Search results for: Meng Nan Chong
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 194

Search results for: Meng Nan Chong

14 Association between Organophosphate Pesticides Exposure and Cognitive Behavior in Taipei Children

Authors: Meng-Ying Chiu, Yu-Fang Huang, Pei-Wei Wang, Yi-Ru Wang, Yi-Shuan Shao, Mei-Lien Chen

Abstract:

Background: Organophosphate pesticides (OPs) are the most heavily used pesticides in agriculture in Taiwan. Therefore, they are commonly detected in general public including pregnant women and children. These compounds are proven endocrine disrupters that may affect the neural development in humans. The aim of this study is to assess the OPs exposure of children in 2 years of age and to examine the association between the exposure concentrations and neurodevelopmental effects in children. Methods: In a prospective cohort of 280 mother-child pairs, urine samples of prenatal and postnatal were collected from each participant and analyzed for metabolites of OPs by using gas chromatography-mass spectrometry. Six analytes were measured including dimethylphosphate (DMP), dimethylthiophosphate (DMTP), dimethyldithiophosphate (DMDTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP). This study created a combined concentration measure for dimethyl compounds (DMs) consisting of the three dimethyl metabolites (DMP, DMTP, and DMDTP), for diethyl compounds (DEs) consisting of the three diethyl metabolites (DEP, DETP, and DEDTP) and six dialkyl phosphate (DAPs). The Bayley Scales of Infant and Toddler Development (Bayley-III) was used to assess children's cognitive behavior at 2 years old. The association between OPs exposure and Bayley-III scale score was determined by using the Mann-Whitney U test. Results: The measurements of urine samples are still on-going. This preliminary data are the report of 56 children aged 2 from the cohort. The detection rates for DMP, DMTP, DMDTP, DEP, DETP, and DEDTP are 80.4%, 69.6%, 64.3%, 64.3%, 62.5%, and 75%, respectively. After adjusting the creatinine concentrations of urine, the median (nmol/g creatinine) of urinary DMP, DMTP, DMDTP, DEP, DETP, DEDTP, DMs, DEs, and DAPs are 153.14, 53.32, 52.13, 19.24, 141.65, 192.17, 308.8, 311.6, and 702.11, respectively. The concentrations of urine are considerably higher than that in other countries. Children’s cognitive behavior was used three scales for Bayley-III, including cognitive, language and motor. In Mann-Whitney U test, the higher levels of DEs had significantly lower motor score (p=0.037), but no significant association was found between the OPs exposure levels and the score of either cognitive or language. Conclusion: The limited sample size suggests that Taipei children are commonly exposed to OPs and OPs exposure might affect the cognitive behavior of young children. This report will present more data to verify the results. The predictors of OPs concentrations, such as dietary pattern will also be included.

Keywords: biomonitoring, children, neurodevelopment, organophosphate pesticides exposure

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13 TARF: Web Toolkit for Annotating RNA-Related Genomic Features

Authors: Jialin Ma, Jia Meng

Abstract:

Genomic features, the genome-based coordinates, are commonly used for the representation of biological features such as genes, RNA transcripts and transcription factor binding sites. For the analysis of RNA-related genomic features, such as RNA modification sites, a common task is to correlate these features with transcript components (5'UTR, CDS, 3'UTR) to explore their distribution characteristics in terms of transcriptomic coordinates, e.g., to examine whether a specific type of biological feature is enriched near transcription start sites. Existing approaches for performing these tasks involve the manipulation of a gene database, conversion from genome-based coordinate to transcript-based coordinate, and visualization methods that are capable of showing RNA transcript components and distribution of the features. These steps are complicated and time consuming, and this is especially true for researchers who are not familiar with relevant tools. To overcome this obstacle, we develop a dedicated web app TARF, which represents web toolkit for annotating RNA-related genomic features. TARF web tool intends to provide a web-based way to easily annotate and visualize RNA-related genomic features. Once a user has uploaded the features with BED format and specified a built-in transcript database or uploaded a customized gene database with GTF format, the tool could fulfill its three main functions. First, it adds annotation on gene and RNA transcript components. For every features provided by the user, the overlapping with RNA transcript components are identified, and the information is combined in one table which is available for copy and download. Summary statistics about ambiguous belongings are also carried out. Second, the tool provides a convenient visualization method of the features on single gene/transcript level. For the selected gene, the tool shows the features with gene model on genome-based view, and also maps the features to transcript-based coordinate and show the distribution against one single spliced RNA transcript. Third, a global transcriptomic view of the genomic features is generated utilizing the Guitar R/Bioconductor package. The distribution of features on RNA transcripts are normalized with respect to RNA transcript landmarks and the enrichment of the features on different RNA transcript components is demonstrated. We tested the newly developed TARF toolkit with 3 different types of genomics features related to chromatin H3K4me3, RNA N6-methyladenosine (m6A) and RNA 5-methylcytosine (m5C), which are obtained from ChIP-Seq, MeRIP-Seq and RNA BS-Seq data, respectively. TARF successfully revealed their respective distribution characteristics, i.e. H3K4me3, m6A and m5C are enriched near transcription starting sites, stop codons and 5’UTRs, respectively. Overall, TARF is a useful web toolkit for annotation and visualization of RNA-related genomic features, and should help simplify the analysis of various RNA-related genomic features, especially those related RNA modifications.

