bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-Destructive Assessment of Agarwood Resin Formation Status in Aquilaria crassna using Near-Infrared Spectroscopy
Authors: Herath, H.M.W.A.I.  , Jinendra, B.M.S.  
Published: February 2024

Agarwood is a unique and valuable resin synthesized within a few tree species of the tree family Thymelaeaceae primarily as a self-defence mechanism against stress causes such as fungal invasions. Instead, artificial inoculation leads to short-time harvesting practiced in intensive commercial-level cultivations. The extraction of this resin can be done only after the harvesting where accurate estimation of resin yield is crucial for avoiding immature or underdeveloped harvesting. However, the amount of resin accumulated in the trunk cannot be estimated by the outside inspection. As a result, trees are being cut down before they have reached their maximum harvest potential. Therefore, precise detection of fragrant resin formation status inside the tree has become one of the primary challenges in the agarwood production industry. Currently, the methods available are either destructive, inefficient, or inaccurate. As such, this study evaluates the possibility of the use of NIR spectroscopy as a non-destructive and quick detection method for agarwood formations status inside trees in the in-situ mode. Near-infrared (NIR) range (588–1,025 nm) spectra were acquired from resin-formed and non-formed areas from twenty tree trunks of agarwood with five different formation levels. The best agarwood formation areas of logs were assigned as class level 1 and the least was assigned as the class level 5. The spectra were acquired near the opening made for the artificial inoculation process of considered Aquilaria crassna tree trunks. The results of Soft Independent Modelling of Class Analogies showed consistent evidence of differences in the NIR spectral profiles of all levels of agarwood formations. The SIMCA discrimination between the resin developed versus not was achieved with 86% accuracy. The accuracy rates of the degree of the presence of agarwood were obtained as 80%, 100%, 85%, 90%, and 85% respectively, as assigned levels 1 to 5 in the SIMCA models. This research revealed the potential possibility of using NIR technology for the prediction of agarwood resin status inside the agarwood tree in A. crassna before harvesting the tree as a non-destructive and rapid method.

Keywords: NIR spectroscopy, Agarwood, Aquilaria crassna, Non-destructive, Agarwood formation
Surface Modification of Montmorillonite Clay Towards the Fabrication of Nanocomposites for Engineering Applications
Authors: Nayanthara, H.H.D.  , Karunarathne, P.K.D.M.C.  , Narangoda, C.J.  
Published: February 2024

Montmorillonite (MMT) is a layered clay mineral composed of silica and alumina sheets with a layer thickness of about 1 nm qualifies it as a two-dimensional nanomaterial. MMT is found in natural clay ores in the Murunkan, Kirinda, and Okanda areas in Sri Lanka. Nanocomposites with enhanced physical and mechanical properties can be prepared by dispersing MMT in a polymer matrix. However, the hydrophilic nature of MMT hinders the incorporation of MMT into hydrophobic polymer matrices. Hence, a suitable surface modification is required to make MMT compatible with polymers. The present study was based on the preparation and analysis of organically modified calcium Montmorillonite (Ca-MMT)-polypropylene nanocomposites as a green technology initiative. Homo-ionic Ca-MMT was prepared by treating commercial MMT-K10 with a CaCl2 solution. The predominant exchangeable divalent cations present in MMT-K10 and Ca-MMT were determined using AAS. The cation exchange capacity of Ca-MMT was about two times greater than that of MMT-K10. Furthermore, XRD analysis showed a slight increase in d- spacing of Ca-MMT compared to MMT-K10. A novel ligand, triethylene glycol dodecyl methyl ether was synthesized by treating triethylene glycol monomethyl ether (TGME) with 50% w/w aqueous solution of sodium hydroxide followed by 1-bromododecane with the molar ratio of TGME:NaOH:1-bromododecane in 1:2:2. The crude product was purified by column chromatography and characterized by FTIR and GCMS analysis. Hydrophilic Ca-MMT was surface modified with the organic ligand presumably via the coordination of triethylene glycol moiety with Ca2+ cations at the outer edge of the MMT particles. The long aliphatic chains in the periphery of the modified MMT particle make it more organophilic. Modified Ca-MMT was characterized by XRD, TGA, and FTIR analysis. The XRD revealed a slight increase in the d-spacing related to the 001 plane of modified Ca-MMT compared to unmodified clay. The effect of modified Ca-MMT loadings (0.5%, 1%, and 1.5%) on the mechanical properties of the nanocomposite was studied. The results implied an enhancement of the mechanical properties in terms of impact resistance, hardness, and flexural properties in the nanocomposite compared to the virgin polymer. The fabricated nanocomposite is a promising engineering material that may have applications in automotive, construction, and packaging products.

Keywords: Montmorillonite, Polypropylene, Nanocomposite, TGME, Compatibility
Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment Using Convolutional Neural Networks
Authors: Dakdareh Sara Ghasemi , Abbasian Karim 
Published: February 2024

Background: Alzheimer’s disease and mild cognitive impairment are common diseases in the elderly, affecting more than 50 million people worldwide in 2020. Early diagnosis is crucial for managing these diseases, but their complexity poses a challenge. Convolutional neural networks have shown promise in accurate diagnosis. Objective: The main objective of this research is to diagnose Alzheimer’s disease and mild cognitive impairment in healthy individuals using convolutional neural networks. Methods: This study utilized three different convolutional neural network models, two of which were pre-trained models, namely AlexNet and DenseNet, while the third model was a CNN1D-LSTM neural network. Results: Among the neural network models used, the AlexNet demonstrated the highest accuracy, exceeding 98%, in diagnosing mild cognitive impairment and Alzheimer’s disease in healthy individuals. Furthermore, the accuracy of the DenseNet and CNN1D-LSTM models is 88% and 91.89%, respectively. Conclusions: The research highlights the potential of convolutional neural networks in diagnosing mild cognitive impairment and Alzheimer’s disease. The use of pre-trained neural networks and the integration of various patient data contribute to achieving accurate results. The high accuracy achieved by the AlexNet neural network underscores its effectiveness in disease classification. These findings pave the way for future research and improvements in the field of diagnosing these diseases using convolutional neural networks, ultimately aiding in early detection and effective management of mild cognitive impairment and Alzheimer’s disease.
Bagaimana prediksi kebangkrutan maskapai di Indonesia menggunakan metode Altman Z-Score?
Authors: Duri Rafika , Kusumawardhani Mawar Ratih 
Published: February 2024

Penelitian ini bertujuan untuk memprediksi kebangkrutan pada salah satu maskapai di Indonesia yaitu PT. Garuda Indonesia (Persero) Tbk dengan menggunakan metode Altman Z-Score. Jenis penelitian ini menggunakan pendekatan deskriptif kuantitatif dengan menggunakan data sekunder yang diambil dari Bursa Efek Indonesia (BEI) berupa data laporan keuangan yang dipublikasikan dari tahun 2017 sampai 2021. Penelitian ini menggunakan jenis pengambilan sampel non probability sampling dengan teknik pengambilan purposive sampling. Hasil penelitian menggunakan Altman Z-Score untuk periode yang diteliti diprediksi mengalami kebangkrutan. Hasil ini diharapkan untuk tahun kondisi mendatang PT. Garuda Indonesia (Persero) Tbk akan membaik dengan memperbaiki sistem manajemen perusahaan menjadi lebih baik lagi.
«Сарыарқа» газетінің қазақ журналистикасы тарихындағы орны
Authors: Рамазан А.А. , Қуантаев Н.К. , Каpимова Б.Ж. 
Published: February 2024

