PREDICTION OF POPULATION DISTRIBUTION IN 2030 USING THE INTEGRATION OF THE CA-ANN LAND COVER CHANGE METHOD WITH NUMERIC EXTRAPOLATION IN KARAWANG-BEKASI, INDONESIA

Population growth continues to increase every year. It is recorded that in 2022 the world population will reach 7,953,952,567 or an increase of 1% from 2021. The increasing number of residents encourages land use/land cover changes to become settlements. In addition to changes in land use/land cover, there is also population mobilization from one place to another. This population movement will coincide with developments that will occur in the area. Monitoring population distribution is necessary to have no concentration in only one area. Areas with too dense a population will cause many problems such as the emergence of slum buildings, congestion, and flooding. In this case, the population density is centralized due to poor regional planning. The absence of prediction of future population distribution is one of the reasons why urban planning in the future is not optimal. This study aims to predict the distribution of the population in 2030. In predicting the distribution of population in 2030, it integrates the prediction of land use/land cover in 2030 with the prediction of the population in 2030. In predicting land use/land in 2030, land use/land in 2005 and 2010 is used as the primary data for change prediction. The method used to predict changes in land use/land cover is the CA-ANN method by considering the driving factors of changes in the form of altitude, distance from the river, and distance from the road. Predicting the population of 2030 will be done by extrapolation using the three mathematical equations approach, they are linear, exponential, and power equation. The results of the prediction of land use/land and population in 2030 are then used to predict the population distribution in 2030. From the results, In the 2030 there was an increase in the class of settlements which reached an area of 745,169 Km2 with the overall accuracy of the land cover model reached 82%. The largest population projection come from exponential equation that until 13024668 in 2030. The model population distribution in 2030, show that there is no significant different between three projection model to be used in model population distribution 2030. It is hoped that this research can be a reference for policymakers in planning sustainable urban development

Sposol: 5 In 1 Smart Portable Solar Light

Smart Portable Solar Light is a project based on a circuit obtained through the internet connection.A few modifications have been done to the original circuit; original circuit uses eight LEDs while this project only uses one main LED.The main source of this system is harvest form the sun.The sun’s radiation is converted to electrical energy that is supplied to a battery,which acts as a power storage for the system.Another set of batteries is used as the structure of the lamp is design to be portable

Hydration and cooling in elite athletes: relationship with performance, body mass loss and body temperatures during the Doha 2019 IAAF World Athletics Championships

Purpose: To characterise hydration, cooling, body mass loss, and core (Tcore) and skin (Tsk) temperatures during World Athletics Championships in hot-humid conditions. Methods: Marathon and race-walk (20 km and 50 km) athletes (n=83, 36 women) completed a pre-race questionnaire. Pre-race and post-race body weight (n=74), Tcore (n=56) and Tsk (n=49; thermography) were measured. Results: Most athletes (93%) had a pre-planned drinking strategy (electrolytes (83%), carbohydrates (81%)) while ice slurry was less common (11%; p<0.001). More men than women relied on electrolytes and carbohydrates (91%–93% vs 67%–72%, p≤0.029). Drinking strategies were based on personal experience (91%) rather than external sources (p<0.001). Most athletes (80%) planned pre-cooling (ice vests (53%), cold towels (45%), neck collars (21%) and ice slurry (21%)) and/or midcooling (93%; head/face dousing (65%) and cold water ingestion (52%)). Menthol usage was negligible (1%–2%). Pre-race Tcore was lower in athletes using ice vests (37.5°C±0.4°C vs 37.8°C±0.3°C, p=0.024). Tcore (pre-race 37.7°C±0.3°C, post-race 39.6°C±0.6°C) was independent of event, ranking or performance (p≥0.225). Pre-race Tsk was correlated with faster race completion (r=0.32, p=0.046) and was higher in non-finishers (did not finish (DNF); 33.8°C±0.9°C vs 32.6°C±1.4°C, p=0.017). Body mass loss was higher in men than women (−2.8±1.5% vs −1.3±1.6%, p<0.001), although not associated with performance. Conclusion: Most athletes’ hydration strategies were pre-planned based on personal experience. Ice vests were the most adopted pre-cooling strategy and the only one minimising Tcore, suggesting that event organisers should be cognisant of logistics (ie, freezers). Dehydration was moderate and unrelated to performance. Pre-race Tsk was related to performance and DNF, suggesting that Tsk modulation should be incorporated into pre-race strategies

Hydration and cooling in elite athletes: relationship with performance, body mass loss and body temperatures during the Doha 2019 IAAF World Athletics Championships.

