Search results for: environmental detection

Authors: Tanwarat Kajsongkram, Saowalux Rotamporn, Sirinat Limbunruang, Sirinan Thubthimthed.

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High-Performance Liquid Chromatography (HPLC) method was developed and validated for simultaneous estimation of 6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing ginger extract. The chromatographic separation was achieved by using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase containing acetonitrile and water (gradient elution). The flow rate was 1.0 ml/min and the absorbance was monitored at 282 nm. The proposed method was validated in terms of the analytical parameters such as specificity, accuracy, precision, linearity, range, limit of detection (LOD), limit of quantification (LOQ), and determined based on the International Conference on Harmonization (ICH) guidelines. The linearity ranges of 6G and 6S were obtained over 20-60 and 6-18 µg/ml respectively. Good linearity was observed over the above-mentioned range with linear regression equation Y= 11016x- 23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of analytes in μg/ml and Y is peak area). The value of correlation coefficient was found to be 0.9994 for both markers. The limit of detection (LOD) and limit of quantification (LOQ) for 6G were 0.8567 and 2.8555 µg/ml and for 6S were 0.3672 and 1.2238 µg/ml respectively. The recovery range for 6G and 6S were found to be 91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels. The RSD values from repeated extractions for 6G and 6S were 3.43 and 3.09% respectively. The validation of developed method on precision, accuracy, specificity, linearity, and range were also performed with well-accepted results.

Keywords: ginger, 6-gingerol, HPLC, 6-shogaol

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Sonia Machraoui, Salam Labidi, Karunakara Naregundi

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Environmental radiation measurements are useful to identify areas of potential natural radiation hazard particularly in areas of phosphate industries where enhanced radiation levels are expected to be present. Measurements of primordial radionuclides concentrations have been carried out in samples collected from Sfax City around the SIAPE phosphate industry of Tunis. The samples analysed include fish, beef meat, egg, and vegetables as well as in soil and grass. Measurements were performed by gamma spectrometry method using a 42% relative efficiency N-type HPGe detector. The activity concentrations of radionuclides were measured by gamma ray spectrometry. As expected, the concentrations of radionuclides belonging to uranium and thorium series were low in food materials. In all the samples analysed, the 137Cs concentration was below detection level, except meat samples which showed the activity concentration of 2.4 Bq kg-1 (dry wt.) The soil to grass transfer factor was found to be similar to those reported in literature. The effective dose to the population due to intake of food products were also estimated and are presented in this paper.

Keywords: effective doses, phosphate industry, transfer coefficients, Tunisia

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Authors: Yi Zhang, Yuan Tian, Jiehua Chen, Sihong Gu

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Chip-scale spin-exchange relaxation free (SERF) atomic magnetometer makes use of millimeter-scale vapor cells micro-fabricated by Micro-electromechanical Systems (MEMS) technique and SERF mechanism, resulting in the characteristics of high spatial resolution and high sensitivity. It is useful for biomagnetic imaging including magnetoencephalography and magnetocardiography. In a prevailing scheme, circularly polarized on-resonance laser beam is adapted for both pumping and probing the atomic polarization. And the magnetic-field-sensitive signal is extracted by transmission laser intensity enhancement as a result of atomic polarization increase on zero field level crossing resonance. The scheme is very suitable for integration, however, the laser amplitude modulation (AM) noise and laser frequency modulation to amplitude modulation (FM-AM) noise is superimposed on the photon shot noise reducing the signal to noise ratio (SNR). To suppress AM and FM-AM noise the paper puts forward a novel scheme which adopts circularly polarized on-resonance light pumping and linearly polarized frequency-detuning laser probing. The transmission beam is divided into transmission and reflection beams by a polarization analyzer, the angle between the analyzer's transmission polarization axis and frequency-detuning laser polarization direction is set to 45°. The magnetic-field-sensitive signal is extracted by polarization rotation enhancement of frequency-detuning laser which induces two beams intensity difference increase as the atomic polarization increases. Therefore, AM and FM-AM noise in two beams are common-mode and can be almost entirely canceled by differential detection. We have carried out an experiment to study our scheme. The experiment reveals that the noise in the differential signal is obviously smaller than that in each beam. The scheme is promising to be applied for developing more sensitive chip-scale magnetometer.

