Search results for: biological insights

Authors: Bhavana Mahajan

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International Relations is a discipline of paradoxes. The State is the dominant political institution, yet little attention has been accorded to why individual countries behave the way they do with the theoretical analysis dismissing the State as a reactionary monolith – thus States either play to “quest for power” or to “systemic” forces. However, States do behave as and are influenced by agents when interacting with international structures as well as with other states. While questions on “competitive power politics” and “trust” have been examined and developed to a fair extent by International Relations theorists in the post 1990s period, their application to the domain of South Asian politics is limited and little research, if any, examines the conduct of foreign policy beyond rational choice. This paper is an initial attempt to marry these theoretical insights with the foreign policy exercised by India especially the case of the “Gujral Doctrine, as one of “non-reciprocal accommodation”. Ignoring the view that such a policy move can be viewed as political “feinting” or deception, it is noteworthy that India even made the first move in terms of defining its role as one who “trusts” rather than one who “seeks” to trust, given the country’s geo-strategic context and threat perceptions.

Keywords: India’s foreign policy, South Asia, social constructivism, English school, trusting relationships, Gujral Doctrine, rationality

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Authors: Salim Yusif

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Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Haruo Okabayashi

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The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/listen to regrettable talk) are set for four minutes each, and the finger plethysmogram (200 Hz) of each participant is measured. As a result, the attractors of the participants who reported “I did not understand my partner” show the collapsed shape, which means the fluctuation of their rhythm is too small to match their partner’s rhythm, and their cross correlation is low. The autonomic balance of both persons tends to resonate during conversation, and both LLEs tend to resonate, too. In human history, in order for human beings as weak mammals to live, they may have been with others; that is, they have brought about resonating characteristics, which is called self-organization. However, the resonant feature sometimes collapses, depending on the lifestyle that the person was formed by himself after birth. It is difficult for people who do not have a lifestyle of mutual gaze to resonate their biological signal waves with others’. These people have features such as anxiety, fatigue, and confusion tendency. Mutual understanding is thought to be formed as a result of cooperation between the features of self-organization of the persons who are talking and the lifestyle indicated by mutual gaze. Such an entanglement phenomenon is called a nonlinear relation. By this research, it is found that the formation of mutual understanding is expressed by the rhythm of a biological signal showing a nonlinear relationship.

Keywords: embodied approach, finger plethysmogram, mutual understanding, nonlinear phenomenon

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Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates into the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: consumer Behavior, social media, online purchasing, online transaction

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Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Na Xiao

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Animal metaphors have many different connotations, ranging from loving emotions to derogatory epithets, but gender expressions using animal metaphors are often imbalanced. Generally, animal metaphors related to females tend to be negative. Little known about the reasons for the negative expressions of animal female metaphors in Chinese contexts still have not been quantified. The Modern Chinese Corpus at the Center for Chinese Linguistics at Peking University (CCL Corpus) provided the data for this research, which aims to identify the influencing variables of gender differences in the description of animal metaphors mapping humans in Chinese by observing the percentage of "tiger" metaphor, which is based on the conceptual metaphor theory. A quantitative research method was used in this study to statistically examine the gender attitude percentage of the "tiger" metaphor using corpus data. This study has proved that the tiger metaphors associated with humans in the Chinese context tend to be negative. Importantly, this study has also shown that the high proportion of tiger metaphorical idioms is what causes the high proportion of negative tiger metaphors that are related to women. This finding can be used as crucial information for future studies on other gender-related animal metaphorical idioms and can offer additional insights for understanding trends in other animal metaphors.

Keywords: Chinese, CCL corpus, gender differences, metaphorical idioms, tigers

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Authors: Sze Ming Yau

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Social worker-client interacting experience is scarcely studied in Hong Kong. Through this qualitative study, the experiences of Hong Kong social work practitioners in relating with clients provide new insights on social worker training and development. Thematic analysis is applied to examine the data collected by in-depth interviews with six local social work practitioners. The results show all practitioners have experienced both positive and challenging situations during the relating process. Their reactions either facilitate or hinder the process. Most of the practitioners’ strong reactions can be accounted for by using the concept of countertransference reactions during the interview session with clients. Moreover, they also have rarely reviewed the implications of those reactions after the session. In addition to countertransference, the self-expectation of practitioners also influences the relating process. Their self-expectations of being capable to help lead to anxiety. Though countertransference and anxiety of practitioners significantly influence the relating process, the practitioners do not adequately address personal issues and anxiety. Enhancing case conceptualization ability is their major coping strategy. The study has implications, including enhancement of social work training, workplace support, practitioner’s self-reflection, and integration of theory and practice.

