-Saharan Africa, where access to piped water was mostly concentrated in urban centres. Access to both sewer or septic sanitation and improved sanitation overall also increased across all LMICs during the study period. For sewer or septic sanitation, access was 46·3% (95% UI 46·1–46·5) in 2017, compared with 28·7% (28·5–29·0) in 2000. Although some units improved access to the safest drinking water or sanitation facilities since 2000, a large absolute number of people continued to not have access in several units with high access to such facilities (>80%) in 2017. More than 253 000 people did not have access to sewer or septic sanitation facilities in the city of Harare, Zimbabwe, despite 88·6% (95% UI 87·2–89·7) access overall. Many units were able to transition from the least safe facilities in 2000 to safe facilities by 2017; for units in which populations primarily practised open defecation in 2000, 686 (95% UI 664–711) of the 1830 (1797–1863) units transitioned to the use of improved sanitation. Geographical disparities in access to improved water across units decreased in 76·1% (95% UI 71·6–80·7) of countries from 2000 to 2017, and in 53·9% (50·6–59·6) of countries for access to improved sanitation, but remained evident subnationally in most countries in 2017. Interpretation: Our estimates, combined with geospatial trends in diarrhoeal burden, identify where efforts to increase access to safe drinking water and sanitation facilities are most needed. By highlighting areas with successful approaches or in need of targeted interventions, our estimates can enable precision public health to effectively progress towards universal access to safe water and sanitation

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations