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Fulltext 10Po, 210Pb and 210Po/210Pb in sediment core from surrounding Sungai Linggi estuary

Zal U’yun Wan Mahmood, Mei, Wo Yii, Abdul Kadir Ishak

Jurnal Sains Nuklear Malaysia, 2016;28(1):1-8.
MyJurnal

This study was performed to observe the variation in the distribution of 210Po,210Pb and 210Po/210Pb activity ratio throughtheir vertical profile of the sediment cores takenat surrounding Sungai Linggi estuary. Five sediment cores were takenin February 2011 and were cutto an intervalof 2 cm layer. Activity concentrations of 210Po and 210Pb were determined using alpha radiochemical analysis and gamma direct measurement, respectively. Generally, the measured activity of 210Po, 210Pb and 210Po/210Pbwere in the ranges of 22.73 –139.06 Bqkg-1dw., 37.88 –176.24 Bqkg-1dw.and 0.23 –1.34, respectively. The variation in the distribution profile for the radionuclides are believed to be influencedby human activities such as agriculture, fertilizer, vehicles, burned fuel fossil and forest, industrialand others via river input from land-base.Other factor is due to organic mattercontent played importantrole as the geochemical carrier to transportthose radionuclides at study area. It was provedthat hasa strong correlation between the radionuclide distribution and the sedimentcomposition of organic matter.Furthermore, in those rangesreflectedthat 210Pb activities were higher than210Po with an activity ratio average of 0.79. This is probably due to dramatic increase of excess 210Pb supplied from atmospheric deposition, in situ decay of 226Ra and as a result of diagenetic remolibilazationof 210Pbin deeper layesof the sediment column. Thus, thosefactors are majorcontributions on thevariation of 210Po and 210Pb in the sediment core at surrounding Sungai Linggi estuary.

Matched MeSH terms: Human Activities
Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms

He Q, Shahabi H, Shirzadi A, Li S, Chen W, Wang N, et al.

Sci Total Environ, 2019 May 01;663:1-15.
PMID: 30708212 DOI: 10.1016/j.scitotenv.2019.01.329

Landslides are major hazards for human activities often causing great damage to human lives and infrastructure. Therefore, the main aim of the present study is to evaluate and compare three machine learning algorithms (MLAs) including Naïve Bayes (NB), radial basis function (RBF) Classifier, and RBF Network for landslide susceptibility mapping (LSM) at Longhai area in China. A total of 14 landslide conditioning factors were obtained from various data sources, then the frequency ratio (FR) and support vector machine (SVM) methods were used for the correlation and selection the most important factors for modelling process, respectively. Subsequently, the resulting three models were validated and compared using some statistical metrics including area under the receiver operating characteristics (AUROC) curve, and Friedman and Wilcoxon signed-rank tests The results indicated that the RBF Classifier model had the highest goodness-of-fit and performance based on the training and validation datasets. The results concluded that the RBF Classifier model outperformed and outclassed (AUROC = 0.881), the NB (AUROC = 0.872) and the RBF Network (AUROC = 0.854) models. The obtained results pointed out that the RBF Classifier model is a promising method for spatial prediction of landslide over the world.

Matched MeSH terms: Human Activities
Fulltext Determination of surface radiation dose and concentrations of uranium and thorium in soil at UiTM-Perhilitan research station Kuala Keniam, Taman Negara, Pahang

Ahmad Saat, Nurulhuda Kassim, Zaini Hamzah, Ahmad Farisz

Journal of Nuclear and Related Technologies, 2010;2010(2):49-54.
MyJurnal

Taman Negara is a famous tourism destination for nature lover in Malaysia. The area is well kept from human activities and disturbances. Since there is no data for human exposure to natural radiation, there is a need to do this study. It will give a baseline data for surface dose and radionuclide concentrations and one can estimate the external hazards index for the visitor to this unexplored area, i.e. UiTM-Perhilitan research station, Kuala Keniam, Taman Negara, Malaysia. The surface dose rate measurements were done in-situ using portable radiation survey meter at the surface and 1 m above the surface. The top soil samples were taken using hand auger up to 15 cm depth at nine locations around research station. Samples were brought back to the UiTM laboratory in Shah Alam, dried, ground to powder form, and sieved using 250 μm sieve. Then the uranium and thorium concentrations were analyzed using Energy Dispersive X-Ray Fluorescence (EDXRF).The mean value for surface dose rates on surface were 0.164 μSv/hr while the mean value for surface dose rates on 1m above the surface were 0.161 μSv/hr. The mean concentration of thorium was 2.62μg/g while the mean concentration of uranium was 0.61μg/g.

Matched MeSH terms: Human Activities
Correlation and persistence of hunting and logging impacts on tropical rainforest mammals

Brodie JF, Giordano AJ, Zipkin EF, Bernard H, Mohd-Azlan J, Ambu L

Conserv Biol, 2015 Feb;29(1):110-21.
PMID: 25196079 DOI: 10.1111/cobi.12389

Humans influence tropical rainforest animals directly via exploitation and indirectly via habitat disturbance. Bushmeat hunting and logging occur extensively in tropical forests and have large effects on particular species. But how they alter animal diversity across landscape scales and whether their impacts are correlated across species remain less known. We used spatially widespread measurements of mammal occurrence across Malaysian Borneo and recently developed multispecies hierarchical models to assess the species richness of medium- to large-bodied terrestrial mammals while accounting for imperfect detection of all species. Hunting was associated with 31% lower species richness. Moreover, hunting remained high even where richness was very low, highlighting that hunting pressure persisted even in chronically overhunted areas. Newly logged sites had 11% lower species richness than unlogged sites, but sites logged >10 years previously had richness levels similar to those in old-growth forest. Hunting was a more serious long-term threat than logging for 91% of primate and ungulate species. Hunting and logging impacts across species were not correlated across taxa. Negative impacts of hunting were the greatest for common mammalian species, but commonness versus rarity was not related to species-specific impacts of logging. Direct human impacts appeared highly persistent and lead to defaunation of certain areas. These impacts were particularly severe for species of ecological importance as seed dispersers and herbivores. Indirect impacts were also strong but appeared to attenuate more rapidly than previously thought. The lack of correlation between direct and indirect impacts across species highlights that multifaceted conservation strategies may be needed for mammal conservation in tropical rainforests, Earth's most biodiverse ecosystems.

Matched MeSH terms: Human Activities
Fulltext Robust video content analysis schemes for human action recognition

Aly CA, Abas FS, Ann GH

Sci Prog, 2021;104(2):368504211005480.
PMID: 33913378 DOI: 10.1177/00368504211005480

INTRODUCTION: Action recognition is a challenging time series classification task that has received much attention in the recent past due to its importance in critical applications, such as surveillance, visual behavior study, topic discovery, security, and content retrieval.
OBJECTIVES: The main objective of the research is to develop a robust and high-performance human action recognition techniques. A combination of local and holistic feature extraction methods used through analyzing the most effective features to extract to reach the objective, followed by using simple and high-performance machine learning algorithms.
METHODS: This paper presents three robust action recognition techniques based on a series of image analysis methods to detect activities in different scenes. The general scheme architecture consists of shot boundary detection, shot frame rate re-sampling, and compact feature vector extraction. This process is achieved by emphasizing variations and extracting strong patterns in feature vectors before classification.
RESULTS: The proposed schemes are tested on datasets with cluttered backgrounds, low- or high-resolution videos, different viewpoints, and different camera motion conditions, namely, the Hollywood-2, KTH, UCF11 (YouTube actions), and Weizmann datasets. The proposed schemes resulted in highly accurate video analysis results compared to those of other works based on four widely used datasets. The First, Second, and Third Schemes provides recognition accuracies of 57.8%, 73.6%, and 52.0% on Hollywood2, 94.5%, 97.0%, and 59.3% on KTH, 94.5%, 95.6%, and 94.2% on UCF11, and 98.9%, 97.8% and 100% on Weizmann.
CONCLUSION: Each of the proposed schemes provides high recognition accuracy compared to other state-of-art methods. Especially, the Second Scheme as it gives excellent comparable results to other benchmarked approaches.

Matched MeSH terms: Human Activities*
Fulltext Classification of Human Daily Activities Using Ensemble Methods Based on Smartphone Inertial Sensors

Ku Abd Rahim KN, Elamvazuthi I, Izhar LI, Capi G

Sensors (Basel), 2018 Nov 26;18(12).
PMID: 30486242 DOI: 10.3390/s18124132

Increasing interest in analyzing human gait using various wearable sensors, which is known as Human Activity Recognition (HAR), can be found in recent research. Sensors such as accelerometers and gyroscopes are widely used in HAR. Recently, high interest has been shown in the use of wearable sensors in numerous applications such as rehabilitation, computer games, animation, filmmaking, and biomechanics. In this paper, classification of human daily activities using Ensemble Methods based on data acquired from smartphone inertial sensors involving about 30 subjects with six different activities is discussed. The six daily activities are walking, walking upstairs, walking downstairs, sitting, standing and lying. It involved three stages of activity recognition; namely, data signal processing (filtering and segmentation), feature extraction and classification. Five types of ensemble classifiers utilized are Bagging, Adaboost, Rotation forest, Ensembles of nested dichotomies (END) and Random subspace. These ensemble classifiers employed Support vector machine (SVM) and Random forest (RF) as the base learners of the ensemble classifiers. The data classification is evaluated with the holdout and 10-fold cross-validation evaluation methods. The performance of each human daily activity was measured in terms of precision, recall, F-measure, and receiver operating characteristic (ROC) curve. In addition, the performance is also measured based on the comparison of overall accuracy rate of classification between different ensemble classifiers and base learners. It was observed that overall, SVM produced better accuracy rate with 99.22% compared to RF with 97.91% based on a random subspace ensemble classifier.

Matched MeSH terms: Human Activities
Fulltext Air quality changes during the COVID-19 lockdown over the Yangtze River Delta Region: An insight into the impact of human activity pattern changes on air pollution variation

Li L, Li Q, Huang L, Wang Q, Zhu A, Xu J, et al.

Sci Total Environ, 2020 Aug 25;732:139282.
PMID: 32413621 DOI: 10.1016/j.scitotenv.2020.139282

The outbreak of COVID-19 has spreaded rapidly across the world. To control the rapid dispersion of the virus, China has imposed national lockdown policies to practise social distancing. This has led to reduced human activities and hence primary air pollutant emissions, which caused improvement of air quality as a side-product. To investigate the air quality changes during the COVID-19 lockdown over the YRD Region, we apply the WRF-CAMx modelling system together with monitoring data to investigate the impact of human activity pattern changes on air quality. Results show that human activities were lowered significantly during the period: industrial operations, VKT, constructions in operation, etc. were significantly reduced, leading to lowered SO2, NOx, PM2.5 and VOCs emissions by approximately 16-26%, 29-47%, 27-46% and 37-57% during the Level I and Level II response periods respectively. These emission reduction has played a significant role in the improvement of air quality. Concentrations of PM2.5, NO2 and SO2 decreased by 31.8%, 45.1% and 20.4% during the Level I period; and 33.2%, 27.2% and 7.6% during the Level II period compared with 2019. However, ozone did not show any reduction and increased greatly. Our results also show that even during the lockdown, with primary emissions reduction of 15%-61%, the daily average PM2.5 concentrations range between 15 and 79 μg m-3, which shows that background and residual pollutions are still high. Source apportionment results indicate that the residual pollution of PM2.5 comes from industry (32.2-61.1%), mobile (3.9-8.1%), dust (2.6-7.7%), residential sources (2.1-28.5%) in YRD and 14.0-28.6% contribution from long-range transport coming from northern China. This indicates that in spite of the extreme reductions in primary emissions, it cannot fully tackle the current air pollution. Re-organisation of the energy and industrial strategy together with trans-regional joint-control for a full long-term air pollution plan need to be further taken into account.

Matched MeSH terms: Human Activities
Fulltext Multi-View Human Action Recognition Using Skeleton Based-FineKNN with Extraneous Frame Scrapping Technique

