Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Determining The Elderly to Use Technology

The use of technology among the elderly depends much on their acceptance and willingness to explore and apply a technology. Previous studies have been conducted to understand the factors that influence the acceptance of electronic technology among the elderly. Therefore, there is a need to have further study on this. In the Malaysian context, studies among the elderly on the acceptance of technology are not ignored. The Malaysian government puts in tremendous efforts to disseminate information and develop facilities for the public through information technology (ICT). The proposed methodology would be quantitative and qualitative. Therefore, the factors that influence the acceptance of technologies among Malaysian senior citizens are interesting to be explored and thus, this becomes the objective of this research.
Dielectric influence on IV curve of graphene field effect transistor

In this article, we have studied the influence of Si3N4 and SiO2 thin film gate dielectrics on the current-voltage characteristics of the graphene-based transistor. The test structure of graphene transistor was fabricated with the top and back gate. Graphene has been produced by chemical vapor deposition, and then transferred to the silicon dioxide on a silicon wafer. The channel of the transistor has been formed by etching in oxygen plasma through a photolithographic mask. Metals electrodes of the drain, source, and gate were deposited by resistive evaporation in a vacuum. It was used titanium / aluminum with a thickness of 50/200 nm. In the case of the back gate, silicon dioxide was used, obtained by thermal oxidation of the silicon substrate. For top gate was used silicon nitride deposited by plasma chemical deposition. It was demonstrated that field effect is more pronounced for the case of SiO2 back gate compare to the Si3N4 top gate. For the SiO2 back gate we have observed that the source- drain current decreases, from 2 mA to 3 mA, with increasing the gate voltage, from 0 to 40 V, at constant source-drain voltage, 2 V. In case of Si3N4 top gate the modulation of source-drain current was not significant for the comparable electric field strength. Based on the value of gate voltage for current minima in transfer function the poor quality of Si3N4 –graphene interface is concluded.
Dosimetric Analysis of Axillary Lymph Node Coverage Using High Tangents in the Prone Position for Left-Sided Breast Cancers

Aim/Objective: Prone positioning is often used to reduce the dose to organs at risk during adjuvant breast irradiation. High tangents are used with supine treatments in patients with the low-volume nodal disease to increase nodal coverage while minimizing toxicities. Our study aims to evaluate nodal coverage for patients treated in the prone position with high tangents. Materials and Methods: Our study analyzed the plans for 20 patients with early-stage, left-sided breast cancers treated at our institution from 2018 to 2019. All patients were treated in the prone position. Axillary nodal levels I-III were contoured, and treatment plans were generated using high tangents. The heart, bilateral lungs, and breast tissue were retrospectively contoured. All plans were evaluated to a dose of 42.4 Gy in 16 fractions. Results: Level I lymph node levels had a mean coverage of 99% of the prescription dose (range: 98-100%). Similarly, level II coverage was approximately 88% (range: 65-100%). The mean coverage for level III was approximately 25% (range: 0-52%). The mean heart dose, mean lung volume receiving ≥20 Gy (V20) for the bilateral lungs, and ipsilateral V20 were 1.69 Gy, 1.64%, and 3.56%, respectively. Conclusion:Treating patients in the prone position with high tangents provides excellent coverage of axillary levels I and II, although there is minimal coverage of axillary level III. Prospective trials are needed to evaluate the clinical outcomes when treating patients with high tangents in the prone position.
Analysis of Fine Dining Restaurant Reviews for Perception of Customers Restaurant Service Quality

The purpose of this study is to model the perception of customers’ service quality in fine dining restaurants (FDRs) and to determine customer sentiments towards the service quality. I analyzed 22,104 reviews of 25 restaurants on TripAdvisor through Aspect-Based Sentiment Analysis (ABSA). In terms of n-gram language models, the classification performance of sentiment polarity was tested with Support Vector Machine (SVM), Naive Bayes (NB), C4.5, and Gradient Boosted Trees (GBT). I compared the performance of the model with Cohen’s kappa, accuracy, precision, recall, and F-measure results. I found five topic models service, experience, surprise, taste, and food kind by using latent Dirichlet allocation (LDA). In sentiment classification, SVM achieved the best results in bigram with 74.5% average F-measure, 94.4% accuracy, and 49.2% kappa results. This study contributes to the elements related to the perception of service quality in FDRs with psychological quality proposed by the surprise topic. This is one of the few studies conducted with ABSA on the perception of service quality in FDRs, and it is the first study examining the issue in terms of n-gram language models.
Endoscopic Screening Program for Control of Esophageal Adenocarcinoma in Varied Populations: A Comparative Cost-Effectiveness Analysis.

BACKGROUND AND AIMS Guidelines suggest endoscopic screening for esophageal adenocarcinoma (EAC) among individuals with symptoms of gastroesophageal reflux disease (GERD) and additional risk factors. We aimed to determine at what age to perform screening and whether sex and race should influence the decision. METHODS We conducted comparative cost-effectiveness analyses using three independent simulation models. For each combination of sex and race (white/black, 100,000 individuals each), we considered 41 screening strategies, including one time or repeated screening. The optimal strategy was that with the highest effectiveness and an incremental cost-effectiveness ratio less than $100,000 per quality-adjusted life-year gained. RESULTS Among white men, 536 EAC deaths were projected without screening, and screening individuals with GERD twice at ages 45 and 60 years was optimal. Screening the entire white male population once at age 55 years was optimal in 26% of probabilistic sensitivity analysis (PSA) runs. Black men had fewer EAC deaths without screening (84), and screening those with GERD once at age 55 years was optimal. Although white women had slightly more EAC deaths (103) than black men, the optimal strategy was no screening, though screening those with GERD once at age 55 years was optimal in 29% of PSA runs. Black women had a very low burden of EAC deaths (29), and no screening was optimal as benefits were very small and some strategies caused net harm. CONCLUSION The optimal strategy of screening differs by race and sex. White men with GERD symptoms can potentially be screened more intensely than currently recommended. Screening women is not cost-effective and may cause net harm for black women.
Slow and temperature-compensated autonomous disassembly of KaiB–KaiC complex

KaiC is the central pacemaker of the circadian clock system in cyanobacteria and forms the core in the hetero-multimeric complexes, such as KaiB–KaiC and KaiA–KaiB–KaiC. Although the formation process and structure of the binary and ternary complexes have been studied extensively, their disassembly dynamics have remained elusive. In this study, we constructed an experimental system to directly measure the autonomous disassembly of the KaiB–KaiC complex under the condition where the dissociated KaiB cannot reassociate with KaiC. At 30°C, the dephosphorylated KaiB–KaiC complex disassembled with an apparent rate of 2.1±0.3 d–1, which was approximately twice the circadian frequency. Our present analysis using a series of KaiC mutants revealed that the apparent disassembly rate correlates with the frequency of the KaiC phosphorylation cycle in the presence of KaiA and KaiB and is robustly temperature-compensated with a Q10 value of 1.05±0.20. The autonomous cancellation of the interactions stabilizing the KaiB–KaiC interface is one of the important phenomena that provide a link between the molecular-scale and system-scale properties.
An averaging process on hypergraphs

Abstract Consider the following iterated process on a hypergraph H. Each vertex v starts with some initial weight $x_v$ . At each step, uniformly at random select an edge e in H, and for each vertex v in e replace the weight of v by the average value of the vertex weights over all vertices in e. This is a generalization of an interactive process on graphs which was first introduced by Aldous and Lanoue. In this paper we use the eigenvalues of a Laplacian for hypergraphs to bound the rate of convergence for this iterated averaging process.
Transmission Line Matrix Method for Two-dimensional Modeling of Terahertz Gaussian Beam Propagation

We present a two-dimensional Transmission Line Matrix (2D TLM) to simulate wave propagation and scattering inside and around an inhomogeneous cylinder for terahertz (THz) imaging. As a particular application, the proposed method is used to construct the dielec- tric proflle or image of cylindrical sample. We compare and validate the 2D TLM with FDTD using TM-mode propagation through inflnitely long lossless and lossy polyethylene cylinders.
Surveying for Natural Enemies of Tuta absoluta (Meyrick) in Selected Parts of Zambia