Keywords: RNA-related genomic features, annotation, visualization, web server

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12 Case Report: Opioid Sparing Anaesthesia with Dexmedetomidine in General Surgery

Authors: Shang Yee Chong

Abstract:

Perioperative pain is a complex mechanism activated by various nociceptive, neuropathic, and inflammatory pathways. Opioids have long been a mainstay for analgesia in this period, even as we are continuously moving towards a multimodal model to improve pain control while minimising side effects. Dexmedetomidine, a potent alpha-2 agonist, is a useful sedative and hypnotic agent. Its use in the intensive care unit has been well described, and it is increasingly an adjunct intraoperatively for its opioid sparing effects and to decrease pain scores. We describe a case of a general surgical patient in whom minimal opioids was required with dexmedetomidine use. The patient was a 61-year-old Indian gentleman with a history of hyperlipidaemia and type 2 diabetes mellitus, presenting with rectal adenocarcinoma detected on colonoscopy. He was scheduled for a robotic ultra-low anterior resection. The patient was induced with intravenous fentanyl 75mcg, propofol 160mg and atracurium 40mg. He was intubated conventionally and mechanically ventilated. Anaesthesia was maintained with inhalational desflurane and anaesthetic depth was measured with the Masimo EEG Sedline brain function monitor. An initial intravenous dexmedetomidine dose (bolus) of 1ug/kg for 10 minutes was given prior to anaesthetic induction and thereafter, an infusion of 0.2-0.4ug/kg/hr to the end of surgery. In addition, a bolus dose of intravenous lignocaine 1.5mg/kg followed by an infusion at 1mg/kg/hr throughout the surgery was administered. A total of 10mmol of magnesium sulphate and intravenous paracetamol 1000mg were also given for analgesia. There were no significant episodes of bradycardia or hypotension. A total of intravenous phenylephrine 650mcg was given throughout to maintain the patient’s mean arterial pressure within 10-15mmHg of baseline. The surgical time lasted for 5 hours and 40minutes. Postoperatively the patient was reversed and extubated successfully. He was alert and comfortable and pain scores were minimal in the immediate post op period in the postoperative recovery unit. Time to first analgesia was 4 hours postoperatively – with paracetamol 1g administered. This was given at 6 hourly intervals strictly for 5 days post surgery, along with celecoxib 200mg BD as prescribed by the surgeon regardless of pain scores. Oral oxycodone was prescribed as a rescue analgesic for pain scores > 3/10, but the patient did not require any dose. Neither was there nausea or vomiting. The patient was discharged on postoperative day 5. This case has reinforced the use of dexmedetomidine as an adjunct in general surgery cases, highlighting its excellent opioid-sparing effects. In the entire patient’s hospital stay, the only dose of opioid he received was 75mcg of fentanyl at the time of anaesthetic induction. The patient suffered no opioid adverse effects such as nausea, vomiting or postoperative ileus, and pain scores varied from 0-2/10. However, intravenous lignocaine infusion was also used in this instance, which would have helped improve pain scores. Paracetamol, lignocaine, and dexmedetomidine is thus an effective, opioid-sparing combination of multi-modal analgesia for major abdominal surgery cases.

