Search results for: human detection

Authors: Amalia Zuhra

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Indonesia is very rich with its natural resources. Natural resource management becomes a challenge for Indonesia. Improper management will make the natural resources run out and future generations will not be able to enjoy the natural wealth. A good rule of law and proper implementation determines the success of the management of a country's natural resources. This paper examines the need to redefine problems and challenges in the management of natural resources in Indonesia in the context of law. The purpose of this article is to overview the latest issues and challenges in natural resource management and to redefine legal provisions related to environmental management and human rights protection so that the management of natural resources in the present and future will be more sustainable. This paper finds that sustainable management of natural resources is absolutely essential. The aspect of environmental protection and human rights must be elaborated more deeply so that the management of natural resources can be done maximally without harming not only people but also the environment.

Keywords: international environmental law, human rights law, natural resource management, sustainable development

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Authors: Luiz Carlos Dias Lima De Oliveira

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Psychology does not have the task of being confined only to the knowledge of losses, weaknesses or diseases, because it is necessary to give analogous dedication to the investigation of human virtues, efforts and aptitudes. The reasons for living with greater constancy and expressiveness act as a protective condition for risk behaviors, but with less constancy and expressiveness they can be a viable parameter of suicidal ideation or potential suicidal initiatives. In other words, Positive Psychology scientifically studies human strengths and virtues. In the same way, we refer to the basic psychological needs of the human being, according to the Theory of Self-Determination: the need for belonging, competence and autonomy to live the best possible life or the ability to make positive decisions in life. In this sense, following the assumptions of Positive Psychology, we raise the question of what are the reasons for living, seeking a way to draw attention to positive aspects of life.

Keywords: psychology, positive, self-determination, belonging, competence, autonomy, depression, suicide.

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Authors: Olukayode Bamgbose, Feyisola Agboola, Adewale M. Taiwo, Olanrewaju Olujimi Oluwole Terebo, Azeez Soyingbe, Akeem Bamgbade

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The present study evaluated the contents and health risk assessment of metals determined in milk and milk product samples collected from the Abeokuta market. Forty-five milk and milk product (yoghurt) samples were digested and analysed for selected metals using Atomic Absorption Spectrophotometric method. Health risk assessment was evaluated for hazard quotient (HQ), hazard index (HI), and cancer risk (CR). Data were subjected to descriptive and inferential statistics. The concentrations of Zn, which ranged from 3.24±0.59 to 4.35±0.59 mg/kg, were the highest in the samples. Cr and Cd were measured below the detection limit of the analytical instrument, while the Pb level was higher than the Codex Alimentarius Commission value of 0.02 mg/kg, indicating unsafe for consumption. However, the HQ of Pb and other metals in milk and milk product samples was less than 1.0, thereby establishing no adverse health effects for Pb and other metals. The distribution pattern of metals in milk and milk product samples followed the decreasing order of Zn > Fe > Ni > Co > Cu > Mn > Pb > Cd/Cr. The CR levels of meals were also less than the permissible limit of 1.0 x 10-4, establishing no possible development of cancer. Keywords: adverse effects, cancer, metals, milk, milk product, the permissible limit.

Keywords: adverse effects, cancer, metals, milk, milk product, permissible limit

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Authors: Swapneel U. Naphade, Dushyant A. Patil, Satyabodh M. Kulkarni

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In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Keywords: agriculture, human factors, product design, soil moisture control

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Authors: Il Ho Park, Joong Seob Lee, Sung Hun Kang, Jae-Min Shin, Il Seok Park, Seok Min Hong, Seok Jin Hong

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Introduction: The human microbiota is the aggregate of microorganisms, and the bacterial microbiome of the human digestive tract contributes to both health and disease. In health, bacteria are key components in the development of mucosal barrier function and in innate and adaptive immune responses, and they also work to suppress the establishment of pathogens. In human upper airway, the sinonasal microbiota might play an important role in chronic rhinosinusitis (CRS). The purpose of this study is to investigate the human upper airway microbiome in CRS patients and to compare the sinonasal microbiome of adults with children. Materials and methods: A total of 19 samples from 19 patients (Group1; 9 CRS in children, aged 5 to 14 years versus Group 2; 10 CRS in adults aged 21 to 59 years) were examined. Swabs were collected from the middle meatus and/or anterior ethmoid region under general anesthesia during endoscopic sinus surgery or tonsillectomy. After DNA extraction from swab samples, we analysed bacterial microbiome consortia using 16s rRNA gene sequencing approach (the Illumina MiSeq platform). Results: In this study, relatively abundance of the six bacterial phyla and tremendous genus and species found in substantial amounts in the individual sinus swab samples, include Corynebacterium, Hemophilus, Moraxella, and Streptococcus species. Anaerobes like Fusobacterium and Bacteroides were abundantly present in the children group, Bacteroides and Propionibacterium were present in adults group. In genus, Haemophilus was the most common CRS microbiome in children and Corynebacterium was the most common CRS microbiome in adults. Conclusions: Our results show the diversity of human upper airway microbiome, and the findings will suggest that CRS is a polymicrobial infection. The Corynebacterium and Hemophilus may live as commensals on mucosal surfaces of sinus in the upper respiratory tract. The further study will be needed for analysis of microbiome-human interactions in upper airway and CRS.

Keywords: microbiome, upper airway, chronic rhinosinusitis, adult and children

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Authors: Raahil Sheikh, Abhishek Maurya, Priya Gujjar, Himanshu Dwivedi, Prathamesh Minde

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UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided.

Keywords: UAV, drone, autonomous system, thermal imaging

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Authors: Atsebaha Gebrekidan Kahsay, Tsehaye Asmelash, Enquebaher Kassaye

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Background: Salmonella remains a global public health problem with a significant burden in sub-Saharan African countries. Human restricted cause of typhoid and paratyphoid fever are S. Typhi and S. Paratyphi, whereas S. Enteritidis and S. Typhimurium is the causative agent of invasive nontyphoidal diseases among humans and animals are their reservoir. The antibiotic resistance of Salmonella is another public health threat around the globe. To come up with full information about human and animal salmonellosis, we made a systematic review of the prevalence, serotypes, and antibiotic resistance of Salmonella in Ethiopia. Methods: This systematic review used Google Scholar and PubMed search engines to search articles from Ethiopia that were published in English in peer-reviewed international journals from 2010 to 2022. We used keywords to identify the intended research articles and used a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to ensure the inclusion and exclusion criteria. Frequencies and percentages were analyzed using Microsoft Excel. Results: Two hundred seven published articles were searched, and 43 were selected for a systematic review, human (28) and animals (15). The prevalence of Salmonella in humans and animals was 434 (5.2%) and 641(10.1%), respectively. Fourteen serotypes were identified from animals, and S. Typhimurium was among the top five. Among the ciprofloxacin-resistant isolates in human studies, 16.7% was the highest, whereas, for ceftriaxone, 100% resistance was reported. Conclusions: The prevalence of Salmonella among diarrheic patients and food handlers (5.2%) was lower than the prevalence in food animals (10.1%). We did not find serotypes of Salmonella in human studies, although fourteen serotypes were included in food-animal studies, and S. Typhimurium was among the top five. Salmonella species from some human studies revealed a non-susceptibility to ceftriaxone. We recommend further study about invasive nontyphoidal Salmonella and predisposing factors among humans and animals in Ethiopia.

Keywords: antibiotic resistance, prevalence, systematic review, serotypes, Salmonella, Ethiopia

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Jin Boo Jeong

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In this study, we elucidated anti-cancer activity and potential molecular mechanism of DKC against human colorectal cancer cells. DKC-E70 suppressed the proliferation of human colorectal cancer cell lines such as HCT116, SW480, LoVo and HT-29. Although DKC-E70 decreased cyclin D1 expression in protein and mRNA level, decreased level of cyclin D1 protein by DKC-E70 occurred at the earlier time than that of cyclin D1 mRNA, which indicates that DKC-E70-mediated downregulation of cyclin D1 protein may be a consequence of the induction of degradation and transcriptional inhibition of cyclin D1. In cyclin D1 degradation, we found that cyclin D1 downregulation by DKC-E70 was attenuated in presence of MG132. In addition, DKC-E70 phosphorylated threonine-286 (T286) of cyclin D1 and T286A abolished cyclin D1 downregulation by DKC-E70. We also observed that DKC-E70-mediated T286 phosphorylation and subsequent cyclin D1 degradation was blocked in presence of the inhibitors of ERK1/2, p38 or GSK3β. In cyclin D1 transcriptional inhibition, DKC-E70 inhibited the expression of β-catenin and TCF4, and β–catenin/TCF-dependent luciferase activity. Our results suggest that DKC-E70 may downregulate cyclin D1 as one of the potential anti-cancer targets through cyclin D1 degradation by T286 phosphorylation dependent on ERK1/2, p38 or GSK3β, and cyclin D1 transcriptional inhibition through Wnt signaling. From these findings, DKC-E70 has potential to be a candidate for the development of chemoprevention or therapeutic agents for human colorectal cancer. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1D1A3B03931713).

