Search results for: teaching report writing for innovative learning

Authors: Ione Loots, Marco van Dijk, Jay Bhagwan

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Historically, South Africa had various small-scale hydropower installations in remote areas that were not incorporated in the national electricity grid. Unfortunately, in the 1960s most of these plants were decommissioned when Eskom, the national power utility, rapidly expanded its grid and capability to produce cheap, reliable, coal-fired electricity. This situation persisted until 2008, when rolling power cuts started to affect all citizens. This, together with the rising monetary and environmental cost of coal-based power generation, has sparked new interest in small-scale hydropower development, especially in remote areas or at locations (like wastewater treatment works) that could not afford to be without electricity for long periods at a time. Even though South Africa does not have the same, large-scale, hydropower potential as some other African countries, significant potential for micro- and small-scale hydropower is hidden in various places. As an example, large quantities of raw and potable water are conveyed daily under either pressurized or gravity conditions over large distances and elevations. Due to the relative water scarcity in the country, South Africa also has more than 4900 registered dams of varying capacities. However, institutional capacity and skills have not been maintained in recent years and therefore the identification of hydropower potential, as well as the development of micro- and small-scale hydropower plants has not gained significant momentum. An assessment model and decision support system for low head hydropower development has been developed to assist designers and decision makers with first-order potential analysis. As a result, various potential sites were identified and many of these sites were situated at existing infrastructure like weirs, barrages or pipelines. One reason for the specific interest in existing infrastructure is the fact that capital expenditure could be minimized and another is the reduced negative environmental impact compared to greenfield sites. This paper will explore the case study of retrofitting an unconventional and innovative hydropower plant to the outlet of a wastewater treatment works in South Africa.

Keywords: low head hydropower, retrofitting, small-scale hydropower, wastewater treatment works

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Authors: J. C. Moctezuma, V. Breña-Medina, Jose Luis Nunez-Yanez, Joseph P. McGeehan

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In this work we make a bifurcation analysis for a single compartment representation of Traub model, one of the most important conductance-based models. The analysis focus in two principal parameters: current and leakage conductance. Study of stable and unstable solutions are explored; also Hop-bifurcation and frequency interpretation when current varies is examined. This study allows having control of neuron dynamics and neuron response when these parameters change. Analysis like this is particularly important for several applications such as: tuning parameters in learning process, neuron excitability tests, measure bursting properties of the neuron, etc. Finally, a hardware implementation results were developed to corroborate these results.

Keywords: Traub model, Pinsky-Rinzel model, Hopf bifurcation, single-compartment models, bifurcation analysis, neuron modeling

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Authors: Muhammad Zafar Khan, Babar Khan, Muhammad Saeed Awan, Farida Begum

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Livestock depredation has greater significance in pastoral societies like Himalaya-Karakoram-Hindu Kush mountain ranges. The dynamics of depredation by large predators (snow leopard and wolf) and its implications for conservation and livelihoods of local people was investigated by household surveys in Hushey valley of Central Karakoram National Park, Pakistan. We found that, during five years (2008-12) 90% of the households in the valley had lost their livestock to snow leopard and wolf, accounting for 4.3% of the total livestock holding per year. On average each household had to bear a loss of 0.8 livestock head per year, equivalent to Pak Rupees 9,853 (US$ 101), or 10% of the average annual cash income. Majority of the predation incidences occurred during late summer in alpine pastures, mostly at night when animals were not penned properly. The prey animals in most of the cases were females or young ones. Of the total predation incidences, 60% were attributed to snow leopard, 37% to wolf, while in 3% the predator was unknown. The fear of snow leopard is greater than that of wolf. As immediate response on predation, majority of the local people (64%, n=99) preferred to report the case to their village conservation committee, 32% had no response while only 1% tended to kill the predator. The perceived causes of predation were: poor guarding practices (77%); reduction in wild prey (13%) and livestock being the favourite food of predators (10%). The most preferred strategies for predator management, according to the respondents were improved and enhanced guarding of livestock (72%), followed by increasing wild prey (18%) and lethal control (10%). To strike a balance between predator populations and pastoral livelihoods, better animal husbandry practices should be promoted including: improved guarding through collective hiring of skilled shepherds; corral improvement and use of guard dogs.

Keywords: Panthera unica, Canis lupus, Karakoram, human-carnivore conflict, predation

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Anum Obaid, Iman Fatima, Wanisha Feroz, Haleema Imran, Hammad Tariq

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In Pakistan, the health of unmarried women over thirty is an emerging public health concern due to its increasing prevalence. Achieving the Sustainable Development Goals (SDGs) requires addressing nutrition and public health issues. This research investigates these goals through the lens of nutrition and public health, specifically examining the challenges faced by unmarried women over thirty in Faisalabad, Pakistan. According to a recent United Nations report, there are 10 million unmarried women over the age of 35 in Pakistan. The United Nations defines health as "a state of complete physical, mental, and social well-being, and not merely the absence of disease or infirmity." Being unmarried and under constant societal pressure profoundly influences the dietary behaviors and nutritional status of these women, affecting their overall health, including physical, mental, and social well-being. A qualitative research approach was employed, involving interviews with both unmarried and married women over thirty. This research examines how marital status influences dietary practices, nutritional status, mental and social health, and their subsequent impacts. Factors such as physical health, mental and emotional status, societal pressure, social health, economic independence, and decision-making power were analyzed to understand the effect of singleness on overall wellness. Findings indicated that marital status significantly affects the dietary patterns and nutritional practices among women in Faisalabad. It was also revealed that unmarried women experienced more stress and had a less optimistic mindset compared to married women, due to loneliness or the absence of a spouse in their lives. Nutritional knowledge varied across marital status, impacting the overall health triangle, including physical, mental, and social health. Understanding these dynamics is crucial for developing targeted interventions to improve nutritional outcomes and overall health among unmarried women in Faisalabad. This study highlights the importance of fostering supportive environments and raising awareness about the health needs of unmarried women over thirty to enhance their overall well-being.

Keywords: health triangle, unmarried woman over thirty, socio-cultural barriers, women’s health

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Authors: Tulika Malviya, Ritesh Chandra Shukla, Praveen Kumar Tandon

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Traditional methods of synthesis are hazardous for the environment and need nature friendly processes for the treatment of industrial effluents and contaminated water. Use of plant parts for the synthesis provides an efficient alternative method. In this paper, we report an ecofriendly and nonhazardous biobased method to prepare zerovalent iron nanoparticles (ZVINPs) using the liquor of commercially available tea. Tea liquor as the reducing agent has many advantages over other polymers. Unlike other polymers, the polyphenols present in tea extract are nontoxic and water soluble at room temperature. In addition, polyphenols can form complexes with metal ions and thereafter reduce the metals. Third, tea extract contains molecules bearing alcoholic functional groups that can be exploited for reduction as well as stabilization of the nanoparticles. Briefly, iron nanoparticles were prepared by adding 2.0 g of montmorillonite K10 (MMT K10) to 5.0 mL of 0.10 M solution of Fe(NO3)3 to which an equal volume of tea liquor was then added drop wise over 20 min with constant stirring. The color of the mixture changed from whitish yellow to black, indicating the formation of iron nanoparticles. The nanoparticles were adsorbed on montmorillonite K10, which is safe and aids in the separation of hazardous arsenic species simply by filtration. Particle sizes ranging from 59.08±7.81 nm were obtained which is confirmed by using different instrumental analyses like IR, XRD, SEM, and surface area studies. Removal of arsenic was done via batch adsorption method. Solutions of As(III) of different concentrations were prepared by diluting the stock solution of NaAsO2 with doubly distilled water. The required amount of in situ prepared ZVINPs supported on MMT K10 was added to a solution of desired strength of As (III). After the solution had been stirred for the preselected time, the solid mass was filtered. The amount of arsenic [in the form of As (V)] remaining in the filtrate was measured using ion chromatograph. Stirring of contaminated water with zerovalent iron nanoparticles supported on montmorillonite K10 for 30 min resulted in up to 99% removal of arsenic as As (III) from its solution at both high and low pH (2.75 and 11.1). It was also observed that, under similar conditions, montmorillonite K10 alone provided only <10% removal of As(III) from water. Adsorption at low pH with precipitation at higher pH has been proposed for As(III) removal.

Keywords: arsenic removal, montmorillonite K10, tea liquor, zerovalent iron nanoparticles

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Vichai Tienthavorn

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Background: Recently, the patients of non-communicable diseases (NCDs) are increasing in Thailand; especially hypertension and diabetes. Hypertension and Diabetes patients were found to be of 3.7 million in 2008. The varieties of human behaviors have been extensively changed in health. Hence, Thai Government has a policy to reduce NCDs. Generally, primary care plays an important role in treatment using medical process. However, NCDs patients have not been decreased. Objectives: This study not only reduce the patient and mortality rate but also increase the quality of life, could apply in different areas and propose to be the national policy, effectively for a long term operation. Methods: Here we report that primary health care (PHC), which is a primary process to screening, rapidly seek the person's risk. The screening tool of the study was Vichai's 7 color balls model, the medical education tool to transfer knowledge from student health team to community through health volunteers, creating community engagement in terms of social participation. It was found that people in community were realized in their health and they can evaluate the level of risk using this model. Results: Projects implementation (2015) in Nong Lom Health Center in Phayao (target group 15-65 years, 2529); screening hypertension coveraged 99.01%, risk group (light green) was decreased to normal group (white) from 1806 to 1893, significant severe patient (red) was decreased to moderate (orange) from 10 to 5. Health Program in behaving change with best practice of 3Es (Eating, Exercise, Emotion) and 3Rs (Reducing tobacco, alcohol, obesity) were applied in risk group; and encourage strictly medication, investigation in severe patient (red). Conclusion: This is the first demonstration of knowledge transfer to community engagement by student, which is the sustainable education in PHC.