Keywords: analgesia, dexmedetomidine, general surgery, opioid sparing

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11 Study on the Focus of Attention of Special Education Students in Primary School

Authors: Tung-Kuang Wu, Hsing-Pei Hsieh, Ying-Ru Meng

Abstract:

Special Education in Taiwan has been facing difficulties including shortage of teachers and lack in resources. Some students need to receive special education are thus not identified or admitted. Fortunately, information technologies can be applied to relieve some of the difficulties. For example, on-line multimedia courseware can be used to assist the learning of special education students and take pretty much workload from special education teachers. However, there may exist cognitive variations between students in special or regular educations, which suggests the design of online courseware requires different considerations. This study aims to investigate the difference in focus of attention (FOA) between special and regular education students of primary school in viewing the computer screen. The study is essential as it helps courseware developers in determining where to put learning elements that matter the most on the right position of screen. It may also assist special education specialists to better understand the subtle differences among various subtypes of learning disabilities. This study involves 76 special education students (among them, 39 are students with mental retardation, MR, and 37 are students with learning disabilities, LDs) and 42 regular education students. The participants were asked to view a computer screen showing a picture partitioned into 3 × 3 areas with each area filled with text or icon. The subjects were then instructed to mark on the prior given paper sheets, which are also partitioned into 3 × 3 grids, the areas corresponding to the pictures on the computer screen that they first set their eyes on. The data are then collected and analyzed. Major findings are listed: 1. In both text and icon scenario, significant differences exist in the first preferred FOA between special and regular education students. The first FOA for the former is mainly on area 1 (upper left area, 53.8% / 51.3% for MR / LDs students in text scenario; and 53.8% / 56.8% for MR / LDs students in icons scenario), while the latter on area 5 (middle area, 50.0% and 57.1% in text and icons scenarios). 2. The second most preferred area in text scenario for students with MR and LDs are area 2 (upper-middle, 20.5%) and 5 (middle area, 24.3%). In icons scenario, the results are similar, but lesser in percentage. 3. Students with LDs that show similar preference (either in text or icons scenarios) in FOA to regular education students tend to be of some specific sub-type of learning disabilities. For instance, students with LDs that chose area 5 (middle area, either in text or icon scenario) as their FOA are mostly ones that have reading or writing disability. Also, three (out of 13) subjects in this category, after going through the rediagnosis process, were excluded from being learning disabilities. In summary, the findings suggest when designing multimedia courseware for students with MR and LDs, the essential learning elements should be placed on area 1, 2 and 5. In addition, FOV preference may also potentially be used as an indicator for diagnosing students with LDs.

Keywords: focus of attention, learning disabilities, mental retardation, on-line multimedia courseware, special education

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10 Integrating System-Level Infrastructure Resilience and Sustainability Based on Fractal: Perspectives and Review

Authors: Qiyao Han, Xianhai Meng

Abstract:

Urban infrastructures refer to the fundamental facilities and systems that serve cities. Due to the global climate change and human activities in recent years, many urban areas around the world are facing enormous challenges from natural and man-made disasters, like flood, earthquake and terrorist attack. For this reason, urban resilience to disasters has attracted increasing attention from researchers and practitioners. Given the complexity of infrastructure systems and the uncertainty of disasters, this paper suggests that studies of resilience could focus on urban functional sustainability (in social, economic and environmental dimensions) supported by infrastructure systems under disturbance. It is supposed that urban infrastructure systems with high resilience should be able to reconfigure themselves without significant declines in critical functions (services), such as primary productivity, hydrological cycles, social relations and economic prosperity. Despite that some methods have been developed to integrate the resilience and sustainability of individual infrastructure components, more work is needed to enable system-level integration. This research presents a conceptual analysis framework for integrating resilience and sustainability based on fractal theory. It is believed that the ability of an ecological system to maintain structure and function in face of disturbance and to reorganize following disturbance-driven change is largely dependent on its self-similar and hierarchical fractal structure, in which cross-scale resilience is produced by the replication of ecosystem processes dominating at different levels. Urban infrastructure systems are analogous to ecological systems because they are interconnected, complex and adaptive, are comprised of interconnected components, and exhibit characteristic scaling properties. Therefore, analyzing resilience of ecological system provides a better understanding about the dynamics and interactions of infrastructure systems. This paper discusses fractal characteristics of ecosystem resilience, reviews literature related to system-level infrastructure resilience, identifies resilience criteria associated with sustainability dimensions, and develops a conceptual analysis framework. Exploration of the relevance of identified criteria to fractal characteristics reveals that there is a great potential to analyze infrastructure systems based on fractal. In the conceptual analysis framework, it is proposed that in order to be resilient, urban infrastructure system needs to be capable of “maintaining” and “reorganizing” multi-scale critical functions under disasters. Finally, the paper identifies areas where further research efforts are needed.

