bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Advancements in Detection and Quantification of Malaria Using Artificial Intelligence
Authors: Yahuza Kabir , Umar Aliyu M , Salisu Baha'uddeen , Atalabi, E. T.  , Gambo Mukhtar Lawal , Abdulkadir Bashir 
Published: September 2024

Study’s Novelty/Excerpt

A review of recent advancements in artificial intelligence (AI)-based techniques, convolutional neural networks (CNNs) and deep learning, for malaria detection and quantification, is presented.
The strengths and limitations of AI approaches in analyzing digital images and blood smears as well as current challenges, including dataset scarcity and algorithm robustness were explored.
The potential scalability of AI-powered systems in resource-limited areas is discussed so as to provide insights to the future of AI-assisted malaria diagnostics and global disease control strategies.

Full Abstract
Plasmodium parasites are the principal causative agents of malaria, a highly infectious and sometimes fatal illness. It is a serious worldwide health risk, particularly in tropical and subtropical areas, where it has become a significant public health threat. Thus, its diagnosis must be timely, efficient, and accurate to allow suitable management and effective control of the disease. With recent technological advancements, it became possible to use current advances in image processing and machine learning to apply artificial intelligence (AI) for the detection /quantification of malaria parasites. The goal of this paper is to present a thorough analysis of the most advanced AI-assisted techniques available today, such as convolutional neural networks (CNNs), deep learning, and computer vision approaches, highlighting their strengths and limitations for identifying and quantifying malaria parasites in a variety of biological materials, including digital photos and blood smears. The review also discusses key challenges and future trends in AI-powered malaria detection, such as dataset scarcity, stability and robustness of algorithms, and scalability at a geographic level for resource-constraining areas. In conclusion, through critically examining the existing literature and research findings, this review showcases the potential of AI-driven technologies to revolutionize malaria diagnosis and surveillance with a view to guiding stakeholders in the choice of effective control strategies against this infectious disease.
Kearifan Lokal Dari Situs Candi Nusantara
Authors: Heru Suherman Lim  
Published: September 2024

Candi-candi di Indonesia pada umumnya berbentuk massa yang tertutup, ritualnya dilakukan di luar bangunan. Dengan demikian ruang luar mempunyai peranan yang sangat penting dalam mendukung fungsi pada candi-candi di Nusantara. Jika dihubungkan dengan pembangunan suatu candi, arah dapat ditentukan oleh mata angin, namun juga oleh pergerakan bintang tertentu. Perletakan candi ini dapat diduga merujuk pada konstelasi bintang tertentu, karena di arah tenggara tidak didapatkan gunung atau benda alam yang lain di bumi sebagai rujukan orientasi. Hal ini dapat dikaitkan pembentukan mandala sebagai dasar perletakkannya. Seperti halnya di Yunani, manusia India atau Timur termasuk Nusantara memandang segala yang dilihat dan dialami sebagai sesuatu kosmos yang agung. Pembagian proporsi yang harmonis dikerjakan bukan karena pemikiran geometris semata melainkan dipengaruhi pula oleh pemikiran kosmologi maka munculah isitilah Mandala.
Perbandingan Kepuasan Pelanggan Terhadap 3 Brand Minuman Kekinian di Medan
Authors: Erickho Chandra  , Ester Fanny Nagatan  , Fendy Wangsa  , Leo Kendrew  , Valencia Taifanny  
Published: September 2024

The main objective of this study was to determine the satisfaction comparison between 3 contemporary beverage brands in Medan. This research falls into the category of quantitative research. The study population consisted of consumers of the contemporary beverage brands TOMORO, KOPI KENANGAN and STARBUCKS in Medan city, and a sample of 30 respondents was selected using the simple random sampling method. Data collection was carried out using a questionnaire via google form. From the analysis, it was found that the KOPI KENANGAN beverage brand has a higher level of satisfaction compared to the TOMORO and STARBUCKS beverage brands. This is due to affordable prices, large product variations and good product quality.
Kajian Sistematic Implementasi Hypnoparenting Dalam Pengasuhan Anak Usia Dini
Authors: Dahlia Dahlia  , J Andree Eko Nugroho  , Willie Japaries  
Published: September 2024

Child is a picture of the future for the family, both and bad character of the child in the future is a reflection of the education received in childhood in the family. Therefore, parents strive to provide good education, nurturing and balanced nutrition for their growth and development. All of that can be done by applying the best method to children in their golden age.
One parenting method that parents can use is hypnoparenting. Hypnoparenting is educating children by giving positive suggestions in order to form a good personality and morals. The purpose of this writing is to explain the concept of hypnoparenting to help parents in parenting at an early age. Methods used in This research is a literature review with data sources obtained from scientific journals and research reports related to the problem.
Sentiment Analysis on Twitter Data using Machine Learning Techniques
Authors: Siddiqui Muhammad Faizan , Iqbal Faiza , Hussain Naveed 
Published: September 2024

Sentiment analysis is a major field of text mining domain. It is used to analyze opinions, sentiments and ideas from any natural language text for example English. In this paper, we have presented an application called “Tweemotions” which uses sentiment analyses to find the opinion about tweets and categorized it as positive or negative comment. The application is, first, trained and tested using a dataset which consists of thousands of tweets obtained from NLTK Corpora. Later, it is trained and tested on twitter’s data directly from obtained from Twitter. Tweemotions is trained and tested using seven “Machine Learning” algorithms such as BernoulliNB, MultinomialNB, Logistic Regression, stochastic gradient descent (SGD) classifier, LinearSVC, SVC, and NuSVC. The application achieved above 81% accuracy when trained using MultinomialNB, BernoulliNB, SVC and NuSVC.
KẾT QUẢ ĐIỀU TRỊ CỨNG KHỚP THÁI DƯƠNG HÀM BẰNG PHƯƠNG PHÁP CẮT CHỎM LỒI CẦU VÀ GHÉP TRUNG BÌ MỠ TỰ THÂN
Authors: Vũ Trung Trực , Bùi Mai Anh 
Published: September 2024

Mục tiêu nghiên cứu: Mô tả đặc điểm lâm sàng, X-quang của bệnh nhân cứng khớp thái dương hàm được điều trị bằng phương pháp cắt chỏm lồi cầu và ghép trung bì mỡ tự thân tại bệnh viện Hữu nghị Việt Đức và nhận xét kết quả điều trị của nhóm bệnh nhân này. Đối tượng và phương pháp nghiên cứu: Các bệnh nhân được chẩn đoán cứng khớp thái dương hàm một bên hoặc hai bên do nguyên nhân tại khớp dựa trên khám lâm sàng và chẩn đoán hình ảnh được phẫu thuật bằng phương pháp cắt chỏm lồi cầu và ghép trung bì mỡ tự thân tại bệnh viện Hữu nghị Việt Đức từ tháng 03 năm 2008 đến tháng 03 năm 2023. Nghiên cứu mô tả cắt ngang. Kết quả: Tỷ lệ nam giới 75%, đa số bệnh nhân từ 19 đến 39 tuổi (7/12 trường hợp), nguyên nhân chính là do chấn thương (58,3%). Cứng khớp một bên gặp ở 7 trường hợp, 5 trường hợp còn lại cứng khớp 2 bên. Đa số cứng khớp độ 3-4 theo Dongmei He (75%). Theo dõi tối thiểu 12 tháng sau phẫu thuật, há miệng tối đa trung bình là 25,3mm (thông số này trước phẫu thuật là 8,6mm), có hai trường hợp cứng khớp tái phát, 2 trường hợp khớp cắn hở cửa. Kết quả điều trị thành công 83,3%. Kết luận: Cứng khớp thái dương hàm gặp nhiều hơn ở nam giới và sau chấn thương. Điều trị bằng phương pháp cắt chỏm lồi cầu và ghép trung bì mỡ tự thân cho kết quả tốt, đơn giản, dễ thực hiện.
DỊCH TỄ HỌC LÂM SÀNG, CẬN LÂM SÀNG BỆNH CÚM MÙA Ở TRẺ EM TẠI BỆNH VIỆN NHI HẢI DƯƠNG
Authors: Bùi Thị Thu Thủy , Nguyễn Thị Diệu Thúy , Nguyễn Thị Thu Hiền , Nguyễn Thị Hoàng Anh , Đặng Thị Hà 
Published: September 2024