Tuta absoluta (Meyrick) is a major pest of tomato for both greenhouse and field-grown. In Zambia, it was first reported in 2016 and has since caused far huge damage to the crop. Several interventions were embarked on ranging from the use of neem but chemicals have been mainly used to control the pest. The purpose of our research was to survey and identify indigenous natural enemies for T. absoluta associated with tomato in the central and Lusaka provinces of Zambia. Surveys were conducted in both in the rainy and dry seasons of 2019 in five sites and potential natural enemies collected were sent to CABI Plantwise laboratory for identification. A predatory species from the family of Miridae was found and its DNA 100% matched Nesidiocoris Tenuis (Reuter) and was later collected for rearing at the University of Zambia Insectaria. This species is reported for the first time on T. absoluta in Zambia. Nesidiocoris tenuis identification will provide a scientific basis for biological control of T. absoluta.
OPTIMALISASI LAHAN TANAH UNTUK AREA RUMAH DAN JALAN MENGGUNAKAN ALGORITMA GENETIKA

Bisnis properti sangat menjanjikan dan sangat banyak peminatnya. Karena pasar dan harga properti yang semakin meningkat setiap harinya. Dalam memulai bisnis properti seperti membangun perumahan dan jalan pada sebidang tanah diperlukan adanya perhitungan agar tanah yang ada dapat dioptimalkan penggunaannya terhadap berbagai tipe kaveling rumah yang akan ditempatkan . Algoritma Genetika telah dipergunakan secara luas dan telah berhasil untuk berbagai optimalisasi permasalahan seperti penentuan jadwal, penentuan rute dan penentuan ruang. Algoritma Genetika dipilih karena dapat memperoleh kombinasi paling optimal tanpa harus mencoba semua kemungkinan kombinasi. Beberapa penelitian menggunakan Algoritma Genetika adalah dalam penyusunan barang, tata letak ruangan, desain ruang dalam rumah, dan pengepakan pallet dalam container dengan forklift. Penelitian ini dimulai dengan identifikasi atribut dan kriteria dalam penempatan kaveling area rumah, merepresentasikan lahan tanah ke dalam grid sebagai struktur kromosom, membuat fungsi kecocokan berdasarkan kriteria, proses optimalisasi lahan tanah untuk area rumah dan jalan dengan Algoritma Genetika, dan menerjemahkan kembali kode hasil perhitungan menjadi denah kaveling area rumah dan jalan yang akan dibangun. Penelitian ini telah menghasilkan sistem optimalisasi lahan dengan jumlah pelanggaran sebanyak 124 pelanggaran. Dalam nilai pelanggaran tersebut terdapat sisa grid lahan pada pinggir area rumah yang dapat dimanfaatkan menjadi taman sebagai fasilitas umum. Perangkat lunak akan dimplementasikan agar mudah digunakan bagi para developer rumah. Kata kunci : Algoritma Genetika, lahan tanah, mutasi, optimalisasi, persilangan, perumahan
Användning av Anammox för en förbättrad kväveavskiljning vid avloppsverk