Keywords: atomic magnetometer, chip scale, differential detection, spin-exchange relaxation free

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Authors: Vinícius L. L. Morrone, David Douek, Helder M. F. Pereira, Bernadete L. M. Grandolpho

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This work aimed to identify the relationships between the level of consumer environmental awareness and their search for sustainable properties, as well as to understand the main sustainability structures considered by these consumers during the decision process. Additionally, the paper looked up to the influence environmental awareness and financial status have over the disposition of buyers to pay more for sustainable properties. To achieve these objectives, 318 questionnaires were answered electronically, after being sent to the Green Building Brazil email basis, as to other Real Estate developers client basis. From all the questionnaires answered, 71 were discarded, leaving a total amount of 247 admitted questionnaires to be analyzed. The responses were evaluated based on the theory of consumer decision making, especially on the influence factors of this process. The data were processed using a PLS model, using the R software. The results have shown that the level of consumer environmental awareness effectively affects the consumer’s will of acquiring a sustainable property or, at least, a property with some environmental friendly structures. The consumer’s environmental awareness also positively impacts the importance consumers give to individual environmental friendly structures. Also, as a consumer value to those individual structures raises, it is also observed a raise in his will to buy a sustainable property. Additionally, the impact of consumer’s environmental awareness and financial status over the willingness to pay more for a property with those attributes. The results indicate that there was no relationship between consumers' environmental awareness and their willingness to pay more for a sustainable property. On the other hand, the financial status and the family income of the consumers showed a positive relation with the willingness to pay more for a sustainable property. This indicates that consumers with better financial conditions, which according to the analysis do not necessarily have a greater environmental awareness, are those who are willing to pay more for a sustainable property. Thus, this study indicates that, even if the environmental awareness impact positively the demand for sustainable structures and properties, this impact is not price reflected, due to the price elasticity of the consumption, especially for a category of lower income consumers. This paper adds to the literature in the way it projects some guidelines to the consumer’s decision process in the Real Estate market in emerging economies, as well as it presents some drivers to pricing decisions.

Keywords: consumer behavior, environmental awareness, real estate pricing, sustainable buildings

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Authors: K. Frahtia, I. Mihoubi, S. Picot

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Leishmaniasis is a group of parasitic disease with a varied clinical expression caused by flagellate protozoa of the Leishmania genus. These diseases are transmitted to humans and animals by the sting of a vector insect, the female sandfly. Among the groups of dipteral disease vectors, Phlebotominae occupy a prime position and play a significant role in human pathology, such as leishmaniasis that affects nearly 350 million people worldwide. The vector control operation launched by health services throughout the country proves to be effective since despite the prevalence of the disease remains high especially in rural areas, leishmaniasis appears to be declining in Algeria. In this context, this study mainly concerns molecular detection of Leishmania from the vector. Furthermore, a molecular diagnosis has also been made on skin samples taken from patients in the region of Constantine, located in the North-East of Algeria. Concerning the vector, 5858 sandflies were captured, including 4360 males and 1498 females. Male specimens were identified based on their morphological. The morphological identification highlighted the presence of the Phlebotomus genus with a prevalence of 93% against 7% represented by the Sergentomyia genus. About the identified species, P. perniciosus is the most abundant with 59.4% of the male identified population followed by P. longicuspis with 24.7% of the workforce. P. perfiliewi is poorly represented by 6.7% of specimens followed by P. papatasi with 2.2% and 1.5% S. dreyfussi. Concerning skin samples, 45/79 (56.96%) collected samples were found positive by real-time PCR. This rate appears to be in sharp decline compared to previous years (alert peak of 30,227 cases in 2005). Concerning the detection of Leishmania from sandflies by RT-PCR, the results show that 3/60 PCR performed genus are positive with melting temperatures corresponding to that of the reference strain (84.1 +/- 0.4 ° C for L. infantum). This proves that the vectors were parasitized. On the other side, identification by RT-PCR species did not give any results. This could be explained by the presence of an insufficient amount of leishmanian DNA in the vector, and therefore support the hypothesis of the regression of leishmaniasis in Constantine.

