bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation and Adsorption Properties of Polymer Particles based on N,
N, N', N'-Tetrakis(4-aminophenyl)-1,4-Benzenediamine
Authors: Huang Jian-Yu , Liu Yong , Huang Ting-Hong , Liu Sheng-Zhi , Wu Ai-Ling
Published: March 2024

Two polymer particles have been prepared by the reaction of N, N, N', N'-tetrakis(4-
aminophenyl)-1,4-benzenediamine, 4, 4-biphenyldialdehyde and isophthalaldehyde, and characterized
by SEM, FTIR and XRD. Based on methylene blue as the model pollutant, the adsorption properties
of two polymer particles have been observed by using different adsorbent dosages, adsorption times
and adsorption temperatures. Experimental data show that the removal rates of methylene blue
wastewater are 74 % for polymer A and 68 % for polymer B, and the removal rates are up to 84% for
polymer A and 74 % for polymer B after photo-catalytic treatment. All these suggest that the adsorption
performance of polymer A is more excellent than that of polymer B. In addition, the methylene
blue adsorption of the two Schiff base products conforms to the Freundlich adsorption isothermal
model.
Role of Artificial Intelligence in Drug Discovery to Revolutionize the Pharmaceutical Industry: Resources, Methods and Applications
Authors: Singh Pranjal Kumar , Sachan Kapil , Khandelwal Vishal , Singh Sumita , Singh Smita
Published: March 2024

Traditional drug discovery methods such as wet-lab testing, validations, and
synthetic techniques are time-consuming and expensive. Artificial Intelligence (AI) approaches
have progressed to the point where they can have a significant impact on the
drug discovery process. Using massive volumes of open data, artificial intelligence
methods are revolutionizing the pharmaceutical industry. In the last few decades, many
AI-based models have been developed and implemented in many areas of the drug development
process. These models have been used as a supplement to conventional research to
uncover superior pharmaceuticals expeditiously. AI's involvement in the pharmaceutical
industry was used mostly for reverse engineering of existing patents and the invention of
new synthesis pathways. Drug research and development to repurposing and productivity
benefits in the pharmaceutical business through clinical trials. AI is studied in this article
for its numerous potential uses. We have discussed how AI can be put to use in the pharmaceutical
sector, specifically for predicting a drug's toxicity, bioactivity, and physicochemical
characteristics, among other things. In this review article, we have discussed its application
to a variety of problems, including de novo drug discovery, target structure prediction, interaction
prediction, and binding affinity prediction. AI for predicting drug interactions and
nanomedicines were also considered.
Development of a Novel Peptide with RGD Tumor Homing Motif: Evaluation of its Anticancer Potential in Hepatocellular Carcinoma and Colon Cancer Cells
Authors: Mohamed Reda Abdallah , Marie Ohoud Mohammed , Badran Dahlia Ibrahim , Hammam Olfat Ali , Ahmed Hend Okasha
Published: March 2024

Background:

Peptide-based therapy has emerged as a promising avenue for
treating various disorders, and recent research has highlighted the potential of anti-cancer
peptides (ACPs) in cancer treatment. In this context, this study aimed to design a novel
peptide incorporating a tumor-homing peptide (RGD) and C-amidation to enhance its anticancer
activity, particularly against liver (HepG2) and colon (HCT-116) cancer cell lines.

Objectives:

The primary objective was to design a peptide with improved anticancer
properties by leveraging the tumor-homing capabilities of RGD and enhancing its activity
through C-amidation. The study sought to evaluate the cytotoxicity of the designed
peptide against red blood cells (RBCs) and normal Vero cells. Furthermore, the anticancer
efficacy of the peptide was assessed in hepatocellular carcinoma (HepG2) and colon
cancer (HCT-116) cell lines. The specific objectives included examining the apoptotic
induction and morphological changes in treated cells compared to untreated cells.

Methods:

The peptide was designed using the ACPred-FL bioinformatics tool, and its
cytotoxicity was assessed through hemolysis assays against RBCs and normal Vero cells.
Anticancer activity was evaluated against HepG2 and HCT-116 cell lines. The analysis
of apoptotic induction involved measuring the relative gene expression of oncogenic
marker BCL2 and apoptotic markers (BAX, BID, CAS-8). Additionally, Cytopathological
examination and Western Blot analysis were employed to study morphological
changes and confirm the quantification of relevant markers.

Results:

The designed peptide, consisting of twelve amino acids with a molecular mass
of 1230.6233 Da and an isoelectric point of 9.81, exhibited low erythrocyte lysis and
minimal toxicity to normal cells. The IC50 values demonstrated significant anticancer activity
against both HepG2 (36.49±2.6 μg/mL) and HCT-116 (11.03±2.5 μg/mL) cell
lines. Treated cells exhibited a significant decrease in the oncogenic marker BCL2 and an
upregulation of apoptotic markers (BAX, BID, CAS-8). Western Blot analysis confirmed
these results in addition to cytopathological examination that scattered apoptotic and degenerative
changes.

Conclusion:

The designed peptide is considered a patent product that displayed remarkable
anticancer activity against hepatocellular carcinoma and colon cancer cell lines, effectively
modulating apoptotic and oncogenic markers. These findings highlight the potential of the
peptide as a therapeutic agent for cancer treatment, emphasizing its clinical significance in
combating liver and colon cancers. Nonetheless, further research and development are warranted
to explore the translational potential of this peptide in clinical studies.
Post-discharge Follow-up Care: Nurses' Experience of Fostering Continuity of Care: A Qualitative Study
Authors: Handiyani Hanny , Kurniawan Moh Heri , Hariyati Rr Tutik Sri , Nuraini Tuti
Published: March 2024

Background

In contemporary healthcare, ensuring continuity of care beyond hospitalization is imperative for optimizing patient outcomes. Post-discharge Follow-up Care (PFC) has emerged as a crucial component in this endeavor, especially with the integration of virtual platforms.

