bluuebunny/crossref_metadata_2025 huggingface dataset:
PRELIMINARY STUDY OF ANTIOXIDANT ACTIVITY OF DRAGONFRUIT, DATES AND KEFIR MIXTURES
Authors: Ajrina Amalia
Published: March 2022

Background: Some previous studies showed that either dragon fruit, dates, or kefir has antioxidant activity. Nevertheless, there has not been any study that showed the activity of the combination of those three elements. Purpose: Therefore, the main purpose of this study is to examine the best combination of dragon fruit, dates, and kefir as an antioxidant activity. Method: The combination variation includes: dragon fruit-dates, dragon fruit-kefir, kefir-dates, and dragon fruit-dates-kefir. Then, the antioxidant activity was tested using the DPPH assay. Result: The variation of dragon fruit and dates, the highest value of antioxidant activity was obtained from the combination of 10: 2 of dragon fruits: dates; that was 76.33 ± 0.27 mg/dL. The combination of dragon fruit and kefir, the highest value was obtained from the variation of 10: 4 of dragon fruit: kefir. For this variation, the antioxidant activity was 80.9 ± 0.4 mg/dL. The combination of kefir and dates, the highest value was obtained from the variation of 10: 3 of kefir: dates. The combination of dragon fruit, dates, and kefir, the highest value of antioxidant activity was obtained from the combination of 4: 10: 1 of dragon fruit: kefir: dates; that was 80.94 ± 0.4 mg/dL. Conclusion: In summary, the highest antioxidant activity came from the combination variation of 4: 10: 1 of dragon fruit: kefir: dates.
ANTIBACTERIAL ACTIVITY OF MANGOSTEEN BARK FRACTION (GARCINIA MANGOSTANA L.) SALMONELLA TYPHI ATCC 13311
Authors: Anggraini Salmah Wilujeng , Erikania Susanti , Maritha Vevi
Published: March 2022

Background: Typhoid fever is caused by Salmonella typhi bacterial infection which spreads via the faecal-oral route and has epidemic potential. Salmonella typhi is a Gram-negative bacterium in the Enterobacteriaceae family. Currently, the use of natural ingredients can be an alternative treatment for typhoid fever, one of which is the mangosteen stem skin (Garcinia mangostana L.). Purpose: To determine the antibacterial activity of mangosteen stem skin fraction against Salmonella typhi ATCC 13311. Method:The maceration method was selected using methanol solvent and fractionation by ECC using ethyl acetate and n-hexane as solvents. This study used five treatments (fraction with a concentration of 20%, 40%, 80%, chloramphenicol 30µg as a positive control, and DMSO as a negative control) which tested their antibacterial activity against Salmonella typhi ATCC 13311 by disc diffusion. Result: The results showed that the ethyl acetate fraction of mangosteen stem skin had the greatest average inhibition zone, that is 13.86 ± 0.72 mm compared to the n-hexane fraction of mangosteen stem skin with an inhibition zone of 10.43 ± 0.73 mm. The data obtained were then analyzed with One-way ANOVA. Conclusion: The results obtained were p=0.000 (sig <0.05), indicating that there was a significant difference between the ethyl acetate fraction and the n-hexane fraction with 20%, 60%, and 80% concentrations with positive control
THE EFFECTIVENESS OF ACUPUNCTURE ON ORTHOPAEDIC PAIN WITHIN A VOCATIONAL REHABILITATION SETTING
Authors: Chetty Laran
Published: March 2022

Background: Acupuncture is rapidly rising in popularity within western populations since its development and consequently there is increasing interest from a variety of clients. Purpose: To evaluate the effectiveness of acupuncture on orthopaedic pain within a vocational rehabilitation setting in London, United Kingdom. Method: A retrospective service evaluation design. A pre- and post-acupuncture questionnaire was utilised as the data collection tool. Result: Eighty-six clients were included in this evaluation because they met the criteria for inclusion. Analysis on the age differences between males and females were not statistically significant (p=0.05). The conditions that were most frequently seen at the clinic included: 57% (49/86) spinal pain; 28% (24/86) upper limb pain; and 15% (13/86) lower limb pain. The mean number of treatment sessions for acupuncture was three (range=1-6). Overall each session of treatment lasted on average twenty minutes (range=15-30). The total number of needles used during each session of treatment averaged five (range=3-8). The reported benefit of treatment was 44% (38/86) excellent, 49% (42/86) good, and 7% (6/86) poor. Conclusion: This evaluation has demonstrated that acupuncture is effective on orthopaedic pain within a vocational rehabilitation setting. Repeat audits and larger sample sizes are needed for confirmation the findings.
THE ROLE OF ACUPUNCTURE THERAPY TO OVERCOME ONE-SIDE HEAD PAIN (MIGRAINE)
Authors: Mainnah Mut , Septriana Maya , Wurlina Wurlina
Published: March 2022

Background: Migraine is a primary headache, usually described as pain attacks lasting 4 - 72 hours, unilateral, throbbing, with moderate to severe pain intensity that can be exacerbated by activity, and can be accompanied by nausea and vomiting, photophobia and phonophobia. Migraine can interfere with patient activities, so that it can reduce productivity and result in an economic burden to the family and reduce the patient's quality of life. To handle it, pharmacological and non-pharmacological therapies can be used. Acupuncture therapy is one of the non-pharmacological therapeutic options that can be used in migraines. Purpose: This article review collects and analyzes journals related to the effect of acupuncture therapy on migraines. The journal search method was carried out electronically from December to April 2021 using several databases such as Pubmed, Sagepub and Google Schoolar with the keywords: acupuncture in cases of migraine, acupuncture for migraine, and acupuncture point for migraine. Review: The journal searches discovered that acupuncture therapy had an effect in reducing pain intensity in migraine cases with the most widely used method that was the manual acupuncture method. However, the most influential method was the combination method of manual acupuncture, herbal acupuncture, and nutritional therapy with the hyperactivity of Yang liver as the frequently occurring syndrome. The frequently used points were the acupuncture points of Fengchi-GB20, Hegu-LI4, Taichong-LR3, Baihui-DU20, Zusanli-ST36, Sanyinjiao-SP6, and Taiyang-EX-HN5.Conclusion: Based on the journal analyses, the combination method of manual acupuncture, herbal acupuncture, and nutritional therapy can reduce pain intensity in migraine cases
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward
Authors: Elyan Eyad , Vuttipittayamongkol Pattaramon , Johnston Pamela , Martin Kyle , McPherson Kyle , Moreno-García Carlos Francisco , Jayne Chrisina , Mostafa Kamal Sarker Md.
Published: March 2022

The recent development in the areas of deep learning and deep convolutional neural networks has significantly progressed and advanced the field of computer vision (CV) and image analysis and understanding. Complex tasks such as classifying and segmenting medical images and localising and recognising objects of interest have become much less challenging. This progress has the potential of accelerating research and deployment of multitudes of medical applications that utilise CV. However, in reality, there are limited practical examples being physically deployed into front-line health facilities. In this paper, we examine the current state of the art in CV as applied to the medical domain. We discuss the main challenges in CV and intelligent data-driven medical applications and suggest future directions to accelerate research, development, and deployment of CV applications in health practices. First, we critically review existing literature in the CV domain that addresses complex vision tasks, including: medical image classification; shape and object recognition from images; and medical segmentation. Second, we present an in-depth discussion of the various challenges that are considered barriers to accelerating research, development, and deployment of intelligent CV methods in real-life medical applications and hospitals. Finally, we conclude by discussing future directions.
Determination of the Fundamental Lateral Bending Mode Frequency of a Spacecraft from its Static Deflection
Authors: Renji K. , Varghese C.S. , Kumar I. Prasanna
Published: March 2022

The primary structure of a spacecraft that involves the central cylinder is designed to meet a specific value of fundamental lateral mode frequency. Though this frequency can be theoretically estimated by using a finite element model, its experimental verification is only possible when the entire spacecraft is made ready. However, static load tests are done on the primary structure of the spacecraft as soon as the structure is realized. In this work, a methodology to determine the fundamental bending mode frequency of a spacecraft from the deflections measured when the structure alone is subjected to static load tests is developed. An expression relating the fundamental lateral bending mode frequency of a spacecraft, having several masses attached at different locations, and the deflection at its tip is derived. Two spacecraft, one of 3000kg class and the other of 6000kg class are taken as examples. The fundamental lateral frequencies are determined using this methodology. These frequencies are also obtained through resonance search tests. It is shown that the derived expression will be very useful in estimating the fundamental lateral mode frequency of a spacecraft with the help of the measured deflection.
Context-Aware Complex Human Activity Recognition using Hybrid Deep Learning Models
Authors: Otebolaku Abayomi , Omolaja Adebola
Published: March 2022

Smart devices such as smartphones, smartwatches, etc. are promising platforms that are being used for automatic recognition of human activities. However, it is difficult to accurately monitor complex human activities due to inter-class pattern similarity, which occurs when different human activities exhibit similar signal patterns or characteristics. Current smartphone-based recognition systems depend on the traditional sensors such as accelerometer and gyroscope, which are inbuilt in these devices. Therefore, apart from using information from the traditional sensors, these systems lack contextual information to support automatic activity recognition. In this article, we explore environment contexts such as illumination(light conditions) and noise level to support sensory data obtained from the traditional sensors using a hybrid of Convolutional Neural Networks and Long Short Time Memory(CNN_LSTM) learning models. The models performed sensor fusion by augmenting the low-level sensor signals with rich contextual data to improve recognition and generalisation ability of the proposed solution. Two sets of experiments were performed to validate the proposed solution. The first set of experiments used inertial sensing data whilst the second set of extensive experiments combined inertial signals with contextual information from environment sensing data. Obtained results demonstrate that contextual information such as environment noise level and illumination using hybrid deep learning models achieved better recognition accuracy than the traditional activity recognition models without contextual information.
Моделирование воздушной ударной волны с использованием уравнений состояния продуктов детонации в форме Джонса-Уилкинса-Ли
Authors: Валько Виктор Васильевич , Valko Viktor Vasil'evich , Гасилов Владимир Анатольевич , Gasilov Vladimir Anatol'evich , Савенко Никита Олегович , Savenko Nikita Olegovich , Соловьeва Валентина Сергеевна , Solovyova Valentina Sergeevna
Published: March 2022

Описывается математическая модель распространения воздушной ударной волны, возникающей вследствие инициации вещества, обладающего высокой энергоeмкостью, и последующего течения смеси воздуха и газообразных продуктов детонации. Обсуждаются различные варианты оценки корректности набора констант, входящих в уравнение состояния продуктов детонации Джонса-Уилкинса-Ли (JWL). Приведены результаты модельных расчетов по предложенной методике, выполненных на структурированных и структурно-нерегулярных сетках. Полученные результаты сравниваются с аналитическими решениями модельных задач и расчетными данными, полученными с помощью коммерческих пакетов.
Об одном численном методе нахождения позиций ядер водорода и кислорода в кластере воды
Authors: Плохотников К Э , Plokhotnikov K E
Published: March 2022

Изложены итоги моделирования пространственных позиций ядер водорода и кислорода в кластере воды с точки зрения прямого вычислительного эксперимента.
Привлекается ранее разработанный автором способ численного решения уравнения
Шредингера, который основан на методе Монте-Карло. Указанный способ решения зарекомендовал себя в качестве весьма эффективного с точки зрения затрат машинного времени. Входными данными рассматриваемого метода выступают средние позиции частиц, входящих в квантовую систему, для расчета которых был разработан другой метод. В рамках метода построения средних позиций квантовых
частиц построено несколько энергетических изомеров кластеров воды. Именно эта
множественность вызывает основной теоретический интерес. Для целей проверки
методики была построена модель отдельной молекулы воды с общепринятой геометрией расположения частиц, а также так называемая геометрия развернутой молекулы воды. Приведенные в работе энергетические изомеры димера, тримера и
гексамера воды рассматриваются в качестве возможных геометрических конструкций кластеров воды и выступают в качестве иллюстрации использования предлагаемой методики расчета квантовых систем. Модель димера воды построена в виде
трех геометрических конструкций расположения ядер водорода и кислорода, условно названных квазидвумерная, в форме октаэдра и квазиодномерная. Модель
тримера воды свелась к обсуждению двух геометрий: трехмерной и квазидвумерной. Наконец, рассмотрена геометрия гексамера воды в форме октаэдра, в вершинах которого находятся ядра кислорода, а в центре размещены все двенадцать протонов. Под моделями кластеров воды понимается построение облаков рассеяния
всех входящих в кластер квантовых частиц.
Управление высокоскоростным течением в канале при помощи пористых вставок
Authors: Северин Александр Владимирович , Severin Alexander Vladimirovich , Луцкий Александр Евгеньевич , Lutsky Alexander Evgenjevich , Меньшов Игорь Станиславович , Menshov Igor Stanislavovich
Published: March 2022

Статья посвящена моделированию сверхзвукового течения газа в канале с пористыми вставками. В одном из вариантов удалось добиться исчезновения отрывной зоны в точке отражения ударной волны. В другом - уменьшения потерь давления торможения примерно на 4% в сравнении с контрольным расчетом, что создает принципиальную возможность существенного повышения эффективности гиперзвуковых прямоточных воздушно-реактивных двигателей.
Drug Consumption Rooms: Welfare State and Diversity in Social Acceptance in Denmark and in France
Authors: Houborg Esben , Jauffret-Roustide Marie
Published: March 2022

Drug consumption rooms (DCRs) have the potential to have a positive impact on the opioid overdose crisis. DCRs could also potentially change the political environment for public health because they can affect the distribution of responsibility for harm reduction between the individual and society by collectivizing responsibility for harm reduction through welfare regimes.

The methodology is based on 2 case studies—1 in Copenhagen, Denmark, and 1 in Paris, France—about residents, people who inject drugs (PWID), and politicians’ experiences of DCRs involving semidirective interviews. Denmark has a long history of harm-reduction policy, and the implementation of DCRs in Copenhagen has happened through close collaboration between local authorities and the local community. France is far more centralized and paternalistic in terms of the distribution of authority and decision-making in welfare and drug policy.

Difficulties in cohabitation between local residents and PWID happened in both countries and can sometimes make public authorities hesitate to implement DCRs because of the NIMBY (“not in my backyard”) phenomenon. However, the Danish and French case studies show that DCRs have the potential to become an instrument for civic cohabitation as well as to contribute to the destigmatization and health of PWID. (Am J Public Health. 2022;112(S2):S159–S165. https://doi.org/10.2105/AJPH.2022.306808 )
Parenting and child mental health during the COVID-19 pandemic: An online study with Portuguese and British Families
Authors: Pereira Ana Isabel
Published: March 2022

COVID-19 and the subsequent public health response created many additional stresses for families. We examined parental behaviour during the COVID-19 pandemic in two European Countries and explored the association between parents’ behaviour and children’s anxiety and quality of life. Caregivers of children and adolescents (N = 442; 86.7% mothers) between 6 and 16 years old (M = 10, SD = 2.85) participated in an online cross-sectional survey in Portugal and the United Kingdom. Results show that higher children’s anxiety and lower quality of life were associated with higher levels of unrealistic parental demands, lower parental self-care, and higher parental emotional dysregulation. Encouragement of children’s emotion expression and management of exposure to COVID-19 information was negatively associated with children’s anxiety. Promotion of routines, support of children’s emotion modulation and promotion of children’s healthy lifestyles were positively associated with children’s quality of life. The predictors differed according to country and age group. These results highlight the importance of specific parenting behaviours on children’s mental health during COVID-19. The need to moderate unrealistic demands and attend to parental self-care to reduce parental emotional dysregulation is important. Keywords: Parenting; child’s anxiety; child’s quality of life; COVID-19.
Streamline Tracing and Applications in Dual-Porosity Dual-Permeability Models
Authors: Onishi Tsubasa , Tanaka Shusei , Chen Hongquan , Kam Dongjae , Xie Jiang , Wang Zhiming , Wen Xian-huan , Datta-Gupta Akhil
Published: March 2022

Streamline-based methods have proven to be effective for various subsurface flow and transport modeling problems. However, the applications are limited in dual-porosity and dual-permeability (DPDK) system due to the difficulty in describing interactions between matrix and fracture during streamline tracing. In this work, we present a robust streamline tracing algorithm for DPDK models and apply the new algorithm to rate allocation optimization in a waterflood reservoir.

In the proposed method, streamlines are traced in both fracture and matrix domains. The interfluxes between fracture and matrix are described by switching streamlines from one domain to another using a probability computed based on the ratio of interfluxes to total fluxes within the domain. The approach is fundamentally similar to the existing streamline tracing technique and can be utilized in streamline-assisted applications, such as flow diagnostics, history matching, and production optimization.

