Does 'portion size' matter? Brain responses to food and non-food cues presented in varying amounts.

Larger portions of food elicit greater intake than smaller portions of food, particularly when foods are high in energy density (kcal/g; ED). The neural mechanisms underlying this effect remain unclear. The present study used fMRI to assess brain activation to food (higher-ED, lower-ED) and non-food (office supplies) images presented in larger and smaller (i.e., age-appropriate) amounts in 61, 7-8-year-olds (29 male, 32 female) without obesity. Larger amounts of food increased activation in bilateral visual and right parahippocampal areas compared to smaller amounts; greater activation to food amount (larger > smaller) in this cluster was associated with smaller increases in food intake as portions increased. Activation to amount (larger > smaller) was stronger for food than office supplies in primary and secondary visual areas, but, for office supplies only, extended into bilateral parahippocampus, inferior parietal cortex, and additional visual areas (e.g., V7). Activation was greater for higher-vs. lower-ED food images in ventromedial prefrontal cortex for both larger and smaller amounts of food; however, this activation extended into left lateral orbital frontal cortex for smaller amounts only. Activation to food cues did not differ by familial risk for obesity. These results highlight potentially distinct neural pathways for encoding food energy content and quantity.

Fuzzy logic, geostatistics, and multiple linear models to evaluate irrigation metrics and their influencing factors in a drought-prone agricultural region.

The quality of water used for irrigation is one of the major threats to maintaining the long-term sustainability of agricultural practices. Although some studies have addressed the suitability of irrigation water in different parts of Bangladesh, the irrigation water quality in the drought-prone region has yet to be thoroughly studied using integrated novel approaches. This study aims to assess the suitability of irrigation water in the drought-prone agricultural region of Bangladesh using traditional irrigation metrics such as sodium percentage (NA%), magnesium adsorption ratio (MAR), Kelley's ratio (KR), sodium adsorption ratio (SAR), total hardness (TH), permeability index (PI), and soluble sodium percentage (SSP), along with novel irrigation indices such as irrigation water quality index (IWQI) and fuzzy irrigation water quality index (FIWQI). Thirty-eight water samples were taken from tube wells, river systems, streamlets, and canals in agricultural areas, then analyzed for cations and anions. The multiple linear regression model predicted that SAR (0.66), KR (0.74), and PI (0.84) were the primary important elements influencing electrical conductivity (EC). Based on the IWQI, all water samples fall into the "suitable" category for irrigation. The FIWQI suggests that 75% of the groundwater and 100% of the surface water samples are excellent for irrigation. The semivariogram model indicates that most irrigation metrics have moderate to low spatial dependence, suggesting strong agricultural and rural influence. Redundancy analysis shows that Na+, Ca2+, Cl-, K+, and HCO3- in water increase with decreasing temperature. Surface water and some groundwater in the southwestern and southeastern parts are suitable for irrigation. The northern and central parts are less suitable for agriculture because of elevated K+ and Mg2+ levels. This study determines irrigation metrics for regional water management and pinpoints suitable areas in the drought-prone region, which provides a comprehensive understanding of sustainable water management and actionable steps for stakeholders and decision-makers.

Human Micro-Expressions in Multimodal Social Behavioral Biometrics.

The advent of Social Behavioral Biometrics (SBB) in the realm of person identification has underscored the importance of understanding unique patterns of social interactions and communication. This paper introduces a novel multimodal SBB system that integrates human micro-expressions from text, an emerging biometric trait, with other established SBB traits in order to enhance online user identification performance. Including human micro-expression, the proposed method extracts five other original SBB traits for a comprehensive representation of the social behavioral characteristics of an individual. Upon finding the independent person identification score by every SBB trait, a rank-level fusion that leverages the weighted Borda count is employed to fuse the scores from all the traits, obtaining the final identification score. The proposed method is evaluated on a benchmark dataset of 250 Twitter users, and the results indicate that the incorporation of human micro-expression with existing SBB traits can substantially boost the overall online user identification performance, with an accuracy of 73.87% and a recall score of 74%. Furthermore, the proposed method outperforms the state-of-the-art SBB systems.