Objective

This study aims to thoroughly investigate nurses' experiences in providing Post-discharge Follow-up Care (PFC) to improve its implementation.

Methods

A descriptive qualitative study was conducted to explore nurses’ experiences of conducting nurse-led follow-up care. This study was conducted at University Hospital, involving nine nurses with experience in administering PFC. Data were collected through focus group interviews. Thematic analysis was performed to identify recurring patterns and themes within the data.

Results

The thematic analysis yielded four overarching themes: 1) “Caring nurse virtually,” emphasizing nurses' dedication to compassionate virtual care, 2) “Constraints and limitations of continuing care,” highlighting challenges in resource management and coordination, 3) “Continuous documentation and coordination,” underscoring their vital role in seamless patient care, and 4) “Nurses’ expectation of technology features,” showing nurses' hopes for advanced features to enhance PFC.

Conclusion

This study provides deep insights into the experiences of nurses in delivering PFC through virtual platforms. It underscores the significance of maintaining emotional connections with patients, even in a virtual environment. The challenges faced in resource management and coordination highlight areas for potential improvement. Additionally, the study highlights the crucial role of accurate documentation and inter-team coordination in ensuring the continuity and quality of care. The nurses' expectations for technological advancements emphasize the need for ongoing innovation in healthcare delivery. These findings collectively contribute to the ongoing evolution of virtual follow-up care practices, ultimately enhancing patient outcomes and experiences beyond the hospital setting.
Quality by Design in Pharmaceutical Development: Current Advances and Future Prospects
Authors: Mohite Popat , Gholap Amol , Pardeshi Sagar , Puri Abhijeet , Rajput Tanavirsing
Published: March 2024

QbD, or Quality by Design, is a cutting-edge methodology adopted
extensively in the pharmaceutical industry. It is defined objects, such as the product's
safety and effectiveness. QbD's primary focus in the pharmaceutical industry is
ensuring the product's security and usefulness. Quality by Design (QbD) seeks to instill
high standards of excellence in the blueprinting process. The International Council for
Harmonization (ICH) has developed guidelines and elements that must be adhered to
guarantee the consistent, high-quality development of pharmaceuticals. This chapter
provides updated guidelines and elements, including quality risk management,
pharmaceutical quality systems, QbD in analytical methods and pharmaceutical
manufacturing, process control, vaccine development, pharmacogenomic, green
synthesis, etc. QbD was briefly defined, and several design tools, regulatory-industry
perspectives, and QbD grounded on science were discussed. It was portrayed that
significant effort was put into developing drug ingredients, excipients, and
manufacturing processes. Quality by design (QbD) is included in the manufacturing
process's development, and the result is steadily improving product quality. Quality
target product profiles, critical quality attributes, analytical process techniques, critical
process parameters control strategy and design space are elements of many
pharmaceutical advancements. Some of the topics covered included the application of
QbD to herbal products, food processing, and biotherapeutics through analytical
process techniques. We are still exploring and compiling all the data and metrics
required to link and show the benefits of QbD to all stakeholders. Nevertheless, the
pharmaceutical sector is quickly using the QbD process to create products that are
reliable, efficient, and of high quality. Soon, a more profound comprehension of the
dosage form parameters supported by the notion of QbD will benefit Risk management
and process and product design, optimizing complex drug delivery systems.
Newer Screening Software for Computer Aided Herbal Drug Interactions and its Development
Authors: Kumar Kadiri Sunil , Tiwari Prashant
Published: March 2024

Self-diagnosis and treatment by consumers as a means of reducing medical
costs contribute to the predicted continued growth in the usage of herbal products.
Herbal products are notoriously difficult to evaluate for potential drug interactions
because of the wide range of possible interactions, the lack of clarity surrounding the
active components, and the often insufficient knowledge of the pharmacokinetics of the
offending constituents. It is a standard practice for innovative drugs in development to
identify particular components from herbal goods and describe their interaction
potential as part of a systematic study of herbal product drug interaction risk. By
cutting down on expenses and development times, computer-assisted drug design has
helped speed up the drug discovery process. The natural origins and variety of
traditional medicinal herbs make them an attractive area of study as a complement to
modern pharmaceuticals. To better understand the pharmacological foundation of the
actions of traditional medicinal plants, researchers have increasingly turned to in silico
approaches, including virtual screening and network analysis. The combination of
virtual screening and network pharmacology can reduce costs and improve efficiency
in the identification of innovative drugs by increasing the proportion of active
compounds among candidates and by providing an appropriate demonstration of the
mechanism of action of medicinal plants. In this chapter, we propose a thorough
technical route that utilizes several in silico approaches to discover the pharmacological
foundation of the effects of medicinal plants. This involves discussing the software
used in the prediction of herb-drug interaction with a suitable database.
Warp and Woof of Drug Designing and Development: An In-Silico Approach
Authors: Chauhan Monika , Gupta Vikas , Arora Anchal , Kaur Gunpreet , Bansal Parveen , Sharma Ravinder
Published: March 2024

Designing and developing a novel therapeutic drug candidate remains a
daunting task and requires a long time with an investment of approximately ~USD 2-3
billion. Owing to the subpar pharmacokinetic or toxicity profiles of the therapeutic
candidates, only one molecule enters the market over a period of 12 to 24 years. So, the
reduction of cost, time, high attrition rate in the clinical phase, or drug failure has
become a challenging and dire question in front of the pharmaceutical industry. In the
last few decades, steep advancements in artificial intelligence, especially computeraided drug design have emerged with robust and swift drug-designing tools. Existing
reports have clearly indicated an imperative and successful adoption of virtual
screening in drug design and optimization. In parallel, advanced bioinformatics
integrated into genomics and proteomics discovering molecular signatures of disease
based on target identification or signaling cascades has directly or indirectly
smoothened the roadmap of the clinical trial. Integrated genomics, proteomics, and
bioinformatics have produced potent new strategies for addressing several biochemical
challenges and generating new approaches that define new biological products.
Therefore, it is fruitful to utilize the computational-based high throughput screening
methods to overcome the hurdles in drug discovery and characterize ventures. Besides
that, bioinformatic analysis speed up drug target selection, drug candidate screening,
and refinement, but it can also assist in characterizing side effects and predicting drug
resistance. In this chapter, the authors have discussed a snapshot of State-of-the-Art
technologies in drug designing and development.
Central Districts, Neighborhoods and Historical Buildings in Present Edirne
Authors: Erdoğan Nevnihal
Published: March 2024

The goal of this chapter is the investigation of old neighborhoods (mahalle),
streets, and houses of the city center and old outer districts (bölge) of the inner Edirne
region. One of the goals of this study is to expose the growth and development of the
inner districts of the Edirne region without overlooking the existing values. In this
context, original establishments (mosques, baths, fountains, soup kitchens, etc) and the
settlement layout (streets and neighborhoods) have been fixed on the existing maps of
the district. The first and second groups of Edirne neighborhoods were investigated in
terms of their history, neighbor relations, and historical house type. The new
neighborhoods of Edirne that make up the third group are continuing to expand from
the eastern portions of the city towards the Edirne plateau.

The data for this study were collected by means of documents gathered from various
institutions, a field study and observations, in situ photography, and a visual survey
carried out in the central and historic districts of Edirne. Maps of different scales were
obtained for the settlements, on which the positions of the existing original
establishments were then drawn. Original establishments such as mosques, baths,
fountains, soup kitchens, etc, and the settlement layout (streets and neighborhoods)
have been drawn on the existing maps of districts. The plans of some historical
residences were drawn with various dimensions and these structures and the historical
streets on which they stand were all photographed. Housing types selected from
different neighborhoods were analyzed.
Recurrent Hemoptysis Post Re-Embolization in a 49 Year-Old Male with Post Tuberculosis Lung Disease (PTLD) and Bronchiectasis
Authors: Primaputri Cindy Carrissa , Pratiwi Suryanti Dwi , Aslam Ahmad Bayhaqi Nasir
Published: March 2024

Introduction: Hemoptysis is a symptom of lung disease, could be caused by lung infections, structural disorders of the lung, malignancy or disorders from outside of the lung. One of the pulmonary intervention for hemoptysis is embolization with a success rate > 70%, but the recurrence rate reaches 10-55%. The prognosis is poor depending on the amount of bleeding (untreated cases can have a mortality risk of over 50%), etiology and presence of recurrences.

Case Illustration: A 49-year-old Male came to the policlinic with recurrent hemoptysis for a year. Non-smoker. History of Lung Tuberculosis (TB), completed treatment 15 years ago. Imaging result showed widening of the right subcostal artery, right posterior intercostal artery, bronchiectasis, active lung tuberculosis and left pulmonary emphysema. First embolization was done during Anti-Tuberculosis Drug (ATD) treatment for 6 months. Symptom of hemoptysis reappeared, then second embolization and fiber optic bronchoscopy (FOB) was performed. From the evaluation, he was diagnosed with infected bronchiectasis and PTLD, therefore given antibiotic medications for 2 weeks.

Discussion: Embolization had been done twice in this case, no significant result. Based on literature, recurrent hemoptysis can still occur with a percentage about 10-55% after embolization and in this case, it might be caused by previous lung structural disorder and lung infections (Lung TB and Infected bronchiectasis).

Conclusion: Although embolization has a success rate of > 70% for hemoptysis treatment, recurrence can still occur and highly dependent on the cause itself and patient's previous lung condition.

Keywords: Hemoptysis, Embolization, Bronchiectasis, FOB, Lung TB, PTLD, ATD
POSITION CONTROL OF A QUADCOPTER WITH PID AND FUZZY-PID CONTROLLER
Authors: Polat Ozan , Sezgin Aziz
Published: March 2024

In this study, PID based efficient control systems are designed and compared for position control of a quadcopter in six degrees of freedom. The main goal is to get the quadcopter to the desired position in three-dimensional space. Firstly, the desired position for the quadcopter to reach is determined. Then, the physical model of the system is selected, and mathematical model is derived according to the physical model. Initially, all external disturbances like drag force and wind are neglected. However, various external disturbances are then applied to the system to measure robustness of the designed controllers. Firstly, PID controller is implemented to the quadcopter system. Secondly, Fuzzy-PID controller is used. Necessary pitch and roll angles are found and control forces are calculated by using both controllers. Also, angular velocities of the motors and current values which are needed to be supplied to each motor are calculated and compared to evaluate performance and applicability of the proposed controllers. According to the results, it is observed that both controllers worked successfully, quadcopter is able to reach the desired location in three-dimensional space. However, Fuzzy-PID controller gives faster response and smaller overshoot levels than basic PID controller. In addition, it is seen that the Fuzzy-PID controller is less affected by external disturbances, and it recovers faster against these changes.
KÜÇÜK ÖLÇEKLİ, TEK EKLEMLİ MANYETİK SARKAÇ MEKANİZMASININ BİLGİSAYAR DESTEKLİ BENZETİMİ VE PID KONTROLÜ
Authors: Yıldız Hüseyin
Published: March 2024

Sağlık ve biyomedikal cihaz teknolojileri günümüzün en önemli konuları arasında yer almaktadır. Son yıllarda teknolojide yaşanan gelişmeler ile birlikte, mikro ve makro ölçekli robotik sistemlerinin ilaç dozajlama, hücre ve DNA dizilimi oluşturma, görüntüleme ve bölgesel müdahale sistemi olarak geliştirilmesi üzerine çalışmalar ön plana çıkmaktadır. Çalışmada küçük ölçekli sistemlerde nesne taşıma, konum manipülasyonu vb. işlemlerde kullanılmak üzere doğrudan manyetik alan ile kontrol edilebilen tek serbestlik dereceli bir robot kol mekanizması(sarkaç) önerilmiştir. Sistemi yöneten elektrik ve mekanik denklem sistemi çıkartılmış, PID kontrolcü tasarımı yapılmıştır. Manyetik kuvvetlerin doğrusal olmayan davranışı nedeni ile Ziegler-Nichols metodları ile kontrolcü parametrelerinin belirlenemediği görülmüştür. PID kontrolcü parametreleri iteratif metodlar kullanılarak optimize edilerek elde edilmiştir. İterasyon algoritması 7 iterasyon sonucunda -0.1788 Aşma, 0.1634 Yerleşme ve 0.0298 mutlak hata ortalaması ile en iyi sonuşlara ulaşmıştır. Ulaşılan PID parametreleri ise kp=5.353, kd=0.2157 ve ki=21.5987’dir. Farklı dalga formlarında (basamak, üşgen ve sinüzoidal) kontrolcü davranışı incelenmiştir. Sistemde oluşan hatalar, kontrolcü gerilim çıkışı ve devrede oluşan akımlar görselleştirilerek detaylandırılmıştır. Çalışmada, 20A akım ile önerilen sarkaç modelinde pozisyon kontrolünün yapılabileceği gösterilmiştir.
SEDIMENTATION ANALYSIS ON SEYHAN DAM RESERVOIR USING LONG TERM BATHYMETRY DATA
Authors: Akgül Mehmet Ali , Güvel Şerife Pınar , Aksu Hakan
Published: March 2024

In this study, sedimentation in the Seyhan Dam reservoir was investigated by analyzing a long-term bathymetric survey dataset. The focus was on understanding how reservoir capacity changes impact reservoir operation rules. The findings revealed that sedimentation from the main branch of the Seyhan River has largely stopped since the construction of the Çatalan Dam, but sedimentation from the Çakıt branch continues. Furthermore, the study observed changes in the upper basin between 1990 and 2018 based on the CORINE Land Cover (CLC) dataset. The forest area increased from 23.71% to 24.36%, and water bodies expanded from 0.3% to 0.9%. This increase in forest and water bodies contributed to a reduction in sediment flow into the Seyhan Dam reservoir. The researchers used regression analysis and found a high correlation (R2=0.96) between water storage capacity changes and time (in years) at a 67.5-meter water level in the Seyhan Dam Reservoir. Overall, the study's results suggest that the decrease in sediment entering from the main branch of the Seyhan River has significantly improved the sedimentation issue.
A STUDY ON DETERMINATION OF TOTAL PHENOLIC AND PROTEIN AMOUNTS OF WASTE GREEN ALGAE OF MAMASIN DAM LAKE (AKSARAY-TURKEY)
Authors: Koç Bilican Behlül , Maruška Audrius Sigitas
Published: March 2024

The excessive proliferation of green algae in aquatic ecosystems threatens aquatic life, leading to oxygen depletion and water pollution. This study investigates two common green algae species, Ulva sp. and Cladophora sp., with potential in terms of protein and phenolic compounds. Cladophora sp. and Ulva sp. extracts were analyzed for total phenolic content using the Folin-Ciocalteau method. Despite lower phenolic content compared to specific plant species, both algae species exhibit various phenolic compounds. GC-MS analysis indicates the presence of major compounds such as limonene in Cladophora sp. and Tetradec-1-ene in Ulva sp., suggesting potential applications in the pharmaceutical and cosmetic industries. Despite modest protein amounts, the study emphasizes that algae, aligned with the increasing interest in plant-based nutrition, are a promising source for plant-based protein production. Ulva sp. and Cladophora sp. algae demonstrate potential as alternative protein sources and reservoirs of bioactive phenolic compounds from waste sources. This study pioneers further research in the food, pharmaceutical, and cosmetic industries to contribute to sustainable water resource utilization.
Mitigating Health-Related Uncertainties During Pregnancy: The Role of Smart Health Monitoring Technologies
Authors: Tretter Max
Published: March 2024