The proposed method is benchmarked with a finite volume (FV)-based approach where grid-based time-of-flight (TOF) distributions were obtained by solving the stationary transport equation. We first validated our method using simple examples. Visual TOF comparisons as well as tracer concentration and allocation factors at wells show good agreement. Next, we applied the proposed method to field-scale models to demonstrate the robustness. The results show that our method offers reduced numerical artifacts and better represents reservoir heterogeneity and well connectivity with subgrid resolutions. The proposed method is then used for rate allocation optimization in DPDK models. A streamline-based gradient-free algorithm is used to optimize net present value (NPV) by adjusting both injection and production well rates under operational constraints. The results show that the optimized schedule offers significant improvement in recovery factor, NPV, and sweep efficiency compared to the base scenario using equal rate injection and production. The optimization algorithm is computationally efficient, as it requires only a few forward reservoir simulations.

A novelty of this work is the streamline tracing algorithm in DPDK reservoir models. The proposed method is simple and easy to implement to existing streamline-based frameworks and is applicable to field-scale reservoir models for flow diagnostics and rate allocation optimization.
Application of Novel Fruit Extract for Flow Assurance of Indian Field Waxy Crude Oil
Authors: Pal Biswadeep , Naiya Tarun
Published: March 2022

This research article deals with the application of shikakai fruit (Senegalia rugata) extract (SE) used as a novel bio-additive for improving flow properties of waxy crude oil (WCO) to reduce pumping cost during pipeline transportation. SE was synthesized using solvent extraction method, which is one of the most common economic extraction processes. Bio-additive was characterized by Fourier transform infrared spectroscopy (FTIR) spectroscopy, carbon, hydrogen, nitrogen, sulfur (CHNS) analysis, gas chromatography-mass gas chromatography-mass spectroscopy (GC-MS), differential light scattering, and thermogravimetric analysis (TGA). Pour point of WCO was decreased by 12°C due to addition of 1,000 ppm of SE on crude oil. Viscosity of WCO reduced significantly after addition of a bio-additive. It was found that viscosity of SE beneficiated crude oil (1,000 ppm dosage) at 30°C is less than that of pure crude at 50°C. So, addition of SE may be an alternative of heating during flow of WCO. Microscopic studies confirm that wax and other solid particles become smaller and more dispersive so that the particles are not able to come closer and form a three-dimensional network. Consequently, flow becomes easier and pumping cost gets reduced. Experimental data related to viscosity better fitted with Casson model and Bingham model before addition of SE depict that significant yield stress is required to restart the flow of crude oil. Due to the addition of SE, yield stress was deceased significantly and crude oil beneficiated with bio-additive tends to behave like a Newtonian fluid. This article also investigates wax deposition through laboratory-designed wax depositional setup. The wax deposition of crude oil after addition of 1,000 ppm SE was comparatively 56 and 75% lower than untreated crude oil when deposition studies were performed for 2 and 4 hours, respectively, at 25°C. Wax crystals of SE-treated crude oil decreased in diameter and disoriented the particles, preventing the formation of three-dimensional networks so that crude oil can easily flow through pipelines. Considering the efficacy of extracted bio-additive and its cost effectiveness, the same can be applied for flow assurance of WCO through pipelines even at very low temperatures.
ProHealth eCoach: User-Centered Design and Development of an eCoach App to Promote Healthy Lifestyle with Personalized Activity Recommendations
Authors: CHATTERJEE AYAN , Prinz Andreas , Gerdes Martin , Martinez Santiago , Pahari Nibedita , Meena Yogesh Kumar
Published: March 2022

Background
Regular physical activity (PA), healthy habits, and a healthy diet are recommended guidelines to maintain a healthy lifestyle. A healthy lifestyle can help to avoid chronic diseases and long-term illnesses. A monitoring and automatic personalized lifestyle recommendation system (i.e., automatic electronic coach or eCoach) with considering clinical and ethical guidelines, individual health status, condition, and preferences may successfully help participants to follow recommendations to maintain a healthy lifestyle. As a prerequisite for the prototype design of such a helpful eCoach system, it is essential to involve the end-users and subject-matter experts throughout the iterative design process.
Methods
We used an iterative user-centered design (UCD) approach with a dialogue-labs method to collect qualitative data from different users (i.e., researchers, non-technical and technical, health professionals, subject-matter experts, and potential end-users) to develop a roadmap for self-management with eCoaching. We designed and developed the eCoach prototype in two stages, adopting different phases of the UCD approach and co-design events. In UCD workshop 1, we focused on identifying end-users, understanding the user’s context, specifying user requirements, designing and developing an initial low-fidelity eCoach prototype. In UCD workshop 2, we focused on maturing the low-fidelity solution design and development for the visualization of continuous and discrete data, artificial intelligence (AI)-based interval forecasting, personalized recommendations, and activity goals.
Results
The UCD approach helped to develop a working prototype of eCoach system that meets end-user's requirements and expectations towards an effective recommendation visualization, considering diversity in culture, quality of life, and human values. The design provides an early version of the solution, consisting of wearable technology, a mobile app, and web content for self-monitoring, goal setting, and lifestyle recommendations in an engaging manner between the eCoach app and end-users.
Conclusions
The adopted UCD approach brings in a design focus on the user and their needs at each phase. Throughout the design process, users have been involved at the heart of the design to create a working research prototype to improve the fit between technology, end-user, and researchers. Furthermore, we performed a technological readiness study of ProHealth eCoach against standard levels set by European Union (EU).
Trial Registration:
Not Applicable.
The association of HPV infection and vaginal microbiota of reproductive women in China: A multicenter cohort study protocol
Authors: Zhou Zuyi , Hou Yi , Qing Wei , Shi Yiya , Zhang Yingxuan , Chen Rongdan , Ou Jinxia , Zhou Hongwei , Chen Muxuan
Published: March 2022