Assessing the challenges to medical waste management during the COVID-19 pandemic: Implications for the environmental sustainability in the emerging economies.

Emerging economies are struggling with proper and efficient management of waste due to their constrained resources and weak management. In recent days, this crisis has worsened due to the outbreak of the highly contagious COVID-19 pandemic. To avoid building up stockpiles and contaminating communities with potentially contagious medical waste (MW), and to ensure sustainability in the current and post-COVID-19 era, it is a dire need to develop and implement a safe and efficient medical waste management (MWM) system. This research, thereby, aims to identify, assess, and prioritize the key challenges to efficient and sustainable MWM to mitigate the impacts of the disruptions caused by situations like the pandemic in emerging economies. An integrated approach consisting of the Best-Worst Method (BWM), Interpretive Structural Modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) has been proposed to achieve the objectives. Based on the literature review and expert feedback, a total of seventeen challenges were identified and later prioritized by using BWM. The top twelve challenges have been further analyzed using ISM-MICMAC to examine their interrelationships. This study reveals that lack of proper law enforcement and insufficient financial support from investors and the government are two crucial challenges for efficient MWM implementation. The research insights can assist healthcare facility administrators, practitioners, and city managers in identifying the associated challenges and shaping strategic decisions for establishing and managing efficient MWM systems to ensure sustainable development in the post-COVID-19 era.

KinectGaitNet: Kinect-Based Gait Recognition Using Deep Convolutional Neural Network.

Over the past decade, gait recognition had gained a lot of attention in various research and industrial domains. These include remote surveillance, border control, medical rehabilitation, emotion detection from posture, fall detection, and sports training. The main advantages of identifying a person by their gait include unobtrusiveness, acceptance, and low costs. This paper proposes a convolutional neural network KinectGaitNet for Kinect-based gait recognition. The 3D coordinates of each of the body joints over the gait cycle are transformed to create a unique input representation. The proposed KinectGaitNet is trained directly using the 3D input representation without the necessity of the handcrafted features. The KinectGaitNet design allows avoiding gait cycle resampling, and the residual learning method ensures high accuracy without the degradation problem. The proposed deep learning architecture surpasses the recognition performance of all state-of-the-art methods for Kinect-based gait recognition by achieving 96.91% accuracy on UPCV and 99.33% accuracy on the KGB dataset. The method is the first, to the best of our knowledge, deep learning-based architecture that is based on a unique 3D input representation of joint coordinates. It achieves performance higher than previous traditional and deep learning methods, with fewer parameters and shorter inference time.

Head Kinematics in Youth Ice Hockey by Player Speed and Impact Direction.

Hockey is a fast-paced sport known for body checking, or intentional collisions used to separate opponents from the puck. Exposure to these impacts is concerning, as evidence suggests head impact exposure (HIE), even if noninjurious, can cause long-term brain changes. Currently, there is limited understanding of the effect of impact direction and collision speed on HIE. Video analysis was used to determine speed and direction for 162 collisions from 13 youth athletes. These data were paired with head kinematic data collected with an instrumented mouthpiece. Relationships between peak resultant head kinematics and speeds were evaluated with linear regression. Mean athlete speeds and relative velocity between athletes ranged from 2.05 to 2.76 m/s. Mean peak resultant linear acceleration, rotational velocity, and rotational acceleration were 13.1 g, 10.5 rad/s, and 1112 rad/s2, respectively. Significant relationships between speeds and head kinematics emerged when stratified by contact characteristics. HIE also varied by direction of collision; most collisions occurred in the forward-oblique (ie, offset from center) direction; frontal collisions had the greatest magnitude peak kinematics. These findings indicate that HIE in youth hockey is influenced by speed and direction of impact. This study may inform future strategies to reduce the severity of HIE in hockey.