Keywords: Algeria, molecular diagnostic, phlebotomus, real time PCR

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Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

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Authors: Kever Bruno Paradelo Gomes, Rosana Carvalho Cristo Martins

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Payment for Environmental Services (PSA) has been a strategy used since the late 1990s by Latin American countries to finance environmental conservation. Payment for Environmental Services has been absorbing a growing amount of time in the discussions around environmentally sustainable development strategies in the world. In Brazil, this theme has permeated the discussions since the publication of the new Forest Code. The objective of this work was to verify the perception of the resident farmers in the region of Ponte Alta, Gama, Federal District, Brazil, on environmental legislation and Payments for Environmental Services. The work was carried out in 99 rural properties of the family farmers of the Rural Nucleus Ponte Alta, Administrative Region of Gama, in the city of Brasília, Federal District, Brazil. The present research is characterized methodologically as a quantitative, exploratory, and descriptive nature. The data treatment was performed through descriptive statistical analysis and hypothesis testing. The perceptions about environmental legislation in the rural area of Ponte Alta, Gama, DF respondents were positive. Although most of the family farmers interviewed have some knowledge about environmental legislation, it is perceived that in practice, the environmental adequacy of property is ineffective given the current situation of sustainable rural development; there is an abyss between what is envisaged by legislation and reality in the field. Thus, as in the reports of other researchers, it is verified that the majority of respondents are not aware of PSA (62.62%). Among those interviewed who were aware of the subject, two learned through the course, three through the university, two through TV and five through other people. The planting of native forest species on the rural property was the most informed practice by farmers if they received some Environmental Service Payment (PSA). Reflections on the environment allow us to infer that the effectiveness and fulfillment of the incentives and rewards in the scope of public policies to encourage the maintenance of environmental services, already existing in all spheres of government, are of great relevance to the process of environmental sustainability of rural properties. The relevance of the present research is an important tool to promote the discussion and formulation of public policies focused on sustainable rural development, especially on payments for environmental services; it is a space of great interest for the strengthening of the social group dedicated to production. Public policies that are efficient and accessible to the small rural producers become decisive elements for the promotion of changes in behavior in the field, be it economic, social, or environmental.

Keywords: forest code, public policy, rural development, sustainable agriculture

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Authors: Pawasuth Saengdee, Chamras Promptmas, Ting Zeng, Silke Leimkühler, Ulla Wollenberger

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Sulfite has been used as a versatile preservative to limit the microbial growth and to control the taste in some food and beverage. However, it has been reported to cause a wide spectrum of severe adverse reactions. Therefore, it is important to determine the amount of sulfite in food and beverage to ensure consumer safety. An efficient electrocatalytic biosensor for sulfite detection was developed by immobilizing of human sulfite oxidase (hSO) on 3-aminoproplytriethoxysilane (APTES) modified indium tin oxide (ITO) electrode. Cyclic voltammetry was employed to investigate the electrochemical characteristics of the hSO modified ITO electrode for various pretreatment and binding conditions. Amperometry was also utilized to demonstrate the current responses of the sulfite sensor toward sodium sulfite in an aqueous solution at a potential of 0 V (vs. Ag/AgCl 1 M KCl). The proposed sulfite sensor has a linear range between 0.5 to 2 mM with a correlation coefficient 0.972. Then, the additional polymer layer of PVA was introduced to extend the linear range of sulfite sensor and protect the enzyme. The linear range of sulfite sensor with 5% coverage increases from 2.8 to 20 mM at a correlation coefficient of 0.983. In addition, the stability of sulfite sensor with 5% PVA coverage increases until 14 days when kept in 0.5 mM Tris-buffer, pH 7.0 at 4 8C. Therefore, this sensor could be applied for the detection of sulfite in the real sample, especially in food and beverage.