Mục tiêu: Mô tả đặc điểm dịch tễ học lâm sàng, cận lâm sàng bệnh cúm mùa ở trẻ em điều trị tại bệnh viện Nhi Hải Dương năm 2023-2024. Đối tượng: Nghiên cứu bao gồm 151 bệnh nhi được chẩn đoán cúm mùa điều trị tại Bệnh viện Nhi Hải Dương từ 1/7/2023 đến 31/3/2024. Phương pháp nghiên cứu: Nghiên cứu mô tả cắt ngang. Kết quả: Độ tuổi trung bình của đối tượng nghiên cứu là 44,69 tháng (1,3 - 164,4 tháng tuổi), trong đó trẻ em từ 12-60 tháng tuổi là nhóm tuổi hay gặp. Tỷ lệ nhiễm cúm A là 89,4%, cúm B là 10,6%. Tỷ lệ mắc nhiều nhất trong năm là vào mùa đông. Các triệu chứng lâm sàng hay gặp là sốt cao (98,7%), nhiệt độ trung bình là 39,17 ± 0,7 °C, ho (80,1%), chảy mũi (53%). Các triệu chứng khác như đau đầu, đau cơ, co giật, nôn, tiêu chảy ít phổ biến hơn. Cận lâm sàng: 32,2% bệnh nhân có bạch cầu tăng và 4,7% có giảm bạch cầu. 76,4% không tăng CRP (<10 mg/L). Kết luận: Độ tuổi hay gặp nhiễm cúm là bệnh nhân nhi 12-60 tháng. Các triệu chứng lâm sàng và cận lâm sàng thường gặp không đặc hiệu
KHẢO SÁT KHẢ NĂNG GẮN SẮT TOÀN PHẦN HUYẾT TƯƠNG Ở BỆNH NHÂN BỆNH THẬN MẠN TÍNH GIAI ĐOẠN CUỐI
Authors: Bùi Văn Tuấn , Đặng Thành Chung , Lê Việt Thắng 
Published: September 2024

Mục tiêu: Khảo sát khả năng gắn sắt toàn phần huyết tương (Total iron binding capacity - TIBC) và mối liên quan với một số đặc điểm lâm sàng và cận lâm sàng ở bệnh nhân bệnh thận mạn tính giai đoạn cuối. Đối tượng và phương pháp: Nghiên cứu mô tả, cắt ngang trên 157 bệnh nhân bệnh thận mạn tính giai đoạn cuối và 54 người bình thường tương đồng về tuổi và giới tại Bệnh viện Quân y 103 từ tháng 1 năm 2022 đến tháng 12 năm 2023. Thu thập đặc điểm lâm sàng, cận lâm sàng của đối tượng nghiên cứu, nồng độ TIBC huyết tương được định lượng bằng phương pháp ELISA. Kết quả: Nồng độ TIBC trung bình nhóm bệnh 51,61 (21,69 – 73,03) (µmol/l) thấp hơn nhóm chứng là 70,39 (47,31 – 90,19) (µmol/l) với p < 0,001.Tỷ lệ BN giảm TIBC huyết tương là 28,7%. Tỷ lệ giảm TIBC ở nam là 36,1%, cao hơn ở nữ là 20,3% với p < 0,05. Nồng độ TIBC liên quan đến tuổi, tuổi ≥ 60 tỷ lệ giảm TIBC cao nhất với p < 0,05. Nồng độ TIBC tương quan thuận với nồng độ Protein (r = 0,213, p < 0,01). Nồng độ TIBC tương quan thuận với số lượng Hồng cầu (r = 0,192, p < 0,05), Hemoglobin (r = 0,229, p < 0,005) và với Hematocrit (r = 0,215, p < 0,01). Kết luận: Nồng độ TIBC huyết tương giảm ở bệnh nhân bệnh thận mạn tính giai đoạn cuối. Nồng độ TIBC huyết tương liên quan đến giới tính, tuổi. Nồng độ TIBC tương quan thuận với nồng độ Protein và các chỉ số hồng cầu.
Multi-year observations of variable incomplete combustion in the New York megacity
Authors: Schiferl Luke D. , Cao Cong , Dalton Bronte , Hallward-Driemeier Andrew , Toledo-Crow Ricardo , Commane Róisín 
Published: September 2024

Abstract. Carbon monoxide (CO) is a regulated air pollutant that impacts tropospheric chemistry and is an important indicator of the incomplete combustion of carbon-based fuels. In this study, we used 4 years (2019–2022) of winter and spring (January–May) atmospheric CO observations to quantify and characterize city-scale CO enhancements (ΔCO) from the New York City metropolitan area (NYCMA). We observed large variability in ΔCO, roughly 60 % of which was explained by atmospheric transport from the surrounding surface areas to the measurement sites, with the remaining 40 % due to changes in emissions on sub-monthly timescales. We evaluated the CO emissions from the Emissions Database for Global Atmospheric Research (EDGAR), which has been used to scale greenhouse gas emissions, and found the emissions are much too low in magnitude. During the COVID-19 shutdown in spring 2020, we observed a flattening of the diurnal pattern of CO emissions, consistent with reductions in daytime transportation. Our results highlight the role of meteorology in driving the variability in air pollutants and show that the transportation sector is unlikely to account for the non-shutdown observed CO emission magnitude and variability, an important distinction for determining the sources of combustion emissions in urban regions like the NYCMA.
Climate and ablation observations from automatic ablation and weather stations at A. P. Olsen Ice Cap transect, northeast Greenland, for May 2008 through May 2022
Authors: Larsen Signe Hillerup , Binder Daniel , Rutishauser Anja , Hynek Bernhard , Fausto Robert Schjøtt , Citterio Michele 
Published: September 2024