Malik NUR, Sheikh UU, Abu-Bakar SAR, Channa A

Sensors (Basel), 2023 Mar 02;23(5).
PMID: 36904953 DOI: 10.3390/s23052745

Human action recognition (HAR) is one of the most active research topics in the field of computer vision. Even though this area is well-researched, HAR algorithms such as 3D Convolution Neural Networks (CNN), Two-stream Networks, and CNN-LSTM (Long Short-Term Memory) suffer from highly complex models. These algorithms involve a huge number of weights adjustments during the training phase, and as a consequence, require high-end configuration machines for real-time HAR applications. Therefore, this paper presents an extraneous frame scrapping technique that employs 2D skeleton features with a Fine-KNN classifier-based HAR system to overcome the dimensionality problems.To illustrate the efficacy of our proposed method, two contemporary datasets i.e., Multi-Camera Action Dataset (MCAD) and INRIA Xmas Motion Acquisition Sequences (IXMAS) dataset was used in experiment. We used the OpenPose technique to extract the 2D information, The proposed method was compared with CNN-LSTM, and other State of the art methods. Results obtained confirm the potential of our technique. The proposed OpenPose-FineKNN with Extraneous Frame Scrapping Technique achieved an accuracy of 89.75% on MCAD dataset and 90.97% on IXMAS dataset better than existing technique.

Matched MeSH terms: Human Activities
Ultrastructural changes of cell morphology and viral morphogenesis of two ecotypes of dengue virus infection in human monocytic U-937 cell

Fish-Low CY, Abu Bakar S, Othman F, Chee HY

Trop Biomed, 2018 Dec 01;35(4):1154-1159.
PMID: 33601863

Dengue virus (DENV) is maintained and circulated in both sylvatic/enzootic and endemic/human cycles and spill over infection of sylvatic DENV into human populations has been reported. Extensive deforestation and increase human activities in forest may increase the risk of human exposure to sylvatic dengue infection and this may become a threat to human. Present study investigated the changes in cell morphology and viral morphogenesis upon infection with sylvatic and endemic ecotypes in human monocytic U-937 cells using transmission electron microscopy. Autophagy, a process that is either pro-viral or anti-viral, was observed in U-937 cells of both infections, however only the replication of endemic DENV was evidenced. An insight into the infection responses of sylvatic progenitors of DENV in susceptible host cells may provide better understanding on dengue emergence in human populations.

Matched MeSH terms: Human Activities
Enhancing coastal ecosystem resilience: Investigating the interplay between safety criteria and ferry employee's perceptions to address climate change impacts

Azmi MA, Mokhtar K, Osnin NA, Razali Chan S, Albasher G, Ali A, et al.

Environ Res, 2023 Dec 01;238(Pt 1):117074.
PMID: 37678506 DOI: 10.1016/j.envres.2023.117074

Coastal ecosystems play an important part in mitigating the effects of climate change. Coastal ecosystems are becoming more susceptible to climate change impacts due to human activities and maritime accidents. The global shipping industry, especially in Southeast Asia, has witnessed numerous accidents, particularly involving passenger ferries, resulting in injuries and fatalities in recent years. In order to mitigate the impact of climate change on coastal ecosystems, this study aimed to evaluate the relationship between employees' perceptions of safety criteria and their own safety behaviour on Langkawi Island, Malaysia. A straightforward random sampling technique was employed to collect data from 112 ferry employees aboard Malaysian-registered passenger boats by administering questionnaires. The findings shed light on the strong connection between providing safety instructions for passengers and safety behaviour among ferry workers. Safety instructions should contain climate-related information to successfully address the effects of climate change. The instructions might include guidance on responding to extreme weather events and understanding the potential consequences of sea-level rise on coastal communities. The ferry company staff should also expand their safe behaviour concept to include training and preparation for climate-related incidents. The need to recognise the interconnectedness between climate change, ferry safety and the protection of coastal ecosystems is emphasised in this study. The findings can be utilised by policymakers, regulatory agencies and ferry operators to design holistic policies that improve safety behaviour, minimise maritime mishaps and preserve the long-term sustainability of coastal ecosystems in the face of difficulties posed by climate change.