A new tool for assessing the risk of fall in children with severe disability: development of the ALICE scale.

Introduction: It is known in the literature that the main cause of physical impairment in children with severe disabilities is falling, which can worsen their already compromised condition. There are no specific scales for this population in the literature, neither in Italian nor in other languages. We created and validated a scale for assessing the risk of falling in children with severe disabilities. Study design: Observational prospective study. Methods: We enrolled children (inpatients or day-hospital) admitted to the "Santa Maria Bambina Centre" of the "Fondazione Onlus Sacra Famiglia" in Cesano Boscone, Milan; the Content Validity Index of the Scale was calculated to assess the content validity of a new scale (ALICE). Cronbach's alpha coefficient (α) was used to examine internal consistency, Spearman's rho coefficient to test inter-rater reliability. Sensitivity, specificity, positive and negative predictive values were calculated. Results: Out of 48 patients enrolled, 14 fell (29.2%). The ALICE scale, with cut-off set at 16, showed a sensitivity of 100%, a specificity of 88.2%, a positive predictive value of 77.8% and a negative predictive value of 100%. The Content Validity Index of the Scale (=0.93), inter-rater reliability (rho=0.91, p<0.001) and Cronbach's alpha (=0.72) were satisfactory. Conclusions: The ALICE scale seems reliable and valid in the disabled population and can be applied by nurses. Further studies with larger samples and a multicentre design are needed.

Arsenic bioaccessibility and fractionation in abandoned mine soils from selected sites in New South Wales, Australia and human health risk assessment.

Understanding the transport behaviour of arsenic (As) from soils to humans is critical when undertaking human health risk assessment and contamination control. This research examined As bioaccessibility in different As fractions and particle size fractions of As-enriched mine soils using different extractions. Bioaccessibility of As ranged from 0.24% to 32% for Solubility Bioaccessibility Research Consortium (SBRC) and Physiologically Based Extraction Test (PBET) methods, with extractable As (using 0.43 M HNO3) being 1.3-24.9%. The highest As bioaccessibility (19-32%) was consistently observed in the fine particle size fraction (< 53 µm) of all three extractions. Sequential extractions revealed that As fractions were mostly associated with crystalline (30-73%) and amorphous (9-59%) Fe/Al oxyhydroxides. The bioaccessibility of As in the gastric phase of SBRC and PBET methods highlighted a positive correlation (R2 = 0.83-0.88, p < 0.01) with exchangeable, surface and amorphous- bound As fractions, while the intestinal phase showed a strong positive correlation (R2 = 0.85-0.89, p < 0.01) with exchangeable and surface bound fractions. The study revealed that As bioaccessibility in soils can potentially be determined using the 0.43 M HNO3 extraction procedure. Health risk assessment confirmed that there was a strong increase in chronic daily intake, hazard quotient and cancer risk, with a reduction in particle size.

A randomised controlled trial of the pectoral nerves-2 (PECS-2) block for radical mastectomy.

We randomly allocated 50 women scheduled for radical mastectomy to pectoral nerves-2 (PECS-2) block (n = 25) or no block (n = 25), 20 and 22 of whom we analysed for the primary outcome of a cumulative 24-h postoperative morphine dose. We gave intra-operative sufentanil, magnesium, dexamethasone and droperidol. Participants received regular postoperative paracetamol, ibuprofen and patient-controlled intravenous morphine. Pectoral nerves-2 block reduced mean (SD) cumulative 24 h postoperative morphine dose from 9.7 (8.9) mg to 5.0 (5.4) mg and 48 h morphine dose from 12.8 (12.5) mg to 6.0 (6.5) mg, p = 0.04 for both. The mean (SD) pain scores 24 h and 48 h after surgery were similar with or without block: 0.8 (1.4) vs. 1.2 (1.9), p = 0.39; and 0.2 (0.4) vs. 0.9 (1.8), p = 0.09, respectively. Rates of postoperative nausea, vomiting and pruritus were unaffected. Rates of chronic pain at six postoperative months were 2/19 and 2/18 after block and no block, respectively, p = 0.95.