Keywords: non-communicable disease, surveillance control and prevention systems, community engagement, primary health care

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Authors: Rafiqul Hasan, A. S. M. Tanim Anwar, Mohammad Azizul Hakim

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Background: Chronic kidney disease (CKD) is a major public health problem that continues to increase in prevalence globally. The prevalence of chronic kidney disease is increasing day by day in low to middle income countries (LMICs). People living in LMICs have the highest need for renal replacement therapy (RRT) despite they have lowest access to various modalities of treatment. As continuous ambulatory peritoneal dialysis (CAPD) does not require advanced technologies, very much infrastructure, dialysis staff support, it should be an ideal form of RRT in LMICs, particularly for those living in remote areas. To authors knowledge there was scarcity of data regarding CAPD performance in remote area of Bangladesh. This study was aimed to report the characteristics and outcomes of CAPD in ESRD patients lived in least developed area of Bangladesh. Methods: This prospective study was conducted in Cox’sbazar Medical College Hospital, Cox’sbazar and Parkview hospital Ltd, Chattogram, Bangladesh. Data were collected by questionnaire from the patients of any age with end-stage renal disease (ESRD) who underwent CAPD in 2018–2021. The baseline characteristics, PD-related complication as well as patient and technique survivals were analyzed. Results: Out of 31 patients who underwent CAPD, 18 (58%) were male on the age range of 15–79 years. The mean follow-up duration was 18 months. Mortality was inversely related with the EF of echocardiography. The peritonitis rate was 0.48 episodes per patient per year. The 1, 3 and 4-year patient survival rates were 64.34% (95% CI = 52.5–81.5), 23.79% (95% CI = 17.9 – 57.4) and 3.22% (95% CI = 31.2–77.5) respectively. Conclusions: In this study, CAPD performance was poorer than usual reference. Cardiac compromised patient and inappropriate dwell might be the main contributing factors behind this scenario. The peritonitis rate was nearly similar to that of developed countries. CAPD was cost effective than HD in remote area. Some accessible measures may be taken to make CAPD a more acceptable RRT modality with improved outcomes in poor socioeconomic backgrounds.

Keywords: dialysis cost, peritoneal dialysis, peritonitis, CAPD, least developed area, remote area, Bangladesh

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Xi Wang, Yoshio Bando

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Lithium-ion batteries (LIBs) can deliver high levels of energy storage density and offer long operating lifetimes, but their power density is too low for many important applications. Therefore, we developed some new strategies and fabricated novel electrodes for fast Li transport and its facile synthesis including N-doped graphene-SnO2 sandwich papers, bicontinuous nanoporous Cu/Li4Ti5O12 electrode, and binder-free N-doped graphene papers. In addition, by using advanced in-TEM, STEM techniques and the theoretical simulations, we systematically studied and understood their storage mechanisms at the atomic scale, which shed a new light on the reasons of the ultrafast lithium storage property and high capacity for these advanced anodes. For example, by using advanced in-situ TEM, we directly investigated these processes using an individual CuO nanowire anode and constructed a LIB prototype within a TEM. Being promising candidates for anodes in lithium-ion batteries (LIBs), transition metal oxide anodes utilizing the so-called conversion mechanism principle typically suffer from the severe capacity fading during the 1st cycle of lithiation–delithiation. Also we report on the atomistic insights of the GN energy storage as revealed by in situ TEM. The lithiation process on edges and basal planes is directly visualized, the pyrrolic N "hole" defect and the perturbed solid-electrolyte-interface (SEI) configurations are observed, and charge transfer states for three N-existing forms are also investigated. In situ HRTEM experiments together with theoretical calculations provide a solid evidence that enlarged edge {0001} spacings and surface "hole" defects result in improved surface capacitive effects and thus high rate capability and the high capacity is owing to short-distance orderings at the edges during discharging and numerous surface defects; the phenomena cannot be understood previously by standard electron or X-ray diffraction analyses.

Keywords: in-situ TEM, STEM, advanced anode, lithium-ion batteries, storage mechanism

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Authors: P. Annapurna, Cecil Ross, Sudhir Krishna, Sweta Srivastava

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Irradiation plays a pivotal role in cervical cancer treatment, however some tumors exhibit resistance to therapy while some exhibit relapse, due to better repair and enhanced resistance mechanisms operational in their cells. The present study aims to understand the signaling mechanism operational in resistance phenotype and in the present study we report the role of Rho GTPase associated protein kinase (ROCK) signaling in cervical carcinoma radio-resistance. ROCK signaling has been implicated in several tumor progressions and is important for DNA repair. Irradiation of spheroid cultures of SiHa cervical carcinoma derived cell line at 6Gy resulted in generation of resistant cells in vitro which had better clonogenic abilities and formed larger and more colonies, in soft agar colony formation assay, as compared to the non-irradiated cells. These cells also exhibited an enhanced motility phenotype. Cell cycle profiling showed the cells to be blocked in G2M phase with enhanced pCDC2 levels indicating onset of possible DNA repair mechanism. Notably, 3 days post-irradiation, irradiated cells showed increased ROCK2 translocation to the nucleus with enhanced protein expression as compared to the non-irradiated cells. Radio-sensitization of the resistant cells was enhanced using Y27632, an inhibitor to ROCK signaling. The treatment of resistant cells with Y27632 resulted in increased cell death upon further irradiation. This observation has been confirmed using inhibitory antibodies to ROCK1/2. Result show that both ROCK1/2 have a functional contribution in radiation resistance of cervical cancer cells derived from cell lines. Interestingly enrichment of stem like cells (Hoechst negative cells) was also observed upon irradiation and these cells were markedly sensitive to Y27632 treatment. Our results thus suggest the role of ROCK signaling in radio-resistance in cervical carcinoma. Further studies with human biopsies, mice models and mechanistic of ROCK signaling in the context of radio-resistance will clarify the role of this molecule further and allow for therapeutics development.

Keywords: cervical carcinoma, radio-resistance, ROCK signaling, cancer treatment

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Authors: Juan Francisco Reinoso Gordo, Francisco Javier Ariza-López, José Rodríguez Avi, Domingo Barrera Rosillo

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The evaluation of the quality of a data product is based on the comparison of the product with a reference of greater accuracy. In the case of MDE data products, quality assessment usually focuses on positional accuracy and few studies consider other terrain characteristics, such as slope and orientation. The proposal that is made consists of evaluating the similarity of two DEMs (a product and a reference), through the joint analysis of the distribution functions of the variables of interest, for example, elevations, slopes and orientations. This is a multivariable approach that focuses on distribution functions, not on single parameters such as mean values or dispersions (e.g. root mean squared error or variance). This is considered to be a more holistic approach. The use of the Kolmogorov-Smirnov test is proposed due to its non-parametric nature, since the distributions of the variables of interest cannot always be adequately modeled by parametric models (e.g. the Normal distribution model). In addition, its application to the multivariate case is carried out jointly by means of a single test on the convolution of the distribution functions of the variables considered, which avoids the use of corrections such as Bonferroni when several statistics hypothesis tests are carried out together. In this work, two DEM products have been considered, DEM02 with a resolution of 2x2 meters and DEM05 with a resolution of 5x5 meters, both generated by the National Geographic Institute of Spain. DEM02 is considered as the reference and DEM05 as the product to be evaluated. In addition, the slope and aspect derived models have been calculated by GIS operations on the two DEM datasets. Through sample simulation processes, the adequate behavior of the Kolmogorov-Smirnov statistical test has been verified when the null hypothesis is true, which allows calibrating the value of the statistic for the desired significance value (e.g. 5%). Once the process has been calibrated, the same process can be applied to compare the similarity of different DEM data sets (e.g. the DEM05 versus the DEM02). In summary, an innovative alternative for the comparison of DEM data sets based on a multinomial non-parametric perspective has been proposed by means of a single Kolmogorov-Smirnov test. This new approach could be extended to other DEM features of interest (e.g. curvature, etc.) and to more than three variables

Keywords: data quality, DEM, kolmogorov-smirnov test, multivariate DEM comparison

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Authors: Haider Javed Uppal, Javed Yunas Uppal

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In today's globalized world, it is necessary to develop a form of music that is able to evoke equal emotional responses among people from diverse cultural backgrounds. Indigenous cultures throughout history have developed their own music cognition, specifically in terms of the connections between music and mood. With the advancements in artificial intelligence technologies, it has become possible to analyze and categorize music features such as timbre, harmony, melody, and rhythm and relate them to the resulting mood effects experienced by listeners. This paper presents a model that utilizes a screenshot translator to convert music from different origins into waveforms, which are then analyzed using machine learning and information retrieval techniques. By connecting these waveforms with Thayer's matrix of moods, a mood classifier has been developed using fuzzy logic algorithms to determine the emotional impact of different types of music on listeners from various cultures.

Keywords: cognition, world music, artificial intelligence, Thayer’s matrix

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Authors: Florence Awde

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In 2023, it was expected 350 parents in Arizona would have a child receive a cancer diagnosis (Welcome Arizona Cancer Foundation For Children, n.d.). The news of a child’s diagnosis with cancer can be overwhelming and confusing, especially for those lucky enough to lack a personal tie to the disease that takes approximately 1800 children’s lives each year in the United States (Deegan et al., n.d.). A parent’s beliefs, attitudes, and understandings surrounding cancer are vital for medical staff to provide adequate and culturally competent care for each patient, especially across cultural and ethnic lines in regions housing multicultural populations. Arizona's cultural/linguistic mosaic houses many White and Latino populations and English and Spanish speakers. Variations in insurance coverage, from those insured through public insurance programs (e.g., Medicaid) or private insurance plans (e.g., employee-sponsored insurance) versus those uninsured, also factor into health-seeking attitudes and behaviors. To further understand parental attitudes, understandings, and beliefs towards childhood cancer, 22 parents (11 of Latino ethnicity, 11 of White ethnicity) were interviewed on these facets of childhood cancer, despite 21 of the 22 never having a child receive a cancer diagnosis. The exploration of these perceptions across ethnic lines revealed a higher report of fear-orientated beliefs amongst Latino parents--hypothesized to be rooted in the starkly contrasting lack of belief in the possibility of recovering for children with cancer, compared to their white counterparts who displayed more optimism in the recovery process. Further, this study’s results lay the foundation for future scholarship to explore avenues of information dispersal to Latino parents that correct misconceptions of health outcomes and enable earlier intervention to be possible, ultimately correlating to better health and treatment outcomes by increasing parental health literacy rates for childhood cancer in the Phoenix Metropolitan.

Keywords: Childhood Cancer, Parental Beliefs, Parental Attitudes, Parental Understandings, Phoenix Metropolitan, Culturally Competent Care, Health Disparities, Health Inequities

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Authors: Girish Prayag, Wantanee Suntikul, Elizabeth Agyeiwaah

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Current research on dark tourism largely follows residents’ perspectives with limited evaluations of tourists’ experiences. Unravelling the case of a dark heritage site in Elmina, Ghana, this paper develops a theoretical model to understand the relationships among four constructs namely, motivation, tourism impacts, place attachment, and satisfaction. Based on a sample of 414 domestic tourists, PLS-SEM confirmed several relationships and inter-relationships among the four constructs. For example, motivation had a positive relationship with perceptions of positive and negative tourism impacts suggesting that the more tourists were motivated to visit the site for cultural/learning experiences, the more positive and negative tourism impacts they perceived. Implications for dark tourism and heritage site management are offered.

Keywords: dark tourism, motivation, place attachment, tourism impacts

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Authors: Mubashra Khalid, Saadia Amir

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This study initiated to explore the empirical relationship between psychological effects of economic recession on the educated youth in Pakistan. The diminishing economic resources during recession can create certain psychological consequences on the physical and cognitive aspects of the individuals. It may generate symptoms like aggression, depression, anxiety, frustration, stress and physical health related problems among the young generation. The sample of the study was consisted of 300 students belonging to six public sector universities of the Punjab province of Pakistan. Two hypotheses were advanced in this study regarding the relationship between recession and its effects on educated youth. The findings of the research represent that a significant relationship exists between decrease in employment opportunities and growing rate of aggression among educated youth and a significant association was found between economic instability and its influence on the learning abilities of the students during recession.

Keywords: psychological effects, recession, educated youth

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Authors: Para Jansuwan, Kerstin K. Zander

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Most people in rural Thailand still depend on agriculture. The rural areas are undergoing changes in their demographic structures with an increasing older population, out migration of younger people and a shift away from work in the agricultural sector towards manufacturing and service provisioning. These changes may lead to a decline in agricultural productivity and food insecurity. Our research aims to examine perceptions of older farmers on how rural demographic change affects them, to investigate how farmers may change their agricultural practices to cope with their ageing and to explore the factors affecting these changes, including the opportunities and challenges arising from them. The data were collected through a household survey with 368 farmers in the Prachin Buri province in central Thailand, the main area for agricultural production. A series of binomial logistic regression models were applied to analyse the data. We found that most farmers suffered from age-related diseases, which compromised their working capacity. Most farmers attempted to reduce labour intense work, by either stopping farming through transferring farmland to their children (41%), stopping farming by giving the land to the others (e.g., selling, leasing out) (28%) and continuing farming with making some changes (e.g., changing crops, employing additional workers) (24%). Farmers’ health and having a potential farm successor were positively associated with the probability of stopping farming by transferring the land to the children. Farmers with a successor were also less likely to stop farming by giving the land to the others. Farmers’ age was negatively associated with the likelihood of continuing farming by making some changes. The results show that most farmers base their decisions on the hope that their children will take over the farms, and that without successor, farmers lease out or sell the land. Without successor, they also no longer invest in expansion and improvement of their farm production, especially adoption of innovative technologies that could help them to maintain their farm productivity. To improve farmers’ quality of life and sustain their farm productivity, policies are needed to support the viability of farms, the access to a pension system and the smooth and successful transfer of the land to a successor of farmers.

Keywords: rural demographic change, older farmer, stopping farming, continuing farming, health and age, farm successor, Thailand

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Authors: Jin-Hyeong Park, Hong-Seok Kim, Jin-Hyeok Yim, Young-Ji Kim, Dong-Hyeon Kim, Jung-Whan Chon, Kun-Ho Seo

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Salmonella contamination in chicken samples can cause major health problems in humans. However, not only the effects of antibiotic treatment during growth but also the impacts of poultry slaughter line on the prevalence of Salmonella in final chicken meat sold to consumers are unknown. In this study, we compared the isolation rates and antimicrobial resistance of Salmonella between antibiotic-free, conventional, conventional Korean native retail chicken meat samples and clonal divergence of Salmonella isolates by multilocus sequence typing. In addition, the distribution of extended-spectrum β-lactamase (ESBL) genes in ESBL-producing Salmonella isolates was analyzed. A total of 72 retail chicken meat samples (n = 24 antibiotic-free broiler [AFB] chickens, n = 24 conventional broiler [CB] chickens, and n = 24 conventional Korean native [CK] chickens) were collected from local retail markets in Seoul, South Korea. The isolation rates of Salmonella were 66.6% in AFB chickens, 45.8% in CB chickens, and 25% in CK chickens. By analyzing the minimum inhibitory concentrations of β -lactam antibiotics with the disc-diffusion test, we found that 81.2% of Salmonella isolates from AFB chickens, 63.6% of isolates from CB chickens, and 50% of isolates from CK chickens were ESBL producers; all ESBL-positive isolates had the CTX-M-15 genotype. Interestingly, all ESBL-producing Salmonella were revealed as ST16 by multilocus sequence typing. In addition, all CTX-M-15-positive isolates had the genetic platform of blaCTX-M gene (IS26-ISEcp1-blaCTX-M-15-IS903), to the best of our knowledge, this is the first report in Salmonella around the world. The Salmonella ST33 strain (S. Hadar) isolated in this study has never been reported in South Korea. In conclusion, our findings showed that antibiotic-free retail chicken meat products were also largely contaminated with ESBL-producing Salmonella and that their ESBL genes and genetic platforms were the same as those isolated from conventional retail chicken meat products.

Keywords: antibiotic-free poultry, conventional poultry, multilocus sequence typing, extended-spectrum β-lactamase, antimicrobial resistance

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Authors: Stefanie Ficht, Lukas Schübel, Magdalena Kleybolte, Markus Eblenkamp, Jana Steger, Dirk Wilhelm, Petra Mela

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Although 3D printing as transformative technology has become of increasing interest in the medical field and the demand for biodegradable polymers has developed to a considerable extent, there are only a few additively manufactured, biodegradable implants on the market. Additionally, the sterilization of such implants and its side effects on degradation have still not been sufficiently studied. Within this work, thermosensitive poly p-dioxanone (PPDO) samples were printed with fused filament fabrication (FFF) and investigated. Subsequently, H₂O₂ plasma and gamma radiation were used as low-temperature sterilization techniques and compared among each other and the control group (no sterilization). In order to assess the effect of different sterilization on the degradation behavior of PPDO, the samples were immersed in phosphate-buffered solution (PBS) over 28 days, and surface morphology, thermal properties, molecular weight, inherent viscosity, and mechanical properties were examined at regular time intervals. The study demonstrates that PPDO was printed with great success and that thermal properties, molecular weight (Mw), and inherent viscosity (IV) were not significantly affected by the printing process itself. H₂O₂ plasma sterilization did not significantly harm the thermosensitive polymer, while gamma radiation lowered IV and Mw statistically significantly compared to the control group (p < 0.001). During immersion in PBS, a decrease in Mw and mechanical strength occurred for all samples. However, gamma sterilized samples were affected to a much higher extent compared to the two other sample groups both in final values and timeline. This was confirmed by scanning electron microscopy showing no changes of surface morphology of (non-sterilized) control samples, first microcracks appearing on plasma sterilized samples after two weeks while being present on gamma sterilized samples already immediately after radiation to then further deteriorate over immersion duration. To conclude, we demonstrated that FFF and H₂O₂ plasma sterilization are well suited for processing thermosensitive, biodegradable polymers used for the development of innovative short-term medical applications.

Keywords: additive manufacturing, sterilization, biodegradable, thermosensitive, medical application

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Authors: Kawinphat Lertpongmanee

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The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Krzysztof Pomorski

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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: Uliana N. Tumanova, Viacheslav M. Lyapin, Vladimir G. Bychenko, Alexandr I. Shchegolev, Gennady T. Sukhikh

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It is well known that the gas formed as a result of postmortem decomposition of tissues can be detected already 24-48 hours after death. In addition, the conditions of keeping and storage of the corpse (temperature and humidity of the environment) significantly determine the rate of occurrence and development of posthumous changes. The presence of sepsis is accompanied by faster postmortem decomposition and decay of the organs and tissues of the body. The presence of gas in the vessels and cavities can be revealed fully at postmortem CT. Radiologists must certainly report on the detection of intraorganic or intravascular gas, wich was detected at postmortem CT, to forensic experts or pathologists before the autopsy. This gas can not be detected during autopsy, but it can be very important for establishing a diagnosis. To explore the possibility of postmortem CT for the evaluation of gas accumulations in the newborns' vessels, who died from congenital sepsis. Researched of 44 newborns bodies (25 male and 19 female sex, at the age from 6 hours to 27 days) after 6 - 12 hours of death. The bodies were stored in the refrigerator at a temperature of +4°C in the supine position. Grouped 12 bodies of newborns that died from congenital sepsis. The control group consisted of 32 bodies of newborns that died without signs of sepsis. Postmortem CT examination was performed at the GEMINI TF TOF16 device, before the autopsy. The localizations of gas accumulations in the vessels were determined on the CT tomograms. The sepsis diagnosis was on the basis of clinical and laboratory data and autopsy results. Gases in the vessels were detected in 33.3% of cases in the group with sepsis, and in the control group - in 34.4%. A group with sepsis most often the gas localized in the heart and liver vessels - 50% each, of observations number with the detected gas in the vessels. In the heart cavities, aorta and mesenteric vessels - 25% each. In control most often gas was detected in the liver (63.6%) and abdominal cavity (54.5%) vessels. In 45.5% the gas localized in the cavities, and in 36.4% in the vessels of the heart. In the cerebral vessels and in the aorta gas was detected in 27.3% and 9.1%, respectively. Postmortem CT has high diagnostic capabilities to detect free gas in vessels. Postmortem changes in newborns that died from sepsis do not affect intravascular gas production within 6-12 hours. Radiation methods should be used as a supplement to the autopsy, including as a kind of ‘guide’, with the indication to the forensic medical expert of certain changes identified during CT studies, for better definition of pathological processes during the autopsy. Postmortem CT can be recommend as a first stage of autopsy.

Keywords: congenital sepsis, gas, newborn, postmortem CT

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Authors: A. Priyanka, Sunil Kumar Kainoor, Parinitha Nayaka

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Introduction: Ever since the ancient times, rape and other sexual offences are considered to be heinous crimes. Rape is not just another word in the dictionary, but it is the most barbaric act of violence committed with sex being the weapon. Rape is among the highest forms of crime experienced by women and children in all sectors of the society. In recent years, there has been an alarming rise in ratio of rape in India. The burden of such crimes on the society is very huge. The venereal diseases are the worst consequence along with unwanted pregnancies. Aims and Objectives: To determine the socio-demographic profile of the survivors of sexual offences reported to Dept. of Forensic Medicine of a South Indian medical college. Material methods: This retrospective study was conducted in the Department of Forensic Medicine of Raichur Institute of Medical Sciences, Raichur, Karnataka, India. Only survivors of sexual offences cases were included in the study group. Examination of all survivors was carried out by doctors of the said Department. Study period is one year six months, January 2015 to June 2016. Results/ case history: In total 140 cases of sexual offences were examined during study period of which the total survivors accounted to 62.85% i.e. 88 cases. Of the 88 survivors, 61 (69.31%) were registered under POCSO Act. The most affected age group of victims was 10-18 years in 59 (67%) cases. 61% were in acquaintance with the assailants, 18% were classmates/ friends, 13% of accused were Family members/ Relatives, 8% were strangers. 85% of the survivors were hailing from rural setup, while 15% were from urban. 60.65% of the survivors were students, 37.7% were doing Coolie/ Agricultural works. Conclusion: Delay in reporting of cases resulted in loss of vital physical evidences as no concrete report could be generated from the forensic lab after examination of specimens thus there should be coordination among doctors, forensic experts and investigating agency. It is worth mentioning that though a large number of cases of sexual offences are reported as rape many among them are consented acts and hence definite evidence of forceful sexual intercourse is lagging.

Keywords: consensual sex, India, POCSO Act- 2012, India, pregnancy, rape, sexual offence

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Authors: Jovanca Smith, Derek Gay

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All universities possess a standard by which students are assessed and administered into their programs. This paper considers the effect of the educational history of students, as measured by specific subject grades in Caribbean examinations, on overall performance in introductory engineering math and mechanics courses. Results reflect a correlation between the highest grade in the Caribbean examinations with a higher probability of successful advancement in the university courses. Alternatively, lower entrance grades are commensurate with underperformance in the university courses. Results also demonstrate that students matriculating with the Caribbean examinations will not necessarily possess a significant advantage over students entering through an alternative route, and while previous educational background of students is a significant indicator of tentative performance in the University level math and mechanics courses, it is not the sole factor.

Keywords: bimodal distribution, differential learning, engineering education, entrance qualification

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Authors: Débora C. Mendes, Matthias Eckert, Cláudia S. Moço, Hélio Martins, Jean-Pierre P. Gonçalves, Miguel Oliveira, José P. Da Silva

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Uncontrolled disposal of construction and demolition waste (C & DW) in embankments in the periphery of cities causes both environmental and social problems, namely erosion, deforestation, water contamination and human conflicts. One of the milestones of EU Horizon 2020 Programme is the management of waste as a resource. To achieve this purpose for C & DW, a detailed analysis of the properties of these materials should be done. In this work we report the physical, chemical and environmental properties of C & DW aggregates from 25 different origins. The results are compared with those of common natural aggregates used in construction. Assays were performed according to European Standards. Additional analysis of heavy metals and organic compounds such as polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), were performed to evaluate their environmental impact. Finally, properties of concrete prepared with C & DW aggregates are also reported. Physical analyses of C & DW aggregates indicated lower quality properties than natural aggregates, particularly for concrete preparation and unbound layers of road pavements. Chemical properties showed that most samples (80%) meet the values required by European regulations for concrete and unbound layers of road pavements. Analyses of heavy metals Cd, Cr, Cu, Pb, Ni, Mo and Zn in the C&DW leachates showed levels below the limits established by the Council Decision of 19 December 2002. Identification and quantification of PCBs and PAHs indicated that few samples shows the presence of these compounds. The measured levels of PCBs and PAHs are also below the limits. Other compounds identified in the C&DW leachates include phthalates and diphenylmethanol. In conclusion, the characterized C&DW aggregates show lower quality properties than natural aggregates but most samples showed to be environmentally safe. A continuous monitoring of the presence of heavy metals and organic compounds should be made to trial safe C&DW aggregates. C&DW aggregates provide a good economic and environmental alternative to natural aggregates.

Keywords: concrete preparation, construction and demolition waste, heavy metals, organic pollutants

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: S. Fröhlich, M. Herold, M. Allmer

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Early stage quantitative analysis of host cell protein (HCP) variations is challenging yet necessary for comprehensive bioprocess development. High resolution mass spectrometry (HRMS) provides a high-end technology for accurate identification alongside with quantitative information. Hereby we describe a flexible HRMS assay platform to quantify HCPs relevant in microbial expression systems such as E. Coli in both up and downstream development by means of MVDA tools. Cell pellets were lysed and proteins extracted, purified samples not further treated before applying the SMART tryptic digest kit. Peptides separation was optimized using an RP-UHPLC separation platform. HRMS-MSMS analysis was conducted on an Orbitrap Velos Elite applying CID. Quantification was performed label-free taking into account ionization properties and physicochemical peptide similarities. Results were analyzed using SIEVE 2.0 (Thermo Fisher Scientific) and SIMCA (Umetrics AG). The developed HRMS platform was applied to an E. Coli expression set with varying productivity and the corresponding downstream process. Selected HCPs were successfully quantified within the fmol range. Analysing HCP networks based on pattern analysis facilitated low level quantification and enhanced validity. This approach is of high relevance for high-throughput screening experiments during upstream development, e.g. for titer determination, dynamic HCP network analysis or product characterization. Considering the downstream purification process, physicochemical clustering of identified HCPs is of relevance to adjust buffer conditions accordingly. However, the technology provides an innovative approach for label-free MS based quantification relying on statistical pattern analysis and comparison. Absolute quantification based on physicochemical properties and peptide similarity score provides a technological approach without the need of sophisticated sample preparation strategies and is therefore proven to be straightforward, sensitive and highly reproducible in terms of product characterization.

Keywords: process analytical technology, mass spectrometry, process characterization, MVDA, pattern recognition

Procedia PDF Downloads 237