Search results for: Promise Ufomadu

Authors: Kathie Records, R. Jeanne Ruiz, Kimberly Ayers, Rebecca Pasillas

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Background: Preterm births of less than 37 weeks gestation occur disproportionately to Hispanics living along the U.S.-Mexico border. Prematurity has devastating and costly effects on children, families and the health care system. Few preventive interventions have been tested for this vulnerable group. Objectives: To present the modeling and pilot testing of the theory-based Mastery Lifestyle Intervention (MLI), designed to reduce and prevent PTB among Mexican American women (the terms Hispanics or Latinas will also be used to represent this group) living in the United States. Design and Methods: The conceptualization of the problem of preterm births and the available literature underpinning the mastery lifestyle intervention will be reviewed. The lifestyle intervention includes foundational components of problem solving therapy and acceptance and commitment therapy. Findings from implementation of a one-group pilot test and focus group evaluated the feasibility and acceptability of the MLI. Summary: Participants found the MLI to be feasible and acceptable, and reported perceiving improved health status and familial relationships. Suggestions were provided for modifications prior to efficacy testing. The MLI appears to be a theoretically and empirically grounded intervention that holds promise for preventing preterm births among Latinas.

Keywords: birth, Hispanic, intervention, stress

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Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Kairat Uteulin, Serik Mukhambetzhanov, Izbasar Rakhimbaiev

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The effects of varying concentrations of growth regulators including 2, 4-D (2,4-Dichlorophenoxyacetic acid), BAP (6-benzylaminopurine), IAA (indole-3-acetic acid) and Kin (kinetin) was investigated for primary callus induction, embryogenic callus formation and regeneration of two elite Taraxacum kok-saghyz (TKS) lines, TKS1 and TKS2. Mature seeds were used as explants for primary callus induction. Different concentrations of 2, 4-D were investigated to study its effect on callus induction and callus growth frequency (CGF). Compact, whitish, healthy and fluffy calli were induced in TKS1 and TKS2 in MS medium supplemented with 5 mg/l and 4 mg/l 2, 4-D respectively. The calli produced were subjected to somatic embryogenesis and regeneration studies. For this purpose, MS Medium was supplemented with different concentrations and combinations of plant growth regulators like IAA and BAP. Maximum embryogenic callus formation was observed in MS medium supplemented with 0.1 mg/l IAA in combination with 1.5 mg/l BAP and it resulted in 73.51% and 62.33% embryogenic callus formation in TKS1 and TKS2 respectively. These optimum concentrations of IAA and BAP were further experimented with different concentrations of Kin for efficient regeneration and it was observed that 1 mg/l Kin was optimum for this purpose. Such studies help in understanding the response of TKS to tissue culture conditions and ultimately promise in improving yield by employing various biotechnological techniques.

Keywords: taraxacum kok-saghyz Rodin, callus, somatic embryogenesis

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Authors: Alanna Goodman, Kayla Murray, Keith Warriner

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The following reports on a comparative study on the efficacy of different decontamination technologies to decrease Listeria monocytogenes inoculated onto white sliced mushrooms and assesses the fate of residual levels during posttreatment storage under aerobic conditions at 8uC. The treatments were chemical (hydrogen peroxide, peroxyacetic acid, ozonated water, electrolyzed water, chitosan, lactic acid), biological (Listeria bacteriophages), and physical (UV-C, UV:hydrogen peroxide). None of the treatments achieved .1.2 log CFU reduction in L. monocytogenes levels; bacteriophages at a multiplicity of infection of 100 and 3% (vol/vol) hydrogen peroxide were the most effective of the treatments tested. However, growth of residual L. monocytogenes during posttreatment storage attained levels equal to or greater than levels in the nontreated controls. The growth of L. monocytogenes was inhibited on mushrooms treated with chitosan, electrolyzed water, peroxyacetic acid, or UV. Yet, L. monocytogenes inoculated onto mushrooms and treated with UV:hydrogen peroxide decreased during posttreatment storage, through a combination of sublethal injury and dehydration of the mushroom surface. Although mushrooms treated with UV:hydrogen peroxide became darker during storage, the samples were visually acceptable relative to controls. In conclusion, of the treatments evaluated, UV:hydrogen peroxide holds promise to control L. monocytogenes on mushroom surfaces.

Keywords: listeria monocytogenes, sliced mushrooms, bacteriophages, UV, sanitizers

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Authors: Ergun Sakalar, Kubra Bilgic

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Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

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Authors: Mariam Badmus, Bothina Manasreh

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Transition metal dichalcogenides (TMDs) have gained significant attention as two-dimensional (2D) materials due to their intrinsic band gaps and unique properties, which make them ideal candidates for electronic and photonic applications. Unlike graphene, which lacks a band gap, TMDs (MX₂, where M is a transition metal and X is a chalcogen such as sulfur, selenium, or tellurium) exhibit semiconductor behavior and can be exfoliated into monolayers, enhancing their properties. The properties of these materials are investigated using density functional theory, a quantum mechanical computational method to solve Schrodinger equation for many body problems to calculate electron density of the atoms involved on which the energy and properties of a system depend. They show promise for use in photodetectors, biosensors, memory devices, and other technologies in communications, health, and energy sectors. In particular, metallic TMDs, which lack an intrinsic band gap, benefit from doping with transition metals, this improves their electronic and optical properties. Doping monolayer TMDs yields more significant improvements than doping bulk materials. Notably, doping with metals such as vanadium enhances the magnetization of TMDs, expanding their potential applications in spintronics. This work highlights the effects of doping on TMDs and explores strategies for optimizing their performance for advanced technological applications.

Keywords: concentration, doping, magnetization, monolayer

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: M. Fette, J. P. Wulfsberg, A. Herrmann, R. H. Ladstaetter

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Present and future lightweight design represents an important key to successful implementation of energy-saving, fuel-efficient and environmentally friendly means of transport in the aerospace and automotive industry. In this context the use of carbon fibre reinforced plastics (CFRP) which are distinguished by their outstanding mechanical properties at relatively low weight, promise significant improvements. Due to the reduction of the total mass, with the resulting lowered fuel or energy consumption and CO2 emissions during the operational phase, commercial aircraft and future vehicles will increasingly be made of CFRP. An auspicious technology for the efficient and economic production of high performance thermoset composites and hybrid structures for future lightweight applications is the combination of carbon fibre sheet moulding compound (SMC), tailored continuous carbon fibre reinforcements and metallic components in a one-shot pressing and curing process. This paper deals with a new hybrid composite technology for aerospace industries, which was developed with the help of a universal innovation and development system. This system supports the management of idea generation, the methodical development of innovative technologies and the achievement of the industrial readiness of these technologies.

Keywords: development system, hybrid composite, innovation system, prepreg, sheet moulding compound

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Authors: Hyehyeon Lee, Juwon Yu, Juwon Kim, Raquel Kristina Leoni Tumiar, Taewon Kim, Juae Kim, Hongsuk Suh

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Recently, the development of photovoltaics is rapidly accelerating as one of green energy sources. So we designed pyrimidine-based polymers with 2-{3-[4,6-bis-(4-hexyl-thiophen-2-yl)-pyrimidin-2-yl]-phenyl}-thiazolo[5,4-b]pyridine (mPTP), as active layer substances for polymer solar cells. Polymers with push-pull types, mPTPBDT-12, mPTPBDT-EH, mPTPBDTT-EH and mPTPTTI, are comprised of electron pushing unit using benzo[1,2-b;3,4-b’]dithiophene (BDT) or 4,8-bis(5-thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene (BDTT) or 6-(2-thienyl)-4H-thieno[3,2-b]indole(TTI) and electron pulling unit using mPTP. The device including mPTPTTI-12 indicated a VOC of 0.67 V, a JSC of 2.16 mA/cm², and a fill factor (FF) of 0.30, giving a power conversion efficiency (PCE) of 0.43%. The device including mPTPBDT-EH indicated a VOC of 0.56 V, a JSC of 2.64 mA/cm², and an FF of 0.30, giving a PCE of 0.44%. The device including mPTPBDTT-EH indicated a VOC of 0.44 V, a JSC of 2.45 mA/cm², and an FF of 0.29, giving a PCE of 0.31%. The device including mPTPTTI indicated a VOC of 0.72 V, a JSC of 4.95 mA/cm², and an FF of 0.32, giving a PCE of 1.15%. Therefore, mPTPBDT-12, mPTPBDT-EH, mPTPBDTT-EH and mPTPTTI were fabricated by Stille polymerization. Their optical properties were measured and the results show that pyrimidine-based polymers have a great promise to act as donor of active layer.

Keywords: polymer solar cells, photovoltaics, thiazolopyridine, conjugated polymer

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Authors: Crescentia Ugwuona

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Appropriate language use has been central and critical in advancing education and human rights for women and girls in many countries the world over. Unfortunately, these lofty aims have often been violated by rural Igbo-Nigerians as they use stereotyping and dehumansing language in their cultural songs against women and girls. The psychological impact of the songs has a significant negative impact on education, human rights, quality of life, and opportunities for many rural Igbo-women and girls in Nigeria. This study, therefore, examines the forms, shades, and manifestations of derogatory and stereotypical language against women and girls the Igbo cultural songs; and how they impede education and human rights for females in Nigeria. Through Critical discourse analysis (CDA) of data collected via recording, the study identifies manifestations of women and girls’ stereotypes such as subjugations, male dominance, inequality in gender roles, suppression, and oppression, and derogatory use of the language against women and girls in the Igbo cultural songs. This study has a great promise of alerting the issues of derogatory and stereotypical language in songs, and contributes to an education aimed at gender equality, emancipator practice of appropriate language use in songs, equal education and human rights for both male and female, respect and solidarity in Nigeria and beyond.

Keywords: gender stereotypes, cultural songs, women and girls, language use in Nigeria, critical discourse analysis, CDA, education

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Authors: Harish Kumar Sharma, Garima Sengar

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Rice bran oil is considered comparatively nutritionally superior than different fats/oils. Therefore, model blends prepared from pure rice bran oil (RBO) and sunflower oil (SFO) were explored for changes in the different physicochemical parameters. Repeated deep fat frying process was carried out by using dried potato in order to study the thermal behaviour of pure rice bran oil, sunflower oil and their model blends. Pure rice bran oil and sunflower oil had shown good thermal stability during the repeated deep fat frying cycles. Although, the model blends constituting 60% RBO + 40% SFO showed better suitability during repeated deep fat frying than the remaining blended oils. The quantification of pure rice bran oil in the blended oils, physically refined rice bran oil (PRBO): SnF (sunflower oil) was carried by different methods. The study revealed that regression equations based on the oryzanol content, palmitic acid composition and iodine value can be used for the quantification. The rice bran oil can easily be quantified in the blended oils based on the oryzanol content by HPLC even at 1% level. The palmitic acid content in blended oils can also be used as an indicator to quantify rice bran oil at or above 20% level in blended oils whereas the method based on ultrasonic velocity, acoustic impedance and relative association showed initial promise in the quantification.

Keywords: rice bran oil, sunflower oil, frying, quantification

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Authors: Milda Istiqomah

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Deradicalization program has long been the subject of investigation. There is a steadily growing interest in examining the results on how Islamist terrorists agree to abandon violence and leave radicalism; however, it is argued that de-radicalization program on terrorism in many countries is still questionable for its effectiveness. This article aims to provide an overview of the deradicalization program specifically related to the victim-centred approach conducted by the Indonesian government and investigates critical issues surrounding the analysis of their effectiveness and outcomes. This research employs several case studies of a victim-centred approach conducted by the Indonesian Witness and Victim Protection Agency as well as the Indonesian Counter-terrorism Agency. This paper argues that the victim-centred approach to de-radicalize former terrorist prisoners faces several implemental challenges; however, the initiative may offer promise for future successful de-radicalization program. Furthermore, until more data surrounding the efficacy of this initiative available, the victim-centred approach may also constitute a significant and essential component of disengagement, de-radicalisation, and reintegration of terrorist prisoners. In conclusion, this paper suggests that further empirical research concerning prevention policies and disengagement interventions related to victim-centred approach need to be explored to give more inputs to the Indonesian government to achieve the effectiveness of de-radicalization program.

Keywords: terrorism, victim-centred approach, de-radicalization, Islamist extremism

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Authors: Omer Ibrahim Abdallh Omer

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Cancer patients often face complex medication regimens, leading to challenges in treatment adherence and clinical outcomes. Pharmacist-led medication therapy management (MTM) has emerged as a potential solution to optimize medication use and improve patient outcomes in oncology settings. In this prospective intervention study, we aimed to evaluate the impact of pharmacist-led MTM on treatment adherence and clinical outcomes among cancer patients. Participants were randomized to receive either pharmacist-led MTM or standard care, with assessments conducted at baseline and follow-up visits. Pharmacist interventions included medication reconciliation, adherence counseling, and personalized care plans. Our findings reveal that pharmacist-led MTM significantly improved medication adherence rates and clinical outcomes compared to standard care. Patients receiving pharmacist interventions reported higher satisfaction levels and perceived value in pharmacist involvement in their cancer care. These results underscore the critical role of pharmacists in optimizing medication therapy and enhancing patient-centered care in oncology settings. Integration of pharmacist-led MTM into routine cancer care pathways holds promise for improving treatment outcomes and quality of life for cancer patients.

Keywords: cancer, medications adherence, medication therapy management, pharmacist

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Authors: Sonia Anand Knowlton

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As the use of Artificial Intelligence is becoming increasingly integrated in virtually every area of life, the need and interest to logically formalize the law and judicial reasoning is growing tremendously. The study of argumentation frameworks (AFs) provides promise in this respect. AF’s provide a way of structuring human reasoning using a formal system of non-monotonic logic. P.M. Dung first introduced this framework and demonstrated that certain arguments must prevail and certain arguments must perish based on whether they are logically “attacked” by other arguments. Dung labelled the set of prevailing arguments as the “preferred extension” of the given argumentation framework. Trevor Bench-Capon’s Value-based Argumentation Frameworks extended Dung’s AF system by allowing arguments to derive their force from the promotion of “preferred” values. In VAF systems, the success of an attack from argument A to argument B (i.e., the triumph of argument A) requires that argument B does not promote a value that is preferred to argument A. There has been thorough discussion of the application of VAFs to the law within the computer science literature, mainly demonstrating that legal cases can be effectively mapped out using VAFs. This article analyses VAFs from a jurisprudential standpoint to provide a philosophical and theoretical analysis of what VAFs tell the legal community about the judicial reasoning, specifically distinguishing between legal and moral reasoning. It highlights the limitations of using VAFs to account for judicial moral reasoning in theory and in practice.

Keywords: nonmonotonic logic, legal formalization, computer science, artificial intelligence, morality

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Authors: Tiffany Gallagher, Sheila Bennett

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Based on data from a larger study, this research is based in a small school district in Ontario, Canada, that has made a transition from self-contained classes for students with exceptionalities to inclusive classroom placements for all students with their age-appropriate peers. The school board aided this transition by hiring Inclusion Coaches with a background in special education to work alongside teachers as partners and inform their inclusive practice. Based on qualitative data from four focus groups conducted with Inclusion Coaches, as well as four blog-style reflections collected at various points over two years, six principles of inclusive practice were identified for coaches. The six principles form a model during transition: pre-requisite, process, precipice, promotion, proof, and promise. These principles are encapsulated in a visual model of a spiraling staircase displaying the conditions that exist prior to coaching, during coaching interactions and considerations for the sustainability of coaching. These six principles are re-iterative and should be re-visited each time a coaching interaction is initiated. Exploring inclusion coaching as a model emulates coaching in other contexts and allows us to examine an established process through a new lens. This research becomes increasingly important as more school boards transition toward inclusive classrooms, The Six ‘P’ Model: Principles of Inclusive Practice for Inclusion Coaches allows for a unique look into a scaffolding model of building educator capacity in an inclusive setting.