Matched MeSH terms: Human Activities
Fulltext BeSafe B2.0 Smart Multisensory Platform for Safety in Workplaces

Márquez-Sánchez S, Campero-Jurado I, Robles-Camarillo D, Rodríguez S, Corchado-Rodríguez JM

Sensors (Basel), 2021 May 12;21(10).
PMID: 34066186 DOI: 10.3390/s21103372

Wearable technologies are becoming a profitable means of monitoring a person's health state, such as heart rate and physical activity. The use of the smartwatch is becoming consolidated, not only as a novelty but also as a very useful tool for daily use. In addition, other devices, such as helmets or belts, are beneficial for monitoring workers and the early detection of any anomaly. They can provide valuable information, especially in work environments, where they help reduce the rate of accidents and occupational diseases, which makes them powerful Personal Protective Equipment (PPE). The constant monitoring of the worker's health can be done in real-time, through temperature, falls, noise, impacts, or heart rate meters, activating an audible and vibrating alarm when an anomaly is detected. The gathered information is transmitted to a server in charge of collecting and processing it. In the first place, this paper provides an exhaustive review of the state of the art on works related to electronics for human activity behavior. After that, a smart multisensory bracelet, combined with other devices, developed a control platform that can improve operators' security in the working environment. Artificial Intelligence and the Internet of Things (AIoT) bring together the information to improve safety on construction sites, power stations, power lines, etc. Real-time and historic data is used to monitor operators' health and a hybrid system between Gaussian Mixture Model and Human Activity Classification. That is, our contribution is also founded on the use of two machine learning models, one based on unsupervised learning and the other one supervised. Where the GMM gave us a performance of 80%, 85%, 70%, and 80% for the 4 classes classified in real time, the LSTM obtained a result under the confusion matrix of 0.769, 0.892, and 0.921 for the carrying-displacing, falls, and walking-standing activities, respectively. This information was sent in real time through the platform that has been used to analyze and process the data in an alarm system.

Matched MeSH terms: Human Activities
Fulltext Ergonomic design optimization for train seat fit parameters

Teo Chuun, B., Dian Darina Indah, D., Darliana, M.

Malaysian Journal of Public Health Medicine, 2018;18(102):73-78.
MyJurnal

This study is aimed at seat design optimization for high-speed train based on the Malaysians sitting anthropometry
data focusing on seat fit parameters. An analysis of anthropometry data composed of 15 dimensions that are
required in seat design was done with 50 male subjects. These data were collected through direct measuring
methods with standard equipment. According to the Malaysian automotive seat fit parameters, the backrest width,
backrest height, cushion width, and cushion length were established based on these anthropometric dimensions:
interscye breadth (5th percentile female and 95th percentile male), hip breadth (95th percentile female), sitting
shoulder height (5th percentile female), and buttock-popliteal length (5th percentile female), respectively. This
study uses the CATIA software to design and analyse the proposed seat design. The fit parameters proposed for the
new design are seat height, 380mm; cushion width, 450mm; backrest width, 450mm and backrest height, 850mm.
The CATIA human activity analysis (based on Rapid Upper Limb Analysis, RULA) was also executed. From the study,
the new conceptual seat design gives the most optimized fit when compared to the current seat.

Matched MeSH terms: Human Activities
Fulltext Hunter-gatherer residential mobility and the marginal value of rainforest patches

Venkataraman VV, Kraft TS, Dominy NJ, Endicott KM

Proc Natl Acad Sci U S A, 2017 03 21;114(12):3097-3102.
PMID: 28265058 DOI: 10.1073/pnas.1617542114

The residential mobility patterns of modern hunter-gatherers broadly reflect local resource availability, but the proximate ecological and social forces that determine the timing of camp movements are poorly known. We tested the hypothesis that the timing of such moves maximizes foraging efficiency as hunter-gatherers move across the landscape. The marginal value theorem predicts when a group should depart a camp and its associated foraging area and move to another based on declining marginal return rates. This influential model has yet to be directly applied in a population of hunter-gatherers, primarily because the shape of gain curves (cumulative resource acquisition through time) and travel times between patches have been difficult to estimate in ethnographic settings. We tested the predictions of the marginal value theorem in the context of hunter-gatherer residential mobility using historical foraging data from nomadic, socially egalitarian Batek hunter-gatherers (n = 93 d across 11 residential camps) living in the tropical rainforests of Peninsular Malaysia. We characterized the gain functions for all resources acquired by the Batek at daily timescales and examined how patterns of individual foraging related to the emergent property of residential movements. Patterns of camp residence times conformed well with the predictions of the marginal value theorem, indicating that communal perceptions of resource depletion are closely linked to collective movement decisions. Despite (and perhaps because of) a protracted process of deliberation and argument about when to depart camps, Batek residential mobility seems to maximize group-level foraging efficiency.

