Miracle-dz/UniFAR-FTUs huggingface dataset:
UCLA Radiocarbon Dates III

The measurements reported in this list have been made in the Isotope Laboratory of the Institute of Geophysics during 1963 and are a continuation of the work reported previously (UCLA I and UCLA II). The same counting procedure—CO2 proportional counting at 1 atm pressure in a 7.5 L counter with three energy channels—continues in use. No barometric effect on the background has been observed, presumably because of the combination of fairly constant barometric pressure in this area and the location of the equipment on the ground floor of a five storey building. Dates continue to be calculated on the basis of a C14 half life of 5568 yr according to the decision of the 1962 Cambridge Conference (Godwin, 1962). The modern standard has been taken as 95% of NBS oxalic acid for all organic samples, while for carbonate material such as shells and tufa, dates have been computed on the basis of estimates of the corresponding contemporary C14 activity (Broecker and Walton, 1959) as indicated in the description accompanying the results.
LEAD: THE HEAVY METAL IN SOIL WATER AND PLANT ENVIRONMENT

Contamination of soils by heavy metals is of widespread occurrence as a result of human agricultural and industrial activities. Among heavy metals, lead is a potential pollutant that readily accumulates in soils and sediments. The lead (Pb) concentration in soil range from 2 to 200 ppm, plants 0.1 to 10 ppm, water 0.04 to 0.10 ppm in drinking water and in ground water 0.015 to 0.075 ppm and air 0.1 to 5 ppm. The sources of lead are containing fertilizers, sewage and sludge, industrial wastes which contains many ppm of lead. Although lead is not an essential element for plant growth but its get easily absorbed / adsorbed and gets accumulated in different plant parts. Uptake of Pb in plants is regulated by pH, particle size and cation exchange capacity of the soils as well as root exudation and other physico-chemical parameters. Excess Pb causes number of toxicity symptoms in plants eg. stunted growth, chlorosis and blackkening of root system. In human health is causes diseases like Apathy, Insomina, Coma and >30 ppm of lead exposure claim the life of animal by gestrointestinal pH, stage of lactation or pregnancy. Remediation of soils contaminated with Pb using phytoremediation and rhizofiltration techniques appear to have great potential for cleaning of Pb - contaminated soils.
Temperament, Character and Organisational well-being among Obstetrics and Gynaecology Personnel: a pilot study

Few studies in the literature have related organisational well-being and temperament according to Cloninger’s bio-psycho-social model. This paper investigates the relationship between dimensions of temperament (NS; HA; RD) and character (CO; SD; ST; P) and dimensions of organisational well-being in Obstetrics and Gynaecology personnel. Thirty-eight subjects, predominantly women (89.5%) aged between 18 and 63 years, participated in the study (M=50.20 SD=9.81). The Temperament and Character Inventory of R. Cloninger et al. (1994) extended version and the C.I. V.I. T. questionnaire. Positive correlations emerged between Self-Directedness and positive perceptions of the context and work and negative correlations between Self-Directedness and negative perceptions of job security and discrimination. Work well-being may be related to certain character traits rather than temperament and this correlation suggests a connection between personality and work adaptation.
Why are tradeswomen leaving the construction industry: An Exploratory Study

The construction industry in the United States is currently undergoing historic shortage of skilled workforce. Several research studies have suggested to attract, recruit, and retain women in construction trades to address some of the workforce shortages in the future and also to improve jobsite productivity. Despite undertaking efforts in this direction to improve recruitment and retention of women in trades, it is observed that several women either left or considered leaving construction trades at some point in their careers. Previous studies focused on issues specific to women in administrative, managerial and leadership roles, however there is very limited knowledge relevant to issues of tradeswomen. This study exclusively focuses on tradeswomen and investigates the causes that influences tradeswomen to leave the construction industry with an intent to develop recommendations to improve their retention. To achieve the objectives, this study conducted twelve qualitative interviews with tradeswomen working in a variety of trades. The study identified important factors such as male dominant culture, inadequate attention from employers regarding tradeswomen issues, workplace and sexual harassment, discrimination such as pay imbalances, improper facilities, and misfit PPE Furthermore, recommendations for employers and industry organization were provided to improve tradeswomen retention. Understanding tradeswomen challenges helps improve their retention thereby improving the diversity in construction industry and contributes to the success of tradeswomen.
Background, Sources, and Methods

Background The scope of this book is the Aegean Bronze Age: the history and material cultures of Crete, the Greek mainland, and the Aegean islands during the period when bronze had replaced stone as the dominant material for tools and weapons, and had not yet been supplanted by iron. The period began around 3100/3000 bce and continued until about 1070 bce ; during its course different groups of people rose from basic subsistence to cultural prominence, interacted with each other and with civilizations around the Mediterranean basin, and subsided again beyond our reach. Serious study of the Aegean Bronze Age began over 120 years ago, fueled by several early projects, including exploration by the French on Santorini, the British at Phylakopi on Melos, and Heinrich Schliemann at Troy, Mycenae, and Tiryns. Schliemann was motivated by a fascination with mythical accounts of the Trojan War, and Sir Arthur Evans, the excavator of Knossos, by curiosity about the signs, in an unknown script, incised into lumps of clay found on Crete. None of these pioneers could have imagined the quantities of sites and artifacts that would subsequently be found, the proliferation of new techniques for everything from excavation itself to scientific dating and provenience studies, or the textual information revealed by the decipherment of the Mycenaean script. Early investigators of the Bronze Age tried to characterize and contrast the material culture of different ethnic groups, with special attention to aspects that could be mapped onto a Homeric vision of the Greek past (Ch. 5, pp. 105–6).
Concordancia de la evaluación de tres medidas del gasto cardiaco en pacientes adultos para cirugía cardiaca del hospital cardiovascular del niño de Cundinamarca

a. Profesor Titular, Anestesiología Cardiovascular, Fundación Universitaria de Ciencias de la salud, Hospital San José, Bogotá, Colombia. b. Instructor asociado, Anestesiología Cardiovascular, Fundación Universitaria de Ciencias de la salud, Hospital San José, Bogotá, Colombia. Anestesiólogo Hospital Cardiovascular del Niño de Cundinamarca. c. Instructor asociado, Anestesiología Cardiovascular, Fundación Universitaria de Ciencias de la salud, Hospital San José, Bogotá, Colombia d. Fellow en Anestesiología Cardiovascular, Fundación Universitaria de Ciencias de la salud, Hospital San José, Bogotá, Colombia. e. Fellow en Anestesiología Cardiovascular, Fundación Universitaria de Ciencias de la salud, Hospital San José, Bogotá, Colombia f. Instructor asociado, División de investigaciones, Fundación Universitaria de Ciencias de la salud, Hospital San José, Hospital San José Infantil, Bogotá, Colombia
AC Resistance Reduction of a Flexible Wireless Power Transmission Coil Using Magnetic Path Control Technology at 13.56 MHz

To reduce the size and weight of wireless power transfer devices, lightweight, thin, and highly efficient power-transmitting and power-receiving coils are required. In this paper, we describe a spiral-shaped flexible flat wire coil with reduced ac resistance, which is suitable for being mounted on electric tools and smart phones. A method for reducing the ac resistance of a flexible coil for wireless power transfer at high frequencies is required. The proposed flexible coil uses magnetic path control technology to suppress the skin and proximity effects by applying a magnetic material to the coils. The proposed coil reduces the ac resistance by 18% at 13.56 MHz in the ISM band, and improves the Q value of the coil by 27%. As a result, the transmission efficiency improves by 1.3% when the distance between the coils in 10 mm.
The Role of Glutamine Synthetase (GS) and Glutamate Synthase (GOGAT) in the Improvement of Nitrogen Use Efficiency in Cereals