Codon-based encoding for DNA sequence analysis.

With the exponential growth of biological sequence data (DNA or Protein Sequence), DNA sequence analysis has become an essential task for biologist to understand the features, functions, structures, and evolution of species. Encoding DNA sequences is an effective method to extract the features from DNA sequences. It is commonly used for visualizing DNA sequences and analyzing similarities/dissimilarities between different species or cells. Although there have been many encoding approaches proposed for DNA sequence analysis, we require more elegant approaches for higher accuracy. In this paper, we propose a noble encoding approach for measuring the degree of similarity/dissimilarity between different species. Our approach can preserve the physiochemical properties, positional information, and the codon usage bias of nucleotides. An extensive performance study shows that our approach provides higher accuracy than existing approaches in terms of the degree of similarity.

The Cerebellar Response to Visual Portion Size Cues Is Associated with the Portion Size Effect in Children.

The neural mechanisms underlying susceptibility to eating more in response to large portions (i.e., the portion size effect) remain unclear. Thus, the present study examined how neural responses to portion size relate to changes in weight and energy consumed as portions increase. Associations were examined across brain regions traditionally implicated in appetite control (i.e., an appetitive network) as well as the cerebellum, which has recently been implicated in appetite-related processes. Children without obesity (i.e., BMI-for-age-and-sex percentile < 90; N = 63; 55% female) viewed images of larger and smaller portions of food during fMRI and, in separate sessions, ate four meals that varied in portion size. Individual-level linear and quadratic associations between intake (kcal, grams) and portion size (i.e., portion size slopes) were estimated. The response to portion size in cerebellar lobules IV-VI was associated with the quadratic portion size slope estimated from gram intake; a greater response to images depicting smaller compared to larger portions was associated with steeper increases in intake with increasing portion sizes. Within the appetitive network, neural responses were not associated with portion size slopes. A decreased cerebellar response to larger amounts of food may increase children's susceptibility to overeating when excessively large portions are served.

A review of microplastic threat mitigation in Asian lentic environments.

Microplastic (MP) pollution has evolved into a significant worldwide environmental concern due to its widespread sources, enduring presence, and adverse effects on lentic ecosystems and human well-being. The growing awareness of the hidden threat posed by MPs in lentic ecosystems has emphasized the need for more in-depth research. Unlike marine environments, there remain unanswered questions about MP hotspots, ecotoxic effects, transport mechanisms, and fragmentation in lentic ecosystems. The introduction of MPs represents a novel threat to long-term environmental health, posing unresolved challenges for sustainable management. While MP pollution in lentic ecosystems has garnered global attention due to its ecotoxicity, our understanding of MP hotspots in lakes from an Asian perspective remains limited. Hence, the aim of this review is to provide a comprehensive analysis of MP hotspots, morphological attributes, ecotoxic impacts, sustainable solutions, and future challenges across Asia. The review summarizes the methods employed in previous studies and the techniques for sampling and analyzing microplastics in lake water and sediment. Notably, most studies concerning lake microplastics tend to follow the order of China > India > Pakistan > Nepal > Turkey > Bangladesh. Additionally, this review critically addresses the analysis of microplastics in lake water and sediment, shedding light on the prevalent net-based sampling methods. Ultimately, this study emphasizes the existing research gaps and suggests new research directions, taking into account recent advancements in the study of microplastics in lentic environments. In conclusion, the review advocates for sustainable interventions to mitigate MP pollution in the future, highlighting the presence of MPs in Asian lakes, water, and sediment, and their potential ecotoxicological repercussions on both the environment and human health.

New constraint on the existence of the µ+ → e+ γ decay.

The analysis of a combined data set, totaling 3.6 × 10(14) stopped muons on target, in the search for the lepton flavor violating decay µ(+) → e(+)γ is presented. The data collected by the MEG experiment at the Paul Scherrer Institut show no excess of events compared to background expectations and yield a new upper limit on the branching ratio of this decay of 5.7 × 10(-13) (90% confidence level). This represents a four times more stringent limit than the previous world best limit set by MEG.

