Search results for: travel cost techniques

Authors: Łukasz Mazur, Kamil Domaradzki, Bartosz Kamecki, Justyna Ignaczak, Sebastian Molin, Aleksander Gil, Tomasz Brylewski

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The rising global power consumption necessitates the development of new energy storage solutions. Prospective technologies include solid oxide electrolyzer cells (SOECs), which convert surplus electrical energy into hydrogen. An electrolyzer cell consists of a porous anode, and cathode, and a dense electrolyte. Power output is increased by connecting cells into stacks using interconnects. Interconnects are currently made from high-chromium ferritic steels – for example, Crofer 22 APU – which exhibit high oxidation resistance and a thermal expansion coefficient that is similar to that of electrode materials. These materials have one disadvantage – their area-specific resistance (ASR) gradually increases due to the formation of a Cr₂O₃ scale on their surface as a result of oxidation. The chromia in the scale also reacts with the water vapor present in the reaction media, forming volatile chromium oxyhydroxides, which in turn react with electrode materials and cause their deterioration. The electrochemical efficiency of SOECs thus decreases. To mitigate this, the interconnect surface can be modified with protective-conducting coatings of spinel or other materials. The high prices of SOEC components -especially the Crofer 22 APU- have prevented their widespread adoption. More inexpensive counterparts, therefore, need to be found, and their properties need to be enhanced to make them viable. Candidates include the Nirosta 4016/1,4016 low-chromium ferritic steel with a chromium content of just 16.3 wt%. This steel's resistance to high-temperature oxidation was improved by depositing Gd₂O₃ nanoparticles on its surface via either dip coating or electrolysis. Modification with CeO₂ or Ce₀.₉Y₀.₁O₂ nanoparticles deposited by means of spray pyrolysis was also tested. These methods were selected because of their low cost and simplicity of application. The aim of this study was to investigate the oxidation kinetics of Nirosta 4016/1,4016 modified using the afore-mentioned methods and to subsequently measure the obtained samples' ASR. The samples were oxidized for 100 h in the air as well as air/H₂O and Ar/H₂/H₂O mixtures at 1073 K. Such conditions reflect those found in the anode and cathode operating space during real-life use of SOECs. Phase and chemical composition and the microstructure of oxidation products were determined using XRD and SEM-EDS. ASR was measured over the range of 623-1073 K using a four-point, two-probe DC technique. The results indicate that the applied nanoparticles improve the oxidation resistance and electrical properties of the studied layered systems. The properties of individual systems varied significantly depending on the applied reaction medium. Gd₂O₃ nanoparticles improved oxidation resistance to a greater degree than either CeO₂ or Ce₀.₉Y₀.₁O₂ nanoparticles. On the other hand, the cerium-containing nanoparticles improved electrical properties regardless of the reaction medium. The ASR values of all surface-modified steel samples were below the 0.1 Ω.cm² threshold set for interconnect materials, which was exceeded in the case of the unmodified reference sample. It can be concluded that the applied modifications increased the oxidation resistance of Nirosta 4016/1.4016 to a level that allows its use as SOEC interconnect material. Acknowledgments: Funding of Research project supported by program "Excellence initiative – research university" for the AGH University of Krakow" is gratefully acknowledged (TB).

Keywords: cerium oxide, ferritic stainless steel, gadolinium oxide, interconnect, SOEC

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Authors: Alexander A. Stakheev, Larisa V. Samokhvalova, Sergey K. Zavriev

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Fusarium fungi are among the most devastating plant pathogens distributed all over the world. Significant reduction of grain yield and quality caused by Fusarium leads to multi-billion dollar annual losses to the world agricultural production. These organisms can also cause infections in immunocompromised persons and produce the wide range of mycotoxins, such as trichothecenes, fumonisins, and zearalenone, which are hazardous to human and animal health. Identification of Fusarium fungi based on the morphology of spores and spore-forming structures, colony color and appearance on specific culture media is often very complicated due to the high similarity of these features for closely related species. Modern Fusarium taxonomy increasingly uses data of crossing experiments (biological species concept) and genetic polymorphism analysis (phylogenetic species concept). A number of novel Fusarium sibling species has been established using DNA barcoding techniques. Species recognition is best made with the combined phylogeny of intron-rich protein coding genes and ribosomal DNA sequences. However, the internal transcribed spacer of (ITS), which is considered to be universal DNA barcode for Fungi, is not suitable for genus Fusarium, because of its insufficient variability between closely related species and the presence of non-orthologous copies in the genome. Nowadays, the translation elongation factor 1 alpha (TEF1α) gene is the “gold standard” of Fusarium taxonomy, but the search for novel informative markers is still needed. In this study, we used two novel DNA markers, frataxin (FXN) and heat shock protein 90 (HSP90) to discover phylogenetic relationships between Fusarium species. Multilocus phylogenetic analysis based on partial sequences of TEF1α, FXN, HSP90, as well as intergenic spacer of ribosomal DNA (IGS), beta-tubulin (β-TUB) and phosphate permease (PHO) genes has been conducted for 120 isolates of 19 Fusarium species from different climatic zones of Russia and neighboring countries using maximum likelihood (ML) and maximum parsimony (MP) algorithms. Our analyses revealed that FXN and HSP90 genes could be considered as informative phylogenetic markers, suitable for evolutionary and taxonomic studies of Fusarium genus. It has been shown that PHO gene possesses more variable (22 %) and parsimony informative (19 %) characters than other markers, including TEF1α (12 % and 9 %, correspondingly) when used for elucidating phylogenetic relationships between F. avenaceum and its closest relatives – F. tricinctum, F. acuminatum, F. torulosum. Application of novel DNA barcodes confirmed the fact that F. arthrosporioides do not represent a separate species but only a subspecies of F. avenaceum. Phylogeny based on partial PHO and FXN sequences revealed the presence of separate cluster of four F. avenaceum strains which were closer to F. torulosum than to major F. avenaceum clade. The strain F-846 from Moldova, morphologically identified as F. poae, formed a separate lineage in all the constructed dendrograms, and could potentially be considered as a separate species, but more information is needed to confirm this conclusion. Variable sites in PHO sequences were used for the first-time development of specific qPCR-based diagnostic assays for F. acuminatum and F. torulosum. This work was supported by Russian Foundation for Basic Research (grant № 15-29-02527).

Keywords: DNA barcode, fusarium, identification, phylogenetics, taxonomy

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Johanes Mandowa

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The study evaluated the status of Occupational Safety and Health Management Systems’ (OSHMSs) implementation by Mutare urban timber processing factories. A descriptive cross sectional survey method was utilized in the study. Questionnaires, interviews and direct observations were the techniques employed to extract primary data from the respondents. Secondary data was acquired from OSH encyclopedia, OSH journals, newspaper articles, internet, past research papers, African Newsletter on OSH and NSSA On-guard magazines among others. Analysis of data collected was conducted using statistical and descriptive methods. Results revealed an unpleasant low uptake rate (16%) of OSH Management Systems by Mutare urban timber processing factories. On a comparative basis, low implementation levels were more pronounced in small timber processing factories than in large factories. The low uptake rate of OSH Management Systems revealed by the study validates the Government of Zimbabwe and its social partners’ observation that the dismal Zimbabwe OSH performance was largely due to non implementation of safety systems at most workplaces. The results exhibited a relationship between availability of a SHE practitioner in Mutare urban timber processing factories and OSHMS implementation. All respondents and interviewees’ agreed that OSH Management Systems are handy in curbing occupational injuries and diseases. It emerged from the study that the top barriers to implementation of safety systems are lack of adequate financial resources, lack of top management commitment and lack of OSHMS implementation expertise. Key motivators for OSHMSs establishment were cited as provision of adequate resources (76%), strong employee involvement (64%) and strong senior management commitment and involvement (60%). Study results demonstrated that both OSHMSs implementation barriers and motivators affect all Mutare urban timber processing factories irrespective of size. The study recommends enactment of a law by Ministry of Public Service, Labour and Social Welfare in consultation with NSSA to make availability of an OSHMS and qualified SHE practitioner mandatory at every workplace. More so, the enacted law should prescribe minimum educational qualification required for one to practice as a SHE practitioner. Ministry of Public Service, Labour and Social Welfare and NSSA should also devise incentives such as reduced WCIF premiums for good OSH performance to cushion Mutare urban timber processing factories from OSHMS implementation costs. The study recommends the incorporation of an OSH module in the academic curriculums of all programmes offered at tertiary institutions so as to ensure that graduates who later end up assuming influential management positions in Mutare urban timber processing factories are abreast with the necessity of OSHMSs in preventing occupational injuries and diseases. In the quest to further boost management’s awareness on the importance of OSHMSs, NSSA and SAZ are urged by the study to conduct OSHMSs awareness breakfast meetings targeting executive management on a periodic basis. The Government of Zimbabwe through the Ministry of Public Service, Labour and Social Welfare should also engage ILO Country Office for Zimbabwe to solicit for ILO’s technical assistance so as to enhance the effectiveness of NSSA’s and SAZ’s OSHMSs promotional programmes.

Keywords: occupational safety health management system, national social security authority, standard association of Zimbabwe, Mutare urban timber processing factories, ministry of public service, labour and social welfare

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Authors: Natalia Podkhodova, Olga Sheremeteva, Mariia Soldaeva

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Creating favorable conditions for students’ comprehension of mathematical content is one of the primary problems in teaching mathematics in secondary school. Psychology research has demonstrated that positive comprehension becomes possible when new information becomes part of student’s subjective experience and when linkages between the attributes of notions and various ways of their presentations can be established. The fact of comprehension includes the ability to build a working situational model and thus becomes an important means of solving mathematical problems. The article describes the implementation of a holistic approach to teaching mathematics designed to address the primary challenges of such teaching, specifically, the challenge of students’ comprehension. This approach consists of (1) establishing links between the attributes of a notion: the sense, the meaning, and the term; (2) taking into account the components of student’s subjective experience -emotional and value, contextual, procedural, communicative- during the educational process; (3) links between different ways to present mathematical information; (4) identifying and leveraging the relationships between real, perceptual and conceptual (scientific) mathematical spaces by applying real-life situational modeling. The article describes approaches to the practical use of these foundational concepts. Identifying how proposed methods and technology influence understanding of material used in teaching mathematics was the research’s primary goal. The research included an experiment in which 256 secondary school students took part: 142 in the experimental group and 114 in the control group. All students in these groups had similar levels of achievement in math and studied math under the same curriculum. In the course of the experiment, comprehension of two topics -'Derivative' and 'Trigonometric functions'- was evaluated. Control group participants were taught using traditional methods. Students in the experimental group were taught using the holistic method: under the teacher’s guidance, they carried out problems designed to establish linkages between notion’s characteristics, to convert information from one mode of presentation to another, as well as problems that required the ability to operate with all modes of presentation. The use of the technology that forms inter-subject notions based on linkages between perceptional, real, and conceptual mathematical spaces proved to be of special interest to the students. Results of the experiment were analyzed by presenting students in each of the groups with a final test in each of the studied topics. The test included problems that required building real situational models. Statistical analysis was used to aggregate test results. Pierson criterion was used to reveal the statistical significance of results (pass-fail the modeling test). A significant difference in results was revealed (p < 0.001), which allowed the authors to conclude that students in the study group showed better comprehension of mathematical information than those in the control group. Also, it was revealed (used Student’s t-test) that the students of the experimental group performed reliably (p = 0.0001) more problems in comparison with those in the control group. The results obtained allow us to conclude that increasing comprehension and assimilation of study material took place as a result of applying implemented methods and techniques.

Keywords: comprehension of mathematical content, holistic approach to teaching mathematics in secondary school, subjective experience, technology of the formation of inter-subject notions

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Authors: Oksana G. Cherednichenko, Anastasia L. Pilyugina, Sergey N.Lukashenko, Elena G. Gubitskaya

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The estimation of accumulated radiation doses in people professionally exposed to ionizing radiation was performed using methods of biological (chromosomal aberrations frequency in lymphocytes) and physical (radionuclides analysis in urine, whole-body radiation meter, individual thermoluminescent dosimeters) dosimetry. A group of 84 "A" category employees after their work in the territory of former Semipalatinsk test site (Kazakhstan) was investigated. The dose rate in some funnels exceeds 40 μSv/h. After radionuclides determination in urine using radiochemical and WBC methods, it was shown that the total effective dose of personnel internal exposure did not exceed 0.2 mSv/year, while an acceptable dose limit for staff is 20 mSv/year. The range of external radiation doses measured with individual thermo-luminescent dosimeters was 0.3-1.406 µSv. The cytogenetic examination showed that chromosomal aberrations frequency in staff was 4.27±0.22%, which is significantly higher than at the people from non-polluting settlement Tausugur (0.87±0.1%) (р ≤ 0.01) and citizens of Almaty (1.6±0.12%) (р≤ 0.01). Chromosomal type aberrations accounted for 2.32±0.16%, 0.27±0.06% of which were dicentrics and centric rings. The cytogenetic analysis of different types group radiosensitivity among «professionals» (age, sex, ethnic group, epidemiological data) revealed no significant differences between the compared values. Using various techniques by frequency of dicentrics and centric rings, the average cumulative radiation dose for group was calculated, and that was 0.084-0.143 Gy. To perform comparative individual dosimetry using physical and biological methods of dose assessment, calibration curves (including own ones) and regression equations based on general frequency of chromosomal aberrations obtained after irradiation of blood samples by gamma-radiation with the dose rate of 0,1 Gy/min were used. Herewith, on the assumption of individual variation of chromosomal aberrations frequency (1–10%), the accumulated dose of radiation varied 0-0.3 Gy. The main problem in the interpretation of individual dosimetry results is reduced to different reaction of the objects to irradiation - radiosensitivity, which dictates the need of quantitative definition of this individual reaction and its consideration in the calculation of the received radiation dose. The entire examined contingent was assigned to a group based on the received dose and detected cytogenetic aberrations. Radiosensitive individuals, at the lowest received dose in a year, showed the highest frequency of chromosomal aberrations (5.72%). In opposite, radioresistant individuals showed the lowest frequency of chromosomal aberrations (2.8%). The cohort correlation according to the criterion of radio-sensitivity in our research was distributed as follows: radio-sensitive (26.2%) — medium radio-sensitivity (57.1%), radioresistant (16.7%). Herewith, the dispersion for radioresistant individuals is 2.3; for the group with medium radio-sensitivity — 3.3; and for radio-sensitive group — 9. These data indicate the highest variation of characteristic (reactions to radiation effect) in the group of radio-sensitive individuals. People with medium radio-sensitivity show significant long-term correlation (0.66; n=48, β ≥ 0.999) between the values of doses defined according to the results of cytogenetic analysis and dose of external radiation obtained with the help of thermoluminescent dosimeters. Mathematical models based on the type of violation of the radiation dose according to the professionals radiosensitivity level were offered.

Keywords: biodosimetry, chromosomal aberrations, ionizing radiation, radiosensitivity

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Authors: Layla Haidar, Shari Esquenazi-Karonika

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Introduction: Mental health includes one’s emotional, psychological, and interpersonal well-being; it ranges from “good” to “poor” on a continuum. At the individual-level, it affects how a person thinks, feels, and acts. Moreover, it determines how they cope with stress, relate to others, and interface with their surroundings. Research has yielded that mental health is directly related with short- and long-term physical health (including chronic disease), health risk behaviors, education-level, employment, and social relationships. As is the case with physical conditions like diabetes, heart disease, and cancer, mitigating the behavioral and genetic risks of debilitating mental health conditions like anxiety and depression can nurture a healthier quality of mental health throughout one’s life. In order to maximize the benefits of prevention, it is important to identify modifiable risks and develop protective habits earlier in life. Methods: The Adolescent Behaviors and Experiences Survey (ABES) dataset was used for this study. The ABES survey was administered to high school students (9th-12th grade) during January 2021- June 2021 by the Centers for Disease Control and Prevention (CDC). The data was analyzed to identify any associations between feelings of sadness, hopelessness, or increased suicidality among high school students with relation to their participation on one or more sports teams and their average daily consumed screen time. Data was analyzed using descriptive and multivariable analytic techniques. A multinomial logistic regression of each variable was conducted to examine if there was an association, while controlling for grade-level, sex, and race. Results: The findings from this study are insightful for administrators and policymakers who wish to address mounting concerns related to student mental health. The study revealed that compared to a student who participated on zero sports teams, students who participated in 1 or more sports teams showed a significantly increased risk of depression (p<0.05). Conversely, the rate of depression in students was significantly less in those who consumed 5 or more hours of screen time per day, compared to those who consumed less than 1 hour per day of screen time (p<0.05). Conclusion: These findings are informative and highlight the importance of understanding the nuances of student participation on sports teams (e.g., physical exertion, social dynamics of team, and the level of competitiveness within the sport). Likewise, the context of an individual’s screen time (e.g., social media, engaging in team-based video games, or watching television) can inform parental or school-based policies about screen time activity. Although physical activity has been proven to be important for emotional and physical well-being of youth, playing on multiple teams could have negative consequences on the emotional state of high school students potentially due to fatigue, overtraining, and injuries. Existing literature has highlighted the negative effects of screen time; however, further research needs to consider the type of screen-based consumption to better understand its effects on mental health.

Keywords: behavioral science, mental health, adolescents, prevention

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Authors: Carles Martinez-Almoyna Gual, Jiwon Choi

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Urban communities face risks of disintegration and segregation as a consequence of globalised migration processes towards urban environments. Linking social and cultural components with environmental and economic dimensions becomes the goal of all the disciplines that aim to shape more sustainable urban environments. Solutions require interdisciplinary approaches and the use of a complex array of tools. One of these tools is the implementation of urban farming, which provides a wide range of advantages for creating more inclusive spaces and integrated communities. Since food is strongly related to the values and identities of any cultural group, it can be used as a medium to promote social inclusion in the context of urban multicultural societies. By bringing people together into specific urban sites, food production can be integrated into multifunctional spaces while addressing social, economic and ecological goals. The goal of this research is to assess different approaches to urban agriculture by analysing three existing community gardens located in Newtown, a suburb of Wellington, New Zealand. As a context for developing research, Newtown offers different approaches to urban farming and is really valuable for observing current trends of socialization in diverse and multicultural societies. All three spaces are located on public land owned by Wellington City Council and confined to a small, complex and progressively denser urban area. The developed analysis was focused on social, cultural and physical dimensions, combining community engagement with different techniques of spatial assessment. At the same time, a detailed investigation of each community garden was conducted with comparative analysis methodologies. This multidirectional setting of the analysis was established for extracting from the case studies both specific and typological knowledge. Each site was analysed and categorised under three broad themes: people, space and food. The analysis revealed that all three case studies had really different spatial settings, different approaches to food production and varying profiles of supportive communities. The main differences identified were demographics, values, objectives, internal organization, appropriation, and perception of the space. The community gardens were approached as case studies for developing design research. Following participatory design processes with the different communities, the knowledge gained from the analysis was used for proposing changes in the physical environment. The end goal of the design research was to improve the capacity of the spaces to facilitate social inclusiveness. In order to generate tangible changes, a range of small, strategic and feasible spatial interventions was explored. The smallness of the proposed interventions facilitates implementation by reducing time frames, technical resources, funding needs, and legal processes, working within the community´s own realm. These small interventions are expected to be implemented over time as part of an ongoing collaboration between the different communities, the university, and the local council. The applied research methodology showcases the capacity of universities to develop civic engagement by working with real communities that have concrete needs and face overall threats of disintegration and segregation.

Keywords: community gardening, landscape architecture, participatory design, placemaking, social inclusion

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Authors: Jia H. Wong, Jingli Zhang, Habsah Mohamad, Iswatun H. Abdullah Ripain, Muhammad Bilal, Amelia J. Lloyd, Abdul A. Mohamed Yusoff, Jafri M. Abdullah

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Epilepsy is one of the most common neurological diseases affecting more than 50 million of people worldwide. Epilepsy is a state of recurrent, spontaneous seizures with multiple syndromes and symptoms of different causes of brain dysfunction, prognosis, and treatments; characterized by transient, occasional and stereotyped interruptions of behavior whereby the excitatory-inhibitory activities within the central nervous system (CNS) are thrown out of balance due to various kinds of interferences. The goal of antiepileptic treatment is to enable patients to be free from seizures or to achieve control of seizures through surgical treatment and/or pharmacotherapy. Pharmacotherapy through AED plays an important role especially in countries with epilepsy treatment gap due to costs and availability of health facilities, skills and resources, yet there are about one-third of the people with epilepsy have drug-resistant seizures. Hence, this poses considerable challenges to the healthcare system and the effort in providing cost-effective treatment as well as the search for alternatives to treatment and management of epilepsy. Enhancement of γ-aminobutyric acid (GABA)-mediated inhibitory neurotransmission is one of the key mechanisms of actions of antiepileptic drugs. GABA type > a receptors (GABAAR) are ligand-gated ion channels that mediate rapid inhibitory neurotransmission upon the binding of GABA with a heteropentameric structure forming a central pore that is permeable to the influx of chloride ions in its activated state. The major isoform of GABAA receptors consists of two α1, two β2, and one γ2 subunit. It is the most abundantly expressed combinations in the brain and the most commonly researched through Xenopus laevis oocytes. With the advancing studies on ethnomedicine and traditional treatments using medicinal plants, increasing evidence reveal that spice and herb plants with medicinal properties play an important role in the treatment of ailments within communities across different cultures. Capsaicin is the primary natural capsaicinoid in hot peppers of plant genus Capsicum, consist of an aromatic ring, an amide linkage and a hydrophobic side chain. The study showed that capsaicins conferred neuroprotection in status epilepticus mouse models through anti-ictogenic, hypothermic, antioxidative, anti-inflammatory, and anti-apoptotic actions in a dose-dependent manner. In this study, five capsaicin derivatives were tested for their ability to increase the GABA-induced chloride current on α1β2γ2S of GABAAR expressed on Xenopus laevis oocytes using the method of two-microelectrode voltage clamp. Two of the capsaicin derivatives, IS5 (N-(4-hydroxy-3-methoxybenzyl)-3-methylbutyramide) and IS10 (N-(4-hydroxy-3-methoxybenzyl)-decanamide) at a concentration of 30µM were able to significantly increase the GABA-induced chloride current with p=0.002 and p=0.026 respectively. This study were able to show the enhancement effect of two capsaicin derivatives with moderate length of hydrocarbon chain on this receptor subtype, revealing the promising inhibitory activity of capsaicin derivatives through enhancement of GABA-induced chloride current and further investigations should be carried out to verify its antiepileptic effects in animal models.

Keywords: α1β2γ2 GABAA receptors, α1β2γ2S, antiepileptic, capsaicin derivatives, two-microelectrode voltage clamp, Xenopus laevis oocytes

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Authors: Tugba Altin

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In a time characterized by escalating climate change impacts, communities globally face extreme events with deep-reaching tangible and intangible consequences. At the intersection of these phenomena lies the profound impact on the cultural and emotional connections that individuals forge with their environments. This study casts a spotlight on the Lytton Creek Fire of 2021, showcasing it as an exemplar of both the visible destruction brought by such events and the more covert yet deeply impactful disturbances to place attachment (PA). Defined as the emotional and cognitive bond individuals form with their surroundings, PA is critical in comprehending how such catastrophic events reshape cultural identity and the bond with the land. Against the stark backdrop of the Lytton Creek Fire's devastation, the research seeks to unpack the multilayered dynamics of PA amidst the tangible wreckage and the intangible repercussions such as emotional distress and disrupted cultural landscapes. Delving deeper, it examines how affected populations renegotiate their affiliations with these drastically altered environments, grappling with both the tangible loss of their homes and the intangible challenges to solace, identity, and community cohesion. This exploration is instrumental in the broader climate change narrative, as it offers crucial insights into how these personal-place relationships can influence and shape climate adaptation and recovery strategies. Departing from traditional data collection methodologies, this study adopts an interpretive phenomenological approach enriched by hermeneutic insights and places the experiences of the Lytton community and its co-researchers at its core. Instead of conventional interviews, innovative methods like walking audio sessions and photo elicitation are employed. These techniques allow participants to immerse themselves back into the environment, reviving and voicing their memories and emotions in real-time. Walking audio captures reflections on spatial narratives after the trauma, whereas photo voices encapsulate the intangible emotions, presenting a visual representation of place-based experiences. Key findings emphasize the indispensability of addressing both the tangible and intangible traumas in community recovery efforts post-disaster. The profound changes to the cultural landscape and the subsequent shifts in PA underscore the need for holistic, culturally attuned, and emotionally insightful adaptation strategies. These strategies, rooted in the lived experiences and testimonies of the affected individuals, promise more resonant and effective recovery efforts. The research further contributes to climate change discourse, highlighting the intertwined pathways of tangible reconstruction and the essentiality of emotional and cultural rejuvenation. Furthermore, the use of participatory methodologies in this inquiry challenges traditional research paradigms, pointing to potential evolutionary shifts in qualitative research norms. Ultimately, this study underscores the need for a more integrative approach in addressing the aftermath of environmental disasters, ensuring that both physical and emotional rebuilding are given equal emphasis.

Keywords: place attachment, community recovery, disaster reponse, sensory responses, intangible traumas, visual methodologies

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Authors: L. Salomon, P. Sklenar

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The Andes hold the highest plant species diversity in the world. How this occurred is one of the most intriguing questions in studies addressing the origin and patterning of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as triggers to this spectacular diversity. The Andes is the species-richest area for the biggest genus from the Asteraceae family: Senecio. There, the genus presents an incredible diversity of species, striking growth form variation, and large niche span. Even when some studies tried to disentangle the evolutionary story for some Andean species in Senecio, they obtained partially resolved and low supported phylogenies, as expected for recently radiated groups. The high-throughput sequencing (HTS) approaches have proved to be a powerful tool answering phylogenetic questions in those groups whose evolutionary stories are recent and traditional techniques like Sanger sequencing are not informative enough. Although these tools have been used to understand the evolution of an increasing number of Andean groups, nowadays, their scope has not been applied for Senecio. This project aims to contribute to a better knowledge of the mechanisms shaping the hyper diversity of Senecio in the Andean region, using HTS focusing on Senecio ser. Culcitium (Asteraceae), recently recircumscribed. Firstly, reconstructing a highly resolved and supported phylogeny, and after assessing the role of allopatric differentiation, hybridization, and genome duplication in the diversification of the group. Using the Hyb-Seq approach, combining target enrichment using Asteraceae COS loci baits and genome skimming, more than 100 new accessions were generated. HybPhyloMaker and HybPiper pipelines were used for the phylogenetic analyses, and another pipeline in development (Paralogue Wizard) was used to deal with paralogues. RAxML was used to generate gene trees and Astral for species tree reconstruction. Phyparts were used to explore as first step of gene tree discordance along the clades. Fully resolved with moderated supported trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within the group, some species formed well-supported clades with morphologically related species, while some species would not have exclusive ancestry, in concordance with previous studies using amplified fragment length polymorphism (AFLP) showing geographical differentiation. Discordance between gene trees was detected. Paralogues were detected for many loci, indicating possible genome duplications; ploidy level estimation using flow cytometry will be carried out during the next months in order to identify the role of this process in the diversification of the group. Likewise, TreeSetViz package for Mesquite, hierarchical likelihood ratio congruence test using Concaterpillar, and Procrustean Approach to Cophylogeny (PACo), will be used to evaluate the congruence among different inheritance patterns. In order to evaluate the influence of hybridization and Incomplete Lineage Sorting (ILS) in each resultant clade from the phylogeny, Joly et al.'s 2009 method in a coalescent scenario and Paterson’s D-statistic will be performed. Even when the main discordance sources between gene trees were not explored in detail yet, the data show that at least to some degree, processes such as genome duplication, hybridization, and/or ILS could be involved in the evolution of the group.

Keywords: adaptive radiations, Andes, genome duplication, hybridization, Senecio

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Authors: Munruchi Kaur

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Agarics are the fruiting bodies of the fungi falling under Phylum Basidiomycota of class Agaricomycetes. North Western parts of India which comprises of mighty Himalayas decorated with snow cap mountains, forested areas, grassland and the Gangetic plains with the altitude varying between 196m to 3600m have a huge potential of naturally growing wild agarics. These mushrooms lavishly grow in wet humid weather conditions that prevail in these parts of India during the monsoon which hits in the early June and continue up to mid-October. In this area, a diverse form of mixed vegetation is available which is represented by coniferous and angiospermic trees, shrubs, herbs, epiphytes, parasites, climbers etc. The vegetation, topography and climate of this area is quite favorable for the growth of agarics. Cedrus deodara, Pinus longifolia, P. roxburghii, P. wallichiana, Abies pindrow, A. spectabilis, Picea smithiana, Taxus sp., Rhododendron sp. and Quercus sp. occur in pure formations or as scattered patches or as mixed forests, whereas the Gangetic plains are dominated by the angiospermic trees and shrubs, they commonly occur along roadsides or in conserved areas or are the avenues plantations, common amongst these are Shorea robusta, Dalbergia sissoo, Melia azadirachta, Acacia sp., Ficus benghalensis, Eucalyptus sp. and Butea monosperma. These agarics can be categorized on the basis of the habitat in which they grow they are usually foliocolous, lignicolous, humicolous, coprophilous or termitophilous. A number of fungal forays were undertaken to different parts of North West India from time to time during the monsoon season with an aim to decipher the agarics diversity of this part of India. Along with collecting the various agarics from diverse habitat, the ethnomycological data was also collected along with by interacting with the local inhabitants of those areas. Based upon the ethnomycological data collected over the years, cataloging of the edible and inedible agarics has been done and cultures of such potential edible agarics were raised with an aim to domesticate these selected taxa. With an aim to reduce the local pressure on these natural resources, a low-cost technology was developed to make it available to the public for cultivation. As a result, 104 taxa were found edible such as Amanita hemibapha var. ochracea, A. chepangiana, A. banningiana, A. vaginata, Agrocybe parasitica, Author: Professor & Dean Faculty of Life Sciences Punjabi University, Patiala. Punjab, India [email protected] Agaricus bisporus, A. andrewii, A. campestris var. campestris, A. silvicola, A. subrutilescens, A. bernardii, A. abruptibulbus, A. fuscovelatus, A. brunnescens, A. augustus, A. silvaticus, A. arvensis, Volvariella bakeri, V. terastia, V. bombycina, V. diplasia, Psathyrella candolleana, Volvopluteus gloiocephalus, Russula cyanoxantha, R. atropurpurea, R. aurea, Clitocybe gibba,Lentinus transitus, L. kashmirinus, L. crinitus, L. ligrinus, Lactarius rubrilacteus, Pleurotus sapidus, Pluteus subcervinus, Macrocybe gigantea, etc. Cultures of various taxa viz. Pleurotus sajor-caju, Macrocybe gigantea, Pluteus petasatus and Lentinus tigrinus were raised and a proper protocol for the domestication of Pleurotus sajor-caju, Macrocybe gigantea, and Lentinus tigrinus has been developed using the locally available agro-wastes.

Keywords: Agaric, culture, domestication, edible

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Authors: Amna Tariq Shah

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Amid the pandemic, the contemporary landscape has experienced accelerated growth in small business activities and an expanding digital marketplace, further exacerbating the issue of non-compliance among self-employed individuals through aggressive tax planning and evasion. This research seeks to address these challenges by developing strategic tax policies that promote voluntary compliance and improve taxpayer facilitation. The study employs the innovative MINDSPACE framework to examine three psychosocial factors—tax communication, tax literacy, and shaming—to optimize policy responses, address administrative shortcomings, and ensure adequate revenue collection for public goods and services. Preliminary findings suggest that incomprehensible communication from tax authorities drives individuals to seek alternative, potentially biased sources of tax information, thereby exacerbating non-compliance. Furthermore, the study reveals low tax literacy among Australian and Pakistani respondents, with many struggling to navigate complex tax processes and comprehend tax laws. Consequently, policy recommendations include simplifying tax return filing and enhancing pre-populated tax returns. In terms of shaming, the research indicates that Australians, being an individualistic society, may not respond well to shaming techniques due to privacy concerns. In contrast, Pakistanis, as a collectivistic society, may be more receptive to naming and shaming approaches. The study employs a mixed-method approach, utilizing interviews and surveys to analyze the issue in both jurisdictions. The use of mixed methods allows for a more comprehensive understanding of tax compliance behavior, combining the depth of qualitative insights with the generalizability of quantitative data, ultimately leading to more robust and well-informed policy recommendations. By examining evidence from opposite jurisdictions, namely a developed country (Australia) and a developing country (Pakistan), the study's applicability is enhanced, providing perspectives from two disparate contexts that offer insights from opposite ends of the economic, cultural, and social spectra. The non-comparative case study methodology offers valuable insights into human behavior, which can be applied to other jurisdictions as well. The application of the MINDSPACE framework in this research is particularly significant, as it introduces a novel approach to tax compliance behavior analysis. By integrating insights from behavioral economics, the framework enables a comprehensive understanding of the psychological and social factors influencing taxpayer decision-making, facilitating the development of targeted and effective policy interventions. This research carries substantial importance as it addresses critical challenges in tax compliance and administration, with far-reaching implications for revenue collection and the provision of public goods and services. By investigating the psychosocial factors that influence taxpayer behavior and utilizing the MINDSPACE framework, the study contributes invaluable insights to the field of tax policy. These insights can inform policymakers and tax administrators in developing more effective tax policies that enhance taxpayer facilitation, address administrative obstacles, promote a more equitable and efficient tax system, and foster voluntary compliance, ultimately strengthening the financial foundation of governments and communities.

Keywords: individual tax compliance behavior, psychosocial factors, tax non-compliance, tax policy

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Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

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In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

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Authors: Jessica Ho

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AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

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Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

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Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Mohd Zaimmudin Mohd Zain, Patsy Perry, Lee Quinn

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This study explores how fashion consumers are influenced by fashion bloggers towards pre-purchase decision for online fashion products in a non-Western context. Malaysians rank among the world’s most avid online shoppers, with apparel the third most popular purchase category. However, extant research on fashion blogging focuses on the developed Western market context. Numerous international fashion retailers have entered the Malaysian market from luxury to fast fashion segments of the market; however Malaysian fashion consumers must balance religious and social norms for modesty with their dress style and adoption of fashion trends. Consumers increasingly mix and match Islamic and Western elements of dress to create new styles enabling them to follow Western fashion trends whilst paying respect to social and religious norms. Social media have revolutionised the way that consumers can search for and find information about fashion products. For online fashion brands with no physical presence, social media provide a means of discovery for consumers. By allowing the creation and exchange of user-generated content (UGC) online, they provide a public forum that gives individual consumers their own voices, as well as access to product information that facilitates their purchase decisions. Social media empower consumers and brands have important roles in facilitating conversations among consumers and themselves, to help consumers connect with them and one another. Fashion blogs have become an important fashion information sources. By sharing their personal style and inspiring their followers with what they wear on popular social media platforms such as Instagram, fashion bloggers have become fashion opinion leaders. By creating UGC to spread useful information to their followers, they influence the pre-purchase decision. Hence, successful Western fashion bloggers such as Chiara Ferragni may earn millions of US dollars every year, and some have created their own fashion ranges and beauty products, become judges in fashion reality shows, won awards, and collaborated with high street and luxury brands. As fashion blogging has become more established worldwide, increasing numbers of fashion bloggers have emerged from non-Western backgrounds to promote Islamic fashion styles, such as Hassanah El-Yacoubi and Dian Pelangi. This study adopts a qualitative approach using netnographic content analysis of consumer comments on two famous Malaysian fashion bloggers’ Instagram accounts during January-March 2016 and qualitative interviews with 16 Malaysian Generation Y fashion consumers during September-October 2016. Netnography adapts ethnographic techniques to the study of online communities or computer-mediated communications. Template analysis of the data involved coding comments according to the theoretical framework, which was developed from the literature review. Initial data analysis shows the strong influence of Malaysian fashion bloggers on their followers in terms of lifestyle and morals as well as fashion style. Followers were guided towards the mix and match trend of dress with Western and Islamic elements, for example, showing how vivid colours or accessories could be worked into an outfit whilst still respecting social and religious norms. The blogger’s Instagram account is a form of online community where followers can communicate and gain guidance and support from other followers, as well as from the blogger.

Keywords: fashion bloggers, Malaysia, qualitative, social media

Procedia PDF Downloads 218

Authors: Cátia Gonçalves, Teresa Nunes, Inês Pina, Ana Vicente, C. Alves, Felix Charvet, Daniel Neves, A. Matos

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The production of charcoal relies on rudimentary technologies using traditional brick kilns. Charcoal is produced under pyrolysis conditions: breaking down the chemical structure of biomass under high temperature in the absence of air. The amount of the pyrolysis products (charcoal, pyroligneous extract, and flue gas) depends on various parameters, including temperature, time, pressure, kiln design, and wood characteristics like the moisture content. This activity is recognized for its inefficiency and high pollution levels, but it is poorly characterized. This activity is widely distributed and is a vital economic activity in certain regions of Portugal, playing a relevant role in the management of woody residues. The location of the units establishes the biomass used for charcoal production. The Portalegre district, in the Alto Alentejo region (Portugal), is a good example, essentially with rural characteristics, with a predominant farming, agricultural, and forestry profile, and with a significant charcoal production activity. In this district, a recent inventory identifies almost 50 charcoal production units, equivalent to more than 450 kilns, of which 80% appear to be in operation. A field campaign was designed with the objective of determining the composition of the emissions released during a charcoal production cycle. A total of 30 samples of particulate matter and 20 gas samples in Tedlar bags were collected. Particulate and gas samplings were performed in parallel, 2 in the morning and 2 in the afternoon, alternating the inlet heads (PM₁₀ and PM₂.₅), in the particulate sampler. The gas and particulate samples were collected in the plume as close as the emission chimney point. The biomass (dry basis) used in the carbonization process was a mixture of cork oak (77 wt.%), holm oak (7 wt.%), stumps (11 wt.%), and charred wood (5 wt.%) from previous carbonization processes. A cylindrical batch kiln (80 m³) with 4.5 m diameter and 5 m of height was used in this study. The composition of the gases was determined by gas chromatography, while the particulate samples (PM₁₀, PM₂.₅) were subjected to different analytical techniques (thermo-optical transmission technique, ion chromatography, HPAE-PAD, and GC-MS after solvent extraction) after prior gravimetric determination, to study their organic and inorganic constituents. The charcoal production cycle presents widely varying operating conditions, which will be reflected in the composition of gases and particles produced and emitted throughout the process. The concentration of PM₁₀ and PM₂.₅ in the plume was calculated, ranging between 0.003 and 0.293 g m⁻³, and 0.004 and 0.292 g m⁻³, respectively. Total carbon, inorganic ions, and sugars account, in average, for PM10 and PM₂.₅, 65 % and 56 %, 2.8 % and 2.3 %, 1.27 %, and 1.21 %, respectively. The organic fraction studied until now includes more than 30 aliphatic compounds and 20 PAHs. The emission factors of particulate matter to produce charcoal in the traditional kiln were 33 g/kg (wooddb) and 27 g/kg (wooddb) for PM₁₀ and PM₂.₅, respectively. With the data obtained in this study, it is possible to fill the lack of information about the environmental impact of the traditional charcoal production in Portugal. Acknowledgment: Authors thanks to FCT – Portuguese Science Foundation, I.P. and to Ministry of Science, Technology and Higher Education of Portugal for financial support within the scope of the project CHARCLEAN (PCIF/GVB/0179/2017) and CESAM (UIDP/50017/2020 + UIDB/50017/2020).

Keywords: brick kilns, charcoal, emission factors, PAHs, total carbon

Procedia PDF Downloads 141

Authors: K. Kamal

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Structural sandwich panels with core of Advanced Composites Laminates l Honeycombs / PU-foams are used in aerospace applications and are also fabricated for use now in some civil engineering applications. An all Advanced Composites Foot Over Bridge (FOB) system, designed and developed for pedestrian traffic is one such application earlier, may be cited as an example here. During development stage of this FoB, a profile of its decks was then spurred as a single corrugate sheet core sandwiched between two Glass Fibre Reinforced Plastics(GFRP) flat laminates. Once successfully fabricated and used, these decks did prove suitable also to form other structure on assembly, such as, erecting temporary shelters. Such corrugated sheet core profile sandwiched panels were then also tried using the construction materials but any conventional method of construction only posed certain difficulties in achieving the required core profile monolithically within the sandwiched slabs and hence it was then abended. Such monolithic construction was, however, subsequently eased out on demonstration by dispensing building materials mix through a suitably designed multi-dispenser system attached to a 3D Printer. This study conducted at lab level was thus reported earlier and it did include the fabrication of a 3D printer in-house first as ‘3DcMP’ as well as on its functional operation, some required sandwich core profiles also been 3D-printed out producing panels hardware. Once a number of these sandwich panels in single corrugated sheet core monolithically printed out, panels were subjected to load test in an experimental set up as also their structural behavior was studied analytically, and subsequently, these results were correlated as reported in the literature. In achieving the required more depths and also to exhibit further the stronger and creating sandwiched decks of better structural and mechanical behavior, further more complex core configuration such as stack corrugate sheets core with a flat mid plane was felt to be the better sandwiched core. Such profile remained as an outcome that turns out merely on stacking of two separately printed out monolithic units of single corrugated sheet core developed earlier as above and bonded them together initially, maintaining a different orientation. For any required sequential understanding of the structural behavior of any such complex profile core sandwiched decks with special emphasis to study of the effect in the variation of corrugation orientation in each distinct tire in this core, it obviously calls for an analytical study first. The rectangular,simply supported decks have therefore been considered for analysis adopting the ‘Advanced Composite Technology(ACT), some numerical results along with some fruitful findings were obtained and these are all presented here in this paper. From this numerical result, it has been observed that a mid flat layer which eventually get created monolethically itself, in addition to eliminating the bonding process in development, has been found to offer more effective bending resistance by such decks subjected to UDL over them. This is understood to have resulted here since the existence of a required shear resistance layer at the mid of the core in this profile, unlike other bending elements. As an addendum to all such efforts made as covered above and was published earlier, this unique stack corrugate sheet core profile sandwiched structural decks, monolithically construction with ease at the site itself, has been printed out from a 3D Printer. On employing 3DcMP and using some innovative building construction materials, holds the future promises of such research & development works since all those several aspects of a 3D printing in construction are now included such as reduction in the required construction time, offering cost effective solutions with freedom in design of any such complex shapes thus can widely now be realized by the modern construction industry.

Keywords: advance composite technology(ACT), corrugated laminates, 3DcMP, foot over bridge (FOB), sandwiched deck units

Procedia PDF Downloads 170

Authors: Alberto Fina, Samuele Colonna, Maria del Mar Bernal, Orietta Monticelli, Mauro Tortello, Renato Gonnelli, Julio Gomez, Chiara Novara, Guido Saracco

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Thermally conductive polymer nanocomposites are of high interest for several applications including low-temperature heat recovery, heat exchangers in a corrosive environment and heat management in electronics and flexible electronics. In this paper, the preparation of thermally conductive nanocomposites exploiting graphene-related materials is addressed, along with their thermal characterization. In particular, correlations between 1- chemical and physical features of the nanoflakes and 2- processing conditions with the heat conduction properties of nanocomposites is studied. Polymers are heat insulators; therefore, the inclusion of conductive particles is the typical solution to obtain a sufficient thermal conductivity. In addition to traditional microparticles such as graphite and ceramics, several nanoparticles have been proposed, including carbon nanotubes and graphene, for the use in polymer nanocomposites. Indeed, thermal conductivities for both carbon nanotubes and graphenes were reported in the wide range of about 1500 to 6000 W/mK, despite such property may decrease dramatically as a function of the size, number of layers, the density of topological defects, re-hybridization defects as well as on the presence of impurities. Different synthetic techniques have been developed, including mechanical cleavage of graphite, epitaxial growth on SiC, chemical vapor deposition, and liquid phase exfoliation. However, the industrial scale-up of graphene, defined as an individual, single-atom-thick sheet of hexagonally arranged sp2-bonded carbons still remains very challenging. For large scale bulk applications in polymer nanocomposites, some graphene-related materials such as multilayer graphenes (MLG), reduced graphene oxide (rGO) or graphite nanoplatelets (GNP) are currently the most interesting graphene-based materials. In this paper, different types of graphene-related materials were characterized for their chemical/physical as well as for thermal properties of individual flakes. Two selected rGOs were annealed at 1700°C in vacuum for 1 h to reduce defectiveness of the carbon structure. Thermal conductivity increase of individual GNP with annealing was assessed via scanning thermal microscopy. Graphene nano papers were prepared from both conventional RGO and annealed RGO flakes. Characterization of the nanopapers evidenced a five-fold increase in the thermal diffusivity on the nano paper plane for annealed nanoflakes, compared to pristine ones, demonstrating the importance of structural defectiveness reduction to maximize the heat dissipation performance. Both pristine and annealed RGO were used to prepare polymer nanocomposites, by melt reactive extrusion. Thermal conductivity showed two- to three-fold increase in the thermal conductivity of the nanocomposite was observed for high temperature treated RGO compared to untreated RGO, evidencing the importance of using low defectivity nanoflakes. Furthermore, the study of different processing paremeters (time, temperature, shear rate) during the preparation of poly (butylene terephthalate) nanocomposites evidenced a clear correlation with the dispersion and fragmentation of the GNP nanoflakes; which in turn affected the thermal conductivity performance. Thermal conductivity of about 1.7 W/mK, i.e. one order of magnitude higher than for pristine polymer, was obtained with 10%wt of annealed GNPs, which is in line with state of the art nanocomposites prepared by more complex and less upscalable in situ polymerization processes.

Keywords: graphene, graphene-related materials, scanning thermal microscopy, thermally conductive polymer nanocomposites

Procedia PDF Downloads 263

Authors: Fossarello Maurizio, Mattana Giorgio, Tatti Filippo.

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The most widely performed surgical procedure in Open-Angle Glaucoma (OAG) is trabeculectomy. Although this filtering procedure is extremely effective, surgical failure and postoperative complications are reported. Due to the its invasive nature and possible complications, trabeculectomy is usually reserved, in practice, for patients who are refractory to medical and laser therapy. Recently, a number of micro-invasive surgical techniques (MIGS: Micro-Invasive Glaucoma Surgery), have been introduced in clinical practice. They meet the criteria of micro-incisional approach, minimal tissue damage, short surgical time, reliable IOP reduction, extremely high safety profile and rapid post-operative recovery. Xen45 Gel Implant (Allergan, Dublin, Ireland) is one of the MIGS alternatives, and consists in a porcine gelatin tube designed to create an aqueous flow from the anterior chamber to the subconjunctival space, bypassing the resistance of the trabecular meshwork. In this study we report the results of this technique as a favorable option in the treatment of OAG for its benefits in term of efficacy and safety, either alone or in combination with cataract surgery. This is a retrospective, single-center study conducted in consecutive OAG patients, who underwent Xen45 Gel Stent implantation alone or in combination with phacoemulsification, from October 2018 to June 2019. The primary endpoint of the study was to evaluate the reduction of both IOP and number of antiglaucoma medications at 12 months. The secondary endpoint was to correlate filtering bleb morphology evaluated by means of anterior segment OCT with efficacy in IOP lowering and eventual further procedures requirement. Data were recorded on Microsoft Excel and study analysis was performed using Microsoft Excel and SPSS (IBM). Mean values with standard deviations were calculated for IOPs and number of antiglaucoma medications at all points. Kolmogorov-Smirnov test showed that IOP followed a normal distribution at all time, therefore the paired Student’s T test was used to compare baseline and postoperative mean IOP. Correlation between postoperative Day 1 IOP and Month 12 IOP was evaluated using Pearson coefficient. Thirty-six eyes of 36 patients were evaluated. As compared to baseline, mean IOP and the mean number of antiglaucoma medications significantly decreased from 27,33 ± 7,67 mmHg to 16,3 ± 2,89 mmHg (38,8% reduction) and from 2,64 ± 1,39 to 0,42 ± 0,8 (84% reduction), respectively, at 12 months after surgery (both p < 0,001). According to bleb morphology, eyes were divided in uniform group (n=8, 22,2%), subconjunctival separation group (n=5, 13,9%), microcystic multiform group (n=9, 25%) and multiple internal layer group (n=14, 38,9%). Comparing to baseline, there was no significative difference in IOP between the 4 groups at month 12 follow-up visit. Adverse events included bleb function decrease (n=14, 38,9%), hypotony (n=8, 22,2%) and choroidal detachment (n=2, 5,6%). All eyes presenting bleb flattening underwent needling and MMC injection. The higher percentage of patients that required secondary needling was in the uniform group (75%), with a significant difference between the groups (p=0,03). Xen45 gel stent, either alone or in combination with phacoemulsification, provided a significant lowering in both IOP and medical antiglaucoma treatment and an elevated safety profile.

Keywords: anterior segment OCT, bleb morphology, micro-invasive glaucoma surgery, open angle glaucoma, Xen45 gel implant

Procedia PDF Downloads 140

Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Ling Ai, Ziyu Zhao, Zeyu Zhou, Xiaochen Yang, Heng Zhai, Stuart Holmes

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Optimizing the catalyst layer structure is crucial for enhancing the performance of proton exchange membrane fuel cells (PEMFCs) with low Platinum (Pt) loading. Current works focused on the utilization, durability, and site activity of Pt particles on support, and performance enhancement has been achieved by loading Pt onto porous support with different morphology, such as graphene, carbon fiber, and carbon black. Some schemes have also incorporated cost considerations to achieve lower Pt loading. However, the design of the catalyst layer (CL) structure in the membrane electrode assembly (MEA) must consider the interactions between the layers. Addressing the crucial aspects of water management, low contact resistance, and the establishment of effective three-phase boundary for MEA, multi-walled carbon nanotubes (MWCNTs) are promising CL support due to their intrinsically high hydrophobicity, high axial electrical conductivity, and potential for ordered alignment. However, the drawbacks of MWCNTs, such as strong agglomeration, wall surface chemical inertness, and unopened ends, are unfavorable for Pt nanoparticle loading, which is detrimental to MEA processing and leads to inhomogeneous CL surfaces. This further deteriorates the utilization of Pt and increases the contact resistance. Robust chemical oxidation or nitrogen doping can introduce polar functional groups onto the surface of MWCNTs, facilitating the creation of open tube ends and inducing defects in tube walls. This improves dispersibility and load capacity but reduces length and conductivity. Consequently, a trade-off exists between maintaining the intrinsic properties and the degree of functionalization of MWCNTs. In this work, MWCNTs were modified based on the operational requirements of the MEA from the viewpoint of interlayer interactions, including the search for the optimal degree of oxidation, N-doping, and micro-arrangement. MWCNT were functionalized by oxidizing, N-doping, as well as micro-alignment to achieve lower contact resistance between CL and proton exchange membrane (PEM), better hydrophobicity, and enhanced performance. Furthermore, this work expects to construct a more continuously distributed three-phase boundary by aligning MWCNT to form a locally ordered structure, which is essential for the efficient utilization of Pt active sites. Different from other chemical oxidation schemes that used HNO3:H2SO4 (1:3) mixed acid to strongly oxidize MWCNT, this scheme adopted pure HNO3 to partially oxidize MWCNT at a lower reflux temperature (80 ℃) and a shorter treatment time (0 to 10 h) to preserve the morphology and intrinsic conductivity of MWCNT. The maximum power density of 979.81 mw cm-2 was achieved by Pt loading on 6h MWCNT oxidation time (Pt-MWCNT6h). This represented a 59.53% improvement over the commercial Pt/C catalyst of 614.17 (mw cm-2). In addition, due to the stronger electrical conductivity, the charge transfer resistance of Pt-MWCNT6h in the electrochemical impedance spectroscopy (EIS) test was 0.09 Ohm cm-2, which was 48.86% lower than that of Pt/C. This study will discuss the developed catalysts and their efficacy in a working fuel cell system. This research will validate the impact of low-functionalization modification of MWCNTs on the performance of PEMFC, which simplifies the preparation challenges of CL and contributing for the widespread commercial application of PEMFCs on a larger scale.

Keywords: carbon nanotubes, electrocatalyst, membrane electrode assembly, proton exchange membrane fuel cell

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Authors: Anupama A. P.

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The Malayalam film industry, known as Mollywood, has a rich tradition of storytelling and cultural significance within Indian cinema. Middlebrow films have emerged as a distinct influential category, particularly in the 1980s, with directors like K.G. George, who engaged with female subjectivity and drew inspiration from the ‘women’s cinema’ of the 1950s and 1960s. In recent decades, particularly post-2010, the industry has transformed significantly with a new generation of filmmakers diverging from melodrama and new wave of the past, incorporating advanced technology and modern content. This study examines the evolution and impact of Malayalam middlebrow cinema in the 21st century, focusing on post-2000 films and their influence on contemporary spectator experiences. These films appeal to a wide range of audiences without compromising on their artistic integrity, tackling social issues and personal dramas with thematic and narrative complexity. Historically, middlebrow films in Malayalam cinema have portrayed realism and addressed the socio-political climate of Kerala, blending realism with reflexivity and moving away from traditional sentimentality. This shift is evident in the new generation of Malayalam films, which present a global representation of characters and a modern treatment of individuals. To provide a comprehensive understanding of this evolution, the study analyzes a diverse selection of films such as Kerala Varma Pazhassi Raja (2009), Drishyam (2013), Maheshinte Prathikaaram (2016), Take Off (2017), and Thondimuthalum Driksakshiyum (2017) and Virus (2019) illustrating the broad thematic range and innovative narrative techniques characteristic of this genre. These films exemplify how middlebrow cinema continues to evolve, adapting to changing societal contexts and audience expectations. This research employs a theoretical methodology, drawing on cultural studies and audience reception theory, utilizing frameworks such as Bordwell’s narrative theory, Deleuze’s concept of deterritorialization, and Hall’s encoding/decoding model to analyze the changes in Malayalam middlebrow cinema and interpret the storytelling methods, spectator experience, and audience reception of these films. The findings indicate that Malayalam middlebrow cinema post-2010 offers a spectator experience that is both intellectually stimulating and broadly appealing. This study highlights the critical role of middlebrow cinema in reflecting and shaping societal values, making it a significant cultural artefact within the broader context of Indian and global cinema. By bridging entertainment with thought-provoking narratives, these films engage audiences and contribute to wider cultural discourse, making them pivotal in contemporary cinematic landscapes. To conclude, this study highlights the importance of Malayalam middle-brow cinema in influencing contemporary cinematic tastes. The nuanced and approachable narratives of post-2010 films are posited to assume an increasingly pivotal role in the future of Malayalam cinema. By providing a deeper understanding of Malayalam middlebrow cinema and its societal implications, this study enriches theoretical discourse, promotes regional cinema, and offers valuable insights into contemporary spectator experiences and the future trajectory of Malayalam cinema.

Keywords: Malayalam cinema, middlebrow cinema, spectator experience, audience reception, deterritorialization

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Atefeh Salehipoor

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: 1. Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. 2. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. 3. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. 4. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. 5. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. 6. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension

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Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Simrin Kafle, Ulrika Enemark

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Catastrophic health expenditure (CHE) is a critical issue in low- and middle-income countries like Nepal, exacerbating financial hardship among vulnerable households. This study assesses the effectiveness of Nepal’s National Health Insurance Program (NHIP), launched in 2015, to reduce out-of-pocket (OOP) healthcare costs and mitigate CHE. Conducted in Pokhara Metropolitan City, the study used an analytical cross-sectional design, sampling 1276 households through a two-stage random sampling method. Data was collected via face-to-face interviews between May and October 2023. The analysis was conducted using SPSS version 29, incorporating propensity score matching to minimize biases and create comparable groups of enrolled and non-enrolled households in the NHIP. PSM helped reduce confounding effects by matching households with similar baseline characteristics. Additionally, a doubly robust methodology was employed, combining propensity score adjustment with regression modeling to enhance the reliability of the results. This comprehensive approach ensured a more accurate estimation of the impact of NHIP enrollment on CHE. Among the 1276 samples, 534 households (41.8%) were enrolled in NHIP. Of them, 84.3% of households renewed their insurance card, though some cited long waiting times, lack of medications, and complex procedures as barriers to renewal. Approximately 57.3% of households reported known diseases before enrollment, with 49.8% attending routine health check-ups in the past year. The primary motivation for enrollment was encouragement from insurance employees (50.2%). The data indicates that 12.5% of enrolled households experienced CHE versus 7.5% among non-enrolled. Enrollment into NHIP does not contribute to lower CHE (AOR: 1.98, 95% CI: 1.21-3.24). Key factors associated with increased CHE risk were presence of non-communicable diseases (NCDs) (AOR: 3.94, 95% CI: 2.10-7.39), acute illnesses/injuries (AOR: 6.70, 95% CI: 3.97-11.30), larger household size (AOR: 3.09, 95% CI: 1.81-5.28), and households below the poverty line (AOR: 5.82, 95% CI: 3.05-11.09). Other factors such as gender, education level, caste/ethnicity, presence of elderly members, and under-five children also showed varying associations with CHE, though not all were statistically significant. The study concludes that enrollment in the NHIP does not significantly reduce the risk of CHE. The reason for this could be inadequate coverage, where high-cost medicines, treatments, and transportation costs are not fully included in the insurance package, leading to significant out-of-pocket expenses. We also considered the long waiting time, lack of medicines, and complex procedures for the utilization of NHIP benefits, which might result in the underuse of covered services. Finally, gaps in enrollment and retention might leave certain households vulnerable to CHE despite the existence of NHIP. Key factors contributing to increased CHE include NCDs, acute illnesses, larger household sizes, and poverty. To improve the program’s effectiveness, it is recommended that NHIP benefits and coverage be expanded to better protect against high healthcare costs. Additionally, simplifying the renewal process, addressing long waiting times, and enhancing the availability of services could improve member satisfaction and retention. Targeted financial protection measures should be implemented for high-risk groups, and efforts should be made to increase awareness and encourage routine health check-ups to prevent severe health issues that contribute to CHE.

Keywords: catastrophic health expenditure, effectiveness, national health insurance program, Nepal

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Authors: Pauliina Haustein

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Improvisation was part of Western classical concert culture and performers’ skill sets until early 20th century. Historical accounts, as well as recent studies, indicate that improvisatory elements in the programme may contribute specifically towards the audiences’ experience of enhanced emotional engagement during the concert. This paper presents findings from the author’s artistic practice research, which explored re-introducing improvisation to Western classical performance practice as a musician (cellist and ensemble partner/leader). In an investigation of four concert cycles, the performer-researcher sought to gain solo and chamber music improvisation techniques (both related to and independent of repertoire), conduct ensemble improvisation rehearsals, design concerts with an improvisatory approach, and reflect on interactions with audiences after each concert. Data was collected through use of reflective diary, video recordings, measurement of sound parameters, questionnaires, a focus group, and interviews. The performer’s empirical experiences and findings from audience research components were juxtaposed and interrogated to better understand the (1) rehearsal and planning processes that enable improvisatory elements to return to Western classical concert experience and (2) the emotional experience and type of engagement that occur throughout the concert experience for both performer and audience members. This informed the development of a concert model, in which a programme of solo and chamber music repertoire and improvisations were combined according to historically evidenced performance practice (including free formal solo and ensemble improvisations based on audience suggestions). Inspired by historical concert culture, where elements of risk-taking, spontaneity, and audience involvement (such as proposing themes for fantasies) were customary, this concert model invited musicians to contribute to the process personally and creatively at all stages, from programme planning, and throughout the live concert. The type of democratic, personal, creative, and empathetic collaboration that emerged, as a result, appears unique in Western classical contexts, rather finding resonance in jazz ensemble, drama, or interdisciplinary settings. The research identified features of ensemble improvisation, such as empathy, emergence, mutual engagement, and collaborative creativity, that became mirrored in audience’s responses, generating higher levels of emotional engagement, empathy, inclusivity, and a participatory, co-creative experience. It appears that duringimprovisatory moments in the concert programme, audience members started feeling more like active participants in za\\a creative, collaborative exchange and became stakeholders in a deeper phenomenon of meaning-making and narrativization. Examining interactions between all involved during the concert revealed that performer-audience impulse exchange occurred on multiple levels of awareness and seemed to build upon each other, resulting in particularly strong experiences of both performer and audience’s engagement. This impact appeared especially meaningful for audience members who were seldom concertgoers and reported little familiarity with classical music. The study found that re-introducing improvisatory elements to Western classical concert programmes has strong potential in increasing audience’s emotional engagement with the musical performance, enabling audience members to connect more personally with the individual performers, and in reaching new-to-classical-music audiences.

Keywords: artistic research, audience engagement, audience experience, classical improvisation, ensemble improvisation, emotional engagement, improvisation, improvisatory approach, musical performance, practice research

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