Keywords: fractal, urban infrastructure, sustainability, system-level resilience

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9 Controlled Nano Texturing in Silicon Wafer for Excellent Optical and Photovoltaic Properties

Authors: Deb Kumar Shah, M. Shaheer Akhtar, Ha Ryeon Lee, O-Bong Yang, Chong Yeal Kim

Abstract:

The crystalline silicon (Si) solar cells are highly renowned photovoltaic technology and well-established as the commercial solar technology. Most of the solar panels are globally installed with the crystalline Si solar modules. At the present scenario, the major photovoltaic (PV) market is shared by c-Si solar cells, but the cost of c-Si panels are still very high as compared with the other PV technology. In order to reduce the cost of Si solar panels, few necessary steps such as low-cost Si manufacturing, cheap antireflection coating materials, inexpensive solar panel manufacturing are to be considered. It is known that the antireflection (AR) layer in c-Si solar cell is an important component to reduce Fresnel reflection for improving the overall conversion efficiency. Generally, Si wafer exhibits the 30% reflection because it normally poses the two major intrinsic drawbacks such as; the spectral mismatch loss and the high Fresnel reflection loss due to the high contrast of refractive indices between air and silicon wafer. In recent years, researchers and scientists are highly devoted to a lot of researches in the field of searching effective and low-cost AR materials. Silicon nitride (SiNx) is well-known AR materials in commercial c-Si solar cells due to its good deposition and interaction with passivated Si surfaces. However, the deposition of SiNx AR is usually performed by expensive plasma enhanced chemical vapor deposition (PECVD) process which could have several demerits like difficult handling and damaging the Si substrate by plasma when secondary electrons collide with the wafer surface for AR coating. It is very important to explore new, low cost and effective AR deposition process to cut the manufacturing cost of c-Si solar cells. One can also be realized that a nano-texturing process like the growth of nanowires, nanorods, nanopyramids, nanopillars, etc. on Si wafer can provide a low reflection on the surface of Si wafer based solar cells. The above nanostructures might be enhanced the antireflection property which provides the larger surface area and effective light trapping. In this work, we report on the development of crystalline Si solar cells without using the AR layer. The Silicon wafer was modified by growing nanowires like Si nanostructures using the wet controlled etching method and directly used for the fabrication of Si solar cell without AR. The nanostructures over Si wafer were optimized in terms of sizes, lengths, and densities by changing the etching conditions. Well-defined and aligned wires like structures were achieved when the etching time is 20 to 30 min. The prepared Si nanostructured displayed the minimum reflectance ~1.64% at 850 nm with the average reflectance of ~2.25% in the wavelength range from 400-1000 nm. The nanostructured Si wafer based solar cells achieved the comparable power conversion efficiency in comparison with c-Si solar cells with SiNx AR layer. From this study, it is confirmed that the reported method (controlled wet etching) is an easy, facile method for preparation of nanostructured like wires on Si wafer with low reflectance in the whole visible region, which has greater prospects in developing c-Si solar cells without AR layer at low cost.

Keywords: chemical etching, conversion efficiency, silicon nanostructures, silicon solar cells, surface modification

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8 Characterization of Herberine Hydrochloride Nanoparticles

Authors: Bao-Fang Wen, Meng-Na Dai, Gao-Pei Zhu, Chen-Xi Zhang, Jing Sun, Xun-Bao Yin, Yu-Han Zhao, Hong-Wei Sun, Wei-Fen Zhang

Abstract:

A drug-loaded nanoparticles containing berberine hydrochloride (BH/FA-CTS-NPs) was prepared. The physicochemical characterizations of BH/FA-CTS-NPs and the inhibitory effect on the HeLa cells were investigated. Folic acid-conjugated chitosan (FA-CTS) was prepared by amino reaction of folic acid active ester and chitosan molecules; BH/FA-CTS-NPs were prepared using ionic cross-linking technique with BH as a model drug. The morphology and particle size were determined by Transmission Electron Microscope (TEM). The average diameters and polydispersity index (PDI) were evaluated by Dynamic Light Scattering (DLS). The interaction between various components and the nanocomplex were characterized by Fourier Transform Infrared Spectroscopy (FT-IR). The entrapment efficiency (EE), drug-loading (DL) and in vitro release were studied by UV spectrophotometer. The effect of cell anti-migratory and anti-invasive actions of BH/FA-CTS-NPs were investigated using MTT assays, wound healing assays, Annexin-V-FITC single staining assays, and flow cytometry, respectively. HeLa nude mice subcutaneously transplanted tumor model was established and treated with different drugs to observe the effect of BH/FA-CTS-NPs in vivo on HeLa bearing tumor. The BH/FA-CTS-NPs prepared in this experiment have a regular shape, uniform particle size, and no aggregation phenomenon. The results of DLS showed that mean particle size, PDI and Zeta potential of BH/FA-CTS NPs were (249.2 ± 3.6) nm, 0.129 ± 0.09, 33.6 ± 2.09, respectively, and the average diameter and PDI were stable in 90 days. The results of FT-IR demonstrated that the characteristic peaks of FA-CTS and BH/FA-CTS-NPs confirmed that FA-CTS cross-linked successfully and BH was encapsulated in NPs. The EE and DL amount were (79.3 ± 3.12) % and (7.24 ± 1.41) %, respectively. The results of in vitro release study indicated that the cumulative release of BH/FA-CTS NPs was (89.48±2.81) % in phosphate-buffered saline (PBS, pH 7.4) within 48h; these results by MTT assays and wund healing assays indicated that BH/FA-CTS NPs not only inhibited the proliferation of HeLa cells in a concentration and time-dependent manner but can induce apoptosis as well. The subcutaneous xenograft tumor formation rate of human cervical cancer cell line HeLa in nude mice was 98% after inoculation for 2 weeks. Compared with BH group and BH/CTS-NPs group, the xenograft tumor growth of BH/FA-CTS-NPs group was obviously slower; the result indicated that BH/FA-CTS-NPs could significantly inhibit the growth of HeLa xenograft tumor. BH/FA-CTS NPs with the sustained release effect could be prepared successfully by the ionic crosslinking method. Considering these properties, block proliferation and impairing the migration of the HeLa cell line, BH/FA-CTS NPs could be an important compound for consideration in the treatment of cervical cancer.

Keywords: folic-acid, chitosan, berberine hydrochloride, nanoparticles, cervical cancer

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7 The Scenario Analysis of Shale Gas Development in China by Applying Natural Gas Pipeline Optimization Model

Authors: Meng Xu, Alexis K. H. Lau, Ming Xu, Bill Barron, Narges Shahraki

Abstract:

As an emerging unconventional energy, shale gas has been an economically viable step towards a cleaner energy future in U.S. China also has shale resources that are estimated to be potentially the largest in the world. In addition, China has enormous unmet for a clean alternative to substitute coal. Nonetheless, the geological complexity of China’s shale basins and issues of water scarcity potentially impose serious constraints on shale gas development in China. Further, even if China could replicate to a significant degree the U.S. shale gas boom, China faces the problem of transporting the gas efficiently overland with its limited pipeline network throughput capacity and coverage. The aim of this study is to identify the potential bottlenecks in China’s gas transmission network, as well as to examine the shale gas development affecting particular supply locations and demand centers. We examine this through application of three scenarios with projecting domestic shale gas supply by 2020: optimistic, medium and conservative shale gas supply, taking references from the International Energy Agency’s (IEA’s) projections and China’s shale gas development plans. Separately we project the gas demand at provincial level, since shale gas will have more significant impact regionally than nationally. To quantitatively assess each shale gas development scenario, we formulated a gas pipeline optimization model. We used ArcGIS to generate the connectivity parameters and pipeline segment length. Other parameters are collected from provincial “twelfth-five year” plans and “China Oil and Gas Pipeline Atlas”. The multi-objective optimization model uses GAMs and Matlab. It aims to minimize the demands that are unable to be met, while simultaneously seeking to minimize total gas supply and transmission costs. The results indicate that, even if the primary objective is to meet the projected gas demand rather than cost minimization, there’s a shortfall of 9% in meeting total demand under the medium scenario. Comparing the results between the optimistic and medium supply of shale gas scenarios, almost half of the shale gas produced in Sichuan province and Chongqing won’t be able to be transmitted out by pipeline. On the demand side, the Henan province and Shanghai gas demand gap could be filled as much as 82% and 39% respectively, with increased shale gas supply. To conclude, the pipeline network in China is currently not sufficient in meeting the projected natural gas demand in 2020 under medium and optimistic scenarios, indicating the need for substantial pipeline capacity expansion for some of the existing network, and the importance of constructing new pipelines from particular supply to demand sites. If the pipeline constraint is overcame, Beijing, Shanghai, Jiangsu and Henan’s gas demand gap could potentially be filled, and China could thereby reduce almost 25% its dependency on LNG imports under the optimistic scenario.