Evaluating barriers to sustainable boiler operation in the apparel manufacturing industry: Implications for mitigating operational hazards in the emerging economies.

The efficiency with which conventional boilers perform, in terms of sustainability, is affected by a variety of factors. Unsustainable boiler operating practices are still surprisingly frequent in developing countries, resulting in environmental liabilities and catastrophic accidents. It is a serious problem in developing countries like Bangladesh, where boilers are utilized extensively in the apparel manufacturing sector. However, no research has yet examined the challenges or barriers associated with sustainable boiler operation in the apparel manufacturing sector. This study, thereby, utilizes an integrated MCDM approach, combining the fuzzy theory and the decision-making trial and evaluation laboratory (DEMATEL) method, to identify, prioritize, and explore the relations among the barriers to sustainable boiler operation in the apparel manufacturing industry, from an emerging economy perspective. The barriers were initially identified from the literature and a visual survey of 127 factories. After expert validation, thirteen barriers were finally selected to be analyzed utilizing the fuzzy DEMATEL method. The study findings revealed that 'Absence of water treatment facilities', 'Fossil fuel burning and GHG emissions', and 'Excessive consumption of groundwater' are the three most prominent barriers to sustainable boiler operation. The cause-effect relations among the barriers suggest that 'Inadequate compliance with safety and hazard regulations' is the most influential and 'Fossil fuel burning and GHG emissions' is the most influenced barrier. This study is expected to guide the managers and policymakers of the apparel manufacturing sector in successfully overcoming the barriers to sustainable boiler operation, thus mitigating the operational hazards and achieving the sustainable development goals (SDGs).

Analysis of the fire risks and mitigation approaches in the apparel manufacturing industry: Implications toward operational safety and sustainability.

Fire risks pose a substantial threat to the apparel manufacturing industry since they can lead to immense property damage, potential loss of life, disruption of business operations, and reputational damage. In an emerging economy like Bangladesh, fire-related hazards are crucial due to the numerous deadly industrial fire incidents in recent years. This research, thereby, proposes an integrated multi-criteria decision-making (MCDM) framework to identify and mitigate fire risk hazards in the apparel manufacturing industry. Initially, the study identified 30 significant fire risk factors from the literature review. Then, after expert validation, an integrated Best Worst Method (BWM) and Weighted Sum Model (WSM) framework was utilized to prioritize the fire risk factors. Twenty-three mitigation actions were proposed afterward for the top-ranked risk factors based on National Fire Protection Association (NFPA) codes. An Interpretive Structural Modeling (ISM) with a Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was later used to explore the interrelationships and dependencies among the mitigation actions. The ranking obtained from the BWM-WSM assessment revealed 'combustible storage unseparated by fire-rated construction,' 'non-standard inspection, testing, and maintenance', and 'inadequate means of egress for the occupant load' as the three most critical fire risk factors. The ISM-MICMAC analysis revealed 'fire-rated construction' and 'standardized detection and protection' as the most-driving mitigation actions. The study outcomes are expected to aid the managers and policymakers in emerging economies in formulating sustainable fire risk management strategies for the apparel industry and thus improve the operational safety and resilience of the sector.

Assessing the critical success factors for implementing industry 4.0 in the pharmaceutical industry: Implications for supply chain sustainability in emerging economies.