Keywords: anticancer, calyx of persimmon, cyclin D1, Diospyros kaki Thunb., human colorectal cancer

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Authors: Tracy Smith-Carrier

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In 1995, the World Health Organization declared that poverty was the biggest killer and the greatest cause of suffering in the world. Income is certainly a key social determinant of health, the lack of which causes innumerable health and mental health conditions. In seeking to provide relief from financial hardship for residents within their populace, states in the Global North have largely turned to the non-profit and charitable sector. The stigma and shame of accessing charity is a significant barrier for many, but what is more problematic is that the embrace of the charitable model has let governments off the hook from responding to their international human rights obligations. Although states are signatories to various human rights treaties and conventions internationally, many of these laws have not been implemented domestically. This presentation explores the limits of the charitable model in addressing poverty in countries of the Global North. Unlike in the ages passed, when poverty was thought to be an individual problem, we now know that poverty is largely systemic in nature. In this presentation, we will identify the structural determinants of poverty, outline why people are reticent to access charitable programs and services and how income security is reproduced through the charitable model, and discuss evidence-informed solutions, such as a basic income guarantee, to move beyond the charitable model in favour of a rights-based justice model. To move beyond charity, we must demand that governments recognize our fundamental human rights and address poverty and hunger using a justice model based on substantive human rights.

Keywords: basic income, charity, poverty, income security, hunger, food security, social justice, human rights

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Wassim Guermazi, Saoussan Boukhris, Neila Annabi Trabelsi, Tarek Rebai, Alya Sellami-Kamoun, Habib Ayadi

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This work investigates the protective effects of the microalga Halamphora sp. extract (H. Ext) as a natural product on lead-intoxicated liver and kidney human cells in vitro and in vivo on rats wistar. HepG2 cells line derived from human hepatocellular carcinoma and HEK293 cells line derived from human embryonic kidney were used for the in vitro study. The analysis of the fatty acids methyl esters of the extract was performed by a GC/MS. Four groups of rats, each of which was composed of six animals, were used for the in vivo experiment. The pretreatment of HepG2 and HEK293 cells line with the extract (100 µg mL-1) significantly (p < 0.05) protected against cytotoxicity induced by lead exposure. In vivo, the biochemical parameters in serum, namely malondialdehyde level (MDA), superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) activities, were measured in supernatants of organ homogenates. H. Ext was found to be rich in fatty acids, essentially palmitic and palmitoleic accounting respectively 29.46% and 42.07% of total fatty acids. Both in vitro and in vivo, the co-treatment with H. Ext allowed the protection of the liver and kidney cells structure, as well as the significant preservation of normal antioxidant and biochemical parameters in rats. Halamphora extract rich in fatty acids has been proven to be effective in protection against Pb-induced toxicity.

Keywords: microalga extract, human cells line, fatty acid, lead exposure, oxidative stress, rats

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Authors: Jonathan Heng, Yoong Cheah Huei

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A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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Authors: Olatokunbo Yakeem

