bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of pretreatment routes for seawater desalination by nanofiltration
Authors: Loreti Hupsel Amanda , Borges Cristiano Piacsek , da Fonseca Fabiana Valéria , Barbosa Gisele Mattedi 
Published: January 2024

Abstract

Nanofiltration (NF) has been used as the default sulfate removal process in platforms to treat seawater for water flooding. Seawater is generally pretreated by chlorination and cartridge filters to reduce fouling of the membranes; however, this pretreatment is insufficient to provide water quality high enough to maintain the productivity of the NF membranes. In this study, the performances of two different pretreatment routes were evaluated. Microfiltration (MF) was evaluated as a replacement for cartridge filters, and the advanced oxidation process UV/H2O2 was evaluated as an additional stage of pretreatment upstream of the cartridge filters. The permeability of the NF membranes after 12 h of seawater sulfate removal in a bench system was 4.4 L·h−1·m−2·bar−1 when the UV/H2O2 process was adopted as the pretreatment and 2.9 L·h−1·m−2·bar−1 when the MF process was adopted, compared to 1.6 L·h−1·m−2·bar−1 achieved for the pretreatment with the cartridge filter alone. These results indicate that NF membrane fouling was significantly higher when seawater was pretreated only by the cartridge filter in comparison to both proposed pretreatments. An economic analysis showed that both systems are economically viable and can potentially reduce the operational costs of the NF sulfate removal process on platforms.
Clinical Implementation of Dual-Energy CT Technical for Hepatobiliary
Imaging
Authors: Li Tian , Xiong Hao , Ji Guang-Hai , Zhang Xiao-Han , Peng Jie , Li Bo 
Published: January 2024

Abstract:
Dual-energy computed tomography (DECT) applies two energy spectra distributions to collect raw data based on traditional CT imaging. The
application of hepatobiliary imaging, has the advantages of optimizing the scanning scheme, improving the imaging quality, highlighting the
disease characterization, and increasing the detection rate of lesions. In order to summarize the clinical application value of DECT in hepatobiliary
diseases, we searched the technical principles of DECT and its existing studies, case reports, and clinical guidelines in hepatobiliary imaging from
2010 to 2023 (especially in the past 5 years) through PubMed and CNKI, focusing on the clinical application of DECT in hepatobiliary diseases,
including liver tumors, diffuse liver lesions, and biliary system lesions. The first part of this article briefly describes the basic concept and technical
advantages of DECT. The following will be reviewed:the detection of lesions, diagnosis and differential diagnosis of lesions, hepatic steatosis,
quantitative analysis of liver iron, and analyze the advantages and disadvantages of DECT in hepatobiliary imaging. Finally, the contents of this
paper are summarized and the development prospect of DECT in hepatobiliary imaging is prospected.
Wide-ranging Study on Synthesis and Biological Evaluation of 1, 2, 3-triazole
Authors: Dudhe Anshu , Dudhe Rupesh , Mahajan Renuka , Pathak Neha , Uplanchiwar Vaibhav , Mansoori Mohammad Hashim 
Published: January 2024

Abstract:
1, 2, 3-Traizole is five-membered heterocyclic compounds having three nitrogen at 1, 2
and 3 positions. 1, 2, 3-Triazoles are important five-membered heterocyclic scaffolds due to their
widespread biological activities. 1, 2, 3-Triazole derivative can be readily obtained in good to
excellent yields through click chemistry, 1, 3-dipolar cycloaddition, Metal Catalysed azide-alyne
cycloaddition method. 1, 2, 3-Triazoles showed various biological activities, such as antiinflammatory, anticonvulsant, antineoplastic, antimicrobial, analgesic, antimalarial, antiviral, antiproliferative, and anticancer activities. The objective of this review is to synthesize pharmacological activity of 1,2,3-triazole derivatives documented in recent literature.
Development of Anato-Smart Media as an Interactive Learning Media for Elementary School Students Regarding Limb Anatomy
Authors: Maftuhah Atik 
Published: January 2024

The subject matter of science, especially related to human anatomy, is one of the most challenging to understand. To help understand science materials, especially human body anatomy, we conducted community service by developing the Anato-Smart book as a learning media for students and teachers of 5th grade of Muhammadiyah 1 Elementary School Surakarta in 2021. The method of implementation in this service includes several stages, including determining the topic of the body system for the learning media that would be developed through the Focus Group Discussion for teachers at Muhammadiyah 1 Elementary School Surakarta, followed by the development of interactive and educational story media Anato-Smart with the title “The Adventures of Andi and Si Balung”, then media trials to 5th graders at Muhammadiyah 1 Elementary School Surakarta, as well as interviews and outspread questionnaires for the evaluation of Anato-Smart media. This service activity resulted in an Anato-Smart teaching media developed to hone the students' analytical skills on limb and skeletal topics. Teachers can use this book to augment interactive lessons and as one of the educational resources for students to learn about potential risks and disorders to the limbs and skeleton in daily life. From the evaluation, the story and education concepts in this Anato-Smart media book are intriguing and facilitate comprehension, however, it is better to lessen the words and increase the number of images to make it more interesting for children. We will use this feedback to improve the final results of this media so that it can be used by other schools, not only by Muhammadiyah 1 Elementary School Surakarta. Collaboration with other parties to develop teaching media in the future is needed to produce educational and interactive teaching media.
Evaluating ApoL1 Genetic Testing Policy Options for Transplant Centers
Authors: McIntosh Tristan , Walsh Heidi , Baldwin Kari , Iltis Ana , Mohan Sumit , Sawinski Deirdre , Goodman Melody , DuBois James M. 
Published: January 2024

Background
Apolipoprotein L1 (ApoL1) variants G1 and G2 are associated with a higher risk of kidney disease. ApoL1 risk variants are predominantly seen in individuals with sub-Saharan African ancestry. In most transplant centers, potential organ donors are being selectively genetically tested for ApoL1 risk variants. Transplant programs have highly variable ApoL1 testing practices and need guidance on essential ApoL1 clinical policy questions.

Methods
We conducted a Delphi consensus panel focused on ApoL1 clinical policy questions, including who gets tested, who decides whether testing occurs, how test results are shared, who receives test results, and how test results are used. A total of 27 panelists across seven stakeholder groups participated: living kidney donors (n=4), deceased donor family members (n=3), recipients of a deceased donor kidney (n=4), recipients of a living donor kidney (n=4), nephrologists (n=4), transplant surgeons (n=4), and genetic counselors (n=4). Nineteen panelists (70%) identified as Black. The Delphi panel process involved two rounds of educational webinars and three rounds of surveys administered to panelists, who were asked to indicate whether they support, could live with, or oppose each policy option.

Results
The panel reached consensus on one or more acceptable policy options for each clinical policy question; panelists supported 18 policy options and opposed 15. Key elements of consensus include the following: ask potential donors about African ancestry rather than race; make testing decisions only after discussion with donors; encourage disclosure of test results to blood relatives and organ recipients but do not require it; use test results to inform decision making, but never for unilateral decisions by transplant programs.

Conclusions
The panel generally supported policy options involving discussion and shared decision making among patients, donors, and family stakeholders. There was general opposition to unilateral decision making and prohibiting donation altogether.
Central Body Fat Distribution and Kidney Function after Living Kidney Donation
Authors: Westenberg Lisa B. , Pol Robert A. , van der Weijden Jessica , de Borst Martin H. , Bakker Stephan J.L. , van Londen Marco ,   on behalf of the Transplant Lines Investigators
Published: January 2024

Background
In most screening guidelines, high body mass index (BMI) is considered a contraindication for kidney donation. New insights suggest that central body fat distribution might provide greater power in assessing kidney risk. This study aimed to determine whether BMI and central body fat distribution measures are associated with long-term kidney function after donor nephrectomy. We hypothesized that higher BMI, waist circumference (WC), and waist-to-height ratio (WHtR) were associated with lower kidney function long term after donation.

