Search results for: personalized advertisement

Authors: Sultan Ahmad Azizi, Gaurang J. Joshi

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Urban transportation has come to lime light in recent times due to deteriorating travel quality. The economic growth of India has boosted significant rise in private vehicle ownership in cities, whereas public transport systems have largely been ignored in metropolitan cities. Even though there is latent demand for public transport systems like organized bus services, most of the metropolitan cities have unsustainably low share of public transport. Unfortunately, Indian metropolitan cities have failed to maintain balance in mode share of various travel modes in absence of timely introduction of mass transit system of required capacity and quality. As a result, personalized travel modes like two wheelers have become principal modes of travel, which cause significant environmental, safety and health hazard to the citizens. Of late, the policy makers have realized the need to improve public transport system in metro cities for sustaining the development. However, the challenge to the transit planning authorities is to design a transit system for cities that may attract people to switch over from their existing and rather convenient mode of travel to the transit system under the influence of household socio-economic characteristics and the given travel pattern. In this context, the fast-growing industrial city of Surat is taken up as a case for the study of likely shift to bus transit. Deterioration of public transport system of bus after 1998, has led to tremendous growth in two-wheeler traffic on city roads. The inadequate and poor service quality of present bus transit has failed to attract the riders and correct the mode use balance in the city. The disaggregate travel behavior for trip generations and the travel mode choice has been studied for the West Adajan residential sector of city. Mode specific utility functions are calibrated under multi-nominal logit environment for two-wheeler, cars and auto rickshaws with respect to bus transit using SPSS. Estimation of shift to bus transit is carried indicate an average 30% of auto rickshaw users and nearly 5% of 2W users are likely to shift to bus transit if service quality is improved. However, car users are not expected to shift to bus transit system.

Keywords: bus transit, disaggregate travel nehavior, mode choice Behavior, public transport

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: V. Jaime Contreras, S. Iliana Nunez, S. Mario Sanchez

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Inside a manufacturing facility, we can find innumerable automatic and manual operations, all of which are relevant to the production process. Some of these processes add more value to the products more than others. Manual operations tend to add value to the product since they can be found in the final assembly area o final operations of the process. In this areas, where a mistake or accident can increase the cost of waste exponentially. To reduce or mitigate these costly mistakes, one approach is to rely on automation to eliminate the operator from the production line - requires a hefty investment and development of specialized machinery. In our approach, the center of the solution is the operator through sufficient and adequate instrumentation, real-time reporting and ergonomics. Efficiency and reduced cycle time can be achieved thorough the integration of Internet-of-Things (IoT) ready technologies into assembly operations to enhance the ergonomics of the workstations. Augmented reality visual aids, RFID triggered personalized workstation dimensions and real-time data transfer and reporting can help achieve these goals. In this case study, a standard work cell will be used for real-life data acquisition and a simulation software to extend the data points beyond the test cycle. Three comparison scenarios will run in the work cell. Each scenario will introduce a dimension of the ergonomics to measure its impact independently. Furthermore, the separate test will determine the limitations of the technology and provide a reference for operating costs and investment required. With the ability, to monitor costs, productivity, cycle time and scrap/waste in real-time the ROI (return on investment) can be determined at the different levels to integration. This case study will help to show that ergonomics in the assembly lines can make significant impact when IoT technologies are introduced. Ergonomics can effectively reduce waste and increase productivity with minimal investment if compared with setting up to custom machine.

Keywords: augmented reality visual aids, ergonomics, real-time data acquisition and reporting, RFID triggered workstation dimensions

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Authors: Elyria Kemp, Kelly Cowart, My Bui

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According to the National Institute of Mental Health, an estimated 31.9% of adolescents have had an anxiety disorder. Several environmental factors may help to contribute to high levels of anxiety and depression in young people (i.e., Generation Z, Millennials). However, as young people negotiate life on social media, they may begin to evaluate themselves using excessively high standards and adopt self-perfectionism tendencies. Broadly defined, self-perfectionism involves very critical evaluations of the self. Perfectionism may also come from others and may manifest as socially prescribed perfectionism, and young adults are reporting higher levels of socially prescribed perfectionism than previous generations. This rising perfectionism is also associated with anxiety, greater physiological reactivity, and a sense of social disconnection. However, theories from psychology suggest that improvement in emotion regulation can contribute to enhanced psychological and emotional well-being. Emotion regulation refers to the ways people manage how and when they experience and express their emotions. Cognitive reappraisal and expressive suppression are common emotion regulation strategies. Cognitive reappraisal involves changing the meaning of a stimulus that involves construing a potentially emotion-eliciting situation in a way that changes its emotional impact. By contrast, expressive suppression involves inhibiting the behavioral expression of emotion. The purpose of this research is to examine the efficacy of social marketing initiatives which promote emotion regulation strategies to help young adults regulate their emotions. In Study 1 a single factor (emotional regulation strategy: a cognitive reappraisal, expressive, control) between-subjects design was conducted using an online, non-student consumer panel (n=96). Sixty-eight percent of participants were male, and 32% were female. Study participants belonged to the Millennial and Gen Z cohort, ranging in age from 22 to 35 (M=27). Participants were first told to spend at least three minutes writing about a public speaking appearance which made them anxious. The purpose of this exercise was to induce anxiety. Next, participants viewed one of three advertisements (randomly assigned) which promoted an emotion regulation strategy—cognitive reappraisal, expressive suppression, or an advertisement non-emotional in nature. After being exposed to one of the ads, participants responded to a measure composed of two items to access their emotional state and the efficacy of the messages in fostering emotion management. Findings indicated that individuals in the cognitive reappraisal condition (M=3.91) exhibited the most positive feelings and more effective emotion regulation than the expressive suppression (M=3.39) and control conditions (M=3.72, F(1,92) = 3.3, p<.05). Results from this research can be used by institutions (e.g., schools) in taking a leadership role in attacking anxiety and other mental health issues. Social stigmas regarding mental health can be removed and a more proactive stance can be taken in promoting healthy coping behaviors and strategies to manage negative emotions.