Matched MeSH terms: Human Activities*
Grain-dependent responses of mammalian diversity to land use and the implications for conservation set-aside

Wearn OR, Carbone C, Rowcliffe JM, Bernard H, Ewers RM

Ecol Appl, 2016 Jul;26(5):1409-1420.
PMID: 27755763 DOI: 10.1890/15-1363

Diversity responses to land-use change are poorly understood at local scales, hindering our ability to make forecasts and management recommendations at scales which are of practical relevance. A key barrier in this has been the underappreciation of grain-dependent diversity responses and the role that β-diversity (variation in community composition across space) plays in this. Decisions about the most effective spatial arrangement of conservation set-aside, for example high conservation value areas, have also neglected β-diversity, despite its role in determining the complementarity of sites. We examined local-scale mammalian species richness and β-diversity across old-growth forest, logged forest, and oil palm plantations in Borneo, using intensive camera- and live-trapping. For the first time, we were able to investigate diversity responses, as well as β-diversity, at multiple spatial grains, and across the whole terrestrial mammal community (large and small mammals); β-diversity was quantified by comparing observed β-diversity with that obtained under a null model, in order to control for sampling effects, and we refer to this as the β-diversity signal. Community responses to land use were grain dependent, with large mammals showing reduced richness in logged forest compared to old-growth forest at the grain of individual sampling points, but no change at the overall land-use level. Responses varied with species group, however, with small mammals increasing in richness at all grains in logged forest compared to old-growth forest. Both species groups were significantly depauperate in oil palm. Large mammal communities in old-growth forest became more heterogeneous at coarser spatial grains and small mammal communities became more homogeneous, while this pattern was reversed in logged forest. Both groups, however, showed a significant β-diversity signal at the finest grain in logged forest, likely due to logging-induced environmental heterogeneity. The β-diversity signal in oil palm was weak, but heterogeneity at the coarsest spatial grain was still evident, likely due to variation in landscape forest cover. Our findings suggest that the most effective spatial arrangement of set-aside will involve trade-offs between conserving large and small mammals. Greater consideration in the conservation and management of tropical landscapes needs to be given to β-diversity at a range of spatial grains.

Matched MeSH terms: Human Activities*
Fulltext General Perceptions and Awareness Level among Local Residents in Penang Island toward Bats Conservation Efforts

Shafie NJ, Sah SAM, Mutalib AHA, Fadzly N

Trop Life Sci Res, 2017 Jul;28(2):31-44.
PMID: 28890759 MyJurnal DOI: 10.21315/tlsr2017.28.2.3

The population of bats has declined from year to year caused by human activities such as logging and hunting activities. Since the human factor is linked to the issues of population decline in many animal species, a community-based conservation strategy that involved local communities is needed. We conducted face-to-face surveys among residents in Penang Island to assess knowledge and awareness level toward bats conservation efforts. We collected demographic values such as age, gender, level of education, length of residency as well as their monthly income, since different group in these variable might have different perception. We found that age groups, level of education and monthly income have shown significant differences among the respondents. However, no other significant differences were indicated for by gender and length of residency. Respondent's knowledge of bats showed that the majority of the respondents were less likely to value the importance of bats in the ecosystem. We recommended stronger legal system, earlier exposure towards environmental education, well-planned urbanisation implementation and long-term monitoring programs to strengthen efforts in conserving bats in Malaysia.

Matched MeSH terms: Human Activities
Fulltext Global warming: can we do something?

Ghazally Ismail

ASM Science Journal, 2011;5(1):73-74.
MyJurnal

Human activity has ‘very likely’ been the primary cause of global warming since the start of the Industrial Revolution (18th–19th century). As a new player in industrial transformation, Malaysia can choose to ignore the warnings of global warming. blame. This may not augur well. Release of greenhouse gases have been categorically linked to climate change and global warming. In her march towards industrialization, Malaysia too has contributed to the release of greenhouse gases. Apart from those arising from natural sources, the industrial sector in Malaysia also releases other types of gases such as the fluorocarbons. This is evident from the worsening air quality in some of our cities. (Copied from article).

Matched MeSH terms: Human Activities
The Genus Cladophora Kützing (Ulvophyceae) as a Globally Distributed Ecological Engineer

Zulkifly SB, Graham JM, Young EB, Mayer RJ, Piotrowski MJ, Smith I, et al.