Мақала қазақ журналистикасы тарихында ерекше орны бар, «Алаш» партиясының жария үні болған «Сарыарқа» газетінің тарихы мен шығарушылары туралы, тақырыптық ерекшеліктері жөнінде деректерді салыстыра бағамдауға арналып отыр.
Қазақ журналистикасы тарихында тұңғыш саяси басылым ретінде шығып тұрған «Сарыарқа» газеті алғашқы сандарынан бастап халыққа бостандық пен теңдіктің мәнін терең түсіндіріп, үндеу жасап, саяси өзгерістерді батыл талдауға үлгі көрсете білген басылым. «Алаш» партиясы құрылғаннан бастап, партия тарапынан өткізілген іс-шаралардың бәрі газет бетінде толық көрініс тапты. А.Байтұрсынұлы шығарған «Қазақ» газеті қазақ ұлтының оянуына түрткі болса, ал «Қазақтан» нәр алған «Сарыарқа» басылымы оянған ұлттың жаңа мемлекет құрудағы талпынысын, ұмтылысын толық бейнелей алды.
Зерттеу мақаланың мақсаты – «Алаш» партиясының жария үні болған «Сарыарқа» газетінің қазақ елінің шынайы тарихын қалыпқа келтірудегі маңыздылығын басты назарда ұстай отырып, қазақ журналистикасының дамуына қосқан үлесін бағалау, басылымда қажырлы еңбек еткен Алаш қайраткерлерінің публицистикалық мұрасына баға беру және бүгінгі ұрпаққа насихаттау.
Мақаланы жазу барысында «Сарыарқа» газетіне қатысты тың деректер пайдаланылды, бүркеншік есімдерге тaлдaу жасалынып, басылымның тарихы мен даму ерекшеліктеріне cараптама жасалынды.
Pengaruh Kepemimpinan, Motivasi, Komunikasi Terhadap Kinerja Pegawai
Authors: Riyanti Tri Yuni , Budianto Apri , Herman Ferey 
Published: February 2024

Penelitian ini melakuakn sebuah riset penelitian dalam menilai pengaruh pengembangan sumber daya manusia berbasis kompetensi terhadap kualitas pelayanan.
Rumusan masalah yang diajukan dalam penelitian ini yaitu sebagai berikut: 1) Pengaruh kepemimpinan terhadap kinerja pegawai. 2) Pengaruh motivasi terhadap kinerja pegawai. 3) Pengarauh komunikasi terhadap kinerja pegawai.4) Pengaruh kepemimpinan, motivasi dan komunikasi terhadap kinerja pada keluarahan sekecamatan cilacap selatan.
Metode penelitian yang digunakan adalah metode kuantitatif deskriptif dengan metode penyebaran kusioner atau angket. Teknik pengumpulan data dalam penelitian ini adalah studi pustaka dan studi lapangan. Sedangkan teknis analisis data yang digunakan penulis dalam penelitian ini yaitu dengan penyebaran kusioner Dari hasil penelitian diperoleh bahwa: 1) Hasil dari penelitian kepemimpinan, motivasi dan komunikasi pada kelurahan sekecamatan Cilacap berpengaruh positif terhadap kinerja dan berpengaruh signifikan, artinya apabila kepemimpinan, motivasi dan komunikasi yang sangat tinggi maka akan berpengaruh terhadap kinerja pegawai. Jadi kepemimpinan, motivasi dan komunikasi adalah factor utama dalam meningkatkan kinerja pegawai di kelurahan sekecamatan cialacap selatan.
Pengaruh Pengembangan Sumber Daya Manusia Berbasis Kompetensi Terhadap Kualitas Pelayanan (Studi pada RSUD Cilacap)
Authors: Santoso Budi Joko , Budianto Apri , Herman Ferey 
Published: February 2024

Penelitian ini melakuakn sebuah riset dalam menilai pengaruh pengembangan sumber daya manusia berbasis kompetensi terhadap kualitas pelayanan. Rumusan masalah yang diajukan dalam penelitian ini yaitu sebagai berikut: 1) Bagaimana pengaruh pengembangan Sumber Daya Manusia tehadap kualitas pelayanan di RSUD Cilacap. Metode penelitian yang digunakan adalah metode kuantitatif deskriptif dengan metode penyebaran kusioner atau angket. Teknik pengumpulan data dalam penelitian ini adalah studi pustaka dan studi lapangan. Sedangkan teknis analisis data yang digunakan penulis dalam penelitian ini yaitu dengan penyebaran kusioner . Dari hasil penelitian diperoleh bahwa: 1) Hasil dari penelitian pengembangan sumber daya manusia berbasis kompetensi di RSUD Cilacap berpengaruh positif terhadap kualitas pelayanan dan berpengaruh signifikan, artinya apabila pengembangan sumber daya manusia berbasiss kompetensi yang sangat tinggi makan akan berpengaruh terhadap kualitas pelayanan .Jadi pengembangan sumber daya manusia berbasis kompetensi adalah factor utama dalam meningkatkan kinerja petugas pada RSUD Cilacap akan meningkat pula.
Efecto residual de desinfectantes de uso hospitalario frente a Acinetobacter baumannii
Authors: Llanga Ayol Katherine Estefanía , Tapia Vallejo Verónica Esperanza , Arteaga Sarmiento Sandra Denisse 
Published: February 2024

Introducción. Acinetobacter baumannii (A. baumannii) es un patógeno multirresistente responsable de infecciones nosocomiales principalmente en la unidad de cuidados intensivos (UCI) y en pacientes inmunocomprometidos. Como medida para evitar la propagación de la bacteria, es necesario realizar la desinfección frecuente en las áreas de atención al paciente y los instrumentos empleados para ello. Por lo que resulta de gran importancia evaluar el efecto residual de los desinfectantes recomendados por el Ministerio de Salud Pública para ser utilizados en ambientes hospitalarios. Objetivo. Verificar la efectividad residual de yodopovidona, peróxido de hidrógeno, glutaraldehído, clorhexidina, hipoclorito de sodio, amonio cuaternario y monopersulfato de potasio empleados como desinfectantes de uso hospitalario frente a A. baumannii. Metodología. Se trató de un estudio cuantitativo, descriptivo y longitudinal, se emplearon cepa de A. baumannii, sobre las cuales se evaluó el efecto residual de clorhexidina, hipoclorito de sodio, amonio cuaternario y monopersulfato de potasio en diferentes periodos de tiempo. Resultados. El glutaraldehído y la clorhexidina fueron los desinfectantes con mejor efecto residual, manteniéndose efectivos hasta las 24 horas, sin embargo, sus halos de inhibición fueron de diámetro pequeño, con lo que sugiere una posible resistencia a los mismos. Conclusión. Los desinfectantes con mejor efecto residual sobre las A. baumannii fueron glutaraldehído y clorhexidina, con inhibición de la bacteria hasta las 24 horas después de su aplicación. De igual forma. El peróxido de hidrógeno obtuvo este efecto hasta las 12 horas. Las concentraciones del hipoclorito de sodio, la yodopovidona y el amonio cuaternario no mostraron efecto residual. Área de estudio general: Bioquímica y Farmacia. Área de estudio específica: Microbiología. Tipo de estudio: Artículo original / Original article.
Production Performances, Meat and Egg Quality, and Serum Biochemical Parameters of Three Native Chicken Genotypes: Laying at Seventh Generation
Authors: Faruque Shakila , Bhuiyan AKFH , Hassan Md Rakibul , Rabbani MAG , Sarker N R , Khatun Halima , Hossain M T , Manu Md Mizanur Rahman , Islam M H , Ali Md Zulfekar 
Published: February 2024

The present study was conducted to assess the laying performances and compare the performances of three native chicken genotypes under intensive management. Egg production was recorded up to 280 days. For Kadaknath (K), a total of 500 pedigree hatched day old chicks were identified individually by wing band. In seventh generation, 26.19%, 10.89% and 18.18% birds of Non-descript Deshi (ND), Hilly (HI) and Naked Neck (NN) had laid egg ranged 80-89%. Chick weight was not affected (p>0.05) by genotype. Fertility of ND, HI and NN was 88.96%, 87.03% and 86.67%, respectively. Significantly (p<0.001) the highest hatchability (90.85%) was found in ND compared to HI (89.25%) and NN (83.94%). The highest egg production number of ND, HI and NN were 79.08, 69.33 and 74.86, respectively. In this study, the average HDEP% of ND, HI and NN were found to be 56.48, 49.52 and 53.47, respectively. Body weight at first lay is 1111.0g and at 8th week is 685.4g. FCR at 0-8 week is 3.0. Significantly (p<0.05) the lowest glucose content was found in K chicken (4.34mMol/L) compared to HI (7.34mMol/L)), NN (5.88mMol/L) and ND (5.76mMol/L). Iron content of blood was non-significantly highest in K chicken compared to other three native chickens. Haemoglobin content of blood was non-significantly highest in HI chicken. ND was superior for egg production, fertility and hatchability traits. No extra ordinary result was found in case of Kadaknath chicken.
SAARC J. Agric., 21(2): 207-216 (2023)
Active trachoma: enhancing image classification using pretrained SOTA models and explainable AI
Authors: Pan Yongjun , Lan Wenyao , Xu Binbin 
Published: February 2024

BackgroundTrachoma, an infectious disease that leads to blindness, continues to pose a significant public health challenge in over 40 countries as of 2023. The initial phase of this disease, “active trachoma” is characterized by inflammation and can be effectively treated with non-surgical interventions. However, if left untreated, it progresses to the “scarring” phase, often requiring surgical intervention. Earlier detection of “active trachoma” is critical to prevent unnecessary surgery and also to reduce the transmission of the infection. Developing accessible tools for a region with limited resources is necessary. Deep neural networks have proven their effectiveness in numerous image and vision-related tasks, yet research on “active trachoma” has received still little attention.MethodIn this study, we adapted several pre-trained state-of-the-art deep neural network models like ResNet, Xception from image classification on “active classification” task. Further experiments were also conducted in three cases: training from scratch, training from pretrained models on raw images and on region-of-interest (ROI) focused images.Results and discussionThe results indicate that these models outperformed the previous studies using the same dataset, achieving an improvement of 6\% on detection of follicular trachomatous inflammation and 12\% for detection of intense trachomatous inflammation. Furthermore, we employed the eXplainable Artificial Intelligence tool Grad-CAM, which revealed a significant discrepancy between eyelid's geometric centroid and attention centroid from models with high classification accuracy. This finding suggests that the conventional method of selecting a region of interest based on the geometric centroid may need to be adjusted. Using XAI can offer valuable insights into understanding the classification and progression of active trachoma.
Enhancing the authenticity of animal by-products: harmonization of DNA extraction methods from novel ingredients
Authors: Filipa-Silva Andreia , Castro Raquel , Rebelo Mariana , Mota Maria J. , Almeida André , Valente Luísa M. P. , Gomes Sónia 
Published: February 2024

Introduction: The increasing global pressure to explore alternative protein sources derived from animal by-products has opened-up opportunities, but it has also created the need to assess their compliance with labelling statements, to ensure consumer’s trust in the composition of both feed and food products. Assessing the authenticity of highly processed animal by-products, particularly within the rapidly expanding Halal food market, presents a significant challenge due to the lack of robust and standardized methodologies. However, the success of DNA based authenticity system is highly dependent on the extracted DNA quantity, quality, and purity ratios from heterogeneous matrices.Material and methods: In this work, nine DNA extraction methods were tested on selected processed animal by-products with high-value and interest for the feed industry: meals from poultry meat, blood and feather, and hydrolysates from swine meat and bone, fish, and black soldier fly. The proposed DNA extraction methods are developed to specifically target swine-specific mitochondrial region, as a case study.Results and discussion: Both the conventional CTAB method and the commercial kits, specifically Invisorb® Spin Tissue Mini and NucleoSpin™ Food, demonstrated superior extraction efficiency and quality ratios. Nevertheless, commercial kits enabled faster detection in comparison to the conventional methods. The absence of swine DNA was successfully validated and confirmed in all animal meals and hydrolysates that did not contain swine in their composition beforehand, demonstrating their compliance with the Halal market requirements.
COVID-19 in pulmonary critically ill patients: metagenomic identification of fungi and characterization of pathogenic microorganisms
Authors: Huang Changjun , Chang Siyuan , Ma Rui , Shang Yishu , Li Yuexia , Wang Yun , Feng Min , Guo Wenzhi 
Published: February 2024