Methods
The study population consisted of living kidney donors. BMI, WC, and WHtR were measured during donor screening. The outcome postdonation kidney function was assessed using measured GFR (mGFR) (mGFR, 125I-iothalamate infusion) at 3 months (n=1042), 5 years (n=556), and 10 years (n=210) of follow-up. Primary multivariable linear regression analyses were performed with BMI and WC and secondary analyses with WHtR. Linear mixed models were performed to investigate change in postdonation eGFR.

Results
The donor age was 52±11 years, and 48% were male. The mean BMI was 26.1±3.6 kg/m2, and WC was 91±11 cm. Higher predonation BMI was associated with lower mGFR throughout follow-up: −1.35 (95% confidence interval [CI], −1.95 to −0.80), −1.55 (95% CI, −2.50 to −0.65), and −2.35 (95% CI, −4.10 to −0.60) ml/min per m2 per 5 kg/m2 higher BMI at 3 months, 5, and 10 years after donation, respectively, adjusted for sex, age, and predonation GFR. For WC, differences in mGFR were −1.30 (95% CI, −1.70 to −0.90), −1.50 (95% CI, −2.20 to −0.80), and −1.70 (95% CI, −3.00 to −0.50) ml/min per m2 per 10 cm higher WC at 3 months, 5, and 10 years after donation, respectively. In male donors, BMI and WC were significantly associated with a negative postdonation change in eGFR.

Conclusions
Higher BMI and WC were independently associated with lower GFR (long term) after living kidney donation.
Preliminary Design of a Compact Superconducting Solenoid for Material Science Applications
Authors: Chavez Daniel , Napsuciale-Mendivil Mauro , Hernández-Chahin Karim , Huamani-Tapia Yembi , Juarez-Hernández Maribel , Córdova-Fraga Teodoro , Gomez-Solis Cristhian 
Published: January 2024

Innovation in new materials is strongly associated with different techniques and technological developments used on the growth and characterization of samples. Recent studies suggest that one could increase the preferable orientation of the crystals while they are being formed on the substance by applying a strong magnetic field. Uncertainty on the magnetic field magnitude, time of exposure, and temperature requirements, impose a challenge from the technological perspective. An upper boundary of 10 T provides a wide enough range for researching the material's growth.
In this work, we present a preliminary design of a compact 7 Tesla superconducting solenoid. The solenoid uses NbTi Cable-in-conduit technology for the windings. The proposed geometry incorporates an experimentation chamber, thermally isolated from the cryogenic solenoid windings, where the uniform magnetic field (3 cm wide x 3.3 cm high) covers the sample and instrumentation.
Deep Learning Based Leaf Disease Classification
Authors: KOKATE JAYESH KRISHNARAO , Kumar Sunil , Kulkarni Anant G 
Published: January 2024

A plant in its healthy state can produce its crops to the utmost of its genetically defined potential. However, on the other hand, a plant which is infected by an infection causing agent which directly or indirectly interferes with the plants’ growth or its functioning. A disease may interfere several processes in a plant’s metabolism. Continuous manual monitoring of farm and leaves of the trees by an expert is not possible, as it would be very expensive and time-consuming. Identification of correct disease accurately when it first appears on the plant is a decisive footstep for proper managing and diseases control in fields. Thus, an automated way of identifying the diseases and accurate classification of disease will play an important role in taking appropriate action for stopping the further crop and yield damage. This paper presents a Xception model of deep learning for identification and classification of the leaf diseases, average accuracy of 98% is resulted in this work. Xception model is utilised in this work and results are presented in terms of precision, recall, and f1-score for the 11 disease classes of tomato leaf.
Analysis & Prediction of New York City Taxi and Uber Demands
Authors: Correa Diego , Moyano Christian 
Published: January 2024