Abstract. The negative surface mass balance of glaciers and ice caps under a warming climate impacts local ecosystems, influencing the volume and timing of water flow in local catchments while also contributing to global sea level rise. Peripheral glaciers distinct to the Greenland ice sheet respond faster to climate change than the main ice sheet. Accurate assessment of surface mass balance depends on in situ observations of near-surface climate and ice ablation, but very few in situ observations of near-surface climate and ice ablation are freely available for Greenland's peripheral glaciers. The transect of three automated weather and ablation stations on the peripheral A. P. Olsen Ice Cap in northeast Greenland is an example of these much needed data. The transect has been monitored since 2008, and in 2022, the old weather and ablation stations were replaced by a new standardized setup. In order to ensure comparable data quality of the old and new monitoring station setups, it is necessary to re-evaluate the data collected between 2008 and 2022. This paper presents the fully reprocessed near-surface climate and ablation data from the A. P. Olsen Ice Cap transect from 2008 to 2022, with a focus on data quality and the usability in ice ablation process studies. The usability of the data is exemplified by the data in an energy balance melt model for two different years. We show that the inherent uncertainties in the data result in an accurate reproduction of ice ablation for just one of the two years. A transect of three automatic ablation and weather stations of this length is unique to Greenland's peripheral glaciers, and it has a broad scale of usage from input to climate reanalysis and detailed surface ablation studies. The dataset can be downloaded at https://doi.org/10.22008/FK2/X9X9GN (Larsen and Citterio, 2023).
Weekly green tide mapping in the Yellow Sea with deep learning: integrating optical and synthetic aperture radar ocean imagery
Authors: Gao Le , Guo Yuan , Li Xiaofeng 
Published: September 2024

Abstract. Since 2008, the Yellow Sea has experienced the world's largest-scale marine disaster, the green tide, marked by the rapid proliferation and accumulation of large floating algae. Leveraging advanced artificial intelligence (AI) models, namely AlgaeNet and GANet, this study comprehensively extracted and analyzed green tide occurrences using optical Moderate Resolution Imaging Spectroradiometer (MODIS) images and microwave Sentinel-1 synthetic aperture radar (SAR) images. However, due to cloud and rain interference and the varying observation frequencies of the two types of satellites, the daily green tide coverage time series throughout the entire life cycle often contain large gaps and missing frames, resulting in discontinuity and limiting their use. Therefore, this study presents a continuous and seamless weekly average green tide coverage dataset with a resolution of 500 m, by integrating highly precise daily optical and SAR data for each week during the green tide breakout. The uncertainty assessment shows that this weekly product conforms to the life pattern of green tide outbreaks and exhibits parabolic-curve-like characteristics, with a low uncertainty (R2=0.89 and RMSE=275 km2). This weekly dataset offers reliable long-term data spanning 15 years, facilitating research in forecasting, climate change analysis, numerical simulation, and disaster prevention planning in the Yellow Sea. The dataset is accessible through the Oceanographic Data Center, Chinese Academy of Sciences (CASODC), along with comprehensive reuse instructions provided at https://doi.org/10.12157/IOCAS.20240410.002 (Gao et al., 2024).
Experimental marketing at pondok pesantren Indonesia
Authors: Wahyuni Sri Intan , Kurnia Fitri Melisa , Hayati Syarifatul 
Published: September 2024