The emerging technologies of Industry 4.0 (I4.0) are crucial to incorporating agility, sustainability, smartness, and competitiveness in the business model, enabling long-term sustainability practices in the pharmaceutical supply chain (PSC). By leveraging the latest technologies of I4.0, pharmaceutical companies can gain real-time visibility into their supply chain (SC) operations, allowing them to make data-driven decisions that improve SC performance, efficiency, resilience, and sustainability. However, to date, no research has examined the critical success factors (CSFs) that enable the pharmaceutical industry to adopt I4.0 successfully to enhance overall SC sustainability. This study, therefore, analyzed the potential CSFs for adopting I4.0 to increase all facets of sustainability in the PSC, especially from the perspective of an emerging economy like Bangladesh. Initially, sixteen CSFs were identified through a comprehensive literature review and expert validation. Later, the finalized CSFs were clustered into three relevant groups and analyzed using a Bayesian best-worst method (BWM)-based multi-criteria decision-making (MCDM) framework. The study findings revealed that "sufficient investment for technological advancement", "digitalized product monitoring and traceability", and "dedicated and robust research and development (R&D) team" are the top three CSFs to adopt I4.0 in the PSC. The study's findings can aid industrial practitioners, managers, and policymakers in creating effective action plans for efficiently adopting I4.0 in PSC to avail of its competitive benefits and ensure a sustainable future for the pharmaceutical industry.

Managing the invisible threat of microplastics in marine ecosystems: Lessons from coast of the Bay of Bengal.

Invisible microplastics (MP) have become a significant problem worldwide in recent years. Although many studies have highlighted the sources, effects, and fate of MPs pollution on various ecosystems in developed countries, there is limited information on MPs in the marine ecosystem along the northeastern coast of the Bay of Bengal (BoB). Coastal ecosystems along the BoB coasts are critical to a biodiverse ecology that supports human survival and resource extraction. However, the multi-environmental hotspots, ecotoxicity effects, transport mechanisms, fates, and intervention measures to control MP pollution initiatives along the BoB coasts have received little attention. Therefore, this review aims to highlight the multi-environmental hotspots, ecotoxicity effects, sources, fates, and intervention measures of MP in the northeastern BoB to understand how MP spreads in the nearshore marine ecosystem. This study critically evaluates the hotspots and ecotoxic effects of pollution from MP on the coastal multi-environment, e.g., soil, sediment, salt, water, and fish, as well as current intervention measures and additional mitigation recommendations. This study identified the northeastern part of the BoB as a hotspot for MP. In addition, the transport mechanisms and fate of MP in different environmental compartments are highlighted, as are research gaps and potential future research areas. Research on the ecotoxic effects of MP on BoB marine ecosystems must be a top priority, given the increasing use of plastics and the presence of significant marine products worldwide. The knowledge gained from this study would inform decision-makers and stakeholders in a way that could reduce the impact of the legacy of micro- and nanoplastics in the area. This study also proposes structural and non-structural measures to mitigate the effects of MPs and promote sustainable management.

Personal protective equipment-derived pollution during Covid-19 era: A critical review of ecotoxicology impacts, intervention strategies, and future challenges.

During the COVID-19 pandemic, people used personal protective equipment (PPE) to lessen the spread of the virus. The release of microplastics (MPs) from discarded PPE is a new threat to the long-term health of the environment and poses challenges that are not yet clear. PPE-derived MPs have been found in multi-environmental compartments, e.g., water, sediments, air, and soil across the Bay of Bengal (BoB). As COVID-19 spreads, healthcare facilities use more plastic PPE, polluting aquatic ecosystems. Excessive PPE use releases MPs into the ecosystem, which aquatic organisms ingest, distressing the food chain and possibly causing ongoing health problems in humans. Thus, post-COVID-19 sustainability depends on proper intervention strategies for PPE waste, which have received scholarly interest. Although many studies have investigated PPE-induced MPs pollution in the BoB countries (e.g., India, Bangladesh, Sri Lanka, and Myanmar), the ecotoxicity impacts, intervention strategies, and future challenges of PPE-derived waste have largely gone unnoticed. Our study presents a critical literature review covering the ecotoxicity impacts, intervention strategies, and future challenges across the BoB countries (e.g., India (162,034.45 tons), Bangladesh (67,996 tons), Sri Lanka (35,707.95 tons), and Myanmar (22,593.5 tons). The ecotoxicity impacts of PPE-derived MPs on human health and other environmental compartments are critically addressed. The review's findings infer a gap in the 5R (Reduce, Reuse, Recycle, Redesign, and Restructure) Strategy's implementation in the BoB coastal regions, hindering the achievement of UN SDG-12. Despite widespread research advancements in the BoB, many questions about PPE-derived MPs pollution from the perspective of the COVID-19 era still need to be answered. In response to the post-COVID-19 environmental remediation concerns, this study highlights the present research gaps and suggests new research directions considering the current MPs' research advancements on COVID-related PPE waste. Finally, the review suggests a framework for proper intervention strategies for reducing and monitoring PPE-derived MPs pollution in the BoB countries.