Keywords: sulfite oxidase, bioelectrocatalytsis, indium tin oxide, direct electrochemistry, sulfite sensor

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Joy Debski

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Due to the varying degrees of the problem posed by global warming, environmental sustainability dominates international discourse. International initiatives' aims and expectations have proven particularly challenging to put into practice in developing nations. To reduce human exploitation of the environment, stricter measures are urgently needed. However, putting them into practice has proven more difficult. Relatively recent information from the Climate Accountability Institute and academic researchers shows that fossil fuel companies are major contributors to the climate crisis. Host communities in oil and gas-producing areas, particularly in developing nations, have grown hostile toward both oil and gas companies and government policies. It is now essential that the three main stakeholders—government, the oil and gas sector, and host communities—cooperate to achieve the shared objective of environmental sustainability. This research, therefore, advocates a governance system for Nigeria that facilitates the achieving the goal of environmental sustainability. This objective is achieved by the research's examination of the main institutional framework for environmental sustainability, evaluation of the strategies used by major oil companies to increase stakeholder engagement in environmental sustainability, and examination of the involvement of host communities in environmental sustainability. The study reveals that while environmental sustainability is important to the identified stakeholders, it's challenging to accomplish without an informed synergy. Hence the research advocates the centralisation of CSR through a CSR commission for environmental sustainability. The commission’s mandate is to facilitate, partner with, and endorse companies. The commission is strongly advised to incorporate host community liaison offices into the process of negotiating contracts with oil and gas firms, as well as to play a facilitative role in helping firms adhere to both domestic and international regulations. The recommendations can benefit Nigerian policymakers in enhancing their unsuccessful efforts to pass CSR legislation. Through the research-proposed CSR department, which has competent training and stakeholder engagement strategies, oil and gas companies can enhance and centralise their goals for environmental sustainability. Finally, the CSR Commission's expertise would give host communities more leverage when negotiating their memorandum of understanding with oil and gas companies.

Keywords: environmental sustainability, corporate social responsibility, CSR, oil and gas, nigeria

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Authors: Zineb Meniaoui, Fatma Zehri, Kamoussi Halioui

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The amplified awareness of companies towards the social and environmental concerns has nowadays become a challenge for firms around the globe. Our study investigates the effects of corporate governance mechanisms on voluntarily social and environmental information disclosure in Canada and France. The study use the content analysis approach, applied on a total of 245 year-observation for the Canadian sample and 245 year-observation for the French sample from 2005 to 2011. Our results show a significant correlation between the board's independence, Corporate Social Responsibility (CSR) committee and expertise as well as the audit quality along with the extent of the social and environmental disclosure. The French firms are found disclosing more societal information than Canadian firms, which might be due to the stakeholders' pressure put on French companies to disclose such societal information.

Keywords: Canada, corporate governance, disclosure determinants , France, social and environmental disclosure

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Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: artificial neural networks, digital image processing, pattern recognition, phytosanitary

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Authors: Wenyu Guo, Malachy O’Rourke, Mark Bowkett, Michael Gilchrist

