Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Gray Wolf Algorithm for Radiation Near-Field Source Localization in Exact Model

Spectral search algorithms are widely used in radiation near-field (RNF) source locations because of their high estimation accuracy, but they have disadvantages such as large computation and long running time. To solve this problem, the Fresnel model is mainly adopted in the existing works of literature to realize the source location estimation in the algorithm of spectral search. Although the operation time is effectively reduced, there is a mismatch between the Fresnel model and the exact model, resulting in the existing method being not suitable for the source location under the exact model. In order to shorten the running time of the RNF source spectrum search algorithm under the exact model, an improved gray wolf optimal (IGWO) algorithm based on the exact model is proposed to estimate the RNF source position, which guarantees the high precision and shorten the operation time. The algorithm uses the noise subspace fitting method as the cost function and the power function as the convergence factor, which shortens the time required for source location and improves the estimation accuracy of the algorithm. The simulation results show that the IGWO algorithm takes less time and has better estimation accuracy than the existing source location algorithms.
Phenotypic Test of Benzo[4,5]imidazo[1,2-c]pyrimidinone-Based Nucleoside and Non-Nucleoside Derivatives against DNA and RNA Viruses, Including Coronaviruses

Emerging and re-emerging viruses periodically cause outbreaks and epidemics around the world, which ultimately lead to global events such as the COVID-19 pandemic. Thus, the urgent need for new antiviral drugs is obvious. Over more than a century of antiviral development, nucleoside analogs have proven to be promising agents against diversified DNA and RNA viruses. Here, we present the synthesis and evaluation of the antiviral activity of nucleoside analogs and their deglycosylated derivatives based on a hydroxybenzo[4,5]imidazo[1,2-c]pyrimidin-1(2H)-one scaffold. The antiviral activity was evaluated against a panel of structurally and phylogenetically diverse RNA and DNA viruses. The leader compound showed micromolar activity against representatives of the family Coronaviridae, including SARS-CoV-2, as well as against respiratory syncytial virus in a submicromolar range without noticeable toxicity for the host cells. Surprisingly, methylation of the aromatic hydroxyl group of the leader compound resulted in micromolar activity against the varicella-zoster virus without any significant impact on cell viability. The leader compound was shown to be a weak inhibitor of the SARS-CoV-2 RNA-dependent RNA polymerase. It also inhibited biocondensate formation important for SARS-CoV-2 replication. The active compounds may be considered as a good starting point for further structure optimization and mechanistic and preclinical studies.
A Novel Prediction Model Based on Quantitative Texture Analysis of Sonographic Images for Malignant Major Salivary Glandular Tumors

Background: The aim of this study was to compare multiple objective ultrasound (US) texture features and develop an objective predictive model for predicting malignant major salivary glandular tumors. Methods: From August 2007 to May 2018, 144 adult patients who had major salivary gland tumors and subsequently underwent surgery were recruited for this study. Representative brightness mode US pictures were selected for texture analysis and used to develop a prediction model. Results: We found that the grayscale intensity and standard deviation of the intensity were significantly different between malignant and pleomorphic adenomas. The contrast, inverse difference (INV) movement, entropy, dissimilarity, and INV also differed significantly between benign and malignant tumors. We used stepwise selection of predictors to develop an objective predictive model, as follows: Score = 1.138 × Age − 1.814 × Intensity + 1.416 × Entropy + 1.714 × Contrast. With an optimal cutoff of 0.58, the diagnostic performance of this model had a sensitivity, specificity, overall accuracy, and area under the curve of 83% (95% confidence interval [CI]: 74%–92%), 74% (65%–84%), 78% (72%–85%), and 0.86 (0.80–0.92), respectively. Conclusion: We have developed a novel computerized diagnostic model based on objective US features to predict malignant major salivary gland tumor. Further improving the computer-aided diagnosis model might change the US examination for major salivary gland tumors in the future.
Outcome of dose-escalated intensity-modulated radiotherapy for limited disease small cell lung cancer

Purpose An optimal once-daily radiotherapy (RT) regimen is under investigation for definitive concurrent chemoradiotherapy (CCRT) in limited disease small cell lung cancer (LD-SCLC). We compared the efficacy and safety of dose escalation with intensity-modulated radiotherapy (IMRT). Materials and Methods Between January 2016 and March 2021, patients treated with definitive CCRT for LD-SCLC with IMRT were retrospectively reviewed. Patients who received a total dose <50 Gy or those with a history of thoracic RT or surgery were excluded. The patients were divided into two groups (standard and dose-escalated) based on the total biologically effective dose (BED, α/β = 10) of 70 Gy. The chemotherapeutic regimen comprised four cycles of etoposide and cisplatin. Results One hundred and twenty-two patients were analyzed and the median follow-up was 27.8 months (range, 4.4 to 76.9 months). The median age of the patients was 63 years (range, 35 to 78 years) and the majority had a history of smoking (86.0%). The 1- and 3-year overall survival rates of the escalated dose group were significantly higher than those of the standard group (93.5% and 50.5% vs. 76.7% and 33.3%, respectively; p = 0.008), as were the 1- and 3-year freedom from in-field failure rates (91.4% and 66.5% vs. 73.8% and 46.9%, respectively; p = 0.018). The incidence of grade 2 or higher acute and late pneumonitis was not significantly different between the two groups (p = 0.062, 0.185). Conclusion Dose-escalated once-daily CCRT with IMRT led to improved locoregional control and survival, with no increase in toxicity.
Computer representation of complex 3-D velocity models

We present a geologic modeling system that can accept the large, irregular surface and volume data typical of exploration studies. The modelling system is based on topological data structures that are used in other areas of computer-aided geometric design. The explicit representation of the model's topology in the data structures is crucial for carrying out the construction and manipulation of the model. The modelling system provides import functions to build 3-D velocity fields from isolated velocity points and to build 3-D surfaces from a collection of points on the surface. It also provides model visualisation and editing functions to merge multiple horizons and velocity definitions into a single model. We demonstrate the system capabilities with a complex salt body embedded in layered sediments and with a model of intersecting horizons and faults.
Effect of Applying Bandura's Theory of Self-efficacy on Anxiety, Disease Uncertainty and Quality of Life among Women Undergoing Hysterectomy

Background : Hysterectomy as a gynecological surgery cause heavy psychological pressure and affect quality of life of women. The research aim was to evaluate the effect of applying Bandura's theory of self-efficacy on anxiety, disease uncertainty and quality of life among women undergoing hysterectomy. Design : A quasi experimental design. Setting : Obstetrics and Gynecological department in Benha University Hospital. Sample : A purposive sample of 84 women undergoing hysterectomy divided into two groups. Data collection tools: Five tools were used: A structured interviewing questionnaire, the general self-efficacy scale, the self-rating anxiety scale, sense of disease uncertainty scale and World Health Organization quality of life scale. Results: There was no statistical significant difference in the mean scores of the self-efficacy, anxiety, sense of uncertainty and quality of life between the study and control groups at pre intervention phase (p ˃ 0.05) compared to the higher mean score among study group than the control group with a highly statistical significant difference after three and six months of intervention (p ≤ 0.001). Conclusion : The implementation of self-efficacy theory model was effective in improving level of knowledge, reducing level of anxiety and disease uncertainty and improving quality of life among women undergoing hysterectomy. Recommendation: Self-efficacy theory model should be explained in printed booklets that ought to be available to all women undergoing hysterectomy in every obstetrics and gynecological facility.
The Impact of Assisted Reproductive Technology on Umbilical Cord Insertion: Increased Risk of Velamentous Cord Insertion in Singleton Pregnancies Conceived through ICSI

Background and Objectives: Vasa previa (VP) is a significant perinatal complication that can have serious consequences for the fetus/neonate. Velamentous cord insertion (VCI) is a crucial finding in prenatal placental morphology surveillance as it is indicative of comorbid VP. Assisted reproductive technology (ART) has been identified as a risk factor for VCI, so identifying risk factors for VCI in ART could improve VP recognition. This study aims to evaluate the displacement of umbilical cord insertion (CI) from the placental center and to examine the relationship between the modes of conception. Materials and Methods: We conducted a retrospective study at the Obstetrics Department of Osaka Metropolitan University Hospital in Japan between May 2020 and June 2022. The study included a total of 1102 patients who delivered after 22 weeks of gestation. They were divided into three groups: spontaneous pregnancy, conventional in vitro fertilization (cIVF), and in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI). We recorded patient background information, perinatal complications, perinatal outcomes, and a numerical “displacement score”, indicating the degree of separation between umbilical CI and the placental center. Results: The displacement score was significantly higher in the cIVF and IVF/ICSI groups compared with the spontaneous conception group. Additionally, the IVF/ICSI group showed a significantly higher displacement score than the cIVF group. Conclusions: Our study provides the first evidence that the methods of ART can affect the location of umbilical CI on the placental surface. Furthermore, we found that IVF/ICSI may contribute to greater displacement of CI from the placental center.
Pengenalan Ekspresi Wajah dengan CNN dan Wavelet