Taxi and Uber are an imperative transportation mode in New York City (NYC). This paper investigates the spatiotemporal distribution of pickups of medallion taxi (Yellow), Street Hail Livery Service taxi (Green), and Uber services in NYC, within the five boroughs: Brooklyn, the Bronx, Manhattan, Queens, and Staten Island. Regression Models and Machine Learning algorithms such as XGboost and Random Forest are used to predict the ridership of taxis and Uber dataset combined in NYC, given a time window of one-hour and locations within zip-code areas. The dataset consisting of over 90 million trips within the period April-September 2014, being Yellow with 86% the most used in the city, followed by Green with 9% and Uber with 5%. In outer boroughs, the number of pickups is 12.9 million (14%), while 77.9 million (86%) were made in Manhattan only. Yellow is the predominant option in Manhattan and Queens, while Green is preferred in Brooklyn and Bronx. In Staten Island, the market is shared between the three services. However, Uber presents a highly rising trend of 81% in Manhattan and 145% in outer boroughs during the analysis period. The regression model XGboost performed best because of its exceptional capacity to catch complex feature dependencies. The XGboost model accomplished an estimation of 38.51 for RMSE and 0.97 for R^2. This model could present valuable insights to taxi companies, decision-makers, and city planners in responding to questions, e.g., how to situate taxis where they are generally required, understand how ridership shifts over time, and the total number of taxis needed to dispatch in order to meet de the demand.
Numerical and experimental performance analysis of a horizontal axis hydrokinetic turbine
Authors: Betancur Gómez J. D. , Ardila Marín J. G. , Chica Arrieta E. L. 
Published: January 2024

Alternative technologies such as hydrokinetic turbines can improve the electric energy conditions in rural or non interconnected areas with a low environmental impact. However, as they are an emergent device they must be studied further to better understand their phenomenology a nd the ways to improve their performance. The numerical and experimental evaluation of rotors under specific operation conditions depending on their hydrodynamic profiles result in efficiency curves for evaluated prototypes, so that devices are proposed which take full advantage of the flow conditions of a specific place. Considering the above, the main objective of this work was to numerically and experimentally evaluate a horizontal axis hydrokinetic turbine rotor prototype with an EPPLER E817 hydrodyna mic profile for a flow velocity of 1.4 m s 1 The simulations were carried out by means of computational fluid dynamics; the k ? SST turbulence model was used, and the torque was monitored. Then, the Grid Convergence Index ( was calculated to establish the results’ numerical uncertainty. For experimentation, the rotor was additively manufactured and tested in a test bench, where tests at velocity of nearly 1,4 m s 1 were performed and the braking voltage was varied to measure torque at different tip speed ratio (TSR Finally, the experimental and numerical curves of power coefficient ( versus TSR were compared Both the simulation and experimental results show th at a TSR of about 4 represents the best operating conditions, but, due to mechanical losses in the experimental setup, the reported Cp values differ between a numerical 0.4 34 and an experimental 0.2 67 The power generated by the evaluated rotor could achie ve 117.0 W, thus showing the potential of this technology for electrical power supply with low environmental impact.
MAPEAMENTO COLABORATIVO E EDUCAÇÃO AMBIENTAL NA GESTÃO DO PARQUE ESTADUAL DO GRAJAÚ
Authors: Porto da Luz Chianello Karina , De Souza Elizabeth Rocha 
Published: January 2024

O Parque Estadual do Grajaú - PEG é uma importante Unidade de Conservação - UC localizada na cidade do Rio de Janeiro – RJ, no bairro do Grajaú. O presente estudo mapeou a infraestrutura do Parque, árvores que configuram pontos de interesse à visitação e os limites, adotando o mapeamento colaborativo dos gestores, voluntários e visitantes como base. Os produtos gerados disponibilizaram atividades para a promoção da educação ambiental aos frequentadores do PEG. O principal interesse do trabalho é destacar aos gestores e visitantes a necessidade para um maior cuidado com o PEG e o reconhecimento de seus recursos, bem como propor um sistema de registro de dados em apoio às atividades dos gestores do Parque. A atividade criada denomina-se “Rota das Árvores”, percurso que chama atenção para as principais árvores e palmeiras da área social dessa UC e sua estrutura de uso público. Os limites gerados foram submetidos e aprovados para inserção na base de dados da empresa Google, e posteriormente foi possível criar uma representação no MyMaps, (na plataforma Google Maps), que deverá auxiliar nas visitas guiadas e atividades de educação ambiental com os visitantes do Parque e da comunidade em geral. O mapeamento colaborativo foi fundamental para a criação das atividades e identificação das estruturas internas do Parque. As maiores dificuldades enfrentadas consistem no ajuste dos dados para o mapeamento e a aprovação pela Google para os limites propostos. No primeiro caso havia uma farta disponibilidade de registros sobre o parque gerado pelos moradores e visitantes e muito não pode ser utilizado pois demandaria adequações e conversões. Esse processo ainda será considerado em etapa futura da pesquisa. No segundo caso, houve uma forte exigência para o aceite de limites gerados por terceiros que não são funcionários ou colaboradores diretos da Google. Apesar disso o registro foi feito de o MyMaps pode ser gerado. O trabalho pretende avançar para a inclusão de novas feições ampliando a visibilidade da área de estudo junto a comunidade e pela gestão de seus espaços públicos.
Enterprise Risk Management as Part of the Organizational Control Package: Review and Implications for Management Accounting Research
Authors: Braumann Evelyn C. , Hiebl Martin R. W. , Posch Arthur 
Published: January 2024