Pregnancy is a time filled with uncertainties, which can be challenging and lead to fear or anxiety for expectant parents. Health monitoring technologies that allow monitoring of the vital signs of both the mother and fetus offer a way to address health-related uncertainties. But are smart health monitoring technologies (SHMTs) actually an effective means to reduce uncertainties during pregnancy, or do they have the opposite effect? Using conceptual reasoning and phenomenological approaches grounded in existing literature, this Viewpoint explores the effects of SHMTs on health-related uncertainties during pregnancy. The argument posits that while SHMTs can alleviate some health-related uncertainties, they may also create new ones. This is particularly the case when the abundance of vital data overwhelms pregnant persons, leads to false-positive diagnoses, or raises concerns about the accuracy and analysis of data. Consequently, it is concluded that the use of SHMTs is not a cure-all for overcoming health-related uncertainties during pregnancy. Since the use of such monitoring technologies can introduce new uncertainties, it is important to carefully consider where and for what purpose they are used, use them sparingly, and promote a pragmatic approach to uncertainties.Using conceptual reasoning and phenomenological approaches grounded in existing literature, the effects of SHMTs on health-related uncertainties during pregnancy are explored. The argument posits that while SHMTs can alleviate some health-related uncertainties, they may also create new ones. This is particularly the case when the abundance of vital data overwhelms pregnant persons, leads to false-positive diagnoses, or raises concerns about the accuracy and analysis of data.
Consequently, it is concluded that the use of SHMTs is not a cure-all for overcoming health-related uncertainties during pregnancy. Since the use of such monitoring technologies can introduce new uncertainties, it is important to carefully consider where and for what purpose they are used, use them sparingly, and promote a pragmatic approach to uncertainties.
Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers
Authors: Klein Ari Z , Gutiérrez Gómez José Agustín , Levine Lisa D , Gonzalez-Hernandez Graciela
Published: March 2024

We manually annotated 9734 tweets that were posted by users who reported their pregnancy on Twitter, and used them to train, evaluate, and deploy deep neural network classifiers (F1-score=0.93) to detect tweets that report having a child with attention-deficit/hyperactivity disorder (678 users), autism spectrum disorders (1744 users), delayed speech (902 users), or asthma (1255 users), demonstrating the potential of Twitter as a complementary resource for assessing associations between pregnancy exposures and childhood health outcomes on a large scale.
Digital Tools to Facilitate the Detection and Treatment of Bipolar Disorder: Key Developments and Future Directions
Authors: de Azevedo Cardoso Taiane , Kochhar Shruti , Torous John , Morton Emma
Published: March 2024

Bipolar disorder (BD) impacts over 40 million people around the world, often manifesting in early adulthood and substantially impacting the quality of life and functioning of individuals. Although early interventions are associated with a better prognosis, the early detection of BD is challenging given the high degree of similarity with other psychiatric conditions, including major depressive disorder, which corroborates the high rates of misdiagnosis. Further, BD has a chronic, relapsing course, and the majority of patients will go on to experience mood relapses despite pharmacological treatment. Digital technologies present promising results to augment early detection of symptoms and enhance BD treatment. In this editorial, we will discuss current findings on the use of digital technologies in the field of BD, while debating the challenges associated with their implementation in clinical practice and the future directions.
Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers (Preprint)
Authors: Klein Ari Z , Gutiérrez Gómez José Agustín , Levine Lisa D , Gonzalez-Hernandez Graciela
Published: March 2024

UNSTRUCTURED

We manually annotated 9734 tweets that were posted by users who reported their pregnancy on Twitter, and used them to train, evaluate, and deploy deep neural network classifiers (F1-score=0.93) to detect tweets that report having a child with attention-deficit/hyperactivity disorder (678 users), autism spectrum disorders (1744 users), delayed speech (902 users), or asthma (1255 users), demonstrating the potential of Twitter as a complementary resource for assessing associations between pregnancy exposures and childhood health outcomes on a large scale.
Assessment of Reliability and Validity of Celiac Disease–Related YouTube Videos: Content Analysis (Preprint)
Authors: Polat Yunus Halil , Cankurtaran Rasim Eren
Published: March 2024

BACKGROUND

YouTube is an increasingly used platform for medical information. However, the reliability and validity of health-related information on celiac disease (CD) on YouTube have not been determined.

OBJECTIVE

This study aimed to analyze the reliability and validity of CD-related YouTube videos.

METHODS

On November 15, 2023, a search was performed on YouTube using the keyword “celiac disease.” This search resulted in a selection of videos, which were then reviewed by 2 separate evaluators for content, origin, and specific features. The evaluators assessed the reliability and quality of these videos using a modified DISCERN (mDISCERN) score, the Journal of the American Medical Association (JAMA) benchmark criteria score, the usefulness score, video power index (VPI), and the Global Quality Scale (GQS) score.

RESULTS

In the analysis of 120 initially screened CD videos, 85 met the criteria for inclusion in the study after certain videos were excluded based on predefined criteria. While the duration of the videos uploaded by health care professionals was significantly longer than the other group (P=.009), it was concluded that the median scores for mDISCERN (4, IQR 4-5 vs 2, IQR 2-3; P<.001), GQS (4, IQR 4-5 vs 3, IQR 2-3; P<.001), JAMA (4, IQR 3-4 vs 2, IQR 2-3; P<.001), and usefulness (8, IQR 7-9 vs 6, IQR 3-6; P<.001) of the videos from this group were significantly higher than those from non–health care professionals. Video interaction parameters, including the median number of views, views per day, likes, dislikes, comments, and VPI, demonstrated no significant difference between the 2 groups.