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Many devices for real-time monitoring of surface water have been developed in the past few years to provide early warning of pollutions and so to decrease the risk of environmental pollution efficiently. One of the most common methodologies used in the detection system is a colorimetric process, in which a container with fixed volume is filled with target ions and reagents to combine a colorimetric dye. The colorimetric ions can sensitively absorb a specific-wavelength radiation beam, and its absorbance rate is proportional to the concentration of the fully developed product, indicating the concentration of target nutrients in the pre-mixed water samples. In order to achieve precise and rapid detection effect, channels with dimensions in the order of micrometers, i.e., microfluidic systems have been developed and introduced into these diagnostics studies. Microfluidics technology largely reduces the surface to volume ratios and decrease the samples/reagents consumption significantly. However, species transport in such miniaturized channels is limited by the low Reynolds numbers in the regimes. Thus, the flow is extremely laminar state, and diffusion is the dominant mass transport process all over the regimes of the microfluidic channels. The objective of this present work has been to analyse the mixing effect and chemistry kinetics in a stop-flow microfluidic device measuring Nitride concentrations in fresh water samples. In order to improve the temporal resolution of the Nitride microfluidic sensor, we have used computational fluid dynamics to investigate the influence that the effectiveness of the mixing process between the sample and reagent within a microfluidic device exerts on the time to completion of the resulting chemical reaction. This computational approach has been complemented by physical experiments. The kinetics of the Griess reaction involving the conversion of sulphanilic acid to a diazonium salt by reaction with nitrite in acidic solution is set in the Laminar Finite-rate chemical reaction in the model. Initially, a methodology was developed to assess the degree of mixing of the sample and reagent within the device. This enabled different designs of the mixing channel to be compared, such as straight, square wave and serpentine geometries. Thereafter, the time to completion of the Griess reaction within a straight mixing channel device was modeled and the reaction time validated with experimental data. Further simulations have been done to compare the reaction time to effective mixing within straight, square wave and serpentine geometries. Results show that square wave channels can significantly improve the mixing effect and provides a low standard deviations of the concentrations of nitride and reagent, while for straight channel microfluidic patterns the corresponding values are 2-3 orders of magnitude greater, and consequently are less efficiently mixed. This has allowed us to design novel channel patterns of micro-mixers with more effective mixing that can be used to detect and monitor levels of nutrients present in water samples, in particular, Nitride. Future generations of water quality monitoring and diagnostic devices will easily exploit this technology.

Keywords: nitride detection, computational fluid dynamics, chemical kinetics, mixing effect

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Authors: Jessica Achebe, Susan Tighe

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The recent Canadian infrastructure report card reveals the unhealthy state of municipal infrastructure intensified challenged faced by municipalities to maintain adequate infrastructure performance thresholds and meet user’s required service levels. For a road agency, huge funding gap issue is inflated by growing concerns of the environmental repercussion of road construction, operation and maintenance activities. As the reduction of material consumption and greenhouse gas emission when maintain and rehabilitating road networks can achieve added benefits including improved life cycle performance of pavements, reduced climate change impacts and human health effect due to less air pollution, improved productivity due to optimal allocation of resources and reduced road user cost. Incorporating environmental sustainability measure into pavement management is solution widely cited and studied. However measuring the environmental performance of road network is still a far-fetched practice in road network management, more so an ostensive agency-wide environmental sustainability or sustainable maintenance specifications is missing. To address this challenge, this present research focuses on the environmental sustainability performance of network-level pavement management. The ultimate goal is to develop a framework to incorporate environmental sustainability in pavement management systems for network-level maintenance programming. In order to achieve this goal, this study reviewed previous studies that employed environmental performance measures, as well as the suitability of environmental performance indicators for the evaluation of the sustainability of network-level pavement maintenance strategies. Through an industry practice survey, this paper provides a brief forward regarding the pavement manager motivations and barriers to making more sustainable decisions, and data needed to support the network-level environmental sustainability. The trends in network-level sustainable pavement management are also presented, existing gaps are highlighted, and ideas are proposed for sustainable network-level pavement management.

Keywords: pavement management, sustainability, network-level evaluation, environment measures

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Authors: Azita Ramezani, Atousa Ramezani

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In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

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Authors: Venkatesh Kumar, Kasun Hewage, Rehan Sadiq