Background: Cervical cancer is a global health concern. Persistent oncogenic human papillomavirus (HPV) infection is a prerequisite for the development of cervical cancer. Emerging research indicates that the vaginal microbiota may play both protective and harmful roles in the acquisition and persistence of HPV and the development of cervical intraepithelial neoplasia (CIN). So far, there is no large-scale longitudinal female vaginal microbiota (VM) study worldwide to reveal the association between vaginal microbiota and the outcome of HPV infection.Methods: This multicenter cohort study will recruit 50 research centers and enroll a total of about 10,000 female volunteers across the country. This study has developed a series of strict inclusion and exclusion criteria for the volunteers. Researchers will draw up a unified questionnaire generated by this protocol to obtain the sociodemographic information, clinical data and lifestyle of all volunteers. Specimens including vaginal secretions and cervical exfoliated cells will be collected at the first visit and follow-up after six months. All samples will be processed in the certified laboratory of the research centers. Twenty-one HPV genetypes and other sexually transmitted pathogens, including Neisseria gonorrhoeae, Chlamydia trachomatis, Ureaplasma urealyticum, Mycoplasma hominis, Mycoplasma genitalium and Herpes simplex virus type Ⅱ will be tested in the first visit and follow-up after six months. Strict quality control will be conducted among every research center, including training staffs and reviewing the qualifications of participating researchers responsible for acquiring data and processing samples.Discussion: The association of HPV infection and vaginal microbiota will be explored in the registry study. In addition, the core microbiota attributes to the persistent HPV infection will be analyzed. The present study aims to create a nationwide database of vaginal microbiota of women in reproductive age.Trial registration: This study has registered in ClinicalTrials.gov (ClinicalTrials.gov Identifier: NCT04694495). Registered: 5 January 2021 Retrospectively registered. https://clinicaltrials.gov/ct2/results?cond=&term=NCT04694495&cntry=&state=&city=&dist=
Whole Transcriptome and Functional Genomic Landscape of A South Indian Cohort of Gastric Tumors
Authors: Pandian Jaishree , Gnanasekaran Madhusudhanan , Vittal Vikash , Sekar Balaji T , Jemimah Helen D , Panneerpandian Ponmathi , Patwardhan Satyajit , Kannan Indhu , Suresh Prem , Selvarasu Karthikeyan , Narasimhan Mohan , Ardhanari Ramesh , Ganesan Kumaresan
Published: March 2022

Gastric cancer is the third most common cause of cancer-related mortality. Genome-wide studies pave way for the delineation of heterogeneities and the possible genomics-guided stratification of tumors. Numerous whole-genome profiles have been established from different parts of globe and are largely lacking from South India. We performed genome-wide expression profiling of 50 gastric tumors and 15 adjacent normal tissues from Madurai, India. The genes differentially expressed in gastric tumors were found comparable with genes from other cohorts across globe. Integrative genomic analysis revealed the transcription factors LEF1, SP1, NFAT, AP1, PAX4, E2F and ATF2 to be upregulated and p53, HNF3, ESR, BMP2, PRC2/SUZ12/EED and NRF2 to be downregulated in gastric tumors. Pathway enrichment analysis showed the higher enrichment of focal adhesion, TGF-β, VEGF, EGFR, MAPK and EMT among the genes upregulated. The gastric acid secretion, digestion and absorption of minerals were identified to be diminished in gastric tumors. In a gene set based comparison of molecular subtypes, the frequency was found to differ between TCGA and Madurai cohorts indicating the disparity in molecular genomic patterns across populations. Thus the identification of the transcription factors, signaling pathways and molecular processes dysregulated in gastric tumors is resourceful and reveals the potential therapeutic targets for the eventual development of targeted gastric cancer therapeutics.
Prognostic Nomogram Based on an Immune-Related Biomarker Model Based on the circRNA-Associated Regulatory Network for Cervical cancer
Authors: Guo Xu , Chen Sui , Wang Sihan , Zhang Hao , Yin Fanying , Guo PhD; Panpan , Zhang Xiaoxu , Liu Xuesong , Yang Zhuo , Han Yanshuo
Published: March 2022

Cervical cancer (CC) is a common cancer among women with poor prognosis. Circular RNA (circRNA), as a ceRNA, plays an important role in regulating microRNAs (miRNAs) in many cancers. The immune microenvironment of CC and the regulatory mechanisms at the transcriptomic level have not been fully explored. This study integrated the expression data of circRNA, Long non-coding RNA (lncRNA), miRNA and mRNA from TCGA database, GTEx database and GEO database, and mapped the ceRNA network through variation analysis and correlation analysis. Based on ceRNA network and tumor immune cell infiltration, we constructed two nomograms that can predict CC patients. Through co expression analysis and gene function enrichment, we explored the relationship between prognostic genes and immune cells in the model and the overall function of network node genes. In addition, we screened the drug RO-3306 with sensitivity to high-risk patients and predicted potential drugs with anti CC function by CMap. In conclusion, the research provides relevant information about the diagnosis, treatment and prognosis of CC patients, and several related drugs for reference. Prospective studies are necessary to validate the prognostic ability of this model.
Unutulmaya Yüz Tutmuş Yöresel Yiyeceklerin Gün Yüzüne Çıkarılması: Bayburt İli Ev Kadınları Üzerine Bir Araştırma (Find Out of Local Foods That Fail to be Forgotten: A Research on House Women in Bayburt Province)
Authors: Apak Ömer Ceyhun , Ünlü Hami , Kıvanç Miraç İlyas
Published: March 2022