Keywords: energy policy, energy systematic analysis, scenario analysis, shale gas in China

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6 Structure Domains Tuning Magnetic Anisotropy and Motivating Novel Electric Behaviors in LaCoO₃ Films

Authors: Dechao Meng, Yongqi Dong, Qiyuan Feng, Zhangzhang Cui, Xiang Hu, Haoliang Huang, Genhao Liang, Huanhua Wang, Hua Zhou, Hawoong Hong, Jinghua Guo, Qingyou Lu, Xiaofang Zhai, Yalin Lu

Abstract:

Great efforts have been taken to reveal the intrinsic origins of emerging ferromagnetism (FM) in strained LaCoO₃ (LCO) films. However, some macro magnetic performances of LCO are still not well understood and even controversial, such as magnetic anisotropy. Determining and understanding magnetic anisotropy might help to find the true causes of FM in turn. Perpendicular magnetic anisotropy (PMA) was the first time to be directly observed in high-quality LCO films with different thickness. The in-plane (IP) and out of plane (OOP) remnant magnetic moment ratio of 30 unit cell (u.c.) films is as large as 20. The easy axis lays in the OOP direction with an IP/OOP coercive field ratio of 10. What's more, the PMA could be simply tuned by changing the thickness. With the thickness increases, the IP/OOP magnetic moment ratio remarkably decrease with magnetic easy axis changing from OOP to IP. Such a huge and tunable PMA performance exhibit strong potentials in fundamental researches or applications. What causes PMA is the first concern. More OOP orbitals occupation may be one of the micro reasons of PMA. A cluster-like magnetic domain pattern was found in 30 u.c. with no obvious color contrasts, similar to that of LaAlO₃/SrTiO₃ films. And the nanosize domains could not be totally switched even at a large OOP magnetic field of 23 T. It indicates strong IP characters or none OOP magnetism of some clusters. The IP magnetic domains might influence the magnetic performance and help to form PMA. Meanwhile some possible nonmagnetic clusters might be the reason why the measured moments of LCO films are smaller than the calculated values 2 μB/Co, one of the biggest confusions in LCO films.What tunes PMA seems much more interesting. Totally different magnetic domain patterns were found in 180 u.c. films with cluster magnetic domains surrounded by < 110 > cross-hatch lines. These lines were regarded as structure domain walls (DWs) determined by 3D reciprocal space mapping (RSM). Two groups of in-plane features with fourfold symmetry were observed near the film diffraction peaks in (002) 3D-RSM. One is along < 110 > directions with a larger intensity, which is well match the lines on the surfaces. The other is much weaker and along < 100 > directions, which is from the normal lattice titling of films deposited on cubic substrates. The < 110 > domain features obtained from (103) and (113) 3D-RSMs exhibit similar evolution of the DWs percentages and magnetic behavior. Structure domains and domain walls are believed to tune PMA performances by transform more IP magnetic moments to OOP. Last but not the least, thick films with lots of structure domains exhibit different electrical transport behaviors. A metal-to-insulator transition (MIT) and an angular dependent negative magnetic resistivity were observed near 150 K, higher than FM transition temperature but similar to that of spin-orbital coupling related 1/4 order diffraction peaks.