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Human trafficking is a crime against gross violations of human rights. Trafficking in persons is a severe socio-economic dilemma that affects the national and international dimensions. Human trafficking or modern-day-slavery emanated from slavery, and it has been in existence before the 6ᵗʰ century. Today, no country is exempted from dehumanizing human beings, and as a result, it has been an international issue. The United Nations (UN) presented the International Protocol to fight human trafficking worldwide, which brought about the international definition of human trafficking. The protocol is to prevent, suppress, and punish trafficking in persons, especially women and children. The trafficking protocol has a link with transnational organised crime rather than migration. Over a hundred and fifty countries nationwide have enacted their criminal and panel code trafficking legislation from the UN trafficking protocol. Sex trafficking is the most common type of exploitation of women and children. Other forms of this crime involve exploiting vulnerable victims through forced labour, child involvement in warfare, domestic servitude, debt bondage, and organ removal for transplantation. Trafficking of women and children into sexual exploitation represents the highest form of human trafficking than other types of exploitation. Trafficking of women and children can either happen internally or across the border. It affects all kinds of people, regardless of their race, social class, culture, religion, and education levels. However, it is more of a gender-based issue against females. Furthermore, human trafficking can lead to life-threatening infections, mental disorders, lifetime trauma, and even the victim's death. The study's significance is to explore why the root causes of women and children trafficking in Nigeria are based around poverty, entrusting children in the hands of relatives and friends, corruption, globalization, weak legislation, and ignorance. The importance of this study is to establish how the national, regional, and international organisations are using the 3P’s Protection, Prevention, and Prosecution) to tackle human trafficking. The methodology approach for this study will be a qualitative paradigm. The rationale behind this selection is that the qualitative method will identify the phenomenon and interpret the findings comprehensively. The data collection will take the form of semi-structured in-depth interviews through telephone and email. The researcher will use a descriptive thematic analysis to analyse the data by using complete coding. In summary, this study aims to recommend to the Nigerian federal government to include human trafficking as a subject in their educational curriculum for early intervention to prevent children from been coerced by criminal gangs. And the research aims to find the root causes of women and children trafficking. Also, to look into the effectiveness of the strategies in place to eradicate human trafficking globally. In the same vein, the research objective is to investigate how the anti-trafficking bodies such as law enforcement and NGOs collaborate to tackle the upsurge in human trafficking.

Keywords: children, Nigeria, trafficking, women

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Authors: Ka Ho Yau, Jan Frederick Engels, Kwok Kei Lai, Reinhard Renneberg

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Lateral flow test is a prevalent technology in various sectors such as food, pharmacology and biomedical sciences. Colloidal gold (CG) is widely used as the signalling molecule because of the ease of synthesis, bimolecular conjugation and its red colour due to intrinsic SPRE. However, the production of colloidal gold is costly and requires vigorous conditions. The stability of colloidal gold are easily affected by environmental factors such as pH, high salt content etc. Silica nanoparticles are well known for its ease of production and stability over a wide range of solvents. Using reverse micro-emulsion (w/o), silica nanoparticles with different sizes can be produced precisely by controlling the amount of water. By incorporating different water-soluble dyes, a rainbow colour of the silica nanoparticles could be produced. Conjugation with biomolecules such as antibodies can be achieved after surface modification of the silica nanoparticles with organosilane. The optimum amount of the antibodies to be labelled was determined by Bradford Assay. In this work, we have demonstrated the ability of the dye-doped silica nanoparticles as a signalling molecule in lateral flow test, which showed a semi-quantitative measurement of the analyte. The image was further analysed for the LOD=10 ng of the analyte. The working range and the linear range of the test were from 0 to 2.15μg/mL and from 0 to 1.07 μg/mL (R2=0.988) respectively. The performance of the tests was comparable to those using colloidal gold with the advantages of lower cost, enhanced stability and having a wide spectrum of colours. The positives lines can be imaged by naked eye or by using a mobile phone camera for a better quantification. Further research has been carried out in multicolour detection of different biomarkers simultaneously. The preliminary results were promising as there was little cross-reactivity being observed for an optimized system. This approach provides a platform for multicolour detection for a set of biomarkers that enhances the accuracy of diseases diagnostics.

Keywords: colorimetric detection, immunosensor, paper-based biosensor, silica

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Authors: Raahil Sheikh, Prathamesh Minde, Priya Gujjar, Himanshu Dwivedi, Abhishek Maurya

Abstract:

UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided

Keywords: UAV, autonomous systems, drones, geo thermal imaging

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Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

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Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

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This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle

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Authors: D. Bąk-Grabowska, K. Grzesik, A. Iwanicka, A. Jagoda

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The process of human resources management in the structures of corporate groups demonstrates certain specificity, resulting from the division of decision-making and executive competencies, which occurs within these structures between a parent company and its subsidiaries. The subprocess of employee assessment is considered crucial, since it provides information for the implementation of personnel function. The empirical studies conducted in corporate groups, within which at least one company is located in Poland, confirmed the critical significance of employee assessment systems in the process of human resources management in corporate groups. Parent companies, most often, retain their decision-making authority within the framework of the discussed process and introduce uniform employee assessment and personnel controlling systems to subsidiary companies. However, the instruments for employee assessment applied in corporate groups do not present such specificity.

Keywords: corporate groups, employee periodical assessment system, holding, human resources management

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Authors: Cheng-Cao Sun, Shu-Jun Li, De-Jia Li

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Long non-coding RNA (lncRNA) X inactivate-specific transcript (XIST) has been verified as an oncogenic gene in several human malignant tumors, and its dysregulation was closed associated with tumor initiation, development and progression. Nevertheless, whether the aberrant expression of XIST in human nasopharyngeal carcinoma (NPC) is corrected with malignancy, metastasis or prognosis has not been elaborated. Here, we discovered that XIST was up-regulated in NPC tissues and higher expression of XIST contributed to a markedly poorer survival time. In addition, multivariate analysis demonstrated XIST was an independent risk factor for prognosis. XIST over-expression enhanced, while XIST silencing hampered the cell growth in NPC. Additionally, mechanistic analysis revealed that XIST up-regulated the expression of miR-34a-5p targeted gene E2F3 through acting as a competitive ‘sponge’ of miR-34a-5p. Taking all into account, we concluded that XIST functioned as an oncogene in NPC through up-regulating E2F3 in part through ‘spongeing’ miR-34a-5p.

Keywords: X inactivate-specific transcript; hsa-miRNA-34a-5p, miR-34a-5p; E2F3, nasopharyngeal carcinoma, tumorigenesis

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Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

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The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

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Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

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Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

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Authors: Kati Skarp, Keijo Varis, Juha Kettunen

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The purpose of this paper is to examine and evaluate the top-down and bottom-up leadership development programs focused on human capital that improve the performance of a company. This study reports on the external top-down leadership development program supported by a consulting company and the internal participatory action research of the bottom-up program. The sickness rate and the lost time incident failure rate decreased and the ideas produced for cost savings improved, leading to increased earnings during the top-down program. The estimated cost savings potential of the bottom-up program was 3.8 million euro based on the cost savings of meeting habits, maintenance practices and the way of working in production. The results of this study are useful for those who plan and evaluate leadership development and human capital productivity consultation programs to improve the performance of a company.

Keywords: leadership, development, human resources, company, indicators, evaluation

Procedia PDF Downloads 316

Authors: Alisa Kazarina, Guntis Gerhards, Elina Petersone-Gordina, Ilva Pole, Viktorija Igumnova, Janis Kimsis, Valentina Capligina, Renate Ranka

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Human body is inhabited by a vast number of microorganisms, collectively known as the human microbiome, and there is a tremendous interest in evolutionary changes in human microbial ecology, diversity and function. The field of paleomicrobiology, study of ancient human microbiome, is powered by modern techniques of Next Generation Sequencing (NGS), which allows extracting microbial genomic data directly from archaeological sample of interest. One of the major techniques is 16S rRNA gene sequencing, by which certain 16S rRNA gene hypervariable regions are being amplified and sequenced. However, some limitations of this method exist including the taxonomic precision and efficacy of different regions used. The aim of this study was to evaluate the phylogenetic sensitivity of different 16S rRNA gene hypervariable regions for microbiome studies in the archaeological samples. Towards this aim, archaeological bone samples and corresponding soil samples from each burial environment were collected in Medieval cemeteries in Latvia. The Ion 16S™ Metagenomics Kit targeting different 16S rRNA gene hypervariable regions was used for library construction (Ion Torrent technologies). Sequenced data were analysed by using appropriate bioinformatic techniques; alignment and taxonomic representation was done using Mothur program. Sequences of most abundant genus were further aligned to E. coli 16S rRNA gene reference sequence using MEGA7 in order to identify the hypervariable region of the segment of interest. Our results showed that different hypervariable regions had different discriminatory power depending on the groups of microbes, as well as the nature of samples. On the basis of our results, we suggest that wider range of primers used can provide more accurate recapitulation of microbial communities in archaeological samples. Acknowledgements. This work was supported by the ERAF grant Nr. 1.1.1.1/16/A/101.