Mutfak kültürü bir destinasyonun veya bir ülkenin en önemli miraslarından birisidir. Tüketim alışkanlıklarının ve beklentilerin değişmesi mutfağa verilen önemi son dönemlerde artırmaya başlamıştır. Bu doğrultuda yöresel yemeklere olan ilgi giderek artmaya başlamış ve insanların bir destinasyonu ziyaret etmesinde önemli bir faktör olarak ortaya çıkmıştır. Doğal güzellikler ve kültürel çekicilikler açısından zengin bir birikime sahip olan Bayburt yöresel yiyecekler bakımından da zengin bir kültüre sahiptir. Coğrafi işaretli yiyeceklerinin olması da bunun bir göstergesi olarak düşünülebilir. Bu açıdan unutulmaya yüz tutmuş yöresel yiyeceklerin ortaya çıkarılması ve sürdürülebilirliğinin sağlanması önemlidir. Bu çalışma ile de Bayburt mutfağına özgü unutulmaya yüz tutmuş yiyeceklerin gün yüzüne çıkarılması hedeflenmiştir. Bu hedefe ulaşabilmek için ilk olarak bir literatür taraması yapılmış ve toplanan verilerden hareketle bir alan araştırması gerçekleştirilmiştir. Nitel araştırma yöntemlerinden yarı yapılandırılmış görüşme tekniği, veri toplama yöntemi olarak kullanılmıştır. Araştırma kapsamında Bayburt ilinde 10 ev kadını ile görüşmeler yapılmıştır. Elde edilen bulgulara göre görüşme yapılan ev kadınlarının %70’i yöresel yiyeceklerin unutulduğu görüşündedir. Ayrıca gençlerin yöresel yiyecekleri öğrenmede istekli görünmedikleri düşünülmektedir.
Seralarda Doğal Havalandırma Açıklıklarının Belirlenmesi
Authors: BAYTORUN A. Nafi , MAKAUY ABASS Mahamed Abdalla
Published: March 2022

Güneş ışınımı şiddetinin yüksek olduğu dönemlerde seralarda bitkilerin arzu ettiği konfor ortamı en ucuz olarak doğal havalandırma ile sağlanabilmektedir. Bitkisel üretimin yapıldığı serada iyi bir havalandırma ile hava sıcaklığı dış sıcaklığın 1-2 oC üzerine çekilirken, bitki sıcaklığı hava sıcaklığının 5-15 oC üzerine yükselmektedir. Belirtilen nedenle havalandırma ile gölgelemenin birlikte yapılması sıcak dönemlerde bitki konfor ortamının sağlanmasında etkili bir iklimlendirme yöntemi olarak kabul edilmektedir. Hava değişim sayısı seralarda havalandırma etkinliğinin belirlenmesinde kullanılan önemli bir parametredir. Hava değişim sayısı havalandırma açıklıklarının büyüklüğüne, konumuna ve havalandırma açıklıklarında

kullanılan böcek tüllerinin porozitelerine bağlı olarak değişmektedir.

Yapılan çalışmada havalandırma açıklıklarının büyüklüğüne, kullanılan böcek tülünün porozite katsayısına ve rüzgâr hızına bağlı olarak hava değişim sayısı ve ulaşılabilen sıcaklık farkı hesaplanmıştır. Yapılan hesaplamalar sonucunda %50 oranında gölgelendirilen, sera taban alanına göre çatısında %40 oranında havalandırma açıklığı bulunan ve havalandırma açıklıklarına böcek tülünün gerildiği seralarda ulaşılan hava değişim katsayısı 30 h-1 olurken sıcaklık farkı 1,6 oC olarak belirlenmiştir.
Farklı Atkı Sıklıklarına Sahip Denim Kumaşların Aşınma Sonucunda Değişen Optik Özelliklerinin İncelenmesi
Authors: SEZGİN BOZOK Sabiha , OĞULATA R. Tuğrul
Published: March 2022

Denim kumaşlar, günlük hayatta kullanım sıklığı en fazla olan tekstil ürünlerinden birisidir. Kullanım esnasında yoğun aşınmaya maruz kalabilen denim ürünlerinde kumaş yapısının zarar görmesiyle meydana gelen optiksel değişiklik de kaçınılmaz hale gelmektedir. Çalışmada, denim kumaşların aşınma ile değişen optik özelliklerini inceleyebilmek amacıyla 3/1 Z dimi dokunmuş, konstrüksiyonunda boyasız olan atkı ipliğinin sıklıkları farklı (16, 20, 24 atkı/cm), çözgü iplikleri ise boyalı üç farklı denim kumaşın aşındırma işlemleri sonunda değişen renk değerleri incelenmiştir. 1000, 2500, 5000, 7500, 10000 aşındırma devirleri sonunda yapılan renk ölçümleri aşındırma öncesi değerlerle karşılaştırılmış ve bu şekilde denim kumaşların renk değişim davranışının incelenmesi amaçlanmıştır. Numunelerde 2500 devir aşındırma sonrasında ilk belirgin toplam renk farkı değeri elde edilmiştir. Uygulanan en yüksek aşındırma devrinden sonra renksiz atkı ipliği sıklığı en az olan numunelerde renk kuvvetindeki düşüş diğerlerine göre daha az çıkmıştır. Numunelerin aşındıkça renk tonlarının mavi ve yeşil tona kaydığı, renklerinin parlaklaştığı tespit edilmiştir.
Fast Computation of Parameters of the Random Variable that is Logarithm of Sum of Two Independent Log-normally Distributed Random Variables
Authors: TÜFEKCİ Zekeriya , DİŞKEN Gökay
Published: March 2022