Man kan fa stor energibesparing och minskad klimatpaverkan om deammonifikation kan anvandas for att avskilja kvave ur huvudstrommen vid kommunala avloppsreningsverk. Processen sker utan oxidation av organiskt material vilket ger mojlighet till okad biogasproduktion. Deammonifikation bestar av biokemiska reaktioner i tva steg: 1) partiell nitritation (da halften av inkommande ammoniummangd oxideras till nitrit med hjalp av aeroba ammoniakoxiderande bakterier, AOB) och 2) anammox (da resten av ammonium och den bildade nitriten overgar till kvavgas med hjalp av anammoxbakterier). Syre behovs bara till steg 1, och ingen extern kolkalla behover tillforas. I dag anvands deammonifikation for rening av varmt och kvaverikt rejektvatten fran slamavvattning, dar det gar att halla hog hastighet pa processen och undvika oxidation av nitrit till nitrat av nitritoxiderande bakterier (NOB). I reningsverkets huvudstrom med relativt kallt och kvavefattigt vatten ar utmaningarna dels att behalla tillracklig biomassa eftersom AOB och anammoxbakterier tillvaxer langsamt, dels att undvika nitritoxidation av NOB som konkurrerar med AOB om syre. Forskare vid kth och chalmers har gjort pilotforsok vid Hammarby Sjostadsverket i en reaktor pa 200 l med biofilmsbarare (MBBR). Forsoken drevs som en enstegsprocess med partiell nitritation och anammox i samma reaktor. Forst studerades effekten av en gradvis sankning av temperaturen fran 19 till 10 °C, och darefter effekten av sankt ammoniumhalt i inkommande avloppsvatten fran 500 till 45 mg/l vid konstant lag temperatur (13 °C). Kvaveforeningarnas koncentration mattes i inflode och utflode. Aktiviteten hos bakteriegrupperna mattes med tester av deras syreupptagning och kvaveupptagning samt formaga att bilda kvavgas. Den mikrobiella sammansattningen studerades. Resultaten visade att mellan 19 och 16 °C var kvaveavskiljningen hog (> 70 procent). Vid 13 °C var kvaveavskiljningen lagre (55 %) och vid 10 °C blev processen instabil med mycket lag avskiljningsgrad (< 20 %). Temperatursankningen paverkade bakteriesammansattningen marginellt. Anammoxbakterierna dominerade biomassan, AOB utgjorde en lagre men stabil andel ytterst i biofilmen och NOB en mycket lag men stabil andel. Vid sankningen av kvavehalten i avloppsvattnet vid lag temperatur (13 °C) var avskiljningsgraden mattlig (< 47 %). Oavsett syrehalten oxiderade NOB stora delar av all nitrit till nitrat. Det visar att det ar svart att undvika oonskad nitritoxidation enbart med styrning av syrehalten i en MBBR vid laga temperaturer och laga kvavehalter. Sankt kvavehalt hade liten paverkan pa den mikrobiella sammansattningen. Det var mikroorganismernas aktivitet snarare an antal och sammansattning som forandrades. Forsoken visade att bararna effektivt kvarhaller langsamvaxande biomassa aven i kalla och kvavefattiga vatten. For framtida tillampning av deammonifikation av huvudstromsvatten maste betydelsen av NOB minska, nagot som kraver forskning och nya strategier.
Search Engine Optimization: A Study

As popularity of web increases, millions of people use search engines to discover information. But search engine users are interested only in top few result pages. So promoting a website in search engine result is a major task in website development. Search engine optimization (SEO) is to complete this work. But sometimes black hat SEO techniques are used which mislead the search engine and increase page ranking higher than deserved in search engine results. This paper present feature of search engine page rank algorithms, SEO techniques and black hat SEO techniques.
Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub‐daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state‐of‐the art applications of ML for water quality models and discuss opportunities to improve the use of ML with emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model‐data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge‐guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision‐relevant predictions of riverine water quality.
A review on phytochemistry and pharmacology of Eclipta alba L.: A valuable medicinal plant

Eclipta alba L. is a medicinal plant included in the Asteraceae family. This plant is generally called as false daisy and bhringaraj. In traditional medicine, this plant is utilized to medicate various diseases in humans such as diabetes, coronary heart disease, gastrointestinal disease, skin disease, vitiligo, skin lesions, respiratory diseases and high blood pressure. Additionally, Eclipta alba has been widely utilized as a hair grower and dye. Eclipta alba contains various active compounds such as glycosides, triterpenoids, alkaloids, flavonoids, coumestans and polyacetyl. This plant is believed to have several pharmacological activities such as antibacterial, antifungal, anthelmintic, antimalarial, hepatoprotective, neuroprotective, immunomodulatory, analgesic, diuretic, hypolipidemic, anti-inflammatory, antidiabetic, antioxidant, anticancer, hair growth promoting, memory enhancing and antivenom. The aim of this review as discussions on the taxonomy, plant description, geographical distribution, phytochemistry, traditional use, medicinal value, pharmacological activity of the Eclipta alba L.
Blood Urea Nitrogen as a Prognostic Marker in Severe Acute Pancreatitis