Keywords: structure domain, magnetic anisotropy, magnetic domain, domain wall, 3D-RSM, strain

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5 The Impact of Social Support on Anxiety and Depression under the Context of COVID-19 Pandemic: A Scoping Review and Meta-Analysis

Authors: Meng Wu, Atif Rahman, Eng Gee, Lim, Jeong Jin Yu, Rong Yan

Abstract:

Context: The COVID-19 pandemic has had a profound impact on mental health, with increased rates of anxiety and depression observed. Social support, a critical factor in mental well-being, has also undergone significant changes during the pandemic. This study aims to explore the relationship between social support, anxiety, and depression during COVID-19, taking into account various demographic and contextual factors. Research Aim: The main objective of this study is to conduct a comprehensive systematic review and meta-analysis to examine the impact of social support on anxiety and depression during the COVID-19 pandemic. The study aims to determine the consistency of these relationships across different age groups, occupations, regions, and research paradigms. Methodology: A scoping review and meta-analytic approach were employed in this study. A search was conducted across six databases from 2020 to 2022 to identify relevant studies. The selected studies were then subjected to random effects models, with pooled correlations (r and ρ) estimated. Homogeneity was assessed using Q and I² tests. Subgroup analyses were conducted to explore variations across different demographic and contextual factors. Findings: The meta-analysis of both cross-sectional and longitudinal studies revealed significant correlations between social support, anxiety, and depression during COVID-19. The pooled correlations (ρ) indicated a negative relationship between social support and anxiety (ρ = -0.30, 95% CI = [-0.333, -0.255]) as well as depression (ρ = -0.27, 95% CI = [-0.370, -0.281]). However, further investigation is required to validate these results across different age groups, occupations, and regions. Theoretical Importance: This study emphasizes the multifaceted role of social support in mental health during the COVID-19 pandemic. It highlights the need to reevaluate and expand our understanding of social support's impact on anxiety and depression. The findings contribute to the existing literature by shedding light on the associations and complexities involved in these relationships. Data Collection and Analysis Procedures: The data collection involved an extensive search across six databases to identify relevant studies. The selected studies were then subjected to rigorous analysis using random effects models and subgroup analyses. Pooled correlations were estimated, and homogeneity was assessed using Q and I² tests. Question Addressed: This study aimed to address the question of the impact of social support on anxiety and depression during the COVID-19 pandemic. It sought to determine the consistency of these relationships across different demographic and contextual factors. Conclusion: The findings of this study highlight the significant association between social support, anxiety, and depression during the COVID-19 pandemic. However, further research is needed to validate these findings across different age groups, occupations, and regions. The study emphasizes the need for a comprehensive understanding of social support's multifaceted role in mental health and the importance of considering various contextual and demographic factors in future investigations.

Keywords: social support, anxiety, depression, COVID-19, meta-analysis

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4 A Foucauldian Analysis of Child Play: Case Study of a Preschool in the United States

Authors: Meng Wang

Abstract:

Historically, young members (children) in the society have been oppressed by adults through direct violent acts. Direct violence was evident in rampant child labor and child maltreatment cases. After acknowledging the rights of children from the United Nations, it is believed in public that children have been protected against direct physical violence. Nevertheless, at present, this paper argues from Foucauldian and disability study standpoints that similar to the old times, children are oppressed objects in the context of child play, which is constructed by adults to substitute direct violence in regulating children. Particularly, this paper suggests that on the one hand, preschool play is a new way that adults adopt to oppress preschoolers and regulate the society as a whole; on the other hand, preschoolers are taught how to play as an acquired skill and master self-regulation through play. There is a line of contemporary research that centers on child play from social constructivism perspective. Yet, current teaching practices pertaining to child play including guided child play and free play, in fact, serve the interest of adults and society at large. By acknowledging and deconstructing the prevalence of 'evidence-based best practice' in early childhood education field within western society, reconstruction of child-adult power relation could be achieved and alternative truth could be found in early childhood education. To support the argument of this paper, an on-going observational case study is conducted in a preschool setting in the United States. Age range of children is 2.5 to 4 years old. Approximately 10 children (5 boys) are participating in this case study. Observation is conducted throughout the weekdays as children follow through the classroom routine with a lead and an assistant teacher. Classroom teachers are interviewed pertaining to their classroom management strategies. Preliminary research finding of this case study suggested that preschool teachers tended to utilize scenarios from preschoolers’ dramatic play to impart core cultural values to young children. These values were pre-determined by adults. In addition, if young children have failed to follow teachers' guidance in terms of playing in a correct way, children ran the risk of being excluded from the play scenario by peers and adults. Furthermore, this study tended to indicate that through child play, preschoolers are obliged to develop an internal violence system, that is self-regulation skill to regulate their own behavior; and if this internal system is unestablished based on various assessments by adults, then potentially there will be consequences of negative labeling and disabling toward young children intended by adults. In conclusion, this paper applies Foucauldian analysis into the context of child play. At present, within preschool, child play is not free as it seems to be. Young children are expected to perform cultural tasks through their play activities designed by adults. Adults utilize child play as technologies of governmentality to further predict and regulate future society at large.