Cereals are the most broadly produced crops and represent the primary source of food worldwide. Nitrogen (N) is a critical mineral nutrient for plant growth and high yield, and the quality of cereal crops greatly depends on a suitable N supply. In the last decades, a massive use of N fertilizers has been achieved in the desire to have high yields of cereal crops, leading to damaging effects for the environment, ecosystems, and human health. To ensure agricultural sustainability and the required food source, many attempts have been made towards developing cereal crops with a more effective nitrogen use efficiency (NUE). NUE depends on N uptake, utilization, and lastly, combining the capability to assimilate N into carbon skeletons and remobilize the N assimilated. The glutamine synthetase (GS)/glutamate synthase (GOGAT) cycle represents a crucial metabolic step of N assimilation, regulating crop yield. In this review, the physiological and genetic studies on GS and GOGAT of the main cereal crops will be examined, giving emphasis on their implications in NUE.
A Loss Differentiation Method Based on Heterogeneous Ensemble Learning Model for Low Earth Orbit Satellite Networks

In light of the high bit error rate in satellite network links, the traditional transmission control protocol (TCP) fails to distinguish between congestion and wireless losses, and existing loss differentiation methods lack heterogeneous ensemble learning models, especially feature selection for loss differentiation, individual classifier selection methods, effective ensemble strategies, etc. A loss differentiation method based on heterogeneous ensemble learning (LDM-HEL) for low-Earth-orbit (LEO) satellite networks is proposed. This method utilizes the Relief and mutual information algorithms for selecting loss differentiation features and employs the least-squares support vector machine, decision tree, logistic regression, and K-nearest neighbor as individual learners. An ensemble strategy is designed using the stochastic gradient descent method to optimize the weights of individual learners. Simulation results demonstrate that the proposed LDM-HEL achieves higher accuracy rate, recall rate, and F1-score in the simulation scenario, and significantly improves throughput performance when applied to TCP. Compared with the integrated model LDM-satellite, the above indexes can be improved by 4.37%, 4.55%, 4.87%, and 9.28%, respectively.
Estimation of Design Flood for Rivers of Saurashtra Region Contributing into the Gulf of Khambhat

Design flood has been estimated for rivers of Saurashtra region contributing into the Gulf of Khambhat using deterministic as well as statistical approach for planning, design and management of hydraulic structures. By comparing the results obtained by these approaches, one can easily estimate the flow rate or peak discharge to a given design return period and can establish the suitability of approach for this study area. Nine river basins with 20 dams of Saurashtra region were analyzed in this study. Though Saurashtra is one of the most water scarce regions of India yet it suffers from the flooding problem, as the numbers of rainy days are very less and the rainfall intensity is very high. Due to being a regulated basin, dam wise study was preferred. Deterministic approach was carried out using synthetic unit hydrograph (SUH) and regional flood formulae (RFF) methods for subzone-3a provided in Central Water Commission (CWC) report, 2001. Statistical approach was carried out using Rainfall frequency analysis employing Gumbel’s EV1distribution. As there is no spill by these hydraulic structures and the annual flood data for the nine river sites are heavily affected by the storage dams in the upstream. Hence these data violate the basic principle of virgin flow. Hence the analysis of these data was not attempted further. The main objective of study was to carry out the rainfall frequency analysis for these river basins to get 24 hour rainfall for a return period of 25, 50 and 100 years for an individual basin instead of using the value obtained by iso-pluvial map to estimate the design flood. The overall results reveals that due to construction of number of dams in 9 river basins, design flood estimation on each dam by using deterministic approach is more feasible. Revised design floods using SUH and RFF method on the basis of estimated rainfall indicates over-estimated and under-estimated design floods. Since the percentage difference is very less between revised SUH and revised RFF method. So, for safety purpose one with higher value should be used.
Sampling Importance Resampling Algorithm with Nonignorable Missing Response Variable Based on Smoothed Quantile Regression