Keywords: capacity building, coaching, inclusion, special education

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Authors: Rabia Faridi, Rizwana Maqbool, Umara Sahar Rana, Zaheer Ahmad

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Climate change impacts agriculture, notably in Germany, where spring faba beans predominate. However, improved winter hardiness aligns with milder winters, enabling autumn-sown varieties. Genetic resistance to Ascochyta blight is vital for crop integration. Traditional breeding faces challenges due to complex inheritance. This study assessed 224 homozygous faba bean lines for Ascochyta resistance traits. To achieve h²>70%, 12 replicates were required (realized h²=87%). Genetic variation and strong trait correlations were observed. Five lines outperformed 29H, while three were highly susceptible. A genome-wide association study (GWAS) with 188 inbred lines and 2058 markers, including 17 guide SNP markers, identified 12 markers associated with resistance traits, potentially indicating new resistance genes. One guide marker (Vf-Mt1g014230-001) on chromosome III validated a known QTL. The guided marker approach complemented GWAS, facilitating marker-assisted selection for Ascochyta resistance. The Göttingen Winter Bean Population offers promise for resistance breeding.

Keywords: genome wide association studies, marker assisted breeding, faba bean, ascochyta blight

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Authors: Mark Osborn

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Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

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Authors: Cris Bravo

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Social entrepreneurship is a new and exciting topic that holds a great promise in helping alleviate the social problems of the world. As a new subject, the meaning of the term is too broad and this is counterproductive in trying to build understanding around the concept. The purpose of this study is to identify and compare the elements of social entrepreneurship as defined by seven international organizations leading social entrepreneurship projects: Ashoka Foundation, Skoll Foundation, Schwab Foundation and Yunus Center; as well as from three other institutions fostering social entrepreneurship: Global Social Benefit Institute, BRAC University, and Socialab. The study used document analysis from Skoll Foundation, Schwab Foundation, Yunus Center and Ashoka Foundation; and open ended interview to experts from the Global Social Benefit Institute at Santa Clara University in United States, BRAC University from Bangladesh, and Socialab from Argentina. The study identified three clearly differentiated schools of thought, based on their views on revenue, scalability, replicability and geographic location. While this study is by no means exhaustive, it provides an indication of the patterns of ideas fostered by important players in the field. By clearly identifying the similarities and differences in the concept of social entrepreneurship, research and practitioners are better equipped to build on the subject, and to promote more adequate and accurate social policies to foster the development of social entrepreneurship.

Keywords: replicability, revenue, scalability, schools of thought, social entrepreneurship

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Authors: Obsi Terfasa, Bhanupriya Das, Mithilish Passawan

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The large-scale application of microbial fuel cell (MFC) technology is significantly hindered by the high cost of the commonly used proton exchange membrane, Nafion. This has led to the recent development of ceramic membranes using various clay minerals. This study evaluates the characteristics and potential use of a new ceramic membrane made from potter’s clay © mixed with different proportions (0, 5, 10 wt%) of fly ash (FA), labeled as CFA0, CFA5, CFA10, for cost-effective and sustainable MFC use. Among these, the CFA10 membrane demonstrated superior quality with a fine pore size distribution (average 0.41 μm), which supports higher water uptake and reduced oxygen diffusion. Its oxygen mass transfer coefficient was 4.13 ± 0.13 × 10⁻⁴ cm/s, about 40% lower than the control. X-ray diffraction analysis revealed that the CFA membrane is rich in quartz, which enhances proton conductance and water retention. Electrochemical kinetics studies, including cyclic voltammetry and electrochemical impedance spectroscopy (EIS), also confirmed the effectiveness of the CFA10 membrane in MFC, showing a peak current output of 15.35 mA and low ohmic resistance (78.2 Ω). The novel CFA10 ceramic membrane, incorporating coal fly ash, a waste material, shows promise for high MFC performance at a significantly reduced cost (96%), making it suitable for sustainable scaling up of the technology.

Keywords: ceramic membrane, Coulombic efficiency, electro-chemical kinetics, fly ash, proton conductivity, microbial fuel cell

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Authors: H. Tayefih, F. farajzade ahari, F. Zarghami, V. Zeighamian, N. Zarghami, Y. Pilehvar-soltanahmadi

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Breast cancer is the most frequently occurring cancer among women throughout the world. Natural compounds such as curcumin hold promise to treat a variety of cancers including breast cancer. However, curcumin's therapeutic application is limited, due to its rapid degradation and poor aqueous solubility. On the other hand, previous studies have stated that drug delivery using nanoparticles might improve the therapeutic response to anticancer drugs. Poly (N-isopropylacrylamide-co-methacrylic acid) (PNIPAAm–MAA) is one of the hydrogel copolymers utilized in the drug delivery system for cancer therapy. The aim of this study was to examine the cytotoxic potential of curcumin encapsulated within the NIPAAm-MAA nanoparticle, on the MCF-7 breast cancer cell line. In this work, polymeric nanoparticles were synthesized through the free radical mechanism, and curcumin was encapsulated into NIPAAm-MAA nanoparticles. Then, the cytotoxic effect of curcumin-loaded NIPAAm-MAA on the MCF-7 breast cancer cell line was measured by MTT assays. The evaluation of the results showed that curcumin-loaded NIPAAm-MAA has more cytotoxic effect on the MCF-7 cell line and efficiently inhibited the growth of the breast cancer cell population, compared with free curcumin. In conclusion, this study indicates that curcumin-loaded NIPAAm-MAA suppresses the growth of the MCF-7 cell line. Overall, it is concluded that encapsulating curcumin into the NIPAAm-MAA copolymer could open up new avenues for breast cancer treatment.

Keywords: PNIPAAm-MAA, breast cancer, curcumin, drug delivery

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Nancy Bartekian, Kaelan Vazquez, Christine Reyna

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Immigrants coming into the United States of America may justify the American system (political, economic, healthcare, criminal justice) and see it as functional. This may be explained because they may come from countries that are even more unstable than the U.S. and/or come here to benefit from the promise of the “American dream” -a narrative that they might be more likely to believe in if they were willing to undergo the costly and sometimes dangerous process to immigrate. Conversely, native-born Americans, as well as immigrants who may have lived in America for a longer period of time, would have more experiences with the various broken systems in America that are dysfunctional, fail to provide adequate services equitably, and/or are steeped in systemic racism and other biases that disadvantage lower-status groups. Thus, our research expects that system justification would decrease, and condemnation would increase with more time spent in the U.S. for immigrant groups. We predict that a) those not born in the U.S. will be more likely to justify the system, b) they will also be less likely to condemn the system, and c) the longer an immigrant has been in the U.S. the less likely they will to justify, and more they will to condemn the system. We will use a mixed-model multivariate analysis of covariance (MANCOVA) and control for race, income, and education. We will also run linear regression models to test if there is a relationship between the length of time in the United States and a decrease in system justification, and length of time and an increase in system condemnation for those not born in the U.S. We will also conduct exploratory analyses to see if the predicted patterns are more likely within certain systems over other systems (political, economic, healthcare, criminal justice).

Keywords: immigration, system justification, system condemnation, system qualification

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Authors: Anastasia Stamatiou, Markus Odermatt, Dominic Leemann, Ludger J. Fischer, Joerg Worlitschek

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The successful integration of thermal energy storage in industrial processes is expected to play an important role in the energy turnaround. Latent heat storage technologies can offer more compact thermal storage at a constant temperature level, in comparison to conventional, sensible thermal storage technologies. The focus of this study is the development of latent heat storage solutions based on the Phase Change Slurry (PCS) concept. Such systems promise higher energy densities both as refrigerants and as storage media while presenting better heat transfer characteristics than conventional latent heat storage technologies. This technology is expected to deliver high thermal power and high-temperature stability which makes it ideal for storage of process heat. An evaluation of important batch processes in industrial applications set the focus on materials with a melting point in the range of 55 - 90 °C. Aluminium ammonium sulfate dodecahydrate (NH₄Al(SO₄)₂·12H₂O) was chosen as the first interesting PCM for the next steps of this study. The ability of this material to produce slurries at the relevant temperatures was demonstrated in a continuous mode in a laboratory test-rig. Critical operational and design parameters were identified.

Keywords: esters, latent heat storage, phase change materials, thermal properties

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Authors: Rashid Javed, Hardy Lehmkuehler, Franz Josef-Behr

Abstract:

Web Processing Services (WPS) have up growing concern in geoinformation research. However, teaching about them is difficult because of the generally complex circumstances of their use. They limit the possibilities for hands- on- exercises on Web Processing Services. To support understanding however a Training Tools Collection was brought on the way at University of Applied Sciences Stuttgart (HFT). It is limited to the scope of Geostatistical Interpolation of sample point data where different algorithms can be used like IDW, Nearest Neighbor etc. The Tools Collection aims to support understanding of the scope, definition and deployment of Web Processing Services. For example it is necessary to characterize the input of Interpolation by the data set, the parameters for the algorithm and the interpolation results (here a grid of interpolated values is assumed). This paper reports on first experiences using a pilot installation. This was intended to find suitable software interfaces for later full implementations and conclude on potential user interface characteristics. Experiences were made with Deegree software, one of several Services Suites (Collections). Being strictly programmed in Java, Deegree offers several OGC compliant Service Implementations that also promise to be of benefit for the project. The mentioned parameters for a WPS were formalized following the paradigm that any meaningful component will be defined in terms of suitable standards. E.g. the data output can be defined as a GML file. But, the choice of meaningful information pieces and user interactions is not free but partially determined by the selected WPS Processing Suite.

Keywords: deegree, interpolation, IDW, web processing service (WPS)

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Authors: Tugba Gurler, Irfan Kurtbas

Abstract:

Roof influences considerably energy demand of buildings. In order to reduce this energy demand, various solutions have been proposed, such as roofs with variable thermal insulation, cool roofs, green roofs, heat exchangers and ventilated roofs, and phase change material (PCM) layered roofs. PCMs suffer from relatively low thermal conductivity despite of their promise of the energy-efficiency initiatives for thermal energy storage (TES). This study not only presents the thermal performance of the concrete roof with PCM layers but also evaluates the products with different design configurations and thicknesses under Central Anatolia Region, Turkey and Nottinghamshire, UK weather conditions. System design limitations and proposed prediction models are discussed in this study. A two-dimensional numerical model has been developed, and governing equations have been solved at each time step. Upper surfaces of the roofs have been modelled with heat flux conditions, while lower surfaces of the roofs with boundary conditions. In addition, suitable roofs have been modeled under symmetry boundary conditions. The results of the designed concrete roofs with PCM layers have been compared with common concrete roofs in Turkey. The UK and the numerical modeling results have been validated with the data given in the literature.

Keywords: phase change material, regional energy demand, roof layers, thermal energy storage

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Authors: Michelle Marquard

Abstract:

The evidence for collaboration technologies (CTs) as a source of business productivity has never been stronger, and grows each day. At the same time, paradoxically, there is an increasingly greater concern about the challenge CTs present to the unity and well-being of the virtual workforce than ever before, but nowhere in the literature has an empirical understanding of these linkages been set out. This study attempted to address by using virtual distance as a measure of the efficacy of CTs to reduce the psychological distance among people. Data from 350 managers and 101 individual contributors across twelve functions in six major industries showed that business value is related to collaboration (r=.84, p < .01), which, in turn, is associated with full spectrum participation (r=.60, p < .01), a summative function of inclusion, integration, and we-intention. Further, virtual distance is negatively related to both collaboration (r=-.54, p < .01) and full spectrum participation (r=-.26, p < .01). Additionally, CIO-CDO relationship is a factor in the degree to which virtual distance is managed in the organization (r=-.26, p < .01). Overall, the results support the positive relationship between business value and collaboration. They also suggest that the extent to which collaboration can be fostered may depend on the degree of full spectrum participation or the level of inclusion, integration, and we-intention among members. Finally, the results indicate that CTs, when managed wisely to lower virtual distance, are a compelling concomitant to collaboration and full spectrum participation. A strategic outcome of this study is an instrumental blueprint of CTs and virtual distance in relation to full spectrum participation that should serve as a shared dashboard for CIOs, CHROs, and CDOs.

Keywords: business value, collaboration, inclusion, integration, we-intention, full spectrum participation, collaboration technologies, virtual distance

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Authors: Yansong Gao, Damith C.Ranasinghe, Siad F. Al-Sarawi, Omid Kavehei, Derek Abbott

Abstract:

Passive crossbar arrays is in principle the simplest functional electrical circuit, together with memristive device in cross-point, holding great promise in future high-density, non-volatile memories. However, the greatest problem of crossbar array is the sneak path current. In this paper, we investigate one type of memristive device with intrinsic rectification behavior to address the sneak path currents. Firstly, a SPICE behavior model written in Verilog-A language of the memristive device is presented to fit experimental data published in literature. Next, systematic performance simulations including read margin and power consumption of crossbar array, which uses the self-rectifying memristive device as storage element at cross-point, with respect to different crossbar sizes, interconnect resistance, ratio of HRS/LRS (High Resistance State/ Low Resistance State), rectification ratio and different read schemes are conducted. Subsequently, Trade-offs among reading margin, power consumption, and reading schemes are analyzed to provide guidelines for circuit design. Finally, performance comparison between the memristive device with/without intrinsic rectification behavior is given to show the worthiness of this intrinsic rectification behavior.

Keywords: memristive device, memristor, crossbar, RRAM, read margin, power consumption

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Authors: Ahmed Azizeldein Abubaker Abdelhafez

Abstract:

This review explores the application of biochar as a strategy for enhancing soil fertility in arid regions, with a focus on Arab countries. Biochar, derived from the carbonization of biomass under low-oxygen conditions, has shown promise in improving the physical and chemical properties of soil, such as increasing water retention and nutrient availability. Despite the challenging conditions of arid and semi-arid regions, characterized by poor soil fertility and severe land degradation, biochar application has emerged as a viable method to enhance agricultural productivity and mitigate environmental issues. This paper examines various aspects of biochar, including production methods, such as pyrolysis and gasification, and the effects of biochar on soil fertility. It discusses different application techniques and presents case studies from Arab countries like Egypt, the United Arab Emirates, Saudi Arabia, Qatar, Oman, and Kuwait, highlighting the successes and challenges faced in implementing biochar technology. The review also addresses the limitations of biochar use in arid regions and suggests future research directions to optimize its effectiveness. Overall, this study underscores the potential of biochar to contribute significantly to sustainable agriculture and ecological restoration in arid environments, advocating for integrated strategies that combine biochar application with other innovative agricultural practices.

Keywords: biochar, soil fertility, arid region, Arab countries, challenges and limitations

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

Abstract:

As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Otilia Ruxandra Vasile, Ecaterina Andronescu, Cristina Daniela Ghitulica, Bogdan Stefan Vasile, Roxana Trusca, Eugeniu Vasile, Alina Maria Holban, Carmen Mariana Chifiriuc, Florin Iordache, Horia Maniu

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Engineered powders offer great promise in several applications, but little information is known about cytotoxicity effects. The aim of the current study was the synthesis and cytotoxicity examination of silver powders using pyrosol method at temperatures of 600°C, 650°C and 700°C, respectively sol-gel method and calcinations at 500°C, 600°C, 700°C and 800°C. We have chosen to synthesize and examine silver particles cytotoxicity due to its use in biological applications. The synthesized Ag powders were characterized from the structural, compositional and morphological point of view by using XRD, SEM, and TEM with SAED. In order to determine the influence of the synthesis route on Ag particles cytotoxicity, different sizes of micro and nanosilver synthesized powders were evaluated for their potential toxicity. For the study of their cytotoxicity, cell cycle and apoptosis have been done analysis through flow cytometry on human colon carcinoma cells and mesenchymal stem cells and through the MTT assay, while the viability and the morphological changes of the cells have been evaluated by using cloning studies. The results showed that the synthesized silver nanoparticles have displayed significant cytotoxicity effects on cell cultures. Our synthesized silver powders were found to present toxicity in a synthesis route and time-dependent manners for pyrosol synthesized nanoparticles; whereas a lower cytotoxicity has been measured after cells were treated with silver nanoparticles synthesized through sol-gel method.

Keywords: Ag, cytotoxicity, pyrosol method, sol-gel method

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