CONCLUSIONS

This study showed that YouTube videos about CD vary significantly in reliability and quality depending on their source. Increasing the production of reliable videos by health care professionals may help to improve patient education and make YouTube a more reliable resource.
Digital Interventions for Reducing Loneliness and Depression in Korean College Students: Mixed Methods Evaluation (Preprint)
Authors: Kang Boyoung , Hong Munpyo
Published: March 2024

BACKGROUND

The COVID-19 pandemic has exacerbated the prevalence of loneliness and depression among college students. Digital interventions, such as Woebot (Woebot Health, Inc) and Happify (Twill Inc), have shown promise in alleviating these symptoms.

OBJECTIVE

This study aims to investigate the effectiveness and acceptability of Woebot and Happify in reducing loneliness and depression among college students after the COVID-19 pandemic.

METHODS

A mixed methods approach was used over 4 months. A total of 63 participants aged 18 to 27 years from Sungkyunkwan University in Seoul, South Korea, were initially recruited, with an inclusion criterion of University of California, Los Angeles (UCLA) Loneliness Scale score ≥34. The final sample consisted of 27 participants due to attrition. Participants were randomly assigned to Woebot (15/27, 55%); Happify (9/27, 33%); or a control group using Bondee (Metadream), a metaverse social network messenger app (3/27, 11%). Quantitative measures (UCLA Loneliness Scale and Patient Health Questionnaire-9) and qualitative assessments (user feedback and focused interviews) were used.

RESULTS

Although mean decreases in loneliness and depression were observed in the control and intervention groups after the intervention, the differences between the control and intervention groups were not statistically significant (UCLA Loneliness: P=.67; Patient Health Questionnaire-9: P=.35). Qualitative data indicated user satisfaction, with suggestions for improved app effectiveness and personalization.

CONCLUSIONS

Despite limitations, this study highlights the potential of well-designed digital interventions in alleviating college students’ loneliness and depression. The findings contribute to the growing body of research on accessible digital mental health tools and underscore the importance of comprehensive support systems. Further research with larger and more diverse samples is needed to better understand the effectiveness and optimization of such interventions.

CLINICALTRIAL

Clinical Research Information Service KCT0009449; https://bit.ly/4d2e4Bu
The hit problem of three variables for the cohomology of the classifying space BE_(s ) as a module over the mod 3 Steenrod Algebra at some low degrees
Authors: Pham Bich Nhu , Nguyen Tu Thinh
Published: March 2024

The hit problem, set up by F. Peterson, finds a minimal set of generators for the polynomial algebra  , as a module over the mod-2 Steenrod algebra. We study the extended hit problem for the cohomology of the classifying space  over field   , with  at degrees d
Repurpose the antimicrobial peptide Buforin II for plasmid transformation into Escherichia coli
Authors: Nguyen Thanh Ngoc , Bui Le Minh
Published: March 2024

Antimicrobial peptides Buforin II, derived from histone H2A, demonstrates strong cell-penetrating activity without cell lysis and strong affinity for internal cellular nucleic acids, making it a potential candidate for macromolecule delivery into bacteria. Herein, we designed a peptide that is the fusion of Buforin II and a polycation tail (KH)6 and assessed its efficiency in delivering plasmid (pGEX-RG-(TAG)5, 7,142 bp)  into Escherichia coli OmniMAX. The peptide and plasmid were incubated at 25°C to form the complexes at various peptide concentrations from 5 to 50 µg/mL. After that, the complexes were incubated with the E. coli competent cells at 25°C. In comparison with the transformation efficiency and normalized transformation efficiency of conventional heat-shock method, a 1.28 and 7.83 times higher transformation efficiency, correspondingly,  was achieved by using novel peptide-based delivery system at peptide concentration of 5 µg/mL. The cell viability of over 90% was displayed at peptide concentration of 5 µg/mL. This study can lead to the development of a transformation approach under mild conditions and an ideal tool for gene delivery.
Assessing Carbon Dioxide (CO2) Absorption Potential of Forests Around Landslides Along the Trans Palopo-Toraja Highways
Authors: Witno Witno , Maria Maria , Liana Liana , Wardi Wardi
Published: March 2024

Forests are crucial in absorbing carbon dioxide (CO2) from the atmosphere through photosynthesis and storing the carbon in its biomass. This research aimed to assess the potential for CO2 absorption of forests around landslides along the Trans Palopo-Toraja highways. This research employed a destructive sampling to measure understorey and litter biomass. Furthermore, it measured the biomass of understorey plants and litter with a destructive method. The 12 measurement plots were purposively placed on the landslide points to represent various vegetation conditions. The results revealed the presence of 77 plant species, totaling 554 individuals on the measurement plots. Plot 4 and Plot 1 showed the highest and lowest carbon absorption potential at 790.39 tons/ha and 199.63 tons/ha, respectively. The estimated average absorption of 12 plots was 461.75 tons/ha. Tree-level vegetation had the highest carbon absorption value due to its bigger diameter and CO2 absorption capacity than saplings and poles.
Classification of Bone Fractures using CNN
Authors: Navyasree P , Narayana S Laxmi , Aeyba N , Sushma S
Published: March 2024