The presence of nonignorable missing response variables often leads to complex conditional distribution patterns that cannot be effectively captured through mean regression. In contrast, quantile regression offers valuable insights into the conditional distribution. Consequently, this article places emphasis on the quantile regression approach to address nonrandom missing data. Taking inspiration from fractional imputation, this paper proposes a novel smoothed quantile regression estimation equation based on a sampling importance resampling (SIR) algorithm instead of nonparametric kernel regression methods. Additionally, we present an augmented inverse probability weighting (AIPW) smoothed quantile regression estimation equation to reduce the influence of potential misspecification in a working model. The consistency and asymptotic normality of the empirical likelihood estimators corresponding to the above estimating equations are proven under the assumption of a correctly specified parameter working model. Furthermore, we demonstrate that the AIPW estimation equation converges to an IPW estimation equation when a parameter working model is misspecified, thus illustrating the robustness of the AIPW estimation approach. Through numerical simulations, we examine the finite sample properties of the proposed method when the working models are both correctly specified and misspecified. Furthermore, we apply the proposed method to analyze HIV—CD4 data, thereby exploring variations in treatment effects and the influence of other covariates across different quantiles.
Genomic Insights into Molecular Regulation Mechanisms of Intramuscular Fat Deposition in Chicken

Intramuscular fat (IMF) plays an important role in the tenderness, water-holding capacity, and flavor of chicken meat, which directly affect meat quality. In recent years, regulatory mechanisms underlying IMF deposition and the development of effective molecular markers have been hot topics in poultry genetic breeding. Therefore, this review focuses on the current understanding of regulatory mechanisms underlying IMF deposition in chickens, which were identified by multiple genomic approaches, including genome-wide association studies, whole transcriptome sequencing, proteome sequencing, single-cell RNA sequencing (scRNA-seq), high-throughput chromosome conformation capture (HiC), DNA methylation sequencing, and m6A methylation sequencing. This review comprehensively and systematically describes genetic and epigenetic factors associated with IMF deposition, which provides a fundamental resource for biomarkers of IMF deposition and provides promising applications for genetic improvement of meat quality in chicken.
AI-Based Risk Score from Tumour-Infiltrating Lymphocyte Predicts Locoregional-Free Survival in Nasopharyngeal Carcinoma

Simple Summary Plasma Epstein–Barr virus (EBV) DNA is an important prognostic marker for nasopharyngeal carcinoma (NPC). However, EBV DNA is less sensitive to locoregional recurrence compared to distant metastasis in NPC. Numerous findings suggest that the presence of tumour-infiltrating lymphocytes (TILs) is associated with NPC prognosis. Nevertheless, NPC is characterised by the presence of abundant TILs. This study aims to generate TIL scores in NPC from H&E-stained tissue slide images for NPC prognosis. We employed artificial intelligence and deep learning-based method for generating TIL score. Our results indicate that our methods have strong prognostic value compared to the EBV DNA copies in locoregional recurrence cases. Abstract Background: Locoregional recurrence of nasopharyngeal carcinoma (NPC) occurs in 10% to 50% of cases following primary treatment. However, the current main prognostic markers for NPC, both stage and plasma Epstein–Barr virus DNA, are not sensitive to locoregional recurrence. Methods: We gathered 385 whole-slide images (WSIs) from haematoxylin and eosin (H&E)-stained NPC sections (n = 367 cases), which were collected from Sun Yat-sen University Cancer Centre. We developed a deep learning algorithm to detect tumour nuclei and lymphocyte nuclei in WSIs, followed by density-based clustering to quantify the tumour-infiltrating lymphocytes (TILs) into 12 scores. The Random Survival Forest model was then trained on the TILs to generate risk score. Results: Based on Kaplan–Meier analysis, the proposed methods were able to stratify low- and high-risk NPC cases in a validation set of locoregional recurrence with a statically significant result (p < 0.001). This finding was also found in distant metastasis-free survival (p < 0.001), progression-free survival (p < 0.001), and regional recurrence-free survival (p < 0.05). Furthermore, in both univariate analysis (HR: 1.58, CI: 1.13–2.19, p < 0.05) and multivariate analysis (HR:1.59, CI: 1.11–2.28, p < 0.05), we also found that our methods demonstrated a strong prognostic value for locoregional recurrence. Conclusion: The proposed novel digital markers could potentially be utilised to assist treatment decisions in cases of NPC.
Detection, Diagnosis, and Monitoring of Early Caries: The Future of Individualized Dental Care