PURPOSE: To characterise hydration, cooling, body mass loss, and core (Tcore) and skin (Tsk) temperatures during World Athletics Championships in hot-humid conditions. METHODS: Marathon and race-walk (20 km and 50 km) athletes (n=83, 36 women) completed a pre-race questionnaire. Pre-race and post-race body weight (n=74), Tcore (n=56) and Tsk (n=49; thermography) were measured. RESULTS: Most athletes (93%) had a pre-planned drinking strategy (electrolytes (83%), carbohydrates (81%)) while ice slurry was less common (11%; p<0.001). More men than women relied on electrolytes and carbohydrates (91%-93% vs 67%-72%, p≤0.029). Drinking strategies were based on personal experience (91%) rather than external sources (p<0.001). Most athletes (80%) planned pre-cooling (ice vests (53%), cold towels (45%), neck collars (21%) and ice slurry (21%)) and/or mid-cooling (93%; head/face dousing (65%) and cold water ingestion (52%)). Menthol usage was negligible (1%-2%). Pre-race Tcore was lower in athletes using ice vests (37.5°C±0.4°C vs 37.8°C±0.3°C, p=0.024). Tcore (pre-race 37.7°C±0.3°C, post-race 39.6°C±0.6°C) was independent of event, ranking or performance (p≥0.225). Pre-race Tsk was correlated with faster race completion (r=0.32, p=0.046) and was higher in non-finishers (did not finish (DNF); 33.8°C±0.9°C vs 32.6°C±1.4°C, p=0.017). Body mass loss was higher in men than women (-2.8±1.5% vs -1.3±1.6%, p<0.001), although not associated with performance. CONCLUSION: Most athletes' hydration strategies were pre-planned based on personal experience. Ice vests were the most adopted pre-cooling strategy and the only one minimising Tcore, suggesting that event organisers should be cognisant of logistics (ie, freezers). Dehydration was moderate and unrelated to performance. Pre-race Tsk was related to performance and DNF, suggesting that Tsk modulation should be incorporated into pre-race strategies

Mitochondrial barcodes of three malaysian butterflies originating from Taman Negara Endau Rompin Johor, Malaysia

Butterflies are projected as reliable and economical biodiversity indicator. Traditionally, taxonomists identified and classified butterfly species based on highly similar and ambiguous morphological appearances which can result in problematic species identification process leading to misidentification of species. DNA barcoding has been developed for taxonomic identification of butterflies to species level. Nonetheless, this approach is hampered by the paucity of reference barcodes encompassing butterflies of all families and species in Malaysia. This study reported four novel DNA barcodes (two cytochrome oxidase subunit I (COI) and two cytochrome b, cytb) of Malaysian butterflies generated using Sanger sequencing. One barcode (DIB032 COI) supported the species identified by taxonomists whereas the other three barcodes (DIB034 COI, DIB034 cytb and DIB046/049 cytb) deduced that the butterfly species were either misidentified or unidentified up to species level due to the lack of reference barcodes in GenBank. The four novel DNA barcodes were deposited in GenBank under the accession number MT210226.1 (DIB032 COI), MT210227.1 (DIB034 COI), MT210228.1 (DIB034 cytb) and MT210229.1 (DIB046/049 cytb)

Pre-cooling for endurance exercise performance in the heat: a systematic review.

PMCID: PMC3568721The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1741-7015/10/166. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Endurance exercise capacity diminishes under hot environmental conditions. Time to exhaustion can be increased by lowering body temperature prior to exercise (pre-cooling). This systematic literature review synthesizes the current findings of the effects of pre-cooling on endurance exercise performance, providing guidance for clinical practice and further research

Multiple Analytical Approaches Reveal Distinct Gene-Environment Interactions in Smokers and Non Smokers in Lung Cancer

Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR), was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11–2.59,p = 0.01), whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25–0.65,p<0.001 and OR = 0.51;95%CI = 0.33–0.78,p = 0.002 respectively). In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His), SULT1A1 213GG (Arg/Arg) or AA (His/His) and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33–10.55,p = 0.006), whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg) and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15–7.51,p = 0.01). MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His) and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His) with testing balance accuracy (TBA) of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A1*2C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer