The Identification of Prenatal Exposure to Mitragynine Using Umbilical Cord Tissue

Objective: Kratom is widely available and literature exploring the effects of prenatal kratom exposure is lacking. This study aims to report a validated method for the detection of mitragynine in the umbilical cord and report our observations for specimens received at a national commercial reference laboratory. Study Design: Assays were validated according to the recommendations of ANSI/ASB. A retrospective evaluation of records at a national reference laboratory was conducted to determine prevalence and co-exposure to other substances of abuse. Result: Mitragynine was detected in 19 of 4456 specimens (0.43%) with concentrations ranging from 4 to >50 ng/g. Thirteen (13) of these specimens were positive for only mitragynine while the other 6 were also positive for either marijuana or opiates. Conclusion: Umbilical cord is a suitable specimen type for the surveillance of maternal kratom use and can be used to identify exposed neonates for further investigations into short- or long- term health consequences.

HQNN-SFOP:Hybrid Quantum Neural Networks with Signal Feature Overlay Projection for Drone Detection Using Radar Return Signals-A Simulation

With the wide application of drone technology,there is an increasing demand for the detection of radar return signals from drones.Existing detection methods mainly rely on time-frequency domain feature extraction and classical machine learning algorithms for image recognition.This method suffers from the problem of large dimensionality of image features,which leads to large input data size and noise affecting learning.Therefore,this paper proposes to extract signal time-domain statistical features for radar return signals from drones and reduce the feature dimension from 512×4 to 16 dimensions.However,the downscaled feature data makes the accuracy of traditional machine learning algorithms decrease,so we propose a new hybrid quantum neural network with signal feature overlay projection(HQNN-SFOP),which reduces the dimensionality of the signal by extracting the statistical features in the time domain of the signal,introduces the signal feature overlay projection to enhance the expression ability of quantum computation on the signal features,and introduces the quantum circuits to improve the neural network’s ability to obtain the inline relationship of features,thus improving the accuracy and migration generalization ability of drone detection.In order to validate the effectiveness of the proposed method,we experimented with the method using the MM model that combines the real parameters of five commercial drones and random drones parameters to generate data to simulate a realistic environment.The results show that the method based on statistical features in the time domain of the signal is able to extract features at smaller scales and obtain higher accuracy on a dataset with an SNR of 10 dB.On the time-domain feature data set,HQNNSFOP obtains the highest accuracy compared to other conventional methods.In addition,HQNN-SFOP has good migration generalization ability on five commercial drones and random drones data at different SNR conditions.Our method verifies the feasibility and effectiveness of signal detection methods based on quantum computation and experimentally demonstrates that the advantages of quantum computation for information processing are still valid in the field of signal processing,it provides a highly efficient method for the drone detection using radar return signals.

Evaluation and Prediction of Groundwater Quality in the Municipality of Za-Kpota (South Benin) Using Machine Learning and Remote Sensing

Accessing drinking water is a global issue. This study aims to contribute to the assessment of groundwater quality in the municipality of Za-Kpota (southern Benin) using remote sensing and Machine Learning. The methodological approach used consisted in linking groundwater physico-chemical parameter data collected in the field and in the laboratory using AFNOR 1994 standardized methods to satellite data (Landsat) in order to sketch out a groundwater quality prediction model. The data was processed using QGis (Semi-Automatic Plugin: SCP) and Python (Jupyter Netebook: Prediction) softwares. The results of water analysis from the sampled wells and boreholes indicated that most of the water is acidic (pH varying between 5.59 and 7.83). The water was moderately mineralized, with conductivity values of less than 1500 μs/cm overall (59 µS/cm to 1344 µS/cm), with high concentrations of nitrates and phosphates in places. The dynamics of groundwater quality in the municipality of Za-Kpota between 2008 and 2022 are also marked by a regression in land use units (a regression in vegetation and marshland formation in favor of built-up areas, bare soil, crops and fallow land) revealed by the diachronic analysis of satellite images from 2008, 2013, 2018 and 2022. Surveys of local residents revealed the use of herbicides and pesticides in agricultural fields, which are the main drivers contributing to the groundwater quality deterioration observed in the study area. Field surveys revealed the use of herbicides and pesticides in agricultural fields, which are factors contributing to the deterioration in groundwater quality observed in the study area. The results of the groundwater quality prediction models (ANN, RF and LR) developed led to the conclusion that the model based on Artificial Neural Networks (ANN: R2 = 0.97 and RMSE = 0) is the best for groundwater quality changes modelling in the Za-Kpota municipality.

Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Assessing Spatio-Temporal Land Cover Changes in Dhund River Basin, Eastern Rajasthan (India), Using Multi-Temporal Landsat Data

Land cover is an impression of natural cover on surface of earth such as bare soil, river, grass etc. and utilization of these natural covers for various human needs and purposes by mankind is defined as land use. Land cover identification, delineation and mapping is important for planning activities, resource management and global monitoring studies while baseline mapping and subsequent monitoring is done by application of land use to get timely information about quantity of land that has been used. The present study has been carried out in Dhund river watershed of Jaipur, Rajasthan which covers an area of about 1828 sq∙km. The minimum and maximum elevation of the area is found to be 214 m and 603 m respectively. Land use and land cover changes of three decades from 1991 to 2021 have been interpreted by using remotes sensing and GIS techniques. ArcGIS software (Arc map 10.2), SOI topographic map, Cartosat-1 DEM and satellite data of Landsat 5 and Landsat 8 have been used for interpretation of eleven classes. The study shows an increase in cultivated land, settlement, waterbody, open forest, plantation and mining due to urbanization because of increasing demands of food, shelter and water while a decrease in dense forest, river, open scrub, wasteland and uncultivated land has also been marked due to destruction of aforementioned by anthropogenic activities such as industrialization resulting in environmental degradation that leads to air, soil and water pollution.

Land Use Land Cover Analysis for Godavari Basin in Maharashtra Using Geographical Information System and Remote Sensing

The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the land use and land cover (LULC) changes within the catchment area of the Godavari River, assessing the repercussions of land and water resource exploitation. Utilizing LANDSAT satellite images from 2009, 2014, and 2019, this research employed supervised classification through the Quantum Geographic Information System (QGIS) software’s SCP plugin. Maximum likelihood classification algorithm was used for the assessment of supervised land use classification. Seven distinct LULC classes—forest, irrigated cropland, agricultural land (fallow), barren land, shrub land, water, and urban land—are delineated for classification purposes. The study revealed substantial changes in the Godavari basin’s land use patterns over the ten-year period from 2009 to 2019. Spatial and temporal dynamics of land use/cover changes (2009-2019) were quantified using three Satellite/Landsat images, a supervised classification algorithm and the post classification change detection technique in GIS. The total study area of the Godavari basin in Maharashtra encompasses 5138175.48 hectares. Notably, the built-up area increased from 0.14% in 2009 to 1.94% in 2019. The proportion of irrigated cropland, which was 62.32% in 2009, declined to 41.52% in 2019. Shrub land witnessed a noteworthy increase from 0.05% to 2.05% over the last decade. The key findings underscored significant declines in barren land, agricultural land, and irrigated cropland, juxtaposed with an expansion in forest land, shrub land, and urban land. The classification methodology achieved an overall accuracy of 80%, with a Kappa Statistic of 71.9% for the satellite images. The overall classification accuracy along with the Kappa value for 2009, 2014 and 2019 supervised land use land cover classification was good enough to detect the changing scenarios of Godavari River basin under study. These findings provide valuable insights for discerning land utilization across various categories, facilitating the adoption of appropriate strategies for sustainable land use in the region.

Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling

The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).

Study of Urban Sprawl and Its Impact on Vegetation, Land Surface Temperature and Air Pollution Using Remote Sensing and GIS in Kathmandu Valley from 2015 to 2020

The Kathmandu Valley has seen substantial urbanization over the past decades while being the nation’s economic centre. Built-up areas have expanded quickly along with the population, having a significantly negative influence on the environment. Recently, Kathmandu was named as the most polluted city in Asia. Urban sprawl has had a negative influence on Kathmandu’s residents in several ways. The state of urban sprawl and the effects it has had on the Kathmandu Valley have been examined using land sat imagery. In this study, IDW was used in GIS to analyze the pollution status using data of PM 2.5 and PM 10 obtained from various monitoring sites. A supervised classification was used to create a LULC map of Kathmandu for the years 2015, 2018, and 2020. To assess the state of the vegetation and determine whether the Kathmandu Valley is being affected by urban heat, NDVI and Land sat temperature calculations were also made. The study’s results were obtained using remote sensing and GIS technology. The built-up area in Kathmandu Valley has grown by 20% over the past five years, impacting land use patterns and deteriorating vegetation cover. Due to the rise of built-up area, which is a good heat absorber, the temperature in the Kathmandu Valley is rising along with the degradation of the vegetation cover. The pollution in the Kathmandu Valley is at its worst, and residents are compelled to breathe air that is significantly more polluted than the prescribed limit.

Simulation of urban affordable housing land-use evolution based on CA-MAS model

In order to simulate the evolution of affordable housing land use a dynamic model that combines cellular automata CA and a multi-agent system MAS is established.This paper aims to utilize the approach of decision factors on site selection of affordable housing through a literature review to construct a hierarchy model of those factors identifying the weight of each factor by an analytic hierarchy process AHP .Based on those weight factors the CA-MAS model is designed. Nanjing city is taken as an example to verify the feasibility of the model.The results show that the CA-MAS model is pragmatic and effective in simulating evolution of affordable housing land use which also promotes the fundamental understanding and perception of the development of affordable housing and urbanization.

Breathe New Life into English Teaching:A Book Review of Using Corpora in the Language Classroom

The present article provides a critical review of Randi Reppen's impressing book Using Corpora in the Language Classroom.It's argued that Randi Reppen's book,despite a few slight flaws,has a strong practical orientation and is a laudable effort to make English language teachers to realize the importance and practicality of bringing corpora into classroom in digital age.The book is particularly worthy of reading for those language teachers(especially beginner teachers) who want to breathe new life into their English teaching.

Prevention of metastasis to liver by using 5-FU intraperitoneal chemotherapy in nude mice inoculated with human colonic cancer cells

AIMS Using a new approach of regional adjuvant chemotherapy to prevent cancer cells hepatic metasta- sis after radical surgery of large bowel cancer. METHODS A model of liver with metastasis of hu- man colonic cancer (HCC) cells in nude mice was used to observe the effect in prevention of metastasis of HCC cells inoculated via spleen applied with early postoper- ative intraperitoneal (IP) chemotherapy using large dose of 5-FU. RESULTS The incidence of metastasis to liver was decreased by 40%,the mean number of metastatic liv- er nodules in each animal was reduced by 50.89% and the mean survival times of each animal was prolonged by 48.21% by using 5-FU 40 mg/NS 40 ml/kg IP for two consecutive days as compared with the controls. CONCLUSIONS IP is a new and more effective re- gional adjuvant chemotheraputic approach in the pre- vention of liver metastasis HCC cells after radical surgery of large bowel cancer.

Continuous Dynamic Rotation Measurements Using a Compact Cold Atom Gyroscope

We present an experimental demonstration of the rotation measurement using a compact cold atom gyroscope. Atom interference fringes are observed in the stationary frame and the rotating frame, respectively. The phase shift and contrast of the interference fringe are experimentally investigated. The results show that the contrast of the interference fringe is well held when the platform is rotated, and the phase shift of the interference fringe is linearly proportional to the rotation rate of the platform. The long-term stability, which is evaluated by the overlapped Allan deviation, is 8.5 × 10^-6 rad/s over the integrating time of 1000s.

Simulation of Land-use Scenarios for Beijing Using CLUE-S and Markov Composite Models

This study investigated and simulated land use patterns in Beijing for the year 2000 and the year 2005 from the actual land use data for the year 1995 and the year 2000,respectively,by combining spatial land allocation simulation using the CLUE-S model,and numerical land demand prediction using the Markov model.The simulations for 2000 and 2005 were confirmed to be generally accurate using Kappa indices.Then the land-use scenarios for Beijing in 2015 were simulated assuming two modes of development:1) urban development following existing trends;and 2) under a strict farmland control.The simulations suggested that under either mode,urbanized areas would expand at the expense of land for other uses.This expansion was predicted to dominate the land-use conversions between 2005 and 2015,and was expected to be accompanied by an extensive loss of farmland.The key susceptible to land-use changes were found to be located at the central urban Beijing and the surrounding regions including Yanqing County,Changping District and Fangshan District.Also,the simulations predicted a considerable expansion of urban/suburban areas in the mountainous regions of Beijing,suggesting a need for priority monitoring and protection.

Quantifying Land Use Change in Zhejiang Coastal Region,China Using Multi-Temporal Landsat TM/ETM+Images

Landsat Thematic Mapper （TM） and Enhanced Thematic Mapper Plus （ETM＋） images in 1985, 1986, 1993, 1994 and 2001 were used to quantify the land use and land cover changes （LUCC） in the Zhejiang coastal region with a stratified unsupervised classification technique in conjunction with visual interpretation and to attempt an identification of the socioeconomic driving forces. In level I an overall accurate classification was achieved using a modified Anderson＇s Ⅰ/Ⅱ/Ⅲ-level classification scheme. The overall accuracy of the land use classification at Anderson level Ⅰ were 89.7% （1985）, 91.6% （1993）, and 90.4% （2001）. The most rapid land use change was a dramatic increase in urban or built-up areas, which quadrupled from 1985 to 2001. Over 90% of this newly expanded built-up area was originally paddy fields or other croplands. In different parts of the Zhejiang coastal region, urban land expansion was spatially uneven. Temporally, land use development did not stabilized, and the two study periods of time （1985-1993 and 1993-2001） had different transition styles. Socioeconomic factors, such as gross domestic product, total population, and financial expenditure, were all highly correlated with the expansion of urban or built-up areas. Based on the degree of urban sprawl and socioeconomic factors, cities and towns were further divided into six subgroups, which may help decision makers improve land use for the region.

RESEARCH ACTIVITIES ON LAND USE/COVER CHANGE IN THE PAST TEN YEARS IN CHINA USING SPACE TECHNOLOGY

Land use/cover change, which in China is characterized by urbanization resulting in a decrease in arable land in the east along with a large area of grassland being cultivated in the west, has been accelerated by rapid economic development in the last years. All of the above changes will affect sustainable development in the next century. The Chinese Academy of Sciences is conducting a study of land use/cover change over the last ten years based on the integration of remote sensing and GIS technology to establish a multitemporal database covering all of China. Fundamental data for land use/cover for the year 1996 has already been developed by the Chinese Academy of Sciences. In order to reconstruct fundamental land use/cover data for the year 1986, a central data processing and analyzing system and a regional data acquisition, processing and analyzing system have been established and are joined together as a network. After the 1986 database is established, the comparative research on the reduction in arable land, urbanization, desertification, changes in forest and grassland, and lake and wetland land use/cover change will be carried out. In addition, a transect for a key regional comparative study was selected along the Changjiang (Yangtze) River. The driving forces of these changes also will be extracted. The result of this study will be not only make a contribution to global land use/cover change research, but will also support decision making for sustainable national development.

Generation of seed lipoxygenase-free soybean using CRISPR-Cas9

Beany flavor induced by three lipoxygenases(LOXs, including LOX1, LOX2, and LOX3)restricts human consumption of soybean. It is desirable to generate lipoxygenase-free new mutant lines to improve the eating quality of soybean oil and protein products. In this study, a pooled clustered regularly interspaced short palindromic repeats(CRISPR)-CRISPRassociated protein 9(Cas9) strategy targeting three GmLox genes(GmLox1, GmLox2, and GmLox3) was applied and 60 T_0 positive transgenic plants were generated, carrying combinations of sg RNAs and mutations. Among them, GmLox-28 and GmLox-60 were gmlox1 gmlox2 gmlox3 triple mutants and GmLox-40 was a gmlox1 gmlox2 double mutant.Sequencing of T_1 mutant plants derived from GmLox-28, GmLox-60, and GmLox-40 showed that mutation in the GmLox gene was inherited by the next generation. Colorimetric assay revealed that plants carrying different combinations of mutations lost the corresponding lipoxygenase activities. Transgene-free mutants were obtained by screening the T_2 generation of lipoxygenase-free mutant lines(GmLox-28 and GmLox-60). These transgeneand lipoxygenase-free mutants could be used for soybean beany flavor reduction without restriction by regulatory frameworks governing transgenic organisms.

Resilience-based retrofitting of existing urban RC-frame buildings using seismic isolation

The improvement of the seismic resilience of existing reinforced-concrete(RC) frame buildings, which is essential for the seismic resilience of a city, has become a critical issue. Although seismic isolation is an effective method for improving the resilient performance of such buildings, target-oriented quantitative improvements of the resilient performance of these buildings have been reported rarely. To address this gap, the seismic resilience of two existing RC frame buildings located in a high seismic intensity region of China were assessed based on the Chinese Standard for Seismic Resilience Assessment of Buildings. The critical engineering demand parameters(EDPs) affecting the seismic resilience of such buildings were identified. Subsequently, the seismic resilience of buildings retrofitted with different isolation schemes(i.e., yield ratios) were evaluated and compared, with emphasis on the relationships among yield ratios, EDPs, and levels of seismic resilience. Accordingly, to achieve the highest level of seismic resilience with respect to the Chinese standard, a yield ratio of 3% was recommended and successfully applied to the target-oriented design for the seismic-resilience improvement of an existing RC frame building. The research outcome can provide an important reference for the resilience-based retrofitting of existing RC frame buildings using seismic isolation in urban cities.

Targeted mutagenesis of amino acid transporter genes for rice quality improvement using the CRISPR/Cas9 system

High grain protein content(GPC) reduces rice eating and cooking quality(ECQ). We generated OsAAP6 and OsAAP10 knockout mutants in three high-yielding japonica varieties and one japonica line using the CRISPR/Cas9 system. Mutation efficiency varied with genetic background in the T_0 generation, and GPC in the T_1 generation decreased significantly,owing mainly to a reduction in glutelin content. Amylose content was down-regulated significantly in some Osaap6 and all Osaap10 mutants. The increased taste value of these mutants was supported by Rapid Visco Analysis(RVA) profiles, which showed higher peak viscosity and breakdown viscosity and lower setback viscosity than the wild type. There were no significant deficiencies in agronomic traits of the mutants. Targeted mutagenesis of OsAAP6 and OsAAP10, especially OsAAP10, using the CRISPR/Cas9 system can rapidly reduce GPC and improve ECQ of rice, providing a new strategy for the breeding cultivars with desired ECQ.

Monitoring Land Use Dynamics in Chanthaburi Province of Thailand Using Digital Remotely Sensed Images

A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.

WISE EXPLOITATION OF NEWLY GROWING LAND RESOURCES——An Assessment on Land-use Change of Chongming Island Using GIS

Chongming Island, the third largest island in China and the largest alluvialisland in the world, is situated in the north of Shanghai Municipality at the mouth of theChangjiang (Yangtze) River. Along the fertile and prosperous sea coast there are a total area ofover 120 x 10~3ha, with a population of 735 000, accruing some 500ha of new tidal land resourcescome from silt, sand and mud carried by the Changjiang River every year, extending about 140m peryear. This dynamic process of alluvial growth has run for some 1500 years. Mudflat on ChongmingIsland at the mouth of the Changjiang River is a resting ground for migratory birds and host morethan a hundred species, including rare cranes and geese. But the local people keep reclaiming thetidal land for economic development. Obviously, it is crucial to have a well-concerted plan forfuture exploitation. In this study, we attempted to investigate the status changes of land use andwild life habitats on Chongming Island in recent 10 years, and then analyzed different humanactivities and their effects on wild life habitats using satellite image data (1990, 1997 and 2000)as well as field survey. Based on the analysis, this study explored the relationships between islandgrowth and land use/cover change (LUCC), predicted what the habitat would be like in the future andtried to find more effective use of this new growing resource. At last, this study provided somepreliminary management plans for Chongming Island that will coordinate the development of localeconomies and the conservation of wild life and their habitats.