Keywords: emotion regulation, anxiety, social marketing, generation z

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Authors: Aijing Luo, Zirui Xin, Yifeng Yuan

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Background: With the rapid development of the online health community, more and more patients or families are seeking health information on the Internet. Objective: This study aimed to discuss how to fully reveal the health information needs expressed by hypertensive patients in their questions in the online environment. Methods: This study randomly selected 1,000 text records from the question data of hypertensive patients from 2008 to 2018 collected from the website www.haodf.com and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning the intention of each hypertensive patient based on the patient’s question and used co-occurrence network analysis to explore the features of the health information needs of hypertensive patients. Results: The classification system for health information needs of patients with hypertension is composed of 9 parts: 355 kinds of drugs, 395 kinds of symptoms and signs, 545 kinds of tests and examinations , 526 kinds of demographic data, 80 kinds of diseases, 37 kinds of risk factors, 43 kinds of emotions, 6 kinds of lifestyles, 49 kinds of questions. The characteristics of the explored online health information needs of the hypertensive patients include: i)more than 49% of patients describe the features such as drugs, symptoms and signs, tests and examinations, demographic data, diseases, etc. ii) these groups are most concerned about treatment (77.8%), followed by diagnosis (32.3%); iii) 65.8% of hypertensive patients will ask doctors online several questions at the same time. 28.3% of the patients are very concerned about how to adjust the medication, and they will ask other treatment-related questions at the same time, including drug side effects, whether to take drugs, how to treat a disease, etc.; secondly, 17.6% of the patients will consult the doctors online about the causes of the clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, medication, and examinations. Conclusion: In the online environment, the health information needs expressed by Chinese hypertensive patients to doctors are personalized; that is, patients with different background features express their questioning intentions to doctors. The classification system constructed in this study can guide health information service providers in the construction of online health resources, to help solve the problem of information asymmetry in communication between doctors and patients.

Keywords: online health community, health information needs, hypertensive patients, doctor-patient communication

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Authors: Rubina Jahan, Mohammad Zayeed Bin Alam, Razia Sultana, Md Faroque Miah

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Mental health remains a significant global public health challenge, profoundly affecting millions worldwide. In Bangladesh, the situation is dire, with the National Mental Health Survey 2018-19 indicating that 19% of adults suffer from any kind of mental disorders, including severe mental disorder of around 2%. Despite these high prevalence rates, there is a substantial treatment gap in low- and middle-income countries, including Bangladesh, where up to 92% of individuals with mental illnesses do not receive adequate care. This gap is exacerbated by social barriers such as stigma, discrimination, social exclusion, poverty, homelessness, and human rights violations. To address these challenges, the SAJIDA Foundation launched the Proshanti in November 2022. Proshanti is a community based supportive housing intervention designed to provide cost-effective, sustainable, long-term care for individuals with chronic mental illnesses. It aims to rehabilitate participants by improving their mental health, quality of life, and equipping them with skills necessary for independent living and social mobility. Currently, Proshanti operates seven houses in Manikganj and Habiganj districts of Bangladesh, accommodating up to 40 individuals. Over a two-year period, individuals have received personalized support from trained personal assistants and care coordinators, regular health checkups, and opportunities for vocational training and community engagement. In this presentation, we will present the outcome of such intervention on individual’s functionality, quality of life and psychological health generated from 24 months of journey. Additionally, a qualitative approach will be employed to understand the facilitators and barriers of program implementation. The Proshanti program represents a promising model for addressing the significant mental health treatment gap in Bangladesh at the community level. Our findings will provide crucial insights into the program's feasibility, effectiveness, and the factors influencing its implementation, potentially guiding future mental health interventions in similar contexts.

Keywords: mental health, community based supportive housing, treatment gap, bangladesh

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Authors: Devyani Shete, Sudeep Rai

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Background: The COVID-19 pandemic has caused one of the highest disruptions to the NHS (National Health Service), especially to the fundamental cervical cancer screening service. To prioritize screening response effectively, it is vital to understand the underlying disease risks amongst groups of women who are less likely to resume their screening/follow up at General Practices. The current government target is to have>=80% of women have an adequate test within the previous 3.5 years (ages 25-49) or 5.5 years (ages 50-64). Aims/Objectives: To increase the number of eligible people aged 25-49 attending cervical screening by 5% at Lakeside Healthcare (a General Practice in Corby). Methods: An online survey was posted on the Lakeside Healthcare website to find out what the barriers towards cervical screening were. It was apparent that patients needed more information catered to their responses. 6 informational videos and a “Cervical Screening Guide” were created for Lakeside patients about cervical screening, which were posted on the Healthcare website. Lakeside also started sending reminder texts to those eligible, with a link to a booking form. Results: On 18th January 2022, 69.7% of patients aged 25-49 years (7207) had an adequate cervical screening test in the last 3.5 years. There were 80 total responders to the online survey. In response to “which of the following are reasons why you have not attended screening”, 30% ticked “I kept putting it off/did not get around to it,” and 13% ticked “I was worried it would be painful or daunting.” In response to “which of the following would make you more likely to book an appointment”, 23% ticked “More detailed explanations of what the risks are if I don’t have screening,” and 20% ticked “I would like more information about the test and what the smear entails.” 10% of responders had previous trauma, whilst 28% of responders said the pandemic had impacted them getting a smear. Survey results were used to carry out interventions to increase smear uptake. On 23rdMarch 2022 (after a 2-month period), 75%of patients aged 25-49 (7119) attended the screening, which was a 5.3% increase from January. Discussion/Conclusion: The survey was vital in carrying out the exact interventions that were required for patients to increase screening uptake, as it is important to know what the populations’ needs are in order to create personalized invitations. This helps to optimise response during a pandemic. A HPV self-sample kit at home could be a popular method of dealing with further outbreaks.

Keywords: gynaecology, cervical screening, public health, COVID-19

Procedia PDF Downloads 139

Authors: Ramin Mehdiabadi

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Background: Breast cancer remains the most prevalent cancer diagnosis and the leading cause of cancer death among women globally, representing 11.7% of new cases and 6.9% of deaths. While the incidence and mortality of major cancers are declining in developed regions like the United States and Western Europe, underdeveloped and developing countries exhibit an increasing trend, attributed to lifestyle factors such as smoking, physical inactivity, and high-calorie diets. Objective: This study explores the intricate relationship between the mammalian transcription factor forkhead box (FoxM1) and the microRNA miR-216b-5p in various subtypes of breast cancer, aiming to deepen the understanding of their roles in tumorigenesis, metastasis, and drug resistance. Methods: Breast cancer subtypes were categorized based on key biomarkers: estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2. These include luminal A, luminal B, HER2 enriched, triple-negative, and normal-like subtypes. We focused on analyzing the expression levels of FoxM1 and miR-216b-5p, given the known role of FoxM1 in cell proliferation and its implications in cancer pathologies such as lung, gastric, and breast cancers. Concurrently, miR-216b-5p's function as a tumor suppressor was evaluated to ascertain its regulatory effects on FoxM1. Results: Preliminary data indicate a nuanced interplay between FoxM1 and miR-216b-5p, suggesting a potential inverse relationship that varies across breast cancer subtypes. This relationship underscores the dual role of these biomarkers in modulating cancer progression and response to treatments. Conclusion: The findings advocate for the potential of miR-216b-5p to serve as a prognostic biomarker and a therapeutic target, particularly in subtypes where FoxM1 is prominently expressed. Understanding these molecular interactions provides crucial insights into the personalized treatment strategies and could lead to more effective therapeutic interventions in breast cancer management. Implications: The study highlights the importance of molecular profiling in breast cancer treatment and emphasizes the need for targeted therapeutic approaches in managing diverse cancer subtypes, particularly in varying global contexts where lifestyle factors significantly impact cancer dynamics.

Keywords: breast cancer, gene expression, FoxM1, microRNA

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Authors: Portia Murphy, Danica Vasic, Anoja W. Gunaratne, Encarnita Sitchon, Teresita Tugonon, Marou Ison, Antoinette Le Busque, Christelle Pagonis, Thomas J. Borody

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Irritable bowel syndrome (IBS) is a chronic gastrointestinal disorder that affects an estimated 11% of the population globally with the most predominant symptoms being abdominal pain, bloating and altered bowel movements. All age groups suffer from IBS although the prevalence of IBS decreases for age groups over 50 years. Women are more likely to suffer from IBS than men. IBS can be categorized into 3 groups based on the type of altered bowel movement: diarrhea-predominant IBS (IBS-D), constipation-predominant IBS (IBS-C) and IBS with mixed bowel habit (IBS-M). The contribution of the gut microbiome to the etiology of IBS is becoming increasingly recognized with rising use of anti-microbial agents. Previous studies on vancomycin and rifaximin used as monotherapy or in combination have been conducted mainly on IBS-C and showed marked improvements in the symptoms. According to our knowledge, no studies reported using these two combinations of antibiotics for IBS-D. Here, we report a consecutive cohort of 18 patients treated with both vancomycin and rifaximin for IBS-D. These patients’ records were reviewed retrospectively. In this cohort, patients ages were between 24-74 years (mean 44 years) and 9 were female. Baseline all patients had diarrhea, 4 with mucus and one with blood. Patients reported other symptoms were abdominal pain (n=11) bloating (n=9), flatulence (n=7), fatigue (n=4) and nausea (n=3). Patients treatments were personalized according to their symptom severity and tolerability and were treated with combination of rifaximin (500 - 3000mg/d) and vancomycin (500mg - 1500mg/d) for an ongoing period. Follow-ups were conducted between 2-32 weeks’ time. Of all patients, 89% patients reported improvement of the symptoms, 1 reported no change and 1 patient’s symptoms got worse. The mechanism of action for both vancomycin and rifaximin involves the inhibition of bacterial cell wall and protein synthesis respectively. The role of these medications in improving the symptoms of this cohort suggests that IBS-D may be microbiome infection driven. In this cohort, similar patient presentations to Clostridium difficile, as well as symptom improvement with the use of rifaximin and particularly vancomycin, suggest that the infectious agent may be an unidentified Clostridium. These preliminary results offer an alternative etiology for IBS-D not previously considered and open the avenue for new research.

Keywords: clostridium deficile, diarrhea predominant Irritable Bowel Syndrome, microbiome, vancomycin/rifaximin combination

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Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

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Authors: Pibool Waijittragum

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This paper has its objectives to reveal contents and personality suitable to women’s newspapers. The research methodology employed in this study is the questionnaire which is derived from a literature review related to newspapers, graphic elements method for print media design and 12 sample sizes of different daily newspapers. In order to acquire an in-depth understanding and comprehensible view of desirable for a women’s newspaper design, graphic elements that related to that personality as well as other preferable elements for a women’s newspaper, including seven editorial Many Thai newspapers were offer a women’s documentary and column space. With its feminine looks, most of them appeared with warm tones and friendly mood through their headlines, contents, illustrations and graphics. The study found that most desirable personalities for a women’s newspaper design in Thailand are: Modern, Chic and Natural. Each personality has significant graphic elements as follows: 1. Modern: significant elements of modern personality comprises of the composition with graduation pattern which creates attractiveness by using an anomalous alignment layout grid and outstanding structure to create focal points and dynamic movement. Dark to black color that has narrowed, limited hue coupled with bright color tones. The round shape of the Thai font style was suitable for this concept. Such Thai fonts have harmonious proportion and consistent stroke with the urban-polite look. 2. Chic: significant elements of chic personality comprises of the proper composition with distinctive scale, using rhythmic repetition and a contrast of scale to draw in reader attention. Vivid and bright color tones with extensive hues coupled with similar color tones and round shape of the Thai font style with a light stroke and consistent line. 3. Natural: significant elements of natural personality comprises of the proper composition using rhythmic repetition that creates a focal point through striking images and harmonious perspective. Warm color tones with restricted hues that appear to look natural. Duo tone color was suitable through the gradually increasing gradient. The Thai style with hand writing font was suitable through the inconsistent stroke. There are 10 types of daily content that were revealed to be the most desirable for Thai women readers, these are: Daily News, Economics News, Education News, Entertainment News, International news, Political News, Public Health News, Scientific News, Social News and Sports News. As well, there are 16 topics identified as very desirable for Thai women readers, such as: Art and Culture, Automobile, Classified, Special Scoop, Editorial, Advertisement, Entertainment, Health and Quality of Life, History, Horoscope, Lifestyle and Fashion, Literature, Nature - Environment and Tourism, Night Life, Stars and Jet Set Gossip, Women’s Issue.

Keywords: women behaviors, feminine looks, newspaper design, news content

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Geliashvili T. M., Tyulyandina A. S., Valiev A. K., Kononets P. V., Kharatishvili T. K., Salkov A. G., Pronin A. I., Gadzhieva E. H., Parnas A. V., Ilyakov V. S.

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Aim/Introduction: Metastasis (Mts) to the sternum, while extremely rare in differentiated thyroid cancer (DTC) (1), requires a personalized, multidisciplinary treatment approach. In aggressively growing Mts to the sternum, which rapidly become unresectable, a comprehensive therapeutic and diagnostic approach is particularly important. Materials and methods: We present a clinical case of solitary Mts to the sternum as first manifestation of a papillary thyroid microcarcinoma in a 55-year-old man. Results: 18F-FDG PET/CT after thyroidectomy confirmed the solitary Mts to the sternum with extremely high FDG uptake (SUVmax=71,1), which predicted its radioiodine-refractory (RIR). Due to close attachment to the mediastinum and rapid growth, Mts was considered unresectable. During the next three months, the patient received targeted therapy with the tyrosine kinase inhibitor (TKI) Lenvatinib 24 mg per day. 1st course of radioiodine therapy (RIT) 6 GBq was also performed, the results of which confirmed the RIR of the tumor process. As a result of systemic therapy (targeted therapy combined with RIT and suppressive hormone therapy with L-thyroxine), there was a significant biochemical response (decrease of serum thyroglobulin level from 50,000 ng/ml to 550 ng/ml) and a partial response with decrease of tumor size (from 80x69x123 mm to 65x50x112 mm) and decrease of FDG accumulation (SUVmax from 71.1 to 63). All of this made possible to perform surgical treatment of Mts - sternal extirpation with its replacement by an individual titanium implant. At the control examination, the stimulated thyroglobulin level was only 134 ng/ml, and PET/CT revealed postoperative areas of 18F-FDG metabolism in the removed sternal Mts. Also, 18F-FDG PET/CT in the early (metabolic) stage revealed two new bone Mts (in the area of L3 SUVmax=17,32 and right iliac bone SUVmax=13,73), which, as well as the removed sternal Mts, appeared to be RIRs at the 2nd course of RIT 6 GBq. Subsequently, on 02.2022, external beam radiation therapy (EBRT) was performed on the newly identified oligometastatic bone foci. At present, the patient is under dynamic monitoring and in the process of suppressive hormone therapy with L-thyroxine. Conclusion: Thus, only due to the early prescription of targeted TKI therapy was it possible to perform surgical resection of Mts to the sternum, thereby improve the patient's quality of life and preserve the possibility of radical treatment in case of oligometastatic disease progression.

Keywords: differentiated thyroid cancer, metastasis to the sternum, radioiodine therapy, radioiodine-refractory cancer, targeted therapy, lenvatinib

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: Emma J. Dale, Christina D. Buesching, Kevin R. Theis, David W. Macdonald

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This study investigates the oral and intestinal microbiomes of wild-living European badgers (Meles meles) and will relate inter-individual differences to social contact networks, somatic and reproductive fitness, varying susceptibility to bovine tuberculous (bTB) and to the olfactory advertisement. Badgers are an interesting model for this research, as they have great variation in body condition, despite living in complex social networks and having access to the same resources. This variation in somatic fitness, in turn, affects breeding success, particularly in females. We postulate that microbiota have a central role to play in determining the successfulness of an individual. Our preliminary results, characterising the microbiota of individual badgers, indicate unique compositions of microbiota communities within social groups of badgers. This basal information will inform further questions related to the extent microbiota influence fitness. Hitherto, the potential role of microbiota has not been considered in determining host condition, but also other key fitness variables, namely; communication and resistance to disease. Badgers deposit their faeces in communal latrines, which play an important role in olfactory communication. Odour profiles of anal and subcaudal gland secretions are highly individual-specific and encode information about group-membership and fitness-relevant parameters, and their chemical composition is strongly dependent on symbiotic microbiota. As badgers sniff/ lick (using their Vomeronasal organ) and over-mark faecal deposits of conspecifics, these microbial communities can be expected to vary with social contact networks. However, this is particularly important in the context of bTB, where badgers are assumed to transmit bTB to cattle as well as conspecifics. Interestingly, we have found that some individuals are more susceptible to bTB than are others. As acquired immunity and thus potential susceptibility to infectious diseases are known to depend also on symbiotic microbiota in other members of the mustelids, a role of particularly oral microbiota can currently not be ruled out as a potential explanation for inter-individual differences in infection susceptibility of bTB in badgers. Tri annually badgers are caught in the context of a long-term population study that began in 1987. As all badgers receive an individual tattoo upon first capture, age, natal as well as previous and current social group-membership and other life history parameters are known for all animals. Swabs (subcaudal ‘scent gland’, anal, genital, nose, mouth and ear) and fecal samples will be taken from all individuals, stored at -80oC until processing. Microbial samples will be processed and identified at Wayne State University’s Theis (Host-Microbe Interactions) Lab, using High Throughput Sequencing (16S rRNA-encoding gene amplification and sequencing). Acknowledgments: Gas-Chromatography/ Mass-spectrometry (in the context of olfactory communication) analyses will be performed through an established collaboration with Dr. Veronica Tinnesand at Telemark University, Norway.

Keywords: communication, energetics, fitness, free-ranging animals, immunology

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Shalini TV, Gangadharan GG, Sriranjini S Jaideep, ASN Seshasayee, Awadhesh Pandit

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Introduction: Prakriti (body-mind constitution of an individual) is a conventional, customized and unique understanding of which is essential for the personalized medicine described in Ayurveda, Indian System of Medicine. Based on the Doshas( functional, bio humoral unit in the body), individuals are categorized into three major Prakriti- Vata, Pitta, and Kapha. The human gut microbiome hosts plenty of highly diverse and metabolically active microorganisms, mainly dominated by the bacteria, which are known to influence the physiology of an individual. Few researches have shown the correlation between the Prakriti and the biochemical parameters. In this study, an attempt was made to explore any correlation between the Prakriti (phenotype of an individual) with the Genetic makeup of the gut microbiome in healthy individuals. Materials and methods: 270 multi-ethnic, healthy volunteers of both sex with the age group between 18 to 40 years, with no history of antibiotics in the last 6 months were recruited into three groups of Vata, Pitta, and Kapha. The Prakriti of the individual was determined using Ayusoft, a software designed by CDAC, Pune, India. The volunteers were subjected to initial screening for the assessment of their height, weight, Body Mass Index, Vital signs and Blood investigations to ensure they are healthy. The stool and saliva samples of the recruited volunteers were collected as per the standard operating procedure developed, and the bacterial DNA was isolated using Qiagen kits. The extracted DNA was subjected to 16s rRNA sequencing using the Illumina kits. The sequencing libraries are targeting the variable V3 and V4 regions of the 16s rRNA gene. Paired sequencing was done on the MiSeq system and data were analyzed using the CLC Genomics workbench 11. Results: The 16s rRNA sequencing of the V3 and V4 regions showed a diverse pattern in both the oral and stool microbial DNA. The study did not reveal any specific pattern of bacterial flora amongst the Prakriti. All the p-values were more than the effective alpha values for all OTUs in both the buccal cavity and stool samples. Therefore, there was no observed significant enrichment of an OTU in the patient samples from either the buccal cavity or stool samples. Conclusion: In healthy volunteers of multi-ethnicity, due to the influence of the various factors, the correlation between the Prakriti and the gut microbiome was not seen.

Keywords: gut microbiome, ayurveda Prakriti, sequencing, multi-ethnic urban population

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

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Authors: Shaun G. Abbott, Rebecca C. Reynolds, John B. F. de Wit

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Low physical activity (PA) levels are a major public health concern in Australia. There is some evidence that PA interventions can increase PA levels via various methods, including online delivery. Low Socioeconomic Status (SES) people participate in less PA than the rest of the population, partly due to poor self-regulation behaviors associated with socioeconomic characteristics. Interventions that involve a particular method of self-regulation, Mental Contrasting with Implementation Intentions (MCII), has regularly achieved healthy behavior change, but few studies focus on PA behavior outcomes and no studies examining the effect of MCII on the PA behaviors of low SES people has been done. In this study, a pilot randomized controlled trial (RCT) will deliver MCII for PA behavior change to individuals of relative disadvantage for the first time. The current pilot study will predict sample size for a future full RCT and test the hypothesis that sedentary participants from areas of relative socioeconomic disadvantage of Sydney, who learn the MCII technique will be more physically active, have improved anthropometry and psychological indicators at the completion of a 12-week intervention compared to baseline and control. Eligible participants of relative socioeconomic disadvantage will be randomly assigned to either the ‘PA Information Plus MCII Intervention Group’ or a ‘PA Information-Only Control Group’. Both groups will attend a baseline and 12-week face-to-face consultation; where PA, anthropometric and psychological data will be gathered. The intervention group will be guided through an MCII session at the baseline appointment to establish a PA goal to aim to achieve over 12 weeks. Other than these baseline and 12-week consultations, all participant interaction will occur online. All participants will receive a ‘Fitbit’ accelerometer to record objectively. PA as a daily step count, along with a PA diary for the duration of the study. PA data will be recorded on a personalized online spreadsheet. Both groups will receive a standard PA information email at weeks 2, 4, and 8. The intervention group will also receive scripted follow-up online appointments to discuss goal progress. The current pilot study is in recruitment stage with findings to be presented at the conference in December if selected.

Keywords: implementation intentions, mental contrasting, motivation, pedometer, physical activity, socioeconomic

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Authors: Elvan G. Bulut, Betul Goksun, Tugba G. Gun, Ozge Sakiyan Demirkol, Kamuran Ayhan, Kezban Candogan

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Dysphagia, difficulty in swallowing solid foods and thin liquids, is one of the common health threats among the elderly who require foods with modified texture in their diet. Although there are some commercial food formulations or hydrocolloids to thicken the liquid foods for dysphagic individuals, there is still a need for developing and offering new food products with enriched nutritional, textural and sensory characteristics to safely nourish these patients. 3D food printing is an appealing alternative in creating personalized foods for this purpose with attractive shape, soft and homogenous texture. In order to modify texture and prevent phase separation, hydrocolloids are generally used. In our laboratory, an optimized 3D printed beef-based formulation specifically for people with swallowing difficulties was developed based on the research project supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK Project # 218O017). The optimized formulation obtained from response surface methodology was 60% beef powder, 5.88% gelatin, and 0.74% kappa-carrageenan (all in a dry basis). This product was enriched with powders of freeze-dried beet, celery, and red capia pepper, butter, and whole milk. Proximate composition (moisture, fat, protein, and ash contents), pH value, CIE lightness (L*), redness (a*) and yellowness (b*), and color difference (ΔE*) values were determined. Counts of total mesophilic aerobic bacteria (TMAB), lactic acid bacteria (LAB), mold and yeast, total coliforms were conducted, and detection of coagulase positive S. aureus, E. coli, and Salmonella spp. were performed. The 3D printed products had 60.11% moisture, 16.51% fat, 13.68% protein, and 1.65% ash, and the pH value was 6.19, whereas the ΔE* value was 3.04. Counts of TMAB, LAB, mold and yeast and total coliforms before and after 3D printing were 5.23-5.41 log cfu/g, < 1 log cfu/g, < 1 log cfu/g, 2.39-2.15 log EMS/g, respectively. Coagulase positive S. aureus, E. coli, and Salmonella spp. were not detected in the products. The data obtained from this study based on determining some important product characteristics of functional beef-based formulation provides an encouraging basis for future research on the subject and should be useful in designing mass production of 3D printed products of similar composition.

Keywords: beef, dysphagia, product characteristics, texture-modified foods, 3D food printing

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Authors: Belyihun Muchie

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This study investigates the low English oral communication skills of 5 second-year English major students at Debark University. It aims to identify the key factors contributing to their weaknesses and propose effective interventions to improve their spoken English proficiency. Mixed-methods research will be employed, utilizing observations, questionnaires, and semi-structured interviews to gather data from the participants. To clearly identify these factors, structured and informal observations will be employed; the former will be used to identify their fluency, pronunciation, vocabulary use, and grammar accuracy, and the later will be suited to observe the natural interactions and communication patterns of learners in the classroom setting. The questionnaires will assess their self-perceptions of their skills, perceived barriers to fluency, and preferred learning styles. Interviews will also delve deeper into their experiences and explore specific obstacles faced in oral communication. Data analysis will involve both quantitative and qualitative responses. The structured observation and questionnaire will be analyzed quantitatively, whereas the informal observation and interview transcripts will be analyzed thematically. Findings will be used to identify the major causes of low oral communication skills, such as limited vocabulary, grammatical errors, pronunciation difficulties, or lack of confidence. They are also helpful to develop targeted solutions addressing these causes, such as intensive pronunciation practice, conversation simulations, personalized feedback, or anxiety-reduction techniques. Finally, the findings will guide designing an intervention plan for implementation during the action research phase. The study's outcomes are expected to provide valuable insights into the challenges faced by English major students in developing oral communication skills, contribute to the development of evidence-based interventions for improving spoken English proficiency in similar contexts, and offer practical recommendations for English language instructors and curriculum developers to enhance student learning outcomes. By addressing the specific needs of these students and implementing tailored interventions, this research aims to bridge the gap between theoretical knowledge and practical speaking ability, equipping them with the confidence and skills to flourish in English communication settings.

Keywords: oral communication skills, mixed-methods, evidence-based interventions, spoken English proficiency

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Authors: Frans J. Smit, Wisdom A. Munzeiwa, Hermanus C. M. Vosloo, Lyn-Marie Birkholtz, Richard K. Haynes

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Malaria and antimicrobial infections remain significant global health concerns, necessitating the continuous search for novel therapeutic approaches. This abstract presents an overview of the potential use of triazenes as effective agents against malaria and various antimicrobial pathogens. Triazenes are a class of compounds characterized by a linear arrangement of three nitrogen atoms, rendering them structurally distinct from their cyclic counterparts. This study investigates the efficacy of triazenes against malaria and explores their antimicrobial activity. Preliminary results revealed significant antimalarial activity of the triazenes, as evidenced by in vitro screening against P. falciparum, the causative agent of malaria. Furthermore, the compounds exhibited broad-spectrum antimicrobial activity, indicating their potential as effective antimicrobial agents. These compounds have shown inhibitory effects on various essential enzymes and processes involved in parasite survival, replication, and transmission. The mechanism of action of triazenes against malaria involves interactions with critical molecular targets, such as enzymes involved in the parasite's metabolic pathways and proteins responsible for host cell invasion. The antimicrobial activity of the triazenes against bacteria and fungi was investigated through disc diffusion screening. The antimicrobial efficacy of triazenes has been observed against both Gram-positive and Gram-negative bacteria, as well as multidrug-resistant strains, making them potential candidates for combating drug-resistant infections. Furthermore, triazenes possess favourable physicochemical properties, such as good stability, solubility, and low toxicity, which are essential for drug development. The structural versatility of triazenes allows for the modification of their chemical composition to enhance their potency, selectivity, and pharmacokinetic properties. These modifications can be tailored to target specific pathogens, increasing the potential for personalized treatment strategies. In conclusion, this study highlights the potential of triazenes as promising candidates for the development of novel antimalarial and antimicrobial therapeutics. Further investigations are necessary to determine the structure-activity relationships and optimize the pharmacological properties of these compounds. The results warrant additional research, including MIC studies, to further explore the antimicrobial activity of the triazenes. Ultimately, these findings contribute to the development of more effective strategies for combating malaria and microbial infections.

Keywords: malaria, anti-microbials, triazene, resistance

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Authors: T. Suleiman, C. Mchugh, H. Ranu

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Background; Asthma continues to be associated with poor patient outcomes, including mortality. An audit of the management of acute asthma admissions in our hospital in 2020 found poor compliance with National Asthma and COPD Audit Project (NACAP) standards which set out to improve inpatient asthma care. Clinical nurse specialists have been shown to improve patient care across a range of specialties. In September 2021, an asthma Nurse Specialist (ANS) was employed in our hospital. Aim; To re-audit management of acute asthma admissions using NACAP standards and assess for quality improvement post-employment of an ANS. Methodology; NACAP standards are wide-reaching; therefore, we focused on ‘specific elements of good practice’ in addition to the provision of inhaled corticosteroids (ICS) on discharge. Medical notes were retrospectively requested from the hospital coding department and selected as per NACAP inclusion criteria. Data collection and entry into the NACAP database were carried out. As this was a clinical audit, ethics approval was not required. Results; Cycle 1 (pre-ANS) and 2 (post-ANS) of the audit included 20 and 32 patients, respectively, with comparable baseline demographics. No patients had a discharge bundle completed on discharge in cycle 1 vs. 84% of cases in cycle 2. Regarding specific components of the bundle, 25% of patients in cycle 1 had their inhaler technique checked vs. 91% in cycle 2. Furthermore, 80% of patients had maintenance medications reviewed in cycle 1 vs. 97% in cycle 2. Medication adherence was addressed in 20% of cases in cycle 1 vs. 88% of cases in cycle 2. Personalized asthma action plans were not issued or reviewed in any cases in cycle 1 as compared with 84% of cases in cycle 2. Triggers were discussed in 30% of cases in cycle 1 vs. 88% of cases in cycle 2. Tobacco dependence was addressed in 44% of cases in cycle 1 vs. 100% of cases in cycle 2. No patients in cycle 1 had community follow-up requested within 2 days vs. 81% of the patients in cycle 2. Similarly, 20% of the patients in cycle 1 vs. 88% of the patients in cycle 2 had a 4-week asthma clinic follow-up requested. 75% of patients in cycle 1 were the recipient of ICS on discharge compared with 94% of patients in cycle 2. Conclusion; Our quality improvement project demonstrates the utility of an ANS in improving performance in the management of acute asthma admissions, evidenced here through concordance with NACAP standards. Asthma is a complex condition with biological, psychological, and sociological components; therefore, ANS is a suitable intervention to improve concordance with guidelines. ANS likely impacted performance directly, for example, by checking inhaler technique, and indirectly as a safety net ensuring doctors included ICS on discharge.

Keywords: asthma, nurse specialist, clinical audit, quality improvement

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Authors: Jia Guo, Qinyuan Huang, Qinyi Zhong, Yanjing Zeng, Yimeng Li, James Wiley, Kin Cheung, Jyu-Lin Chen

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Context: Mothers with abdominal obesity, particularly in China, face challenges in managing their health due to family responsibilities. Existing diabetes prevention programs do not cater specifically to this demographic. Research Aim: To assess the feasibility, acceptability, and efficacy of an mHealth-based diabetes prevention program tailored for Chinese mothers with abdominal obesity in reducing weight-related variables and diabetes risk. Methodology: A randomized controlled trial was conducted in Changsha, China, where the mHealth group received personalized modules and health messages, while the control group received general health education. Data were collected at baseline, 3 months, and 6 months. Findings: The mHealth intervention significantly improved waist circumference, modifiable diabetes risk scores, daily steps, self-efficacy for physical activity, social support for physical activity, and physical health satisfaction compared to the control group. However, no differences were found in BMI and certain other variables. Theoretical Importance: The study demonstrates the feasibility and efficacy of a tailored mHealth intervention for Chinese mothers with abdominal obesity, emphasizing the potential for such programs to improve health outcomes in this population. Data Collection: Data on various variables including weight-related measures, diabetes risk scores, behavioral and psychological factors were collected at baseline, 3 months, and 6 months from participants in the mHealth and control groups. Analysis Procedures: Generalized estimating equations were used to analyze the data collected from the mHealth and control groups at different time points during the study period. Question Addressed: The study addressed the effectiveness of an mHealth-based diabetes prevention program tailored for Chinese mothers with abdominal obesity in improving various health outcomes compared to traditional general health education approaches. Conclusion: The tailored mHealth intervention proved to be feasible and effective in improving weight-related variables, physical activity, and physical health satisfaction among Chinese mothers with abdominal obesity, highlighting its potential for delivering diabetes prevention programs to this population.

Keywords: type 2 diabetes, mHealth, obesity, prevention, mothers

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Authors: Mehrnaz Mostafavi, Alireza Azani, Mahtab Shabani, Fatemeh Ghafari

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While filled with promise and wonder, space exploration also presents significant challenges, one of the foremost being the threat of cosmic radiation to astronaut health. Recent advancements in assessing these risks and developing protective strategies have shed new light on this issue. Cosmic radiation encompasses a variety of high-energy particles originating from sources like solar particle events, galactic cosmic rays, and cosmic rays from beyond the solar system. These particles, composed of protons, electrons, and heavy ions, pose a substantial threat to human health in space due to the lack of Earth's protective atmosphere and magnetic field. Researchers have made significant progress in assessing the risks associated with cosmic radiation exposure. By employing advanced dosimetry techniques and conducting biological studies, they have gained insights into how cosmic radiation affects astronauts' health, including increasing the risk of cancer and radiation sickness. This research has led to personalized risk assessment methods tailored to individual astronaut profiles. Distinctive protection strategies have been proposed to combat the dangers of cosmic radiation. These include developing spacecraft shielding materials and designs to enhance radiation protection. Additionally, researchers are exploring pharmacological interventions such as radioprotective drugs and antioxidant therapies to mitigate the biological effects of radiation exposure and preserve astronaut well-being. The findings from recent research have significant implications for the future of space exploration. By advancing our understanding of cosmic radiation risks and developing effective protection strategies, we pave the way for safer and more sustainable human missions beyond Earth's orbit. This is especially crucial for long-duration missions to destinations like Mars, where astronauts will face prolonged exposure to cosmic radiation. In conclusion, recent research has marked a milestone in addressing the challenges posed by cosmic radiation in space exploration. By delving into the complexities of cosmic radiation exposure and developing innovative protection strategies, scientists are ensuring the health and resilience of astronauts as they venture into the vast expanse of the cosmos. Continued research and collaboration in this area are essential for overcoming the cosmic radiation challenge and enabling humanity to embark on new frontiers of exploration and discovery in space.

Keywords: Space exploration, cosmic radiation, astronaut health, risk assessment, protective strategies