In this paper, two fast methods are proposed for computation of mean and variance of a random variable which is logarithm of two log-normally distributed random variables. It is shown that mean and variance can be computed using only one dimensional numerical integration method. The speed of the proposedalgorithms is compared with the baseline algorithm. Simulation results showed that the first proposed method decreases the execution time by an average of 43.98 %. Simulation results also showed that the second proposed method is faster than the first proposed method for the variances greater than 0.325.
Türkiye’nin Güneş Enerjisi Potansiyeli ve İskenderun için Örnek Üretim Projeksiyonu
Authors: KUMRUOĞLU Levent Cenk , ATEŞ Salih Berkan
Published: March 2022

Kişi başına düşen enerji tüketiminin artmasıyla beraber, arz-talep dengesinin sağlıklı bir şekilde devam ettirebilmesi için enerji santrallerine olan yatırımlar devam etmektedir. Oluşan temiz enerji bilinci, çevreci ve uzun ömürlü Güneş Enerji Santrallerine (GES) olan yatırımları gün geçtikçe artırmaktadır. Yaşanan Kovid-19 pandemisi süresince, enerji tüketimlerinin çoğu yenilenebilir santrallerinden karşılanmış ve GES’den üretilen elektrik, büyük paya sahip olmuştur. Yapılan bu çalışmada, özellikle Türkçe kaynaklar içerisinde GES’in hammadde kaynağı olan güneş ışınımları ve ülkemizin güneş potansiyeline dair yapılan araştırmalar incelenmiştir. Güneş potansiyelinin, üretim potansiyeline dönüştürülmesinde oluşan kayıplar ve üretim potansiyelin artırılmasına yönelik konular araştırılmıştır. Ayrıca İskenderun Teknik Üniversitesi Kampüsü içinde bulunan bina çatısına 60 kWp GES tasarlanarak, PVGIS, PVsyst, SMA Web Desing yazılımları ile tahmini elektrik üretimleri hesaplanmıştır.
Comparison of EEMD-ARIMA, EEMD-BP and EEMD-SVM algorithms for predicting the hourly urban water consumption
Authors: Liu Xingpo , Zhang Yiqing , Zhang Qichen
Published: March 2022

Short-term (e.g., hourly) urban water consumption (or demand) prediction is of great significance for the optimal operation of the intelligent water distribution pump stations. In this study, three single models (autoregressive integrated moving average (ARIMA), back-propagation (BP), support vector machine (SVM)) and three hybrid models (ensemble empirical mode decomposition (EEMD)-ARIMA, EEMD-BP and EEMD-SVM) were developed and compared in terms of prediction accuracy and application convenience. 31-day (1 month) hourly flow series from a water distribution division in Shanghai were used for the demonstration case study, among which 30-day data used for model training and 1-day data used for model verification. Finally, the effects of historical data length on the prediction accuracy of three hybrid models were also analyzed, and the optima of the historical data length for three hybrid models were obtained. Results reveal that (1) the mean absolute percentage errors (MAPE) of EEMD-ARIMA, EEMD-BP, EEMD-SVM, ARIMA, BP and SVM are 5.2036, 1.4460, 1.3424, 5.7891, 4.3857 and 3.8470%, respectively. (2) In terms of prediction accuracy and actual practice convenience, EEMD-SVM performs best among the above six models. (3) The EEMD algorithm is effective for improving the prediction accuracy of six models. (4) The optimal historical data length of EEMD-ARIMA, EEMD-BP and EEMD-SVM are 11, 11 and 10 days, respectively.
Research Progress in Antineoplastic, Antibacterial, and Anti-inflammatory Activities of Seven-membered Heterocyclic Derivatives
Authors: Li Bin , Chen Chen , Jia Jingjing , He Ling
Published: March 2022

Seven-membered heterocyclic compounds are important drug scaffolds because
of their unique chemical structures. They widely exist in natural products and show a variety
of biological activities. They have been used commonly in central nervous system
drugs in the past 30 years. In the past decade, many studies have been conducted on their
activities, including antitumor, antibacterial, etc. Herein, we summarize the research advances
in different kinds of seven-membered heterocyclic compounds containing nitrogen,
oxygen, and sulfur heteroatoms with antitumor, antisepsis, and anti-inflammation activities
in the past ten years, which are expected to be beneficial to the development and
design of novel drugs for the corresponding indications.
Nanotechnology: A Promising Targeted Drug Delivery System for
Brain Tumours and Alzheimer's Disease
Authors: Unnisa Aziz , Greig Nigel H. , Kamal Mohammad A.
Published: March 2022