Dengan berkembangnya teknologi di jaman modern ini diharapkan komputer juga mampu mengenali ekspresi wajah manusia. Hal itu dapat terwujud dengan kemajuan machine learning. Machine learning telah menjadi bagian dari kehidupan sehari-hari bagi banyak orang di seluruh dunia. Penemuan dan implementasi machine learning memungkinkan komputer untuk belajar dan memprediksi pola yang mungkin terjadi dan dapat digunakan untuk membantu manusia melakukan kegiatan sehari-hari. Salah satunya yaitu Convolutional Neural Network. Pada penelitian ini akan digunakan wavelet transform untuk membantu meningkatkan akurasi dari convolutional neural network dan mempercepat peningkatan akurasi. Wavelet berguna untuk melakukan compressing pada gambar sehingga lebih mudah untuk diolah. Gambar yang dihasilkan oleh wavelet terbagi menjadi 4 frekuensi yang berbeda-beda. Setiap gambar yang dihasilkan oleh wavelet diuji cobakan kedalam convolutional neural network. Berdasarkan hasil uji coba yang dilakukan, akurasi terbaik didapatkan dari dataset KDEF dengan menggunakan gambar wavelet berfrekuensi Low-Low (LL) dengan akurasi yang didapatkan sebesar 79%. Sedangkan hasil uji coba menggunakan dataset buatan sendiri didapatkan akurasi terbaik dengan menggunakan wavelet berfrekuensi Low-Low (LL) dengan akurasi yang didapatkan sebesar 36,925%.
Genome-Wide Analysis of Stress-Responsive Genes and Alternative Splice Variants in Arabidopsis Roots under Osmotic Stresses

Plant roots show distinct gene-expression profiles from those of shoots under abiotic stress conditions. In this study, we performed mRNA sequencing (mRNA-Seq) to analyze the transcriptional profiling of Arabidopsis roots under osmotic stress conditions—high salinity (NaCl) and drought (mannitol). The roots demonstrated significantly distinct gene-expression changes from those of the aerial parts under both the NaCl and the mannitol treatment. We identified 68 closely connected transcription-factor genes involved in osmotic stress-signal transduction in roots. Well-known abscisic acid (ABA)-dependent and/or ABA-independent osmotic stress-responsive genes were not considerably upregulated in the roots compared to those in the aerial parts, indicating that the osmotic stress response in the roots may be regulated by other uncharacterized stress pathways. Moreover, we identified 26 osmotic-stress-responsive genes with distinct expressions of alternative splice variants in the roots. The quantitative reverse-transcription polymerase chain reaction further confirmed that alternative splice variants, such as those for ANNAT4, MAGL6, TRM19, and CAD9, were differentially expressed in the roots, suggesting that alternative splicing is an important regulatory mechanism in the osmotic stress response in roots. Altogether, our results suggest that tightly connected transcription-factor families, as well as alternative splicing and the resulting splice variants, are involved in the osmotic stress response in roots.
Managing Healthcare Product Demand Effectively in The Post-Covid-19 Environment: Navigating Demand Variability and Forecasting Complexities

Managing the demand for healthcare products is a complex problem requiring in-depth knowledge of epidemiological trends, supply chain dynamics, and regulatory considerations. The intricate management of healthcare product demand in the post-COVID-19 era is thoroughly explored in this study. It is divided into nine sections exploring various facets of this critical field, emphasizing the persistent demand variations and difficulty in forecasting in the healthcare industry. It underscores the necessity for efficient demand management techniques in the changing healthcare environment. The significance of historical demand trends and provides examples of how studying historical data is essential for comprehending and forecasting the demand for healthcare products. Identifying seasonal fluctuations, forecasting disease outbreaks, and improving inventory management are emphasized. Investigating the difficulties in predicting the need for healthcare products, deals with problems caused by epidemiological ambiguity, supply chain breakdowns, patient demographics, regulatory adjustments, and technological advancements. The importance of data availability and quality in accurate demand forecasting is emphasized in this section. It encompasses scenario planning, resource allocation, technology adoption, supplier diversity, flexible manufacturing, collaborative and information sharing, data-driven decision-making, demand forecasting models, and strategic stockpiling. "Data Analytics and Predictive Modeling in Demand Forecasting," emphasize the function of these techniques in comprehending and forecasting demand trends. All covered are time series analysis, machine learning algorithms, epidemic predictive modeling, supply chain integration, scenario planning, optimization, risk assessment, in-the-moment monitoring, and feedback loops. "Supply Chain Resilience and Demand Response" explains why it's crucial to create robust supply chains and successfully adapt to demand changes. Supplier diversity, strategic stockpiling, agile production, real-time visibility, teamwork, data-driven decision-making, scenario planning, and regulatory flexibility are all covered
Determinação do fluxo de CO2 no norte do Pantanal mato-grossense