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Residential buildings consume significant amounts of energy and produce a large amount of emissions and waste. However, there is a substantial potential for energy savings in this sector which needs to be evaluated over the life cycle of residential buildings. Life Cycle Assessment (LCA) methodology has been employed to study the primary energy uses and associated environmental impacts of different phases (i.e., product, construction, use, end of life, and beyond building life) for residential buildings. Four different alternatives of residential buildings in Vancouver (BC, Canada) with a 50-year lifespan have been evaluated, including High Rise Apartment (HRA), Low Rise Apartment (LRA), Single family Attached House (SAH), and Single family Detached House (SDH). Life cycle performance of the buildings is evaluated for embodied energy, embodied environmental impacts, operational energy, operational environmental impacts, total life-cycle energy, and total life cycle environmental impacts. Estimation of operational energy and LCA are performed using DesignBuilder software and Athena Impact estimator software respectively. The study results revealed that over the life span of the buildings, the relationship between the energy use and the environmental impacts are identical. LRA is found to be the best alternative in terms of embodied energy use and embodied environmental impacts; while, HRA showed the best life-cycle performance in terms of minimum energy use and environmental impacts. Sensitivity analysis has also been carried out to study the influence of building service lifespan over 50, 75, and 100 years on the relative significance of embodied energy and total life cycle energy. The life-cycle energy requirements for SDH is found to be a significant component among the four types of residential buildings. The overall disclose that the primary operations of these buildings accounts for 90% of the total life cycle energy which far outweighs minor differences in embodied effects between the buildings.

Keywords: building simulation, environmental impacts, life cycle assessment, life cycle energy analysis, residential buildings

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Authors: Ragaa T. Darwish, Maha A. Demellawy, Haidy M. Megahed, Doreen N. Younan, Wael S. Kholeif

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The testing of drug abuse is authentic in order to affirm the misuse of drugs. Several analytical approaches have been developed for the detection of drugs of abuse in pharmaceutical and common biological samples, but few methodologies have been created to identify them from fingerprints. Liquid Chromatography-Mass Spectrometry (LC-MS) plays a major role in this field. The current study aimed at assessing the possibility of detection of some drugs of abuse (tramadol, clonazepam, and phenobarbital) from fingerprints using LC-MS in drug abusers. The aim was extended in order to assess the possibility of detection of the above-mentioned drugs in fingerprints of drug handlers till three days of handling the drugs. The study was conducted on randomly selected adult individuals who were either drug abusers seeking treatment at centers of drug dependence in Alexandria, Egypt or normal volunteers who were asked to handle the different studied drugs (drug handlers). An informed consent was obtained from all individuals. Participants were classified into 3 groups; control group that consisted of 50 normal individuals (neither abusing nor handling drugs), drug abuser group that consisted of 30 individuals who abused tramadol, clonazepam or phenobarbital (10 individuals for each drug) and drug handler group that consisted of 50 individuals who were touching either the powder of drugs of abuse: tramadol, clonazepam or phenobarbital (10 individuals for each drug) or the powder of the control substances which were of similar appearance (white powder) and that might be used in the adulteration of drugs of abuse: acetyl salicylic acid and acetaminophen (10 individuals for each drug). Samples were taken from the handler individuals for three consecutive days for the same individual. The diagnosis of drug abusers was based on the current Diagnostic and Statistical Manual of Mental disorders (DSM-V) and urine screening tests using immunoassay technique. Preliminary drug screening tests of urine samples were also done for drug handlers and the control groups to indicate the presence or absence of the studied drugs of abuse. Fingerprints of all participants were then taken on a filter paper previously soaked with methanol to be analyzed by LC-MS using SCIEX Triple Quad or QTRAP 5500 System. The concentration of drugs in each sample was calculated using the regression equations between concentration in ng/ml and peak area of each reference standard. All fingerprint samples from drug abusers showed positive results with LC-MS for the tested drugs, while all samples from the control individuals showed negative results. A significant difference was noted between the concentration of the drugs and the duration of abuse. Tramadol, clonazepam, and phenobarbital were also successfully detected from fingerprints of drug handlers till 3 days of handling the drugs. The mean concentration of the chosen drugs of abuse among the handlers group decreased when the days of samples intake increased.