Prevalence of Dental Caries in Children in Mymensingh and Its Associated Risk Factors: A Cross-Sectional Study.

BACKGROUND: Children suffer from various oral and periodontal diseases. Dental caries is one of the most prevalent oral diseases among children in the world. This study was conducted to identify the prevalence and risk factors of dental caries in children in Mymensingh, Bangladesh. METHODS: A cross-sectional study was conducted on 362 pediatric patients who attended the Dental Unit of Mymensingh Medical College from March to September 2019. The sample size was calculated using a statistical formula and the children were selected using a systematic random sampling technique. Children and their guardians were interviewed and data were recorded using a structured questionnaire. Risk factors were analyzed using multivariate logistic regression. RESULTS: The overall prevalence of dental caries was 82.7%. The prevalence of caries was significantly higher in aged children (8-10 years) and also in rural, low-income, and illiterate families. Seven significant risk factors were identified that included residence in the rural area (OR: 7.31 [1.73-30.83]), a parental income of BDT ≤ 20,000 per month (OR: 4.75 [1.49-15.05]), reduced duration (≤1 min) of teeth cleaning (OR: 18.54 [2.05-168.17]), teeth cleaning before breakfast (OR: 93.30 [10.95-795.32]), the spoon-feeding method (OR: 12.57 [2.09-75.61]), long-term (37-48 months) breastfeeding (OR: 212.53 [8.69-5195.25]), and family oral problem (OR: 8.20 [2.57-26.16]). CONCLUSIONS: The prevalence of dental caries among the children in Mymensingh is very high and was associated with residence in rural areas, parental income, reduced duration of teeth cleaning, teeth cleaning before breakfast, the spoon-feeding method, long-term breastfeeding, and family oral problems.

Soil washing of arsenic from mixed contaminated abandoned mine soils and fate of arsenic after washing.

Arsenic contamination in abandoned soils is a global concern which warrants an effective method of remediation. In this study, two organic acids and one biodegradable chelating agent were used to treat arsenic (As) contaminated abandoned mine soils. The concentration of As was 19,100 and 75,350 (mg/kg) for Webbs Consols (WC) and Mole River (MR) samples, respectively. X-ray diffraction and scanning electron microscopy confirmed that tooeleite, arsenopyrite, scorodite and quartz were the major minerals in these soils. A major portion of the As was composed of amorphous and crystalline oxides of Fe and Al determined by sequential extraction. Among the three washing reagents (oxalic acid, citric acid and EDDS) oxalic acid showed the best performance for extracting As. Based on the batch experiment, 0.5 M oxalic acid and 3 h of washing was the most efficient treatment to extract As and other trace elements. Extraction of As, Fe, and Pb was 70, 55, and 48% respectively for WC, while 68, 45 and 63% respectively for MR soil. Oxalic acid extracted 75 and 83% of As and Fe, respectively from tooeleite. Leachability and bioaccessibility of As and Fe in the treated soil was reduced due to washing. However, bioaccessibility and leachability of Pb in soil and Fe and As in tooeleite increased in washed samples. Though the leachability and bioaccessibility of As and Fe in soil was reduced in the treated soil, As still exceeded the USEPA criteria (5 mg/L) which is needed to successfully remediate soil by washing. Soil washing and subsequent solidification/stabilization could be an alternative option to remediate extremely contaminated abandoned mine soil.