One of the objectives of this reaserch is to find out how Experiential Marketing is impelented at Pondok Pesantren. Judging from the growth and development experienced by Pondok Pesantren Syafa’aturrasul from 2018 to 2022, public interest continues to increase, so that the number of students at Pondok Pesantren Syafa’aturrasul currently stands at 1500 students. Seeing this potential, the researcher was interested in conducting research on experiential marketing conducted by Pondok Pesantren This research is a qualitative descriptive study using triangulation to test the validity of the data. The data collection techniques are interviews, observation, documentation and questionnaires. Based on data analysis, strategies for implementing experiential marketing, namely in terms of sense, feel, think, act and relate marketing. The result of data analysis show that Pondok Pesantren implements experiential marketing well.
Genomic analysis of cultivated infant microbiomes identifies Bifidobacterium 2’-fucosyllactose utilization can be facilitated by co-existing species
Authors: Lou Clare 
Published: September 2024

Human milk oligosaccharides (HMOs) ensure proper infant gut microbiome establishment. Isolate studies have revealed the genetic basis for HMO metabolism, but they exclude the possibility of HMO assimilation via synergistic interactions involving multiple organisms. Here, we investigated microbiome responses to 2'-fucosyllactose (2’FL), a prevalent HMO and infant formula additive, by establishing individualized microbiomes using fecal samples from three different infants as the inocula. Bifidobacterium breve, a prominent member of infant microbiomes, typically cannot metabolize 2’FL. Using metagenomic data, we predicted that extracellular fucosidases encoded by co-existing members such as Ruminococcus gnavus initiate 2’FL breakdown, thus critical for B. breve’s growth. Using both targeted co-cultures and by supplementation of R. gnavus into one microbiome, we show that R. gnavus can promote extensive growth of B. breve through the release of lactose from 2’FL. Overall, microbiome cultivation combined with genome-resolved metagenomics demonstrated that HMO utilization can vary with an individual’s microbiome.Link to OA paper: https://www.biorxiv.org/content/10.1101/2023.03.10.532136v1
Achieving pan-microbiome biological insights via the dbBact knowledge base
Authors: Shental Noam 
Published: September 2024

Microbiome 16S rRNA studies have examined diverse habitats, including oceans, soil, plants, animals, and large cross-sectional human studies. However, finding commonalities between different experiments, habitats, or conditions is very difficult due to technical issues related to using different primer pairs and relying on taxonomy for scientific reporting. Hence, grosso modo, the 16S rRNA microbiome literature has not been integrated into a collaborative body of knowledge. It often comprises effectively isolated studies, where researchers may be completely unaware of commonalities between their findings and those in other studies, especially across different niches or habitats. In the past five years, we have created dbBact (www.dbbact.org), a knowledge base, to bridge this gap and lay the groundwork for gaining core pan-microbiome insights. Briefly, amplicon sequence variants (ASVs) from datasets of published papers are manually analyzed, and bacterial sequences associated with experimental conditions are uploaded to dbBact, together with ontology-based characterizations (e.g., “the abundance of sequence ACTGGA… was higher in fecal samples of horses with colitis compared to healthy controls in California”). To date, dbBact contains data from more than 1000 published studies across diverse habitats, spanning 370,000 unique 16S rRNA ASVs, with approximately 1,500,000 sequence-to-phenotype associations. We demonstrated how dbBact provides many types of novel hypotheses that cannot be formulated by standard methods (Amir et al., Nucleic Acids Research, 2023). We will show how dbBact may be (1) applied as part of microbiome research in any niche; (2) allow a new type of meta-analysis; and (3) be harnessed to answer ecological questions. Link to publication: https://academic.oup.com/nar/article/51/13/6593/7199329?login=true
Comparative Genomic and Metagenomic Investigations of the Corynebacterium tuberculostearicum Species Complex Reveals Potential Mechanisms Underlying Associations To Skin Health and Disease
Authors: Salamzade Rauf 
Published: September 2024

Corynebacterium are a diverse genus and dominant member of the human skin microbiome. Recently, we reported that the most prevalent Corynebacterium species found on skin, including Corynebacterium tuberculostearicum and Corynebacterium kefirresidentii, comprise a narrow species complex despite the diversity of the genus. Here, we apply high-resolution phylogenomics and comparative genomics to describe the structure of the C. tuberculostearicum species complex and highlight genetic traits which are enriched or depleted in it relative to other Corynebacterium. Through metagenomic investigations, we also find that individual species within the complex can associate with specific body sites. Finally, we discover that one species from the complex, C. kefirresidentii, increases in relative abundance during atopic dermatitis flares, and show that most genomes of this species encode a colocalized set of putative virulence genes.Link to OA paper: https://journals.asm.org/doi/10.1128/spectrum.03578-22
Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity
Authors: Peng Ye 
Published: September 2024

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.Link to OA paper: https://www.tandfonline.com/doi/full/10.1080/19490976.2024.2323234