Keywords: drugs of abuse, fingerprints, liquid chromatography–mass spectrometry, tramadol

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Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

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Authors: Ayad Dalloo, Sulaf Dalloo

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Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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Authors: Jocelyn Floresca

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This paper aimed to present the by-product of the introduction of environmental ecology awareness on a formal education level utilizing the program course of Physical Education, particularly in the tertiary level. It is based on the premise that the radical need for environmental protection may not only necessarily be the work of people in the pure sciences but also deemed necessary to look into more avenues of the school setting particularly in the field of Physical Education. In the Philippines, most schools’ Physical Education focuses on the advancement of sports, fitness and wellness which are mostly done in the confines of a closed building. The paper dwells into the introduction of Physical Education as an outdoor recreation activity where in the participants of the study had the opportunity to indulge in activities undertaken outside the confines of buildings and going into large areas of the environment. It looked into the individual participant’s environmental social behaviour and effects on the participant’s perceptions in terms of the set objectives of Physical Education before and after the study’s intervention. The study utilized the formal course in Physical Education on nature walks, mountaineering and bird watching as interventions to gain perceptions and understanding. The introduction of the environmental ecology activities as a formal Physical Education course has resulted in deeper awareness that led to understanding the need to protect the environment, appreciation of the value of natural areas and acquiring behaviour for a sustainable use of the environment during the practice of Physical Education. Also, prior to the introduction of environmental ecology in Physical Education as a formal study; participants have no knowledge of what dwells in the identified sites of intervention. Whereas after the study, participants were able to identify various species of birds and plants found in the sites of the study that may lead to further conservation of the particular species.

Keywords: appreciation, conservation, environmental ecology, outdoor

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Authors: Ahmed Elbeheri, Tarek Zayed

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Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.

Keywords: steel bridge, bridge inspection, steel corrosion, image processing

Procedia PDF Downloads 285

Authors: Allan F. F. Alves, Fernando A. Bacchim Neto, Guilherme Giacomini, Marcela de Oliveira, Ana L. M. Pavan, Maria E. D. Rosa, Diana R. Pina

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Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke.

Keywords: ischemic stroke, image processing, CT scans, Fuzzy C-means

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Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

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Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: fire detector, rack, response characteristic, warehouse

Procedia PDF Downloads 728

Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Joseph Omeiza Alao

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The wobbly state of waste management and the high level of environmental irresponsibility is a threat to environmental security, which invariably endangered public health, regional groundwater systems and atmospheric condition. The dumping of waste materials in water bodies and gutters and the frequent burning of waste materials heaped at dumpsites as well depict the highest level of environmental indiscipline. These unruly human factors have compelled this study to apply four different techniques for environmental impact assessment and the possible public health risks of poor waste management in Nigeria. The techniques include a geophysical survey (resistivity data acquisition), dispatched questionnaire surveys, physiochemical water analysis and a physical survey of several dumpsites. While the resistivity data indicates high-level dumpsite leachate invading the ground soil down to the water table, the physiochemical water analysis depicts high content of BOD (401 – 711) mg/l, COD (731 – 1312) mg/l, TDS (419 – 1871) mg/l and heavy metals (0.014 – 1.971) mg/l present in the regional groundwater systems, which have altered the chemistry of the regional groundwater. The resistivity data shows that the overburdened soil layer overlaying the regional groundwater systems was very low (4.5 Ωm – 151 Ωm) as against the existing data (180 Ωm – 3500 Ωm). However, the physical surveys and the dispatched questionnaire surveys explore the depth of environmental irresponsibility among the citizen. While the imprints of gross environmental indiscipline may be absolutely irreversible, adequate knowledge of the environmental implications of careless waste disposal. After a critical examination of the current waste management strategies in Nigeria, the study suggests a future direction for environmental security and sustainability. Several influential regional factors, such as geology, climatic conditions, and hydrology, were also discussed.

Keywords: groundwater, environmental indiscipline, waste management, water analysis, leachate plumes, public health

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Authors: Ghanima Al-Sharrah, Haitham M. Lababidi, Yusuf I. Ali

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The main objective of the current work is to introduce sustainability factors in optimizing the supply chain model for process industries. The supply chain models are normally based on purely economic considerations related to costs and profits. To account for sustainability, two additional factors have been introduced; environment and risk. A supply chain for an entire petroleum organization has been considered for implementing and testing the proposed optimization models. The environmental and risk factors were introduced as indicators reflecting the anticipated impact of the optimal production scenarios on sustainability. The aggregation method used in extending the single objective function to multi-objective function is proven to be quite effective in balancing the contribution of each objective term. The results indicate that introducing sustainability factor would slightly reduce the economic benefit while improving the environmental and risk reduction performances of the process industries.