Dental caries remains a significant global health issue. It was highlighted by the World Health Organization’s 2022 reports that despite the efforts and scientific advancements in caries detection and management, the situation has only marginally improved over the past three decades. The persistence of this problem may be linked to outdated concepts developed almost a century ago but are still guiding dentists’ approach to caries management today. There is a need to reconsider professional strategies for preventing and managing the disease. Contemporary dentistry could benefit from embracing new concepts and technologies for caries detection and management. Dentists should explore, among others, alternative methods for caries detection such as optical-based caries detection. These tools have been established for over a decade and they align with current disease understanding and international recommendations, emphasizing early detection and minimally invasive management. This narrative review presents the current state of knowledge and recent trends in caries detection, diagnosis, monitoring, and management, offering insights into future perspectives for clinical applications and research topics.
Effect of Early Gestational Body Mass Index and Gestational Weight Gain on Pregnancy Outcome

10.30699/jogcr.8. 6.563 Background & Objective: The maintenance of an appropriate weight before and during pregnancy has a significant effect on pregnancy outcomes. Therefore, this study attempts to explore the relationship between pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) in the Indian antenatal population. This was a prospective study. Materials & Methods: This study was conducted on a total of 301 pregnant women who fulfilled the inclusion criteria booked from the first trimester till delivery in the department of Obstetrics and Gynecology, SGRRIM & HS, from January 2020 to June 2021. The weight and height of the participants were recorded at their first visit to the antenatal clinic using standard protocol. BMI was recorded and GWG was calculated at each antenatal clinic visit. BMI and GWG were correlated with antepartum, intrapartum and postpartum complications with the application of appropriate statistical tests. Results: In our study, higher pre-pregnancy BMI and GWG significantly increased the risk of perinatal adverse outcomes. Increased rates of cesarean section (57.1%), operative vaginal delivery (9.5%), gestational diabetes mellitus (9.5%), and pre-eclampsia (28.6%) were observed in obese women as compared to women with normal pre-pregnancy BMI and gestational weight gain. These were found to be statistically significant (p-value <0.001). Conclusion: Appropriate nutrition prior to and throughout the pregnancy plays an important role in determining the health of both mother and fetus. There is a positive correlation between early pregnancy BMI and GWG, and the course of pregnancy, and its outcome.
Dynamic MPC-Based Scheduling in a Smart Manufacturing System Problem

This paper introduces a dynamic scheduling algorithm designed to minimize makespan within a smart manufacturing system, accommodating delays in the production process. The proposed approach relies on Model Predictive Control (MPC) principles and adapts flow-shop scheduling theory to solve an open-shop scheduling problem. It aims to strike a balance between the ideal, delay-free solution and robustness in the case of processing time delays. By combining MPC theory with flow-shop scheduling, the algorithm offers a robust approach to open-shop scheduling problems, even with uncertain processing times. Iterated upon the arrival of each new job on the shop floor, the algorithm incorporates a control horizon to predict impending job arrivals and seamlessly integrates them into the scheduling process. Efficiency is examined through a comprehensive case study, where it is compared against a similar, offline scheduling algorithm. This novel method not only optimizes scheduling but also adapts to dynamic scenarios, reducing the computational demand and the information needed to optimize the production process, thus making it suitable for agile manufacturing environments. The results demonstrate the algorithm’s efficacy in achieving competitive scheduling performance with nearly the same makespan as the offline algorithm, while accounting for uncertainties in processing times. A robustness analysis confirms the reliability of the proposed approach, showing an average improvement of 5% in makespan across different delay magnitudes.