Objectives To explore independent risk factors with good and early predictive power for SAP severity and prognosis. Methods Patients with SAP were enrolled at Central South University Xiangya Hospital between April 2017 and May 2021 and used as the training cohort. From June 2021 to February 2022, all patients with SAP were defined as external patients for validation. Patients were grouped by survival status at a 30-day posthospital admission and then compared in terms of basic information and laboratory tests to screen the independent risk factors. Results A total of 249 patients with SAP were enrolled in the training cohort. The all-cause mortality rate at a 30-day postadmission was 25.8% (51/198). Blood urea nitrogen (BUN) levels were significantly higher in the mortality group (20.45 [interquartile range (IQR), 19.7] mmol/L) than in the survival group (6.685 [IQR, 6.3] mmol/L; P < 0.001). After propensity score matching (PSM), the BUN level was still higher in the mortality group than in the survival group (18.415 [IQR, 19.555] mmol/L vs. 10.63 [IQR, 6.03] mmol/L; P = 0.005). The area under the curve (AUC) of the receiver operating characteristic curve (ROC) of BUN was 0.820 (95% confidence interval, 0.721–0.870; P < 0.001). The optimal BUN level cut-off for predicting a 30-day all-cause mortality was 10.745 mmol/L. Moreover, patients with SAP were grouped according to BUN levels and stratified according to optimal cut-off value. Patients with high BNU levels were associated with significantly higher rates of invasive mechanical ventilation (before PSM: 61.8% vs. 20.6%, P < 0.001; after PSM: 71.1% vs. 32%, P = 0.048) and a 30-day all-cause mortality (before PSM: 44.9% vs. 6.9%, P < 0.001; after PSM: 60% vs. 34.5%, P = 0.032) than those with low BNU levels before or after PSM. The effectiveness of BUN as a prognostic marker was further validated using ROC curves for the external validation set (n = 49). The AUC of BUN was 0.803 (95% CI, 0.655–0.950; P = 0.011). It showed a good ability to predict a 30-day all-cause mortality in patients with SAP. We also observed similar results regarding disease severity, including the Acute Physiology and Chronic Health Evaluation II score (before PSM: 16 [IQR, 8] vs. 8 [IQR, 6], P < 0.001; after PSM: 18 [IQR, 10] vs. 12 [IQR, 7], P < 0.001), SOFA score (before PSM: 7 [IQR, 5] vs. 3 [IQR, 3], P < 0.001; after PSM: 8 [IQR, 5] vs. 5 [IQR, 3.5], P < 0.001), and mMarshall score (before PSM: 4 [IQR, 3] vs. 3 [IQR, 1], P < 0.001; after PSM: 5 [IQR, 2.5] vs. 3 [IQR, 1], P < 0.001). There was significant increase in intensive care unit occupancy in the high BUN level group before PSM (93.3% vs. 73.1%, P < 0.001), but not after PSM (97.8% vs. 86.2%, P = 0.074). Conclusions Our results showed that BUN levels within 24 h after hospital admission were independent risk factors for a 30-day all-cause death in patients with SAP.
IMPLEMENTASI TRANSFER LEARNING DALAM MENDETEKSI PENYAKIT PADA DAUN GANDUM

Wheat is one of the most frequently consumed commodities of Indonesian people. This plant is often consumed as an carbohydrate addition or rice substitution. Most Indonesians process the wheat for ingredients such as flour, bread, instant noodles, cereals and other processed ingredients. Unfortunately, the demand for wheat is not suitable with level of production. One of the factors that hinder wheat production is crop failure due to disease or pests. Diseases that are often found in wheat are Septoria and Stripe Rust. The disease can be identified by color and leaf spot, but it is difficult to distinguish between the two diseases. With the rapid development of technology, this problem can be solved using one of the deep learning techniques known as transfer learning. The purpose of this study was to test five pretrained models to diagnose disease in wheat leaf, the models tested were InceptionV3, MobileNetV2, VGG16, ResNet101V2, DenseNet201. The results of testing and comparing five pretrained models, InceptionV3 gives better results than other models with a low computation time of only 976 seconds or the equivalent of 16 minutes and has a very high accuracy.