Keywords: environmental indicators, optimization, risk, supply chain

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Authors: W. J. Zhang, Y. Q. Du, M. L. Wang

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Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancement in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Eight DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, cirrhosis and diabetes. Our tests indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, reproducibility, and repeatability. Furthermore, different molecules can be distinguished through pattern recognition enabled by this sensor array. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or bimolecular detection for the noninvasive diagnostics of diseases and health monitoring.

Keywords: breath analysis, diagnosis, DNA-SWNT sensor array, noninvasive

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Authors: Shah Sufaid, Hussain Shahid, Tianyan You, Liu Guiwu, Qiao Guanjun

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Nickel oxide (NiO) is an optimal material for precise detection of hydrogen (H₂) gas due to its high catalytic activity and low resistivity. However, the gas response kinetics of H₂ gas molecules with the surface of NiO concurrence limitation imposed by its solid structure, leading to a diminished gas response value and slow electron-hole transport. Herein, NiO@CuO NFs with porous sharp-tip and nanospheres morphology were successfully synthesized by using a metal-organic framework (MOFs) as a precursor. The fabricated porous 2 wt% NiO@CuO NFs present outstanding selectivity towards H₂ gas, including a high sensitivity of a response value (170 to 20 ppm at 150 °C) higher than that of porous Ni-MOF (6), low detection limit (300 ppb) with a notable response (21), short response and recovery times at (300 ppb, 40/63 s and 20 ppm, 100/167 s), exceptional long-term stability and repeatability. Furthermore, an understanding of NiO@CuO sensor functioning in an actual environment has been obtained by using the impact of relative humidity as well. The boosted hydrogen sensing properties may be attributed due to synergistic effects of numerous facts including p-p heterojunction at the interface between NiO and CuO nanoflowers. Particularly, a porous Ni-MOF structure combined with the chemical sensitization effect of NiO with the rough surface of CuO nanosphere, are examined. This research presents an effective method for development of Ni-MOF derived metal oxide semiconductor (MOS) heterostructures with rigorous morphology and composition, suitable for gas sensing application.

Keywords: NiO@CuO NFs, metal organic framework, porous structure, H₂, gas sensing

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Authors: Jan Jezek, Zdenek Pilat, Filip Smatlo, Pavel Zemanek

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We present a device that combines fluorescence spectroscopy with fiber optics and dielectrophoretic micromanipulation in PDMS (poly-(dimethylsiloxane)) microfluidic chips. The device allows high speed detection (in the order of kHz) of the fluorescence signal, which is coming from the sample by an inserted optical fiber, e.g. from a micro-droplet flow in a microfluidic chip, or even from the liquid flowing in the transparent capillary, etc. The device uses a laser diode at a wavelength suitable for excitation of fluorescence, excitation and emission filters, optics for focusing the laser radiation into the optical fiber, and a highly sensitive fast photodiode for detection of fluorescence. The device is combined with dielectrophoretic sorting on a chip for sorting of micro-droplets according to their fluorescence intensity. The electrodes are created by lift-off technology on a glass substrate, or by using channels filled with a soft metal alloy or an electrolyte. This device found its use in screening of enzymatic reactions and sorting of individual fluorescently labelled microorganisms. The authors acknowledge the support from the Grant Agency of the Czech Republic (GA16-07965S) and Ministry of Education, Youth and Sports of the Czech Republic (LO1212) together with the European Commission (ALISI No. CZ.1.05/2.1.00/01.0017).

Keywords: dielectrophoretic sorting, fiber optics, laser, microfluidic chips, microdroplets, spectroscopy

Procedia PDF Downloads 700