Keywords: child play, developmentally appropriate practice, DAP, poststructuralism, technologies of governmentality

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3 Automatic Adult Age Estimation Using Deep Learning of the ResNeXt Model Based on CT Reconstruction Images of the Costal Cartilage

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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2 A Study of the Atlantoaxial Fracture or Dislocation in Motorcyclists with Helmet Accidents

Authors: Shao-Huang Wu, Ai-Yun Wu, Meng-Chen Wu, Chun-Liang Wu, Kai-Ping Shaw, Hsiao-Ting Chen

Abstract:

Objective: To analyze the forensic autopsy data of known passengers and compare it with the National database of the autopsy report in 2017, and obtain the special patterned injuries, which can be used as the reference for the reconstruction of hit-and-run motor vehicle accidents. Methods: Analyze the items of the Motor Vehicle Accident Report, including Date of accident, Time occurred, Day, Acc. severity, Acc. Location, Acc. Class, Collision with Vehicle, Motorcyclists Codes, Safety equipment use, etc. Analyzed the items of the Autopsy Report included, including General Description, Clothing and Valuables, External Examination, Head and Neck Trauma, Trunk Trauma, Other Injuries, Internal Examination, Associated Items, Autopsy Determinations, etc. Materials: Case 1. The process of injury formation: the car was chased forward and collided with the scooter. The passenger wearing the helmet fell to the ground. The helmet crashed under the bottom of the sedan, and the bottom of the sedan was raised. Additionally, the sedan was hit on the left by the other sedan behind, resulting in the front sedan turning 180 degrees on the spot. The passenger’s head was rotated, and the cervical spine was fractured. Injuries: 1. Fracture of atlantoaxial joint 2. Fracture of the left clavicle, scapula, and proximal humerus 3. Fracture of the 1-10 left ribs and 2-7 right ribs with lung contusion and hemothorax 4. Fracture of the transverse process of 2-5 lumbar vertebras 5. Comminuted fracture of the right femur 6. Suspected subarachnoid space and subdural hemorrhage 7. Laceration of the spleen. Case 2. The process of injury formation: The motorcyclist wearing the helmet fell to the left by himself, and his chest was crushed by the car going straight. Only his upper body was under the car and the helmet finally fell off. Injuries: 1. Dislocation of atlantoaxial joint 2. Laceration on the left posterior occipital 3. Laceration on the left frontal 4. Laceration on the left side of the chin 5. Strip bruising on the anterior neck 6. Open rib fracture of the right chest wall 7. Comminuted fracture of both 1-12 ribs 8. Fracture of the sternum 9. Rupture of the left lung 10. Rupture of the left and right atria, heart tip and several large vessels 11. The aortic root is nearly transected 12. Severe rupture of the liver. Results: The common features of the two cases were the fracture or dislocation of the atlantoaxial joint and both helmets that were crashed. There were no atlantoaxial fractures or dislocations in 27 pedestrians (without wearing a helmet) versus motor vehicle accidents in 2017 the National database of an autopsy report, but there were two atlantoaxial fracture or dislocation cases in the database, both of which were cases of falling from height. Conclusion: The cervical spine fracture injury of the motorcyclist, who was wearing a helmet, is very likely to be a patterned injury caused by his/her fall and rollover under the sedan. It could provide a reference for forensic peers.

Keywords: patterned injuries, atlantoaxial fracture or dislocation, accident reconstruction, motorcycle accident with helmet, forensic autopsy data

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1 Low-Cost, Portable Optical Sensor with Regression Algorithm Models for Accurate Monitoring of Nitrites in Environments

Authors: David X. Dong, Qingming Zhang, Meng Lu

Abstract:

Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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