Keywords: coping, countertransference, reactions, relating process, social workers

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Authors: Neslihan Beyazit, Sahin Bayraktar, Cahit Demetgul

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Transition metal ions have an important role in biochemistry and biomimetic systems and may provide the basis of models for active sites of biological targets. The presence of copper(II), iron(II) and zinc(II) is crucial in many biological processes. Tetradentate N2O2 donor Schiff base ligands are well known to form stable transition metal complexes and these complexes have also applications in clinical and analytical fields. In this study, we present salient structural features and the details of cathecholase activity of Fe(II) complex of a new Schiff Base ligand. A new asymmetrical N2O2 donor Schiff base ligand and its Fe(II) complex were synthesized by condensation of 4-nitro-1,2 phenylenediamine with 6-formyl-7-hydroxy-5-methoxy-2-methylbenzopyran-4-one and by using an appropriate Fe(II) salt, respectively. Schiff base ligand and its metal complex were characterized by using FT-IR, 1H NMR, 13C NMR, UV-Vis, elemental analysis and magnetic susceptibility. In order to determine the kinetics parameters of catechol oxidase-like activity of Schiff base Fe(II) complex, the oxidation of the 3,5-di-tert-butylcatechol (3,5-DTBC) was measured at 25°C by monitoring the increase of the absorption band at 390-400 nm of the product 3,5-di-tert-butylcatequinone (3,5-DTBQ). The compatibility of catalytic reaction with Michaelis-Menten kinetics also investigated by the method of initial rates by monitoring the growth of the 390–400 nm band of 3,5-DTBQ as a function of time. Kinetic studies showed that Fe(II) complex of the new N2O2 donor Schiff base ligand was capable of acting as a model compound for simulating the catecholase properties of type-3 copper proteins.

Keywords: catecholase activity, Michaelis-Menten kinetics, Schiff base, transition metals

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Authors: Elias Akoury

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Nuclear Magnetic Resonance (NMR) spectroscopy is an indispensable technique used in structure determination of small and macromolecules to study their physical properties, elucidation of characteristic interactions, dynamics and thermodynamic processes. Quantum mechanics defines the theoretical description of NMR spectroscopy and treatment of the dynamics of nuclear spin systems. The phenomenon of residual dipolar coupling (RDCs) has become a routine tool for accurate structure determination by providing global orientation information of magnetic dipole-dipole interaction vectors within a common reference frame. This offers accessibility of distance-independent angular information and insights to local relaxation. The measurement of RDCs requires an anisotropic orientation medium for the molecules to partially align along the magnetic field. This can be achieved by introduction of liquid crystals or attaching a paramagnetic center. Although anisotropic paramagnetic tags continue to mark achievements in the biomolecular NMR of large proteins, its application in small organic molecules remains unspread. Here, we propose a strategy for the synthesis of a lanthanide tag and the measurement of RDCs in organic molecules using paramagnetic lanthanide complexes.

Keywords: lanthanide tags, NMR spectroscopy, residual dipolar coupling, quantum mechanics of spin dynamics

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Authors: Oliver Marunțălu, Elena Elisabeta Manea, Lăcrămioara Diana Robescu, Mihai Necșoiu, Gheorghe Lăzăroiu, Dana Andreya Bondrea

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In order to obtain efficient pollutants removal in small-scale wastewater treatment plants, uniform water flow has to be achieved. The experimental setup, designed for treating high-load wastewater (leachate), consists of two aerobic biological reactors and a lamellar settler. Both biological tanks were aerated by using three different types of aeration systems - perforated pipes, membrane air diffusers and tube ceramic diffusers. The possibility of homogenizing the water mass with each of the air diffusion systems was evaluated comparatively. The oxygen concentration was determined by optical sensors with data logging. The experimental data was analyzed comparatively for all three different air dispersion systems aiming to identify the oxygen concentration variation during different operational conditions. The Oxygenation Capacity was calculated for each of the three systems and used as performance and selection parameter. The global mass transfer coefficients were also evaluated as important tools in designing the aeration system. Even though using the tubular porous diffusers leads to higher oxygen concentration compared to the perforated pipe system (which provides medium-sized bubbles in the aqueous solution), it doesn’t achieve the threshold limit of 80% oxygen saturation in less than 30 minutes. The study has shown that the optimal solution for the studied configuration was the radial air diffusers which ensure an oxygen saturation of 80% in 20 minutes. An increment of the values was identified when the air flow was increased.

Keywords: flow, aeration, bioreactor, oxygen concentration

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Cornellia Ayu, Putrianti Herni, Saptoto Robertus

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In the context of global tourism and creative economies, digital maturity has become a crucial factor for the sustainable development of small and medium enterprises (SMEs). This paper explores the journey toward digital maturity among SMEs in Sleman, Yogyakarta, Indonesia, focusing on their empowerment to foster sustainable tourism and creative economy growth. The study adopts a mixed-methods approach, integrating qualitative interviews with SME owners and quantitative surveys to assess their digital capabilities and readiness. Data were collected from a diverse sample of SMEs engaged in various sectors, including crafts and culinary services. Findings reveal significant gaps in digital literacy and infrastructure, impeding the full realization of digital benefits. However, targeted interventions, such as digital training programs and the provision of affordable technology, have shown promise in bridging these gaps. The study concludes that enhancing digital maturity among SMEs is vital for their competitiveness and sustainability in the modern economy. The insights gained can inform policymakers and stakeholders aiming to bolster the digital transformation of SMEs in similar contexts.

Keywords: digital maturity, small medium enterprises, digital literacy, sustainable tourism, creative economy

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Authors: Yaxin Tang, Mingao Hou, Qian He, Guangfu Luo

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Bimetallic nanoparticles serve as a promising class of catalysts with tunable properties suitable for diverse catalytic reactions, yet a comprehensive understanding of their actual structures under operating conditions and the optimal design principles remains largely elusive. In this study, we unveil a prevalent surface segregation phenomenon in nearly 100 platinum-group-element-based bimetallic nanoparticles through first principles-based molecular dynamics simulations. Our findings highlight that two components in a nanoparticle with relatively lower surface energy tend to segregate to the surface. Motivated by this discovery, we propose a deliberate exploitation of surface segregation in designing bimetallic nanoparticle catalysts, aiming for heightened stability and reduced consumption of precious metals. To validate this strategy, we further investigate 36 platinum-based bimetallic nanoparticles for propane dehydrogenation catalysis. Through a systematic examination of catalytic sites on nanoparticles, we identify several systems as top candidates with Pt-enriched surfaces, remarkable thermal stability, and superior catalytic activity for propane dehydrogenation. The insights gained garnered from this study are anticipated to provide a valuable framework for the optimal design of other bimetallic nanoparticles.

Keywords: bimetallic nanoparticles, platinum-group element, catalysis, surface segregation, first-principles calculations

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Authors: Ngonidzashe Mangoma, Caroline Marigold Sebata

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The release of cyanide-rich effluents from gold mines, and other industries, into the environment, is a global concern considering the well-known metabolic effects of cyanide in all forms of life. Such effluents need to be treated to remove cyanide, among other pollutants, before their disposal. This study aimed at investigating the possible use of bacteria in the biological removal of cyanide from cyanide-rich effluents. Firstly, cyanide-degrading bacteria were isolated from gold mine effluents and characterised. The isolates were then tested for their ability to grow in the presence of cyanide and their tolerance to increasing levels of the compound. To evaluate each isolate’s cyanide-degrading activities, isolates were grown in the simulated and actual effluent, and a titrimetric method was used to quantify residual cyanide over a number of days. Cyanide degradation efficiency (DE) was then calculated for each isolate. Identification of positive isolates involved 16S rRNA gene amplification and sequence analysis through BLAST. Six cyanide-utilising bacterial strains were isolated. Two of the isolates were identified as Klebsiella spp. while the other two were shown to be different strains of Clostridium bifermentans. All isolates showed normal growth in the presence of cyanide, with growth being inhibited at 700 mg/L cyanide and beyond. Cyanide degradation efficiency for all isolates in the simulated effluent ranged from 79% to 97%. All isolates were able to remove cyanide from actual gold mine effluent with very high DE values (90 – 94%) being recorded. Isolates obtained in this study were able to efficiently remove cyanide from both simulated and actual effluent. This observation clearly demonstrates the feasibility of the biological removal of cyanide from cyanide-rich gold mine effluents and should, therefore, motivate research towards the possible large-scale application of this technology.

Keywords: cyanide effluent, bioremediation, Clostridium bifermentans, Klebsiella spp, environment

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Authors: Job Bapyibi Guyson, Bangripa Kefas

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The advent of social media has no doubt provided platforms that facilitate the spread of fake news. The devastating impact of this does not only end with the prevalence of rumours and propaganda but also poses potential impact on individuals’ mental well-being. Therefore, this study on examining the impact of fake news on the mental health of residents in Jos metropolis among others interrogates the impact of exposure to fake news on residents' mental health. Anchored on the Cultivation Theory, the study adopted quantitative method and surveyed two the opinions of hundred (200) social media users in Jos metropolis using purposive sampling technique. The findings reveal that a significant majority of respondents perceive fake news as highly prevalent on social media, with associated feelings of anxiety and stress. The majority of the respondents express confidence in identifying fake news, though a notable proportion lacks such confidence. Strategies for managing the mental impact of encountering fake news include ignoring it, fact checking, discussing with others, reporting to platforms, and seeking professional support. Based on these insights, recommendations were proposed to address the challenges posed by fake news. These include promoting media literacy, integrating fact-checking tools, adjusting algorithms and fostering digital well-being features among others.

Keywords: fake news, mental health, social media, impact

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Authors: Brang Mai Lazing

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The central argument of this paper proposes that while democracy cannot guarantee transparency, authentic transparency within the hierarchy of the Church can be pursued as a means of dealing with cases of clergy sexual abuse. Amid the recent global scandal of clergy sexual abuse cases, a previous study has argued that a democratic rule should be applied to the administration of the Church so that, while a democratic Church could be compelled to exercise greater transparency when handling such cases, the Church might thereby regain credibility. Using the methodology of literature analysis, this paper explores the necessity for hierarchy and finds that democracy cannot be a guarantee for transparency. Further, through a dialogue between the theological insights of Benedict XVI and Edward Schillebeeckx, this paper argues that transparency practices are possible within the hierarchy of the Catholic Church in dealing with clergy sexual abuse cases. Finally, three implications of transparency in dealing with clergy sexual abuse cases are proposed, viz.: (a) that the harm which is ultimately done to the sacred faith of believers and to the sacred origin of the hierarchy through clergy sexual abuse cases should be given greater emphasis, (b) that the removal of unnecessary layers within the Church hierarchy or replacement with layers empowered with the authority to effect change might help implement accountability and transparency practices, and (c) that any changes made to enhance transparency should be made in terms of ‘adaptability’.

Keywords: Benedict XVI, clergy sexual abuses, democracy, Edward Schillebeeckx, hierarchy, transparency

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Authors: Abrar Abuzaid, Maha Alaaeddine, Haya Alesayi

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This project is centered around understanding the usage and impact of Alexa, Amazon's popular virtual assistant, in everyday life. Alexa, known for its integration into devices like Amazon Echo, offers functionalities such as voice interaction, media control, providing real-time information, and managing smart home devices. Our primary focus is to conduct a straightforward survey aimed at uncovering how people use Alexa in their daily routines. We plan to reach out to a wide range of individuals to get a diverse perspective on how Alexa is being utilized for various tasks, the frequency and context of its use, and the overall user experience. The survey will explore the most common uses of Alexa, its impact on daily life, features that users find most beneficial, and improvements they are looking for. This project is not just about collecting data but also about understanding the real-world applications of a technology like Alexa and how it fits into different lifestyles. By examining the responses, we aim to gain a practical understanding of Alexa's role in homes and possibly in workplaces. This project will provide insights into user satisfaction and areas where Alexa could be enhanced to meet the evolving needs of its users. It’s a step towards connecting technology with everyday life, making it more accessible and user-friendly

Keywords: Amazon Alexa, artificial intelligence, smart speaker, natural language processing

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Authors: Araba A. Z. Osei-Tutu, Ebenezer Odame, Joseph Bawa, Samuel Amponsah

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Education is recognized as a fundamental human right and a catalyst for development. Despite progress in the provision of higher education on the African continent, there persist challenges with the tripartite areas of access, equity and quality. Therefore, this systematic review aimed at providing a comprehensive overview of conversations and voices of scholars on these three concepts in HE in Africa. The systematic review employed a thematic analysis approach, synthesizing findings from 38 selected sources. After a critical analysis of the sources included in the systematic review, deficits in access, quality, and equity were outlined, focusing on infrastructure, regional disparities, and privatization challenges. The review also revealed the weak enforcement of quality assurance measures. Strategies for improvement, proffered by the study, include expanding public sector HE, deregulating the educational sector, promoting open and distance learning, implementing preferential admission policies, and enhancing financial aid. This research contributes valuable insights for policymakers, educators, and stakeholders, fostering a collaborative approach to address challenges and promote holistic development in African higher education.

Keywords: access, equity, quality, higher education, Africa, systematic review, strategies

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Authors: Daidai Shen, Jean Claude Thill, Wenjia Zhang

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This study explores the dynamics of synergy and complementarity within city networks, specifically focusing on the headquarters-subsidiary relations of firms. We begin by defining these two types of networks and establishing their pivotal roles in shaping city network structures. Utilizing the mesoscale analytic approach of weighted stochastic block modeling, we discern relational patterns between city pairs and determine connection strengths through statistical inference. Furthermore, we introduce a community detection approach to uncover the underlying structure of these networks using advanced statistical methods. Our analysis, based on comprehensive network data up to 2017, reveals the coexistence of both complementarity and synergy networks within China’s technology-intensive manufacturing cities. Notably, firms in technology hardware and office & computing machinery predominantly contribute to the complementarity city networks. In contrast, a distinct synergy city network, underpinned by the cities of Suzhou and Dongguan, emerges amidst the expansive complementarity structures in technology hardware and equipment. These findings provide new insights into the relational dynamics and structural configurations of city networks in the context of technology-intensive manufacturing, highlighting the nuanced interplay between synergy and complementarity.

Keywords: city system, complementarity, synergy network, higher-order network

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Authors: Wenfan Yan, Yumei Han

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Objectives: Educational inequality persists between China's ethnic minority regions and the mainland. The key to rectifying this disparity lies in enhancing the quality of educators. This paper delves into the Chinese government's innovative policy, "Group Educators Supporting Tibet" (GEST), designed to bridge the shortage of high-quality teachers in Tibet, a representative underprivileged ethnic minority area. GEST aims to foster collective action by networking provincial expert educators with Tibetan counterparts and collaborating between supporting provincial educational entities and Tibetan education entities. Theoretical Framework: The unequal distribution of social capital contributes significantly to the educational gap between ethnic minority areas and other regions in China. Within the framework of social network theory, motivated GEST educators take action to foster resources and relationships. This study captures grassroots perspectives to outline how social networking contributes to the policy objective of enhancing Tibetan teachers' quality and eradicating educational injustice. Methodology: A sequential mixed-methods approach was adopted to scrutinize policy impacts from the vantage point of social networking. Quantitative research involved surveys for GEST and Tibetan teachers, exploring demographics, perceptions of policy significance, motivations, actions, and networking habits. Qualitative research included focus group interviews with GEST educators, local teachers, and students from program schools. The findings were meticulously analyzed to provide comprehensive insights into stakeholders' experiences and the impacts of the GEST policy. Key Findings: The policy empowers individuals to impact Tibetan education significantly. Motivated GEST educators with prior educational support experiences contribute to its success. Supported by a collective -school, city, province, and government- the new social structure fosters higher efficiency. GEST's approach surpasses conventional methods. The individual, backed by educators, realizes the potential of transformative class design. Collective activities -pedagogy research, teaching, mentoring, training, and partnerships- equip Tibetan teachers, enhancing educational quality and equity. This collaborative effort establishes a robust foundation for the policy's success, emphasizing the collective impact on Tibetan education. Contributions: This study contributes to international policy studies focused on educational equity through collective teacher action. Using a mixed-methods approach and guided by social networking theory, it accentuates stakeholders' perspectives, elucidating the genuine impacts of the GEST policy. The study underscores the advancement of social networking, the reinforcement of local teacher quality, and the transformative potential of cultivating a more equitable and adept teaching workforce in Tibet. Limitations of the Study and Suggestions for Future Research Directions: While the study emphasizes the positive impacts of motivated GEST educators, there might be aspects or challenges not fully explored. A more comprehensive understanding of potential drawbacks or obstacles would provide a more balanced view. For future studies, investigating the long-term impact of the GEST policy on educational quality could provide insights into the sustainability of the improvements observed. Also, understanding the perspectives of Tibetan teachers who may not have directly benefited from GEST could reveal potential disparities in policy implementation.

Keywords: teacher development, social networking, teacher quality, mixed research method

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Authors: Asma Ansari, Afsheen Aman, Shah Ali Ul Qader

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In the past few years, numerous concerns have been raised against increased bacterial resistance towards effective drugs and become a debated issue all over the world. With the emergence of drug resistant pathogens, the interaction of natural antimicrobial compounds and antibacterial nanoparticles has emerged as a potential candidate for combating infectious diseases. Microbial diversity in the biome provides an opportunity to screen new species which are capable of producing large number of antimicrobial compounds. Among these antimicrobial compounds, bacteriocins are highly specific and efficient antagonists. A combination of bacteriocin along with nanoparticles could prove to be more potent due to broadened antibacterial spectrum with possibly lower doses. In the current study, silver nanoparticles were synthesized through biological reduction using various isolated bacterial, fungal and yeast strains. Spectroscopy and scanning electron microscopy (SEM) was performed for the confirmation of nanoparticles. Bacteriocin was characterized and purified to homogeneity through gel permeation chromatography. The estimated molecular weight of bacteriocin was 10 kDa. Amino acid analysis and N-terminal sequencing revealed the novelty of the protein. Then antibacterial potential of silver nanoparticles and broad inhibitory spectrum bacteriocin was determined through agar well diffusion assay. These synthesized bacteriocin-Nanoparticles exhibit a good potential for clinical applications as compared to bacteriocin alone. This combination of bacteriocin with nanoparticles will be used as a new sort of biocide in the field of nano-proteomics. The advancement of nanoparticles-mediated drug delivery system will open a new age for rapid eradication of pathogens from biological systems.

Keywords: BAC-IB17, multidrug resistance, purification, silver nanoparticles

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Authors: Kadir Gök

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In this study, a vacuum system was developed for orthopedic drilling processes, and the most efficient processing parameters were determined using statistical analysis of temperature rise. A reverse engineering technique was used to obtain a 3D model of the chip vacuum system, and the obtained point cloud data was transferred to Solidworks software in STL format. An experimental design method was performed by selecting different parameters and their levels, such as RPM, feed rate, and drill bit diameter, to determine the most efficient processing parameters in temperature rise using ANOVA. Additionally, the bone chip-vacuum device was developed and performed successfully to collect the whole chips and fragments in the bone drilling experimental tests, and the chip-collecting device was found to be useful in removing overheating from the drilling zone. The effects of processing parameters on the temperature levels during the chip-vacuuming were determined, and it was found that bone chips and fractures can be used as autograft and allograft for tissue engineering. Overall, this study provides significant insights into the development of a vacuum system for orthopedic drilling processes and the use of bone chips and fractures in tissue engineering applications.

Keywords: vacuum system, orthopedic drilling, temperature rise, bone chips

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Authors: Emma Garcia-Meca, Jennifer Martinez-Ferrero, Camino Ramon Llorens

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This paper provides insights into how narcissistic Chief Executive Officers (CEOs) influence the presence of women in top management teams (TMT). We also study whether a CEO's power and gender and the gender diversity of the firm's board moderate the relationship between CEO narcissism and TMT gender diversity. Our results reveal that narcissistic CEOs are less likely to support women in TMTs, confirming that CEO personality traits influence team structure. Further results suggest that this aversion increases as the CEO's power grows when female representation on boards decreases and when the CEO is a woman. This paper integrates theories that use the social psychology and upper echelon theories, offering a greater understanding of how CEO personality traits influence the structure of firms. We also contribute to the knowledge about how different governance characteristics can moderate the influence of narcissistic CEOs on women in TMTs, highlighting the relevance of governance traits that increase the effect of narcissism. The results demonstrate different female behavior toward promoting TMT gender equality depending on the specific position of women in the firm's hierarchy and their psychological attributes. We find that women directors support social identity values, and narcissistic female CEOs act like queen bees.

Keywords: gender diversity, board, corporate governance, female CEO, management

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Authors: Aghamusa Azizov

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This study investigates the correlation between solar activity and sentiment in news media coverage, using a large-scale dataset of solar activity since 1750 and over 15 million articles from "The New York Times" dating from 1851 onwards. Employing Pearson's correlation coefficient and multiple Natural Language Processing (NLP) tools—TextBlob, Vader, and DistillBERT—the research examines the extent to which fluctuations in solar phenomena are reflected in the sentiment of historical news narratives. The findings reveal that the correlation between solar activity and media sentiment is generally negligible, suggesting a weak influence of solar patterns on the portrayal of events in news media. Notably, a moderate positive correlation was observed between the sentiments derived from TextBlob and Vader, indicating consistency across NLP tools. The analysis provides insights into the historical impact of solar activity on human affairs and highlights the importance of using multiple analytical methods to understand complex relationships in large datasets. The study contributes to the broader understanding of how extraterrestrial factors may intersect with media-reported events and underlines the intricate nature of interdisciplinary research in the data science and historical domains.

Keywords: solar activity correlation, media sentiment analysis, natural language processing, historical event patterns

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Authors: Dilin Chen, Kang Luo, Jian Wu, Chun Yang, Hongliang Yi

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Electrically driven flows (EDF) systems play an important role in fuel cells, electrochemistry, bioseparation technology, fluid pumping, and microswimmers. The core scientific problem is multifield coupling, the further development of which depends on the exploration of nonlinear instabilities, force competing mechanisms, and energy budgets. In our study, two categories of electrostatic force-dominated phenomena, induced charge electrosmosis (ICEO) and ion conduction pumping are investigated while considering polymer rheological characteristics and heat gradients. With finite volume methods, the thermal modulation strategy of ICEO under the thermal buoyancy force is numerically analyzed, and the electroelastic instability turn associated with polymer addition is extended. The results reveal that the thermal buoyancy forces are sufficient to create typical thermogravitational convection in competition with electroconvective modes. Electroelastic instability tends to be promoted by weak electrical forces, and polymers effectively alter the unstable transition routes. Our letter paves the way for improved mixing and heat transmission in microdevices, as well as insights into the non-Newtonian nature of electrohydrodynamic dynamics.

Keywords: non-Newtonian fluid, electroosmotic flow, electrohydrodynamic, viscoelastic liquids, heat transfer

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Authors: Valeria Piccioni, Matthias Leschok, Ina Cheibas, Illias Hischier, Benjamin Dillenburger, Arno Schlueter, Matthias Kohler, Fabio Gramazio

Abstract:

The decarbonisation of the building sector requires the development of building components that provide energy efficiency while producing minimal environmental impact. Recent advancements in large-scale 3D printing have shown that it is possible to fabricate components with embedded performances that can be tuned for their specific application. We investigate the potential of polymer 3D printing for the fabrication of translucent facade components. In this study, we explore the effect of geometry on thermal insulation of printed cavity structures following a Hot Box test method. The experimental results are used to calibrate a finite-element simulation model which can support the informed design of 3D printed insulation structures. We show that it is possible to fabricate components providing thermal insulation ranging from 1.7 to 0.95 W/m2K only by changing the internal cavity distribution and size. Moreover, we identify design guidelines that can be used to fabricate components for different climatic conditions and thermal insulation requirements. The research conducted provides the first insights into the thermal behaviour of polymer 3DP facades on a large scale. These can be used as design guidelines for further research toward performant and low-embodied energy 3D printed facade components.

Keywords: 3D printing, thermal performance, polymers, facade components, hot-box method

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Authors: Phimsupha Kokchang, Divine Ifransca Wijaya

Abstract:

The energy transition is crucial for mitigating climate change and achieving sustainable development and resilience. As the energy transition advances, generation Z is entering the economic world and will soon be responsible for taking care of the environment. This study aims to investigate the factors influencing generation Z’s pro-environmental behavior to support the energy transition. The theory of planned behavior approach was combined with the pro-environmental behavior concept to examine generation Z’s support toward the energy transition through participating in activism, using energy from renewable sources, opting for energy-efficient utilities or vehicles, and influencing others. Data were collected through an online questionnaire of 400 respondents aged 18-26 living in Jakarta, Indonesia. Partial least square structural equation modeling (PLS-SEM) using SmartPLS 3.0 software was used to analyze the reliability and validity of the measurement model. The results show that attitude, subjective norms, and perceived behavior control positively correlate with generation Z’s pro-environmental behavior to support the energy transition. This finding could enhance understanding and provide insights to formulate effective strategies and policies to increase generation Z’s support towards the energy transition. This study contributes to the energy transition discussion as it is included in the Sustainable Development Goals, as well as pro-environmental behavior and theory of planned behavior literature.

Keywords: energy transition, pro-environmental behavior, theory of planned behavior, generation Z

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Authors: Christiana Ene Ogwuche, Joseph Amupitan, George Ndukwe, Rachael Ayo

Abstract:

Maesobotrya barteri (Baill), belonging to the family Euphorbiaceae, is a medicinal plant growing widely in tropical Africa. The Aerial plant parts of Maesobotrya barteri (Baill) were collected fresh from Orokam, Ogbadibo local Government of Benue State, Nigeria in July 2013. Taxonomical identification was done by Mallam Musa Abdullahi at the Herbarium unit of Biological Sciences Department, ABU, Zaria, Nigeria. Pulverized aerial parts of Maesobotrya barteri (960g) was exhaustively extracted successively using petroleum ether, chloroform, ethyl acetate and methanol and concentrated in the rotary evaporator at 40°C. The Petroleum ether extract had the second highest activity against test microbes from preliminary crude microbial screenings. The Petroleum ether extract was subjected to phytochemical studies, antimicrobial analysis and column chromatography (CC). The column chromatography yielded fraction PE, which was further purified using preparative thin layer chromatography to give PE1. The structure of the isolated compound was established using 1-D NMR and 2-D NMR spectroscopic analysis and by direct comparison with data reported in literature was confirmed to be a mixture, an isomer of Betulinic acid and Oleanolic acid, both with the molecular weight (C₃₀H₄₈O₃). The bioactivity of this compound was carried out using some clinical pathogens and the activity compared with standard drugs, and this was found to be comparable with the standard drug.

Keywords: Maesobotrya barteri, medicinal plant, bioactivity, petroleum spirit extract, butellinic acid, oleanilic acid

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Authors: Karam Al-Assaf, Israa Al Khaffaf, Ryan Al Tayeb, Ayman Alzaatreh

Abstract:

A significant, manageable hazard to public health, happiness, and the achievement of sustainable development is air pollution. Outdoor air pollution has increased globally over the previous years, exposing billions of people worldwide to hazardous air. With UAE being no different, there are a variety of pollution-related problems that need to be addressed. Therefore, to gain insights from the government and decision makers, this study aims to analyze the annual trends of the five major air pollutants (NO2, SO2, O3, CO, and PM10) across five emirates in the UAE (Abu Dhabi, Dubai, Sharjah, Ajman, and Ras AL Khaimah) from 2013 to 2020. The results of the analysis revealed that air pollutants NO2, SO2, and PM10 were significantly different across the years and states. Moreover, it was found that the levels of NO2 are significantly different in Dubai across the years. Moreover, the levels of SO2 are significantly different in Sharjah across the years. Furthermore, it was found that PM10 was significantly different in Ajman across the years. Moreover, the analysis of the significant difference in the pollutants in the three areas (Downtown, Residential, Industrial) revealed that there is no significant difference in the pollutant levels across the years in the three different areas. This tool has shown its effectiveness in monitoring pollutant trends, providing valuable data for government investigations and control measures across the UAE. Additionally, it serves as a valuable resource for decision-makers to develop and implement policies aimed at improving pollutant levels.

Keywords: air pollution, air pollutant, repeated measures, MANOVA, UAE

Procedia PDF Downloads 60