BackgroundFungal co-infection is prevalent in critically ill patients with COVID-19. The conventional approach applied to fungal identification has relatively low sensitivity and is time-consuming. The metagenomic next-generation sequencing (mNGS) technology can simultaneously detect a variety of microorganisms, and is increasingly being used for the rapid detection and diagnosis of pathogens.MethodsIn this single-center retrospective study, we described the clinical presentation and outcomes of COVID-19 and mNGS positive for fungi in pulmonary critically ill patients during the outbreak of Omicron infection from December 2022 to January 2023.ResultsAmong 43 COVID-19 patients with acute respiratory distress syndrome (ARDS) on a single intensive care unit (ICU), 10 were reported to be fungal positive using the mNGS test. The number of pathogenic microorganisms detected by mNGS was significantly higher than that via traditional methods, especially in the detection of fungi and viruses. Aspergillus infection was dominant, and most of these patients also had concurrent bacterial or viral infections. Probable or possible COVID-19-associated pulmonary aspergillosis (CAPA) was diagnosed in all 10 patients, and the prognosis was poor.ConclusionPatients with COVID-19 may be at increased risk of developing fungal infections as well as concurrent bacterial or viral infections, and mNGS can be a powerful tool in identifying these infections. Clinicians should be aware of the increased risk of fungal infections in COVID-19 patients, particularly those who have underlying immunocompromising conditions, and should monitor for early signs of infection.
Identification of a novel Scn3b mutation in a Chinese Brugada syndrome pedigree: implications for Nav1.5 electrophysiological properties and intracellular distribution of Nav1.5 and Navβ3
Authors: Fan Jun , Wang Shao-hua , Cao Li-li , Li Wei-jie , Sun Shao-xi , Luo Shao-ling , Pan Yi-chao , Tan Wen-liang , Wu Tian-yuan , Liu Zhen , Yu Bing-bo 
Published: February 2024

BackgroundThe Scn3b gene encodes for Navβ3, a pivotal regulatory subunit of the fast sodium channel in cardiomyocytes. However, its mutation status in the Chinese population suffering from Brugada Syndrome (BrS) has not been characterized, and the contributory pathophysiological mechanisms to disease pathology remain undefined.Methods and ResultsA Scn3b (c.260C&gt;T, p.P87l) mutation was identified in a patient with BrS of Chinese descent. Functional analyses demonstrated that sodium channel activation for the wild type, mutant samples, and co-expression of both commenced at −55 mv and peaked at −25 mv. The mutant group exhibited a notable reduction, approximately 60%, in peak sodium channel activation current (INa) at −25 mv. The parameters for half-maximal activation voltages (V1/2) and slope factors (k) showed no significant differences when comparing wild type, mutant, and combined expression groups (P = 0.98 and P = 0.65, respectively). Additionally, no significant disparities were evident in terms of the steady-state sodium channel inactivation parameters V1/2 and k (with P-values of 0.85 and 0.25, respectively), nor were there significant differences in the activation time constant τ (P = 0.59) and late sodium current density (P = 0.23) across the wild-type, mutant, and co-expressed groups. Confocal imaging and Western blot analysis demonstrated decreased plasma membrane localization of SCN3B and SCN5A in the P87l group. Computational simulations of cardiac action potentials suggested that SCN3B P87l can alter the morphology of the action potentials within the endocardium and epicardium while reducing the peak of depolarization.ConclusionsThe pathogenic impact of the Scn3b P87l mutation predominantly originates from a reduction in peak INa activation current coupled with decreased cell surface expression of Nav1.5 and Navβ3. These alterations may influence cardiac action potential configurations and contribute to the risk of ventricular arrhythmias in individuals with BrS.