Nanotechnology is the process of modulating shape and size at the nanoscale
to design and manufacture structures, devices, and systems. Nanotechnology's prospective
breakthroughs are incredible, and some cannot even be comprehended right now.
The blood-brain barrier, which is a prominent physiological barrier in the brain, limits
the adequate elimination of malignant cells by changing the concentration of therapeutic
agents at the target tissue. Nanotechnology has sparked interest in recent years as a way
to solve these issues and improve drug delivery. Inorganic and organic nanomaterials
have been found to be beneficial for bioimaging approaches and controlled drug delivery
systems. Brain cancer (BC) and Alzheimer’s disease (AD) are two of the prominent disorders
of the brain. Even though the pathophysiology and pathways for both disorders are
different, nanotechnology with common features can deliver drugs over the BBB, advancing
the treatment of both disorders. This innovative technology could provide a foundation
for combining diagnostics, treatments, and delivery of targeted drugs to the tumour
site, further supervising the response and designing and delivering materials by employing
atomic and molecular elements. There is currently limited treatment for Alzheimer's
disease, and reversing further progression is difficult. Recently, various nanocarriers
have been investigated to improve the bioavailability and efficacy of many AD treatment
drugs. Nanotechnology-assisted drugs can penetrate the BBB and reach the target tissue.
However, further research is required in this field to ensure the safety and efficacy of
drug-loaded nanoparticles. The application of nanotechnology in the diagnosis and treatment
of brain tumours and Alzheimer's disease is briefly discussed in this review.
Vitamin B-related Gene Polymorphisms and Cardiovascular Disease
Authors: Katsa Maria Efthymia , Gil Andrea Paola Rojas
Published: March 2022

Hyperhomocysteinemia is an independent risk factor for atherosclerosis, even in early
childhood. A mutation in genes that code homocysteine metabolism enzymes or deficiency of specific
vitamin cofactors may cause hyperhomocysteinemia. Vitamin B complex has been correlated with
serum homocysteine levels. Any abnormality in its metabolism or nutritional deficiency may lead to
hyperhomocysteinemia. Both vitamin B complex and homocysteine levels are partly genetically
determined. Specifically, the most studied polymorphism is 677T-C in exon 5 of the 5,10-
methylenetetrahydrofolate reductase (MTHFR) gene, which plays an important role in folate’s
metabolism. This polymorphism has been shown to be correlated with hypertension and
cardiovascular disease. Polymorphisms in methylenetetrahydrofolate dehydrogenase (NADP+
dependent) 1-like (MTHFD1L) gene have also been correlated with increased risk for coronary artery
disease. Other common serious polymorphisms regard the area with high linkage disequilibrium,
including the neuroblastoma breakpoint family, NBPF3 gene, and ~ 12-50 kb upstream of the tissue
nonspecific alkaline phosphatase gene. Finally, the polymorphisms which have been mostly associated
with vitamin B12 concentration are the rs11254363 polymorphism at intron 52 of the intrinsic factor
vitamin B12 receptor of the CUBN and the rs526934 polymorphism at intron 8 of transcobalamin I.
To sum up, several polymorphisms have already been associated with vitamin B complexes and
therefore homocysteine level, highlighting the complex nature of vitamin B genetics.
The Lesson from the First Italian Lockdown: Impacts on Anxiety and
Depressive Symptoms and Sleep Quality in Patients with Remission of
Inflammatory Bowel Disease
Authors: Spina Annamaria , Mazzarella Chiara , Dallio Marcello , Romeo Mario , Pellegrino Raffaele , Durante Tommaso , Romano Marco , Loguercio Carmelina , Di Mauro Maurizio , Federico Alessandro , Gravina Antonietta Gerarda
Published: March 2022

Background:

During the COVID-19 pandemic in Italy, decisions were taken to adopt re-strictive legislative measures, such as the first half of the 2020 lockdown. In those months, patients with inflammatory bowel disease experienced social isolation and reduced access to health care.

Objective:

We aimed to evaluate, in this condition, the presence of remission subgroups that were most impacted by the lockdown.

Methods:

During the first Italian lockdown, we recruited patients with remission of inflammatory bowel disease by administering an online questionnaire including patient demographics, the Beck Anxiety Questionnaire Inventory, the Beck Depression Inventory questionnaire, and the Pittsburg Sleep Quality Index, all validated standardized questionnaires for anxiety symptom levels, depres-sion, and sleep quality.

Results:

Our results showed how female patients (p<0.0001) with Crohn’s disease (p<0.001) expe-rienced worse levels of anxiety symptoms. Female patients (p<0.0001) between 50 and 60 years of age (p=0.013) with Crohn’s disease (p=0.047) experienced worse levels of depressive symptoms. Females also experienced significantly worse sleep levels (p<0.001). We found a correlation be-tween the number of sleeping hours (p<0.001) and the time taken to fall asleep (p<0.001) and the Beck Anxiety Questionnaire Inventory,which showed a linear worsening of the number of minutes it took to fall asleep, and the Beck Depression Inventory questionnaire.

Conclusion:

Among patients with remission of inflammatory bowel disease, female patients, pa-tients with Crohn’s disease, and people aged between 50 and 70 years should be considered for screening for anxiety and depression disorders and an assessment of sleep quality.
Hybrid Model-Based and Data-Driven Solution for Uncertainty Quantification at the Microscale
Authors: Quesada-Molina Jose Pablo , Mariani Stefano
Published: March 2022

Background:

Due to their size, microelectromechanical systems (MEMS) display performance
indices affected by uncertainties linked to the mechanical properties and to the geometry of the
films constituting their movable parts.

Objective:

In this perspective, a recently proposed multiscale and hybrid solution for uncertainty
quantification is discussed.

Methods:

The proposed method is based on the (deep) learning of the morphology-affected elasticity
of the polycrystalline films and of the microfabrication-induced defective geometry of the devices.
The results at the material and at the device levels are linked through a reduced-order representation
of the response of the entire device to the external stimuli, foreseen to finally feed a Monte Carlo uncertainty
quantification engine.

Results:

Preliminary results relevant to a single-axis resonant Lorentz force micro-magnetometer have
shown a noteworthy capability of the proposed multiscale deep learning method to account for the
mentioned uncertainty sources at the microscale.

Conclusion:

A promising two-scale deep learning approach has been proposed for polysilicon MEMS
sensors to account for both materials- and geometry-governed uncertainties and to properly describe
the scale-dependent response of MEMS devices.