Keywords: 16S rRNA gene, ancient human microbiome, archaeology, bioinformatics, genomics, microbiome, molecular biology, next-generation sequencing

Procedia PDF Downloads 175

Authors: Won Kyung Ham, Kang Hoon Cho, Sang C. Park

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Presented in this paper is a framework of a software ‘WEMax’. The WEMax is invented for analysis and simulation for manned assembly lines to sustain and improve performance of manufacturing systems. In a manufacturing system, performance, such as productivity, is a key of competitiveness for output products. However, the manned assembly lines are difficult to forecast performance, because human labors are not expectable factors by computer simulation models or mathematical models. Existing approaches to performance forecasting of the manned assembly lines are limited to matters of the human itself, such as ergonomic and workload design, and non-human-factor-relevant simulation. Consequently, an approach for the forecasting and improvement of manned assembly line performance is needed to research. As a solution of the current problem, this study proposes a framework that is for generation and simulation of virtual manned assembly lines, and the framework has been implemented as a software.

Keywords: performance forecasting, simulation, virtual manned assembly line, WEMax

Procedia PDF Downloads 315

Authors: O. Starineca

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Some organizations as employers have difficulties to attract job seekers and retain their employees. Strategic planning of Human Resources (HR) presumes broad analysis of perspectives including analysis of potential job seekers in the field. Human Resources Recruitment (HRR) influences employer brand of an organization and peculiarities of both external organizational factors and stakeholders. Defining peculiarities of the future job seekers, who could potentially become the employees of the organization, could help to adjust HRR tools and methods adapt to the youngest generation employees’ preferences and be more successful in selecting the best candidates, who are likely to be loyal to the employer. The aim of the empirical study is definition of some students’ as job seekers peculiarities and their requirements to their potential employer. The survey in Latvia, Lithuania and Spain. Respondents were students from these countries’ tertiary education institutions Public Administration (PA) or relevant study programs. All three countries students’ peculiarities have just a slight difference. Overall, they all wish to work for a socially responsible employer that is able to provide positive working environment and possibilities for professional development and learning. However, respondents from each country have own peculiarities. The study might have a practical application. PA of the examined countries might use the results developing employer brand and creating job advertisements focusing on recent graduates’ recruitment.

Keywords: generation Y, human resources recruitment, job seekers, public administration

Procedia PDF Downloads 188

Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

Procedia PDF Downloads 110

Authors: Kiran Fatima, Kashif Ali

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Staphylococcus aureus is an opportunistic human as well as animal pathogen that causes a variety of diseases. A total of 70 staphylococci isolates were obtained from soil, water, yogurt, and clinical samples. The likely staphylococci clinical isolates were identified phenotypically by different biochemical tests. Molecular identification was done by PCR using species-specific 16S rRNA primer pairs, and finally, 50 isolates were found to be positive as Staphylococcus aureus, sciuri, xylous and cohnii. Screened isolates were further analyzed by several microbiological diagnostics tests, including gram staining, coagulase, capsule, hemolysis, fermentation of glucose, lactose, maltose, and sucrose tests enzymatic reactions. It was found that 78%, 81%, and 51% of isolates were positive for gelatin hydrolysis, protease, and lipase activities, respectively. Antibiogram analysis of isolated Staphylococcus aureus strains with respect to different antimicrobial agents revealed resistance patterns ranging from 57 to 96%. Our study also shows 70% of strains to be MRSA, 54.3% as VRSA, and 54.3% as both MRSA and VRSA. All the identified isolates were subjected to detection of mecA, nuc, and hlb genes, and 70%, 84%, and 40% were found to harbour mecA, nuc, and hlb genes, respectively. The current investigation is highly important and informative for the high-level multidrug-resistant Staphylococcus aureus infections inclusive also of methicillin and vancomycin.

Keywords: MRSA, VRSA, mecA, MSSA

Procedia PDF Downloads 112