Abstract: Bone breaks are common injury that require exact and opportune conclusion for legitimate treatment and administration. In this consider, we proposed a bone break location framework based on convolutional neural network systems (CNNs) to help radiologists within the location and classification of breaks from restorative imaging information, such as Xrays. The proposed framework points to computerize the break discovery prepare and give an effective and dependable device for restorative experts. The CNN-based break discovery framework comprises of a few key components, including picture preprocessing, include extraction, and classification. Within the preprocessing organize, the input X-ray pictures are preprocessed to upgrade picture quality and evacuate disturbance, guaranteeing ideal execution amid the consequent stages. Another, the CNN demonstrate is utilized to extricate important highlights from the preprocessed pictures. The demonstrate comprises of different convolutional layers that consequently learn and distinguish fracture-related designs and structures. To prepare the CNN demonstrate, a expansive dataset of labeled X- ray pictures with break comments is collected and utilized for show preparing. The preparing prepare includes nourishing the pictures into the arrange, optimizing the model's parameters utilizing back engendering, and iteratively altering the weights to play down the classification mistake. The prepared show is at that point assessed on a isolated test dataset to evaluate its execution in terms of exactness, affectability, specificity, and other significant measurements
Design it Yourself (DIY): Create the Home of Your Dreams
Authors: M Manjunath , Gaikwad Dr Smita M
Published: March 2024

Abstract: Interior design is a field that combines creativity and technical knowledge to design indoor spaces that are aesthetically pleasing, functional, and improve quality of life. It encompasses various specializations, like residential or commercial design, and involves collaboration with professionals to bring the designs to life. The industry is constantly evolving with new trends and technologies, making it a dynamic and exciting career option.
Competitiveness Analysis and Strategies to Improve Small and Medium Enterprises Performance
Authors: Waridin Waridin , Wafa A.F Muhamad , Tantra I Gusti Lanang Putu
Published: March 2024

Global economic dynamics encourage industry to excel and be competitive. This research aims to identify industry characteristics, measure the level of industrial competitiveness; and then provide strategy suggestions to increase industrial competitiveness. The Porter Diamond Model is used in this research to measure the level of competitiveness of the exhaust industry, where there are four indicators of industrial competitiveness, namely factor conditions, demand conditions, company strategy and competitive structure, as well as related and supporting industries. Using qualitative methods, data collection is carried out using questionnaires. The primary data used was taken from exhaust manufacturers in Purbalingga Regency totaling 67 respondents. Strategy recommendations for increasing industrial competitiveness are determined based on urgency-performance analysis. The results of the industrial competitiveness analysis show that condition factors provide the highest contribution to the competitiveness of the exhaust industry compared to other indicators. Urgency-performance analysis shows that 5 out of 10 sub-factors driving competitiveness have underact status. The strategy to increase industrial competitiveness focuses on competitiveness sub-factors with “under act” status. These strategies include: 1) Providing better business development systems and services, 2) Developing business capacity, and 3) Expanding industrial cooperation.
Marketing Strategy on Heritage Manuaba Royal Palace Tourist Attraction in Kenderan Tourism Village, Bali
Authors: Premayani Ni Wayan Wina , Wijaya Putu Yudy , Susanti Putu Herny , Suputra Gusti Alit , Oktarini Luh Nik , Yoga Gede Agus Dian Maha
Published: March 2024

The Manuaba Royal Palace is one of the heritage tourist attractions that has cultural heritage, building architecture, and artifact collections with historical value; however, to date, this tourist destination has not been optimal in presenting tourists to be able to visit this region, so a comprehensive and measurable marketing strategy is needed to accelerate its development. This study aimed to analyze marketing strategies for the heritage tourist attraction of the Manuaba Royal Palace in the Kenderan Tourism Village, Bali. A mixed method research design was used by conducting interviews with the managers of as many as 30 Manuaba Royal Palace tourist destinations who met the inclusion and exclusion criteria. The data obtained were analyzed using IFAS, EFAS, and SWOT matrices and are presented descriptively. The results show that the Manuaba Royal Palace has implemented the 7P marketing mix strategy, currently in Quadrant I (a very favorable situation because it has great opportunities to demonstrate internal strength) and S<O (the direction of Manuaba Royal Pae's policy in growth strategy conditions). The current focus and marketing strategy includes developing technology-based historical courses accompanied by the use of social media, presenting information related to intangible cultural heritage, and guiding tourists more massively by providing exclusive packages for booking heritage tourism online. In the future, it is important to maximize the marketing strategies used to increase the number of visits and to be more competitive in the tourism industry.
Impact of Investment, Funding, and Profitability on Indonesian Manufacturing Firm Valuation
Authors: Kepramareni Putu , Mirayani Luh Putri Mas , Idayani Ni Putu Tisha Manika
Published: March 2024

This research seeks to examine the impact of investment decisions, funding choices, dividend policies, company growth, and profitability on the valuation of manufacturing firms listed on the Indonesia Stock Exchange from 2020 to 2022. The analytical approach employed involves multiple linear regression analysis, utilizing annual data collected from manufacturing companies listed on the Indonesia Stock Exchange within the specified timeframe. The research sample consists of 135 selected entities determined through the purposive sampling method. The outcomes of the research reveal that investment decisions exert a negative impact on company value, whereas funding and profitability decisions demonstrate a positive influence on company value. However, dividend policy and company growth do not exhibit a statistically significant effect on company value. These results contribute to a more profound comprehension of the determinants shaping company value within the realm of manufacturing companies in Indonesia. This could serve as a reference for corporate managers when formulating strategic decisions to enhance their company's value. It is anticipated that future research endeavors may build upon this research by incorporating additional variables with potential impacts on company value, such as capital structure.
Forming an Optimal Portfolio with a Single Index Model: Empirical study on banking stocks in the LQ45 Index
Authors: Suarjana I Wayan , Surasmi Ida Ayu
Published: March 2024