ABSTRACT
Research on enterprise risk management (ERM) has increased considerably in the past two decades. Although management accounting researchers have substantially contributed to these advancements, previous reviews of the ERM literature have not discussed in depth the role of ERM as part of the organizational control package and how management accounting research could build on its research traditions to further our collective understanding of ERM. In this paper, we therefore adopt a management control perspective to critically analyze both quantitative and qualitative empirical ERM research and specifically focus on the integration of ERM in organizational control packages. Taking a complementarity perspective and accounting for the decision-facilitating and decision-influencing purposes of management accounting and control systems (MACS), we recommend several broader avenues for future management accounting research on ERM.
Does Political Uncertainty Obfuscate Narrative Disclosure?
Authors: Mekhaimer Mohamed , Soliman Marwa , Zhang Weining 
Published: January 2024

ABSTRACT
We examine the relation between political uncertainty and narrative disclosure complexity in conference calls. Using firm-level political uncertainty, we find that political uncertainty is positively associated with firms’ disclosures complexity as measured by the Fog index. Decomposing complexity into two latent components—information and obfuscation—we show that political uncertainty significantly increases the obfuscation but has no impact on the information. Further analysis reveals that complex disclosure is motivated by expected poor future performance amid political uncertainty. We also show that, during periods of heightened political uncertainty, obfuscated disclosure is associated with reduced earnings informativeness, increased dispersion in analyst forecasts, and higher volatility in forecast revisions. These findings are robust to including and excluding sentences containing complex political bigrams when calculating Fog. Further evidence shows that, during periods of political uncertainty, managers tend to use a more ambiguous tone and provide scripted and shorter (longer) responses to analysts’ questions (presentations).
Going green with artificial intelligence: The path of technological change towards the renewable energy transition
Authors: Yin Hua-Tang , Wen Jun , Chang Chun-Ping 
Published: January 2024

Research background: The twin pressures of economic downturn and climate change faced by countries around the world have become more pronounced over the past decade. A renewable energy transition is believed to play a central role in mitigating the economic-climate paradox. While the architectural and computational power of artificial intelligence is particularly well suited to address the challenges of massive data processing and demand forecasting during a renewable energy transition, there is very scant empirical assessment that takes a social science perspective and explores the effects of AI development on the energy transition.
Purpose of the article: This paper aims to answer two key questions: One is, how does AI software development promote or inhibit the shift of energy consumption towards renewables? The other is, under what policy interventions does AI software development have a more positive effect on promoting renewable energy consumption?
Methods: We employ a dataset of 62 economies covering the period 2011–2020 to analyze the impact of AI software development on the energy transition, where possible confounders, including political and economic characteristics and time-invariant elements, are controlled using fixed-effects estimation along with specified covariates.
Findings & value added: AI software development can promote the energy transition towards renewables. There is suggestive evidence that the core mechanism linking such a positive relationship tends to lie in improving innovation performance in environmental monitoring rather than in green computing. Government support for R&D in renewable energy technologies is found to be significantly beneficial for harnessing the positive impact of AI software development on the energy transition. Compared to non-market-based environmental policies, market-based environmental policies have a more significant positive moderating effect on the relationship between AI software development and energy transition.