J Phycol, 2013 Feb;49(1):1-17.
PMID: 27008383 DOI: 10.1111/jpy.12025

The green algal genus Cladophora forms conspicuous nearshore populations in marine and freshwaters worldwide, commonly dominating peri-phyton communities. As the result of human activities, including the nutrient pollution of nearshore waters, Cladophora-dominated periphyton can form nuisance blooms. On the other hand, Cladophora has ecological functions that are beneficial, but less well appreciated. For example, Cladophora has previously been characterized as an ecological engineer because its complex structure fosters functional and taxonomic diversity of benthic microfauna. Here, we review classic and recent literature concerning taxonomy, cell biology, morphology, reproductive biology, and ecology of the genus Cladophora, to examine how this alga functions to modify habitats and influence littoral biogeochemistry. We review the evidence that Cladophora supports large, diverse populations of microalgal and bacterial epiphytes that influence the cycling of carbon and other key elements, and that the high production of cellulose and hydrocarbons by Cladophora-dominated periphyton has the potential for diverse technological applications, including wastewater remediation coupled to renewable biofuel production. We postulate that well-known aspects of Cladophora morphology, hydrodynamically stable and perennial holdfasts, distinctively branched architecture, unusually large cell and sporangial size and robust cell wall construction, are major factors contributing to the multiple roles of this organism as an ecological engineer.

Matched MeSH terms: Human Activities
Apes in the Anthropocene: flexibility and survival

Hockings KJ, McLennan MR, Carvalho S, Ancrenaz M, Bobe R, Byrne RW, et al.

Trends Ecol Evol, 2015 Apr;30(4):215-22.
PMID: 25766059 DOI: 10.1016/j.tree.2015.02.002

We are in a new epoch, the Anthropocene, and research into our closest living relatives, the great apes, must keep pace with the rate that our species is driving change. While a goal of many studies is to understand how great apes behave in natural contexts, the impact of human activities must increasingly be taken into account. This is both a challenge and an opportunity, which can importantly inform research in three diverse fields: cognition, human evolution, and conservation. No long-term great ape research site is wholly unaffected by human influence, but research at those that are especially affected by human activity is particularly important for ensuring that our great ape kin survive the Anthropocene.

Matched MeSH terms: Human Activities*
Fulltext Development of a User-Adaptable Human Fall Detection Based on Fall Risk Levels Using Depth Sensor

Nizam Y, Mohd MNH, Jamil MMA

Sensors (Basel), 2018 Jul 13;18(7).
PMID: 30011823 DOI: 10.3390/s18072260

Unintentional falls are a major public health concern for many communities, especially with aging populations. There are various approaches used to classify human activities for fall detection. Related studies have employed wearable, non-invasive sensors, video cameras and depth sensor-based approaches to develop such monitoring systems. The proposed approach in this study uses a depth sensor and employs a unique procedure which identifies the fall risk levels to adapt the algorithm for different people with their physical strength to withstand falls. The inclusion of the fall risk level identification, further enhanced and improved the accuracy of the fall detection. The experimental results showed promising performance in adapting the algorithm for people with different fall risk levels for fall detection.

Matched MeSH terms: Human Activities
River and fish pollution in Malaysia: A green ergonomics perspective

Poon WC, Herath G, Sarker A, Masuda T, Kada R

Appl Ergon, 2016 Feb 21.
PMID: 26911247 DOI: 10.1016/j.apergo.2016.02.009

Human activities, such as industrial, agricultural, and domestic pursuits, discharge effluents into riverine ecological systems that contains aquatic resources, such as fish, which are also used by humans. We conducted case studies in Malaysia to investigate the impacts of these human activities on water and fish resources, as well as on human well-being from an ergonomics perspective. This research shows that a green ergonomics approach can provide us with useful insights into sustainable relationships between humans and ecology in facilitating human well-being in consideration of the overall performance of the social-ecological system. Heavy metal concentrations contained in the effluents pollute river water and contaminate fish, eventually creating significant health risks and economic costs for residents, including the polluters. The study suggests a number of policy interventions to change human behavior and achieve greater collaboration between various levels of government, academia, civil society, and businesses to help establish sustainable relationships between humans and ecology in Malaysia.

Matched MeSH terms: Human Activities

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