The aim of forming an optimal portfolio in this research is to determine the composition of the shares that form the portfolio. Apart from that, this research also aims to determine the expected return and risk of the portfolio being formed. The research sample is 5 banks included in the LQ45 Index. The data used is monthly stock prices. Data analysis uses a single index model, where the reference index is the Composite Stock Price Index on the Indonesian Stock Exchange. The results of the analysis found that there were shares of 4 banks that were included in the optimal portfolio. The proportion of each stock in the portfolio is as follows: Bank Mandiri 60.13%, Bank BRI 26.71%, Bank BCA 8.91%, and Bank BNI 4.25%. The portfolio formed is able to minimize risk compared to the shares that form the portfolio.
PENGARUH PROFITABILITY RATIO, LEVERAGE DAN MARKET RATIO TERHADAP RETURN SAHAM SEKTOR ENERGI DI BEI
Authors: Patni Ida Ayu Gede Gandhi , Wirya Sanjaya I Ketut Puja , Purnami A.A. Sri
Published: March 2024

Tujuan penelitian ini adalah untuk mengetahui pengaruh profitability ratio, leverage, dan market ratio terhadap return saham. Penelitian ini mengunakan jenis data kuantitif dengan sumber data sekunder yang diperoleh dari www.idx.co.id. Teknik pengambilan sampel menggunakan teknik purposive sampling, sehingga terdapat 60 data yang diperoleh dari 15 perusahaan sampel dengan 4 tahun pengamatan dari tahun 2018-2021. Teknik analisis data yang digunakan adalah analisis regresi linier berganda dimana variabel independenya adalah profitability ratio yang diwakilkan dengan ROE, leverage yang diwakilkan dengan DER, dan market ratio yang diwakilkan dengan EPS dan DPR. Sedangkan variabel dependenya adalah return saham. Hasil uji statistik F (Simultan) menyatakan bahwa nilai signifikansi sebesar 0,000 lebih kecil dari 0,050 yang artinya variabel ROE, DER, EPS, dan DPR secara bersama-sama berpengaruh signifikan terhadap return saham. Sedangkan hasil uji t (Parsial) menunjukan bahwa ROE berpengaruh positif dan signifikan terhadap return saham, DER berpengaruh negatif tidak signifikan terhadap return saham, EPS berpengaruh negatif tidak signifikan terhadap return saham, dan DPR berpengaruh positif tidak signifikan terhadap return saham.
PENGARUH PENGUNGKAPAN ENVIRONMENTAL, SOCIAL, AND GOVERNANCE (ESG) TERHADAP EFISIENSI INVESTASI
Authors: Fajri Yudha  , Rahman Annisaa
Published: March 2024

This research aims to test and analyze the influence of ESG disclosure both in aggregate and the influence of partial ESG components consisting of environmental, social and corporate governance disclosures on investment efficiency in companies listed on the IDX for the 2017-2021 period. Data collection in this research used the documentation method. This research uses purposive sampling as a sampling method with a total sample of 210 companies listed on the IDX. The results of this study show that aggregate ESG disclosure has a positive effect on investment efficiency. Meanwhile, partial ESG disclosure has no influence on investment efficiency. The findings of this research provide important awareness to companies regarding the benefits of carrying out comprehensive ESG disclosures.
Pengaruh Aktivitas sosial Dan Lingkungan Terhadap Nilai perusahaan Dengan Gender Deversity Sebagai variabel Moderasi Pada Perusahaan Pertambangan
Authors: Kartana I Wayan , Eryani I Gusti Agung Putu , Putra I Made Wianto , Ekayani Ni Nengah Seri
Published: March 2024

Penelitian ini bertujuan menginvestigasi peranan moderasi Gender Diversity Dewan Direksi dan Gender Diversity Dewan Komisaris atas pengaruh aktivitas sosial dan aktivitas lingkungan terhadap nilai perusahaan. Populasi penelitian adalah Perusahaan Pertambangan terdaftar di Bursa Efek Indonesia dari Tahun 2017 sampai 2021. Variabel penelitian ini terdiri dari: variabel independen yaitu aktivitas sosial dan aktivitas lingkungan, variabel dependen yaitu nilai perusahaam diukur dengan price book value (PBV), variabel moderasi gender diversity Dewan Direksi dan Dewan Komisaris serta menggunakan 3 variabel kontrol yaitu ukuran perusahaan (size), umur perusahaan serta return on assets (RAO). Penelitian ini menggunakan teknik analisis regresi linear berganda dengan SPSS 17.0. Hasil penelitian menunjukan aktivitas sosial berpengaruh negatif signifikan terhadap nilai perusahaan, aktivitas lingkungan berpengaruh positif signifikan terhadap nilai perusahaan. Hasil pengujian moderasi Gender Diversity Dewan Direksi berperan memperlemah pengaruh aktivitas lingkungan terhadap nilai perusahaan, namaun tidak berperan mememoderasi pengaruh aktivitas sosial terhadap nilai perusahaan. Gender Diversity Dewan Komisaris  berperan memperkuat pengaruh aktivitas lingkungan terhadap nilai perusahaan namum berperan memperlemah pengaruh aktivitas sosial terhadap nilai perusahaan. Hasil pengujian variabel kontrol umur perusahaan dan ROA berpengaruh terhadap nilai perusahaan, tetapi size tidak berpengaruh terhadap nilai perusahaan. Limitasi penelitian ini belum memasukan aktivitas ekonomi dan tata kelola sebagai diterminan dari nialai perusahaan dan tekanan stakeholder sebagai variabel moderasi.