ABSTRACT: DETERMINATION OF CO 2 FLOW IN THE NORTHERN “MATO-GROSSENSE” PANTANALIn the Brazilian Pantanal region, there are some monodominant species which are suited as environmental changes indicators. The study of the dynamics of CO 2 exchange between those plants communities and the atmosphere contributes to evaluate those ecosystems behavior. Therefore, the purpose of this study was to determine the CO 2 flux (Acf) of Vochysia divergens Pohl mono species forest in northern Pantanal. The CO 2 flux was estimated by the modified Bowen ratio method. For this, net solar radiation, surface heat flux and soil temperature and air humidity data and CO 2 concentration profiles, collected at a 32m high tower installed in this area were used. The CO 2 concentrations along the canopy profiles ware greater during clear sky conditions in nighttime periods. The Acf over Vochysia divergens Pohl canopy was positive in nighttime period and negative during daytime. The highest Acf values ware collected during clear sky conditions, 75% higher than partly cloudy sky conditions.
Spline Response Functions for Direct and Carry‐over Effects Involving a Single Nutrient

Two continuous models which interpret the principles underlying the law of the minimum in crop response to an essential nutrient are presented. Such single-nutrient response functions are the linear response and plateau model (LRP), and the linear, quadratic and plateau model (LQP). A spline algorithm was developed to estimate these functions. Both functions were applied to data from a field experiment carried out in Salta, Argentina, to study the response of three cuts of Rhodes grass, Chloris gayana Kunth, to N fertilization with urea. Furthermore, two associated models for carry over of available N in the soil, as well as carry-over effects on yield, either within a growth season or between consecutive seasons, were developed. These are the platform and linear response model (PLR), and the platform, quadratic and linear response model (PQL). The LQP model, and its counterpart for carry over (PQL), imply the existence of an apparent, although restricted substitution between the limiting nutrient and the next potential limiting factor, whereas the LRP and PLR models are based on the non-substitution assumption. It is emphasized that the restricted substitution of the LQP and PQL models is strongly situation specific, and that they can collapse into LRP and PLR fits without a quadratic domain, as they often did in this study. The quadratic polynomial equation was used throughout as a reference model with extended substitution. At worst, the spline functions performed equally well as the quadratic polynomial, and in some situations they provided a substantial increase in the goodness of fit. Hence, it is reconfirmed in this study that, while polynomial responses tend to overestimate the optimum fertilizer rate, the LRP and LQP models are better suited to provide more realistic optimum levels of fertilization. The carry-over effect on yield was found to be more relevant within a growth season (R² = 0.58) than between seasons (R² = 0.38). Both the PLR and PQL models were able to explain 90 % of the variability in residual N in the soil as a function of the level of urea applied at the beginning of the growth period. The estimated minimum levels of fertilization required to attain the plateau yield showed a tendency to decrease as a result of the carryover effect. These doses were 430 and 250 kg N ha⁻¹ for the two cuts of the first season, and 223 kg N ha⁻¹ for the first cut of the second season. The methodological contributions of this paper are that: (i) it provides continuity for the LRP model and (ii) the knot(s) of the spline functions are endogenously obtained through an iterative procedure which maximizes the goodness of fit.
Problems Associated with Estimating Ground Water Discharge and Recharge from Stream‐Discharge Records

Ground water discharge and recharge frequently have been estimated with hydrograph‐separation techniques, but the critical assumptions of the techniques have not been investigated. The critical assumptions are that the hydraulic characteristics of the contributing aquifer (recession index) can be estimated from stream‐discharge records; that periods of exclusively ground water discharge can be reliably identified; and that stream‐discharge peaks approximate the magnitude and timing of recharge events. The first assumption was tested by estimating the recession index from stream‐discharge hydrographs, ground water hydrographs, and hydraulic diffusivity estimates from aquifer tests in basins throughout the eastern United States and Montana. The recession index frequently could not be estimated reliably from stream‐discharge records alone because many of the estimates of the recession index were greater than 1000 days. The ratio of stream discharge during base flow periods was two to 36 times greater than the maximum expected range of ground water discharge at 12 of the 13 field sites. The identification of the ground water component of stream‐discharge records was ambiguous because drainage from bank‐storage, wetlands, surface water bodies, soils, and snowpacks frequently exceeded ground water discharge and also decreased exponentially during recession periods. The timing and magnitude of recharge events could not be ascertained from stream‐discharge records at any of the sites investigated because recharge events were not directly correlated with stream peaks. When used alone, the recession‐curve‐displacement method and other hydrograph‐separation techniques are poor tools for estimating ground water discharge or recharge because the major assumptions of the methods are commonly and grossly violated. Multiple, alternative methods of estimating ground water discharge and recharge should be used because of the uncertainty associated with any one technique.