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Authors: Mekroud Amel

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Introduction The rate of use by the elderly of emergency departments, operating rooms and intensive care units has increased worldwide. Emergency surgery is a context where evaluation is often insufficient, with incomplete information gathering. The aim of this work is to shed light on the frequent use of emergency surgeries by the elderly and their characteristics, as well as on the lack of geriatric assessment scores in the emergency room. Material : Prospective, observational and descriptive, monocentric study. Patients aged 65 and over, admitted for emergency surgery in the operating room, were counted. Emergency operating room including visceral surgery, urology, traumatology and neurosurgery. Parameters studied: Patient characteristics, degree of autonomy, type of surgical pathology, operative management times, preoperative evaluation, postoperative outcome Results : 192 patients were identified over 12 months, from 09.01.2017 to 08.31.2018 Age from 65 to 101 years, 79.81 years +/- 8.38. With predominance of the age group between [65-75 years] 41.1% Female predominance, Sexratio = 0.81 Elderly subjects with total motor autonomy are in the majority at 57.8% Subjects without pathological ATCD represent 12.5% of cases Those who are on only one type of medication or without any treatment are at 36.9% Discussion : The emergency operative care of the elderly patient for a surgical or traumatological pathology is characterized by many specificities linked first to the emergency context, where the evaluation is often insufficient, besides the fact that the elderly patient has particularities requiring reception in centers with experience in the care of this category of patient, or, failing that, a center which uses the minimum of geriatric evaluation scores which are simplified for the emergency departments. In our hospital, we have not yet made this evaluation routine in the emergency room and this delay in the introduction of these scores can be directly attributed to the covid 19 pandemic. Besides the standard preoperative assessment, only 43.2% of patients were assessed in the preoperative period by an anesthesiologist. Traumatological emergencies come first 68.2% followed by visceral emergencies 19.2% (including proctological, urological emergencies), neurosurgical emergencies 7.8% and finally peripheral emergency surgery all acts combined 4.7%. Hospital stay at 9.6 +/- 16.8 days, average operability time of 4.5 +/- 3 days. Death rate at 7.29% Conclusion This work has demonstrated the major impact of emergency surgery, which remains curable for the most part, on the elderly patient despite total motor and cognitive autonomy preoperatively. The improvement of the preoperative evaluation, the reduction of the operating time and enhanced recovery after surgery, with personalized protocols, are the only guarantee for the resumption of preoperative autonomy in these patients.

Keywords: emergency surgery, elderly patients, preoperative geriatric scores, curable emergency surgical pathologies

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Authors: Emílie Kučerová, Tereza Veverková, Marina Morozovová, Eva Kudová, Jitka Viktorová

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The blood-brain barrier (BBB) is a key element regulating the transport of substances between the blood and the central nervous system (CNS). The BBB protects the CNS from potentially harmful substances and maintains a suitable environment for nervous activity in the CNS, but at the same time, it represents a significant obstacle to the entry of drugs into the CNS. Pharmacoresistant epilepsy is a form of epilepsy that cannot be suppressed using two (or more) appropriately chosen antiepileptic drugs. In many cases, pharmacoresistant epilepsy is characterized by an increased concentration of efflux pumps on the luminal sides of the endothelial cells that form the BBB and an increased number of drug-metabolizing enzymes in the BBB cells, thereby preventing the effective transport of antiepileptic drugs into the CNS. Currently, a number of scientific groups are focusing on the preparation and improvement of BBB models in vitro in order to study cell interactions or transport mechanisms. However, in pathological conditions such as pharmacoresistant epilepsy, there are changes in BBB structure, and current BBB models are insufficient for related research. Our goal is to develop a suitable BBB model for pharmacoresistant epilepsy in vitro and use it to test the transfer of potential antiepileptic drugs. This model is created by co-culturing immortalized human cerebral microvascular endothelial cells, human vascular pericytes and immortalized human astrocytes. The BBB in vitro is cultivated in the form of a 2D transwell model and the integrity of the barrier is verified by measuring transendothelial electrical resistance (TEER). From the current results, a contact cell arrangement with the cultivation of endothelial cells on the upper side of the insert and the co-cultivation of astrocytes and pericytes on the lower side of the insert is selected as the most promising for BBB model cultivation. The pharmacoresistance of the BBB model is achieved by long-term cultivation of endothelial cells in an increasing concentration of selected antiepileptic drugs, which should lead to increased production of efflux pumps and drug-metabolizing enzymes. The pharmacoresistant BBB model in vitro will be further used for the screening of substances that could act both as antiepileptics and at the same time as inhibitors of efflux pumps in endothelial cells. This project was supported by the Technology Agency of the Czech Republic (TACR), Personalized Medicine: Translational research towards biomedical applications, No. TN02000109 and by the Academy of Sciences of the Czech Republic (AS CR) – grant RVO 61388963.

Keywords: antiepileptic drugs, blood-brain barrier, efflux transporters, pharmacoresistance

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Authors: Clement Yeboah, Eva Laryea

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A pretest-posttest within subjects experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant, indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant, indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop an interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, computer game-based learning, statistics achievement, statistics anxiety

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Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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Authors: Tianjie Zhang, Bingqian Cheng, Peng Zeng

Abstract:

Engineering science and technology progress and innovation have become an important engine to promote social development. The reform exploration of "new engineering" in China has drawn extensive attention around the world, with its connotation as "to cultivate future diversified, innovative and outstanding engineering talents by taking ‘fostering character and civic virtue’ as the guide, responding to changes and shaping the future as the construction concept, and inheritance and innovation, crossover and fusion, coordination and sharing as the principal approach". In this context, Tianjin University, as a traditional Chinese university with advantages in engineering, further launched the CCII (Coherent-Collaborative-Interdisciplinary-Innovation) program, raising the cultivation idea of integrating new liberal arts education, multidisciplinary engineering education and personalized professional education. As urban planning practice in China has undergone the evolution of "physical planning -- comprehensive strategic planning -- resource management-oriented planning", planning education has also experienced the transmutation process of "building foundation -- urban scientific foundation -- multi-disciplinary integration". As a characteristic and advantageous discipline of Tianjin University, the major of Urban and Rural Planning, in accordance with the "CCII Program of Tianjin University", aims to build China's top and world-class major, and implements the following educational reform measures: 1. Adding corresponding English courses, such as advanced course on GIS Analysis, courses on comparative studies in international planning involving ecological resources and the sociology of the humanities, etc. 2. Holding "Academician Forum", inviting international academicians to give lectures or seminars to track international frontier scientific research issues. 3. Organizing "International Joint Workshop" to provide students with international exchange and design practice platform. 4. Setting up a business practice base, so that students can find problems from practice and solve them in an innovative way. Through these measures, the Urban and Rural Planning major of Tianjin University has formed a talent training system with multi-disciplinary cross integration and orienting to the future science and technology.

Keywords: China, higher education reform, innovation, new engineering education, rural and urban planning, Tianjin University

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